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Drivers of human migration: a review of scientific evidence.

1. Introduction

2. systematic literature reviews for evidence based policymaking, 3. evidence materials on migration drivers—methodology of selection.

• studies that concentrated on population-geographical segments too specific to be able to confidently claim wider, at least country-level, validity (e.g., migration incentives of Polish construction workers, Italian university graduates, farmworkers, physicians, and the like)
• studies analysing migration intentions, not the already pursued migration decisions, or studies analysing post-accession migration
• studies for which duplicates have been discovered, most often working papers that preceded a later-published journal article, by the same authors and on the same topic (where only the later publications were maintained).

4. Content Analysis of the Evidence Materials

6. conclusions, 6.1. limitations, 6.2. future research, supplementary materials, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Pitoski, D.; Lampoltshammer, T.J.; Parycek, P. Drivers of Human Migration: A Review of Scientific Evidence. Soc. Sci. 2021 , 10 , 21. https://doi.org/10.3390/socsci10010021

Pitoski D, Lampoltshammer TJ, Parycek P. Drivers of Human Migration: A Review of Scientific Evidence. Social Sciences . 2021; 10(1):21. https://doi.org/10.3390/socsci10010021

Pitoski, Dino, Thomas J. Lampoltshammer, and Peter Parycek. 2021. "Drivers of Human Migration: A Review of Scientific Evidence" Social Sciences 10, no. 1: 21. https://doi.org/10.3390/socsci10010021

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Article Contents

1. introduction, 2. studies of migration studies, 3. methodology, 4. metadata on migration studies, 5. topic clusters in migration studies, 6. trends in topic networks in migration studies, 7. conclusions, acknowledgements.

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Mapping migration studies: An empirical analysis of the coming of age of a research field

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Asya Pisarevskaya, Nathan Levy, Peter Scholten, Joost Jansen, Mapping migration studies: An empirical analysis of the coming of age of a research field, Migration Studies , Volume 8, Issue 3, September 2020, Pages 455–481, https://doi.org/10.1093/migration/mnz031

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Migration studies have developed rapidly as a research field over the past decades. This article provides an empirical analysis not only on the development in volume and the internationalization of the field, but also on the development in terms of topical focus within migration studies over the past three decades. To capture volume, internationalisation, and topic focus, our analysis involves a computer-based topic modelling of the landscape of migration studies. Rather than a linear growth path towards an increasingly diversified and fragmented field, as suggested in the literature, this reveals a more complex path of coming of age of migration studies. Although there seems to be even an accelerated growth for migration studies in terms of volume, its internationalisation proceeds only slowly. Furthermore, our analysis shows that rather than a growth of diversification of topics within migration topic, we see a shift between various topics within the field. Finally, our study shows that there is no consistent trend to more fragmentation in the field; in contrast, it reveals a recent recovery of connectedness between the topics in the field, suggesting an institutionalisation or even theoretical and conceptual coming of age of migration studies.

Migration studies have developed rapidly as a research field in recent decades. It encompasses studies on all types of international and internal migration, migrants, and migration-related diversity ( King, 2002 ; Scholten, 2018 ). Many scholars have observed the increase in the volume of research on migration ( Massey et al., 1998 ; Bommes and Morawska, 2005 ; Scholten et al., 2015 ). Additionally, the field has become increasingly varied in terms of links to broader disciplines ( King, 2012 ; Brettell and Hollifield, 2014 ) and in terms of different methods used ( Vargas-Silva, 2012 ; Zapata-Barrero and Yalaz, 2018 ). It is now a field that has in many senses ‘come of age’: it has internationalised with scholars involved from many countries; it has institutionalised through a growing number of journals; an increasing number of institutes dedicated to migration studies; and more and more students are pursuing migration-related courses. These trends are also visible in the growing presence of international research networks in the field of migration.

Besides looking at the development of migration in studies in terms of size, interdisciplinarity, internationalisation, and institutionalisation, we focus in this article on the development in topical focus of migration studies. We address the question how has the field of migration studies developed in terms of its topical focuses? What topics have been discussed within migration studies? How has the topical composition of the field changed, both in terms of diversity (versus unity) and connectedness (versus fragmentation)? Here, the focus is not on influential publications, authors, or institutes, but rather on what topics scholars have written about in migration studies. The degree of diversity among and connectedness between these topics, especially in the context of quantitative growth, will provide an empirical indication of whether a ‘field’ of migration studies exists, or to what extent it is fragmented.

Consideration of the development of migration studies invokes several theoretical questions. Various scholars have argued that the growth of migration studies has kept pace not only with the growing prominence of migration itself but also with the growing attention of nation–states in particular towards controlling migration. The coproduction of knowledge between research and policy, some argue ( Scholten, 2011 ), has given migration research an inclination towards paradigmatic closure, especially around specific national perspectives on migration. Wimmer and Glick Schiller (2002 ) speak in this regard of ‘methodological nationalism’, and others refer to the prominence of national models that would be reproduced by scholars and policymakers ( Bommes and Morawska, 2005 ; Favell, 2003 ). More generally, this has led, some might argue, to an overconcentration of the field on a narrow number of topics, such as integration and migration control, and a consequent call to ‘de-migranticise’ migration research ( Dahinden, 2016 ; see also Schinkel, 2018 ).

However, recent studies suggest that the growth of migration studies involves a ‘coming of age’ in terms of growing diversity of research within the field. This diversification of migration studies has occurred along the lines of internationalisation ( Scholten et al., 2015 ), disciplinary variation ( Yans-McLaughlin, 1990 ; King, 2012 ; Brettell and Hollifield, 2014 ) and methodological variation ( Vargas-Silva, 2012 ; Zapata-Barrero and Yalaz, 2018 ). The International Organization for Migration ( IOM, 2017 : 95) even concludes that ‘the volume, diversity, and growth of both white and grey literature preclude a [manual] systematic review’ of migration research produced in 2015 and 2016 alone .

Nonetheless, in this article, we attempt to empirically trace the development of migration studies over the past three decades, and seek to find evidence for the claim that the ‘coming of age’ of migration studies indeed involves a broadening of the variety of topics within the field. We pursue an inductive approach to mapping the academic landscape of >30 years of migration studies. This includes a content analysis based on a topic modelling algorithm, applied to publications from migration journals and book series. We trace the changes over time of how the topics are distributed within the corpus and the extent to which they refer to one another. We conclude by giving a first interpretation of the patterns we found in the coming of age of migration studies, which is to set an agenda for further studies of and reflection on the development of this research field. While migration research is certainly not limited to journals and book series that focus specifically on migration, our methods enable us to gain a representative snapshot of what the field looks like, using content from sources that migration researchers regard as relevant.

Migration has always been studied from a variety of disciplines ( Cohen, 1996 ; Brettell and Hollifield, 2014 ), such as economics, sociology, history, and demography ( van Dalen, 2018 ), using a variety of methods ( Vargas-Silva, 2012 ; Zapata-Barrero and Yalaz, 2018 ), and in a number of countries ( Carling, 2015 ), though dominated by Northern Hemisphere scholarship (see, e.g. Piguet et al., 2018 ), especially from North America and Europe ( Bommes and Morawska, 2005 ). Taking stock of various studies on the development of migration studies, we can define several expectations that we will put to an empirical test.

Ravenstein’s (1885) 11 Laws of Migration is widely regarded as the beginning of scholarly thinking on this topic (see Zolberg, 1989 ; Greenwood and Hunt, 2003 ; Castles and Miller, 2014 ; Nestorowicz and Anacka, 2018 ). Thomas and Znaniecki’s (1918) five-volume study of Polish migrants in Europe and America laid is also noted as an early example of migration research. However, according to Greenwood and Hunt (2003 ), migration research ‘took off’ in the 1930s when Thomas (1938) indexed 191 studies of migration across the USA, UK, and Germany. Most ‘early’ migration research was quantitative (see, e.g. Thornthwaite, 1934 ; Thomas, 1938 ). In addition, from the beginning, migration research developed with two empirical traditions: research on internal migration and research on international migration ( King and Skeldon, 2010 ; Nestorowicz and Anacka, 2018 : 2).

