research paper on global migration

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• Published: 07 September 2023

World’s human migration patterns in 2000–2019 unveiled by high-resolution data

• Venla Niva   ORCID: orcid.org/0000-0002-1456-4881 1   na1 ,
• Alexander Horton   ORCID: orcid.org/0000-0003-3067-7138 1 ,
• Vili Virkki   ORCID: orcid.org/0000-0002-2603-3420 1 ,
• Matias Heino 1 ,
• Maria Kosonen 1 ,
• Marko Kallio   ORCID: orcid.org/0000-0002-6917-7790 1 , 2 ,
• Pekka Kinnunen   ORCID: orcid.org/0000-0003-0373-2795 1 ,
• Guy J. Abel   ORCID: orcid.org/0000-0002-4893-5687 3 , 4 , 5 ,
• Raya Muttarak 6 ,
• Maija Taka   ORCID: orcid.org/0000-0002-6147-9137 1 ,
• Olli Varis 1 &
• Matti Kummu   ORCID: orcid.org/0000-0001-5096-0163 1   na1  

Nature Human Behaviour volume  7 ,  pages 2023–2037 ( 2023 ) Cite this article

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• Climate-change adaptation
• Climate-change impacts
• Socioeconomic scenarios

Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world’s urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration—a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration.

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Since the 1990s, human migration has been one of the top public concerns and political agenda items in Europe and North America 1 . Millions of people have been forced to flee due to conflicts while also millions have voluntarily moved to urban areas seeking better economic prospects. Around the world, diverse environmental factors, such as droughts, floods and other natural hazards also push people to move. Most of this mobility takes place within a short distance, making internal migration the most prevalent form of migration across the globe 2 . Indeed, climate-induced migration is shown to be more common within national borders 3 . Yet, public attention tends to focus on international migration including both voluntary and forced migration. Subnational information about the estimates of the number of migrants (and immobile persons), their origin and destination and the conditions of migration are much needed for planning of urban services and infrastructure as well as rural development 4 . Understanding migration patterns across spatial scales—including its conditions, magnitude and impact—is thus fundamental for policy design.

Whilst subnational (5 arcmin, ~10 km resolution) decadal estimates of net migration for three decades between 1970 and 2000 are available 5 , global-scale data on subnational migration for more recent years are sparse. One study 6 provides a more recent estimate of migration at grid cell level for 1975–2015 (5 year interval) but the baseline data are derived from national-level birth and death data. Other estimates describe global international migration by using national-level data 7 , 8 or internal migration at the national level, based on national census data. These studies suffer from a long time interval between census years (typically 10 years) 9 . The coarse spatial and temporal resolutions of these data hinder the ability to conduct gridded migration trend analyses over time.

Our study aims to address these research gaps by developing a detailed annual net migration dataset, by collecting, gap-filling and harmonizing (1) comprehensive national-level birth and death rate datasets for 216 countries or sovereign states; and (2) subnational data for births (covering 163 countries, divided into 2,555 administrative units) and deaths (123 countries, 2,067 administrative units) (Extended Data Fig. 1 ; Methods ). In doing so, we provide a detailed analysis of the spatiotemporal development of (1) the magnitude of net migration and (2) its impact on population growth over the past two decades. Firstly, for magnitude, we collected reported data from various sources to create an annual net migration dataset for 2000–2019, using national and subnational birth and death data, downscaled to 5 arcmin resolution (~10 km at the equator) with selected socioeconomic variables (Fig. 1 ; Methods ). These data enable us to perform analyses on net migration trends and patterns from local to global scales. Our gridded net migration data allow, for instance, comparing the intensity of net migration and its trends at several administrative scales. It is also possible to analyse the types of sending and receiving areas (rural or urban) at multiple scales (regional, national (administrative 0), provincial (administrative 1) and communal (administrative 2)) over the past two decades. Indeed, there is no such systematic global-scale classification on, for instance, which urban areas are net senders and which rural areas are net receivers. Here, we present rigorous analyses of the distribution of the types of origin and destination areas.

a , b , Reported annual subnational birth ( a ) and death rates ( b ) for 2000–2019 are based on various global and national datasets with some of the intermediate results ( Methods ). c – f , For downscaling to 5 arcmin grid level, we used four annual gridded or subnational datasets of ( c ) human development index, ( d ) scaled population density, ( e ) share of reproductive women and ( f ) share of life lived in each grid cell, as detailed in the panels. g – i , The annual downscaled birth ( g ) and death ( h ) rates allowed us to estimate the natural population change for each year ( i ). j , k , When combining this with reported population change based on WorldPop 55 ( j ), we were able to calculate annual net migration for 2000–2019 ( k ). See Methods for more details.

Our paper also contributes to analysing the impact of human migration on population change. Using our annual gridded dataset to map migration in parallel with demographic and geophysical data (Extended Data Figs. 2 and 3 ), we were able to assess the impact of net migration on rural and urban population change at national, subnational and communal levels and across different societal and climatic conditions. Understanding the contribution of migration to population change is crucial because migration affects sending and receiving societies in various ways. In terms of economic consequences, migration influences socioeconomic development of both sending and receiving areas—for example, by increasing productivity in receiving areas and reducing income inequalities across countries through remittances 10 , 11 . Nevertheless, migration can also cause considerable pressure on the infrastructure and services of the receiving areas 4 and consequently exacerbate the vulnerability of migrants 12 , 13 . However, few empirical studies have analysed the impact of migration on population change at the global scale over the past decades. Our analysis thus provides a solid quantitative foundation towards understanding the extended societal impacts caused by migration.

We first developed a gridded global net migration dataset at annual timesteps for 2000–2019 (Fig. 1 ). This here-developed dataset (openly available at https://doi.org/10.5281/zenodo.7997134 ) was constructed from subnational (administrative 1) birth and death rate data collected across 2,555 and 2,067 administrative units, respectively (Fig. 1a–b ; Methods ), downscaled to 5 arcmin resolution with rasterized socioeconomic data developed in this study and finally adjusted to match the subnational data collected (Fig. 1c–f ; Methods ).

Our birth and death rate data revealed considerable intranational heterogeneities, particularly in large countries, such as Russia, the United States, China, Brazil and India (Fig. 1g–h ). This highlights the importance of using subnational (particularly downscaled) data instead of national data (as used in ref. 6 ) for understanding global population dynamics. These downscaled birth and death data then allowed us to estimate natural change in population (deaths subtracted from births) for each year and grid cell (Fig. 1i ). When combined with reported annual population change over the same time period (Fig. 1j ), we were able to estimate annual net migration in each grid cell (Fig. 1k ) using a similar method to that of ref. 5 ( Methods ). Here, net migration can be either negative (more people out-migrating than in-migrating) or positive (more people in-migrating than out-migrating).

It should be noted that our data are prone to uncertainties that originate from collected subnational data but propagate to all derived data products—including birth and death rates, natural change in population, as well as net migration estimates. Subject to data availability, we performed a partial validation for our data products by comparing gridded data with subnational (mostly administrative 2 level) data ( Methods; Supplementary Table 2 and Supplementary Figs. 1 – 6 ). However, this validation cannot capture areas where uncertainties may be the highest—that is, areas in which the collected census data are not available or of poor quality, for example, those suffering from sporadic census years or changing subnational administrative units. To ensure global spatial and temporal coverage, we applied a series of adjustments and corrections to the data ( Methods ). Nevertheless, higher uncertainties remain in some countries (such as those in Africa, the Middle East and parts of Asia) than in others (such as those in Europe and much the Americas). As proxies of original data quality, we provide the description, resolution, timespan and sources of each collected dataset in the Supplementary Data .

Magnitude of global net migration

Temporal dynamics of net migration depend on scale.

To assess global migration dynamics, we aggregated net migration at three spatial levels: communal (administrative level 2), provincial (administrative level 1) and national (administrative level 0) (Fig. 2 ). This approach allowed us to compare the magnitude of migration that occurs at different spatial levels. Our results show that migration patterns vary remarkably across nations. On a national scale over the entire 20 year study period, net migration was positive (that is, in-migration was greater than out-migration) in Australia, North America, as well as parts of Europe and the Middle East—all being areas that have attracted either asylum or job seekers or both (Fig. 2 and Extended Data Fig. 4 ). Net migration was negative in countries like Syria, Lithuania, Zimbabwe, Venezuela and Guyana (Fig. 2e )—in line with previous assessments from Venezuela and Syria, where millions of people have fled a humanitarian crisis and conflict 14 , 15 , 16 and also from Lithuania and Zimbabwe where numerous people have out-migrated in search of better economic prospects 17 , 18 .

a , c , e , Sum of annual net migration over 2000–2019 is shown for communal (administrative 2) ( a ), provincial (administrative 1) ( c ) and national (administrative 0) ( e ) levels. b , d , f , Net migration trend (slope) over 2000–2019 is shown for communes ( b ), provinces ( d ) and countries ( f ). The trend was determined by calculating the slope of linear regression line. Negative net migration refers to a situation in which more people out-migrate than in-migrate and positive net migration refers to a situation in which more people in-migrate than out-migrate. With our online net migration explorer tool, it is possible to explore these patterns for each year and subnational unit: https://wdrg.aalto.fi/global-net-migration-explorer/ .

At a provincial level, the migration patterns reflect the prevalence of internal migration in many countries, as can be observed from both net-positive and net-negative provinces. For example, in China, the coastal areas show positive net migration while negative net migration (out-migration is greater than in-migration) was observed in many inland provinces (Fig. 2c ). This is consistent with the well-founded internal migration patterns in China where labour migration is concentrated towards urban, coastal areas 19 . The same applies to many other countries, such as the United States, where urban centres are attracting people from other states and abroad 20 , 21 . When assessing net migration at even finer spatial detail (communal level), interesting patterns start to arise. For example, in the United States, many states with positive net migration (Fig. 2c ) are characterized by mainly negative county-level net migration (Fig. 2a ). See our online net migration explorer tool for more detail: https://wdrg.aalto.fi/global-net-migration-explorer/

Our dataset also allowed us to explore the temporal dynamics of net migration over the study period (2000–2019) across three administrative levels. We assessed the trend of net migration at each level over the study period (2000–2019) by using linear regression. The results follow a similar pattern as cumulative net migration where the trend changes according to the administrative level. Further, the results show interesting patterns of where net migration has a negative trend and where it has a positive trend over the past two decades. In North America, for instance, net migration shows a declining trend in almost all regions, excluding small pockets in the southwest (Fig. 2b,d ). The same applies to South America, especially Brazil and Chile, where net migration has been on a growing trend in the northern parts of these countries, while in the south the trend has been declining; and Australia, where the trend of net migration has been positive in the middle parts, while being negative in the coastal regions of the continent (Fig. 2b,d ).

Rural and urban migration show high global variation

We further assessed the development of net migration by studying how net migration differs in rural and urban areas (Extended Data Fig. 5 ). Urban areas often receive migrants from rural areas— the so-called ‘urban pull–rural push’ situation 22 . We assessed if this holds true across 12 world regions (Extended Data Fig. 4 ) and for each country at three administrative levels by using the GADM delineation (national, administrative level 0; provincial, administrative level 1; and communal, administrative level 2). Here, we combined our net migration dataset with an urban extent dataset for 2000–2019 that was created for this study. The urban extent dataset maps urban areas on the basis of scaled population density and share of urban population at national level, annually for 2000–2019 ( Methods ; Extended Data Fig. 3 ).

Our data show that when aggregated globally, urban net migration was positive (more in-migrants than out-migrants) throughout the study period (2000–2019), while rural net migration remained negative (except for years 2010 and 2012) (Fig. 3m ). The magnitude of global net migration ranged annually from near-zero to around three net migrants per 1,000 people (Fig. 3m ). Notable spatiotemporal variation between rural and urban net migration was evident at the regional level (Fig. 3a–l ) as well as at national, provincial and communal levels (Extended Data Fig. 6 ). However, no considerable change in net migration rates towards urban or rural areas was observed in any region between 2000 and 2019. Both rural and urban net migration were negative (down to approximately −10 net migrants per 1,000 people) nearly throughout the study period in Central America (Fig. 3a ), whereas in North America (Fig. 3g ) and Oceania (Fig. 3h ), total net migration was steadily positive (with a constant magnitude of at least +5 net migrants per 1,000 people). In East Asia (Fig. 3b ), net migration was negative in rural areas and positive in urban areas (with magnitudes <5 net migrants per 1,000 people) while in other regions, the pattern was more complex (Fig. 3 ).

a – m , The regional sums for each year (Central America ( a ), East Asia ( b ), Eastern Europe ( c ), Europe ( d ), Middle East ( e ), North Africa ( f ), North America ( g ), Oceania ( h ), South American ( i ), South Asia ( j ), Southeast Asia ( k ) and Sub-Saharan Africa ( l )) and the annual global sum ( m ) of urban and rural net migration. Urban and rural net migration are reported per 1,000 urban or rural inhabitants in each region. The regional division follows the UN country grouping (Extended Data Fig. 4 ). See gridded net migration in rural and urban areas in Extended Data Fig. 5 .

In Eastern Europe and the Middle East, rural and urban net migration rates fluctuated annually, especially during the years preceding the Arab Spring, followed by massive rural out-migration and urban in-migration between 2011 and 2013—with magnitudes up to almost +40 net migrants per 1,000 people and down to −20 net migrants per 1,000 people (Fig. 3e ). Out-migration from Syria was among the largest in the world between 2010 and 2015, during when more than 2 million people left to neighbouring countries Turkey and Lebanon 2 , 14 , 23 . This explains a sharp influx of migrants to rural and urban areas in Eastern Europe group that includes Turkey (Fig. 3c ). Although our results align with previous estimates of migration in the Middle East, these regions are prone to high uncertainties in the data.

Net-receiving provinces contain a third of global population

When focusing on national and subnational scales, the global urban pull–rural push pattern (Fig. 3m ) becomes patchier (Fig. 4 ). At the national scale, 36% of global population (in 2019) lived in countries where this pattern was evident. These countries include the Nordics and several countries in Africa, Southeast and East Asia (Fig. 4c ). However, at the subnational scale, many more people lived in provinces and communes which were either net receivers or net senders, as presented by negative or positive net migration in both urban and rural areas. Such provinces were located in the United States, Canada and Australia, while Russia, the northeast of the United States, Mexico and the Balkans, for example, accommodated multiple net-sending provinces (Fig. 4b ).

a – c , The communal ( a ), provincial ( b ) and national ( c ) levels. Each administrative unit was categorized into one of the four classes on the basis of the ‘direction’ of migration in rural and urban areas. For example, if net migration in an administrative unit was positive in both urban and rural areas, then that unit would be categorized as a net receiver, whereas a unit in which urban net migration was positive and rural net migration negative would be categorized as urban pull–rural push. The share of population living in each category was calculated for each administrative level. For instance, 36% of global population lived in communes where both urban and rural net migration were positive (net-receiving communes). See net migration in rural and urban areas by different administrative levels in Extended Data Fig. 6 .

A situation where urban net migration was negative and rural net migration positive (rural pull–urban push) was observed in few locations, such as certain provinces of Indonesia, Congo, Venezuela and Pakistan (Fig. 4b ), covering in total 22% of the world’s population. Notably, 37% of the global population lived in the urban and rural areas of net-receiving communes. Extensive rural in-migration is probably explained by interprovincial and intercommunal migration between rural areas and immigration from other countries. Studies show that a trend of rural–urban migration is shifting towards more complex mobility patterns, of which rural–rural mobility is one of the most prevalent types of internal migration. Especially in Sub-Saharan Africa, people tend to move between rural areas as seasonal circular migration and for economic diversification, given better access to land or job prospects than in cities 24 , 25 . In Europe, a similar pattern appears in rural areas attracting workers in the agricultural sector within the same country or from abroad 26 . Large urban agglomerates may also push people to move to rural areas in search of more affordable housing (counter-urbanization; see ref. 27 for counter-urbanization in Australia and ref. 28 for the United States). It should be noted that the results are strongly influenced by the delineation of urban areas ( Methods ).

Impact of migration on population change

Migration often accelerates urban population growth.

Net migration taking place in densely populated areas can be relatively large compared to natural population change (Figs. 1i,k and 2a ). In such cases, large-scale migration can strain natural and human resources, as well as infrastructure, which are insufficient to serve a steep surge in population, particularly in urban areas 4 , 29 . On the other hand, migration can potentially help ageing societies like those in Europe to maintain their work force 30 , 31 . To empirically examine the role of migration in population change globally, we compared natural population change (deaths subtracted from births) with reported population change in rural and urban areas at the three administrative levels.

We found that about half of the global urban population lived in areas that were affected by positive net migration in a way that positive net migration added to a naturally growing urban population. Notably, in some urban areas—especially in the Nordics, Germany, Austria and Spain—positive net migration even shifted a naturally decreasing population towards growth (Fig. 5c,e ). In very few countries, positive net migration slowed down natural decline in urban population but this affected urban areas accounting only for ~1% of global urban population. About 39–44% of the urban population lived in areas affected by negative net migration that slowed down urban population growth (Fig. 5 ). There were fewer cases (0–6% of urban population) where naturally growing urban population declined due to intensive out-migration. Such areas could be detected mainly at communal level in countries such as France, Italy, the United States and India.

a – f , The communal ( a , b ), provincial ( c , d ) and national ( e , f ) levels for urban ( a , c , e ) and rural ( b , d , f ) areas. Impact is divided into seven categories by comparing total population change, net migration and natural population change (growth or decline). Total population change includes both net migration and natural change. Natural change is measured with births and deaths, that is population change without migration. For example, net migration slows down urban population decline when urban net migration is positive but total urban population change is negative ( Methods ). Share of global urban and rural population living in each category shows the share of global urban or rural inhabitants living in areas under each type of impact.

Negative net migration impacted rural areas more often than urban areas: 10% of global rural population lived in communes where out-migration turned rural population growth to a total population decline (Fig. 5b ). Approximately half of the global rural population lived in countries where rural population growth was slowed down by negative net migration, whereas one-fifth of rural population lived in countries where negative net migration accelerated the prevailing decline in population (Fig. 5f ). Yet, positive net migration propelled rural population growth in multiple provinces and communes accounting for around a third of global rural population. In Russian provinces and communes bordering Kazakhstan, for instance, in-migration of skilled workers from Kazakhstan potentially explains the accelerated rural population growth or slowed rural population decline 32 .

Human development is associated with migration more than aridity

Global migration is known to be driven by both socioeconomic and environmental factors 3 , 13 . Here, we analyse how total, urban and rural net migration co-occur with different socioclimatic conditions, dividing the globe into 100 socioclimatic bins (Extended Data Fig. 7 ) on the basis of the level of aridity, human development (measured by human development index (HDI); Extended Data Fig. 8 ) and population. Each bin accommodates ~1% of the global population ( Methods ).

Our results show that, over the past 20 years, high net migration often co-occurs with high HDI and high aridity, which is evident especially in urban areas (Fig. 6a ). For instance, urban areas in the Arabian Peninsula, arid parts of North America, Australia, Argentina and the Mediterranean region had high (mostly above +60 net migrants per 1,000 people over the study period) positive net migration rates (Fig. 6a ). High positive net-migration rates in many Middle Eastern countries, such as Qatar, Oman and Saudi Arabia (Fig. 2e ), are explained by large labour migration particularly from Asian and African countries 33 . On the other hand, in Australia and North America, the ‘preference of low-density living’ 34 can explain positive net migration in rural areas. Notably, high HDI is common for these regions whereas the range of aridity is wider.

a – d , For each socioclimatic bin, urban net migration per 1,000 urban population summed over the study period ( a ), the impact of urban net migration on urban population change in each socioclimatic bin ( b ), rural net migration per 1,000 rural population summed over the study period ( c ) and the impact of rural net migration on rural population change ( d ). Here, net migration per urban or rural population was calculated as a zonal sum of net migration in urban ( a ) and rural ( c ) areas in each bin and then divided with the respective urban or rural population count in the respective bin. The maps are spatial representations of the heatmaps. Socioclimatic bins are based on socioeconomic and climatic conditions represented by human development and aridity indices ( Methods ; Extended Data Figs. 7 and 8 ).

In terms of negative net migration, global out-migration hotspots (areas with substantial negative net migration) are located in socioclimatic conditions with middle-level aridity and human development. This was especially the case in rural areas (Fig. 6c ). High negative net migration rates could be observed in regions like Central America, northeastern Brazil, Central Africa and Southeast Asia (mostly below −60 net migrants per 1,000 people over the study period). This aligns with recent studies showing that most migration is originating from areas where people have sufficient capacity to move and use migration as a form of adaptation to unfavourable environmental conditions 3 .

Positive net migration often co-occurs with high HDI

When comparing natural population growth with net migration across different socioclimatic conditions, we found that the contribution of migration to population change ( Methods ) was more strongly associated with the level of human development than with aridity (Fig. 6b,d ). Positive net migration often contributed to increasing population growth, slowing population decline or shifting declining population to growth in areas with relatively high human development. Our results show that the climatic factor, as measured by the level of aridity, has a weaker association with the impact of migration on population growth. Therefore, migration can accelerate or slow down population growth in a wide range of climatic conditions.

For instance, most of Europe, North America and Australia, which are regions with high human development, experienced increasing urban population due to positive net migration (Fig. 6b ). Notably, the capacity to cope with the pressure on physical and social infrastructure from population growth is high in these regions. On the other hand, many urban regions in West, East and South Africa, Arabia, as well as India, Bangladesh, China and Southeast Asia had positive net migration accelerating their natural population growth, while they also have more limited capacity (HDI) to cope with a growing population (Fig. 6b ). Urban regions with the lowest human development level experienced negative net migration and consequently a slowing down of natural population growth. While this may indicate that out-migration from those areas is alleviating the pressure caused by natural population growth, it can also reflect urban out-migration pushed by urban poverty.

Finally, the role of migration in rural population change follows a general pattern in which regions with higher human development level are impacted by positive net migration. Declining rural populations turned to growth due to positive net migration in North America and Australia (Fig. 6d ), whereas rural population decline was slowed down by positive net migration in most of Europe, parts of Russia and South America.

Discussion and concluding remarks

Despite recent progress in estimating global international 7 , 8 , 35 , 36 and internal migration 9 , 37 , global migration datasets often suffer from poor spatial and/or temporal resolutions. Our annual gridded net migration data cover the entire globe, allowing the analysis of both local and regional net migration patterns at various geospatial scales. Using these data, we have quantified the magnitude and impact of net migration over the past 20 years in three administrative levels and in socioclimatic zones. Our analysis highlights the importance of considering the spatial scale when analysing migration patterns. We showed that global net migration patterns depend strongly on the scale of analysis, both for the magnitude of migration and also for the trend (Fig. 2 ). Within the study period of 2000–2019, net global urban migration has been predominantly positive while net rural migration has been negative (Fig. 3m ), aligning with previous urbanization literature 38 . Further, we showed that the volume and impact of migration are positively associated with the level of human development (positive net migration often co-occurs with high HDI) and this association is stronger than that of climate and migration (Fig. 6 ).

Previous studies argue that migration often originates from areas where people have sufficient capacity to move and to use migration as one form of adaptation to unfavourable environmental conditions, often by migrating to urban areas 29 , 39 , 40 , 41 . Our analysis provides a global quantification of this argument and shows that rural out-migration hotspots were located in socioclimatic conditions with a middle level of aridity and human development (Fig. 6c,d ). This corresponds to about 50% of the global urban population who experienced accelerated population growth in the past two decades (Fig. 5 ). Notably, a relatively large volume of positive urban net migration took place in locations with medium-to-high levels of human development, indicating higher capacity to cope with additional pressures (Fig. 6a,b ).

Despite accelerating urbanization over the past 20 years, positive net migration has increased population growth and helped to slow down population decline in many rural areas (Figs. 5 and 6c,d ). Rural–rural migration, especially over short distances, is common particularly in smaller countries with few provincial and communal urban centres that attract migrants from other parts of the country 7 . Our results show that areas where migration slowed rural population decline were located in high-income countries (Fig. 6d ), and some countries may have reached a point where urbanization has turned to counter-urbanization 34 . On the other hand, the share of people living in urban areas is expected to grow, especially in lower income regions, such as Africa 42 . With the global average temperatures continuing to rise, impoverished urban areas are particularly vulnerable to the impact of extreme climate events, given lower capacity to manage population growth and to provide basic services and infrastructure 43 . Increased climatic hazards such as heatwaves, water stress, floods and droughts will increase the vulnerability of people living in the outskirts of poor urban agglomerates, which are already the predominant destinations for migrants, particularly in Africa 44 . Notably, such developments are visible in our study. For instance, migration-induced urban population growth over the past two decades was visible around the fast-growing cities of Nigeria, Angola, Kenya and Tanzania, where the capacity to cope with the accelerating population growth was remarkably low (Figs. 5 and 6 ).

While our study sheds light on global migration trends and patterns at various spatial scales, there are several limitations. First, given that our data derive net migration from the difference between total and natural population change, it is impossible to distinguish between different types of migrants such as refugees, internally displaced persons or economic migrants. Our data mask out important individual migration events and external shocks, such as conflict, altogether by only describing whether an area experienced more in-migration than out-migration, or vice versa, without being able to differentiate the dynamics of migration flows in and/or out of an area 45 . This can be particularly relevant, for instance, in areas under prolonged conflicts in our study period, such as Afghanistan, Syria and Iraq. Further, our analysis used long-term averages of climatic and socioeconomic conditions, thus masking any interannual or intra-annual variation of net migration related to sudden shocks, such as extreme weather events.

It is also important to note that the data collected from national censuses and other databases ( Methods ; Extended Data Fig. 1 ) were available at different temporal resolutions. Data for low-income countries were scarcer, while the information from high-income countries was generally more detailed. In some cases, the sources for births and deaths information were also different. To minimize uncertainties, the produced birth and death grids were adjusted so that the subnational sum of births and deaths matched with the collected subnational (administrative level 1) birth and death counts ( Supplementary Data ). Further, subnational data at administrative level 1 were harmonized with national data; that is, we ensured that the sum of births and deaths at the grid level agree at the national level with United Nations (UN) statistics. We validated the WorldPop data, downscaled births and deaths data as well as the produced net migration data against reported values, mostly at administrative level 2 (finer level than used for creating the gridded datasets). Validations show that the data are in line with reported data and thus indicate good performance of our downscaling method (Supplementary Figs. 1 – 6 and Supplementary Table 2 ). To smooth over inaccuracies, we recommend aggregating the data over some spatial or temporal units (for example, administrative/environmental zoning, 5 year period instead of an annual timestep).

Here, we have quantified the magnitude and impacts of net migration over the past two decades. In the light of our results, we emphasize the importance of subnational analysis of migration and, with our data, we provide various future research openings in studying complex human mobilities inside and between administrative boundaries and in other zones—combined with the co-occurrence of extreme weather, disasters, conflicts and migration events, for example. Capturing migration patterns not only between countries but also within countries and socioeconomic and geophysical zonings is essential for policy design, international cooperation and shared responsibility—all essential for managing internal and international migration and other mobilities 29 . Finally, our results underline the necessity of coupling environmental drivers with proxies of human development. Internal and international migration are expected to increase in unprecedentedly complex and rapidly changing socioclimatic conditions 46 and thus, increasing the empirical understanding of the global patterns of migration and its multifaceted drivers is very important 47 .

The overall workflow is illustrated in Fig. 1 , while a more detailed methodological explanation is given below.

Data processing for harmonized subnational data

We first collected national and subnational data for 1990–2019. For births, we used two global databases, namely STATcompiler 48 and Eurostat 49 , as well as national census data. Altogether we found subnational (administrative level 1) data for 163 countries which were divided altogether for 2,555 administrative units (Extended Data Fig. 1 ). For deaths, we used two databases, namely OECD regional stats 50 and Eurostat 51 , as well as national census data. For deaths, we found subnational data for 124 countries and 2,067 administrative units. For both data (births and deaths) and for each country, we evaluated the best-available data source (by the number of available years and missing data entries, if multiple data sources were available). The datasets used are described in the Supplementary Data and origin of data for each country illustrated in Extended Data Fig. 1 , which also shows the administrative units used in STATcompiler 52 , Eurostat 53 and OECD 54 .

As data were available either as a crude birth or death rate or as a number of births or deaths, we needed to harmonize the data so that all observations would be as a rate (births or deaths per 1,000 people). For this, we aggregated population data for each administrative unit and for each year, using WorldPop 55 gridded 1 km data for 2000–2019 and HYDE 3.2 (ref. 56 ) for 1990–2000. HYDE data were bias-corrected with delta change method 57 to be consistent with WorldPop data. Although WorldPop data were available also for the year 2020 at the time of data processing, our analysis required computing population change that could not be done for the 2020 WorldPop data and thus, final data are limited to 2019. While our final dataset covers years 2000–2019, collecting data for the previous decade made interpolations between years possible.

Once all data were transformed to rates, we filled missing data entries. Some data entries were missing due to changes in administrative units and temporal gaps in used datasets. For changes in administrative boundaries, we used Administrative Divisions of Countries (Statoids) database 58 . We processed the missing data according to following types (see list of subnational areas in each category in the Supplementary Data ):

Combine (number of cases in birth dataset ( n births  = 11; n deaths  = 11). In subnational units with low population (typically <50,000)—with available data for the number of births or deaths—the birth or death rates ended up differing substantially from the surrounding administrative units. In these cases, we ‘combined’ the unit with a neighbouring larger subnational unit so that the rate was calculated for both, using the combined number of births or deaths and population—that is, they ended having the same rate. For example, we combined Ulaanbaatar (Mongolia) with the surrounding Töv province, as rates in Ulaanbaatar were not realistic (probably because of how the population in the capital is defined).

Split ( n births  = 15; n deaths  = 14). In cases when a larger administrative unit was split to two or more subnational units during the extended study period and parts of the data were given only for the larger unit, we estimated birth or death rates before the split using the birth or death rate of the first timestep when these were split to separate units. We did this by calculating the combined birth or death rate, using subnational population and then used this to calculate the ratio between combined birth or death rate and each individual administrative unit birth or death rate. These were then multiplied with the ‘combined’ birth or death rate for years before the split. This way, we were able to estimate the birth or death rate for all individual administrative units for the time in which they were still one unit. For example, Panamá subnational unit was split in 2014 into two units: Panamá and Panamá Oeste. Birth rate data exist for combined Panamá over 2001–2013 and then for both split units from the year 2014 onwards. We thus first calculated the combined birth rate (in this case) for year 2014 using subnational population:

This \({\rm{birthRate}}_{\rm{comb}_{2014}}\) was then used to estimate the rates for each subnational unit separately:

and these were finally used to estimate the birth rate for each subnational unit for pre-2014 period (example for year 2013 given below):

where birthRate_Panama(combined)_2013 is the reported birth rate for the combined administrative unit for year 2013 (before the split).

Part of the data missing ( n births  = 31; n deaths  = 19). In cases of gaps in the reported data, we used the neighbouring area with the least difference in births or deaths as the scaling neighbour to scale the missing data. For this, we used the data from the closest year to the missing data year, for which data existed for both administrative units. We then calculated the ratio between these administrative units and used this ratio to estimate the missing data:

No data at all ( n births  = 24; n deaths  = 29). For some subnational units (often remote islands or other remote areas with very low population), no data existed. In this case, we used national average values.

Once we had filled the missing data entries, we interpolated and extrapolated the years for which there were no data available for any subnational unit, using interpolation and harmonization methods adapted from ref. 59 . Shortly, we first interpolated missing national values between the years with available data using linear interpolation. Then, we extrapolated missing data points either before the first reported year or after the last one. For extrapolation, we used macroregional ( n  = 12; see ref. 59 ) trends that were calculated using population-weighted national birth and death rates of those countries with full data coverage over the extended study period (1990–2019).

We then used the interpolated and extrapolated subnational birth and death rates to calculate population-weighted national average birth and death rates for each country and year. These rates were then compared with reported national values (compiled from World Bank and UN databases), resulting in an annual ratio between the reported death and birth rates and the ones calculated from subnational units. When we then used this national ratio to correct the bias of the subnational-level birth and death rates, we ensured that our data matched with reported data at the national level.

As the final result, we attained gap-filled harmonized full time series for all subnational areas for which data were available as well as for those countries for which no subnational data were found (Extended Data Fig. 1 ). We produced a combined dataset (both gridded and polygon formats) for both birth and death rates, which consisted of subnational values for those areas where it was available and national values for others.

Downscaling to gridded level

We used multiple linear regression together with area-to-point kriging (ATPK) 60 , 61 to downscale the subnational birth and death rates to 5 arcmin (~10 km at the equator) resolution. The downscaling was done so that the average birth and death rates (total births and deaths of an area) were maintained at the administrative unit (subnational or national, depending on the source data) scale 62 . For the regression model, we used ‘relative population density’ (for urbanization proxy) and ‘subnational human development index’ data as independent variables in downscaling both births and deaths. Income and mean years of schooling, both being indicators of HDI, have been shown to correlate well with babies per woman at national scale 63 and ref. 5 used population density as a proxy for estimating the difference in natural population increase between urban and rural areas. For births, these were used together with gridded data of ‘share of women of reproductive age (15–49 years) of total population’ and for deaths with gridded data of ‘ratio of average age and life expectancy’. The ‘share of women of reproductive age (15–49 years) of total population’ is also used by ref. 64 to downscale births to gridded scale—although they did it only for one year and selected countries. For the independent variables used for downscaling, we used annual datasets for 2000–2019. These data were produced for this analysis by using openly available global datasets. Data preparations for the independent variables are described below, followed by the downscaling method in details.

Data preparation of independent variables for downscaling

Human development index.

We used tabulated subnational HDI data from ref. 65 to create a gridded and gap-filled gridded subnational HDI dataset for each year over 2000–2019, at 5 arcmin resolution. We used a similar method to fill missing years and rasterize the data as ref. 59 use in their gridded HDI dataset.

Relative population density

Rather than using global population density or night light data as the proxy of urbanization rate, we used population density scaled between 0 and 1 for each country. Using the WorldPop dataset 55 , we first extracted the 5th and 95th percentiles of population density by country across all years from 2000 to 2020, after the lowest population density cells (population density < 1 person per km 2 ) were omitted. We then scaled population densities within each country and year between 0 and 1, such that:

where popdScaled is the scaled population density for a year, popd is the unscaled population density for that year, popd95th is the 95th percentile population density for the country in question (using all years) and popd5th is the 5th percentile population density (using all years).

The scaled population density then indicates the degree of urbanization an area has undergone relative to the maximum state of urbanization experienced by that country across 2000–2020.

Share of women of reproductive age of total population

We used WorldPop ‘Age and sex structures’ dataset 66 to count the number of women of reproductive age (15–49 years). The data provide annual estimates globally for each 30 arcsec grid cell for the “[…] total number of people per grid square broken down by sex and age groupings (including 0–1 and by 5-year up to 80+)” (ref. 67 ). We aggregated these data to 5 arcmin resolution and divided this with the aggregated (from 30 arcsec to 5 arcmin) total population count of each grid cell using WorldPop ‘Population counts’ data 55 . This resulted in the share of women of reproductive age for each grid cell at 5 arcmin resolution. We repeated this for years 2000, 2005, 2010, 2015 and 2020 and interpolated the missing years to get annual gridded data for 2000–2020 (see map of the last timestep in Fig. 1e ).

Ratio of average age and life expectancy

To first calculate the average age of population in each grid cell, we used the same WorldPop ‘Age and sex structures’ dataset 66 that was used to compute the ‘share of women of reproductive age (15–49 years) of total population’ (see above). The data include the number of males and females by age group and thus, it allowed us to estimate the average age (for example, for the age group 5–9 years, we used an average age of 7 years). However, the dataset does not specify the average age for the age group 80+ and, thus, we needed to use UN population prospects national-level data to estimate it for each country and year and separately for females and males. From the national-level data, we first estimated the average age of that age group (separately for females and males) and then combined that with the grid cell level data—that is, assuming that in each grid cell of a country in question, the share of population over 80 years old had an average age equal to national average. As a result, we reached an estimate of the average age for each 5 arcmin grid cell. We then used the life expectancy component of subnational HDI data from ref. 65 . To fill missing years and rasterize the data, we used a method similar to the one ref. 59 use in their gridded HDI dataset. Finally, we took the ratio of these two datasets, resulting in a ratio of average age and life expectancy—the percentage of how much of their expected length of life has an average person lived—for each year over our study period 2000–2019.

Downscaling methods

To downscale the collated census data from the subnational administrative boundary scale to 5 arcmin gridded scale, we fitted multiple linear regression models of death and birth rates against global independent variables introduced above. Separate regression models were fitted for four income groups, where grouping was based on their relative income band 68 : low, lower middle, upper middle or high income. We first applied these regression models at the subnational administrative boundary scale to assess model performance and to calculate residuals (differences between model estimates and reported data) for each subnational administrative area. We then applied the regression models at the 5 arcmin scale and adjusted the estimates using an ATPK for the residuals calculated at the subnational administrative boundary scale. Finally, the downscaled estimates were adjusted to ensure that the total number of births and deaths matched the original data when aggregated to the subnational administration boundary scale 62 . Below, each step is presented in more detail.