In subsequent decades, studies of migration studies describe a burgeoning field. Pedraza-Bailey (1990) refers to a ‘veritable boom’ of knowledge production by the 1980s. A prominent part of these debates focussed around the concept of assimilation ( Gordon, 1964 ) in the 1950s and 1960s (see also Morawska, 1990 ). By the 1970s, in light of the civil rights movements, researchers were increasingly focussed on race and ethnic relations. However, migration research in this period lacked an interdisciplinary ‘synthesis’ and was likely not well-connected ( Kritz et al., 1981 : 10; Pryor, 1981 ; King, 2012 : 9–11). Through the 1980s, European migration scholarship was ‘catching up’ ( Bommes and Morawska, 2005 : 14) with the larger field across the Atlantic. Substantively, research became increasingly mindful of migrant experiences and critical of (national) borders and policies ( Pedraza-Bailey, 1990 : 49). King (2012) also observes this ‘cultural turn’ towards more qualitative anthropological migration research by the beginning of the 1990s, reflective of trends in social sciences more widely ( King, 2012 : 24). In the 1990s, Massey et al. (1993, 1998 ) and Massey (1994) reflected on the state of the academic landscape. Their literature review (1998) notes over 300 articles on immigration in the USA, and over 150 European publications. Despite growth, they note that the field did not develop as coherently in Europe at it had done in North America (1998: 122).

We therefore expect to see a significant growth of the field during the 1980s and 1990s, and more fragmentation, with a prominence of topics related to culture and borders.

At the turn of the millennium, Portes (1997) lists what were, in his view, the five key themes in (international) migration research: 1 transnational communities; 2 the new second generation; 3 households and gender; 4 states and state systems; and 5 cross-national comparisons. This came a year after Cohen’s review of Theories of Migration (1996), which classifies nine key thematic ‘dyads’ in migration studies, such as internal versus international migration; individual versus contextual reasons to migrate; temporary versus permanent migration; and push versus pull factors (see full list in Cohen, 1996 : 12–15). However, despite increasing knowledge production, Portes argues that the problem in these years was the opposite of what Kritz et al. (1981) observe above; scholars had access to and generated increasing amounts of data, but failed to achieve ‘conceptual breakthrough’ ( Portes, 1997 : 801), again suggesting fragmentation in the field.

Thus, in late 1990s and early 2000s scholarship we expect to find a prominence of topics related to these five themes, and a limited number of “new” topics.

In the 21st century, studies of migration studies indicate that there has been a re-orientation away from ‘states and state systems’. This is exemplified by Wimmer and Glick Schiller’s (2002) widely cited commentary on ‘methodological nationalism’, and the alleged naturalisation of nation-state societies in migration research (see Thranhardt and Bommes, 2010 ), leading to an apparent pre-occupation with the integration paradigm since the 1980s according to Favell (2003) and others ( Dahinden, 2016 ; Schinkel, 2018 ). This debate is picked up in Bommes and Morawska’s (2005) edited volume, and Lavenex (2005) . Describing this shift, Geddes (2005) , in the same volume, observes a trend of ‘Europeanised’ knowledge production, stimulated by the research framework programmes of the EU. Meanwhile, on this topic, others highlight a ‘local turn’ in migration and diversity research ( Caponio and Borkert, 2010 ; Zapata-Barrero et al., 2017) .

In this light, we expect to observe a growth in references to European (and other supra-national) level and local-level topics in the 21t century compared to before 2000.

As well as the ‘cultural turn’ mentioned above, King (2012 : 24–25) observes a re-inscription of migration within wider social phenomena—in terms of changes to the constitutive elements of host (and sending) societies—as a key development in recent migration scholarship. Furthermore, transnationalism, in his view, continues to dominate scholarship, though this dominance is disproportionate, he argues, to empirical reality. According to Scholten (2018) , migration research has indeed become more complex as the century has progressed. While the field has continued to grow and institutionalise thanks to networks like International Migration, Integration and Social Cohesion in Europe (IMISCOE) and Network of Migration Research on Africa (NOMRA), this has been in a context of apparently increasing ‘fragmentation’ observed by several scholars for many years (see Massey et al., 1998 : 17; Penninx et al., 2008 : 8; Martiniello, 2013 ; Scholten et al., 2015 : 331–335).

On this basis, we expect a complex picture to emerge for recent scholarship, with thematic references to multiple social phenomena, and a high level of diversity within the topic composition of the field. We furthermore expect increased fragmentation within migration studies in recent years.

The key expectation of this article is, therefore, that the recent topical composition of migration studies displays greater diversity than in previous decades as the field has grown. Following that logic, we hypothesise that with diversification (increasingly varied topical focuses), fragmentation (decreasing connections between topics) has also occurred.

The empirical analysis of the development in volume and topic composition of migration studies is based on the quantitative methods of bibliometrics and topic modelling. Although bibliometric analysis has not been widely used in the field of migration (for some exceptions, see Carling, 2015 ; Nestorowicz and Anacka, 2018 ; Piguet et al., 2018 ; Sweileh et al., 2018 ; van Dalen, 2018 ), this type of research is increasingly popular ( Fortunato et al., 2018 ). A bibliometric analysis can help map what Kajikawa et al. (2007) call an ‘academic landscape’. Our analysis pursues a similar objective for the field of migration studies. However, rather than using citations and authors to guide our analysis, we extract a model of latent topics from the contents of abstracts . In other words, we are focussed on the landscape of content rather than influence.

3.1 Topic modelling

Topic modelling involves a computer-based strategy for identifying topics or topic clusters that figure centrally in a specific textual landscape (e.g. Jiang et al., 2016 ). This is a class of unsupervised machine learning techniques ( Evans and Aceves, 2016 : 22), which are used to inductively explore and discover patterns and regularities within a corpus of texts. Among the most widely used topic models is Latent Dirichlet Allocation (LDA). LDA is a type of Bayesian probabilistic model that builds on the assumption that each document in a corpus discusses multiple topics in differing proportions. Therefore, Document A might primarily be about Topic 1 (60 per cent), but it also refers to terms associated with Topic 2 (30 per cent), and, to a lesser extent, Topic 3 (10 per cent). A topic, then, is defined as a probability distribution over a fixed vocabulary, that is, the totality of words present in the corpus. The advantage of the unsupervised LDA approach that we take is that it does not limit the topic model to our preconceptions of which topics are studied by migration researchers and therefore should be found in the literature. Instead, it allows for an inductive sketching of the field, and consequently an element of surprise ( Halford and Savage, 2017 : 1141–1142). To determine the optimal number of topics, we used the package ldatuning to calculate the statistically optimal number of topics, a number which we then qualitatively validated.

The chosen LDA model produced two main outcomes. First, it yielded a matrix with per-document topic proportions, which allow us to generate an idea of the topics discussed in the abstracts. Secondly, the model returned a matrix with per-topic word probabilities. Essentially, the topics are a collection of words ordered by their probability of (co-)occurrence. Each topic contains all the words from all the abstracts, but some words have a much higher likelihood to belong to the identified topic. The 20–30 most probable words for each topic can be helpful in understanding the content of the topic. The third step we undertook was to look at those most probable words by a group of experts familiar with the field and label them. We did this systematically and individually by first looking at the top 5 words, then the top 30, trying to find an umbrella label that would summarize the topic. The initial labels suggested by each of us were then compared and negotiated in a group discussion. To verify the labels even more, in case of a doubt, we read several selected abstracts marked by the algorithm as exhibiting a topic, and through this were able to further refine the names of the topics.

It is important to remember that this list of topics should not be considered a theoretically driven attempt to categorize the field. It is purely inductive because the algorithm is unable to understand theories, conceptual frames, and approaches; it makes a judgement only on the basis of words. So if words are often mentioned together, the computer regards their probability of belonging to one topic as high.

3.2 Dataset of publications

For the topic modelling, we created a dataset that is representative of publications relevant to migration studies. First, we identified the most relevant sources of literature. Here we chose not only to follow rankings in citation indices, but also to ask migration scholars, in an expert survey, to identify what they considered to be relevant sources. This survey was distributed among a group of senior scholars associated with the IMISCOE Network; 25 scholars anonymously completed the survey. A set of journals and book series was identified from existing indices (such as Google Scholar, Web of Science, and Scopus) which were then validated and added to by respondents. Included in our eventual dataset were all journals and book series that were mentioned at least by two experts in the survey. The dataset includes 40 journals and 4 book series (see Supplementary Data A). Non-English journals were omitted from data collection because the algorithm can only analyse one language. Despite their influence on the field, we also did not consider broader disciplinary journals (for instance, sociological journals or economic journals) for the dataset. Such journals, we acknowledge, have published some of the most important research in the history of migration studies, but even with their omission, it is still possible to achieve our goal of obtaining a representative snapshot of what migration researchers have studied, rather than who or which papers have been most influential. In addition, both because of the language restriction of the algorithm and because of the Global North’s dominance in the field that is mentioned above ( Bommes and Morawska, 2005 ; Piguet et al., 2018 ), there is likely to be an under-representation of scholarship from the Global South in our dataset.