Linear regression models

On the basis of the dataset from the World Bank 68 , we split countries into four income bands, marking them as low, lower middle, upper middle or high income. For each income bracket, we fitted a different regression model to capture the differing relationships between birth or death rates and independent variables.

Both birth and death rate models used the scaled population density and HDI data as predictor variables, with birth rate models additionally including the ‘share of women of reproductive age (15–49 years) of total population’ variable, whilst death rate models additionally included the ‘ratio of average age and life expectancy’ variable. The predictor variables were aggregated at the subnational administrative boundary scale by taking average values, which were then used for regression against either birth rates or death rates across all years (2000–2019).

We applied these regression models to predict birth and death rates for each grid cell, aggregated the cell-wise values at the subnational scale by weighting them with population and then assessed model performance and calculated residuals against the collated census data. We found that the models predicted birth and death rates well, with the coefficient of determinations being 0.74 and 0.60, respectively (Supplementary Table 1 ).

ATPK of the residuals and final population-weighted adjustment

Having calculated the residuals between modelled estimates of birth and death rates at the subnational scale and the collated census data, we performed an ATPK procedure to distribute these residuals across a 5 arcmin point mesh following the method described in ref. 69 . These grid-scale distributions of the residuals were then added to a grid-scale application of the regression models to give a first approximation for the downscaled datasets of both birth and death rates.

Finally, we adjusted the downscaled approximations to ensure that the total number of births or deaths represented in the downscaled dataset matched the collated census data at the subnational scale by applying equation ( 8 ) to each grid cell:

where R i adjusted is the adjusted rate (birth or death) in the grid cell, R i is the approximated rate in the grid cell, j  = 1 …n are the grid cells that fall within each subnational administrative boundary, p j is the population within grid cell j taken from WorldPop and C n is the census data birth or death rate for the subnational boundary containing cells j  = 1 …n .

Net migration data

The downscaled gridded births and deaths data (Fig. 1g,h ) were then used to calculate natural population change (deaths subtracted from births) (Fig. 1i ). Together with annual global gridded population count for 2000–2020 55 (Fig. 1j ), the natural population change data allowed us to calculate net migration for each year and grid cell (Fig. 1k ) as ’natural population change’ subtracted from ‘reported population change’.

Validation of data

We validated all downscaled datasets (WorldPop data and gridded births, deaths and net migration) with subnational and/or national observations. Subnational observations at administrative level 2 were collected from OECD 50 , 70 , Eurostat 49 , 51 , 71 , national statistical service of South Korea 72 and from ref. 73 . National observations were collected from the UN 74 . Here, it should be noted that the subnational validation data for population, births and deaths were collected at administrative level 2 (communal) whereas level 1 (provincial) data were used for producing and harmonizing the gridded datasets. Level 1 (provincial) data were used in validating the net migration estimates.

WorldPop data were validated against OECD data 70 which reports population counts for 1,818 subnational units globally. WorldPop data were first aggregated to the subnational units and then compared with OECD data through correlation analysis. Validation results are presented in detail in Supplementary Fig. 1 and Supplementary Table 2 .

Downscaled births and deaths

Downscaled births and deaths were validated against Eurostat subnational data ( n  = 1,504) and OECD subnational data ( n  = 1,883), respectively. Gridded birth and death rates were first aggregated to the respective subnational units and then compared with the observed values. Validation results are provided in the Supplementary Fig. 2 and Supplementary Table 2 .

Net migration

For validating net migration data, we used national-level data provided by the UN 74 and subnational observations collected from ref. 73 for the United States (counties; n  = 3,056), national statistical service of South Korea (provinces; n  = 16) (ref. 72 ) and Eurostat for Europe (districts; n  = 1,522) (ref. 71 ). Gridded net migration data were first aggregated to the national/subnational units and then compared with the observations in the respective resolution. Subnational validation was conducted for both the total net migration count as well as the rate (net migration per population). Total net migration for a unit was first obtained by aggregating (zonal sum) the gridded net migration estimates over a subnational unit. Annual rate of net migration per population for a subnational unit could then be calculated by dividing both the aggregate sum of net migration and the observed net migration by the aggregate sum of population count (here, WorldPop data were used) of the respective subnational unit. Additionally, cumulative sums of net migration were calculated for both the estimated (here-produced) and observed net migration data. Cumulative sums were calculated for years 2000–2005, 2006–2010, 2011–2015, 2015–2020 (5 year sums) and for years 2000–2010 and 2011–2020 (10 year sums). Rates for the accumulated net migration counts were calculated by dividing the accumulated sum by the respective 5 or 10 year population average in the given subnational unit. Validation results and country-specific details are provided in Supplementary Figs. 3 – 6 and Supplementary Table 2 .

Urban extent data

Existing mappings of global urban areas include exercises like the one mapping global human settlements and urban centres by using a ‘degree of urbanization’ approach that divides human settlements into rural, semi-urban and urban areas on the basis of population size, population and the density of built-up areas. However, these data cover only a few years 75 . A recent urban extent dataset developed by using night light data also covers only one timestep 76 , while the most up-to-date time-series data of global urban extent cover nearly 100 years (2010–2100) (ref. 77 ), hence missing a decade from our study period.

Thus, we created urban extent data for each country for each year by using gridded relative population density (see above) and the share of urban population of total population for each country and year. The tabulated annual share of urban population in each country was acquired from the UN World Urbanization Prospects 42 . By going through each country cell by cell, the share of urban population was used to find a population density threshold where urban population turns to rural. Here, it was assumed that all urban area cells were more densely populated than all rural area cells. In other words, the calculation propagated in descending order of population density so that the sparsest-populated cell within urban extent was assumed to be more densely populated than the densest-populated cell not within the urban extent.

This was done by first calculating the total and urban population for each country:

Then, a threshold where urban population turns to rural was defined by calculating the cumulative population count. Starting from the cells with highest relative population density, population count in each grid cell in each country was summed until the cumulative count met the urban population defined above (urbanPop). All cells in the cumulative count were assigned value 1 (urban) and the rest were assigned value 0 (rural).

Zonal statistics: administrative areas and socioclimatic bins

For the three administrative levels, we used the Global Administrative Areas (GADM) levels 0, 1 and 2 for national, provincial and communal areas, respectively.

All zonal statistics in the study were done with the zonal tool in terra package (v.1.5-12) in R 78 . Socioclimatic bins were created by using global gridded data of aridity (global aridity index 79 ), human development (human development index; see above) and population counts for 2000–2019 (ref. 55 ). For the climatic factor, aridity index—a ratio of potential evaporation to precipitation—was chosen to capture the different atmospheric and land surface processes shaping terrestrial dryness. Aridity index has been used to assess desertification under climate change 80 . Here, the zonal analyses were conducted by using a long-term estimate of net migration (accumulated sum over the study period 2000–2019), which is why the impacts of short-term events, such as natural disasters, are not visible in the analysis.

Our binning divides global inhabited areas into 100 socioclimatologically analogous zones, which have similar human development and climatic conditions. The binning was conducted in two steps. First, we divided all considered grid cells into ten population-weighted quantiles on the basis of HDI. After that, each HDI quantile was again divided into ten population-weighted quantiles on the basis of aridity. All values in the first aridity quantile of the first HDI quantile would fall under the first bin (bin no. 0), while values in the second aridity quantile of the first HDI quantile would go in the second bin (bin no. 1). The division of bins is illustrated in Extended Data Fig. 7 . This division ensured that each bin incorporates ~1% of the global population. The binning represented as a heatmap could then be transformed into a map representation (Extended Data Fig. 8c ). Urban and rural areas in each bin could be extracted by using the urban extent data (see above). Global maps and description of the preprocessing of both human development, aridity index and socioclimatic bins are available in Extended Data Fig. 8 .

Impact calculations

Impact of total, rural and urban migration on respective populations was calculated for each administrative unit, as well as for each socioclimatic bin. First, migration data and population counts were aggregated for each spatial unit for each year (2000–2019) by using zonal sum. Then, total population change between 2019 and 2000 and accumulated net migration were calculated for each unit:

Population change without migration (natural population change) could then be calculated by subtracting cumulative net migration from total population change:

The impact of migration on population was deducted by comparing population change to cumulative net migration by using the following criteria:

Direction of migration

The direction of migration was studied in rural and urban areas at three administrative levels. Here, accumulated rural and urban net migration over 2000–2019 were calculated and compared to define the direction of migration according to the following criteria:

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All the data used in this study are publicly available. The resultant datasets are available at the following open-access repository https://doi.org/10.5281/zenodo.7997134 , including the following datasets: annual global net migration rates at grid scale as a multiband GeoTIFF with 5 arcmin resolution for 2000–2019; annual global net migration rates for adm0, adm1 and adm2 levels as polygon layers (gpkg-files); and annual global birth and death rates as multiband GeoTIFFs with 5 arcmin resolution for 2000–2019. Data are visualized in online net migration explorer at https://wdrg.aalto.fi/global-net-migration-explorer/ . Data underlying the web application are available in the repository with all other data.

Code availability

The analysis was performed using RStudio (R v.4.1.2). The code is available at https://github.com/mattikummu/global_net_migration.git . The online net migration explorer was conducted using RStudio (R v.4.2.2). The code is available at https://github.com/vvirkki/net-migration-explorer.git .

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Acknowledgements

This study was funded by Maa- ja vesitekniikan tuki ry, the European Research Council under the European Union’s Horizon 2020 research and innovation programme (SOS.aquaterra project; grant no. 819202), the European Research Council under the European Union’s Horizon 2020 research and innovation programme (POPCLIMA project, grant no. 101002973), the Aalto University School of Engineering, the Academy of Finland (TREFORM project; grant no. 339834), the Academy of Finland (WATVUL project; grant no. 317320) and the National Science Foundation of China funding research fund for International Young Scientists (grant no. 41950410572). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We would like to thank M. Jalava from Aalto University for help with issues related to computations and setting up a server for the web application.

Open Access funding provided by Aalto University.

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These authors contributed equally: Venla Niva, Matti Kummu.

Authors and Affiliations

Water and Environmental Engineering Research Group, School of Engineering, Aalto University, Espoo, Finland

Venla Niva, Alexander Horton, Vili Virkki, Matias Heino, Maria Kosonen, Marko Kallio, Pekka Kinnunen, Maija Taka, Olli Varis & Matti Kummu

Geoinformatics Research Group, School of Engineering, Aalto University, Espoo, Finland

Marko Kallio

International Institute for Applied Systems Analysis, Laxenburg, Austria

Guy J. Abel

Asian Demographic Research Institute, Shanghai University, Shanghai, China

Faculty of Social Sciences, The University of Hong Kong, Pokfulam, Hong Kong

Department of Statistical Sciences, University of Bologna, Bologna, Italy

Raya Muttarak

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Contributions

V.N. and M. Kummu designed the research. Data collection and processing was led by M. Kummu and M. Kosonen with help from A.H., V.V., M.H., M. Kallio, P.K. and V.N. V.N. and M. Kummu performed the analysis with help from A.H. V.V. created the online net migration explorer. V.N. and M. Kummu created the illustrations. All authors discussed the methods and results and helped shape the research and analysis. V.N. and M. Kummu took the lead in writing the manuscript with important contributions from all authors.

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Correspondence to Venla Niva or Matti Kummu .

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Extended data

Extended data fig. 1 origin of datasets used..

Origin of the datasets used for a) birth rates and b) death rates. See Methods for more details. Sources for the data are provided in Supplementary Data Table. The geospatial files used in the maps are from The DHS Program 52 , Eurostat 53 , OECD 54 and GADM ( www.gadm.org ).

Extended Data Fig. 2 Input variables used for downscaling birth and death rates.

(a) Human Development Index, (b) population density, scaled between 0–1, (c) share of women of reproductive age (15–49) of total population and (d) share of life lived for an average person. Each dataset includes annual values for each year over 2000–2019 – shown here are the data for the last timestep, that is year 2019.

Extended Data Fig. 3 Urban and rural areas.

Example of (a) global urban areas in 2019 and in three timesteps (b: 2000, c: 2010, d: 2019) in the South China Sea around the Malaysian peninsula.

Extended Data Fig. 4 Regional division.

Regional division based on the UN country grouping.

Extended Data Fig. 5 Net migration in rural and urban areas.

Net migration in urban and rural grid cells in three timesteps: 2000 (a,b), 2010 (c,d) and 2019 (e,f).

Extended Data Fig. 6 Cumulative net migration in urban and rural areas.

Cumulative net migration (per 1000 urban and rural inhabitants in each administrative unit) in urban and rural areas over 2000–2019. Three administrative levels are shown: a-b: communal (admin 2 level), c-d: provincial (admin 1 level) and e-f: national (admin 0 level).

Extended Data Fig. 7 Schematic illustration of creating the socioeconomic bins.

Illustration of how the Human Development Index (HDI) and Aridity (AI) were combined to create socioeconomic bins. Each bin includes ca 1% of global population.

Extended Data Fig. 8 Socioclimatic bins with the input data for them.

Global maps of (a) human development index, (b) global aridity index and (c) socioclimatic bins. Each bin includes ca 1% of global population. See Methods for more details.

Supplementary information

Supplementary information.

Supplementary Text, Figs. 1–6 and Tables 1 and 2.

Reporting Summary

Peer review file, supplementary data.

Description, resolution, timespan and sources of each collected dataset.

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Niva, V., Horton, A., Virkki, V. et al. World’s human migration patterns in 2000–2019 unveiled by high-resolution data. Nat Hum Behav 7 , 2023–2037 (2023). https://doi.org/10.1038/s41562-023-01689-4

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• Published: 08 August 2018

Migration and health: a global public health research priority

• Kolitha Wickramage 1 ,
• Jo Vearey 2 ,
• Anthony B. Zwi 3 ,
• Courtland Robinson 4 &
• Michael Knipper 5  

BMC Public Health volume  18 , Article number:  987 ( 2018 ) Cite this article

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With 244 million international migrants, and significantly more people moving within their country of birth, there is an urgent need to engage with migration at all levels in order to support progress towards global health and development targets. In response to this, the 2nd Global Consultation on Migration and Health– held in Colombo, Sri Lanka in February 2017 – facilitated discussions concerning the role of research in supporting evidence-informed health responses that engage with migration.

Conclusions

Drawing on discussions with policy makers, research scholars, civil society, and United Nations agencies held in Colombo, we emphasize the urgent need for quality research on international and domestic (in-country) migration and health to support efforts to achieve the Sustainable Development Goals (SDGs). The SDGs aim to ‘leave no-one behind’ irrespective of their legal status. An ethically sound human rights approach to research that involves engagement across multiple disciplines is required. Researchers need to be sensitive when designing and disseminating research findings as data on migration and health may be misused, both at an individual and population level. We emphasize the importance of creating an ‘enabling environment’ for migration and health research at national, regional and global levels, and call for the development of meaningful linkages – such as through research reference groups – to support evidence-informed inter-sectoral policy and priority setting processes.

Peer Review reports

Migration and health are increasingly recognized as a global public health priority [ 1 ]. Incorporating mixed flows of economic, forced, and irregular migration, migration has increased in extent and complexity. Globally, it is estimated that there are 244 million international migrants and significantly more internal migrants – people moving within their country of birth [ 2 ]. Whilst the majority of international migrants move between countries of the ‘global south’ [ 2 ], these movements between low and middle-income countries remain a “blind spot” for policymakers, researchers and the media, with disproportionate political and policy attention focused on irregular migration to high-income countries. Migration is increasingly recognized as a determinant of health [ 3 , 4 , 5 ]. However, the bidirectional relationship between migration and health remains poorly understood, and action on migration and health remains limited, negatively impacting not only those who migrate but also sending, receiving, and ‘left-behind’ communities [ 1 ].

In February 2017, an international group of researchers participated in the 2nd Global Consultation on Migration and Health held in Colombo, Sri Lanka with the objectives of sharing lessons learned, good practices, and research in addressing the relationship between migration and health [ 1 ]. Hosted by the International Organization for Migration (IOM), the World Health Organization (WHO), and the Sri Lankan government, the Global Consultation brought together governments, civil society, international organizations, and academic representatives in order to address migration and health. The Consultation facilitated engagement with the health needs of migrants, reconciling the focus on long-term economic and structural migration - both within and across international borders - with that of acute, large-scale displacement flows that may include refugees, asylum seekers, internally displaced persons and undocumented migrants.

The Consultation was organised around inputs on three thematic areas: Global Health [ 6 ]; Vulnerability and Resilience [ 7 ]; and, Development [ 8 ]. These inputs guided working group discussions exploring either policy, research, or monitoring in relation to migration and health. This paper reports on the outcomes of the research group after an extensive period of debate at the Consultation and over the subsequent 9 months. We identify key issues that should guide research practice in the field of migration and health, and outline strategies to support the development of evidence-informed policies and practices at global, regional, national, and local levels [ 9 ]. Debate and discussion at the Consultation, and below, were guided by two key questions:

What are the opportunities and challenges, and the essential components associated with developing a research agenda on migration and health?

What values and approaches should guide the development of a national research agenda and data collection system on migration and health?

Our discussions emphasized that international targets, such as the Sustainable Development Goals (SDGs) and Universal Health Coverage (UHC; Health target 3.8 of the SDGs), are unlikely to be achieved if the dynamics of migration are not better understood and incorporated in policy and programming. To address this, and in order to improve policy and programming, a renewed focus on enhancing our understanding of the linkages between both international and internal migration and health, as well as the outcomes and impacts arising from them, is urgently needed.

Migration and health research: Leave no-one behind

The Sustainable Development Goals (SDGs) identify migration as both a catalyst and a driver for sustainable development. A clarion call of the SDGs is to ‘leave no-one behind’, irrespective of their legal status, in order to achieve Universal Health Coverage (UHC) for all [ 10 ]. In many countries, however, equitable access to health services is considered as a goal only in relation to citizens. Additionally, internal migration is left out of programming and policy interventions designed to support UHC for all. While UHC aims at ensuring “everyone” can access affordable health systems without increasing the risk of financial ruin or impoverishment, the formulation of UHC remains unclear regarding non-nationals/non-citizens [ 11 ]. While many international declarations state that the right to health applies to all, including migrants and non-citizens, many national policies exclude these groups in whole or part [ 12 ].

In addition to international and internal migration, the health concerns associated with labour migration require attention; migrant workers are estimated to account for 150.3 million of the 244 million international migrants [ 2 ]. While labour migration leads to significant economic gains for countries of origin and destination, true developmental benefits are only realised with access to safe, orderly and humane migration practice [ 13 ]. Many migrant labourers work in conditions of precarious employment, within ‘difficult, degrading and dangerous’ jobs yet little is known about the health status, health outcomes, and resilience/vulnerability trajectories of these migrant workers and their ‘left behind’ families. Many undergo health assessments as a pre-condition for travel and migration, yet many such programs remain unlinked to national public health systems [ 14 ].

Our discussions highlighted the complex and heterogeneous nature of research on migration and health, with particular concerns raised around the emphasis on international rather than internal migration, in view of the greater volume of the latter. The need for a multilevel research agenda to guide appropriate action on international and internal migration, health, and development was highlighted. In order to account for immediate, long-term and inter-generational impacts on health outcomes, migration and health research should: (1) incorporate the different phases of migration (Fig. 1 ); (2) adopt a life-course approach; and, (3) integrate a social determinants of health (SDH) approach.

Factors influencing health and wellbeing of migrants and their families along the phases of migration

Unease was expressed about the increasingly polarised political viewpoints on migration, often propagated by nationalist and populist movements, which present real challenges to researchers. This may also be associated with a reluctance to finance research exploring discriminatory policies that limit the access of international migrants to health services and other positive determinants of health, including work and housing.

The increasing complexity of global, regional, and national migration trends, as well as disagreements about the correct way to define and label different types of migrants, create additional difficulties within an already tense and politically contested research domain. Associated with this are the particular challenges associated with collecting and utilising data on ‘irregular migrants’ – international migrants currently without the documentation required to legally be in a particular country. These undocumented migrants, often living in the shadows of society, are more vulnerable to poor health outcomes due to restrictive policies on access to health and social services, to safe working and living conditions, and/or a reluctance to access services for fear of arrest, detention and/or deportation [ 15 , 16 ]. Whilst arguments for improving access to health care for marginalised migrants are based on principles of equity, public health, and human rights, the importance of research on the economic implications of limiting access to care for international migrants was highlighted [ 2 ]. This challenging terrain generated a myriad of research questions during the group discussions (Table 1 ).

Towards a framework for advancing migration and health research

The consultation took into account the extensive research experience of the group (see Appendix ), as well as engagement with key literature and context-specific evidence [see, for example 1–7]. Discussion led to the development of a framework that brings together what we identify as the key components for advancing a global, multi-level, migration and health research agenda (Fig. 2 ). Two areas of focus to advance the migration and health research agenda were identified: (1) exploring health issues across various migrant typologies , and (2) improving our understanding of the interactions between migration and health . Advancing research in both areas is essential if we are to improve our understanding of how to respond to the complex linkages between both international and internal migration and health. This, we argue, can be achieved by moving away from an approach that exceptionalises migration and migrants, to one that integrates migration into overall health systems research, design, and delivery, and conceptualises this as a way to support the achievement of good health for all.

Advancing Migration and Health Research at National, Regional and Global Levels: a conceptual framework

Building from these focus areas, our framework outlines the essential components for the development and application of multi-level research on migration and health. First are key principles underlying research practice: promoting interdisciplinary, human rights oriented, ethically sound approaches for working with migrants. Second are multi-level stewardship functions needed to meaningfully link migration and health research to policy practice and priority setting, [ 17 ]. This includes establishing knowledge exchange mechanisms, financing, commissioning, and utilising research to guide evidence informed policies. This may better enable health systems to become ‘migration aware’ [ 18 ] or what the International Organization for Migration (IOM) terms ‘mobility competent’ - sensitive to health and migration [ 1 ].

Migration and health research: Two key focus areas

Migrant typologies.

To assist in understanding the associations between migration and health, our research must find ways to better capture and engage with complex, dynamic, and often intersecting migrant typologies. We must be careful not to cluster migrants and their associated lived experiences, to simple, reductionist categories such as internal versus cross-border or documented versus undocumented, or even refugee versus economic migrant [ 19 ]. However, we do need a way of categorising different migrant groups when, for example, exploring epidemiological profiles and associated burdens of disease. To do this, we need to develop a set of nuanced yet flexible typologies that are able to capture the contextually relevant factors affecting migrant experiences, at both the individual and population levels. As outlined in Table 2 , this will require careful consideration of multiple factors to assist us in improving our understandings of the ways in which diverse migrant groups are associated, or not, with various health and wellbeing outcomes. Definitions that are based on immigration status - such as ‘refugee’, ‘immigrant’ or ‘asylum seeker’ - will incorporate diverse sub-groups, often with different levels of health vulnerabilities and resiliencies based on their migration trajectory. For instance, a refugee entering a country with an offer of permanent resettlement or with a recognized temporary protected status, will have different opportunities and challenges than an asylum-seeker, or migrant worker, crossing a border possibly without documents or a clear pathway to needed healthcare and protections. Each of these migrating populations carry different health burdens (and resiliencies) from their country of origin, their social position and access to resources, and their migration experiences; and each will face different barriers and uncertainties as they seek access to services, support and integrate in host communities. The definitions of migrant groups adopted by states not only need clear elucidation but also need to reflect the context-specific conditions affecting health access and protection. In Europe, for example, the entitlements to health care for asylum seekers differ by country [ 20 ]. The Migrant Integration Policy Index (MIPEX) health strand was developed as a tool to monitor policies affecting migrant integration in 38 different countries [ 18 ]. It measures the equitability of policies relating to four issues: migrants’ entitlements to health services; accessibility of health services for migrants; responsiveness to migrants’ needs; and measures to achieve change. Such tools are important steps in assessing migrant integration and for implementing migrant-sensitive policies that are aligned with the person-centred UHC principles.

An awareness of this complexity underlies the need to document multiple migrant voices and migration experiences along the diverse trajectories when exploring associations between migration and health. This could, for instance, involve capturing the voices of children and other family members ‘left-behind’ as a result of labour migration, or of seasonal migrant workers. Research into the issues, policies and programmes that influence health and health literacy among migrant populations and the role that communities, households, industries, schools, and transnational networks play in promoting health also needs exploration.

Key challenges exist when attempting to use and compare migration data internationally, as a result of differences in the definition of who is an international migrant, non-national, or internal migrant; inconsistent data sources; and limited data coverage. A recent analysis of the availability, reliability and comparability of data on international migration flows in European countries noted that “comparing migration flows in various countries would be like comparing pears and apples” [ 21 ]. The use of standard indicators can result in unreliable data if migration dynamics are not considered. For example, measures of life expectancy are skewed if international migrants return to their home countries when they are seriously ill, but their departure is not accounted for in vital registration or other systems [ 21 ]. Reporting that is based on incomplete, poor quality or non-comparable population data that fails to measure and/or report migration can give rise to misleading conclusions and limits the validity of data interpretation.

Research at the nexus of migration and health

We recognise the bi-directionality of the relationship between migration and health. Our research should explore how different forms of migration influence health – at both individual and population levels - and how health status affects decisions to migrate and shapes post-migration experience. Migration trajectories can positively or negatively impact health outcomes, just as health status can affect migration outcomes; this two-way relationship should be better reflected in research. To support this, we must be sure to differentiate carefully between different migrant typologies – for example within or across international borders and for what purpose: work, family reunification, escape from persecution, flight from conflict or natural disaster, or to seek asylum. Each of these operates within substantially different contexts whether one takes the migrant and their health into account, or their rights and entitlements, or how they are seen by the dominant society or community to which they migrate. We recognise that being a migrant is not in itself a risk to health: it is the conditions associated with migration that may increase vulnerability to poor health [ 4 ]. Owing to the ways in which people move and the spaces they traverse or at which they arrive, migrants may reside in - or pass through - ‘spaces of vulnerability’ [ 22 ] – key spaces associated with potentially negative health outcomes – including along transport corridors, urban slums, construction sites, commercial farms, fishing communities, mines, and detention centres. Such spaces may contain a combination of social, economic and physical conditions that may increase the likelihood of exposure to violence and abuse and/or acquisition of communicable or non-communicable disease [ 22 ]. The daily stressors that may be experienced in these spaces are increasingly acknowledged to affect emotional wellbeing and mental health [ 23 ].

As migration is an ever-changing dynamic process, generating and maintaining timely and comparable migration data and improving relevant information systems is important. ‘Quick wins’ in obtaining migration and health data by integrating migration variables into existing national demographic and health surveys, for instance, were highlighted. National disease control programs such as tuberculosis, HIV and malaria control programs should also be encouraged to collect data on internal and international migration, especially in cross-border areas. Communicable disease control remains a key health concern associated with human migration. Our discussions recognised the importance of embracing systems-theory approach for improving understanding of how migration influences not only disease transmission but also health promotion, and health-care seeking behaviours. The importance of collecting such data with strict adherence to research ethics and human rights was emphasised.

Towards a multilevel migration and health research agenda

To effectively inform policies and programs on migration and health, it is essential to invest in evidence generation through research at local, national, regional, and global levels. Identified approaches include the establishment of research reference groups at each level to support, guide, and connect the development and application of research to support evidence-informed policy making at multiple levels. Mapping and analysis of key stakeholders, migration patterns, existing legal frameworks, data source, and research output via bibliometric analysis is needed. Multi-level migration and health policy and priority setting processes must be guided by interdisciplinary and multisectoral thinking in order to address the multiple determinants associated with the health of both internal and cross-border migrants.

Key constituencies need to be mobilised from academia, civil society, international organizations, the private sector including employer groups, trade unions and migrant worker networks. These groups may also play a role in commissioning or directly undertaking applied research in order to advance better outcomes for migrants and communities in both places of origin and destination. High-level political leadership and health and development champions should raise the visibility of migration and health research. It is important to utilise existing research structures and resources to support the development of a research agenda on migration and health, as well as to seek support for the development of dedicated research commissions on migration and health at multiple levels in order to harness evidence to drive policy-making and programme formation. For instance, the Government of Sri Lanka, with the technical cooperation of IOM, commissioned a National Migration Health Research Study in 2010 to explore health impacts of inbound, outbound, and internal migrant flows including those of left-behind migrant families. The research findings ultimately contributed to the formulation of an evidence-informed National Migration Health Policy and national action plan in 2013 [ 24 ]. The research was led through local research institutions and research process were linked to an inter-ministerial and inter-agency process chaired by the Minister of Health. This evidence informed policy making process also led to a number of national programs such as ‘the national border health program’ in 2013, revitalizing domestic legal frameworks on health security, and advancing health protection of migrant workers at regional inter-governmental initiatives such as the Colombo Process.

At the regional level, consultative processes are required to develop common approaches to migration and health, including communicable disease surveillance, monitoring of interventions, applied research collaboration across national borders and capacity building – particularly interdisciplinary postgraduate training. For instance, the Mekong Basin Disease Surveillance (MBDS) Consortium is a sub-regional co-operation spearheaded by health ministries from member countries Cambodia, China, Lao PDR, Myanmar, Thailand and Vietnam [ 25 ]. In relation to labour migration, regional processes – such as the Colombo Process [ 26 ] - should explore the management of overseas employment and contractual labour. In addition, migrant health-related concerns should be emphasised in the negotiation of free trade agreements that increase migration between states, such as the Post-2015 Health Development Agenda for a “ Healthy, Caring and Sustainable Community ” initiative of the Association of South-East Asian Nations (ASEAN) [ 27 ] and efforts to implement the “Health in all Policies” strategy of the European Union [ 7 ].

Methods to map human mobility for public health preparedness and response stemming from outbreaks and other health emergencies are needed in order to provide accurate information on population movements, for monitoring the progression of outbreaks, predicting future spread and allocating resources for surveillance and containment strategies. Human mobility was a critical factor in the spread of Ebola virus in the West African region.

A coordinated global research agenda on migration and health is urgently needed. Potential elements include collaboration with stakeholders involved in implementing global initiatives – such as the SDGs – to ensure that indicators and data collection strategies are sensitive to both internal and cross-border migration, and health related issues. Identification of datasets and data collection processes that can be adapted and mined for disaggregated health data related to migration are also crucial in advancing the evidence base. We support the development of a sustainable global reference group that can share research evidence, expertise and experience, develop methodological and ethical guidelines, undertake multi-country studies, provide training and build a global knowledge hub in migration and health. Such a group can also mobilise funders and development partners, collaborate with scientific and professional associations, and engage with journals and publishers to create awareness on the need to better promote migration and health research.

The ‘Migration, Health, and Development Research Initiative’ (MHADRI) is a global network of academics and other research partners who aim to advance migration and health research practice [ 28 ]. The research network was formed around the need to build a global alliance of migration and health researchers and provide a platform to share, collaborate, develop, mentor, advocate and disseminate inter-disciplinary research at the nexus of health and migration. A key goal of the network is to enable researchers from developing nations the opportunity to collaborate and promote research in the Global South. The network has grown to encompass 100 researchers globally, across diverse disciplines, geographic areas and stages of career. A global reference group would be well placed to develop good practice guides on data collection systems, research methods and ethics; research translation and dissemination; and, policy integration strategies.

Research principles

We identified core principles that should guide research on migration and health, and work with migrant populations: an ethically sound human rights approach to research that involves engagement across multiple disciplines. Researchers need to be sensitive when designing and disseminating research findings as data on migration and health may be misused, both at an individual and population level. Key questions related to how researchers can exercise their duty of care as they engage in research, and how we can promote careful use of data and research to make sure it does more good than harm. Activities associated with international migration sometimes take place in a climate of victim blaming, othering, and stigmatisation that prioritises purported national security concerns [ 29 ]. Pressing concerns were identified that relate to the ways in which researchers can navigate this increasingly challenging environment, and how trust can be established among different stakeholders – including with international migrant groups. Securitization agendas also affect the health of migrants by excluding, discriminating and/or blaming migrants as vectors of disease. Ethical approaches to research, with a clear commitment to universal human rights, are therefore paramount in a climate of increasingly restrictive immigration regimes.

Discussions also highlighted the challenges associated with the collection of data with and from migrant populations. These include sampling, biases, and practical barriers such as language and culture, as well as the challenges inherent in reaching people who are often highly marginalised and potentially criminalised. Particular attention needs to be given to ethical issues: protecting confidentiality and ensuring that participation in research does not have an adverse impact on migrants, especially irregular migrants, and that participants gain access to relevant services if required. The development of meaningful partnerships and respectful research practice with actors involved in the migration process will also improve the quality, reliability, legitimacy, and use of the data generated.

Contributions from a range of disciplines – such as anthropology, demography, sociology, law, political science, psychology, policy analysis, public health, and epidemiology – are required to unpack the complex relationships between migration and health. Approaches to “slow research” [ 30 ] may help increase the sensitivity of epistemologies and methods to local realities, intricate dynamics, and the multiple voices and perceptions of migrants, health professionals and other individuals involved [ 24 ]. However, the lack of dedicated research units, institutes or centres on migration and health - especially within lower-income country contexts - require existing researchers and scholars to consolidate and better engage with sub-regional, regional and global research networks to ensure capacity building, mentoring, and support. Sensitising the donor community to the migration and health agenda, especially those funding research, is paramount. Curriculum development and teaching support for building the next generation of migration and health researchers is critical to successfully building and sustaining future research on migration and health.

Stewardship elements

We discussed the importance of developing appropriate research translation and engagement activities in order to support key, identified stewardship functions [ 17 ] at the global, regional, national and local levels. Key gaps in stewardship related to the lack of major funding mechanisms for research at national, regional, and global levels, and the need to invest in capacity building for emerging researchers through training programs and support, especially for researchers in lower-income country settings. Collaboration is required to support relationships among researchers and with relevant stakeholders, particularly with migrant communities. This includes building inclusive migration and health research networks, developing communities of practice, and supporting collaborations with those working on other global health priorities. Our research also needs to include the experiences of service providers who engage with various migrant populations, such as those within the health care sectors, border management, law enforcement, and labour migration. The development of effective research translation and public engagement strategies for sharing research findings is critical: not only to shape multi-level policy processes but also public and political opinion.

There was clear consensus on our commitment to enhancing the quality and breadth of multi-level research evidence to support the development of improved responses to migration and health. The importance of an ‘enabling environment’ for migration and health research at local, national, regional and global levels was emphasised, as was the development of meaningful linkages – such as through research reference groups – to support evidence-informed and intersectoral policy and priority setting processes. Our research needs to be underpinned by a human rights approach to health and sound ethical practice. With adequate funding, capacity development, and support for academic freedom, we can improve the evidence base to guide policy and programming for migration and health at multiple levels and in so doing contribute to improving health for all.

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Acknowledgements

Members of the research stream at the 2nd Global Consultation on Migration and Health who participated and contributed to the discussions (see Appendix ).

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All authors contributed to structuring and facilitating the research stream at the Global Consultation. KW, JV, AZ, CR, MK documented and synthesized the key themes emergent from the working groups and prepared ‘mind maps’. KW authored a section in the final report from the Global Consultation on behalf of the research stream, on which this article is based. JV wrote first draft of the article. KW and JV revised the article based on very helpful comments from two reviewers. All authors reviewed and approved the final manuscript.

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Members of the research stream at the 2nd Global Consultation on Migration and Health

In alphabetical order:

Ibrahim Abubakar (Director, Institute for Global Health, University College London, United Kingdom)

Anjali Borhade (Associate Professor, Indian Institute of Public Health, India)

Chee-khoon Chan (Research Associate, University of Malaya, Malaysia)

Julia Puebla Fortier (Executive Director, Diversity Rx - Resources for Cross Cultural Health Care)

Charles Hui (Associate Professor of Paediatrics and Chief of Infectious Diseases, University of Ottawa, Ottawa, Ontario)

Michael Knipper (Associate Professor, Institute of the History of Medicine of the University of Giessen, Germany)

Michela Martini (Migration Health Regional Specialist, IOM Regional Office for Horn, East and Southern Africa, Nairobi, Kenya)

Moeketsi Modisenyane, National Department of Health, South Africa

Davide Mosca (Director, Migration Health Division, IOM, Geneva, Switzerland)

Kevin Pottie (Associate Professor, Faculty of Medicine, University of Ottawa, Ottawa, Ontario)

Bayard Roberts (Director, The Centre for Health and Social Change at the London School of Hygiene and Tropical Medicine, London, United Kingdom)

William Courtland Robinson (Associate Professor, Johns Hopkins Bloomberg, School of Public Health, USA)

Chesmal Siriwardhana (Associate Professor, London School for Hygiene and Tropical Medicine)

Ursula Trummer (Head, Center for Health and Migration, Vienna, Austria)

Jo Vearey (Associate Professor, African Centre for Migration & Society (ACMS), University of the Witwatersrand)

Kolitha Wickramage (Migration Health and Epidemiology Coordinator, IOM, Manila, Philippines)

Anthony Zwi (Professor of Global Health and Development, The University of New South Wales, Sydney, Australia)

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Wickramage, K., Vearey, J., Zwi, A.B. et al. Migration and health: a global public health research priority. BMC Public Health 18 , 987 (2018). https://doi.org/10.1186/s12889-018-5932-5

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Article contents

Global migration: causes and consequences.

• Benjamin Helms Benjamin Helms Department of Politics, University of Virginia
•  and  David Leblang David Leblang Department of Politics, Frank Batten School of Leadership and Public Policy, University of Virginia
• https://doi.org/10.1093/acrefore/9780190228637.013.631
• Published online: 25 February 2019

International migration is a multifaceted process with distinct stages and decision points. An initial decision to leave one’s country of birth may be made by the individual or the family unit, and this decision may reflect a desire to reconnect with friends and family who have already moved abroad, a need to diversify the family’s access to financial capital, a demand to increase wages, or a belief that conditions abroad will provide social and/or political benefits not available in the homeland. Once the individual has decided to move abroad, the next decision is the choice of destination. Standard explanations of destination choice have focused on the physical costs associated with moving—moving shorter distances is often less expensive than moving to a destination farther away; these explanations have recently been modified to include other social, political, familial, and cultural dimensions as part of the transaction cost associated with migrating. Arrival in a host country does not mean that an émigré’s relationship with their homeland is over. Migrant networks are an engine of global economic integration—expatriates help expand trade and investment flows, they transmit skills and knowledge back to their homelands, and they remit financial and human capital. Aware of the value of their external populations, home countries have developed a range of policies that enable them to “harness” their diasporas.

• immigration
• international political economy
• factor flows
• gravity models

Introduction

The steady growth of international labor migration is an important, yet underappreciated, aspect of globalization. 1 In 1970 , just 78 million people, or about 2.1% of the global population, lived outside their country of birth. By 1990 , that number had nearly doubled to more than 150 million people, or about 2.8% of the global population (United Nations Population Division, 2012 ). Despite the growth of populist political parties and restrictionist movements in key destination countries, the growth in global migration shows no signs of slowing down, with nearly 250 million people living outside their country of birth as of 2015 . While 34% of all global migrants live in industrialized countries (with the United States and Germany leading the way), 38% of all global migration occurs between developing countries (World Bank, 2016 ).

Identifying the causes and consequences of international labor migration is essential to our broader understanding of globalization. Scholars across diverse academic fields, including economics, political science, sociology, law, and demography, have attempted to explain why individuals voluntarily leave their homelands. The dominant thread in the labor migration literature is influenced by microeconomics, which posits that individuals contemplating migration are rational, utility-maximizing actors who carefully weigh the potential costs and benefits of leaving their country of origin (e.g., Borjas, 1989 ; Portes & Böröcz, 1989 ; Grogger & Hanson, 2011 ). The act of migration, from this perspective, is typically conceptualized as an investment from which a migrant expects to receive some benefit, whether it be in the form of increased income, political freedom, or enhanced social ties (Schultz, 1961 ; Sjaastad, 1962 ; Collier & Hoeffler, 2014 ).

In this article we go beyond the treatment of migration as a single decision and conceive of it as a multifaceted process with distinct stages and decision points. We identify factors that are relevant at different stages in the migration process and highlight how and when certain factors interact with others during the migration process. Economic factors such as the wage differential between origin and destination countries, for example, may be the driving factor behind someone’s initial decision to migrate (Borjas, 1989 ). But when choosing a specific destination, economic factors may be conditioned by political or social conditions in that destination (Fitzgerald, Leblang, & Teets, 2014 ). Each stage or decision point has distinguishing features that are important in determining how (potential) migrants respond to the driving forces identified by scholars.

This is certainly not a theoretical innovation; migration has long been conceived of as a multi-step process, and scholars often identify the stage or decision point to which their argument best applies. However, most interdisciplinary syntheses of the literature on international labor migration do not provide a systematic treatment of this defining feature, instead organizing theoretical and empirical contributions by field of study, unit or level of analysis, or theoretical tradition (e.g., Portes & Böröcz, 1989 ; Massey et al., 1993 ; European Asylum Support Office, 2016 ). Such approaches are undoubtedly valuable in their own right. Our decision to organize this discussion by stage allows us to understand this as a process, rather than as a set of discrete events. As a result, we conceptualize international labor migration as three stages or decision points: (a) the decision to migrate or to remain at home, (b) the choice of destination, and (c) the manner by which expatriates re-engage—or choose not to re-engage—with their country of origin once abroad. We also use these decision points to highlight a number of potential new directions for future research in this still-evolving field.

Figure 1. Global migration intentions by educational attainment, 2008–2017.

Should I Stay or Should I Go, Now?

The massive growth in international labor migration in the age of globalization is remarkable, but the fact remains that over 95% of the world’s population never leave their country of origin (United Nations Population Division, 2012 ). Figure 1 shows the percentage of people who expressed an intention to move abroad between 2008 and 2017 by educational attainment, according to data from the Gallup World Poll. Over this time period, it appears that those who were highly educated expressed intent to migrate in greater numbers than those who had less than a college education, although these two groups have converged in recent years. What is most striking, however, is that a vast majority of people, regardless of educational attainment, expressed no desire to move abroad. Even though absolute flows of migrants have grown at a near-exponential rate, relative to their non-migrating counterparts, they remain a small minority. What factors are important in determining who decides to migrate and who decides to remain at home? 2

From Neoclassical Economics to the Mobility Transition

Neoclassical economic models posit that the primary driving factor behind migration is the expected difference in wages (discounted future income streams) between origin and destination countries (Sjaastad, 1962 ; Borjas, 1989 ; Clark, Hatton, & Williamson, 2007 ). All else equal, when the wage gap, minus the costs associated with moving between origin and destination, is high, these models predict large flows of labor migrants. In equilibrium, as more individuals move from origin to destination countries, the wage differential narrows, which in turn leads to zero net migration (Lewis, 1954 ; Harris & Todaro, 1970 ). Traditional models predict a negative monotonic relationship between the wage gap and the number of migrants (e.g., Sjaastad, 1962 ). However, the predictions of neoclassical models are not well supported by the empirical record. Empirical evidence shows that, at least in a cross-section, the relationship between economic development and migration is more akin to an inverted U. For countries with low levels of per capita income, we observe little migration due to a liquidity constraint: at this end of the income distribution, individuals do not have sufficient resources to cover even minor costs associated with moving abroad. Increasing income helps to decrease this constraint, and consequently we observe increased levels of emigration as incomes rise (de Haas, 2007 ). This effect, however, is not monotonic: as countries reach middle-income status, declining wage differentials lead to flattening rates of emigration, and then decreasing rates as countries enter later stages of economic development. 3

Some research explains this curvilinear relationship by focusing on the interaction between emigration incentives and constraints : for example, increased income initially makes migration more affordable (reduces constraints), but also simultaneously reduces the relative economic benefits of migrating as the wage differential narrows (as potential migrants now have the financial capacity to enhance local amenities) (Dao, Docquier, Parsons, & Peri, 2016 ). The theoretical underpinnings of this interaction, however, are not without controversy. Clemens identifies several classes of theory that attempt to explain this curvilinear relationship—a relationship that has been referred to in the literature as the mobility transition (Clemens, 2014 ). These theories include: demographic changes resulting from development that also favor emigration up to a point (Easterlin, 1961 ; Tomaske, 1971 ), the loosening of credit restraints on would-be migrants (Vanderkamp, 1971 ; Hatton & Williamson, 1994 ), a breakdown of information barriers via the building of transnational social networks (Epstein, 2008 ), structural economic changes in the development process that result in worker dislocation (Zelinsky, 1971 ; Massey, 1988 ), the dynamics of economic inequality and relative deprivation (Stark, 1984 ; Stark & Yitzhaki, 1988 ; Stark & Taylor, 1991 ), and changing immigration policies in destination countries toward increasingly wealthy countries (Clemens, 2014 ). While each of these play some role in the mobility transition curve, Dao et al. ( 2016 ) run an empirical horse race between numerous explanations and find that changing skill composition resulting from economic development is the most substantively important driver. Economic development is correlated with an increase in a country’s level of education; an increase in the level of education, in turn, is correlated with increased emigration. However, traditional explanations involving microeconomic drivers such as income, credit constraints, and economic inequality remain important factors (Dao et al., 2016 ). The diversity of explanations offered for the mobility transition curve indicates that while most research agrees the inverted-U relationship is an accurate empirical portrayal of the relationship between development and migration, little theoretical agreement exists on what drives this relationship. Complicating this disagreement is the difficulty of empirically disentangling highly correlated factors such as income, skill composition, and demographic trends in order to identify robust causal relationships.

Political Conditions at the Origin

While there is a scholarly consensus around the mobility transition and the role of economic conditions, emerging research suggests that the political environment in the origin country may also be salient. We do not refer here to forced migration, such as in the case of those who leave because they are fleeing political persecution or violent conflict. Rather, we focus on political conditions in the homeland that influence a potential migrant’s decision to emigrate voluntarily. Interpretations of how, and the extent to which, political conditions in origin countries (independent of economic conditions) influence the decision to migrate have been heavily influenced by Hirschman’s “Exit, Voice, and Loyalty” framework (Hirschman, 1970 , 1978 ). Hirschman argues that the opportunity to exit—to exit a firm, an organization, or a country—places pressure on the local authorities; voting with one’s feet forces organizations to reassess their operations.

When applied to the politics of emigration, Hirschman’s framework generates two different hypotheses. On the one hand, politicians may allow, encourage, or force the emigration of groups that oppose the regime as a political safety valve of sorts. This provides the government with a mechanism with which to manage potential political challengers by encouraging their exit. On the other hand, politicians—especially those in autocracies—may actively work to prevent exit because they fear the emigration of economic elites, the highly skilled, and others who have resources vital to the survival of the regime. 4

A small number of studies investigate how local-level, rather than national, political circumstances affect a potential migrant’s calculus. The limited empirical evidence currently available suggests that local conditions are substantively important determinants of the emigration decision. When individuals are highly satisfied with local amenities such as their own standard of living, quality of public services, and overall sense of physical security, they express far less intention to migrate compared with highly dissatisfied individuals (Dustmann & Okatenko, 2014 ). Furthermore, availability of public transport and access to better education facilities decreases the propensity to express an intention to emigrate (Cazzuffi & Modrego, 2018 ). This relationship holds across all levels of wealth and economic development, and there is some evidence that satisfaction with local amenities matters as much as, or even more than, income or wealth (Dustmann & Okatenko, 2014 ).

Political corruption, on both national and local levels, also has substantively important effects on potential migrants, especially those who are highly skilled. Broadly defined as the use of public office for political gain, political corruption operates as both a direct and an indirect factor promoting emigration. 5 Firstly, corruption may have a direct effect on the desire to emigrate in that it can decrease the political and economic power of an individual, leading to a lower standard of living and poorer quality of life in origin countries. If the reduction in life satisfaction resulting from corruption is sufficiently high—either by itself or in combination with other “push” factors—then the exit option becomes more attractive (Cooray & Schneider, 2016 ). Secondly, corruption also operates through indirect channels that influence other push factors. Given the large literature on how political corruption influences a number of development outcomes, it is conceivable that corruption affects the decision-making process of a potential migrant through its negative effect on social spending, education, and public health (Mo, 2001 ; Mauro, 1998 ; Gupta, Davoodi, & Thigonson, 2001 ).

The combination of its direct and indirect impacts means that corruption could be a significant part of a migrant’s decision-making process. At present there is limited work exploring this question, and the research does not yield a consensus. Some scholars argue that political corruption has no substantive effect on total bilateral migration, but that it does encourage migration among the highly skilled (Dimant, Krieger, & Meierrieks, 2013 ). This is the case, the argument goes, because corruption causes the greatest relative harm to the utility of those who have invested in human capital, who migrate to escape the negative effect on their fixed investment. In contrast, others find that a high level of corruption does increase emigration at the aggregate level (Poprawe, 2015 ). More nuanced arguments take into account the intensity of corruption: low to moderate levels of corruption lead to increased emigration of all groups, and especially of the highly skilled. But at high levels of corruption, emigration begins to decrease, indicating that intense corruption can act as a mobility constraint (Cooray & Schneider, 2016 ). All of these existing accounts, however, employ state-level measures of corruption by non-governmental organizations, such as those produced by Transparency International. Scholars have yet to harness micro-level survey data to explore the influence of personal corruption perception on the individual’s decision-making process.

The Land of Hopes and Dreams

Given that an individual has decided to emigrate, the next decision point is to choose a destination country. Advanced industrial democracies, such as those in the OECD, are major migrant-receiving countries, but so are Russia and several Gulf countries including Saudi Arabia, Qatar, and the United Arab Emirates (World Bank, 2016 ). A country’s constellation of political, economic, and social attributes is crucial to understanding an emigrant’s choice of destination. Potential migrants weigh all of these factors simultaneously when choosing a destination: will the destination allow political rights for the migrant and their children, is access to the labor market possible, and does the destination provide an opportunity for reunification with friends and family? In this section we focus on the non-economic factors that draw migrants to certain countries over others. In addition, we emphasize how skill level adds layers of complexity to a migrant’s calculus.

Political Environment, Both Formal and Informal

As noted earlier, traditional neoclassical models and their extensions place wage differentials and associated economic variables at the heart of a migrant’s choice. Gravity models posit that migrants choose a destination country based on their expected income—which itself is a function of the wage rate and the probability of finding employment in the destination—less the costs associated with moving (Ravenstein, 1885 ; Todaro, 1969 ; Borjas, 1989 ). A rigid focus on economic factors, however, blinds us to the empirical reality that a destination country’s political environment influences what destination a migrant chooses (Borjas, 1989 ). A country’s legal and political rights structure for migrants, as well as its level of tolerance for newcomers, is critical to migrants discriminating between an array of potential destinations. Fitzgerald, Leblang, and Teets ( 2014 ) argue, for example, that states with restrictive citizenship policies and strong radical right anti-immigrant parties will receive fewer migrants, while states with relatively liberal citizenship requirements and weak radical right political movements will receive more migrants. In the rational actor framework, migrants seek countries with hospitable political environments to maximize both their political representation in government and their access to labor market opportunities as a result of citizenship rights and social acceptance (Fitzgerald et al., 2014 ).

Using a broad sample of origin countries and 18 destination countries, they find that relative restrictiveness of citizenship policies and level of domestic support for the radical right are substantively important determinants of global migratory flows. Further, they find that these political variables condition a migrant’s choice of destination: the relative importance of economic factors such as the unemployment rate or the wage differential diminishes as a destination country’s political environment becomes more open for migrants. In other words, when migrants are choosing a destination country, political considerations may trump economic ones—a finding that is an important amendment to the primarily economics-focused calculus of the initial stage of the immigration decision.

However, prior to choosing and entering a destination country, a migrant must also navigate a country’s immigration policy—the regulation of both migrant entry and the rights and status of current migrants. While it is often assumed that a relatively more restrictive immigration policy deters entry, and vice versa, a lack of quantitative data has limited the ability of scholars to confirm this intuition cross-nationally. Money ( 1999 ) emphasizes that the policy output of immigration politics does not necessarily correlate with the outcome of international migrant flows. There are a number of unanswered questions in this field, including: is immigration policy a meaningful determinant of global flows of migration? Do certain kinds of immigration policies matter more than others? How does immigration policy interact with other political and economic factors, such as unemployment and social networks?

Only a handful of studies analyze whether or not immigration policy is a significant determinant of the size and character of migratory flows. Perhaps the most prominent answer to this question is the “gap hypothesis,” which posits that immigration rates continue to increase despite increasingly restrictive immigration policies in advanced countries (Cornelius & Tsuda, 2004 ). Some subsequent work seems to grant support to the gap hypothesis, indicating that immigration policy may not be a relevant factor and that national sovereignty as it relates to dictating migrant inflows has eroded significantly (Sassen, 1996 ; Castles, 2004 ). The gap hypothesis is not without its critics, with other scholars arguing that the existing empirical evidence actually lends it little or no support (Messina, 2007 ).

A more recent body of literature does indicate that immigration policy matters. Brücker and Schröder ( 2011 ), for example, find that immigration policies built to attract highly skilled migrants lead to higher admittance rates. They also show that diffusion processes cause neighboring countries to implement similar policy measures. Ortega and Peri ( 2013 ), in contrast to the gap hypothesis literature, find that restrictive immigration policy indeed reduces migrant inflows. But immigration policy can also have unintended effects on international migration: when entry requirements increase, migrant inflows decrease, but migrant outflows also decrease (Czaika & de Haas, 2016 ). This indicates that restrictive immigration policy may also lead to reduced circular migrant flows and encourage long-term settlement in destination countries.

Disaggregating immigration policy into its different components provides a clearer picture of how immigration policy may matter, and whether certain components matter more than others. Immigration policy is composed of both external and internal regulations. External regulations refer to policies that control migrant entry, such as eligibility requirements for migrants and additional conditions of entry. Internal regulations refer to policies that apply to migrants who have already gained status in the country, such as the security of a migrant’s legal status and the rights they are afforded. Helbling and Leblang ( 2017 ), using a comprehensive data set of bilateral migrant flows and the Immigration Policies in Comparison (IMPIC) data set, find that, in general, external regulations prove slightly more important in understanding migrant inflows (Helbling, Bjerre, Römer, & Zobel, 2017 ). This indicates that potential migrants focus more on how to cross borders, and less on the security of their status and rights once they settle. They do find, however, that both external and internal components of immigration are substantively important to international migrant flows.

The effects of policy, however, cannot be understood in isolation from other drivers of migration. Firstly, poor economic conditions and restrictive immigration policy are mutually reinforcing: when the unemployment rate is elevated, restrictive policies are more effective in deterring migrant flows. An increase in policy effectiveness in poor economic conditions suggests that states care more about deterring immigration when the economy is performing poorly. Secondly, a destination country’s restrictive immigration policy is more effective when migrants come from origin countries that have a common colonial heritage. This suggests that cultural similarities and migrant networks help to spread information about the immigration policy environment in the destination country. Social networks prove to be crucial in determining how much migrants know about the immigration policies of destination countries, regardless of other cultural factors such as colonial heritage or common language (Helbling & Leblang, 2017 ). In summary, more recent work supports the idea that immigration policy of destination countries exerts a significant influence on both the size and character of international migration flows. Much work remains to be done in terms of understanding the nuances of specific immigration policy components, the effect of policy change over time, and through what mechanisms immigration policy operates.

Transnational Social Networks

None of this should be taken to suggest that only political and economic considerations matter when a potential migrant contemplates a potential destination; perhaps one of the biggest contributions to the study of bilateral migration is the role played by transnational social networks. Migrating is a risky undertaking, and to minimize that risk, migrants are more likely to move to destinations where they can “readily tap into networks of co-ethnics” (Fitzgerald et al., 2014 , p. 410). Dense networks of co-ethnics not only help provide information about economic opportunities, but also serve as a social safety net which, in turn, helps decrease the risks associated with migration, including, but not limited to, finding housing and integrating into a new community (Massey, 1988 ; Portes & Böröcz, 1989 ; Portes, 1995 ; Massey et al., 1993 ; Faist, 2000 ; Sassen, 1995 ; Light, Bernard, & Kim, 1999 ). Having a transnational network of family members is quite important to destination choice; if a destination country has an immigration policy that emphasizes family reunification, migrants can use their familial connections to gain economically valuable permanent resident or citizenship status more easily than in other countries (Massey et al., 1993 , p. 450; Helbing & Leblang, 2017 ). When the migrant is comparing potential destinations, countries in which that migrant has a strong social network will be heavily favored in a cost–benefit analysis.

Note, however, that even outside of a strict rational actor framework with perfect information, transnational social networks still may be quite salient to destination choice. An interesting alternative hypothesis for the patterns we observe draws on theories from financial market behavior which focus on herding. Migrants choosing a destination observe the decisions of their co-ethnics who previously migrated and assume that those decisions were based on a relevant set of information, such as job opportunities or social tolerance of migrants. New migrants then choose the same destination as their co-ethnics not based on actual exchanges of valuable information, but based solely on the assumption that previous migration decisions were based on rational calculation (Epstein & Gang, 2006 ; Epstein, 2008 ). This is a classic example of herding, and the existing empirical evidence on the importance of transnational social networks cannot invalidate this alternative hypothesis. One could also explain social network effects through the lens of cumulative causation or feedback loops: the initial existence of connections in destination countries makes the act of migration less risky and attracts additional co-ethnics. This further expands migrant networks in a destination, further decreasing risk for future waves of migrants, and so on (Massey, 1990 ; Fussel & Massey, 2004 ; Fussel, 2010 ).

No matter the pathway by which social networks operate, the empirical evidence indicates that they are one of the most important determinants of destination choice. Potential migrants from Mexico, for example, who are able to tap into existing networks in the United States face lower direct, opportunity, and psychological costs of international migration (Massey & Garcia España, 1987 ). This same relationship holds in the European context; a study of Bulgarian and Italian migrants indicates that those with “social capital” in a destination community are more likely to migrate and to choose that particular destination (Haug, 2008 ). Studies that are more broadly cross-national in nature also confirm the social network hypothesis across a range of contexts and time periods (e.g., Clark et al., 2007 ; Hatton & Williamson, 2011 ; Fitzgerald et al., 2014 ).

Despite the importance of social networks, it is, again, important to qualify their role in framing the choice of destinations. It seems that the existence of co-ethnics in destination countries most strongly influences emigration when they are relatively few in number. Clark et al. ( 2007 ), in their study of migration to the United States, find that the “friends and relatives effect” falls to zero once the migrant stock in the United States reaches 8.3% of the source-country population. In addition, social networks alone cannot explain destination choice because their explanatory power is context-dependent. For instance, restrictive immigration policies limiting legal migration channels and family reunification may dampen the effectiveness of networks (Böcker, 1994 ; Collyer, 2006 ). Social networks are not an independent force, but also interact with economic and political realities to produce the global migration patterns we observe.

The Lens of Skill

For ease of presentation, we have up to now treated migrants as a relatively homogeneous group that faces similar push and pull factors throughout the decision-making process. Of course, not all migrants experience the same economic, political, and social incentives in the same way at each stage of the decision-making process. Perhaps the most salient differentiating feature of migrants is skill or education level. Generally, one can discuss a spectrum of skill and education level for current migrants, from relatively less educated (having attained a high school degree or less) to relatively more educated (having attained a college or post-graduate degree). The factors presented here that influence destination choice interact with a migrant’s skill level to produce differing destination choice patterns.

A migrant’s level of education, or human capital, often serves as a filter for the political treatment he or she anticipates in a particular destination country. For instance, the American public has a favorable view of highly educated migrants who hold higher-status jobs, while simultaneously having an opposite view of migrants who have less job training and do not hold a college degree (Hainmueller & Hiscox, 2010 ; Hainmueller & Hopkins, 2015 ). Indeed, the political discourse surrounding migration often emphasizes skill level and education as markers of migrants who “should be” admitted, across both countries and the ideological spectrum. 6 While political tolerance may be a condition of entry for migrants in the aggregate, the relatively privileged status of highly educated and skilled migrants in most destination countries may mean that this condition is not as salient.

While it is still an open question to what extent immigration policy influences international migration, it is clear that not all migrants face evenly applied migration restrictions. Most attractive destination countries have policies that explicitly favor highly skilled migrants, since these individuals often fill labor shortages in advanced industries such as high technology and applied science. Countries such as Australia, Canada, and New Zealand all employ so-called “points-based” immigration systems in which those with advanced degrees and needed skills are institutionally favored for legal entry (Papademetriou & Sumption, 2011 ). Meanwhile, the United States maintains the H-1B visa program, which is restricted by educational attainment and can only be used to fill jobs in which no native talent is available (USCIS). Even if destination countries decide to adopt more restrictive immigration policies, the move toward restriction has typically been focused on low-skilled migrants (Peters, 2017 ). In other words, even if immigration policy worldwide becomes more restrictive, this will almost certainly not occur at the expense of highly skilled migrants and will not prevent them choosing their most preferred destination.

Bring It on Home to Me

This article began by asserting that international labor migration is an important piece of globalization, as significant as cross-border flows of capital, goods, and services. This section argues that migrant flows enhance flows of capital and commodities. Uniquely modern conditions such as advanced telecommunications, affordable and efficient international travel, and the liberalization of financial flows mean that diasporas—populations of migrants living outside their countries of origin—and home countries often re-engage with each other (Vertovec, 2004 ; Waldinger, 2008 ). This section reviews some of the newest and most thought-provoking research on international labor migration, research that explores diaspora re-engagement and how that re-engagement alters international flows of income, portfolio and foreign direct investment (FDI), trade, and migratory flows themselves.

Remittances

As previously argued, migration is often driven by the prospect of higher wages. Rational, utility-maximizing migrants incur the cost of migration in order to earn increased income that they could not earn at home. But when migrants obtain higher wages, this additional increment to income is not always designated for individual consumption. Often, migrants use their new income to send remittances, direct transfers of money from one individual to another across national borders. Once a marginal financial flow, in 2015 remittances totaled $431 billion, far outpacing foreign aid ($135 billion) and nearly passing private debt and portfolio equity ($443 billion). More than 70% of total global remittances flow into developing countries (World Bank, 2016 ). In comparison with other financial flows such as portfolio investment and FDI, remittances are more impervious to economic crises, suggesting that they may be a countercyclical force to global downturns (Leblang, 2017 ).

Remittances represent one of the most common ways in which migrants re-engage with their homeland and alter both global income flows and distribution. Why do migrants surrender large portions of their new income, supposedly the very reason they migrated in the first place, to their families back home? New economics of labor migration (NELM) theory argues that immigration itself is motivated by a family’s need or demand for remittances—that remittances are an integral part of a family’s strategy for diversifying household financial risk (Stark & Bloom, 1985 ). Remittances “are a manifestation of informal contractual agreements between migrants and the households from which they move,” indicating that remitting is not an individual-level or purely altruistic action but rather occurs in a larger social context, that of one’s immediate or extended family (European Asylum Support Office, 2016 , p. 15).

The impact of migrant remittances on countries of origin is multifaceted yet somewhat ambiguous. Most scholarly work focuses on whether remittances positively or negatively influence existing economic conditions. A number of studies find that remittances modestly reduce poverty levels in developing countries (Adams & Page, 2005 ; Yang & Martinez, 2006 ; Acosta, Calderon, Fajnzybler, & Lopez, 2008 ; Lokshin, Bontch-Osmolovski, & Glinskaya, 2010 ). On other measures of economic well-being, such as growth, inequality, and health, the literature is quite mixed and no definitive conclusions can be drawn. For instance, some studies find that remittances encourage investment in human capital (Yang, 2008 ; Adams & Cuecuecha, 2010 ), while others find no such effect and suggest that families typically spend remittances on non-productive consumption goods (Chami, Fullenkamp, & Jahjah, 2003 ). Here we can only scratch the surface of the empirical work on remittances and economic outcomes. 7

Some of the most recent research in the field argues that remittances have a distinct political dimension, affecting regime support in developing countries and altering the conditions in which elections are held. Ahmed ( 2012 ), grouping remittances with foreign aid, argues that increased remittances allow autocratic governments to extend their tenure in office. These governments can strategically channel unearned government and household income to finance political patronage networks, which leads to a reduced likelihood of autocratic turnover, regime collapse, and mass protests against the regime. More recent research posits nearly the exact opposite: remittances are linked to a greater likelihood of democratization under autocratic regimes. Escriba-Folch, Meseguer, and Wright ( 2015 ) argue that since remittances directly increase household incomes, they reduce voter reliance on political patronage networks, undermining a key tool of autocratic stability.

Remittances may also play an important role in countries with democratic institutions, yet more research is needed to fully understand the conditions under which they matter and their substantive impact. Particularly, remittances may alter the dynamics of an election as an additional and external financial flow. There is evidence of political remittance cycles : the value of remittances spikes in the run-up to elections in developing countries. The total value of remittances to the average developing country increases by 6.6% during election years, and by 12% in elections in which no incumbent or named successor is running (O’Mahony, 2012 ). The effect is even larger in the poorest of developing countries. Finer-grained tests of this hypothesis provide additional support: using monthly and quarterly data confirms the existence of political remittance cycles, as well as using subnational rather than cross-national data (Nyblade & O’Mahony, 2014 ). However, these studies do not reveal why remittances spike, or what the effects of that spike are on electoral outcomes such as vote share, campaign financing, and political strategy.

Remittances represent a massive international financial flow that warrants more scholarly attention. While there are numerous studies on the relationship between remittances and key economic indicators, there remains much room for further work on their relationship to political outcomes in developing countries. Do remittances hasten the downfall of autocratic regimes, or do they contribute to autocratic stability? In democratic contexts, do remittances substantively influence electoral outcomes, and if so, which outcomes and how? Finally, do remittances prevent even more migration because they allow one “breadwinner from abroad” to provide for the household that remains in the homeland? While data limitations are formidable, these questions are important to the study of both international and comparative political economy.

Bilateral Trade

The argument that migrant or co-ethnic networks play an important role in international economic exchange is not novel. Greif ( 1989 , 1993 ) illustrates the role that the Maghrebi traders of the 11th century played in providing informal institutional guarantees that facilitated trade. This is but a single example. Cowen’s historical survey identifies not only the Phoenicians but also the “Spanish Jews [who] were indispensable for international commerce in the Middle Ages. The Armenians controlled the overland route between the Orient and Europe as late as the nineteenth century . Lebanese Christians developed trade between the various parts of the Ottoman empire” (Cowen, 1997 , p. 170). Rauch and Trindade ( 2002 ) provide robust empirical evidence linking the Chinese diaspora to patterns of imports and exports with their home country.

A variety of case studies document the importance of migrant networks in helping overcome problems of information asymmetries. In his study of Indian expatriates residing in the United States, Kapur ( 2014 ) documents how that community provides U.S. investors with a signal of the work ethic, labor quality, and business culture that exists in India. Likewise, Weidenbaum and Hughes ( 1996 ) chronicle the Bamboo Network—the linkages between ethnic Chinese living outside mainland China and their homeland—and how these linkages provide superior access to information and opportunities for investment.

Connections between migrant communities across countries affect cross-national investment even when these connections do not provide information about investment opportunities. In his work on the Maghrebi traders of the 11th century , Greif argues that this trading network was effective because it was able to credibly threaten collective punishment by all merchants if even one of them defected (Greif, 1989 , 1993 ). Grief shows that this co-ethnic network was able to share information regarding the past actions of actors (they could communicate a reputation)—something that was essential for the efficient functioning of markets in the absence of formal legal rules. Weidenbaum and Hughes reach a similar conclusion about the effectiveness of the Bamboo Network, remarking that “if a business owner violates an agreement, he is blacklisted. This is far worse than being sued, because the entire Chinese networks will refrain from doing business with the guilty party” (Hughes, 1996 , p. 51).

Migrants not only alter the flow of income by remitting to their countries of origin, but also influence patterns of international portfolio investment and FDI. Most existing literature on international capital allocation emphasizes monadic factors such as the importance of credible commitments and state institutional quality, failing to address explicitly dyadic phenomena that may also drive investment. Diaspora networks, in particular, facilitate cross-border investment in a number of ways. They foster a higher degree of familiarity between home and host countries, leading to a greater preference for investment in specific countries. Diaspora networks can also decrease information asymmetries in highly uncertain international capital markets in two ways. Firstly, they can provide investors with salient information about their homeland, such as consumer tastes, that can influence investment decision-making. Secondly, they can share knowledge about investment opportunities, regulation and procedures, and customs that decrease transaction costs associated with cross-border investment (Leblang, 2010 ). This place of importance for migrants suggests to the broader international political economy literature the importance of non-institutional mechanisms for channeling economic activity.

Although the hypothesized link between migrants and international investment has only recently been identified, the quantitative evidence available supports that hypothesis. Leblang ( 2010 ), using dyadic cross-sectional data, finds that diaspora networks “have both a substantively significant effect and a statistically significant effect on cross-border investment,” including international portfolio investment and FDI (p. 584). The effect of bilateral migratory flows correlates positively with the degree of information asymmetry: when informational imperfections are more pervasive in a dyad, migrants (especially the highly skilled) play a disproportionately large role in international capital allocation (Kugler, Levinthal, & Rapoport, 2017 ). Other quantitative studies find substantively similar results for FDI alone (e.g., Javorcik, Özden, Spatareanu, & Neagu, 2011 ; Aubry, Rapoport, & Reshef, 2016 ).

Many questions still remain unanswered. Firstly, does the effect of migrants on investment follow the waves of the global economy, or is it countercyclical as remittances have been shown to be? Secondly, how does this additional investment, facilitated by migrants, affect socioeconomic outcomes such as inequality, poverty, and economic development (Leblang, 2010 )? Does the participation of migrants lead to more successful FDI projects in developing countries because of their ability to break down information barriers? Within portfolio investment, do migrants lead to a preference for certain asset classes over others, and if so, what are the effects on bilateral and international capital markets? These are just a few directions in an area ripe for additional research.

Return Migration and Dual Citizenship

Besides financial flows, migrants themselves directly contribute to global flows of capital by returning to their countries of origin in large numbers. This phenomenon of return migration—or circular migration—can come in a few temporal forms, including long-term migration followed by a permanent return to a country of origin, or repeat migration in which a migrant regularly moves between destination and origin countries (Dumont & Spielvogel, 2008 ). While comparable data on return migration is scarce, some reports suggest that 20% to 50% of all immigrants leave their destination country within five years after their arrival (e.g., Borjas & Bratsberg, 1996 ; Aydemir & Robinson, 2008 ; Bratsberg, Raaum, & Sørlie, 2007 ; Dustmann & Weiss, 2007 ). An independent theoretical and empirical account of return migration does not yet exist in the literature and is beyond the scope of this paper. But in the rational actor framework, motivations to return home include a failure to realize the expected benefits of migration, changing preferences toward a migrant’s home country, achievement of a savings or other economic goal, or the opening of additional employment opportunities back home due to newly acquired experience or greater levels of economic development (Dumont & Spielvogel, 2008 ).

While most migration literature treats the country of origin as a passive actor that only provides the conditions for migration, new literature on return migration gives home country policies pride of place. Origin countries can craft policies that encourage diaspora re-engagement, incentivizing individuals to return home. Dual citizenship, for example, is an extension of extraterritorial rights, allowing migrants to retain full legal status in their home country. Dual citizenship “decreases the transaction costs associated with entering a host country’s labor market and makes it easier for migrants to return home” (Leblang, 2017 , p. 77). This leads migrants to invest their financial resources in the form of remittances back home as well as their valuable human capital. When states provide such extraterritorial rights, expatriates are 10% more likely to remit and 3% more likely to return home. Dual citizenship is also associated with a doubling of the dollar amount of remittances received by a home country (Leblang, 2017 ). These striking results suggest that in addition to the power of migrants to affect cross-border flows of money and people, countries of origin can also play a significant role.

Conclusion and Future Directions

This brief article has attempted to synthesize a broad range of literature from political science, economics, sociology, migration studies, and more to construct an account of international labor migration. To do so, the migratory process was broken down into distinct stages and decision points, focusing particularly on the decision to migrate, destination choice, and the re-engagement of migrants with their homeland. In doing so, the article also discussed the interlinkages of international migration with other fields of study in international political economy, including cross-border financial flows, trade, and investment. Through a multiplicity of approaches, we have gained a greater understanding of why people decide to move, why they decide to move to one country over another, and how and why they engage with the global economy and their homeland. Despite this intellectual progress, there remain many paths for future research at each stage of the migratory process; we highlight just a few of them here.

We know that income differentials, social ties, and local political conditions are important variables influencing the migration process. Yet the question remains: why do a small but growing number of people choose to leave while the overwhelming majority of people remain in their country of birth? Here, individual- or family-level subjective characteristics may be significant. There are a handful of observational studies that explore the relationship between subjective well-being or life satisfaction and the intention to migrate, with the nascent consensus being that life dissatisfaction increases the intention to migrate (Cai, Esipova, Oppenheimer, & Feng, 2014 ; Otrachshenko & Popova, 2014 ; Nikolova & Graham, 2015 ). But more research on intrinsic or subjective measures is needed to understand (a) their independent importance more fully and (b) how they interact with objective economic, political, and social factors. For instance, do those who are more optimistic migrate in larger numbers? Do minority individuals who feel they live in an environment in which diversity is not accepted feel a greater urge to leave home? Synthesizing these types of subjective variables and perceptions with the more prominent gravity-style models could result in a more complete picture of the international migration process.