Secondly, we gathered metadata on publications from the selected journals and book series using the Scopus and Web of Science electronic catalogues, and manually collecting from those sources available on neither Scopus nor Web of Science. The metadata included authors, years, titles, and abstracts. We collected all available data up to the end of 2017. In total, 94 per cent of our metadata originated from Scopus, ∼1 per cent from Web of Science, and 5 per cent was gathered manually. One limitation of our dataset lies in the fact that the electronic catalogue of Scopus, unfortunately, does not list all articles and abstracts ever published by all the journals (their policy is to collect articles and abstracts ‘where available’ ( Elsevier, 2017 )). There was no technical possibility of assessing Scopus or WoS’ proportional coverage of all articles actually published. The only way to improve the dataset in this regard would be to manually collect and count abstracts from journal websites. This is also why many relevant books were not included in our dataset; they are not indexed in such repositories.

In the earliest years of available data, only a few journals were publishing (with limited coverage of this on Scopus) specifically on migration. However, Fig. 1 below demonstrates that the numbers constantly grew between 1959 and 2018. As Fig. 1 shows, in the first 30 years (1959–88), the number of migration journals increased by 15, while in the following three decades (1989–2018), this growth intensified as the number of journals tripled to 45 in the survey (see Supplementary Data A for abbreviations).

Number of journals focussed on migration and migration-related diversity (1959–2018) Source: Own calculations.

Within all 40 journals in the dataset, we were able to access and extract for our analysis 29,844 articles, of which 22,140 contained abstracts. Furthermore, we collected 901 available abstracts of chapters in the 4 book series: 2 series were downloaded from the Scopus index (Immigration and Asylum Law in Europe; Handbook of the Economics of International Migration), and the abstracts of the other 2 series, selected from our expert survey (the IMISCOE Research Series Migration Diasporas and Citizenship), were collected manually. Given the necessity of manually collecting the metadata for 896 abstracts of the chapters in these series, it was both practical and logical to set these two series as the cut-off point. Ultimately, we get a better picture of the academic landscape as a whole with some expert-approved book series than with none .

Despite the limitations of access, we can still have an approximate idea on how the volume of publications changed overtime. The chart ( Fig. 2 ) below shows that both the number of published articles and the number of abstracts of these articles follow the same trend—a rapid growth after the turn of the century. In 2017, there were three times more articles published per year than in 2000.

Publications and abstracts in the dataset (1959–2018).

The cumulative graph ( Fig. 3 ) below shows the total numbers of publications and the available abstracts. For the creation of our inductively driven topic model, we used all available abstracts in the entire timeframe. However, to evaluate the dynamics of topics over time, we decided to limit the timeframe of our chronological analyses to 1986–2017, because as of 1986, there were more than 10 active journals and more articles had abstracts. This analysis therefore covers the topical evolution of migration studies in the past three decades.

Cumulative total of publications and abstracts (1959–2017).

Migration studies has only internationalised very slowly in support of what others have previously argued ( Bommes and Morawska, 2005 ; Piguet et al., 2018 ). Figure 4 gives a snapshot of the geographic dispersion of the articles (including those without abstracts) that we collected from Scopus. Where available, we extracted the country of authors’ university affiliations. The colour shades represent the per capita publication volume. English-language migration scholarship has been dominated by researchers based, unsurprisingly, in Anglophone and Northern European countries.

Migration research output per capita (based on available affiliation data within dataset).

The topic modelling (following the LDA model) led us, as discussed in methods, to the definition of 60 as the optimal number of topics for mapping migration studies. Each topic is a string of words that, according to the LDA algorithm, belong together. We reviewed the top 30 words for each word string and assigned labels that encapsulated their meaning. Two of the 60 word strings were too generic and did not describe anything related to migration studies; therefore, we excluded them. Subsequently, the remaining 58 topics were organised into a number of clusters. In the Table 1 below, you can see all the topic labels, the topic clusters they are grouped into and the first 5 (out of 30) most probable words defining those topics.

Topics in migration studies

After presenting all the observed topics in the corpus of our publication data, we examined which topics and topic clusters are most frequent in general (between 1964 and 2017), and how their prominence has been changing over the years. On the basis of the matrix of per-item topic proportions generated by LDA analysis, we calculated the shares of each topic in the whole corpus. On the level of individual topics, around 25 per cent of all abstract texts is about the top 10 most prominent topics, which you can see in Fig. 5 below. Among those, #56 identity narratives (migration-related diversity), #39 migration theory, and #29 migration flows are the three most frequently detected topics.

Top 10 topics in the whole corpus of abstracts.

On the level of topic clusters, Fig. 6 (left) shows that migration-related diversity (26 per cent) and migration processes (19 per cent) clearly comprise the two largest clusters in terms of volume, also because they have the largest number topics belonging to them. However, due to our methodology of labelling these topics and grouping them into clusters, it is complicated to make comparisons between topic clusters in terms of relative size, because some clusters simply contain more topics. Calculating average proportions of topics within each cluster allows us to control for the number of topics per cluster, and with this measure, we can better compare the relative prominence of clusters. Figure 6 (right) shows that migration research and statistics have the highest average of topic proportions, followed by the cluster of migration processes and immigrant incorporation.

Topic proportions per cluster.

An analysis on the level of topic clusters in the project’s time frame (1986–2017) reveals several significant trends. First, when discussing shifts in topics over time, we can see that different topics have received more focus in different time frames. Figure 7 shows the ‘age’ of topics, calculated as average years weighted by proportions of publications within a topic per year. The average year of the articles on the same topic is a proxy for the age of the topic. This gives us an understanding of which topics were studied more often compared with others in the past and which topics are emerging. Thus, an average year can be understood as the ‘high-point’ of a topic’s relative prominence in the field. For instance, the oldest topics in our dataset are #22 ‘Migrant demographics’, followed by #45 ‘Governance of migration’ and #46 ‘Migration statistics and survey research’. The newest topics include #14 ‘Mobilities’ and #48 ‘Intra-EU mobility’.

Average topic age, weighted by proportions of publications (publications of 1986–2017). Note: Numbers near dots indicate the numeric id of topics (see Table 1 for the names).

When looking at the weighted ‘age’ of the clusters, it becomes clear that the focus on migration research and statistics is the ‘oldest’, which echoes what Greenwood and Hunt (2003 ) observe. This resonates with the idea that migration studies has roots in more demographic studies of migration and diversity (cf. Thornthwaite, 1934 ; Thomas, 1938 ), which somewhat contrasts with what van Dalen (2018) has found. Geographies of migration (studies related to specific migration flows, origins, and destinations) were also more prominent in the 1990s than now, and immigrant incorporation peaked at the turn of the century. However, gender and family, diversity, and health are more recent themes, as was mentioned above (see Fig. 8 ). This somewhat indicates a possible post-methodological nationalism, post-integration paradigm era in migration research going hand-in-hand with research that, as King (2012) argues, situates migration within wider social and political domains (cf. Scholten, 2018 ).

Diversity of topics and topic clusters (1985–2017).

Then, we analysed the diversification of publications over the various clusters. Based on the literature review, we expected the diversification to have increased over the years, signalling a move beyond paradigmatic closure. Figure 9 (below) shows that we can hardly speak of a significant increase of diversity in migration studies publications. Over the years, only a marginal increase in the diversity of topics is observed. The Gini-Simpson index of diversity in 1985 was around 0.95 and increased to 0.98 from 1997 onwards. Similarly, there is little difference between the sizes of topic clusters over the years. Both ways of calculating the Gini-Simpson index of diversity by clusters resulted in a rather stable picture showing some fluctuations between 0.82 and 0.86. This indicates that there has never been a clear hegemony of any cluster at any time. In other words, over the past three decades, the diversity of topics and topic clusters was quite stable: there have always been a great variety of topics discussed in the literature of migration studies, with no topic or cluster holding a clear monopoly.

Average age of topic clusters, weighted by proportions (publications of 1986–2017).

Subsequently, we focussed on trends in topic networks. As our goal is to describe the general development of migration studies as a field, we decided to analyse topic networks in three equal periods of 10 years (Period 1 (1988–97); Period 2 (1998–2007); Period 3 (2008–17)). On the basis of the LDA-generated matrix with per-abstract topic proportions (The LDA algorithm determines the proportions of all topics observed within each abstract. Therefore, each abstract can contain several topics with a substantial prominence), we calculated the topic-by-topic Spearman correlation coefficients in each of the time frames. From the received distribution of the correlation coefficients, we chose to focus on the top 25 per cent strongest correlations period. In order to highlight difference in strength of connections, we assigned different weights to the correlations between the topics. Coefficient values above the 75th percentile (0.438) but ≤0.5 were weighted 1; correlations above 0.5 but ≤0.6 were weighted 2; and correlations >0.6 were weighted 3. We visualised these topic networks using the software Gephi.