For the “typical” migrant, one who is relatively less educated than the population in the chosen destination and does not have specialized skills, social networks are key to minimizing the risk of migrating and quickly tapping into economic opportunities in destination countries. Does this remain true for those who are highly educated? Although little empirical research exists on the topic, greater human capital and often-accompanying financial resources may operate as a substitute for the advantages offered by social networks, such as housing, overcoming linguistic barriers, and finding gainful employment. This would indicate that the “friends and family effect” is not as influential for this subset of migrants. Economic considerations, such as which destination offers the largest relative wage differential, or political considerations, such as the ease of quickly acquiring full citizenship rights, may matter more for the highly skilled. Neoclassical economic models of migration may best capture the behavior of migrants who hold human capital and who have the financial resources to independently migrate in a way that maximizes income or utility more broadly.

Since we have focused on international migration as a series of discrete decision points in this article, we have perhaps underemphasized the complexity of the physical migration process. In reality, migrants often do not pick a country and travel directly there, but travel through (perhaps several) countries of transit such as Mexico, Morocco, or Turkey along the way (Angel Castillo, 2006 ; Natter, 2013 ; Icduygu, 2005 ). There is little existing theoretical work to understand the role of transit countries in the migratory process, with much of it focusing on the potential for cooperation between destination and transit countries in managing primarily illegal immigration (Kahana & Lecker, 2005 ; Djajic & Michael, 2014 ; Djajic & Michael, 2016 ). Another related strand of the literature focuses on how wealthy destination countries are “externalizing” their immigration policy, encompassing a broader part of the migratory process than simply crossing a physically demarcated border (Duvell, 2012 ; Menjivar, 2014 ). But many questions remain, such as the following: how do we understand those who desire to enter, say, the United States, but instead relocate permanently to Mexico along the way? How do countries of transit handle the pressure of transit migrants, and how does this affect economic and political outcomes in these countries?

Finally, the focus of nearly all literature on international migration (and this article as a byproduct) implicitly views advanced economies as the only prominent destinations. However, this belies the fact that 38% of all migration stays within the “Global South” (World Bank, 2016 ). While there is certainly some literature on this phenomenon (see Ratha & Shaw, 2007 ; Gindling, 2009 ; Hujo & Piper, 2007 ), international political economy scholars have yet to sufficiently tackle this topic. The overarching research question here is: do the same push and pull factors that influence the decision to migrate and destination choice apply to those who migrate within the Global South? Do we need to construct new theories of international migration with less emphasis on factors such as wage differentials and political tolerance, or are these sufficient to understand this facet of the phenomenon? If we fail to answer these questions, we may miss explaining a significant proportion of international migration with its own consequences and policy implications.

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1. Our use of the term international labor migration follows academic and legal conventions; we use the term migration to refer to the voluntary movement of people across national borders, either in a temporary or permanent fashion. This excludes any discussion of refugees, asylum seekers, or any other groups that are forced to migrate.

2. We do not have space in this article to delve into the theoretical and empirical work unpacking the effect of demographic characteristics—age, gender, marital status, household size, and so forth on the migration decision and on subsequent flows of migrants. For comprehensive reviews, see Lichter ( 1983 ), Morrison and Lichter ( 1988 ); United Nations Population Division ( 2013 ); and Zaiceva and Zimmerman ( 2014 ).

3. Zelinsky ( 1971 ) originally identified this relationship and termed it mobility transition curve . A wealth of empirical work supports Zelinsky’s descriptive theory in a number of contexts (see Akerman, 1976 ; Gould, 1979 ; Hatton & Williamson, 1994 ; and Dao et al., 2016 ).

4. For a review of the arguments as well as some empirical tests, see Miller and Peters ( 2018 ) and Docquier, Lodigiani, Rapoport, and Schiff ( 2018 ).

5. Transparency International. “What is corruption?”

6. For example, former United Kingdom Independence Party leader Nigel Farage has called for the United Kingdom to adopt an immigration system that only allows in highly skilled migrants (“UKIP launches immigration policy”). In 2014, US President Barack Obama emphasized that he wanted to attract international students to American universities and that they “create jobs, businesses, and industries right here in America” (USA Today: “Full text: Obama’s immigration speech”). A key issue in Germany’s 2018 government formation was the creation of skill-based migration laws (Severin & Martin, 2018 ).

7. For a more comprehensive review, see Rapoport and Docquier ( 2006 ); and Adams ( 2011 ).

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Since 2000, IOM has been producing its flagship world migration reports every two years. The World Migration  Report 2024 , the twelfth in the world migration report series, has been produced to contribute to increased understanding of migration and mobility throughout the world. This new edition presents key data and information on migration as well as thematic chapters on highly topical migration issues, and is structured to focus on two key contributions for readers: Part I: key information on migration and migrants (including migration-related statistics); and Part II: balanced, evidence-based analysis of complex and emerging migration issues.

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Trends and Patterns of Global Refugee Migration

This paper studies long‐term trends and patterns in global refugee migration. We explore the intensity, spread, and distance of refugee migration at a global, regional, and country level between 1951 and 2018. The analysis did not detect a long‐term increase in the global intensity of refugee migration. Primarily depending on levels of conflict, refugee numbers have fluctuated at levels of between 0.1 and 0.3 percent of the world population. Apparent increases in numbers of the globally displaced are driven by the inclusion of populations and countries that were previously excluded from the data. While refugee populations continue to be concentrated in countries with low‐to‐medium income levels, the analysis reveals several geographic shifts in refugee migration. Refugees tend to come from a shrinking number of origin countries and move to an increasing variety of destination countries. This trend seems to reflect a concentration of recurrent conflict cycles in a relatively small number of countries and a parallel increase in the number of safe destinations. Although the vast majority of refugees remain near to origin countries, the average distance between origin and destination countries has increased over time, presumably linked to the greater ease of travel and migration‐facilitating networks.

Introduction

Refugee migration is at the center of political debates and has been the subject of an expanding body of academic research. Most research focuses on the movement of particular refugee populations, generally as a consequence of the outbreak of violent conflicts in various parts of the world. Few studies investigate the long‐term trends and patterns of refugee migration (see Marfleet 2007 ). Because the study of refugee migration tends to be highly policy driven (Black 2001 ; Bakewell 2008 ), most studies focus on pressing issues such as refugee reception and support, the geographies of recent refugee migrations, or immediate responses to specific refugee urgencies. This bias toward the “present” often obstructs the analysis of longer‐term trends of refugee migration as well as the factors explaining structural changes in these trends. Moreover, because of its more‐limited coverage in terms of years or its focus on asylum flows to Western countries, prior research has been insufficiently able to provide a more long‐term, global perspective.

To fill this gap, this paper makes a comprehensive analysis of trends and patterns of global refugee migration between 1951 and 2018. Drawing on the UN High Commissioner for Refugees (UNHCR) Population Statistics Database, its aim is to provide a global analysis of long‐term post‐WWII trends and patterns in terms of the intensity, geographic reach, and regional orientation of refugees migration. As such, this paper also goes beyond the usual focus on the number of refugees by studying how geographic patterns of refugee migration in terms of countries and regions of origin and destination have been changing. Such an analysis can help us to improve our understanding of the factors that could explain changing patterns of refugee migration. The UNHCR database covers refugee stocks —that is the number of refugees that are present in a country or region at a certain moment in time—and is therefore not suitable for studying short‐term refugee migration or circular flows. Yet “stock” data are used to assess long‐term refugee trends, which reflects the focus of this paper.

Although this study will refer to internally displaced persons or “IDPs” 1 where relevant, the focus is on international refugees. 2 The main reason for this is the limited availability of reliable long‐term data on IDPs. Although IDP statistics exist from 1969 onward (Schmeidl and Jenkins 1999 , 2003 ), the data are less “systemized” than refugee statistics, in the sense that national governments are responsible for the reporting (Schmeidl 2000 ). Many IDPs move unrecorded within the boundaries of their nation‐states, which makes the coverage of IDP statistics generally less reliable than that of refugee statistics. Second, the focus on international refugees is warranted because of this study's focus on macrolevel, global shifts in the distribution of refugee populations.

The analysis in this paper builds on prior research that has given a number of valuable insights into the trends and drivers of refugee migration. First, earlier studies have shown that the scale of refugee migration has fluctuated considerably since the mid‐twentieth century (see Gatrell 2013 ; FitzGerald and Arar 2018 ) and that the vast majority of refugees in the world stay close to their countries of origin in what is often referred to as the “Global South” (see Puerto Gomez et al. 2010 ). Most people fleeing civil war and human rights abuse are either forcibly displaced within their own country or seek refuge in a country nearby (Hatton 2020 ). In 2017, for instance, about 80 percent of refugees worldwide resided in countries neighboring their origin country and 85 percent were in developing countries (UNCHR 2018 ). This seems to challenge the idea of refugees traveling greater distances; but, thus far, there has been no evidence of the evolution of these patterns over time.

Second, prior research indicates that fluctuations in refugee numbers are primarily determined by levels of conflict, oppression, and political stability in origin countries (Schmeidl 1997 , 2001 ; Neumayer 2005 ; Moore and Shellman 2007 ). Hatton ( 2020 ) argued that the most important origin‐country variables determining asylum flow to Western countries are political terror and the lack of civil liberties; civil war seems to matter less, perhaps because war per se does not necessarily confer refugee status (see Hatton 2009 , 2017 , 2020 ). Conflict also affects people's resources and livelihood opportunities and can have a destructive effect on the physical and economic infrastructure of countries, factors which may also prompt people to leave (Lindley 2010 ). In that sense, the socioeconomic context of the origin country, deteriorated by conflict, also plays a role in driving refugee migration.

Prior research has refuted the idea that refugee migration is, to any significant degree, directly driven by socioeconomic factors in destination countries. This is quite different from processes of labor migration, which tend to be primarily driven by destination‐country labor demand and recruitment (Piore 1979 ; Mayda 2010 ; Ortega and Peri 2013 ; Ambrosini 2016 ; de Haas et al. 2019 ). Such factors were found to play a relatively minor role in asylum migration to Western countries (Hatton 2020 ). This resonates with a statistical study on global refugee destinations by Moore and Shellman ( 2007 ), which showed that economic opportunities as well as political freedom in destination countries played a minor role in destination choices for refugees. They argued that “Instead of responding to greater wage opportunities and institutional democracy, people go where others have gone before them, usually crossing a nearby border” (Moore and Shellman, 2007, 831).

What does play a more significant role in destination choice, as with other forms of migration, is the location of family and community members already living abroad, with new refugees often following the beaten track (Lindley 2010 ; de Haas, Miller, and Castles 2020 ; Müller‐Funk 2019 ). The most powerful variable determining the destination choice of asylum‐seekers is the population of previous migrants from the same origin country (Hatton 2020 ). The geographic distance between origin and destination countries has a strongly negative effect on the number of asylum applications, reflecting the greater costs and hazards associated with refugee migration (Hatton 2020 ). Another important factor in destination choice is access to resources. Generally, the socioeconomic background of forced migrants determines “routes taken, means of migration and destinations reached” (Van Hear 2006 , 125) and, as such, those who flee from low‐income countries often have little influence on the destination choice. Fransen, Vargas‐Silva, and Siegel ( 2018 ) described how Burundians living close to the border crossed it on foot when conflict erupted, whereas those who lived farther from the border became internally displaced. These findings corroborate the common observation that the vast majority of refugees tend to stay in neighboring countries. Apart from reasons such as cultural familiarity and social proximity, a lack of resources enabling refugees to travel farther and pay intermediaries or smugglers to reach more faraway destinations is an important explanatory factor (see also Müller‐Funk 2019 ).

For governments of destination countries, the greater degree of social identification with refugee populations from neighboring countries often makes it more difficult to close the borders and to prevent citizens from helping coethnic and coreligious people to cross them. Sometimes, nearby states welcome refugees from neighboring countries (at least initially) for various political, diplomatic, and economic reasons. For instance, in response to the influx of asylum seekers—mainly from Syria—to Europe in 2015 and 2016, Jordan leveraged its refugee‐hosting capacity in order to negotiate financial and other support from wealthy states in the “Global North” (Arar 2017 ), while Turkey was also able to use the presence of millions of Syrian refugees to its economic and diplomatic advantage (İçduygu and Üstübici 2014 ).

Asylum policies in destination countries often do matter but are generally of secondary importance in determining destination choice. For instance, in a statistical study on the determinants of refugee migration for 19 Western destination countries, Hatton ( 2009 ) found that the tightening of asylum policies between 2001 and 2006 reduced the number of asylum applications but that the policy restrictions only accounted for about a third of the decline in applications (Hatton 2009 , 183). Analyses using quantified policy indexes show that border controls and restrictive asylum policies have a significant deterrent effect while welfare policies do not (Hatton 2004 , 2009 , 2017 ). Hatton ( 2020 ) argued that the 2016 agreement between the European Union and Turkey showed that arrivals of asylum seekers can be curbed drastically only through the application of draconian policies and in close cooperation with “transit” countries. There is also evidence that restrictive immigration policies can push prospective asylum seekers into an undocumented status (Czaika and Hobolth 2016 ) or re‐route migration to other destinations.

A new age of refugee migration?

Public discourse and scholarly analysis have recently suggested that levels and patterns of refugee migration have undergone quantitative and qualitative changes. Since 2010, refugee numbers seem to have surged and refugees are increasingly applying for asylum in Western countries. Governments and international organizations have regularly claimed that refugee numbers are increasing rapidly. In 2020, UNHCR reported that the global displaced population is “at a record high” with almost 80 million individuals (refugees, IDPs, and asylum seekers) being forcefully displaced by the end of 2019. It also claimed that the number of refugees (26 million) is “the highest ever seen.” 3 Such alarmist statements tend to be replicated by other international organizations, 4 are amplified by mass media, and have therefore fueled a certain perception that the world has entered a new age of refugee migration, characterized by intensified refugee movement as a result of conflict, oppression, and climate change and various forms of environmental havoc. Refugee movements as a result of “disasters” have been described as “one of the biggest humanitarian challenges of the 21st century.” 5

A related idea is that globalization—the growing interconnectedness of the world—has boosted the refugee movement. With falling costs of communication and travel, more and more refugees would find ways to flee their homelands to reach a wider variety of increasingly distant destinations, allegedly increasing pressure on Western asylum systems. Recent increases in refugee movements from countries such as Syria to Europe and from Central America to the United States seem to confirm this impression. For instance, Brell, Dustmann, and Preston ( 2020 , 30) argued that “In coming years, the outflow of refugees from poorer regions of the world seems likely to continue undiminished, given the continued political fragility of populous and growing countries from which migration to safer locations is increasingly easy.”

Hatton ( 2020 ) suggested that increasing numbers of asylum applications in the Western world should be understood against the background of the evolution of international policy—such as the growing international alignment with the 1951 UN Refugee Convention and the EU's Common European Asylum System—which would have “provided clear incentives for spontaneous migration from poor, strife‐prone countries to the developed world” (2020, 91). Increasing asylum applications in Western countries would also be fueled by the growth of transit routes and migrant networks (Hatton 2020 ; see also Capps et al. 2019 ).

However, there are reasons to question the validity of these claims as well as the extent to which the extrapolation of recent trends into the future is warranted. First of all, the recent increase in refugee arrivals in Europe and North America may reflect the simple fact that conflicts such as in Syria and Central America have occurred in geographic proximity to Western destinations. We should therefore not jump to the conclusion that this is part of some long‐term trend without properly investigating it first.

Second, a general analysis of long‐term trends in population mobility by Czaika and de Haas ( 2015 ) has questioned the idea that international migration has accelerated as a consequence of globalization. The authors found that, while, since WWII, the overall intensity of global migration had remained stable at levels of around 3 percent of the world population, the main changes in global migration were in terms of the geographic direction of migration flows. This is particularly seen in the demise both of Europe as a global source of settlers and migrants and South America as a global migration destination, as well as the emergence of Europe and the Middle East as new global migration destinations. Migrants from an increasingly diverse array of Asian, Latin American, and African countries have been increasingly concentrating in a small and shrinking pool of prime destination countries. Czaika and de Haas, therefore, concluded that the global migration map has become more skewed—with more countries converting from net immigration into net emigration countries—and that this reflects the asymmetric nature of globalization processes. This finding defies simplistic reasonings according to which globalization, in combination with global inequalities, would automatically result in intensified population movements. In line with this, the same study found that, between 1960 and 2000, the average distance traveled between origin and destination countries only increased modestly, from 3,000 to 3,700 km.

Although this analysis included all forms of migration—refugee‐ and nonrefugee‐related—it justifies a critical examination of the assumptions that “globalization” is leading to increasing refugee migration and that there is a structurally growing trend in the proportion of asylum seekers reaching Western countries. Such claims cannot be taken for granted and may, in fact, reflect a Western‐centric (research) bias—according to which most refugees and other migrants want to move to Western countries—and an unfounded extrapolation of recent events into the future. This gives reason to hypothesize that, in line with global migration trends, the main changes in refugee migration have been directional—geographic rather than in terms of intensity and distance. Civil wars are increasingly concentrated in a relatively small number of lower income countries that experience recurrent cycles of war (Blattman and Miguel 2010 ). Afghanistan, Burundi, and Sudan are notable examples of countries engulfed in this “conflict trap” (Collier and Sambanis 2002 ). From this, we can hypothesize that refugees increasingly originate from a small number of relatively poorer countries that are involved in protracted conflicts. However, the recent occurrence of conflicts in Libya, Syria, and Venezuela exemplifies the fact that civil conflicts are not unique to low‐income countries.

The perception of an increasing trend in refugee numbers may also have been influenced by the use of the post‐1951 period as a benchmark for our numerical analyses on refugee migration. This was the year in which the 1951 Convention Relating to the Status of Refugees was signed, which prescribes the rights and obligations of refugees and provides a formal definition of a refugee. 6 As a consequence of the convention, data collection on this type of migration was initiated by UNHCR and systemized over time. The absence of refugees as an internationally recognized legal category before 1951 explains the absence of systematic data on them from earlier periods. Yet only a cursory glance at historical sources is enough to show that large‐scale refugee movements are certainly not a new phenomenon (see Marrus 1985 , 2002 ; Skran 1995 ; Zolberg 1983 ; Zolberg, Suhrke, and Aguayo 1989 ; and Gatrell 2013 for historical overviews). Zolberg ( 1983 ), for example, describes how early‐modern state formation in Western Europe between the late‐fifteenth and the late‐seventeenth centuries led to various population displacements, totaling at least one million people. During World War I (1914–1918) an estimated 10 million Europeans were displaced, either internally or internationally (Gatrell 2007 , 2008 , 2013 ). Combined with the aftermath of the Balkan War (1912–1913), an estimated 12 million people were displaced after World War I (Gatrell 2013 ).

The Russian Revolution (1917–1920) prompted the displacement of 1 million people (Gatrell 2013 ). The Greek–Turkish War (1919–1922) displaced approximately 1.5 million people, while an estimated 465,000 Spanish refugees fled to France during the Spanish Civil War (1936–1939). The Second Sino‐Japanese War between China and Japan (1937–1945) led to the estimated displacement of 60–95 million people (MacKinnon 2008 ; Muscolino 2010 ). An estimated 3–10 million people were killed as a consequence of Japanese aggression in Asia between 1931 and 1945 (Rummel 1998 ) and approximately 60 million Europeans were displaced during World War II (Proudfoot 1956 ). The Holocaust involved the systematic persecution, deportation, and murder of around 6 million European Jews by the Nazi regime (de Haas, Miller, and Castles 2020 ).

In the aftermath of World War II, the global displaced population had risen to 175 million—approximately 8 percent of the world population at the time and much higher than current levels even by absolute, let alone relative, numbers. The end of World War II witnessed the mass population movements in Europe of Holocaust survivors, displaced persons, and ethnic groups, such as the approximately 12 million ethnic Germans expelled as part of ethnic cleansing policies in Eastern Europe (Ther 1996 ). Postcolonial processes of state formation also reinforced displacement. In 1947, for example, when India and Pakistan gained independence from Britain, between 10 and 15 million Hindus and Muslims crossed the borders of the two new nation‐states after partition (Gatrell 2013 ).

Displacement was therefore at a record high in the mid‐twentieth century compared to both the early‐ and the late‐twentieth centuries (Gatrell 2013 ). These massive displacements were an important impetus for the establishment of organizations like the UNHCR and the Intergovernmental Committee for European Migration (the predecessor of the International Organization for Migration) in an effort to find more effective international responses to situations of human displacement (de Haas, Miller, and Castles 2020 ). This also provided the framework and incentive for the registration of refugee populations.

The fact that refugee records only started after the mid‐century peak and that early data were scant means that recent numbers may be inflated if they are not put into historical context. More generally, this begs the question of whether recent increases in refugee numbers as well as asylum applications in Western countries reflect a structural change in trends and patterns of global refugee migration, or a “normal” and therefore temporary response to the recent increase in conflict levels in particular countries, with refugee numbers likely to go down again after conflicts subside.

Data and methodology

One of the factors complicating long‐term, global analyses have long been the limited availability and quality of data, a situation which has recently been changing. A first longitudinal study in forced migration (Schmeidl 1997 ) created a dataset (1969–1990), extended a few years later by Moore and Shellman ( 2004 ) (1951–1995); in more recent years UNHCR picked up on these prior efforts by compiling the Population Statistics Database covering refugee data since 1951. UNHCR published its first annual statistical overview in 1994 (UNHCR 2000 ). Although far from perfect or complete, this database does allow us to conduct long‐term analyses of global refugee migration.

We use the UNHCR Population Statistics Database—which provides worldwide macrolevel statistics on the numbers of refugees—to study trends in refugee migration after 1951. 7 The database draws on various data sources, including survey data; census data; and registration data collected by local governments, UNHCR field offices, and NGOs. Although the UNHCR database is the most comprehensive one available, it has several limitations. Besides changing definitions and administrative practices across countries, the most important shortcoming which stands in the way of the analysis of refugee migration trends is the limited coverage in terms of older data for some countries. In order to avoid misinterpreting data, the paper will take these limitations into account and perform analyses using all available data as well as more‐limited data selections that only include countries for which data were available for the entire period we were interested.

For our analysis, we constructed indices that capture the intensity, spread, and distance of refugee migration, based on methodologies developed by Czaika and de Haas ( 2015 ) to analyze global migration trends. Combining these indices enables us to assess potential changes in the diversification of refugee migration over time. To this end, we studied the intensity, spread , and distance of refugee migration since 1951 (see Table  1 ). First, the intensity of refugee migration is defined as the refugee rate, which is measured as the number of refugees as a percentage of the world population. We study the intensity of refugee migration from an origin‐ as well as destination‐country perspective, by calculating the number of refugees as a share of origin‐ or residence‐country populations.

Dimensions of refugee migrations

SOURCE: Czaika & De Haas ( 2015 ).

Second, the spread of refugee migration is defined as “the global spread of migrants across all possible bilateral (country‐to‐country) migration corridors” (Czaika and de Haas 2015 , 296–297). This measurement is based on the Hirschman–Herfindahl index (Hirschman 1964 ), a statistical measure that can be used to capture the concentration of migrants in bilateral country corridors. Following Czaika and de Haas ( 2015 ), we subtracted the score from 1 to gain a measurement of spread instead of concentration. The index provides a score between 0 and 1, with higher scores indicating a more equal spread of refugee migration across bilateral corridors. We also calculated the global refugee emigration spread , which is an indicator of the spread of refugees across origin countries, and the global refugee immigration spread , which measures the spread of refugees across destination countries, calculated as one minus the sum of squares of the share of (emigrant or immigrant) refugees of the global refugee population for each country i in the world:

Finally, distance is measured as the geographic distance (in kilometers) between refugees’ origin and residence countries. We use the GeoDist database (Mayer and Zignago 2011 ) for the distance variable, which includes measures of bivariate distances between all countries in the world. We use the distance measurement calculated with “the great circle formula,” which uses bilateral distances between the most populated cities within countries. The relevance of absolute geographic distance may seem limited in a globalizing world in which cultural or legal barriers may be as important as, or more important than, geographic distance. Yet geographic distance still matters in terms of travel costs and the likelihood of crossing significant legal barriers (such as immigration restrictions) or the occurrence of cultural and social differences. As with the spread measure, in this paper, we distinguish between the average distances that refugees traveled from an origin‐ and a residence‐country perspective. This means that we calculated the average distance traveled for all refugees from each origin country as well as all refugees living in each destination country.

The intensity, spread, and distance of refugee migration after 1951

Global patterns: intensity, spread, and distance.

To analyze the evolution of refugee migration over recent years, we calculated global refugee populations (“stocks”) both in absolute terms and relative to the world population between 1951 and 2018 (Figure  1 ). For comparative purposes, we also added data on the number (or “stock”) of IDPs from 1969 onward. The early IDP data (1969–2000) are derived from the Global Refugee Project (Schmeidl and Jenkins 1999 ). The statistics are estimates based on annual UNHCR and US Committee for Refugees and Immigrants (USCRI) reports. Later IDP statistics (after 2000) are derived from the UNHCR Population Database and are based on data from the Internal Displacement Monitoring Centre (IDMC). Throughout this section, we use the term “global displacement” when we refer to both IDPs and refugees.

Global displacement: 1951–2018 NOTES: Refugee data are derived from the UNHCR Population Statistics Database. Data for IDPs for the 1969–2000 period are derived from Schmeidl and Jenkins ( 1999 ). Data for IDPs from 2000 onward are derived from the UNHCR database and provided by IDMC.

Figure  1 indicates that global displacement has increased drastically over the past five decades. This corroborates common perceptions of soaring displacement. Whereas, in 1951, approximately 1.8 million displaced persons were reported, numbers had risen to 44 million by the early 1990s, after which global displacement decreased again in the early 2000s, followed by a peak after 2005. This decrease coincides with the above‐mentioned shift in data sources used for the IDP statistics. It is not clear exactly why the IDMC statistics are much lower than those of USCRI, but this is likely related to differences in measurement or the inclusion versus exclusion of certain populations. This highlights the sensitivity of forced displacement statistics to changes in definitions or measurements and the importance of interpreting such data with the greatest possible care.

By 2018, the figure of the global displaced had risen to 62 million. However, Figure  1 also shows that most of this statistical increase since the early 2000s is driven by a sharp increase in IDP numbers—those included in UNHCR statistics increased sharply from 4.2 million in 2003 to 41.4 million by 2018. A large part of the increase in IDP numbers seems to have been driven by improved statistical coverage for this group as well as a looser definition of who belongs to this category. For instance, in 2007, individuals in “IDP‐like situations” were added to the number of IDPs and removed from the “others of concern” group in which they used to be classified. There were 12 countries included in the data in 2003; this increased to 31 countries by 2018. In that same period and notwithstanding periodic fluctuations, international refugee numbers have remained fairly stable. Refugee numbers decreased between 1993 and the early 2000s, from roughly 16 to 9 million. After the early 2000s, refugee numbers increased to 20.4 million by 2018. Another important observation is that refugee and IDP statistics follow the same trends and fluctuations over time.

To measure the intensity or relative magnitude of refugee migration, Figure  1 also depicts global displacement as a percentage of the world population between 1951 and 2018. This analysis reveals that refugee statistics have fluctuated at levels of between 0.1 and 0.3 percent of the world population over the past seven decades and that the intensity of refugee migration has gone down since the 1990s despite an upturn in recent years. Even though the total number of displaced as a share of the world population has increased from 0.10 to 0.27 percent since the early 2000s, this increase is mainly driven by the inclusion of IDP data. Between the early 2000s and 2018, the number of IDPs as a percentage of the world population increased from 0.07 to 0.5 percent, while that of refugees relative to the world population decreased from 0.33 percent in 1992 to 0.27 percent in 2018. Another reason to nuance the idea of a global increase in refugee populations is the fact that Palestinian refugees—a total of 904,122 in 1951—are excluded from UNHCR statistics, as they formally fall under the protection of the United Nations Relief and Works Agency for Palestine Refugees.

Overall, Figure  1 refines the idea that the intensity of refugee migration has increased. When looking solely at refugees, the current intensity of refugee migration is indeed higher than in the 1950s; however, it is also significantly lower today than in the 1990s, when it peaked at 0.33 percent. Taking a more long‐term perspective, the picture becomes even more nuanced. As mentioned above, 175 million people—approximately 8 percent of the world population—were displaced worldwide in the aftermath of World War II (Gatrell 2013 ). This is significantly more than the 62 million people—0.8 percent of the world population—who were displaced in 2018.

The common perception that refugee movements are rapidly increasing can also be linked to another assumption—the idea that the level of violent conflicts has been increasing. However, this idea also seems to be based on perception rather than fact because, since WWII, the level of violent conflicts and government oppression seems to have shown a decreasing rather than an increasing trend. For instance, the intensity of conflicts as measured by the number of battle‐related deaths in state‐based conflicts has shown a decreasing trend (see Figure  2 ). From a peak at 550,000 in the annual number of deaths around 1949–1950 (Chinese and Greek civil wars and the Korean War), the number of battle‐related deaths dropped to 30,000 in 1955 to rise to another peak of 290,000 in 1972 (Vietnam War) and 240,000 in 1984 (Iran–Iraq War, Afghanistan War). Since 1989, the annual number of battle‐related deaths has never exceeded 100,000 in 25 years, not even during the Bosnian War (1992–1995). After reaching a peak at around 80,000 in 1999–2000 (DRC war and the Ethiopia–Eritrea war), the number dropped to an absolute low of 21,000 in 2010. Recent conflicts in Syria, the Middle East, and South Sudan made numbers rise to new peaks in 2014 (105,000) and 2017 (134,000) but they have dropped again recently. If we look at the nature of political regimes, we also see a clear post‐WWII trend toward decreased autocratic governance. While, in 1946, the share of the world population living in democratic countries hovered at levels from 30 and 35 percent between 1947 and 1982, it rose to 50 percent in 1992, increasing again to 57 percent in 2005–2006. Although this percentage has been stagnating at levels of around 55 percent in recent years, the long‐term trend is clearly toward democracy, although it is too early to tell whether recent attacks on democracy will herald a future increase in autocracy. 8

Number of battle‐related deaths in state‐based conflicts: 1946–2018 NOTE: UCDP/PRIO Armed Conflict Dataset, Uppsala Conflict Data Program, and Peace Research Institute Oslo.

Such data give reason to think that earlier UNHCR data underrepresented true refugee numbers. Research has shown that conflict intensity, measured by the number of battle‐related deaths, is positively correlated to levels of forced migration (Melander, Öberg, and Hall 2009 ; Turkoglu and Chadefaux 2019 ). Yet, in the early 1950s, the number of battle‐related deaths in state‐based conflicts was at an all‐time high, while reported refugee stocks (Figure  2 ) were relatively low. The number of global battle‐related deaths also reached a peak in the 1970s, a figure which is not mirrored in the refugee data, probably because many of the displaced were unaccounted for.

The poor geographic coverage of older refugee statistics is another reason to question the idea that the intensity of refugee migration has increased. The collection of refugee statistics has improved significantly over time, particularly after 1990 (Crisp 1999 ), and an increasing number of countries have been included in UNHCR data. A long‐term analysis of refugee trends (as in Figure  1 ) can therefore be potentially misleading because statistics are not comparable between years. The long‐term increase in refugee migration up to 1990, as suggested by Figure  1 , may therefore largely reflect improvements in measurement rather than a real increase. The collection of reliable IDP statistics presents an even greater challenge to governments and humanitarian organizations because IDPs often move unregistered and tend to have shorter cycles of displacement. There is also a lack of clear definition by agencies and governments of what actually constitutes an “IDP” (see, e.g., Bennett 1998 ). Even more so than in the case of refugees, rising IDP numbers may therefore reflect data improvements rather than actual changes.

To illustrate improved data coverage over time, Table  2 gives an overview of refugee data provided by the UNCHR Population Database between 1951 and 2018. The database contained information on 21 countries in 1951, increasing to 76 in 1970, 114 in 1980, 147 in 1990, 194 in 2000, 211 in 2010, and 216 in 2018. For the early decades, refugee data were unavailable for many countries, particularly those outside the Western world. In 1951, the 10 countries with the highest numbers of refugees included in the UNHCR database are the United States, France, Austria, Germany, the UK, Australia, Canada, Belgium, Sweden, and Hong Kong. 9 As described before, data on approximately 900,000 Palestinian refugees are absent from the 1951 data; including this group would increase the number of reported refugees in that year from 1.8 to 2.7 million.

Data overview: 1951–2018

NOTE: Based on data from the UNHCR Population Statistics Database.

Moreover, in the 1950s, information on origin countries is missing. The tenfold increase in the number of countries covered between 1970 and 2018 shows that the UNHCR database should be used with caution. The number of net refugee‐origin countries increased between 1990 and 2018, which seems to reflect an increase in civil wars in the 1990s after the end of the Cold War (Blattman and Miguel 2010 ). The 1990s were a particularly volatile decade, with insurgencies arising in various countries such as Algeria, Afghanistan, Burundi, Liberia, Rwanda, Sierra Leone, and the former Yugoslavia. This confirms that fluctuations in the global refugee population primarily reflect those in the incidence of conflicts for more‐recent decades. Because of the better coverage and reliability of recent data, subsequent analyses will focus on the 1980–2018 period.

Global emigration and immigration intensity

In Figure  3 , we make a distinction between the intensity of refugee migration from both origin‐ and destination‐country perspectives. The emigration intensity is calculated as the average percentage of refugees relative to the origin‐country populations, whereas the immigration intensity is calculated as the average percentage of refugees relative to the destination‐country populations, for each year and for a fixed set of countries (69 destination countries and 51 origin countries) for which we have data for each year since 1980. The figure shows a relatively stable trend in refugee immigration intensity over time. Between 1980 and 2018, refugees constitute on average between 0.3 percent and 1 percent of the destination‐country populations.

Refugees relative to origin‐ and destination‐country population (%): 1980–2018 NOTES: Refugee data are derived from the UNHCR Population Statistics Database. The fixed set of countries includes 69 destination countries and 51 origin countries for which we have data for each year since 1980. The emigration intensity is calculated as the average percentage of refugees relative to the origin‐country populations, whereas the immigration intensity is calculated as the average percentage of refugees relative to the destination‐country populations.

The highest peak in refugee migration intensity over the 1980–2018 period occurred in the 1990s—which saw increasing civil conflict around the world, such as in the Balkans, the Horn of Africa, and the African Great Lakes region—and after 2010, when conflict broke out or intensified in countries like Iraq, Libya, Syria, and Yemen, alongside continuing conflict in, inter alia, Somalia and Sudan. In 2018, the top five countries hosting the greatest percentages of refugees relative to their total populations included Lebanon, Jordan, Nauru, Turkey, and Chad. Taking an origin‐country perspective, the intensity of refugee emigration varied between 2.5 and 3.5 percent of origin‐country populations between 1980 and the mid‐1990s. Between 2000 and 2010, these levels dropped to around 1.5 percent. After 2012 the emigration intensity went up again. In 2018, countries with the highest refugee emigration intensity were Syria, South Sudan, Afghanistan, Somalia, and Burundi. A global overview (maps) of the origin and destination countries n 2018 can be found in the Appendix.

However, the most important finding is that the post‐1980 increase in refugee migration suggested by Figure  1 is not reproduced in this analysis. If we use a time‐invariant set of countries, the pattern is one of (conflict‐related) fluctuation rather than an overall increase. What appeared to be an increase in refugee migration reflects the growing number of countries included in UNHCR data rather than a real increase in refugee migration.

The global spread of refugee migration

Table  3 shows the top 15 refugee‐destination and refugee‐origin countries in 1980, 1990, 2000, 2010, and 2018, both in absolute numbers (in millions) and as shares of global refugee numbers. Refugees concentrate in a relatively small number of destinations, although the level of concentration has undergone some changes. The percentage of global refugees residing in the top 15 refugee‐hosting countries decreased from 84 to 72 percent between 1980 and 2010, after which it increased slightly again between 2010 and 2018. However, 75 percent is still 10 percentage points lower than in the 1980s. This is a first indication that the global spread or diversification of refugee migration in terms of destination countries has been increasing.

Top 15 refugee‐hosting and refugee‐sending countries: 1980–2018

NOTE: Refugee data are derived from the UNHCR Population Statistics Database.

From an origin‐country perspective, trends show more variation over time. In 1980, the top 15 refugee‐origin countries represented 97 percent of all refugees included in the UNHCR database. Between 1980 and 1990, this percentage decreased to around 80 percent, after which it increased again to 83 percent in 2000 and 2010, to peak in 2018 at 91 percent. Overall, the data analysis shows a higher level of diversification in terms of destination compared to origin countries. While the bulk of the global refugee population has come from a relatively small number of countries (Syria, Afghanistan, South Sudan, Myanmar, Venezuela, and Somalia in 2018, for instance), the number of destination countries seems to have been increasing and diversifying. Another trend is that more low‐ and middle‐income countries enter the top 15 refugee‐hosting countries. This could, however, be due to more low‐ and middle‐income countries starting to collect statistics on refugee populations in recent years. So, this trend may partly be a statistical artifact.