To compare networks of topics in each period, we used three common statistics of network analysis: 1 average degree of connections; 2 average weighted degree of connections; and 3 network density. The average degree of connections shows how many connections to other topics each topic in the network has on average. This measure can vary from 0 to N − 1, where N is the total number of topics in the network. Some correlations of topics are stronger and were assigned the Weight 2 or 3. These are included in the statistics of average weighted degree of connections, which shows us the variations in strength of existing connections between the topics. Network density is a proportion of existing links over the number of all potentially possible links between the topics. This measure varies from 0 = entirely disconnected topics to 1 = extremely dense network, where every topic is connected to every topic.

Table 2 shows that all network measures vary across the three periods. In Period 1, each topic had on average 21 links with other topics, while in Period 2, that number was much lower (11.5 links). In Period 3, the average degree of connections grew again, but not to the level of Period 1. The same trend is observed in the strength of these links—in Period 1, the correlations between the topics were stronger than in Period 3, while they were the weakest in Period 2. The density of the topic networks was highest in Period 1 (0.4), then in Period 2, the topic network became sparser before densifying again in Period 3 (but not to the extent of Period 1’s density).

Topic network statistics

These fluctuations on network statistics indicate that in the years 1988–97, topics within the analysed field of migration studies were mentioned in the same articles and book chapters more often, while at the turn of the 21st century, these topic co-occurrences became less frequent; publications therefore became more specialised and topics were more isolated from each other. In the past 10 years, migration studies once again became more connected, the dialogues between the topics emerged more frequently. These are important observations about topical development in the field of migration studies. The reasons behind these changes require further, possibly more qualitative explanation.

To get a more in-depth view of the content of these topic networks, we made an overview of the changes in the topic clusters across the three periods. As we can see in Fig. 10 , some changes emerge in terms of the prominence of various clusters. The two largest clusters (also by the number of topics within them) are migration-related diversity and migration processes. The cluster of migration-related diversity increased in its share of each period’s publications by around 20 per cent. This reflects our above remarks on the literature surrounding the integration debate, and the ‘cultural turn’ King mentions (2012). And the topic cluster migration processes also increased moderately its share.

Prominence and change in topic clusters 1988–2017.

Compared with the first period, the topic cluster of gender and family studies grew the fastest, with the largest growth observed in the turn of the century (relative to its original size). This suggests a growing awareness of gender and family-related aspects of migration although as a percentage of the total corpus it remains one the smallest clusters. Therefore, Massey et al.’s (1998) argument that households and gender represented a quantitatively significant pillar of migration research could be considered an overestimation. The cluster of health studies in migration research also grew significantly in the Period 2 although in Period 3, the percentage of publications in this cluster diminished. This suggests a rising awareness of health in relation to migration and diversity (see Sweileh et al., 2018 ) although this too remains one of the smallest clusters.

The cluster on Immigrant incorporation lost prominence the most over the past 30 years. This seems to resonate with the argument that ‘integrationism’ or the ‘integration paradigm’ was rather in the late 1990s (see Favell, 2003 ; Dahinden, 2016 ) and is losing its prominence. A somewhat slower but steady loss was also observed in the cluster of Geographies of migration and Migration research and statistics. This also suggests not only a decreasing emphasis on demographics within migration studies, but also a decreasing reflexivity in the development of the field and the focus on theory-building.

We will now go into more detail and show the most connected topics and top 10 most prominent topics in each period. Figures 11–13 show the network maps of topics in each period. The size of circles reflects the number and strength of links per each topic: the bigger the size, the more connected this topic is to the others; the biggest circles indicate the most connected topics. While the prominence of a topic is measured by the number of publications on that topic, it is important to note that the connectedness the topic has nothing necessarily to do with the amount of publications on that topic; in theory, a topic could appear in many articles without any reference to other topics (which would mean that it is prominent but isolated).

Topic network in 1988–97. Note: Numbers indicate topics' numerical ids, see Table 1 for topics' names.

Topic network in 1998–2007. Note: Numbers indicate topics' numerical ids, see Table 1 for topics' names.

Topic network in 2008–2017. Note: Numbers indicate topics' numerical ids, see Table 1 for topics' names.

Thus, in the section below, we describe the most connected and most prominent topics in migration research per period. The degree of connectedness is a useful indicator of the extent to which we can speak of a ‘field’ of migration research. If topics are well-connected, especially in a context of increased knowledge production and changes in prominence among topics, then this would suggest that a shared conceptual and theoretical language exists.

6.1 Period 1: 1988–97

The five central topics with the highest degree of connectedness (the weighted degree of connectedness of these topics was above 60) were ‘black studies’, ‘mobilities’, ‘ICT, media and migration’, ‘migration in/from Israel and Palestine’, and ‘intra-EU mobility’. These topics are related to geopolitical regions, ethnicity, and race. The high degree of connectedness of these topics shows that ‘they often occurred together with other topics in the analysed abstracts from this period’. This is expected because research on migration and diversity inevitably discusses its subject within a certain geographical, political, or ethnic scope. Geographies usually appear in abstracts as countries of migrants’ origin or destination. The prominence of ‘black studies’ reflects the dominance of American research on diversity, which was most pronounced in this period ( Fig. 11 ).

The high degree of connectedness of the topics on ICT and ‘media’ is indicative of wider societal trends in the 1990s. As with any new phenomenon, it clearly attracted the attention of researchers who wanted to understand its relationship with migration issues.

Among the top 10 topics with the most publications in this period (see Supplementary Data B) were those describing the characteristics of migration flows (first) and migration populations (third). It goes in line with the trends of the most connected topics described above. Interest in questions of migrants’ socio-economic position (fourth) in the receiving societies and discussion on ‘labour migration’ (ninth) were also prevalent. Jointly, these topics confirm that in the earlier years, migration was ‘studied often from the perspectives of economics and demographics’ ( van Dalen, 2018 ).

Topics, such as ‘education and language training’ (second), community development’ (sixth), and ‘intercultural communication’ (eighth), point at scholarly interest in the issues of social cohesion and socio-cultural integration of migrants. This lends strong support to Favell’s ‘integration paradigm’ argument about this period and suggests that the coproduction of knowledge between research and policy was indeed very strong ( Scholten, 2011 ). This is further supported by the prominence of the topic ‘governance of migration’ (seventh), reflecting the evolution of migration and integration policymaking in the late 1980s and beginning of the 1990s, exemplified by the development of the Schengen area and the EU more widely; governance of refugee flows from the Balkan region (also somewhat represented in the topic ‘southern-European migration’, which was the 10th most prominent); and governance of post-Soviet migration. Interestingly, this is the only period in which ‘migration histories’ is among the top 10 topics, despite the later establishment of a journal dedicated to the very discipline of history. Together these topics account for 42 per cent of all migration studies publications in that period of time.

6.2 Period 2: 1998–2007

In the second period, as the general degree of connectedness in the topic networks decreased, the following five topics maintained a large number of connections in comparison to others, as their average weighted degree of connections ranged between 36 and 57 ties. The five topics were ‘migration in/from Israel and Palestine’, ‘black studies’, ‘Asian migration’, ‘religious diversity’, and ‘migration, sexuality, and health’ ( Fig. 12 ).

Here we can observe the same geographical focus of the most connected topics, as well as the new trends in the migration research. ‘Asian migration’ became one of the most connected topics, meaning that migration from/to and within that region provoked more interest of migration scholars than in the previous decade. This development appears to be in relation to high-skill migration, in one sense, because of its strong connections with the topics ‘Asian expat migration’ and ‘ICT, media, and migration’; and, in another sense, in relation to the growing Muslim population in Europe thanks to its strong connection to ‘religious diversity’. The high connectedness of the topic ‘migration sexuality and health’ can be explained by the dramatic rise of the volume of publications within the clusters ‘gender and family’ studies and ‘health’ in this time-frame as shown in the charts on page 13, and already argued by Portes (1997) .

In this period, ‘identity narratives’ became the most prominent topic (see Supplementary Data B), which suggests increased scholarly attention on the subjective experiences of migrants. Meanwhile ‘migrant flows’ and ‘migrant demographics’ decreased in prominence from the top 3 to the sixth and eighth position, respectively. The issues of education and socio-economic position remained prominent. The emergence of topics ‘migration and diversity in (higher) education’ (fifth) and ‘cultural diversity’ (seventh) in the top 10 of this period seem to reflect a shift from integrationism to studies of diversity. The simultaneous rise of ‘migration theory’ (to fourth) possibly illustrates the debates on methodological nationalism which emerged in the early 2000s. The combination of theoretical maturity and the intensified growth in the number of migration journals at the turn of the century suggests that the field was becoming institutionalised.