To provide a statistical measure for the geographic distribution of refugee migration in terms of both origin and destination countries, we use the (inversed) Hirschman‐Herfindahl Index. Figure  3 shows the global spread of refugee migration between 1980 and 2018, as well as the spread of refugees in terms of origin and destination countries. As described, higher scores indicate a more equal spread of refugee migration across origin and destination countries, respectively.

Figure  4 shows that the global refugee population has spread more equally across bilateral corridors. This increase particularly occurred in the 1986–1991 period, after which it stabilized at values of around 0.95 from the early 1990s. The global spread or distribution of refugees is lower than that of nonrefugee migrants—a level which, as reported by Czaika and de Haas ( 2015 , 296), hovered at around 0.99 between 1980 and 2000. This shows that refugees tend to be more concentrated in particular countries of origin and destination. The increasing global spread of refugees seems to be particularly driven by a post‐1980 diversification of destination countries, particularly in more recent years. Trends for the diversity of refugee migration in terms of origin countries are quite different and less linear. After a period of relative stability in the 1980s, the global refugee‐origin spread increased rapidly between 1980 and the mid‐1990s. This reflected the outbreak of new conflicts in the post–Cold War era—particularly in the Balkans, the Horn of Africa, and the African Great Lakes region. However, after 1995 the origin‐country diversity decreased, reflecting a drop in the number of prime refugee‐producing countries. The refugee destination‐country spread is consistently higher than the emigrant spread and the gap seems to have widened between the early 1990s and 2000. To check whether this reflected the inclusion of more countries in recent data, we ran the analysis with a fixed set of origin and destination countries for which we have data for all years since the 1980s. Using these data, we find the same trends as the analysis using the nonfixed dataset.

Global spread of refugees: 1980–2018 NOTES: Refugee data are derived from the UNHCR Population Statistics Database. The fixed set of countries includes 69 destination countries and 51 origin countries for which we have data for each year since 1980.

Global distances traveled by refugees

Figure  5 shows the average geographic distance between refugees’ country of destination and country of origin (in kilometers) for each year since 1980. These calculations have been weighted by the number of refugees in each corridor containing refugees. To crosscheck the validity of these findings, we also included this measurement for a fixed set of origin countries from 1980 to 2018. The results show that the average geographic distance between origin and destination country has increased over time but that the trends are nonlinear. This trend is visible using measurements both of all countries and the fixed set of origin countries. Between 1980 and 2018, the average distance that refugees traveled increased by 40 percent, from approximately 1,000 km to around 1,500. These increases are most apparent in the 1990s and 2000s. The sharp drop after 2006 seems to be largely driven by the inclusion of people in “refugee‐like” situations in UNHCR refugee numbers since 2007, 10 among whom there are many Colombians and Haitians who are residing in the Americas. This observation shows how changes in definitions can bias aggregated figures.

Average geographic distance (in km): 1980–2018 NOTES: Refugee data are derived from the UNHCR Population Statistics Database. The fixed set of countries includes 69 destination countries and 51 origin countries for which we have data for each year since 1980. Calculations have been weighted by the number of refugees in each corridor containing refugees.

On average, refugees travel shorter distances than “regular” migrants. Czaika and de Haas ( 2015 ) found that migrants traveled on average 3,657 km in 2000. This was a 16 percent increase compared to 1980 when the average distance was 3,128 km. This may reflect the fact that refugees prefer to stay close to home and more often lack the resources to travel long distances and acquire essential paperwork such as passports and visas. Although refugees travel shorter distances than regular migrants, the rate with which the average distance increased over time is higher than for “regular” migrants.

Regional patterns: Intensity, spread, and distance

Figure  6 displays the distribution of refugees by region of origin and destination between 1980 and 2018. Most refugees originated from Asia and Africa, particularly in the 1990s and late 2010s. As shown in Table  3 , nine of the top 15 origin countries in the 1990s were African countries (Ethiopia, Mozambique, Liberia, Sudan, Somalia, Angola, Rwanda, Burundi, and Chad), while the peak in Asia mainly reflects enduring conflicts in Afghanistan, Iraq, and Vietnam. Together, these countries accounted for 46 percent of the global refugee population in 1990. In 2018, approximately 10 and 7 million refugees originated from Asia and Africa, respectively. In that year, 32 percent of the world refugee population originated from Syria, followed by 15 percent from Afghanistan. The third most important origin country in Asia was Myanmar, which mirrors the increasing outflows of Rohingya refugees. Recent increases in refugee numbers from Africa largely reflect increasing refugee outflows from South Sudan, Eritrea, and the Central African Republic. Europe and the Americas have mostly been refugee‐receiving regions, although a small peak can be observed in Europe in the early 1990s, which was a result of refugees from the former Yugoslavia moving to Western Europe as well as Albanians arriving in Italy.

Refugee emigration (top) and immigration (bottom) by region (in millions) NOTES: Refugee data are derived from the UNHCR Population Statistics Database. Refugee statistics are presented by region in absolute numbers.

Figure  6 also shows that regions with high refugee outmigration (particularly West Asia and East and Central Africa) also host relatively large refugee populations, indicating that most refugees reside within their origin region. For example, 6 million refugees originated from Africa in 2018, while the continent also hosted 5.5 million refugees in that same year. The main refugee‐hosting countries in Africa in 2018 were Uganda and Ethiopia, neighboring countries to refugee‐producing ones such as South Sudan, Somalia, and the Democratic Republic of the Congo (). The same pattern can be observed for Asia: 10 million refugees originated from the region, which hosted 8.6 million refugees. Analyses of country‐level statistics confirmed that most Asian refugees are hosted in the region: Syrian refugees mainly reside in Lebanon, Jordan, and Turkey, many Afghan refugees are in “protracted” situations in Iran and Pakistan, and many Vietnamese refugees are in a protracted situation in China. Countries in Europe and the Americas tend to host more refugees than they “produce.”

Focusing on the regional refugee emigration intensity , Figure  7 reveals that Asia and Africa also have the highest refugee emigration intensity. In the 1990s, this peaked in Africa and Asia, reaching between 0.94 and 0.26 percent, respectively. However, refugee emigration intensity declined significantly in later years, almost reaching that of Europe, Oceania, and the Americas in 2010, with intensity in Africa reaching levels of 0.28 percent. Between 2010 and 2018, refugee migration from Asia and Africa increased again in the wake of violent conflicts in Syria, South Sudan, and Somalia. The refugee emigration intensity in Europe showed a peak in the 1990s following a conflict in the former Yugoslavia and the wake of the collapse of the Soviet Union. Compared to other world regions, the refugee emigration intensity in the Americas and Oceania has been comparatively low and stable over time.

Refugee emigration (top) and immigration intensity (bottom) by region (%) NOTES: Refugee data are derived from the UNHCR Population Statistics Database. The intensity of refugee migration is defined as the refugee rate, which is measured as the number of refugees (immigrants or emigrants) as a percentage of the region's population.

Figure  7 also shows the refugee immigration intensity for each region. From the mid‐1980s onward, Africa has consistently had the highest intensity. Europe is the second most important region in terms of the number of refugees relative to its population, reflecting its geographic proximity to conflict zones within both Europe and the Middle East. Particularly in the mid‐1990s and after 2015, relative refugee immigration intensity increased in Europe. After the Syrian conflict erupted in 2011, the number of refugees as a percentage of Europe's population increased from 0.22 in 2010 to 0.37 in 2018, reaching levels similar to those in the early 2000s. Although Asia hosts the most refugees in absolute terms, in relative terms refugee immigration intensity is less significant, despite the outbreak of conflict in Syria, after which many refugees settled in Turkey, Jordan, and Lebanon. The Americas and Oceania consistently have the lowest refugee immigration intensity. 11

Regional destination patterns

The previous figures revealed that regions with high refugee outmigration also tend to host the most refugee immigrant populations. Table  4 shows that 83.46 percent of refugees resided in their region of origin in 2018. The global percentage shows a steady decline from the 1980s, when 98.27 percent of global refugees resided in their origin region, after which the figure steadily declined to 96.08 percent in 1990, 89.15 percent in 2000, and 84.13 percent in 2010. Although the majority of refugees continue to reside in their region of origin, these statistics suggest diversification of destinations and further travels of refugees over time.

Regional origins of refugees by residence region: 1980–2018

NOTES: Refugee data are derived from the UNHCR Population Statistics Database.

However, there are large differences across regions. Table  4 shows that the vast majority of refugees residing in Africa and Asia also originate from these regions, with regional refugee retention rates ranging from 94 to 100 percent, respectively. In 2018, Sudan, Uganda, and Ethiopia were the main refugee‐destination countries in Africa, with refugees mostly originating from South Sudan. In Asia, the top three refugee‐hosting countries were Turkey, Pakistan, and Iran, hosting mainly refugees from Syria and Afghanistan. The situation is quite different in other world regions. In Europe, there has been a clear shift in the regional origins of refugees over time. In 2000, Europe mainly hosted refugees from other European countries, such as Bosnia and Herzegovina, Serbia and Kosovo, and Croatia; however, over time, the shares of refugees originating from Asia (Afghanistan and later Syria) and Africa increased. In 2018, approximately 83 percent of refugees residing in Europe came from other continents. In that same year, only 2 percent of refugees residing in Oceania originated from there. Oceania, particularly Australia, mainly hosts refugees from Asia.

Background analysis revealed that the stark increase in the number of refugees in the Americas originating from the region—from 14 percent to 59 percent between 2006 and 2007—is a statistical artifact reflecting the aforementioned inclusion of intra‐regional migrants in “refugee‐like” situations who were previously excluded. In 2000, the Americas still hosted a sizeable number of refugees from Europe, predominantly people who fled the wars in the former Yugoslavia. The largest group of refugees in the Americas, however, continues to be from the Americas and the Caribbean—particularly from Colombia, Venezuela, Haiti, El Salvador, and Guatemala. Asian refugees residing in the Americas were mostly from China.

Region‐specific distance covered by refugees

One of the general assumptions in the literature is that refugees travel increasingly long distances because of the falling costs of travel and communication. While this was confirmed on a global scale (Figure  4 ), region‐specific trends can help us to further understand the factors explaining these global tendencies. Table  5 , therefore, examines the average distances traveled by refugees originating from different world regions. These patterns reveal that, at a regional level, average distances between origin and destination countries increased between the 1980s and the 2000s, slightly decreasing after 2010.

Average distance traveled from and to different regions (in km): 1980–2018

NOTES: Refugee data are derived from the UNHCR Population Statistics Database. Numbers are rounded.

On average, refugees originating from Oceania travel the longest distances, although these fluctuate substantially over time. The long‐distance traveled from Oceania is mostly because of high shares of refugees originating from Fiji who are resettled in Canada and the United States. Refugees from Europe traveled the second‐longest distances in the 1990s, which mainly reflects refugees from the former Yugoslavia who moved to the United States. After the 1990s, the average distance that refugees traveled from European countries decreased and remained stable at around 2,000 km, which is comparable to the average distances that refugees traveled from countries in Asia, Africa, and the Americas in later years.

Refugees traveling to Oceania and the Americas crossed the longest distances by far. The United States, Australia, and New Zealand host relatively large populations of resettled refugees. Even though resettlement numbers are small, this might have influenced the results upward because the distances crossed are large. For example, the largest group of resettled refugees in the United States traditionally consisted of refugees originating from the DRC, whereas in more recent years the United States hosted relatively large groups of Ethiopians, Cameroonians, Somalians, and Guineans, many of them coming through resettlement programs.

The average distance that refugees travel from their origin countries to Europe is stable over time and hovers at around 4,000 km. This finding corresponds with the earlier finding that the vast majority of refugees residing in Europe originate from other continents. Refugees residing in Africa and Asia traveled the shortest distances, between approximately 1,000 and 1,200 km, with the pattern remaining stable over time. This finding aligns with the general observation that most refugees originating from these regions tend to reside in neighboring countries in the same region.

Refugees from and to low‐, middle‐, and high‐income countries

We now turn to country‐level analyses to test the idea that refugees increasingly come from low‐income countries because recurrent cycles of conflict tend to concentrate on a limited number of them. We grouped the origin countries in our data into three equally sized groups based on their GDP (see Figures  8 and  9 ). The findings confirm that most refugees originate from low‐income countries and that these numbers have increased over time. Countries with low GDP also have the largest average numbers of refugees residing abroad relative to their populations, although the pattern fluctuates over time (Figure  8 ). The majority of the world's refugees are also hosted by low‐income countries. This was particularly the case in the 1990s when approximately half of the world's refugees resided in the 30 poorest countries. Relative to their populations, countries in the low and medium GDP group host most refugees as well. Particularly in the 1990s and after 2010, medium GDP countries host significant shares of refugees. Both figures, however, clearly show that high‐income countries share the lowest “burden” in terms of hosting the world's refugee populations, although differences across country income groups have decreased since the early 1990s.

Refugees by origin and destination country, GDP per capita (absolute numbers) NOTES: Refugee data are derived from the UNHCR Population Statistics Database. Data on GDP per capita is derived from the World Bank Development Indicators. Countries were grouped into three equally sized groups (low, medium, and high GDP) each year. Refugee statistics are presented in absolute numbers

Refugees by origin and destination country, GDP per capita level (%) NOTES: Refugee data are derived from the UNHCR Population Statistics Database. Data on GDP per capita is derived from the World Bank Development Indicators. Countries were grouped into three equally sized groups (low, medium, and high GDP) each year.

This paper has studied the long‐term trends and patterns of global refugee migration, with particular emphasis on the post‐WWII period. Importantly, the analysis did not detect a long‐term increase in global levels of refugee migration—refuting conventional wisdom, the long‐term levels have been quite stable over time. Primarily depending on levels of conflict, refugee numbers have fluctuated at between 0.1 and 0.3 percent of the world population. The analysis also showed that apparent increases in the numbers of globally displaced are driven by the inclusion of populations and countries that were previously excluded from the dataset. Besides a strong increase in the number of countries included in the UNHCR database over the last half‐century (from 76 in 1970 to 214 in 2018), recent figures have been artificially inflated through the inclusion of previously unregistered or underreported IDPs as well as people in “refugee‐like” situations in refugee statistics. This shows the dangers of using refugees and, more generally, migration data uncritically. Our analysis also highlights the bias and politics involved in choices around defining, collecting, and presenting displacement statistics. Finally, our analyses are based on stock data, which allowed us to study long‐term trends, but which is less suitable to study short‐term trends, circular flows, or the average duration of displacement (see, e.g., Devictor and Do 2017 ).

While refugee populations continue to be concentrated in countries with low‐to‐medium income levels, the analysis reveals several geographic shifts in refugee migration. Such shifts primarily reflect the idiosyncratic occurrence of conflicts rather than being part of some broad, inevitable trend toward intensified conflict—in fact, the long‐term trend has been toward reduced levels of violent conflict. While levels of refugee migration have remained stable, refugees have tended to come from a shrinking number of origin countries and to move to an increasing variety of destination countries over recent decades. This trend seems to reflect a concentration of recurrent conflict cycles in a relatively small number of countries and a parallel increase in the number of safe destination countries. Although the vast majority of refugees continue to stay near their origin countries, the average distance between origin and destination countries has increased over time, presumably linked to the greater ease of travel and the migration‐facilitating function of networks.

Yet, overall, these findings challenge the assumption that we are experiencing a global “refugee crisis.” From a historical perspective, the claim of “unprecedented levels” of forced migration seems even more unjustified, especially when we compare current levels to earlier periods. Rather than a general increase, we observe fluctuations in refugee migration over time, as well as geographic shifts in the spread and distance of refugee migration. The fact that refugee records only started after the mid‐century peak and that, until the 1990s, the data were only partial, means that recent numbers may seem inflated if they are not put into a historical context. This suggests that recent surges in refugee numbers as well as asylum applications in Western countries do not reflect a structural change in the trends and patterns of global refugee migration but, rather, reflect a “normal” and therefore temporary response to recent increases in conflict levels in particular countries, with refugee numbers usually going down again after the conflicts subside.

ACKNOWLEDGMENTS

The research leading to these results is part of the MADE (Migration as Development) Consolidator Grant project and has received funding from the European Research Council under the European Community's Horizon 2020 Programme (H2020/2015‐2020)/ERC Grant Agreement 648496. We thank Dr. Simona Vezzoli, Dr. Kerilyn Schewel, Dr. Katharina Natter, Flor Macias Delgado, and Siebert Wielstra for their valuable comments on earlier drafts of this paper, and Dr. Rik Linssen for the data visualization.

Sonja Fransen, United Nations University ‐ Maastricht Economic and Social Research Institute on Innovation and Technology (UNU‐MERIT), Maastricht University. Post code: 6211AX. Email: [email protected] . Hein de Haas, Faculty of Social and Behavioural Sciences, University of Amsterdam. Post code: 1018WS.

1 IDPs are “persons or groups of persons who have been forced to leave their home or place of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or man‐made disasters, and who have not crossed an international border” (UNHCR 2013 ).

2 Refugees are defined in the UNHCR database as “individuals recognized under the 1951 Convention Relating to the Status of Refugees; its 1967 Protocol; the 1969 OAU Convention Governing the Specific Aspects of Refugee Problems in Africa; those recognized in accordance with the UNHCR Statute; individuals granted complementary forms of protection; or, those enjoying ‘temporary protection’” (UNHCR 2013 ). In the 1951 Refugee Convention, a refugee is defined as “someone who is unable or unwilling to return to their country of origin owing to a well‐founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group, or political opinion.” (United Nations General Assembly 1951, Article 1).

3 https://www.unrefugees.org/refugee‐facts/statistics/, accessed November 3, 2021

4 See, e.g., https://www.refugeecouncil.org.uk/latest/news/unhcr-reports-highest-ever-number-of-forcibly-displaced-people-worldwide/ , accessed 1 July 2020; https://www.amnesty.org/en/what-we-do/refugees-asylum-seekers-and-migrants/global-refugee-crisis-statistics-and-facts/ , accessed 1 July 2020.

5 https://disasterdisplacement.org/the-platform/the-context , accessed 1 July 2020.

6 This global treaty was prepared in the aftermath of the World War II and initially allowed each state to choose between applying the refugee definition to persons displaced by “events occurring in Europe” or “events occurring in Europe or elsewhere before 1 January 1951. The 1951 Refugee Convention was later amended to the 1967 Protocol to protect refugees globally.

7 These data are available at http://popstats.unhcr.org , accessed July 14, 2020.

8 Data source: Our World in Data – calculations by Max Roser (Oxford University), based on Polity IV data.

9 The other refugee‐hosting countries included in the 1951 statistics are Luxembourg, Denmark, Tunisia, Spain, Norway, Turkey, Morocco, Switzerland, the Netherlands, Greece, and Italy.

10 According to UNHCR, people in a refugee‐like situation “includes groups of persons who are outside their country or territory of origin and who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained” (UNHCR 2008 , 4).

11 The peak in refugee immigration intensity in Oceania in the 1980s was due to high numbers of refugees residing in Australia—whose origins are marked as “unknown” in the UNHCR dataset—and high numbers from Indonesia residing in Papua New Guinea.

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• Original Article
• Open access
• Published: 24 February 2021

A theory of migration: the aspirations-capabilities framework

• Hein de Haas   ORCID: orcid.org/0000-0001-7593-6207 1  

Comparative Migration Studies volume  9 , Article number:  8 ( 2021 ) Cite this article

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This paper elaborates an aspirations–capabilities framework to advance our understanding of human mobility as an intrinsic part of broader processes of social change. In order to achieve a more meaningful understanding of agency and structure in migration processes, this framework conceptualises migration as a function of aspirations and capabilities to migrate within given sets of perceived geographical opportunity structures. It distinguishes between the instrumental (means-to-an-end) and intrinsic (directly wellbeing-affecting) dimensions of human mobility. This yields a vision in which moving and staying are seen as complementary manifestations of migratory agency and in which human mobility is defined as people’s capability to choose where to live, including the option to stay, rather than as the act of moving or migrating itself. Drawing on Berlin’s concepts of positive and negative liberty (as manifestations of the widely varying structural conditions under which migration occurs) this paper conceptualises how macro-structural change shapes people’s migratory aspirations and capabilities. The resulting framework helps to understand the complex and often counter-intuitive ways in which processes of social transformation and ‘development’ shape patterns of migration and enable us to integrate the analysis of almost all forms of migratory mobility within one meta-conceptual framework.

Introduction

Migration theory has been at an impasse for several decades (see Arango 2000 ; de Haas 2010a ; Massey et al. 1993 ; Massey  2019 ; Skeldon 2012 ). The field of migration studies has remained a surprisingly under-theorised field of social inquiry. This is unfortunate, as we can only develop a richer understanding of migration processes if we do not conceptually separate them from broader processes of social change of which they are a constituent part. Much thinking on migration remain implicitly or explicitly based on simplistic push–pull models or neo-classical individual income (or ‘utility’) maximising assumptions, despite their manifest inability to explain real-world patterns and processes of migration. Although prior migration theories have been rightfully criticised for their unrealistic assumptions, researchers have generally been better at debunking such theories than at coming up with viable theoretical alternatives.

To overcome this impasse and to advance our understanding of migration processes as an intrinsic part of broader processes of social change and ‘development’, this paper elaborates a theoretical framework that conceptualises migration as a function of people’s capabilities and aspirations to migrate within given sets of perceived geographical opportunity structures . Applying Sen’s ( 1999 ) capabilities framework to migration, this paper defines human mobility as people’s capability (freedom) to choose where to live – including the option to stay – instead of a more or less automated, passive and ‘cause-and-effect’ response to a set of static push and pull factors. The paper draws on Berlin’s ( 1969 ) concepts of positive and negative liberty to theorise the complex and non-linear ways in which macro-structural change can shape migration aspirations and capabilities, as well as to define new, theory-derived categories of human mobility and migration.

Migration theory: what is the problem?

Migration studies is an under-theorised field of social-scientific inquiry, in which the recent trend has been one of theoretical regression rather than progress. Earlier contributions to the field – such as Lee’s ( 1966 ) theory of migration, Mabogunje’s ( 1970 ) migration systems theory, Zelinsky’s ( 1971 ) mobility transition theory, Skeldon's ( 1990 ) work on migration transitions, Harris and Todaro’s ( 1970 ) neo-classical migration theory, Piore’s ( 1979 ) dual labour-market theory, Stark’s ( 1978 , 1991 ) new economics of labour migration and Massey’s ( 1990 ) cumulative causation theory – all tried to come up with generalised understandings of migration phenomena. With the exception of a few authors (Carling 2002 ; Faist 2000 ; Hatton and Williamson 1998 ; Skeldon 1997 ), in more recent decades the systematic theorisation of migration processes has been largely abandoned (see Skeldon 2012 ). In their seminal overview of migration theories, Massey and his colleagues (Massey et al. 1993 , p. 432) concluded that much thinking on migration ‘remains mired in nineteenth-century concepts, models, and assumptions’. Unfortunately, not much has changed since then.

This state of theoretical underdevelopment strongly contrasts with the huge increase in the number of empirical studies on migration. The lack of systematic theorising hampers our ability to meaningfully interpret empirical ‘facts’, to understand how macro-structural factors shape migration processes as well as to explain the huge diversity in migration experiences across different ethnic, gender, skill and class groups. Particularly since the rise of ‘postmodern’ social science in the 1970s and 1980s, big-picture migration theory-making has been largely abandoned. In reaction to the critique on ‘grand theory’ as well as the state-bias and ‘methodological nationalism’ (Wimmer and Glick Schiller 2002 ) inherent in much (policy-driven) migration research, recent work, particularly by anthropologists and sociologists, has focused on studying and conceptualising the (transnational, multicultural, diasporic, creolised) lives, identities and experiences of migrants from an ‘emic’ perspective.

Notwithstanding the considerable merits of such research, this has unfortunately coincided with an increasing gap between sociologists, anthropologists and also geographers conducting qualitative, interpretative micro-studies on migrants’ experiences on the one hand and the branches of economics, sociology and demography that have increasingly focused on quantitative regression analysis to examine the ‘causes’ and ‘impacts’ of migration largely along the (implicit or explicit) lines of the ‘push–pull’ model. While qualitative researchers often seem to have rejected the idea of explanatory migration theories altogether as naïvely positivist, the theoretical veneer of quantitative approaches has also remained extremely thin, as they do generally not go beyond an (often implicit) functionalist ‘push–pull’ perspective, according to which migrants are actors seeking to maximise income or ‘utility’. Both qualitative and quantitative approaches have failed to adequately capture the vital role of difficult-to-quantify structural factors such as inequality, power and states in shaping migration processes, or to develop a meaningful idea of human agency beyond the voluntaristic assumptions of neo-classical models or the portrayal of migrants as more or less passive victims of capitalist forces, as is common in historical-structural theories.

The ‘migration is too complex’ fallacy

The central problem in migration research is the absence of a central body of theories that summarises, generalises and systematises the accumulated insights of a vast amount of empirical research, that can serve as a common frame of reference within which to examine, interpret, understand and explain 'facts' and ‘findings’ from various disciplinary and paradigmatic perspectives, and that can guide future research. Several factors contribute to this lack of progress in our generalised understanding of migration, including:

the ‘receiving country bias’ and the concomitant ignorance of the causes, consequences and experiences of migration from an origin-area perspective, leading to one-sided, biased understandings of migration;

the dominance of government perspectives, ‘methodological nationalism’ (see Wimmer and Glick Schiller 2002 ) and the related tendency to uncritically adopt state categories to classify migrants and migration, which often sustain distorted, ideological views on migration;

disciplinary and methodological divides, particularly between quantitative (positivist) and qualitative (interpretative) approaches;

the divide between the study of ‘forced’ and that of ‘voluntary’ migration; and

the divide between the study of international and that of internal migration.

Researchers have frequently argued that a comprehensive or universal migration theory will never arise because migration is too complex and diverse a phenomenon (see Castles and Miller 2009 ; Salt 1987 ). However, this argument is not convincing for two main reasons. First, it would be misleading to suggest that the goal of social theory is to develop all-explaining, universal theories because social phenomena always need to be understood within the specific historical and social contexts in which they occur and can therefore never be captured by a simple set of formulas, ‘laws’, models or regression equations. Second, complexity can never be a reason to abandon efforts to build better social theories. After all, social phenomena are complex by nature and complexity has not stood in the way of theoretical advancement in other fields of social inquiry. In fact, we need to turn the argument upside down: the complexity which is so characteristic of social processes is the very reason why we need social theories, as they help us to make sense of and to discern patterns amidst the sometimes dazzling diversity – and the apparently random, chaotic and non-systemic nature – of human experiences and social interactions. In other words, social theories help us to see the wood for the (empirical) trees.

Importantly, the notion of complexity does not imply that social phenomena and social processes are chaotic or devoid of regularities, patterns or structure. Rather, complexity implies that they consist of many parts in elaborate, multi-layered arrangements. From a micro-perspective, the diversity of migration experiences may seem bewildering but, once we start to zoom out, regularities and patterns tend to emerge. This reflects the very purpose of social theory: to discern patterns in order to make sense of what is happening around us. For instance, as Ravenstein ( 1885 , particularly for the case of Britain) and Mabogunje ( 1970 , particularly for the case of Africa) have already shown, migration is anything but a random phenomenon. In different geographical and historical settings, they both observed that most migrants move along spatially clustered pathways between very particular communities in origin and destination areas. Similarly, at a macro level, Zelinsky ( 1971 ), Skeldon ( 1990 ) and Hatton and Williamson ( 1998 ) observed clear long-term regularities between demographic, economic and social transitions on the one hand and the sequenced emergence and decline of particular forms of internal and international human mobility on the other.

Paradigmatic classification of migration theories

Since the late-nineteenth century, various theories have emerged in various social-science disciplines which all aim at understanding the processes that drive migration. Such early migration theories can be clustered together into two main paradigms, following a more general division between ‘functionalist’ and ‘historical-structural’ social theory. Despite their various disciplinary origins, theories within each of these two main paradigms share basic assumptions about the nature of society and how society should be studied. For instance, neo-classical equilibrium models (from economics), push–pull models and migration systems theories (mainly from geography and demography) as well as dominant interpretations of migrant network theories (primarily from sociology) can all be situated within the functionalist paradigm of social theory, according to which migration is, by and large, an optimisation strategy of individuals or families making cost–benefit calculations.

Likewise, despite differences in nuance and level of analysis, neo-Marxist conflict theory, dependency theory (Frank 1966 ), world systems theory (Wallerstein 1974 , 1980 ), dual labour-market theory (Piore 1979 ) and critical globalisation theory (see Sassen 1991 ) have broadly similar interpretations of migration as being shaped by structural economic and power inequalities, both within and between societies, as well as the ways in which migration plays a key role in reproducing and reinforcing such inequalities. All these theories can be situated within the historical-structural  paradigm, also known as ‘conflict theory’, which focuses on how powerful elites oppress and exploit poor and vulnerable people, how capital seeks to recruit and exploit labour and how ideology and religion play a key role in justifying exploitation and injustice by making them appear as the normal and natural order of things.

More recent theories that focus on migrants’ everyday experiences, perceptions and identity – such as transnational (Vertovec 2009 ), diaspora (Cohen 1997 ; Safran 1991 ) and creolisation (Cohen 2007 ) theories – can all be situated within the symbolic interactionist perspective in social theory. We can perhaps distinguish a fourth, slightly more hybrid, group of meso-level theories that focus on the continuation or ‘internal dynamics’ (de Haas 2010b ) of migration, such as network theories, migration systems theory (Mabogunje 1970 ) and cumulative causation theory (Massey 1990 ). We can thus reduce what may initially appear as a rather dizzying theoretical complexity by combining existing disciplinary theories (ranging from economics to anthropology) under the conceptual umbrellas of the main social-theory paradigms. For the sake of brevity and because the goal of this paper is to advance an understanding of migration processes as part of broader social change, the following analysis will focus on the classic distinction between functionalist and historical-structural theories.

Limitations of functionalist and historical-structural theories

Functionalist social theory tends to see society as a system, a collection of interdependent parts (individuals, actors), somehow analogous to the functioning of an organism, in which an inherent tendency towards equilibrium exists. Functionalist migration theories generally see migration as a positive phenomenon contributing to productivity, prosperity and, eventually, greater equality in origin and destination societies through bidirectional flows of resources such as money, goods and knowledge. Essentially, they interpret migration as an optimisation strategy, in which individuals (and sometimes families or households) use migration to access higher and more-secure sources of income and other livelihood opportunities.

Neo-classical migration theory, as pioneered by Todaro ( 1969 ) and Harris and Todaro ( 1970 ), is the most prominent representative of functionalist migration theories but there are more theoretical currents that can be grouped under the functionalist migration paradigm. Push–pull models are basically a prototype version of neo-classical migration theories as they interpret migration as a function of income and other opportunity gaps between origin and destination areas. These functionalist models are all based on the explicit or implicit assumption that people make rational decisions in order to maximise income or ‘utility’. The only major exception on this rule seems to be the new economics of labour migration (NELM) pioneered by Stark ( 1978 , 1991 ), which conceptualises migration occurring in contexts of relative poverty and constraints as a household’s or family’s (instead of an individual’s) co-insurance strategy aimed at diversifying (instead of maximising) income through risk-spreading. Although it acknowledges the role of structural constraints in shaping migration decisions, NELM is also ultimately based on the assumption that households are rational actors engaging in a long-term economic optimisation strategy.

At the macro level, from a functionalist perspective, individual optimisation decisions are expected to contribute to a more optimal allocation of factors of production – primarily through the transfer of labour from poor to rich areas and countries and concomitant reverse flows of capital from rich to poor areas – which is expected to decrease economic gaps between origin and destination areas (de Haas 2010a ). However, such accounts typically ignore how poverty, inequality, immigration restrictions, government repression and violence can prevent people from migrating, cause their forced displacement or compel migrants into exploitative work conditions. This explains why the social and economic benefits of migration often accrue disproportionally to the already better-off in origin and destination societies – migrants and non-migrant ‘natives’ alike.

The central problem of functionalist migration theory is its reductionist character. The ‘push–pull’ reasoning on which these explanations are based strongly resonates with intuition but has proved to be inadequate and often plainly misleading in understanding real-world migration processes. Push–pull models are not able to explain migration  as a social process , as they tend to list a number of static factors that obviously play ‘some’ role in migration but without specifying their role and interactions or providing a structural account of the social processes driving population movements. Skeldon ( 1990 , pp. 125–126) therefore argued that push-pull models leave us with ‘a list of factors, all of which can clearly contribute to migration, but which lack a framework to bring them together in an explanatory system’, leading him to conclude that ‘the push–pull theory is but a platitude at best’.

If we reformulate the cornerstone functionalist assumption as ‘most people migrate in the expectation of finding better opportunities at the destination’, probably few would disagree. This assumption, that people basically have good reasons to move, however, is so general that it is of little use in explaining the geographically patterned and socially differentiated nature of migration processes. In other words: knowing what motivates individual people to move does not really help us to explain the processes, patterns and drivers of migration at the structural level.

The real questions are more complex and beg more complex answers. For instance, why do wealthier, more ‘developed’ societies tend to have higher levels of immigration and emigration than poor and ‘underdeveloped’ societies, while push–pull and neo-classical models would predict the contrary? How can we explain that most migration does not occur from the poorest to the richest societies? Why does ‘development’ in origin countries often lead to increased emigration propensities? And why do most people actually not migrate despite the existence of huge income and opportunity gaps within and between countries?

Functionalist migration theories have inherent difficulties explaining the socially and geographically differentiated nature of migration processes, in which structural inequality and discriminatory practices strongly favour the access of particular social groups and classes to attractive, legal migration opportunities, while excluding others by depriving them of rights or compelling them into exploitative situations. People’s ability to make independent migration choices is constrained by states and other structures such as family, community, networks and culture, which ultimately determine the social, economic and human resources which people are able and willing to deploy to migrate. At best, functionalist theories and push–pull models can incorporate such structural constraints as ‘market imperfections’ in theoretical models or cost-increasing factors in regression analyses. However, this exposes their inability to conceptualise how structural forces actively shape migration processes and often stand at the very origins of large-sale migration systems.

Colonialism, warfare, labour recruitment, migration policies, land dispossession, eviction due to infrastructure projects (e.g., road and dam construction) and cultural change are all examples of complex macro-structural change processes that cannot be reduced to ‘factors’ or ‘variables’ affecting migration costs. For instance, much large-scale migration has its origins in active efforts by states and employers to recruit foreign labour (see de Haas et al. 2020a ; Piore 1979 ). This shows the need to conceptualise the role of states, businesses, recruiters and various other migration intermediaries (see Agunias 2009 ) as well organisations (such as the UNHCR, IOM or humanitarian organisations (see Olayo-Méndez 2018 )) in actively shaping migration processes and creating entirely new migration patterns instead of reducing them to cost-increasing constraints in ‘naturally’ occurring migration processes. A full understanding of the role of such structural migration drivers therefore obviously defies their reduction to a few factors  in a mathematical theoretical model or variables in an empirical regression model.

Besides their general inability to conceptualise how structural factors and actors have actively shaped migration processes throughout history, functionalist theories have difficulties in explaining how, in the real world, migration can reinforce pre-existing inequalities. This upsets the underlying equilibrium assumption of functionalist theories, according to which social and market forces, if left to their own devices, would automatically tend towards equilibrium and in which (free) migration is thus expected to lead to income convergence and, eventually, less migration. Myrdal ( 1957 ) already argued that, without redistributive government intervention, socio-economic processes of ‘cumulative causation’ tend to reinforce inequalities between poor and rich areas, rather than the other way around. In the same vein, historical-structural theories argue that structures have, in fact, a tendency to reproduce or even reinforce inequalities, both ‘vertically’ between social groups (such as classes) and ‘horizontally’ across space (i.e., between peripheral rural areas and cities or between rich and poor countries).

For instance, in the poorest countries of Africa and Asia, legal migration opportunities to Europe, North America and other wealthy countries are mainly the prerogative of elite groups, who possess the right diplomas to qualify for a work or study visa and who have the financial means to pay for their migration. If it is mainly rather well-off groups who gain access to the most lucrative forms of legal migration, while others remain stuck in immobility or are relegated to exploitative forms of (often undocumented) migration, this is likely to sustain or even deepen inequalities within origin societies. As Van Hear ( 2014 ) argued, migration and its outcomes are “shaped by the resources that would-be migrants can muster and that in turn the capacity to mobilise such resources is largely determined by socio-economic background or class” (Van Hear 2014 , p. 100).