Overall, the changes in the top 10 most prominent topics seem to show a shifting attention from ‘who’ and ‘what’ questions to ‘how’ and ‘why’ questions. Moreover, the top 10 topics now account only for 26 per cent of all migration studies (a 15 per cent decrease compared with the period before). This means that there were many more topics which were nearly as prominent as those in the top 10. Such change again supports our claim that in this period, there were more intensive ‘sub-field’ developments in migration studies than in the previous period.

6.3 Period 3: 2008–17

In the last decade, the most connected topics have continued to be: ‘migration in/from Israel and Palestine’, ‘Asian migration’, and ‘black studies’. The hypothetical reasons for their central position in the network of topics are the same as in the previous period. The new most-connected topics—‘Conflicts, violence, and migration’, together with the topic ‘Religious diversity’—might indicate to a certain extent the widespread interest in the ‘refugee crisis’ of recent years ( Fig. 13 ).

The publications on the top 10 most prominent topics constituted a third of all migration literature of this period analysed in our study. A closer look at them reveals the following trends (see Supplementary Data B for details). ‘Mobilities’ is the topic of the highest prominence in this period. Together with ‘diasporas and transnationalism’ (fourth), this reflects the rise of critical thinking on methodological nationalism ( Wimmer and Glick Schiller, 2002 ) and the continued prominence of transnationalism in the post-‘mobility turn’ era ( Urry (2007) , cited in King, 2012 ).

The interest in subjective experiences of migration and diversity has continued, as ‘identity narratives’ continues to be prominent, with the second highest proportion of publications, and as ‘Discrimination and socio-psychological issues’ have become the eighth most prominent topic. This also echoes an increasing interest in the intersection of (mental) health and migration (cf. Sweileh et al., 2018 ).

The prominence of the topics ‘human rights law and protection’ (10th) and ‘governance of migration and diversity’ (9th), together with ‘conflicts, violence, and migration’ being one of the most connected topics, could be seen as a reflection of the academic interest in forced migration and asylum. Finally, in this period, the topics ‘race and racism’ (fifth) and ‘black studies’ (seventh) made it into the top 10. Since ‘black studies’ is also one of the most connected topics, such developments may reflect the growing attention to structural and inter-personal racism not only in the USA, perhaps reflecting the #blacklivesmatter movement, as well as in Europe, where the idea of ‘white Europeanness’ has featured in much public discourse.

6.4 Some hypotheses for further research

Why does the connectedness of topics change across three periods? In an attempt to explain these changes, we took a closer look at the geographical distribution of publications in each period. One of the trends that may at least partially explain the loss of connectedness between the topics in Period 2 could be related to the growing internationalisation of English language academic literature linked to a sharp increase in migration-focussed publications during the 1990s.

Internationalisation can be observed in two ways. First, the geographies of English language journal publications have become more diverse over the years. In the period 1988–97, the authors’ institutional affiliations spanned 57 countries. This increased to 72 in 1998–2007, and then to 100 in 2007–18 (we counted only those countries which contained at least 2 publications in our dataset). Alongside this, even though developed Anglophone countries (the USA, Canada, Australia, the UK, Ireland, and New Zealand) account for the majority of publications of our overall dataset, the share of publications originating from non-Anglophone countries has increased over time. In 1988–97, the number of publications from non-Anglophone European (EU+EEA) countries was around 13 per cent. By 2008–17, this had significantly increased to 28 per cent. Additionally, in the rest of the world, we observe a slight proportional increase from 9.5 per cent in the first period to 10.6 per cent in the last decade. Developed Anglophone countries witness a 16 per cent decrease in their share of all articles on migration. The trends of internationalisation illustrated above, combined with the loss of connectedness at the turn of the 21st century, seem to indicate that English became the lingua-franca for academic research on migration in a rather organic manner.

It is possible that a new inflow of ideas came from the increased number of countries publishing on migration whose native language is not English. This rise in ‘competition’ might also have catalysed innovation in the schools that had longer established centres for migration studies. Evidence for this lies in the rise in prominence of the topic ‘migration theory’ during this period. It is also possible that the expansion of the European Union and its research framework programmes, as well as the Erasmus Programmes and Erasmus Mundus, have perhaps brought novel, comparative, perspectives in the field. All this together might have created fruitful soil for developing unique themes and approaches, since such approaches in theory lead to more success and, crucially, more funds for research institutions.

This, however, cannot fully explain why in Period 3 the field became more connected again, other than that the framework programmes—in particular framework programme 8, Horizon 2020—encourage the building of scientific bridges, so to speak. Our hypothesis is thus that after the burst of publications and ideas in Period 2, scholars began trying to connect these new themes and topics to each other through emergent international networks and projects. Perhaps even the creation and work of the IMISCOE (2004-) and NOMRA (1998-) networks contributed to this process of institutionalisation. This, however, requires much further thought and exploration, but for now, we know that the relationship between the growth, the diversification, and the connectedness in this emergent research field is less straightforward than we might previously have suggested. This begs for further investigation perhaps within a sociology of science framework.

This article offers an inductive mapping of the topical focus of migration studies over a period of more than 30 years of development of the research field. Based on the literature, we expected to observe increasing diversity of topics within the field and increasing fragmentation between the topics, also in relation to the rapid growth in volume and internationalisation of publications in migration studies. However, rather than growth and increased diversity leading to increased fragmentation, our analysis reveals a complex picture of a rapidly growing field where the diversity of topics has remained relatively stable. Also, even as the field has internationalised, it has retained its overall connectedness, albeit with a slight and temporary fragmentation at the turn of the century. In this sense, we can argue that migration studies have indeed come of age as a distinct research field.

In terms of the volume of the field of migration studies, our study reveals an exponential growth trajectory, especially since the mid-1990s. This involves both the number of outlets and the number of publications therein. There also seems to be a consistent path to internationalisation of the field, with scholars from an increasing number of countries publishing on migration, and a somewhat shrinking share of publications from Anglo-American countries. However, our analysis shows that this has not provoked an increased diversity of topics in the field. Instead, the data showed that there have been several important shifts in terms of which topics have been most prominent in migration studies. The field has moved from focusing on issues of demographics, statistics, and governance, to an increasing focus on mobilities, migration-related diversity, gender, and health. Also, interest in specific geographies of migration seems to have decreased.

These shifts partially resonated with the expectations derived from the literature. In the 1980s and 1990s, we observed the expected widespread interest in culture, seen in publications dealing primarily with ‘education and language training’, ‘community development’, and ‘intercultural communication’. This continued to be the case at the turn of the century, where ‘identity narratives’ and ‘cultural diversity’ became prominent. The expected focus on borders in the periods ( Pedraza-Bailey, 1990 ) was represented by the high proportion of research on the ‘governance of migration’, ‘migration flows’, and in the highly connected topic ‘intra-EU mobility’. Following Portes (1997) , we expected ‘transnational communities’, ‘states and state systems’, and the ‘new second generation’ to be key themes for the ‘new century’. Transnationalism shifts attention away from geographies of migration and nation–states, and indeed, our study shows that ‘geographies of migration’ gave way to ‘mobilities’, the most prominent topic in the last decade. This trend is supported by the focus on ‘diasporas and transnationalism’ and ‘identity narratives’ since the 2000s, including literature on migrants’ and their descendants’ dual identities. These developments indicate a paradigmatic shift in migration studies, possibly caused by criticism of methodological nationalism. Moreover, our data show that themes of families and gender have been discussed more in the 21st century, which is in line with Portes’ predictions.

The transition from geographies to mobilities and from the governance of migration to the governance of migration-related diversity, race and racism, discrimination, and social–psychological issues indicates a shifting attention in migration studies from questions of ‘who’ and ‘what’ towards ‘how’ and ‘why’. In other words, a more nuanced understanding of the complexity of migration processes and consequences emerges, with greater consideration of both the global and the individual levels of analysis.

However, this complexification has not led to thematic fragmentation in the long run. We did not find a linear trend towards more fragmentation, meaning that migration studies have continued to be a field. After an initial period of high connectedness of research mainly coming from America and the UK, there was a period with significantly fewer connections within migration studies (1998–2007), followed by a recovery of connectedness since then, while internationalisation has continued. What does this tell us?

We may hypothesise that the young age of the field and the tendency towards methodological nationalism may have contributed to more connectedness in the early days of migration studies. The accelerated growth and internationalisation of the field since the late 1990s may have come with an initial phase of slight fragmentation. The increased share of publications from outside the USA may have caused this, as according to Massey et al. (1998) , European migration research was then more conceptually dispersed than across the Atlantic. The recent recovery of connectedness could then be hypothesised as an indicator of the field’s institutionalisation, especially at the European level, and growing conceptual and theoretical development. As ‘wisdom comes with age’, this may be an indication of the ‘coming of age’ of migration studies as a field with a shared conceptual and theoretical foundation.

The authors would like to thank the three anonymous reviewers for their constructive feedback, as well as dr. J.F. Alvarado for his advice in the early stages of work on this article.