Such arguments resonate with neo-Marxist political economy and historical-structural theories that emphasise how social, economic, cultural and political structures constrain and direct the behaviour of people in ways that do not generally create greater equilibrium but, rather, reinforce such inequalities. These theories emphasise the role of businesses – and states representing their interests – in shaping migration and see labour migrants, both forced and voluntary, as providing a cheap, exploitable labour force, mainly serving the interests of wealthy groups, areas and countries (de Haas et al. 2020a ; Piore 1979 ). These theories emphasize that economic and political power is unequally distributed and that cultural beliefs (such as religion and tradition) as well as social practices serve to justify and reproduce such inequalities. From this perspective, it is thus the already privileged in destination societies, such as employers and capital-owning elite groups more in general, who mainly benefit from migration. This is reflected in migration rules and political discourses that favour and praise the skilled and wealthy and disdain or vilify the less-skilled, vulnerable, ethnically different and poor migrants and often relegate them to be exploited in the informal sector. From this perspective, the real aim of anti-immigration policies is not to stop immigration but to create an appearance of control (see Massey et al. 1998 , p. 288), with the associated anti-immigrant political discourses serving to justify the economic exploitation of vulnerable migrant groups and to blame migrants for problems not of their own making.

However, the central problem of such historical-structural views is that they leave hardly any room for human agency . They tend to depict migrants as pawns – pushed and pulled around by global macro forces – or as victims of capitalism who have no choice but to migrate in order to survive. Views of migration as a ‘desperate flight from misery’, or that portray migrants as passive victims of smugglers and traffickers, do no justice to the fact that the vast majority of migrants move of their own free will. Indeed, a large body of research evidence shows that most migrants succeed in significantly improving their livelihoods through internal and international migration (de Haas et al. 2020a ; Massey et al. 1998 ; UNDP 2009 ). In addition, juxtaposing mainstream narratives depicting smugglers as ‘unscrupulous and ruthless criminal gangs preying on vulnerable and desperate migrants’, the lived experiences of migrants expose a much more nuanced reality, with smugglers generally functioning as migration facilitators who can be close friends, acquaintances or more distant service deliverers (Zhang et al. 2018 , p. 6).

Historical-structural views are often based on underlying assumptions that much 'South-North' migration is a largely irrational process that would  often not be in the interests of migrants themselves, as they would be blinded by over-optimistic mirages about life abroad and deceived by untrustworthy recruiters, smugglers and traffickers. This assumption is also reproduced in official discourses and policies according to which prospective migrants should be educated about the risks and costs of migration through information campaigns. This clearly denies the fact that, even for less-skilled or undocumented migrants, migration still has huge potential to improve the long-term wellbeing of themselves and their families and that they are therefore willing to endure situations of exploitation and suffering, however unjustified these may be from a moral and ethical point of view.

Towards a more meaningful understanding of migratory agency

At first sight, functionalist and historical-structural accounts of migration seem diametrically opposed in their understanding of migration, in terms both of its social causes and of its consequences for destination and origin areas. However, what both paradigms have in common is a general inability to provide a meaningful understanding of human agency through their portrayal of migrants either as rather soulless individual utility-optimisers or as rather passive victims of global capitalist forces. Numerous studies have highlighted the limited but real ability of migrants to defy government restrictions, discrimination and xenophobia by migrating over closed borders, by buying in the services of recruiters, lawyers, smugglers and various other migration intermediaries, and by forging networks and new identities as well as establishing communities and their own economic structures in destination societies (Agunias 2009 ; De Haan et al. 2000 ; de Haas 2010b ; Stark 1991 ; Zhang et al. 2018 ). It would therefore be just as unrealistic to depict migrants as victims desperately fleeing situations of destitution, opression and human misery as it would be to depict them as entirely rational and free actors who constantly make rational cost–benefit calculations. This shows that neither functionalist nor historical-structural theories provide realistic accounts of migratory agency. The central challenge in advancing migration theory is therefore the elaboration of conceptual tools that improve our ability to simultaneously account for structure and agency in understanding processes and experiences of migration, without discarding the important insights which both functionalist and historial-structural paradigms offer and thus rejecting them altogether.

Theoretical exclusivism versus conceptual eclecticism

While the assumptions of neither functionalist nor historical-structural theories have universal value, both sets of explanations can nevertheless be useful in developing a richer, nuanced and contextualised understanding of migration processes. After all, functionalist theories may have greater explanatory value for some types of relatively unconstrainted forms of human mobility – such as much internal and high-skilled migration – while historical-structural theories may have greater explanatory value for forms of migration where government restrictions, exploitation and involuntariness play a more important role. Migration can be a very empowering experience but can, in other cases, take more exploitative forms.

Thus, instead of rejecting either set of explanations, insights from both paradigms need to be incorporated in a new, overarching theoretical paradigm on migration that can unite them. Instead of seeing theories as exclusive truth claims, we need a vision in which the validity of theoretical assumptions is contingent on the specific conditions under which migration occurs, the specific social and class groups concerned, as well as on levels of analysis. This implies that both the functionalist and historical-structural paradigms can have explanatory power and relevance and can, therefore, to a certain extent, be combined and integrated in a wider meta-theoretical framework which is able to simultaneously incorporate agency and structure in explaining migration and which acknowledges that the vast majority of migrants face some level of constraint yet also have some level of choice.

The way forward is therefore not to develop entirely new theories but to find concepts and analytical tools that help us to build upon and bridge insights provided by existing theories – not only within but also across paradigms. This implies a rejection of the somewhat common idea that we cannot combine social theories that are based on conflicting paradigmatic assumptions, particularly if we combine explanations at different levels of analysis.

A simple example may serve to illustrate the relevance of insights from both functionalist and historical-structural migration theories. From a macro-level perspective, some forms of migration seem rather exploitative – such as undocumented migration from Mexico to the US, Morocco to Spain, Mali to Côte d’Ivoire, Myanmar to Thailand or Indonesia to Malaysia – where uncertain legal status or ‘illegality’ enables employers to hire and fire migrant workers as they please and to pay low wages. At the macro level, such ‘exploitative’ forms of migration can exacerbate economic gaps between origin and destination areas by supplying cheap labour and boosting profits and income growth in destination areas for which reverse resource flows to origin areas such as remittances cannot compensate. Unequal terms of trade, higher productivity and economics of scale can lead to a further concentration of economic activities in wealthy destination countries along with the sustained migration of workers from poor countries to support them (see Martin and Taylor 1996 ). At the micro level, however, it may still make sense for people to migrate if this increases family income significantly and enables them to build a house, afford health care, send their children to school or start a small enterprise. The second insight does not prove the first wrong – vice versa.

This resonates with the argument of Massey and his colleagues (Massey et al. 1993 , p. 432), who stated that there is considerable scope to combine insights from different theories:

A full understanding of contemporary migration processes will not be achieved by relying on the tools of one discipline alone or by focusing on a single level of analysis. Rather, their complex, multifaceted nature requires a sophisticated theory that incorporates a variety of perspectives, levels and assumptions.

Some migration researchers have countered this idea. For instance, Bakewell ( 2010 , p. 1692) argued that Massey et al.’s ( 1993 ) claim that there are no necessary, inherent contradictions between different theories is hard to sustain ‘when one considers very different ontological and epistemological foundations of migration theories’. This is essentially is a Kuhnian argument on the incommensurability of scientific paradigms. As Kuhn ( 1962 ) argued in The Structure of Scientific Revolutions , the proponents of different paradigms live in different worlds and use different vocabularies and criteria determining the legitimacy of both problems and proposed solutions in terms of methodology and analysis. Each paradigm therefore has the tendency to satisfy the criteria it sets for itself and to reject the problem definition as well as evaluation criteria used by other paradigms (Kuhn 1962 , p. 109). Importantly, such a Kuhnian view precludes combination or comparison across scientific paradigms, as adherents of different paradigms seem to be living in largely self-contained ‘truth bubbles’.

Kuhn’s view is extremely valuable for understanding the limited communication and the lack of recognition and appreciation among social scientists conducting research across paradigmatic, methodological and disciplinary divides. Yet there is also good reason to question the full applicability of the Kuhnian incommensurability principle to the social sciences (see also Urry 1973 ). Importantly, Kuhn based his argument on an analysis of the history of the natural sciences. In contrast to natural sciences, social theories typically have no universal bearing but are specific to particular historical and geographical contexts. The positivist universality claims of most natural-science theories can therefore not simply be extended to the social sciences, where theories need to be contextualised and historicised in order to make them meaningful and to be clearer about their specific applicability. Hence, in the social sciences, theories and paradigms do not need to be mutually exclusive a priori. Rather, they offer different explanations of social phenomena which can frequently be combined, particularly if they apply to different historical or social contexts, social groups or levels of analysis, or if they look at the same social phenomenon from different thematic, disciplinary and methodological angles.

It is therefore also dangerous to blindly apply the Popperian falsification principle to the analysis of the social world. For instance, if an empirical analysis conducted within a particular context shows that neo-classical ‘predictor variables’ such as wage differences do not have a significant effect on this particular form of migration, this still does not provide sufficient evidence to reject the theory as a whole. It may simply mean that a particular theory may have little or no explanatory power in that particular context. This does not provide a licence for a sloppy practice of ‘anything goes’ ad-hoc theorising but, rather, makes the case for more analytical precision in carefully assessing the applicability of particular theories in particular settings and at particular levels of analysis. Because theories have often been formulated to explain specific forms of migration occurring in particular geographical and historical contexts, a greater awareness of the history of theories is essential if we are to understand their particular claims and applicability.

Instead of ‘rejecting’ or ‘confirming’ hypotheses and theories, social analyses would gain interpretative depth and theoretical relevance if they indicate which contextual factors may explain certain expected or unexpected empirical observations. One single experiment defying Newton’s law of universal gravitation should indeed suffice to reject his theory. However, in contrast to the natural sciences, in social sciences it is often not about one theory being ‘right’ or ‘wrong’, let alone about testing the validity of an entire theory by plugging in a predictor variable ‘representing’ the theory in a regression model. In this context, Garip ( 2012 , p. 425) rightly argued that migration researchers tend to ‘reduce theories to competing sets of independent variables ... [which] inevitably leads to either/or theoretical stances, rather than an emphasis on the complementarity of different theories’. Instead of stubbornly adhering to theoretical exclusivism, social theory-building should therefore be an inherently eclectic affair, in which an openness should exist to potentially combine different theoretical perspectives as part of an effort to develop more comprehensive, nuanced and, therefore, more realistic conceptual frameworks.

To summarise, migration theories can potentially be combined across five analytical dimensions:

At different levels of analysis : macro-, meso- and micro-level explanations of migration may require different conceptual tools. For instance, forms of exploitative labour migration that seem to fit within the neo-Marxist paradigm can still be rational for migrants and their families.

In different (geographical, regional, national) contexts . For instance, functionalist neo-classical theories may work better to explain relatively unconstrained migration in wealthier countries, while historical-structural approaches may be more useful to explain migration within and from poor or ‘developing’ countries or occurring under conditions of oppression and violence.

Across different social groups : even at the same point in time and in the same geographical and national context, migration is a socially differentiated process; different theories are therefore likely to have varying degrees of applicability to different occupational, skill, income, class or ethnic groups. For instance, neo-classical assumptions may hold relatively well in explaining the migration of higher-skilled migrants, whereas neo-Marxist theories may be more useful in understanding the migration of less-skilled and relatively poor manual workers.

At different points of time . The drivers and internal dynamics of migration processes often change over time and over the various trajectories and successive stages of migration system formation and decline (de Haas 2010b ); so, too, therefore, do the social, cultural and economic mechanisms explaining such migration. For instance, Garip ( 2012 ) identified four distinct types of Mexico–US migrants over the 1970–2000 period and argued that these types gained prevalence during specific time periods depending on the changing conditions in the two countries.

From different thematic or disciplinary perspectives . We can look at the same manifestation of migration from various analytical perspectives. For instance, we can study how social transformation processes shape migration processes simultaneously from cultural, political, economic, technological and demographic perspectives as well as through the use of various methodologies and data. This provides different – and generally complementary – angles from which to study and explain the same social process (see de Haas et al. 2020b )

This highlights the considerable potential to combine different theories to improve our understanding of migration processes across different levels of analysis (and aggregation), contexts, social groups and periods. In this way, disciplines, theories and paradigms become interpretative frameworks that reflect a particular way of viewing the world or dominating certain societies or periods. Such varying perspectives can be complementary (when they stress different dimensions of the same phenomenon) or may seem conflicting (when their fundamental assumptions clash) – although what initially appears to be a clash of assumptions may partly reflect their applicability to different contexts, social groups and levels of analyses. This shows the danger of buying into one particular train of thought, in which theories can easily devolve into intellectual straightjackets rather than conceptual toolboxes. This should compel us to achieve a deeper understanding of the concrete historical, geographical and social contexts in which migration occurs. It also highlights the need to break with bad habits of disciplinary and methodological parochialism.

Migration as an intrinsic part of broader social change

A first essential step in our quest to achieve an more comprehensive theoretical understanding of migration is to connect migration theories to general social-scientific theories. This reflects the need to (re) conceptualise migration as an intrinsic part of broader processes of economic, political, cultural, technological and demographic change embodied in concepts such as social transformation, ‘development’ and globalisation. Footnote 1 This is in opposition to more conventional scientific views which portray migration as either a response to development disequilibria or a function of static ‘push’ and ‘pull’ factors as well as policy views that portray migration either as a ‘problem to be solved’ or, conversely, as a solution to problems (such as population ageing). However, migration is a social process that cannot be seen in isolation from the broader processes of change of which it is a constituent part.

Urbanisation is perhaps the best example to illustrate this fundamental point. Since the onset of the industrial revolution, migration and urbanisation have been intrinsically intertwined processes which can therefore not be conceptualised separately. It is as unconceivable to understand modern urbanisation processes without understanding rural-to-urban migration as it is to understand rural-to-urban migration without understanding urbanisation processes. This exposes the flawed assumptions underlying attempts by governments to curb rural-to-urban migration through rural development programmes (see Rhoda 1983 ), as such policies cannot stop broader processes of social transformation and capitalist expansion which inevitably undermine traditional agrarian livelihoods, encourage the growth of the urban sector and irrevocably change ideas of the ‘good life’ amongst new generations towards more urban lifestyles (see Mabogunje 1970 ; Schewel 2019 ).

While broader processes of social change shape migration, through its social, economic, cultural, demographic and political impacts, to some extent migration also affects these processes in its own right. For instance, remittances can increase income inequality and relative deprivation in origin communities and therefore further increase emigration aspirations, while large-scale immigration can affect the structure and segmentation of labour markets in destination countries (Massey 1990 ; de Haas et al. 2020a ). Although this relationship is reciprocal, it also tends to be a highly asymmetrical one, because migration is generally unlikely to affect the deep structures of origin and destination societies unless it takes on truly massive proportions (see Portes 2010 ) or colonisers subjugate native populations through military force. This reciprocal but asymmetric relation between migration and broader social change is depicted in Fig.  1 .

Prior research has shown that social transformation and economic development often shape migration in complex and often quite counter-intuitive ways that reveal the inadequacy of conventional migration theories. In low-income societies, marginal increases in income, improving education, infrastructure expansion, urbanisation and concomitant transformations from largely agrarian to industrial and service-based economic systems are generally associated with increasing levels of both internal and international migration. In other words, development initially leads to more migration. Only in the longer term, when societies become wealthier and predominantly urban, does emigration tend to decrease and immigration to increase, after which societies transition from being net emigration to net immigration countries. Such mobility or migration transitions were first hypothesised by Zelinsky ( 1971 ) and further elaborated on by Skeldon ( 1990 ,  1997 ). In 2010, I  elaborated a theoretical explanation of the social mechanisms underpinning the occurrence of migration transitions and, drawing on new data, I performed a first global test of the relation between levels of development and levels of immigration and emigration (de Haas 2010c ). These empirical analyses confirmed migration transition theory and were further validated by subsequent studies (Clemens 2014 , 2020 ; de Haas and Fransen 2018 ). Historical studies, such as of the European emigrations to the ‘New World’ between 1850 and 1914 (Hatton and Williamson 1998 ), also seem to confirm the transition model.

This non-linear relationship between development and migration levels clearly challenges functionalist, and historical-structural migration theories as well as push–pull models, which all implicitly or explicitly assume that the reduction of poverty and economic gaps will reduce migration. More in general, these insights highlight the need to conceptualize migration as a normal social process. As long as societies change (which they always do), social stratifications persist (which is equally likely) and people go through life stages (which is inevitable), people will keep on migrating – and settling. Societies are in constant mutation and migration should therefore be seen as a normal process, instead of being normatively cast as an undesirable or desirable process (in public debates), as the ‘antithesis’ of development (as in historical-structural accounts) or as a largely temporary response to development disequilibria (as in neo-classical accounts). The relevant theoretical question is therefore not ‘why people move’ (which tends to yield overly generic and rather meaningless platitudes of the ‘push–pull’ genre) but, rather, how patterns and experiences of migration are shaped by broader processes of social change.

Conceptualising structure and agency in migration processes

The main conceptual problem of conventional theoretical accounts of migration remains their inability to meaningfully conceptualise how individual migrants and groups of migrants exert agency within broader structural constraints. Because of their centrality to our analysis and because of frequent confusion around their meaning, it is important to define the key terms of agency and structure. Agency reflects the limited – but real – ability of human beings (or social groups) to make independent choices and to impose these on the world and, hence, to alter the structures that shape and constrain people’s opportunities or freedoms. Structure can be defined as patterns of social relations, beliefs and behaviour. Factors and institutions such as class, religion, gender, ethnicity, networks and markets as well as cultural belief systems all sustain inequalities and social hierarchies and limit the opportunities that people have – or perceive they have – and the economic, social and cultural resources which they can access – thus significantly constraining their freedom or agency as well as their ideas, knowledge and self-consciousness.

As mentioned above, historical-structural theories tend to portray migrants as relatively passive actors or victims who are pushed around the globe by the macro-forces of global capitalism. Because they focus on the behaviour of actors (individual migrants) and may therefore come across as more ‘agentic’ at first sight, functionalist theories basically argue the same and do not ascribe much, if any, real agency – and therefore power – to migrants. Push–pull and neo-classical gravity models (the latter borrowed from the natural sciences) basically assume that people will migrate if the benefits of migration exceed the costs. This reflects an implicit assumption that people are motivated by individual cost-benefit calculations aimed at income or utility maximisation and will therefore react in automatic, universal and predictable ways to external stimuli or ‘push’ and ‘pull’ factors. As already embedded in the very semantics of the ‘push’ and ‘pull’ terminology, which we therefore need to reject, this reduces people to objects who operate in a social vacuum and who lack a will, perceptions and preferences of their own as well as the ability to actively and subjectively choose between different options. Footnote 2 Functionalist theories and actor-focused empirical applications such as ‘agent-based modelling’, should, however insightful they can be, therefore not be misidentified as ‘agentic’ theories.

Conventional migration theories tend to ignore five vital issues with regard to migratory agency. First, people’s access to economic (material), social (other people), cultural (ideas, knowledge and skills) and bodily (good health, physical condition and habitus) resources shapes their ability to move (or, conversely, their ability to stay), their preferences and aspirations (to stay or to go), their choice in terms of destinations and their ability to obtain work, housing, education and legal status while protecting themselves against abuse and exploitation. Because of social hierarchies and structural inequality, such access to migratory resources tends to be unequally distributed within and across communities and societies.

Second, people’s perceptions of the ‘good life’ and, hence, their life aspirations, vary hugely across different social and cultural contexts. In addition, such aspirations are anything but fixed and tend to change as people move through their life course and as societies change. Depending on people’s subjective life aspirations as well as their (equally) subjective perceptions of opportunities ‘here’ and ‘there’, they may – or may not – develop a desire to migrate. It is therefore unrealistic to simply assume that dissimilar social groups will develop similar aspirations and tendencies to migrate even when exposed to similar set of external factors or stimuli or ‘push’ and ‘pull’ factors.

Third, people do not uniquely migrate out of an instrumental ‘means-to-an-end’ desire to achieve aspired levels of wealth or living standards but may also value migration for more intrinsic reasons – such as wanderlust, curiosity and an innate desire to break free and discover new horizons. This means that not only the ‘functional’ but also the intrinsic, subjective value which people ascribe to mobility should be given a serious place in migration theory. Across societies and throughout history, particularly young people have often harboured a strong desire to leave home – at least temporarily – for a variety of reasons, from the socio-psychological need to separate from their parents, proving their independence and as a rite de passage marking their transition to adulthood. ‘Gap years’ and working holidays are not necessarily a unique prerogative of privileged Western youth but can also be seen as a modern manifestation of a more universal intrinsic desire of many young people to move and discover the world – before settling down. Berriane et al. ( 2013 ), for instance, observed that quite a number of sub-Saharan migrants in Morocco frame their journey in terms of ‘adventure’ and the desire to try out life elsewhere and should not, therefore, be automatically crunched into the stereotypical categories of marginalised or ‘desperate’ economic migrants or refugees.

Fourth, conventional migration theories fail to incorporate mobility and immobility in the same conceptual framework. This is necessary because movement is as much the norm as is sedentary life – and many people experience both over their lifetime. Modern sedentary lifestyles assume residency – but changing residency requires migration. This implies that we need to embed our understanding of migration within broader theoretical frameworks that include non-migratory mobility and people’s desire to move as well as to stay put and have a place ‘to live’.

Last but not least, it is important to bridge the dichotomous divide between the study of voluntary and that of forced migration. While virtually all migrants face some level of constraint, ‘forced migrants’ also have some level of agency as, otherwise, they would not be able to move in the first place. Refugees exercise their agency as far as possible in even the face of appalling circumstances. It is only under extreme conditions such as slavery and deportation that agency may be discounted largely or completely (see de Haas 2009 ). Conversely, most migrants normally cast as ‘voluntary’ face considerable constraints. For instance, many migrants who primarily move for work do so because they face severe constraints on personal development at home and the range of migration options available to them tends to be limited by economic, political and social constraints.

The fact that all migrants face constraints challenges the conventional dichotomy between ‘forced’ and ‘voluntary’ migration. It appears, therefore, more appropriate to conceive of a continuum running from low to high constraints under which migration occurs, rather than applying a dichotomous classification of forced versus voluntary migration to much more complex realities in which all people deal with structural constraints, although to highly varying degrees. In this way, reductionist, dichotomous classifications between forced and voluntary migration (see also Richmond 1988 ) can be overcome or nuanced, in ways that enable us to integrate virtually all forms of migration into one overarching meta-conceptual framework.

Addressing these five challenges requires the elaboration of new concepts of human mobility that can simultaneously account for both agency and structure. However, this is easier said than done, and the crucial question is how to do this in practice . To achieve this, the following sections will argue how a meta-theoretical conceptualisation of migration as a function of aspirations and capabilities to move (1) expands the theoretical concept of human mobility to include movement and non-movement, (2) improves our ability to develop a richer and more realistic understanding of the ways in which macro-level change affects people’s migratory agency and (3) enables us to elaborate new, theory-derived migration and mobility categories.

Migration as a function of capabilities and aspirations

In 2002, Jørgen Carling published a seminal paper  exploring the role of aspirations and ‘abilities’ in migration processes. He introduced the concept of ‘involuntary immobility’ to describe the phenomenon of the growing numbers of people living in Cape Verde (and poorer countries more generally) who wish, but do not have the ability, to migrate (Carling 2002 ). Analysing the case of wartime migration in Mozambique, Lubkemann ( 2008 ) also applied the concept of involuntary immobility to argue that the usual conflation of migration with displacement conceals a large category of people who suffer from ‘displacement in place’ through ‘involuntary immobilisation’ because warfare trapped them in the places they wanted to leave. While this concept has been mainly applied to origin societies, involuntary immobility can also be used to describe situations in places of destination when aspiring return migrants cannot go back because of a lack of resources, border controls or adverse conditions in origin countries. It may also describe situations in which migrants ‘in transit’ are immobilised if they become ‘stuck’ as a consequence of a lack of resources, violence, border controls or a combination thereof (see Collyer et al. 2012 ).

The systematic distinction between the ability (or capability) and the aspiration to migrate allows for richer, nuanced and more realistic migration categorisations. This also resonated with my own fieldwork in south-Moroccan oases between 1993 and 1994 (de Haas 1995 , 1998 ) and between 1998 and 2000 (de Haas 2003 , 2006 ), which inspired me to develop alternative ways of theorising migration, because conventional migration theories struck me as somewhat useless in explaining the migration dynamics I observed. Particularly during my fieldwork in the south-Moroccan Todgha valley (de Haas 2003 , 2006 ), I was confronted with the following puzzle: despite significant increases in income and general living conditions over previous decades, out-migration from the Todgha valley to big cities in Morocco and, particularly, European countries like France, the Netherlands and Spain had continued unabated. This did not fit at all within neo-classical migration theories and push–pull models, which would have predicted decreasing emigration as a consequence of improved local living standards.

This inspired me to adopt the concepts of aspirations and capabilities as theoretical tools enabling me to better understand what I was observing (de Haas 2003 , 2006 , 2014b ). I argued that, although local living conditions had improved significantly in preceding decades, people’s general life aspirations had increased faster, leading to growing migration aspirations. Improved education, increased media exposure alongside the regular return of the migrant ‘role models’ and exposure to their relative wealth had all contributed to rapidly increasing material and changing social aspirations of people living in the valley. Particularly international migration had become so strongly associated with material and social success that many youngsters had become virtually obsessed with leaving. This ‘culture of migration’ also contributed to rapidly changing ideas of the ‘good life’ and an increasing disaffection with traditional, agrarian lifestyles. So, growing aspirations and capabilities to migrate had inspired and enabled increasing numbers of people to leave the valley despite, or paradoxically rather because of , significant improvements in local living standards, income and education.

The core argument of this paper  is that the fragmented insights from different disciplinary theories can be integrated into a single meta-theoretical framework through conceptualising virtually all forms of migration as a function of aspirations and capabilities to migrate within given sets of perceived geographical opportunity structures , in which

Migration aspirations are a function of people’s general life aspirations and perceived geographical opportunity structures.

Migration capabilities are contingent on positive (‘freedom to’) and negative (‘freedom from’) liberties.

The concept of migration aspirations expands the notion of migratory agency into the subjective realm. This addresses the central shortcoming of functionalist and historical-structural theories, which implicitly assume that people respond to external ‘stimuli’ in quite uniform – and therefore predictable – ways. In this view, migration aspirations reflect people’s general life preferences as well as their subjective perceptions about opportunities and life elsewhere. Both general life and more specific migration aspirations are thus affected by culture, education, personal disposition, identification, information and the images to which people are exposed.

Aspirations are conceptually distinct, although empirically not independent from, capabilities. A good example is education in rural areas, which expands not only people’s skills and knowledge but also people’s awareness of alternative, consumerist, urban or foreign lifestyles. This often changes people’s notions of the ‘good life’ and they may subsequently start to aspire to migrate, partly independently from ‘objective’ material conditions at home. However, education may also increase aspirations in a different way, because it may prompt teenagers and young adults to start thinking that these new material and cultural lifestyles are actually within their reach – reflecting the notion of the ‘capacity to aspire’ (Appadurai 2004 ; see also Czaika and Vothknecht 2012 ). In this way, increasing capabilities can increase aspirations. Generally, preferences tend to change and material and consumerist aspirations tend to increase along with broader processes of social transformation usually associated with capitalist development and modernisation (see de Haas et al. 2020b ). However, the extent to which changing preferences translate into migration aspirations depends on the degree to which people perceive that their subjective needs and desires can be fulfilled locally. However, in general, increased access to new ideas through education and the media tends to change people’s ideas about the ‘good life’ in such a way that it increases their desire to explore new horizons and move out of rural places towards towns and cities or foreign lands.

The vital intrinsic dimension of migration aspirations

It is essential to distinguish the (1) instrumental and (2) intrinsic dimensions of migration aspirations. ‘Gap years’ and ‘lifestyle migration’ can be examples of the latter, while labour and student migration are examples of the former although, in practice, intrinsic and instrumental aspirations may occur simultaneously and often reinforce each other. Instrumental aspirations have received the most attention in research and are related to migration as a ‘functional’ or ‘utilitarian’ means to achieve another end, such as a higher income, higher social status, better health care, better education or, in the case of refugees, protection from persecution and violence. Intrinsic aspirations refer to the value which people may attach to the migration experience in and of itself, such as the joy and pleasure derived from exploring new societies, seeing the ‘bright lights’ of the city (Harris and Todaro 1970 , p. 126), or experiencing the social prestige linked to proving oneself and enduring the suffering and taking the risks often associated with migration – to be subsequently seen as a ‘man (or woman) of the world’ or the social status, recognition and respect that usually comes with the ability to provide for the family.

People can also derive wellbeing from having potential  access to mobility freedom, irrespective of whether people use these freedoms or not . The central idea is that the very awareness of having the freedom to move and migrate can add to people’s life satisfaction, in the same way that freedom of speech and religion, the right to organise protest marches or to run for office can contribute to people’s wellbeing, irrespective of whether or not they eventually use those freedoms. Conversely, if people do not enjoy such freedom, they are likely to experience this as a form of wellbeing-decreasing deprivation. For instance, many young Moroccans describe their country as a ‘prison’ because of European migration restrictions. In Carling’s ( 2002 ) terms, they feel stuck in involuntary immobility. This does not mean that they will all migrate if given the opportunity but the feeling of deprivation is real.

So, border walls or other migration restrictions might actually fuel the desire to get to the other side by creating an obsession with ‘getting out’ as soon as the opportunity presents itself, while full mobility rights might paradoxically decrease such aspirations. Before Spain introduced travel visas for Moroccans in 1991, it was common for young Moroccan adults to spend a few (summer) months or years in Spain, often with mixed motives of tourism, pleasure and work. The introduction of visa requirements largely cut off such free circulation, created a market for smuggling and increased the tendency to stay longer for those who still managed to get in – which encouraged the increasingly permanent settlement of Moroccans in Spain (de Haas 2014a ). While numerous empirical studies have indicated that most people would prefer to stay home and many migrants wish to return to their countries of origin, the irony is that the very deprivation of mobility freedom or the expectation of the future tightening of migration regimes may actually encourage non-migrants to get moving (before it is too late) and for migrants to cancel return plans (out of fear of not being able to migrate again).

This is what Vezzoli ( 2015 ) observed in her comparison of migration patterns from Suriname, Guyana and French Guyana, three neighbouring countries located in South America. Guyana and Suriname became independent from Britain and the Netherlands in 1966 and 1975, respectively. French Guyana is a French département and, as a consequence, its inhabitants are full French citizens. The paradox is that more than half of the population of Guyana and Suriname live abroad despite – or paradoxically partly because – migration restrictions imposed by their former colonisers and other destination countries, as this has contributed to an obsession with ‘getting out’. In contrast, the French Guyanese tend to have a more relaxed attitude towards emigration because, as French citizens, they have full mobility rights. Apart from better social security and living conditions, this partly explains why emigration has remained at quite low levels (Vezzoli 2015 ).

Life aspirations can thus often include mobility freedom as an intrinsically valuable and wellbeing-enhancing right, experience and awareness. This intrinsic dimension of migration aspirations is not taken seriously in the predominantly ‘functionalist’ migration literature, or it is set apart as an entirely and essentially different category of migration – e.g., ‘lifestyle migration’ (Benson and O’Reilly 2009 ). We do know from empirical research, however, that intrinsic ‘adventure’ and ‘lifestyle’ motives are not the prerogative of privileged Europeans or North Americans but can also be common among other migrant groups, such as undocumented migrants in England (Bloch et al. 2011 ) or African migrants crossing the Sahara (see Berriane et al. 2013 ; Bredeloup 2008 ; Pian 2009 ). This highlights the need to put the intrinsic dimensions of mobility freedom centre stage when theorising migration.

Migration as freedom

Although not developed to analyse migration, Amartya Sen’s ( 1999 ) capabilities approach, which he proposed to reconceptualise ‘development’, provides useful conceptual tools that can also be fruitfully applied to analysing migration , as it helps us to simultaneously grasp the instrumental and intrinsic dimensions of migration capabilities and aspirations as well as to conceptualise how migration is an intrinsic part of broader development and change. Based on his critique of narrow, income-focused definitions of development, Sen ( 1999 ) conceptualised development as the process of expanding the substantive freedoms that people enjoy. He operationalised this through the concept of human capability , which he defined as the ability of human beings to lead lives they have reason to value and to enhance the substantive choices they have. Sen  argued that income growth itself should not be the litmus test for development theorists but the question whether the capabilities (or freedoms) of people to control their own lives have expanded. Sen posited that freedom is central to the process of development for two reasons. First, there is the intrinsic importance of human freedoms in directly adding to people’s quality of life, which has to be distinguished from the second, instrumental , value of freedoms in also contributing to human and economic progress (Sen 1999 ).

I initially applied Sen’s capabilities approach to the study of migration to evaluate the development impacts of migration and remittances in origin communities, not only in terms of income, but also in terms of wellbeing-enhancing improvements in living standards. Yet I disovered that the capabilities approach was also a valuable concept to understand how, conversely, processes of social transformation and development shape migration (de Haas 2003 , 2006 , 2010a ). Changes in economic, social, cultural and political conditions in origin areas may affect migration propensities in two different ways. First, economic growth and improvements in living standards are likely to increase people’s migration capabilities by increasing their ability to assume the costs and risks of migrating. Second, the extent to which local opportunities allow people to lead the lives they have reason to value (which reflects Sen’s definition of development) at home is also likely to affect their migration aspirations.

Thus, by applying Sen’s capabilities approach to migration, we can learn to see migration not only as an instrumental-functional means-to-an-end to improve people’s living conditions but also as a potentially wellbeing-enhancing factor in its own right. This alludes to the intrinsic, wellbeing-enhancing (non-instrumental and non-utilitarian) dimension of migration and this, at a philosophical level, also expands our understanding of mobility not so much as the act or capability of moving but as the ability to decide where to live, including the option to stay at home . Based on this definition, people may enjoy mobility freedoms without ever using them, while migration can only be seen as genuinely wellbeing-enhancing and empowering if people also have the option to stay. This distinction between the intrinsic and the instrumental dimensions of migration enables us to go beyond common functionalist, instrumentalist views on migration, in which:

the intrinsic dimension of migration is the direct contribution of the freedom of mobility to people’s wellbeing, irrespective of whether they move or not (‘migration as freedom’). It relates to (particularly young) people’s innate desire for adventure, discovery and separation from (the parental) home for shorter or longer periods as well as to the intrinsic wellbeing derived from the awareness of having the optional freedom to move. Such freedoms do not have to result in actual movement in order to be enjoyed: it is the very awareness of having the option – or freedom – of staying or going where one wants that matters most;

the instrumental (functional, means-to-an-end) dimension of migration reflects the role of migration as a way to achieve other personal or family goals such as increased income, education, living standards or, in the case of refugees, personal safety. While people need a certain level of capabilities to be able to migrate, migration can further increase such capabilities. This corroborates the idea that migration is often quite literally an investment of families and individuals in a better future rather than a ‘desperate flight from misery’ as dominant discourses on migration often tend to frame it.

Usually, migratory agency is associated with the act of moving and setting up residency in another place or country. This reflects, however, a one-sided view since, after all, real agency also involve the option to not act (see Emirbayer and Mische 1998 ), as long as a real choice is present. A truly agentic view on migration should therefore capture both non-migratory and migratory behaviour. There is a long-standing controversy in the migration literature about whether migration or sedentary behaviour is the norm. The first argument is that migration is a universal part of the human experience and that we tend to erroneously misrepresent past societies as largely ‘immobile’, with migration being the ‘normal’ pattern. The second argument is that most people, if given the choice, prefer to stay at home (the ‘home preference’) and that migration is in fact rather limited in magnitude if we consider the huge economic inequalities across the globe.

Yet from a theoretical point of view this debate seems somehow futile. First, a truly agentic view on migration does not presume either moving or moving as the norm but, rather, acknowledges that they are two sides of the same freedom-of-mobility coin. Second, at both the practical and the conceptual level, migration is only a meaningful and relevant category in the context of sedentary lifestyles (as the concept of migration implies a change in residence). The lifestyles and livelihoods of hunter-gatherers and nomads are often characterised by permanent mobility and a lack of permanent residence – which renders a category like migration rather obsolete and meaningless. So, migration presumes sedentarism as much as sedentarism presumes migration. The residential lifestyles of both agrarian and capitalist-industrialised societies have thus ‘created’ the need for migration as a continuous adaptive response to social change and social transformation as well as a linguistic and conceptual category.

Third, considering that people make migration decisions as members of social groups, migratory and sedentary behaviour are often interrelated. For instance, one of the strengths of new economics of labour migration (Stark 1978 , 1991 ) is the idea that migration is a strategy by rural households to diversify their income portfolio through the migration of one or a few family members. This means that there is often a strong co-dependency between non-migrant and migrant family members. This implies that migration matters to most of us, whether we move or not. Although only about 3% of the world’s population has migrated across borders and a roughly estimated 12% within borders (de Haas et al. 2020a ), most people in the world are affected by migration in direct or indirect ways, either through family and other social ties or through the impacts of migration on origin and destination societies more in general.

Redefining human mobility

Migration and sedentary behaviour are thus interconnected. We therefore need a truly agentic understanding of human mobility that can simultaneously capture movement and non-movement. Following Sen’s general argument on the intrinsic wellbeing-enhancing value of human freedoms, we should therefore also conceptualise the very capability to move (migrate) as a fundamental human freedom. To capture the idea of migration as a freedom in its own right, we should define human mobility not by the criterion of actual movement but as people’s capability (freedom) to choose where to live – with migration as the associated functioning (see also de Haas 2009 ; de Haas and Rodríguez 2010 ). Essentially, human mobility thus includes the freedom to stay, which we can classify as voluntary immobility (contrasting Carling’s ( 2002 ) concept of involuntary immobility ).

This is related to the concept of capabilities in two different ways: first, people need access to social (other people), cultural (ideas, knowledge and skills Footnote 3 ) and economic (material) resources if they are to exert migratory agency. Under highly constrained conditions of poverty and oppression, people often lack the resources to leave. Second, if people have no realistic option to remain – for instance through war, persecution, deportation or eviction by governments – or if they are pressured by their families to work abroad, they may feel deprived of an essential part of their human mobility freedoms, which is the option to stay. Conversely, if people feel deprived of the capability to move, the concomitant frustration of being ‘trapped’ may fuel migration aspirations and can even create an obsession with ‘getting out’.

Drawing on the capabilities–aspirations framework, Table  1 elaborates a theoretical categorisation of five ideal-typical individual mobility types. Based on our new definition of mobility as ‘people’s capability (freedom) to choose where to live, including the option to stay’, this categorisation of mobility types also includes various forms of immobility . This enables the theoretically desirable inclusion of both movement and non-movement within the same conceptual ambit as manifestations of the two sides of the same freedom-of-mobility coin.

This categorisation builds upon Carling’s ( 2002 ) ‘involuntary immobility’ concept but expands with four other mobility types. It acknowledges a reality in which (cultural) preferences, aspirations and capabilities are deeply affected by macro-structural factors. It is only possible to speak about the ‘voluntariness’ of mobility or immobility if there was a reasonable option to stay. That does not mean that refugees and other groups of ‘distress migrants’ do not have any agency (otherwise they could not have moved in the first place), but that their migration is forced to the extent that they have been deprived of mobility freedoms; they had no real option to remain as that would have put them in serious danger of being persecuted, injured or murdered. For refugees, migration is primarily a response to severe danger at home rather than a positive response to opportunities elsewhere. Obviously, once a decision to leave has been made, such opportunities will play a role in deciding how, when and where to go and people will try to exert their agency as much as possible, although they cannot be conceptualised as the main reason to migrate. Thus, refugees are forced migrants because they had no option to remain.

Similarly, migrants who may be classified as ‘voluntary return migrants’ by governments or international organisations may only be ‘willing’ to return not out of a real, intrinsic desire to do so but because they either have no access to social amenities and shelter or they risk imprisonment, violence and other abuse (such as separation from their children) in destination countries. Under such situations of extreme distress and pressure, migrants may eventually decide to return and be compelled to sign forms confirming consent to their ‘voluntary repatriation’, even if this is against their own intrinsic preferences or desires (see Cleton and Chauvin 2020 ). Boersema et al. ( 2014 ) referred to this category as ‘soft deportation’. From a theoretical perspective, we can classify this as ‘involuntary mobility’. Even if such migrants are not literally forced to move (i.e., by violent means through deportation) they may, under severe threat, feel compelled to move even if is this strongly against their own intrinsic desire. The categories ‘voluntary mobility’ and ‘voluntary immobility’ only apply to people who have the capability to migrate but also have a reasonable option to stay (with the term ‘reasonable’ implying that this would not put them in dangerous, highly exploitative or life-threatening situations) and for whom the decision as to whether or not to go is primarily affected by their (instrumental or intrinsic) migration aspirations.

A final category concerns people with low capabilities and aspirations to move. How can we categorise a person living in poverty, who is neither able to migrate nor has ever imagined doing so? Based on the idea that capabilities affect aspirations (Appadurai 2004 , see also Czaika and Vothknecht 2012 ), we may perhaps say that this person is deprived of the capability to aspire as well as the capability to move. This raises the philosophical question as to what extent we can call this form of immobility “voluntary”? Schewel ( 2015 , 2020 ) therefore proposed the category of acquiescent immobility to describe situations in which people are neither able to migrate nor desire to do so. Schewel argued that because ‘acquiescent’ implies an acceptance of constraints (the Latin origins of the word meaning ‘to remain at rest’) this may be an appropriate term to describe this mobility category. However, we clearly need more research on the formation of aspirations to move or to stay and on the extent to which decisions to stay can indeed be seen as ‘acquiescent’ or, rather, reflect a post-hoc rationalisation of mobility deprivation.

Positive and negative liberty as manifestations of structural conditions

As argued thus far, the capabilities approach enables us to conceptualise human mobility (people’s freedom to choose where to live) as a wellbeing-enhancing capability in its own right (‘migration as freedom’). In order to further enhance our understanding of how these individual migration capabilities and aspirations are shaped by, and interact with, macro-structural processes, it is useful to draw on the distinction between positive and negative liberties made by Isaiah Berlin and to apply it to the study of migration. In his Four Essays on Liberty , Berlin ( 1969 ) made a fundamental distinction between negative and positive liberty (or freedom). In brief, the concept of negative liberty refers to the absence of obstacles, barriers or constraints. This comes close to popular ways of conceiving freedom, which often focus on the role of governments in imposing constraints on people’s freedom or even being an outright threat to people’s lives, for instance through regulation, oppression, violence or war. Positive liberty refers to the ability to take control of one’s life and to realise one’s fundamental purposes. As Berlin argued, positive liberty ‘derives from the wish on the part of the individual to be his own master’ (Berlin 1969 , p. 131). While Berlin’s argument focused on people’s role in choosing who governs society, this concept is also applicable to the ability – or agency – of people to actively change their life circumstances. Berlin’s concept of positive liberty therefore comes very close to Sen’s concept of capabilities as people’s ability to enhance the substantive choices they have.

The twin concepts of negative and positive liberties provide a useful conceptual link between the macro-structural conditions which shape these liberties on the one hand and people’s individual aspirations and capabilities – concepts which embody choice and agency but which are ultimately constrained by these structural conditions – on the other. From this perspective, the absence of external constraint (negative liberty) is not a sufficient condition for people to exert migratory agency, because they need a certain degree of ‘positive liberty’ that will enable them to enjoy genuine mobility freedom – which implies a real choice about where to live. For instance, governments may grant nominal freedom of movement but poor people may still lack positive liberty in the form of capabilities and access to resources that would enable them to actually use such negative liberty.

People may aspire to flee situations of poverty, distress and danger but they still need certain ‘positive liberties’ (capabilities) in the form of resources such as money, social connections, knowledge and physical ability, in order to be able to flee. The most vulnerable populations may not, therefore, have the option to flee and may be trapped into ‘involuntary immobility’. Poor people often only migrate if forced by conflict or disasters – and then mainly move over short distances – while the most vulnerable are often deprived of the possibility to move at all. For instance, when Hurricane Katrina hit New Orleans in 2005, many of the (car-less) poor were trapped in the city (Gemenne 2010 ; see de Haas et al. 2020a , p. 37). In the civil conflict that broke out in Libya in 2011, hundreds of thousands of guestworkers from sub-Saharan Africa were trapped in the country and exposed to abuse, violence, imprisonment and sometimes murder. In contrast to high-skilled migrants from European or other powerful states, they were immobilised because they lacked the resources and connections to move out (de Haas and Sigona 2012 ). This insight has important consequences for the way we analyse migration. For instance, scenarios that predict massive international migration as a result of climate-change are rather unrealistic partly because they ignore evidence that the most vulnerable populations who are most at risk to be negativelly affected by climate change generally lack the resource to move over large distances. In fact, deprivation as a result of climate change-driven environmental change (such as an increased incidence of droughts or flooding) may  deprive them from the capabilties to go elsewhere and therefore immobilize them in situ (see Foresight 2011 ; de Haas 2020 ).

This perspective helps us to understand the complex, often non-linear and frequently counter-intuitive ways in which macro-structural processes of social transformation shape trends and patterns of migration, because negative and positive liberties often impinge in quite different ways – and sometimes opposite directions – upon migration aspirations and capabilities. This renders the analysis of the effects of macro-structural conditions on migration patterns far from straightforward: although the deprivation of negative and positive liberties and awareness of better opportunities elsewhere may increase people’s migration aspirations, the absolute deprivation of the same negative or positive liberties, or both, may prevent people from exerting migratory agency. Conversely, while increases in negative and positive liberties may increase people’s mobility freedom, this does not necessarily lead to more migration as, under such conditions, more people may also be able to realise their intrinsic preference to stay through an increased ability to meet their life aspirations at home. Likewise, as we have seen, increasing mobility freedoms through the liberalisation of migration regimes may paradoxically decrease long-term, permanent emigration as it may take away people’s obsession with ‘getting out’.

The structural formation of migration aspirations and capabilities

Figure  2 depicts the various ways in which life aspirations and capabilities are affected by structurally determined positive and negative liberties and how these may affect mobility freedoms and people’s migration decisions. Negative liberty affects both people’s life aspirations and capabilities; the interaction between these factors explains complex, sometimes counter-intuitive migration outcomes. For instance, while it may seem likely that political oppression and violence will increase migration aspirations, the same factors may also deprive people of the capability of moving – such as through exit restrictions – or actually prompt them to stay so that they can protect family and community members. The concepts of negative and positive freedom therefore enable the incorporation of the role of states and policies in migration theories. From this perspective, mobility deprivation can happen either through negative liberty deprivation – for instance when authoritarian states deprive their citizens of the right to leave – or through positive liberty deprivation – when people lack the access to social, cultural and economic resources needed for realising migration aspirations.

Expanded aspirations–capabilities framework for conceptualising migratory agency

Positive liberty primarily affects people’s capabilities in the form of their access to social, economic and cultural resources or ‘capitals’. Indirectly – and drawing on the notion of the ‘capacity to aspire’ (Appadurai 2004 ; Czaika and Vothknecht 2012 ) – increased capabilities are also likely to increase aspirations, by (1) making people aware of alternative opportunities and lifestyles and by (2) making people believe that migration is ‘within their reach’, that they can actually ‘make it’. For instance, acquiring a school or university degree is likely not only to increase knowledge about opportunities elsewhere but also to instil the belief and self-confidence that it is actually possible to find a job, to live in a strange place or to secure a visa.

Embracing a more ‘modern’ lifestyle, with its concomitant increase in perceived material needs, only prompts aspirations to migrate if people believe that their life goals cannot be fulfilled locally within the foreseeable future and if they believe that better opportunities exist elsewhere. Elaborating on Hirschman’s ( 1978 ) ‘exit or voice’ hypothesis we can argue that, if people are discontent, they can either try to change these circumstances (by raising their voice), consent (acquiesce) or leave. Thus, the imagined opportunities for future local change and people’s belief in their own power and moral obligation to contribute to such change will affect the extent to which increased life aspirations will translate into migration aspirations. A mismatch between personal life aspirations and conditions at home do not therefore necessarily translate into migration: they can also be fulfilled at home – for instance by starting up a business, pursuing an education, joining political movements or taking up arms. It only translates in migration aspirations if people lack, or lose, belief in future local change.

In order to simultaneously incorporate structure and agency migration theory, we need to connect both concepts and conceptualise their dialectics. In this respect, ‘structure’ is often unilaterally seen as a set of constraints. However, this is too limited a view. Essentially, structures are about patterns – or regularities and repetitions in social relations and social behaviour. Structures thus simultaneously constrain the migration of particular social groups while facilitating the migration of other groups along very specific geographical and social pathways. For instance, states and their policies have a strong structuring effect on migration, which means that they can facilitate and actively stimulate (particularly through recruitment) the movement of some (national, age, gender, skill, class and ethnic) groups while simultaneously hindering the movement of others.

Government policies, recruitment and other macro-structural factors thus shape socially differentiated, highly specialised and geographically bundled pathways (also known as ‘migration corridors’) linking very particular social groups and places over space. Once such initial patterns are set, migrant networks, feedback processes known as ‘cumulative causation’ (Massey 1990 ) and various other ‘internal dynamics’ (de Haas 2010b ) tend to give migration processes their own momentum and thereby reproduce such patterns, giving migration an “identifiable geographical structure that persists across space and time” (Mabogunje 1970 , p. 12). However, notwithstanding the importance of such internal dynamics in perpetuating migration and the consolidation of migration systems, the crucial point is that governments, employers and recruiters often play a key role in setting initial migration patterns that are subsequently reproduced over space and time.

The entire set of structural conditions at home and in imagined migration destinations creates complex opportunity structures, endowing different individuals and social groups with various sets of negative and positive liberties, which, depending on how these structural conditions affect people’s capabilities and aspirations and how people perceive these conditions through their social, cultural and personal lenses, may, or may not, make them decide to migrate. In turn, such migratory agency reciprocally affects these structural conditions through various feedback effects, which may stimulate more migration over the paths beaten by initial (pioneer) migrants (de Haas 2010b ).

The aspirations–capabilities framework therefore enables us to explain why social transformation or ‘development’ is initially associated with increasing migration levels (see Skeldon 1990 , 1997 , 2012 ; de Haas 2007 , 2010c ). Particularly if regions or countries transform from a low-income, agrarian and peripheral status to a middle-income, industrialising and urbanising status, migration aspirations and capabilities both tend to increase rapidly, explaining the paradox of development-driven emigration booms. As long as people’s ideas of the ‘good life’ (generally away from traditional rural-agrarian lifestyles Footnote 4 ) and the associated growth in material aspirations change faster than and outmatch local opportunities, this typically leads to growing migration propensities.

Only in the longer term, when local opportunities start to increasingly match aspirations, can we expect migration propensities to go down. While such capabilities and aspirations manifest themselves at an individual level, they are ultimately shaped by macro-structural changes such as the expansion of infrastructure, education and the media. This exposes the potential of the aspirations–capabilities approach to link macro-structural change processes to individual perceptions, experiences and agency with regards to migration decision-making.

Towards new migration categories

As manifestations of structural conditions, the concepts of positive and negative liberty are also useful in operationalising ‘structural conditions’. This enables the development of a four-pronged typology of migration categories as presented in Table  2 , which represents an ideal-typical categorisation of concrete manifestations of migration under different contextual configurations of relatively high and low positive and negative liberty. Table 2 also indicates the explanatory relevance of some of the main migration theories for these different contextual migration categories.

The categorisation presented in Table 2 is tentative and would benefit from further elaboration, verification and refinement. This main purpose of this effort is not to propose a ‘definitive’ categorisation of migration but, rather, to illustrate how the meta-theoretical framework presented in this paper can be helpful in developing a more systematic way of ‘contextualising’ the assumptions of the different theories and, in so doing, achieving greater precision when specifying the varying applicability of different theories. This exemplifies my position that theoretical assumptions should be seen as contextualised statements (or generalisations) rather than mutually exclusive truth claims.

As mentioned earlier, ‘neo-classical’ theories have a relatively higher relevance to explain the more or less free migration of relatively well-off people, under relatively unconstrained conditions characterised by high levels of positive and negative liberty. In their turn, neo-Marxist and other historical-structural theories may be comparatively more powerful in understanding and interpreting the precarious migration which takes place under highly constrained conditions – such as migration restrictions or the lack of state protection against abuse and discrimination. Such constraints reduce the agency of migrants, making them more vulnerable to exploitation by employers, recruiters, state agents or smugglers – and often frustrate their attempts to achieve upward socio-economic mobility through study and work. This can apply to both impoverished labour migrants and the majority of people forcibly displaced by conflict, disasters or persecution who lack the means and contacts to move over large distances. Although they had the resources and the ‘positive liberty’ to leave, they are at high risk of becoming trapped or ‘involuntarily immobilized’ along the journey or at the destination, deprived of the resources and freedom to continue the journey or to return.

In the category of improvement migration , people have relatively low levels of positive liberty (such as manifested by limited financial resources) but face relatively high negative liberty (such as manifested by access to legal migration opportunities and residency in wealthier countries) – which creates the conditions under which migration can be a successful way of achieving upward socio-economic mobility. For instance, recruitment programmes have historically given relatively poor people access to work opportunities abroad, thus fitting within dual labour-market theory (Piore 1979 ). Under other circumstances, family members often pool their resources to invest in the migration of one or more family members. This seems to fit with the assumptions of the new economics of labour migration (NELM), which conceptualises migration as a risk-sharing strategy by households aiming to diversify their income, generate remittances and improve the long-term wellbeing of the family (Stark 1978 , 1991 ). Theories on the internal dynamics of migration processes (Massey 1990 ; de Haas 2010b ) help to explain how migration often facilitates further migration through cost- and risk-lowering network effects. This explains the partial self-perpetuation of such migration even after recruitment has stopped and the original causes of migration such as labour demand have fallen away. This set of theoretical explanations seems to apply, for instance, to Mediterranean ‘guestworkers’ who were initially recruited to work in North-West European countries in the post-WWII decades as well as to Mexican migrant workers who were recruited to work in the US through Bracero programme between 1942 to 1964.

In other situations, people may face high levels of external constraint (negative liberty, such as through oppression, persecution or violent conflict) but still manage to migrate through their access to financial, social and human resources (positive liberty). Examples of this category could include skilled and/or relatively well-off refugees who are actually able to make it to other countries and obtain legal residency. This category, which I have tentatively named distress migration is a form of forced migration that needs further elaboration because existing migration theories seem to apply less easily to this category – reflecting the low level of theorisation of refugee migration. However, based on our definition of human mobility as the capacity to choose where to live, refugees are thus forced migrants because they have no reasonable option to stay even though they have some degree of agency in terms of having the resources and capacity to escape, move to another country and choose where to go.

There seem to be two basic ways of conceptualising ‘forced mobility’ – either as a conscious act to escape external threats and oppression (negative liberty deprivation) or livelihood insecurity and poverty (positive liberty deprivation) or as a literally forced mobility – such as through eviction, deportation or enslavement. In the first case, migrants still have agency and migration can be instrumentally or intrinsically voluntary; in the latter case, agency is entirely ruled out. For distress migrants, the existence of certain positive liberties – for instance speaking the host country language, having family already residing in the country, having the means to pay for a journey that is farther from home – can further increase both their aspiration and capabilities to migrate. Footnote 5 While ‘distress migrants’ have some level of positive liberty and agency (or capability) over where they choose to go, ‘precarious migrants’ lack such resources, generally move over short distances, are more likely to get stuck in situations of ‘involuntary immobility’ and are more vulnerable to exploitation and extortion by state agents, employers or smugglers.

While Table 2 gives an indication of which migration theories seem the most relevant and the ‘best fit’ for these migration categories, it does not mean that each theory exclusively applies to that category but, rather, to where they seem to have the strongest explanatory power. As I argued earlier, there is considerable leeway to combine theories, particularly when applied to different levels of analysis. As argued above, although much migration of less-skilled workers may appear to be exploitative from a macro-structural point of view (fitting historical-structural theory), it may often still be beneficial from the point of view of individual migrants and their families (fitting neo-classical or NELM theories). Migrants may also shift categories over time – for instance if a restrictive turn in policies or increasing racism turns ‘improvement migration’ into ‘precarious migration’, while the reverse may, for instance, apply if ‘precarious migrants’ get access to legal status through regularisation campaigns. The applicability of these categorisations also depends on the type of migration. For instance, the same person may have the positive and negative liberties enabling her to migrate internally but lack the resources and access to documents enabling her to migrate across borders.

This paper has elaborated an aspirations–capabilities framework to advance a new, comprehensive understanding of human mobility as an intrinsic part of broader social transformation processes. Drawing on previous work (Carling 2001 , 2002 ; de Haas 2003 , 2009 ) on aspirations and capabilities, this paper has expanded these concepts and embedded them in the wider theoretical perspectives on capabilities in development theory offered by Sen ( 1999 ) as well as the distinction between negative and positive liberty posited by Berlin ( 1969 ). While neither Sen nor Berlin developed these concepts to explain migration, this paper has argued that they can be fruitfully applied to migration to provide a richer, more agentic and realistic understanding of migration processes. Arguing in favour of conceptual eclecticism to bridge disciplinary and paradigmatic divides, this paper has shown the conceptual exigency and theoretical benefits of conceiving migration as an intrinsic part of broader processes of social transformation. Such a conceptualisation requires the embedding of the analysis of migration into general theories of societal change without reverting to the top-down causal determinism of conventional (historical-structural or functionalist) migration theories.

Except for extreme situations like slavery and deportation, migrants are neither passive subjects nor actors who react in automated and uniform ways to sets of ‘push’ and ‘pull’ factors – whether these be the macro-forces of global capitalism, wage gaps, violence or environmental stress. In order to migrate, people need to take the active decision to move and have the resources to do so. While historical-structural theories tend to portray migrants as passive pawns or victims of the forces of global capitalism, neo-classical and other functionalist migration theories implicitly assume that people’s preferences and, hence, life aspirations are constant across societies and over time, mostly boiling down to individual income (or ‘utility’) maximisation. This reveals that functionalist migration theories, despite their guise as ‘actor-focused’ models, are socially sterile and devoid of any real sense of agency, as individual choices are supposed to be entirely predictable outcomes of individual cost–benefit analyses based on fixed, static sets of assumed preferences.

The crucial flaw in this type of thinking is the assumption that people’s perceptions and preferences are (1) driven by individual utility maximisation; that (2) people’s preferences are uniform across societies and that (3) such preferences are static. So, in various ways, conventional migration theories all tend conceptualise migrants as persons being ‘pulled’ and ‘pushed’ like atoms by somewhat abstract economic, political, demographic or environmental causal forces. This ignores the fact that factors such as culture, education and exposure to media and other sources of images, ideas and knowledge are likely to have a huge impact on (1) people’s preferences and notions of the ‘good life’ and, hence, personal life aspirations, as well as (2) their knowledge, awareness and perception of opportunities ‘here’ and ‘there’.

This paper has argued that we can achieve a more meaningful understanding of agency in migration processes by conceptualising migration as a function of aspirations and capabilities to migrate within given sets of perceived opportunity structures. On this basis, we can define human mobility as people’s capability (freedom) to choose where to live – including the option to stay – rather than the act of moving itself. Moving and staying then become complementary manifestations of the same migratory agency. This conceptualisation enables us to move beyond the futile debate over whether migration or sedentary behaviour is the norm, since a truly agentic view on migration does not presume either moving or staying as the norm, but acknowledges that they are two sides of the same freedom-of-mobility coin. This enables us to overcome dichotomous and simplistic classifications such as between forced and voluntary migration and to integrate the analysis of most forms of migratory mobility within one meta-conceptual framework.

The application to migration studies of Sen’s ( 1999 ) capabilities perspective on development creates the conceptual space to achieve a deeper understanding of the role of capabilities in shaping migration aspirations as well as to make a vital analytical distinction between the instrumental and the intrinsic dimensions of human mobility. In order to acquire a more systematic understanding of the dialectics between structure and agency in migration processes, Berlin’s ( 1969 ) distinction between positive and negative liberties is a useful theoretical tool to elaborate a more structured, systematic and contextualised view of how macro-structural change processes affect people’s aspirations and capabilities to migrate in complex, non-linear and frequently counter-intuitive ways.

The resulting framework creates significant scope for improved theoretical synthesis by integrating different migration theories under one meta-conceptual umbrella. Instead of being mutually exclusive, within this alternative vision different migration theories have various degrees of explanatory power to understand various forms of migration occurring under specific conditions, among particular social groups and migrant categories and at various levels of analysis. This exemplifies the broader argument of this paper, which posits that, in migration theory specifically and social theory more generally, theoretical assumptions should be seen as contextualised statements rather than as mutually exclusive truth claims.

While this paper is hopefully useful in the much-needed effort to elaborate a more comprehensive, contextualised and integrated theorisation of human mobility, significant additional conceptual work remains to be done. For instance, considerable theoretical progress can be achieved by further embedding migration studies within broader theories of social change. This can, for instance, be done through applying insights from fields such as social psychology and behavioural economics. Research in such fields has yielded advanced insights into people’s (often non-rational) behaviour and factors that may affect migration aspirations but have rarely been applied to migration studies. Significant progress can also be achieved by integrating social-scientific and historicising approaches to studying migration. While social-scientific perspectives on migration could benefit from a better historisation and the adoption of longue durée perspectives, historical studies of migration could benefit from the adoption of social-scientific perspectives and theories to elaborate improved explanatory accounts of historical migration trends – for instance through adopting historical comparative methods (see Vezzoli 2015 ). Footnote 6 More generally, as the world and social realities are constantly changing, no social theory will ever be ‘final’, as ongoing processes of social transformation will perpetually create the need for theoretical innovation in order to make sense of these changing realities and the diverse ways in which people give meaning to them.

Future theoretical work can help us to address several remaining conceptual puzzles. For instance, we may wonder to what extent we can really separate intrinsic from instrumental migration aspirations, as they often seem conflated in practice. After all, what appears to be an intrinsic and subjective desire for adventure and the discovery of new horizons could, at least subconsciously, also fulfil a ‘functional’ role in the psychological separation-individuation process of adolescents and young adults, as a way to acquire new knowledge, meet future partners, find a job and establish independence. Conversely, what appears to be a move abroad to earn more money can be difficult to separate from the social prestige which successful migration – particularly when it initially involves significant risks and courage – can bring, particularly in communities where migration has become a rite de passage and is cast in positive cultural-normative ways.

Another, related conceptual puzzle is that of voluntariness. To what extent can we classify migration as voluntary if a migrant does not want to move but does so for the sake of the long-term economic future of the family? Perhaps we can argue here that such a migrant has no intrinsic desire to move but that the decision to move still emanates from an autonomous decision and real willingness to sacrifice short- to medium-term individual wellbeing (for instance, being separated from loved ones or being deprived of sexual relations or the alienating experiences of living in a strange and sometimes hostile society) from the (instrumental) wish to improve the long-term wellbeing of the family (presumably after return or family reunion). However, what if family members are put under immense social pressure to migrate against their own intrinsic desire? This could for instance apply to labour migrants who move abroad to work because of their family’s social expectations, although they may personally resent this; but it can also apply to adolescents sent to boarding school abroad by their affluent parents. What, therefore, can we say about children and adolescents who often have little input into the mobility decisions of their parents and who may feel that they are ‘moved around’ as if they were a piece of luggage. We cannot ignore the considerable emotional stress and social costs implicated in the loss of friends, a familiar environment, alienation and the constant need to adapt to new situations, even if they live a life of material privilege. This begs the question as to whether we can conceptualise such children as forced migrants.

This highlights the inherently blurred lines between the concepts of ‘voluntary’ and ‘forced’ migration. There are parallels with similar debates, such as those on the difficulties in conceptualising forced versus voluntary marriage (see Enright 2009 ). In such situations there is often a conflict between the desire to be a member of social groups for psychological and social-security reasons on the one hand and the personal drive towards autonomy on the other. This shows the importance of developing conceptual tools that can help us to gain more nuanced understandings of the interaction between structure and agency in social action. This also suggests that the aspirations–capabilities framework developed in this paper can be useful for other domains of social theory.

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This paper does not use any primary research data, and is fully based on other publications and the author’s analysis.

This paper is not the appropriate place to extensively discuss the pros and cons of these different concepts, which all refer to social change but have different foci and disciplinary origins. For the sake of brevity, this paper will use the terms social transformation and development as shorthands to indicate broader, more fundamental processes of social change (for a more elaborate discussion, see de Haas et al. 2020b ).

This also exemplifies the fundamentally problematic nature of transposing natural-science notions of causality to the social sciences, in both theorising and empirical analysis.

Economists would rather call this ‘human capital’.

In urbanized societies, and later in the lifecycle when people establish families, urbanites may aspire to live in the countryside again in search for calm, nature and community, or find a compromise by moving to suburbs.

I thank Sarah Salehi for bringing my attention to this point.

From this perspective, there is, indeed, good reason to consider history (also) as a social science.

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Acknowledgments

The research leading to this article is part of the MADE (Migration as Development) project and has received funding from the European Research Council under the European Community’s Horizon 2020 Programme (H2020/2015-2020)/ERC Consolidator Grant Agreement 648496. The author is grateful to Oliver Bakewell, Naluwembe Binaisa, Mathias Czaika, Katharina Natter, Edo Mahendra, Sarah Salehi, Kerilyn Schewel, Sorana Toma, María Villares-Varela and Simona Vezzoli for their generous comments on earlier versions of this paper. He thanks Sally Kingsborough for proofreading an earlier version of this text and Jenny Money for final editing.

Funding to conduct the research and write the article was provided by the European Research Council (see acknowledgements).

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de Haas, H. A theory of migration: the aspirations-capabilities framework. CMS 9 , 8 (2021). https://doi.org/10.1186/s40878-020-00210-4

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Climatic disasters are displacing millions of people every year across the world. Growing academic attention in recent decades has addressed different dimensions of the nexus between climatic events and human migration. Based on a systematic review approach, this study investigates how climate-induced migration studies are framed in the published literature and identifies key gaps in existing studies. 161 journal articles were systematically selected and reviewed (published between 1990 and 2019). Result shows diverse academic discourses on policies, climate vulnerabilities, adaptation, resilience, conflict, security, and environmental issues across a range of disciplines. It identifies Asia as the most studied area followed by Oceania, illustrating that the greatest focus of research to date has been tropical and subtropical climatic regions. Moreover, this study identifies the impact of climate-induced migration on livelihoods, socio-economic conditions, culture, security, and health of climate-induced migrants. Specifically, this review demonstrates that very little is known about the livelihood outcomes of climate migrants in their international destination and their impacts on host communities. The study offers a research agenda to guide academic endeavors toward addressing current gaps in knowledge, including a pressing need for global and national policies to address climate migration as a significant global challenge.

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Introduction

Population displacement can be driven by climatic hazards such as floods, droughts (hydrologic), and storms (atmospheric), and geophysical hazards such as earthquakes, volcanic eruptions, and tsunami (Smith and Smith 2013 ). The interactions between natural hazard events, and social, political, and human factors, frequently act to intensify the negative effects of climatic and geophysical hazards, leading to political and social unrest, increased social vulnerability, and human suffering. As a consequence of these adverse effects, people migrate from their native land, causing stress, uncertainty, and loss of lives and properties. However, such migration can also have positive impacts on migrants’ lives. For example, migrants may be able to diversify their livelihood and have greater access to education or healthcare.

In 2020, 30.7 million people from 149 countries and territories were displaced due to different natural disasters. Among them, climatic disasters were solely responsible for displacing 30 million people within their own country, with the highest recorded displacement occurring in 2010 when 38.3 million people were displaced (IDMC 2021a ; IOM 2021 ). It is difficult to estimate the actual number of people that moved due to the impacts of climate change (Mcleman 2019 ), because peoples’ migration decisions are triggered by a range of contextual factors (de Haas 2021 ). Nevertheless, the Internal Displacement Monitoring Centre (IDMC) states that approximately 283.4 million people were displaced internally between the years 2008 and 2020 because of climatic disasters across the globe (Table 1 ). This number represents almost 89% of the total disaster-induced displacement that occurred during this timeframe (IDMC 2021a ).

People who move from their homes due to climate-driven hazards are described in a range of ways, including climate migrants, environmental migrants, climate refugees, environmental refugees, and so on (Perkiss and Moerman 2018 ). The process of migration related to climate-driven hazards is variously described as environmental migration, environmental displacement, climate-induced migration or climigration (Bronen 2008 ).

In this research, we focus on climate-induced migration more specifically induced by slow-onset climatic disasters (sea-level rise, drought, salinity etc.), rapid onset extreme climatic events (storms, floods etc.), or both (precipitation, erosion etc.). This study investigates how climate change-induced migration studies are framed in the existing literature and identifies key gaps in the published literature.

There is a significant ongoing debate about the links between climate change and human migration in the academic literature. Some researchers strongly believe that climate change directly causes people to move, whereas the others argue that climate change is just one of the contextual factors in peoples’ migration decisions (Laczko and Aghazarm 2009 ). Although there are scholarly opinions that call into question climate change as a primary cause of migration (Black 2001 ; Black et al. 2011 ; McLeman 2014 ), there is also evidence that climate change causes severe environmental effects and exacerbates the vulnerabilities of people that force them to leave their place of living (Bronen and Chapin 2013 ; Laczko and Aghazarm 2009 ; McLeman 2014 ).

Moreover, the relationship between the adverse effects of climate change and different types of human mobility (migration, displacement, or planned relocation) has become increasingly recognized in recent years (Kälin and Cantor 2017 ). It is assumed in general that the number of climate displaced people is likely to increase in future (Mcleman 2019 ; Wilkinson et al. 2016 ), and climate change could permanently displace an estimated 150 million to nearly 1 billion people as a critical driver by 2050 (Held 2016 ; Perkiss and Moerman 2018 ). As the number of climate migrants increases rapidly in some areas of the world (IDMC 2017 ), it is now confirmed as a significant global challenge (Apap 2019 ) and recognized as a considerable threat to human populations (Ionesco et al. 2017 ).

Climate migration has multifaceted impacts on peoples’ livelihoods. Being displaced from their home, people migrate within their own country, described as internal migration, or across borders to other countries known as international migration. Internal movements of climate migrants occur mostly to nearby major cities or large urban centers (Poncelet et al. 2010 ). Climate migrants who try to move internationally are significantly challenged by two different security problems. Firstly, they cannot live in their own homeland because of worsening climatic impacts and are forced to leave their ancestral land. Secondly, they cannot move to other countries quickly to find a safer place because, according to international law, climate migrants are not refugees and they are not supported by the UN Refugee Convention or any international formal protection policies (Apap 2019 ; Mcleman 2019 ). In this situation, they live with significant livelihood uncertainty. The United Nation’s Sustainable Development Goals (SDGs) and the Sendai Framework for Disaster Risk Reduction (SFDRR) recognize them as a key group that is highly exposed and vulnerable because of their circumstances (Ionesco et al. 2017 ). Hence, policy development to address complex climate migration issues has become an emerging priority around the globe (Apap 2019 ).

In order to address this global challenge, there has been growing academic and policy attention focused on regional (Kampala Convention-2009 by African Union), national (Nansen Initiative—2012 by Norway and Switzerland), and international (Global Compact for Safe, Orderly and Regular Migration- 2018 by United Nations) levels of climate-induced migration in recent years. Myers’s ( 2002 ) seminal article signposted environmentally driven migration as one of the most significant challenges of the twenty-first century, and later, similar assumptions were made by Christian Aid (Baird et al. 2007 ), IOM (Brown 2008 ), and Care International (Warner et al. 2009 ). Such predictions led to a proliferation of the academic discourse on migration, focused on national and international security, policy frameworks, and human rights (Boncour and Burson 2009 ). Other studies have focused on vulnerability assessment, risk reduction, adaptation, resettlement, relocation, sustainability, and resilience, considering pre-, during and post-disaster circumstances of climate migration (Bronen 2011 ; Bronen and Chapin 2013 ; IDMC 2019 ; IOM 2021 ; King et al. 2014 ).

This research contributes to the discourse by identifying the gaps in the published literature regarding climate migration. A systematic literature review was undertaken to shed light on the current extent of academic literature, including gaps in knowledge to develop a climate migration research agenda. Two notable review papers provided a solid foundation for this endeavor. First, Piguet et al. ( 2018 ) developed a comprehensive review of publications on environment-induced migration from a global perspective based on a bibliographic database—CliMig. Their detailed mapping of environmentally induced migration research focused on five categories of climatic hazards (droughts, floods, hurricanes, sea-level rise, and rainfall); however, it did not include salinity and erosion which are also climate-driven and has direct effects on internal and international migration (Chen and Mueller 2018 ; Mallick and Sultana 2017 ; Rahman and Gain 2020 ).

The second key review paper was by Obokata et al. ( 2014 ), which provided an evidence-based explanation of the environmental factors leading to migration, and the non-environmental factors that influence the migration behaviors of people. Their scope of analysis was limited to international migration and excluded other types of migration, such as internal climate-induced migration.

Although migration, or more specifically environmental migration, was occurring over many decades of the twentieth century, the IPCC First Assessment report was released in 1990, which presented the first indications of the risks of climate change-induced human movement (IPCC 1990 ). This milestone report then stimulated the academic discourse, and consequently, a rapid increase in climate migration publication resulted. For this reason, the current study undertook a systematic review of literature across three decades beginning in 1990 and ending in 2019. This study aims to understand how the published literature has framed the climate-induced migration discourse. This paper identifies the key gaps in existing scholarship in this field and proposes a research agenda for future consideration on current and emerging climate migration issues.