This research is associated with the CrossMigration project, funded by the European Union's Horizon 2020 research and innovation programme under the grant agreement Ares(2017) 5627812-770121.

Conflict of interest statement . None declared.

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Migration Drivers: Why Do People Migrate?

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• Mathias Czaika 2 &
• Constantin Reinprecht 2  

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Growing social and economic inequalities, and consequently, unfulfilled life aspirations trigger the migration intentions of millions, if not billions of people around the world. Surveys by Gallup World Poll suggest that more than 750 million adults would like to migrate if they had the chance to do so (Esipova et al., 2018). Hence, globally ‘only’ one in eight adults express a desire to migrate. This is a surprisingly small fraction given the fact that a much larger but unknown number of people would have good reasons to migrate in order to realise economic, professional, political, or social opportunities elsewhere. At the same time, only small fractions of those who aspire to migrate are actually able to realise it.

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Growing social and economic inequalities, and consequently, unfulfilled life aspirations trigger the migration intentions of millions, if not billions of people around the world. Surveys by Gallup World Poll suggest that more than 750 million adults would like to migrate if they had the chance to do so (Esipova et al., 2018 ). Hence, globally ‘only’ one in eight adults express a desire to migrate. This is a surprisingly small fraction given the fact that a much larger but unknown number of people would have good reasons to migrate in order to realise economic, professional, political, or social opportunities elsewhere. At the same time, only small fractions of those who aspire to migrate are actually able to realise it.

However, why do people want to migrate in the first place? At specific moments in people’s lives a number of factors come together and stimulate migration intentions, which, given some achievable livelihood opportunities, may end up in temporary or permanent moves to another domestic or international destination. Factors that drive both migration intentions (and aspirations) and actual moves are manifold and multifaceted, and over the past decades, migration researchers have been identifying and describing numerous factors and contexts that shape both individual migration trajectories and broader migration processes. Researchers studying drivers of migration are hereby asking: what are relevant factors that are driving migration, and how do these drivers operate in time and space? To what extent and in what ways do they influence, i.e. trigger or hinder, migration decision-making of some people but not of others? Moreover, how do multidimensional migration drivers interact and create complex driver configurations that may affect some people more than others in aspiring and realising migration as a viable behavioural option?

A term that is often used in migration studies is migration determinants , suggesting a structural and ‘deterministic’, i.e. causal, relationship between some external factors and migration. However, this conception is rather misleading as it ignores the central role of human agency in migration processes (Bakewell, 2010 ; Carling & Talleraas, 2016 ) and the often indirect or intervening role of some contextual factors in a migration (decision-making) process. Root causes is another term widely used, particularly in policy circles, where root causes are mostly understood as ‘the social and political conditions that induce departures - especially poverty, repression, and violent conflict’ (Carling & Talleraas, 2016 , p. 6). But also this concept of a migration-inducing factor is relatively narrow because it is rarely a single or specific fundamental causal factor that is setting people in motion. Rather, it is a number of factors that are mutually mediating and conjointly shaping migration decisions and broader migration dynamics and patterns. We therefore prefer the term migration drivers (rather than causes or determinants) of migration as ‘structural elements that enable and constrain the exercise of agency by social actors’ and make ‘certain decisions, routes or destinations more likely’ (Van Hear et al., 2018 , p. 928).

At a higher level of aggregation, structural disparities between places, which may turn out as locations of origin and destination, create the context that make migration decisions more likely. These spatial disparities may reflect long-standing social and economic inequalities and gaps in living standards both within countries and internationally between, for instance, the global North and South—as well as cyclical or seasonal economic fluctuations. At lower levels of aggregation, i.e. at the meso- and micro-level, migration drivers facilitate or constrain migration by affecting perceptions about migration opportunities and influencing people’s capacities to realise these opportunities. Consequently, people’s perceptions about spatial opportunity gaps are necessary pre-conditions in people’s migration decision-making.

Besides structurally embedded and therefore mostly slow-changing disparities in livelihood opportunities, specific events, and sudden developments, including some rapid policy changes, may both predispose and ultimately trigger migration. The complex interplay of multiple economic, political, social, and other gradual developments and sudden events may dynamically change migration opportunities for heterogeneous groups of people. The concept of complex driver environments , that is time-space-dependent configurations of multidimensional drivers that define people’s willingness and ability to change life situations through migration, forms the theoretical underpinning of this chapter.

In the remainder of this chapter, we briefly outline some key, and by now, classical theories of migration that are often referred to in explaining migration outcomes. We then propose a taxonomy of 24 migration drivers, categorised into nine driver dimensions, and elaborate on the key features of their configurational interplay that characterises migration driver environments. Following that, we provide a meta-review of scholarly work on migration drivers and discusses the state of knowledge on person-specific, group-specific, and more macro-structural and external migration drivers.

1 Migration Drivers: The Theoretical Basis

1.1 classical theories of migration: an overview.

The reasons why people migrate have been theorised and studied for decades and the scientific literature has identified a number of fundamental dimensions of migration drivers including economic, political, social, cultural, demographic, and ecological factors (for comprehensive reviews see Ghatak et al., 1996 ; Hagen-Zanker, 2008 ; King, 2012 ; Massey et al., 1993 ). We briefly outline some influential theories of migration including functional perspectives of migration being instrumental for income maximisation or historical-structural theories explaining migration as the result of class-based deprivations in (global) capitalist systems.

Neoclassical migration theory, based on Sjaastad’s ( 1962 ) cost-benefit model and Lee’s ( 1966 ) push-pull model of migration , suggests that individuals migrate due to the discrepancy in economic opportunities between those available at a destination and a lack thereof at the place of residence. The interrelated decisions of whether and where to migrate are linked to existence of substantive income or utility differentials between places. People tend to move if expected returns to migration are beneficial. Although Lee’s push-pull model, as well as the augmented gravity model, explain overall migration flows between locations relatively well, these models have also been criticised for failing to explain why the majority of people do not migrate despite severe income differentials (Bogue, 1977 ; Hagen-Zanker, 2008 ). One reason for immobility is the fact that migrants are not simple pushed and pulled between places according to wage gaps or livelihood differentials, but people’s own agency and self-determination decides whether and where to relocate (Bakewell, 2010 ).

Another critique of the neoclassical migration model is that it suffers from methodological individualism, i.e. it assumes that individuals are the main decision-making units. However, individuals belong to households and communities who influence or even take the decisions, or people may even move as a family. Scholars have therefore urged for a reconsideration migration decision-making, and two perspectives on the role of households have emerged (Boyd, 1989 ; Sell & De Jong, 1978 ). First, family structure and functions have both direct and indirect effects on migration decision-making but the individual remains the decision-maker, and secondly, the family is the ultimate migration decision-making unit.

Harbison ( 1981 ) argues that family structure and function are not merely additional explanatory variables. Families transmit information and shape individuals’ motivations, values, and ultimately migration norms, thereby directly and indirectly affecting migration decision-making. Further, structural and functional family characteristics affect the perceptions of costs and benefits associated with migration. However, it is unclear how potential intra-family dissent affects migration decision-making processes. Bargaining models explain family migration decisions by interrelated utility maximisations at the household and the individual level, respectively (Abraham & Nisic, 2012 ). However, bargaining do often not consider coordination and communication problems (Kalter, 1998 ).

The new economics of labour migration (Stark & Bloom, 1985 ) put the household or family at the centre of migration decision-making, arguing that households are able to diversify income risks and control uncertainty by allocating individual household members to specific income sources, and therefore, alternative migration options (Haug, 2008 ; Massey et al., 1993 ). Family ties embody important social externalities, which affect migration decision-making (Mincer, 1978 ). For instance, negative externalities, represented by strong ties to the place and people at origin, decrease the likelihood of migration. At the same time, family and friends living elsewhere establish positive externalities by transmitting valuable information that reduces migration-related uncertainty (Stark & Bloom, 1985 ). Externalities are also the driving force behind migration when relative rather than absolute deprivation is spurring migration aspirations, as people compare their own well-being, income and living standards to others around them (Stark & Taylor, 1989 , 1991 ). More recent migration decision-making models have been adapted as they combine individual factors with a focus on the family or household (Anam & Chiang, 2007 ).

Network theory claims that migration as a social outcome is based on the complex interplay of decisions taken by individual actors, family and friends, migrant organisations, and other economic and political factors (Boyd, 1989 ). Social networks hereby influence not only whether and how migration takes place, but also where migrants are predominantly moving to (Haug, 2008 ). Ritchey ( 1976 ) states that people with access to relevant social capital incentivises migration by providing information, financial assistance, and practical support. However, Heitmueller ( 2006 ) adds that network effects can go in both directions, that is information provided through networks is not necessarily only positive but can also discourage migration. More migrants at a particular place has a positive community and family effect attracting more migrants to this destination. At the same time, local labour markets may saturate and wages might in turn decrease. Therefore, there might be a point where migrants in destination countries either withhold information or send even negative messages ‘[…] to hamper further migration’ (Heitmueller, 2006 , p. 706).

Network theory is also a useful perspective to understand the perpetuation of migration (Massey et al., 1993 ) and destination choice once migrant networks are established. However, network theory does also not explain migration when migrant networks are absent, or how migrant networks dissolve (de Haas, 2010 ). Epstein ( 2008 ) distinguishes between network and herd effects. Herd behaviour means discounting or disregarding private information to follow the behaviour of others. This is rational given the assumption that others base their decisions on better information (Epstein, 2002 ). Herd behaviour results in migrants following the flow rather than the stock (i.e. established network) of previous migrants. While herd effects cannot account for new, pioneering migration, they can explain migrant clustering in destinations when network effects are still likely to be small.

As emigration may continue over time, a “ culture of migration ” might emerge that changes a society’s values and perceptions associated with migration (Massey et al., 1993 ). The culture of migration manifests at the individual level—people who have migrated in the past are more likely to migrate in the future—and the community level when migration becomes a normative behaviour—a “rite of passage”—in the community (Kandel & Massey, 2002 ). When information about migration options diffuses widely in the community, it can perpetuate migration. In a culture of migration, this information can also spread to people without direct access to migrant networks. The culture of migration, in contrast to network theory, can hence explain why people may migrate even in the absence of networks (Ali, 2007 ).

While the theories discussed so far have mostly focused on individuals or households as the decision-making unit, more structural theories conceptualise migration as an intrinsic part of historical processes and societal developments. Zelinsky ( 1971 ) argues that demographic transitions and modernisation processes explain the development and changing patterns of human mobility in Europe over the last 200 years. Historical-structural models, based upon neo-Marxist interpretations of capitalism, stress the importance of structures and forces operating at the macro-structural level. Migration is driven by the global demand and supply of cheap and flexible workers in segmented labour markets to sustain continued economic growth and development in capitalist labour-recruiting countries (Piore, 1979 ; Sassen, 1991 ). In the same way, world systems theory holds that capitalist systems destroy traditional economic structures and livelihoods, and thereby shape domestic and international migration patterns (Wallerstein, 1974 ). The world capitalist system, disguised in colonialism, has hereby triggered an ‘age of migration’ in the nineteenth and early twentieth century.

Contemporarily, in the postcolonial era, world systems theory claims that postcolonial systems resemble those during colonialism due to neoliberalism and corporate capitalism, including transnational ties (international trade, foreign investment etc.) between former colonial powers and colonies, but also a shared history and culture, language, administrative links, and migration governance (Fawcett, 1989 ). Historical-structural models have mainly been criticised for denying migrants’ agency and regarding them “as little more than passive pawns in the play of great powers and world processes presided over by the logic of capital accumulation” (Arango, 2004 , p. 27). Migration flows further do not always correspond to capital flows, as demonstrated by increasing South-South migration. These models also disregard the role of states, which political economy models of migration sought to rectify. Proponents of political economy models hold that political systems and geopolitical shifts in global economic, political, and military power drive migration processes (Castles, 2010 ; Czaika & de Haas, 2014 ).

1.2 Migration Drivers: Dimensions and Functions

Migration theories establish multiple reasons of why, when, where, and how people migrate. They attribute different forms and levels of agency to individual migrants. While some theories point to specific factors that drive migration, others remain vague about the actual factors that drive migration. The circumstances, the ways and modes, and the extent to which a set of driving factors may influence migration (decision-making) processes are dependent on the functionality of migration drivers, which is a central aspect in understanding the specific role (single or combinations of) migration drivers may play in migration. What almost all migration theories have in common is that migration, as both an individual behavioural option and a broader collective action, is highly context-dependent. Consequently, the interplay of factors and configuration of complex driver environments the effect on migration outcomes is very specific to the time and space in which migration decisions are taken.

Context-specific functionalities of migration drivers can be distinguished along some key functions (cf. Van Hear et al., 2018 ). Predisposing factors reflect fundamental societal structures and structural disparities and define the broadest, most fundamental layer of opportunity structures (cf. de Haas, 2010 ). As a basic methodological premise, we may assume that people respond to extrinsic or intrinsic predisposing stimuli when deciding about migration (Czaika & Reinprecht, 2020 ). Predisposing factors do not directly, nor in an ‘unfiltered’ manner, affect people’s decision-making but are mediated by drivers that facilitate, constrain, accelerate, consolidate, or diminish migration (Van Hear et al., 2018 ). For instance, structures of economic and social inequalities may be mediated by cultural norms (e.g. class-based, social status) or provisions of political and civil rights, which may absorb or neutralise the migration-stimulating effect of inequality structures. Similarly, drivers of immobility constrain migration and stimulate individuals to stay put (Schewel, 2019 ).

Proximate drivers ‘downscale’ and localise predisposing macro-structural factors bringing them closer to the immediate ‘decision context’ of a potential migrant. Macro-structure context and developments are disaggregated and translated into situational triggering factors of migration that establish the actual reasons for migrating, including unemployment, job offer, marriage, persecution, flooding, etc. Beyond the degree of immediacy, migration driver functions can further be characterised by their temporality, selectivity, and geography. Temporality refers to the permanent or transitory character of a driver. For instance, demographic transitions or adaptations of cultural norms are usually slow-changing and therefore relatively inelastic (‘resilient’) structural drivers while natural disasters, or a coup d’état, are phenomena resulting in rapidly changing driver environments (‘shocks’). Selectivity refers to the fact that broader social, economic, or political transformations do not normally homogeneously affect all societal groups in the same way and to the same extent. Business cycles, for instance, can affect societal groups in very different ways and to an extent that depends on the age, gender, ethnicity, social status, or profession of the potential migrant. Finally, the geography refers to the locus and scope of a migration driver. The geographical scope of a macro-structural driver can be anything between local and global, while the locus of a migration driver refers to the geographical location of a migration journey where a driver may be operating (origin, transit or destination).

2 Migration Drivers: Interactions and Configurations

Migration is a decision taken in the context of personal needs, livelihood challenges and opportunities, stress, urgency and uncertainty, based on incomplete information about migration prospects and possible outcomes of alternative behavioural options. Thus, migration decisions are both situational and contextual, that is the configuration of complex driver environments is very specific to the time and place in which migration aspirations are formed and decisions taken. It is usually not a single driver but more often a complex combination of economic, political, social, and other developments and events that may dynamically influence both migration opportunities as well as the willingness and ability to migrate. The intertemporal accumulation of triggering factors leads to certain ‘tipping point’ situations, at which larger population movements are suddenly set in motion. For instance, many Syrians stayed in their hometowns years into the civil war and only fled to neighbouring countries once their economic basis of subsistence eroded and was further degrading through environmental stress to an extent where staying was no longer a viable option (Bijak & Czaika, 2020 ). Migration drivers may trigger, enable, mediate, or predispose an individual, a group of people, or a population to move. Migration drivers usually ‘cluster to operate as more than the sum of the single drivers that constitute them’ (Van Hear et al., 2018 , p. 934). That is, migration drivers do not work in isolation but in combination with other migration drivers establishing migration driver configurations.

As we will see in the empirical part of this chapter, most studies analysing migration drivers only focus on very specific drivers of migration. Few studies explore complex configurations of drivers, including their often non-linear, interacting, and combined effects on migration processes. Interaction effects in particular are regularly neglected. They occur when the effect of one driver depends on the presence and intensity of one or more other factors. Interaction effects reflect the importance of third factors that may influence causal relationships between a driver of migration and migration outcomes.

3 Migration Drivers: Some Empirical Evidence

3.1 a typology and meta-review.

Following the conceptualisation of migration drivers in the previous section, we now provide an overview of the existing evidence on the migration driver dimensions and factors and discuss the empirical state of knowledge. We synthesise evidence about migration processes more profoundly and hereby elaborate on key insights and findings from the scientific literature across multiple domains of migration drivers. Footnote 1 To evaluate the driving factors of why people migrate, we consulted a vast amount of the empirical academic literature on migration drivers. The total number of studies of migration drivers has increased more than eightfold since 2010 with an average annual growth rate of over 12%. Footnote 2 In an attempt to structure this knowledge accumulation on the drivers of migration, we have developed a taxonomy consisting of nine driver dimensions and 24 driving factors that may all play a direct (independent) or indirect (conjoined) role in enabling or constraining migration processes at different analytical levels (Table 3.1 ). The dimensionality of migration drivers refers to the nine societal areas a migration driver belongs to, each comprising a number of driving factors further specifying these broader dimensions. An extensive literature review has revealed that these 24 driving factors are not only priority areas of migration driver research but also play a key role for a more fundamental understanding of the dynamics of migration processes.