In the following section, we outline the systematic review method and identify how journal articles were searched, selected, reviewed, and analyzed. In the next section, we present the results of this study. Results are organized into four subsections that illustrate the reviewed literature in the following ways—spatial and temporal trends, disciplinary foci, triggering forces of migration, and other key issues. Finally, we conclude by identifying research gaps, addressing the limitations of this study, and presenting a research agenda.

Methodology

We have adopted a systematic review methodology for this study because it provides an …overall picture of the evidence in a topic area which is needed to direct future research efforts (Petticrew and Robert 2006 ). Systematic reviews reduce the bias of a traditional narrative review, although it is challenging to eliminate researcher bias while interpreting and synthesizing results (Doyle et al. 2019 ). It also limits systematic bias by identifying, evaluating, and synthesizing all relevant studies to answer specific questions or sets of questions, and produces a scientific summary of the evidence in any research area (Petticrew and Robert 2006 ). Moreover, systematic reviews effectively address the research question and identify knowledge gaps and future research priorities (Mallett et al. 2012 ). We have adopted this approach following the methodology developed by Berrang-Ford et al. ( 2011 ) which was tested in the field of environmental and climate change studies, with measurable outcomes. We have conducted the review following these four steps—article search, selection, review, and analysis (Fig.  1 ).

Systematic review flowchart

Article search

We conducted a comprehensive literature search to identify the published academic literature on climate-induced migration to develop a clear understanding of this field of study. We identified sixteen commonly used keywords to search for articles that are predominantly used in the literature. ProQuest central database was selected and used in consultation with a skilled subject librarian to search for the relevant articles for this study. We conducted this literature search in July 2019 using the key thesaurus terms, presented in Table 2 . All keywords were then searched individually in the publication’s title and abstract. We only considered English language peer-reviewed articles for this study, published between the years 1990 and 2019 (up to June).

Article selection

The main purpose of this process was to ensure the selection of appropriate literatures for further analysis. We approached the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA), a systematic evaluation tool, which was also used by Huq et al. ( 2021 ). In stage one of the selection process, 277 articles were counted based on our search criteria. In stage two, we excluded 25 duplicates, and 252 articles remained for further assessment. In the third and final stage of the detailed assessment of each paper, we identified a further 91 publications that were not relevant to our study but appeared in our searched list because search terms were briefly mentioned in their title and/or abstract without being described in further detail. As these articles did not fit with the aim and content of this research, we excluded those 91 and selected a final 161 articles for this study.

Article review

All the selected articles were then considered for detailed review in order to achieve the purpose of the study. A questionnaire (Online Attachment—A) was developed partially following Berrang-Ford et al. ( 2011 ); Obokata et al. ( 2014 ) and Piguet et al. ( 2018 ) to investigate how climate migration studies are framed in the published literature. Then each article was reviewed in detail in response to the individual parameters of the questionnaire such as general information ( article title, authors name, publication year, journal, discipline, content ), methodological approach ( qualitative, quantitative, mixed ), focused study areas ( country, climatic zones ), source of migrants ( rural, urban ), migration types ( internal, international ), impacts of climate migration ( social, economic, political, health, cultural, environmental, security ), causes of migration ( climatic: flood, sea-level rise, drought etc ., other: socio-economic, political, cultural ), target communities ( displaced community, receiving community ), and livelihoods ( housing, income, employment, etc . ) of climate migrants described in the publications.

Article analysis

All the data were recorded in Microsoft Office Excel spreadsheets. Relevant data for each parameter were filtered, analyzed, and summarized using the necessary Excel tools. Referencing was compiled through Mendeley Desktop.

Spatial and temporal trend

General information.

In this section, the publication date of the reviewed articles was used in order to identify the development of the academic discourse in climate migration studies over the last three decades (1990–2019). Results show the increasing focus of academic attention on this area of research over that timeframe. The study found only four publications between the years 1990 and 1999. During 2000–2009, an additional 16 articles were published, which was followed by an almost 90 percent (141 publications) increase in reviewed articles over the period of 2010–2019 (Table 3 ).

Reviewed study areas

In 84 reviewed articles, the study reported research focused on a particular location, and in some cases, they considered two or more areas for their research. Therefore, multiple counting for each study has been considered, which represents all the continents except Antarctica. The analysis shows that Asia (38%) is the continent with the greatest number of climate migration studies, followed by Oceania (20%), North America (17%), and Africa (14%). In contrast, Europe and South America have received less attention, with 7% and 5%, respectively. Table 4 presents the distribution of study areas by continent focused on the reviewed papers.

Climatic zones of the reviewed studies

This study identified the climatic zones of the study areas in order to find out which zones are most commonly studied among the reviewed studies. We adopted the climatic zones of the world from Peel et al. ( 2007 ), which is the updated version of Koppen’s climate classification, and categorizes the world climate into five major zones, i.e., (i) tropical, (ii) arid, (iii) temperate, (iv) cold, and (v) polar. This review shows that 86 publications mentioned their study areas, equating to 54% of the total reviewed papers. Among them, 81% referred to a specific region as their study area. The study areas were then classified into the above-mentioned climatic zones with one reference offered randomly for each country as an example of the range of research that has been conducted.

This study reveals that 49% of this group (among 81%) focused on tropical climatic areas such as Bangladesh (Islam et al. 2014 ), Cambodia (Jacobson et al. 2019 ), Kiribati (Bedford et al. 2016 ), Papua New Guinea (Connell and Lutkehaus 2017 ), Philippines (Tanyag 2018 ), Tuvalu (Locke 2009 ), and Vanuatu (Perumal 2018 ) among others, and 16% focused on arid climatic zones such as African Sahel (McLeman and Hunter 2010 ), Israel (Weinthal et al. 2015 ), Peru (Scheffran 2008 ), and Senegal (Nawrotzki et al. 2016a , b ). In addition to these, 13% of authors focused on temperate regions, i.e., Mexico (Nawrotzki et al. 2016a , b ), Nepal (Chapagain and Gentle 2015 ), Taiwan (Kang 2013 ), UK (Abel et al. 2013 ), and the USA (Rice et al. 2015 ) for their study and 3% focused on cold climatic areas, i.e., Alaska: USA (Marino and Lazrus 2015 ), Canada (Omeziri and Gore 2014 ), and northern parts of China (Ye et al. 2012 ). No studies were found based on polar regions (Fig.  2 ). Some studies did not specify a region or country of study but instead focused on broader regions such as Africa (White 2012 ), Asia–Pacific (Mayer 2013 ), Europe (Werz and Hoffman 2016 ), Latin America (Wiegel 2017 ), and Pacific (Hingley 2017 ).

Climatic zones of the reviewed study areas-adopted from Peel (2007)

Migration types and sources of climate migrants

Migration types here refer to whether migration was internal (within a country or region) or international (across borders), and sources of climate migrants refer to people from rural or urban source regions. Most authors (73%) mentioned nothing regarding migration types, but a quarter (27%) explicitly discussed internal or international migration. Among them, 11% described climate migration within countries and 10% investigated cross-border migration. Some authors (6%) were concerned with both internal and international climate migration. Source regions for climate migrants were not often considered, with only 19 publications mentioning the origin of migrants. Among these, 11 articles stated that migration occurred from rural areas, and two publications discussed migration from urban areas. Also, six articles described climate migration from both rural and urban areas.

Disciplinary foci

Research discipline.

This study reveals that climate migration studies are becoming more focal issues in different research disciplines that include more than 40 subject areas. Hence, we developed a typology for the reviewed articles based on the relevant research themes. The typology consists of six research disciplines, each of which includes different subjects, as follows.

Social sciences: Social sciences, Sociology, Political Science, International Relations, Comprehensive Works, Population Studies, Anthropology, Social Services and Welfare, History, Philosophy, Ethnic Interests, Civil Rights, Women's Studies

Geography and environment: Meteorology, Environmental Studies, Energy, Conservation, Earth Sciences, Geography, Agriculture, Geology, Biology, Archaeology, Pollution

Business studies and development: Management, Business and Economics, International Commerce, International Development and Assistance, Economics, Insurance, Investments, Accounting

Law, policy, and planning: Law, Military, Civil Defense, Criminology and Security, Environmental policy

Health and medical science: Public Health, Psychology, Medical Sciences, Physical Fitness, and Hygiene

Other: Literature, Library and Information Sciences, Physics, Technology

Among the reviewed publications, some articles were discussed from the perspective of one particular discipline, while others came from two or more disciplines. Therefore, multiple counting for each discipline was considered during the analysis. The study reveals that Social Science covers the highest percentage of publications (41%), followed by Geography and Environment (30%), Business Studies and development (10%), Law, policy and planning (9%), and Health and medical science (7%). Only 2% of publications are not covered by any of these disciplines.

Primary research themes

The authors discussed a diverse range of themes in the reviewed articles. Key themes have been classified into eight categories based on their topics and focusing subjects. Some of the publications focused on multiple themes, which were counted separately under each theme. Most of the authors (27%) focused on Politics and policy issues, and almost a fifth (18%) of total articles focused on the themes of population, health, and development issues. Human rights, conflicts, and security issues were discussed in 16% of papers, and climate, vulnerability, adaptation, and resilience topics were the focus of 12% of publications. In 11% of publications, the authors focused on identity and cultural issues, and socio-economic topics comprised a further 9% of the total. Environmental issues were discussed by 4% of reviewed articles and 3% of publications did not fit into any of the above categories and are described as Other.

Methodological approaches

This review identified that researchers applied both qualitative and quantitative methods in climate migration research. A total of 82% of the reviewed articles used qualitative methodologies, and 9% quantitative. In addition to these, 9% of articles used mixed methods in climate migration research. Of those who used qualitative studies, most were review-based (86%), comprising systematic review, empirical evidence-based review, critical synthesis review, critical discourse review, and policy review. Only 14% of qualitative studies used interview methods (7%), case studies (6%), and focus group discussion (1%). Data sources reported in the reviewed literature for the quantitative research included secondary data (73%), historical data (13%), remote sensing data (7%), and survey data (7%).

Triggering forces of migration

Climatic causes of migration.

The reviewed publications outlined a range of different causes of climate migration. This study reveals nineteen climate-related causes of migration. We merged these causes into eight categories, defined as (i) climate change (climate change, global warming, temperature, environmental change, climate-induced natural disaster, meteorological events, extreme weather, heatwave), (ii) flood, (iii) sea-level rise (sea-level rise, melting glacier), (iv) drought (drought, desertification), (v) storm (storm, cyclone, hurricane, typhoon), (vi) salinity (salinity, tidal surge), (vii) precipitation-induced landslide, and (viii) erosion (coastal erosion, river erosion). “Climate change” is defined as a separate category because some publications named climate change as an overarching driver of migration, rather than specifying any particular hazard. In 70 publications, authors mentioned particular climatic events that were solely responsible for human migration, and 53 of these articles predominantly identified climate change as the main driver of migration, followed by sea-level rise (6), drought (4), flood (3), storm (2), and precipitation-induced landslide (2). In the remaining articles, scholars identified two or more climatic events that were collectively responsible for human displacement. Based on these articles, multiple counting for each climatic event was considered and the results show that climate change was the most commonly cited cause in 126 articles, along with other climatic causes. The authors also identified sea-level rise, drought, flood, and storms as the significant drivers of peoples’ migration along with other climatic drivers, which were mentioned in 51, 46, 44, and 43 articles, respectively. Precipitation-induced landslide and erosion were recognized in 17 and 12 articles, respectively, as the causes of human displacement, whereas eight articles identified salinity as the main reason.

Influencing causes of migration

Although this review was focused on identifying the climatic causes of human displacement, some other causes emerged during the analysis that also influence migration. In 68 publications, economic, social, environmental, political, cultural, and psychological causes were stated as drivers of migration, in addition to the climatic causes. Among these, economic causes (32%) have been identified as the most common driver, followed by social (25%) and environmental (22%) causes. Some articles described political causes (16%), and the remainder mentioned cultural (3%) and psychological (1%) drivers of migration.

Other key issues

• Impacts of climate migration

One of the key findings of this review concerns the impacts of climate migration. In 48 publications, authors described a range of different impacts caused by climate migration, such as social, economic, political, health, cultural, environmental, and security. All the impacts were identified based on the location of climate migrants which are classified into the following three categories: (i) impacts on the place of origin, (ii) impacts on the place of destination, and (iii) impacts on both origin and destination. The review demonstrates that the impacts of climate migration were more frequently identified for the place of origin rather than for the destination. In the place of origin, authors discussed the economic, social, and cultural impacts, compared to political, security, health, and environmental impacts. In contrast, in the destination, scholars were more focused on security and cultural impacts. Overall, security, cultural and economic impacts were the most frequently discussed themes by the authors of reviewed literature in comparison with other impacts (Table 5 ).

Discussed communities

More than half of the reviewed articles ( N  = 81) described climate migrants and/or their receiving communities. In most of the discussions, authors talked about both displaced and host communities together (57%). In more than two-fifths of articles, they considered only displaced communities (42%). In contrast, none of the authors of the reviewed literature discussed host communities in detail in their publications, except Dorent ( 2011 ). Only a few authors briefly mentioned host communities during the discussion of climate migration impacts.

Livelihoods of climate migrants

This review demonstrates that the overall livelihood of climate migrants has not been a key focus in any of the reviewed literature. However, a few separate parameters of livelihoods, including housing, income and employment, health, access to resources, and education were mentioned in 23 articles. The analysis shows that the livelihoods of migrants in their place of origin (71%) were more likely to be considered compared to their destination (11%). In some articles (18%), authors addressed the livelihoods of climate migrants considering both their place of origin and destination. In total, all the articles which considered livelihoods had a specific focus on internal migration, and none mentioned the livelihoods of climate migrants in terms of international migration.

Discussion and research gaps

Climate change-induced migration is neither new (Nagra 2017 ), nor a future hypothetical phenomenon—it is a current reality (Coughlin 2018 ). This review provides a comprehensive analysis of how this field of study is framed in the existing literature. The academic discourse on human migration due to climate change is suggestive of a long-standing causal connection, which is hard to dissociate (Milán-García et al. 2021 ; Parrish et al. 2020 ; Piguet et al. 2011 ).

The review of spatial and temporal trends of climate-induced migration studies illustrates the growth in the field since the release of 1st IPCC report in 1990. In addition, this review has explored some basic questions that are useful to guide future research in this field of study, for instance, which study areas have received greater or lesser focus? Where are these study areas located in relation to global climatic zones? How are people migrating, i.e., internally, or internationally? What are the spatial sources of climate-induced migrants, i.e., rural, or urban environments?

This review also demonstrates that the expansion of climate migration research increased rapidly after 2000, although the studies in this field began before 2000 (Table 3 ). It denotes that the global academia and policymakers have emphasized their focus on this topic in recent decades (Milán-García et al. 2021 ; Piguet et al. 2011 ). Moreover, this review identifies the Asia–Pacific region as the global ‘hotspot’ of climate migration research (Table 4 ). This reflects the IDMC ( 2019 ) report that states more than 80% of the total displacement between 2008 and 2018 occurred within this region. Moreover, a significant proportion of global environmental displacement will continue to occur in the Asia–Pacific region (Mayer, 2013 ). Therefore, this region could be considered as a critical ‘living laboratory’ for future climate migration research.

Climate migration is mostly occurring internally (IDMC 2021a ; Laczko and Aghazarm 2009 ), and in recent years, it has been widely acknowledged in the policy areas (Fussell et al. 2014 ; The World Bank 2018 ). Nevertheless, this study reveals that only a quarter of the reviewed studies for example, Chapagain and Gentle ( 2015 ), Islam et al. ( 2014 ), and Prasain ( 2018 ) have considered the migration types (internal or international) and sources (rural or urban) of climate migrants in their research. Thus, this review identifies the gap and need for contributions to the academic discourse that investigate migration types, the origin of migrants, and their patterns of migration.

The review of the disciplinary foci of climate-induced migration literature reveals that a broader range of disciplines are now focusing on this research topic, which suggests that greater interdisciplinarity is developing in the discourse. IDMC ( 2021b ) data presented in Table 1 show that climate-induced disasters are displacing millions of people every year, but surprisingly none of the reviewed publications appeared under the subject category of disaster management in the database. This reflects the emergent nature of the academic discourse on climate migration and disaster management, which includes recent studies by Ye et al. ( 2012 ), Tanyag ( 2018 ), and Hamza et al. ( 2017 ). In addition, politics and policy issues regarding climate migration were discussed by scholars; however, no country-specific policies were found during the review that considered both the origin and host communities of climate migrants.

Campbell ( 2014 ) argues that there is insufficient empirical evidence within climate migration research. However, this review reveals that research in this area has been undertaken using a range of methodologies, from qualitative (review, case study, interview, focus group discussion etc.) to quantitative (based on survey data, secondary data, historical data, and remote sensing data), which has produced a strong foundation of work to guide future pathways for interdisciplinary climate migration research. A significant proportion of the research to date has been review-based. Also, there is a lack of empirical studies in this research field that consider the application of geographic information system and remote sensing.

It is clear from reviewing the triggering forces of climate-induced migration literature that climatic events are dominantly responsible for climate migration, which is supported by Rahman and Gain ( 2020 ), Connell and Lutkehaus ( 2017 ), Gemenne ( 2015 ), and Kniveton et al. ( 2012 ). Despite this, there are some other influencing push and/or pull factors such as socio-economic, political, cultural, etc., which are likely to compound (or be compounded by) climate impacts, to trigger the migration process (Black et al. 2011 ; de Haas 2011 , 2021 ; Fussell et al. 2014 ). While there remains ample anecdotal evidence of the relationship between climate change impacts and migration, the specific reasons for people to decide to migrate are interwoven with indirect pressures, such as livelihood disruption, poverty, war, or disaster (Werz and Hoffman 2016 ). Moreover, why people choose to stay at their places is also essential in the context of creeping environmental and climate-induced migration (Mallick and Schanze 2020 ).

One of the other key issues reviewed in this study is that the literature to date fails to build an understanding of the impacts of climate migration on both the origin (source regions) and destination of the climate migrants. There are very few studies such as Comstock and Cook ( 2018 ), Maurel and Tuccio ( 2016 ), Pryce and Chen ( 2011 ), Rahaman et al. ( 2018 ), Rice et al. ( 2015 ), and Schwan and Yu ( 2017 ) that investigate different aspects of socio-economic impacts (housing, health, social, economic, etc.) of climate migration in the destination region, and this presents a clear gap in knowledge that requires further study. Also, no current research has been identified during the review that focused on the environmental impacts of climate migration.

In addition, this review identifies that there was less attention paid to the impacts of climate migration on host communities compared to displaced populations in their new locations. Given that migration will continue to increase globally, there is likely to be a growing need to understand the range of potential impacts on host communities. Although some countries and regions are developing policies to manage internal migration, there are no formal protection policies for cross-border climate migration (Nishimura 2015 ; OHCHR 2018 ; Olsson 2015 ; Zaman 2021 ). Therefore, policy arrangements for managing the needs of climate displaced people in their new communities need to be developed to account for issues related to impacts, livelihoods, community cohesion, and cultural diversity and values. Future research should address the significant gap in understanding the livelihoods of climate migrants in their cross border or international destination. More specifically, in developed countries where the employment sector is more formalized, there is less room for informal economic practices that are common in developing contexts. More formal employment arrangements make it challenging for migrants to establish new livelihoods, alongside other challenges such as language barriers, and other financial, social, cultural and well-being issues.

Limitations and future research scope

Limitations of this study.

There are some limitations to this systematic review; firstly, this review used ProQuest as the sole database for the analysis, and future work could extend the scope to include other major databases. Secondly, this study only considered English language literature, and there are likely to be significant publications in other languages relating to climate migration that were not included in this analysis. Thirdly, looking at pre-1990 or post-2019 literature could add more exciting findings to the search list, which would provide more informative literature. Finally, the outputs of this review are limited to the nature of the search terms, and thus, if other words or texts such as climate-induced relocation or mobility were used, it might extend the range of the review.

Toward a research agenda for climate migration

This review has highlighted several exciting future research opportunities that will build on the strong foundation of work over the past decades in the field of climate migration studies. These include the following research themes; (i) a richer understanding of the full range of impacts (such as social, economic, environmental, and cultural) of climate migration on host communities; (ii) in-depth analysis of the livelihoods of climate-induced migrants in their new destination; (iii) evidence-based research on internal and international climate migration with their sources; (iv) long-term migration policy development at national, regional, or international levels considering both climate migrants and host communities; (v) scope and application of geographic information systems and remote sensing in this area of research, and (vi) developing sustainable livelihood frameworks for climate migrants. The authors believe that academic contributions to these research themes will drive climate migration challenges toward long-term solutions, particularly in those countries that are going to be hosting increasing numbers of climate migrants in future.

This study aimed to understand the past three decades of academic endeavor on climate migration and to identify the gaps in the existing literature in order to inform a research agenda for future research. Climate change, climate-induced migration, and climate migrants are now considered significant global challenges. Climate migrants are identified as a vulnerable group, and a consideration of issues for this group is essential in addressing the goals of the SDGs and SFDRRR. There is a growing body of knowledge that reflects the global relevance of climate migration as a major current and future challenge (Boncour and Burson 2009 ). Addressing the issues and challenges of this form of migration will improve the survival and certain resettlement rights of climate migrants (Miller 2017 ). Therefore, this review contributes a research agenda for future climate migration studies. This study has revealed a critical need to establish a universally agreed definition of ‘climate-induced migrants’ and ‘climate-induced migration,’ which remains unclear to date. Lack of clarity only acts to reduce the visibility of issues related to climate-induced migration. In addition, there is a crucial need to improve the evidence base for climate-induced migration by improving current global datasets, to inform local, regional, and global policy development. Policies need to be future-looking in preparation for a rapid and significant increase in climate-related migration across the globe, within and across national borders. For instance, it is important for receiving countries to anticipate an upsurge in migration by developing appropriate policies to support new migrants, particularly regarding visa and immigration arrangements. Addressing current gaps in knowledge will lead to improved pathways to manage this global migration challenge, which is now a critical need if we are to achieve a sustainable future in a climate-challenged world.

Data availability

Data are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to thank Dr Douglas Hill, Dr Ashraful Alam and Dr Bishawjit Mallick for their feedback on the initial draft of this article.

This research has been supported by a University of Otago Doctoral Scholarship. Open Access funding is enabled and organized by CAUL and its Member Institutions.

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World Migration Report 2024 Reveals Latest Global Trends and Challenges in Human Mobility 

• International remittances surged by 650 per cent, from USD 128 billion to USD 831 billion between 2000 and 2022. 
• Migrant remittances surpass foreign direct investment in boosting the GDP of developing nations. 
• 281 million international migrants globally; number of those displaced hit a record high by the end of 2022 at 117 million.  

Dhaka/Geneva, 7 May – The International Organization for Migration (IOM) today launched the World Migration Report 2024 , which reveals significant shifts in global migration patterns, including a record number of displaced people and a major increase in international remittances.  

IOM Director General Amy Pope formally released the report in Bangladesh, which stands at the forefront of migration challenges, including emigration, immigration and displacement.   

“The World Migration Report 2024 helps demystify the complexity of human mobility through evidence-based data and analysis,” IOM Director General Amy Pope said at the launch. “In a world grappling with uncertainty, understanding migration dynamics is essential for informed decision-making and effective policy responses, and the World Migration Report advances this understanding by shedding light on longstanding trends and emerging challenges.” 

The report highlights that international migration remains a driver of human development and economic growth, highlighted by a more than 650 per cent increase in international remittances from 2000 to 2022, rising from USD 128 billion to USD 831 billion. The growth continued despite predictions from many analysts that remittances would decrease substantially because of COVID-19.  

Of that 831 billion in remittances, 647 billion were sent by migrants to low– and middle-income countries. These remittances can constitute a significant portion of those countries' GDPs, and globally, these remittances now surpass foreign direct investment in those countries. 

Highlighting key findings, the report reveals that while international migration continues to drive human development, challenges persist. With an estimated 281 million international migrants worldwide, the number of displaced individuals due to conflict, violence, disaster, and other reasons has surged to the highest levels in modern-day records, reaching 117 million, underscoring the urgency of addressing displacement crises.  

Migration, an intrinsic part of human history, is often overshadowed by sensationalized narratives. However, the reality is far more nuanced than what captures headlines. Most migration is regular, safe, and regionally focused, directly linked to opportunities and livelihoods. Yet, misinformation and politicization have clouded public discourse, necessitating a clear and accurate portrayal of migration dynamics.  

By choosing Dhaka as the report's launch site, IOM not only highlights the country's efforts in supporting vulnerable migrants and fostering pathways for regular migration but also recognizes Bangladesh's important role in shaping global migration discourse and policy.  

As a Global Compact for Safe, Orderly, and Regular Migration Champion country, Bangladesh has demonstrated a strong commitment to addressing migration issues and implementing policies that safeguard migrants' rights. This proactive engagement aligns with IOM's strategic objectives, making Bangladesh an ideal location to launch the 2024 World Migration Report.  

IOM’s World Migration Report, with its innovative digital tools and comprehensive analysis, aims to help dispel myths, provide critical insights, and inspire meaningful action in addressing the challenges and opportunities of human mobility.  

"We hope the report inspires collaborative efforts to harness the potential of migration as a driver for human development and global prosperity," DG Pope said. 

“As one of the GCM champion countries, Bangladesh will not only continue to act upon the pledges it has made for its domestic context but would also take up emerging issues and challenges pertaining to migration and development for informed deliberations at the international level,” said Dr. Hasan Mahmud, Honourable Foreign Minister, Government of the People’s Republic of Bangladesh.

Notes to editors: 

This launch is part of IOM Director General’s first three-day visit to Bangladesh. 

For more information, please contact: 

Marie McAuliffe, World Migration Report Editor at [email protected]  

For media requests: Florence Kim at [email protected]  

RELATED NEWS

Iom's world migration report shows global displacement rising despite covid-19 mobility limits, iom’s world migration report 2020  wins  international  design  awards , world migration report launches dynamic new data visualization platform, world migration report 2020 launched.

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About migration

World Migration Report 2024 Reveals Latest Global Trends and Challenges in Human Mobility 

• International remittances surged by 650 per cent, from USD 128 billion to USD 831 billion between 2000 and 2022. 
• Migrant remittances surpass foreign direct investment in boosting the GDP of developing nations. 
• 281 million international migrants globally; number of those displaced hit a record high by the end of 2022 at 117 million.  

To access the World Migration Report 2024, visit the WMR website . 

Dhaka/Geneva, 7 May – The International Organization for Migration (IOM) today launched the World Migration Report 2024 , which reveals significant shifts in global migration patterns, including a record number of displaced people and a major increase in international remittances.  

IOM Director General Amy Pope formally released the report in Bangladesh, which stands at the forefront of migration challenges, including emigration, immigration and displacement.   

“The World Migration Report 2024 helps demystify the complexity of human mobility through evidence-based data and analysis,” IOM Director General Amy Pope said at the launch. “In a world grappling with uncertainty, understanding migration dynamics is essential for informed decision-making and effective policy responses, and the World Migration Report advances this understanding by shedding light on longstanding trends and emerging challenges.” 

The report highlights that international migration remains a driver of human development and economic growth, highlighted by a more than 650 per cent increase in international remittances from 2000 to 2022, rising from USD 128 billion to USD 831 billion. The growth continued despite predictions from many analysts that remittances would decrease substantially because of COVID-19.  

Of that 831 billion in remittances, 647 billion were sent by migrants to low– and middle-income countries. These remittances can constitute a significant portion of those countries' GDPs, and globally, these remittances now surpass foreign direct investment in those countries. 

Highlighting key findings, the report reveals that while international migration continues to drive human development, challenges persist. With an estimated 281 million international migrants worldwide, the number of displaced individuals due to conflict, violence, disaster, and other reasons has surged to the highest levels in modern-day records, reaching 117 million, underscoring the urgency of addressing displacement crises.  

Migration, an intrinsic part of human history, is often overshadowed by sensationalized narratives. However, the reality is far more nuanced than what captures headlines. Most migration is regular, safe, and regionally focused, directly linked to opportunities and livelihoods. Yet, misinformation and politicization have clouded public discourse, necessitating a clear and accurate portrayal of migration dynamics.  

By choosing Dhaka as the report's launch site, IOM not only highlights the country's efforts in supporting vulnerable migrants and fostering pathways for regular migration but also recognizes Bangladesh's important role in shaping global migration discourse and policy.  

As a Global Compact for Safe, Orderly, and Regular Migration Champion country, Bangladesh has demonstrated a strong commitment to addressing migration issues and implementing policies that safeguard migrants' rights. This proactive engagement aligns with IOM's strategic objectives, making Bangladesh an ideal location to launch the 2024 World Migration Report.  

IOM’s World Migration Report, with its innovative digital tools and comprehensive analysis, aims to help dispel myths, provide critical insights, and inspire meaningful action in addressing the challenges and opportunities of human mobility.  

“We hope the report inspires collaborative efforts to harness the potential of migration as a driver for human development and global prosperity,” DG Pope said. 

“As one of the GCM champion countries, Bangladesh will not only continue to act upon the pledges it has made for its domestic context but would also take up emerging issues and challenges pertaining to migration and development for informed deliberations at the international level,” said Dr. Hasan Mahmud, Honourable Foreign Minister, Government of the People’s Republic of Bangladesh.

Notes to editors: 

This launch is part of IOM Director General’s first three-day visit to Bangladesh. 

For more information, please contact: 

Marie McAuliffe, World Migration Report Editor at [email protected]  

For media requests: Florence Kim at [email protected]  

RELATED NEWS

Joint statement by japan, norway, sweden, switzerland and the united states following their visit to the rohingya refugee camps in cox’s bazar, bangladesh, 75.9 million people living in internal displacement in 2023: idmc report, iom chief visits bangladesh, secures funding commitments for rohingya refugees, floods displace thousands in east africa; iom calls for sustained efforts to address climate mobility.

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About Migration

World Migration Report 2024 Reveals Latest Global Trends and Challenges in Human Mobility 

• International remittances surged by 650 per cent, from USD 128 billion to USD 831 billion between 2000 and 2022. 
• Migrant remittances surpass foreign direct investment in boosting the GDP of developing nations. 
• 281 million international migrants globally; number of those displaced hit a record high by the end of 2022 at 117 million.

The International Organization for Migration (IOM) launched the World Migration Report 2024, which reveals significant shifts in global migration patterns, including a record number of displaced people and a major increase in international remittances.  

IOM Director General Amy Pope formally released the report in Bangladesh, which stands at the forefront of migration challenges, including emigration, immigration and displacement.    “The World Migration Report 2024 helps demystify the complexity of human mobility through evidence-based data and analysis,” IOM Director General Amy Pope said at the launch. “In a world grappling with uncertainty, understanding migration dynamics is essential for informed decision-making and effective policy responses, and the World Migration Report advances this understanding by shedding light on longstanding trends and emerging challenges.” 

The report highlights that international migration remains a driver of human development and economic growth, highlighted by a more than 650 per cent increase in international remittances from 2000 to 2022, rising from USD 128 billion to USD 831 billion. The growth continued despite predictions from many analysts that remittances would decrease substantially because of COVID-19.  

Of that 831 billion in remittances, 647 billion were sent by migrants to low– and middle-income countries. These remittances can constitute a significant portion of those countries' GDPs, and globally, these remittances now surpass foreign direct investment in those countries. 

Highlighting key findings, the report reveals that while international migration continues to drive human development, challenges persist. With an estimated 281 million international migrants worldwide, the number of displaced individuals due to conflict, violence, disaster, and other reasons has surged to the highest levels in modern-day records, reaching 117 million, underscoring the urgency of addressing displacement crises.  

Migration, an intrinsic part of human history, is often overshadowed by sensationalized narratives. However, the reality is far more nuanced than what captures headlines. Most migration is regular, safe, and regionally focused, directly linked to opportunities and livelihoods. Yet, misinformation and politicization have clouded public discourse, necessitating a clear and accurate portrayal of migration dynamics.  

IOM’s World Migration Report, with its innovative digital tools and comprehensive analysis, aims to help dispel myths, provide critical insights, and inspire meaningful action in addressing the challenges and opportunities of human mobility.  

"We hope the report inspires collaborative efforts to harness the potential of migration as a driver for human development and global prosperity," DG Pope said. 

To access the World Migration Report 2024, visit World Migration Report | International Organization for Migration, IOM  

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'Performance has the ability to reshape our understanding of migration and citizenship'

Ana Gabriela Carmona-Pereda: Performing & Media Arts

A&S Communications

Ana Gabriela Carmona-Pereda

Performing & Media Arts Bronx, N.Y.

What was your favorite class and why?  

Prof. Aldape Muñoz’s PMA 3215: Performance and Immigration was one of my favorite classes at Cornell. As the daughter of Mexican immigrant parents and someone deeply interested in performance art, the course's focus on the power of performance in shaping discussions around migration resonated with me on a personal and intellectual level. The class delved into the complexities of immigration debates and the experiences of those labeled as "undocumented," "illegal," "displaced," or "exiled." Through a nuanced exploration of various performances, we interrogated how immigration narratives are constructed and challenged, and how belonging is redefined through artistic expression. One of the most compelling aspects of the course was the opportunity to engage with works by BIPOC scholars and artists such as Ramon River Servera, Josefina Baez, Marissa Chibas and Guadalupe Maravilla, who has an exhibition at the Johnson Museum through June 9, 2024. Attending live performances like the Kitchen Theatre’s "Sanctuary City" provided a tangible connection to the themes we discussed in class. Seeing these narratives come to life on stage reinforced the idea that performance has the ability to not only reflect but also reshape our understanding of migration and citizenship. As I navigated discussions on immigration policies and administrative processes, I found myself drawing from my own family's experiences and reflecting on how performance can serve as a means of exploration, healing and empowerment for communities.

What Cornell memory do you treasure the most?  

This semester I worked alongside a graduate student, Isabel Padilla Carlo, and Prof. Aldape Muñoz to lead workshops based on NAKA Dance Theatre and Mujeres Unidas y Activas (MUA), a collaborative project known as, ¡Y Basta Ya! Working with immigrant and indigenous women in Ithaca and surrounding areas, we created a safe and empowering space for vulnerability and visibility. By April, we had visiting artists from NAKA Dance Theatre, Jose and Debby, join us along with women from MUA, to rehearse and stage a performance piece at The Kitchen Theatre. The result was an entire stage of folks dancing unapologetically to reggaeton, salsa and cumbia. I will forever be grateful for the joy, care and tenderness I experienced during the rehearsal process, final performance and community event. To be a part of Cornell is to know and cherish the communities that exist beyond the hill.       

What have you accomplished as a Cornell student that you are most proud of?

Participating in Cornell’s Study Abroad Program during the fall semester of my senior year was an experience I cherish deeply and am proud to have accomplished. Having never left the country before, I took the opportunity to study abroad in Mexico City, where I immersed myself in the wonderful culture. There, I not only delved into the rich tapestry of Mexican traditions, festivals and cuisine but also forged meaningful connections within the local community, where I experienced the warmth of the people through their care and love. One of my favorite memories was when I got the opportunity to visit my relatives in Oaxaca, Mexico. This journey allowed me to strengthen familial bonds, foster cross-cultural connections and gain profound insights into my own identity that will reflect in my future artistic endeavors.

Who or what influenced your Cornell education the most?    

I wouldn't have made it here today if it weren’t for the guidance of advisors at the Higher Education Opportunity Program (HEOP), who helped me recognize the truth in my power, potential and identity. The connections I built were largely shaped by my willingness to be open. In an elitist, competitive environment where many strive to maintain a composed façade, finding a space for genuine emotional expression was challenging but not impossible. Although there's no place that cradles and soothes me like the New York City subway, my advisor's office was where I found both solace and the courage to share my doubts and accomplishments throughout my time at Cornell. It was where I felt the most heard and celebrated for being my most authentic self. 

If you were to offer advice to an incoming first-year student, what would you say?

Bring your most authentic self into every space and opportunity you encounter. Make an effort to reach out to people and maintain those connections through honesty and vulnerability; here you will find support, love and encouragement. Trust that you will find your people and those professors/advisors/mentors who will support your career path and mentor you. Also don’t forget to give back in equal measure. Remember that there are a plethora of tools and opportunities available to support your artistic, intellectual and career endeavors, whether through grants, student organizations or research funds. Most importantly, there’s more beyond Cornell. Don’t be afraid to connect with those outside of the Cornell community to connect and learn!

Every year, our faculty nominate graduating Arts & Sciences students to be featured as part of our Extraordinary Journeys series.  Read more about the Class of 202 4.

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