We identified driving factors both deductively through our and experts’ knowledge of the migration literature, and inductively using a rapid evidence assessment (REA) of almost 300 empirical studies of migration drivers in 2019. The analysis builds on a rapid evidence assessment of this vast amount of scientific literature published until 2019. Footnote 3 We have not attempted to systematically assess the quality of the studies analysed but trust that collectively these studies are authoritative for understanding the role, effects, and functions of driving factors in migration processes. Figure 3.1 displays the share and distribution of reviewed empirical and non-empirical studies by driver dimension. On average, we identified 2.5 migration drivers per empirical study, which explains why the total number of drivers exceeds the total number of studies analysed (463). Economic and socio-cultural drivers hereby outnumber the other driver dimensions while environmental drivers have received relatively little attention. While this might reflect a biased selection of the literature, we believe that our extensive literature search is broadly representative of the core body of literature on migration drivers.

Number and distribution of empirical and non-empirical studies, by migration driver dimension (n = 463)

Figure 3.2 displays the distribution of the reviewed empirical studies according to driver dimension, method and level of analysis, locus of the migration driver, and data sources used. Almost half of all studies evaluate economic and socio-cultural drivers. Two thirds use quantitative methods and only 8% mixed methods. Micro-level studies dominate in our review, accounting for two thirds of all studies while meso-level studies merely representing a small minority of 3%. The level corresponds to the study, which is not necessarily the same level the driver operates. There is an almost equal proportion of studies evaluating migration drivers that operate at the origin, destination, or at origin and destination. Merely 1% focuses on drivers in transit contexts. Almost half of all studies use surveys with administrative records and interviews accounting for almost a quarter each. Other methods (e.g. experimental, participant observation) account for 4%.

Overview of empirical studies (n = 296)

Figure 3.3 shows that the distribution of migration driver studies across the nine driver dimensions has remained relatively stable over time with economic drivers accounting for around a quarter of all migration drivers. The relative importance of socio-cultural and demographic drivers has decreased while that of individual and environmental drivers has increased.

Distribution of migration drivers in empirical studies, 2000–2018, 5-year rolling averages (n = 271)

As an indication of the relevance of complex migration driver configurations, Table 3.2 shows the existing coverage of empirical studies in the migration driver literature that address more than one specific driver. Note that the percentages in rows and columns do not add up to 100, as on average one study elaborates on 2.5 driver dimensions. For instance, the first row indicates that 69% of all empirical studies of demographic drivers also evaluate economic drivers. Demographic studies are almost equally likely to be examined conjointly with socio-cultural drivers (66%) but a lot less likely with security (9%) and have never been examined conjointly with environmental drivers in our sample. The column on the far right indicates that 9% of all studies that examine demographic drivers do so without reference to any of the other eight driver dimensions.

Table 3.2 demonstrates that the dominance of economic drivers stems not from the fact that many studies only examine economic drivers but that they are analysed conjointly with many other migration drivers, for instance in 51% of the studies with individual-level drivers or in 80% of the studies with factors representing human development (column ‘Econ.’). Economic drivers are predominantly studied conjointly with socio-cultural drivers, reflecting a considerable number of quantitative studies that examine the importance of economic push and pull factors in combination with, for instance, migrant networks. Environmental factors are often investigated in conjunction with economic drivers, reflecting the link between economic opportunities and climate change and natural disasters. However, almost a third of all studies focusing on environmental drivers examine these in isolation. Human development drivers are overwhelmingly examined conjointly with economic drivers, reflecting the interplay between employment, education, and training. Individual drivers are often studied together with socio-cultural drivers, as personal migration experience is often linked to migrant networks and cultural ties. The miniscule overlap with supranational drivers (3%) highlights the fact that studies generally evaluate micro- and macro- levels separately but very rarely together. A quarter of studies have evaluated individual aspirations, attitudes, and resources without recourse to other driver dimensions. Politico-institutional drivers are rarely studied in combination with environmental drivers but rather with security-related drivers.

The following sections explore these driver dimensions in detail. We emphasise driver dimensions where certain drivers have been studied disproportionately for certain migration forms or geographical regions. We group migration-driving factors into individual-specific, group-specific, and macro-structural drivers. We hereby provide a succinct and comprehensive overview of the current state of knowledge of all relevant migration drivers. However, due to their relevance in both academia and public discourse , we put some more elaboration on four driver dimensions, namely economic, political (public and migration policies), security-related, and environmental factors.

3.2 Individual-Specific Drivers: Aspirations and Capability

Material and non-material personal and household resources , or lack thereof, can facilitate or constrain migration. Such resources include financial assets and property (Kley, 2011 ; Zijlstra & van Liempt, 2017 ) but also information and access to information and communication technologies (Dekker et al., 2016 ; Farré & Fasani, 2013 ; Muto, 2012 ). These resources not only affect whether individuals migrate and which channel they choose but also are particularly important during the migration journey. The lack of financial resources constrains the poorest who might not be able to afford relocation costs (De Jong et al., 2005 ), paying for visas, or if necessary, to hire smuggling services (Düvell, 2018 ). At the same time, wealth can also be associated with smaller emigration rates from more developed countries compared to less developed middle-income countries (Clemens, 2014 , Dustmann & Okatenko, 2014 ). Thus, the nexus between economic resources and migration propensity follows a non-linear, often inverse U-shaped relationship. For instance, small but growing landholdings increase migration inclinations but only until they are large enough to sustain a regular income from farming (Oda, 2007 ).

Aside economic resources, non-tangible resources such as migration experience of either oneself or other family members are an important (psychological) factor, which has widely been found to be formative in developing migration aspirations and in the decision-making process itself (Richter & Taylor, 2008 ; Tsegai, 2007 ). Aspirations such as the immanent “desire for a better life” (Özden et al., 2018 ) and for the fulfilment of individual or collective needs (Cai et al., 2014 ) are an important personal resource and important prerequisite for considering and realising a migration project. To better life circumstances, people require a “capacity to aspire” (Appadurai, 2004 ), which refers to the capacity to imagine a better life better and it is nurtured by a person’s economic, social, emotional, and cognitive resources (Sell & De Jong, 1978 ). However, aspirations are not static but individuals who migrate to fulfil their (life) aspirations might actually see their aspirations increase rather than decrease after migration, as they become exposed to new opportunities and lifestyles (Czaika & Vothknecht, 2014 ). However, migration can also decrease aspirations, as migrants are unable to realise their aspired lives at the new destination (Boccagni 2017 ).

Attitudes , views, and perceptions about one’s own country and the desire to live in another country influence whether and where individuals migrate (Schapendonk, 2012 ). Some specific individual characteristics and personality traits may reason this inner drive for migration (Canache et al., 2013 ; Frieze et al., 2006 ; Jokela, 2009 ). Open mindedness, longing for personal experience, and an adventurous personality are consistently found to drive migration intentions and behaviour. Emotions and feelings, often in conjunction with more tangible drivers, also affect migration (Boccagni & Baldassar, 2015 ). Overall, however, non-tangible attitudes and perceptions seem to be rather subordinate to more tangible socio-economic resources or demographic factors, including a person’s age or marital status.

3.3 Group-Specific and Internal Migration Drivers

As already indicated in the theoretical part, and in accordance with the new economics of labour migration (Stark & Levhari, 198 2), several studies find evidence for the effect of household size and family structure on migration patterns as well as the influential role the family can play in migration decision-making (Meyer, 2018 ). Household size is found to affect (internal) migration of family members to other rural or urban locations, aiming to work in different economic sectors than other family members to diversify risk and smooth household income (Gubhaju & De Jong, 2009 ; VanWey, 2003 ). International migration is often driven by similar goals (Constant & Massey, 2002 ), but often with a gender-specific effect on the migration propensity. The presence of children or elderly dependents generally increases male migration but decreases female migration, highlighting the gendered division of the work-care nexus (De Jong, 2000 ). In contrast, the presence of elderly non-dependent family members increases female migration, as they are enabled to participate in the labour market (Danzer & Dietz, 2014 ). Life course events, such as retirement and one’s children leaving the house spur migration, as spouses are not constrained by employment or educational responsibilities (Stockdale, 2014 ). In contrast, being in marriage and in a dual breadwinning household decreases the likelihood of migration (Etling et al., 2018 ).

Gender affects migration at the macro-level (differential labour demand, e.g. domestic work vs. construction), meso-level (work-care nexus), and micro-level (family roles) (Lutz, 2010 ). Gender roles and norms, such as caregiving and breadwinning, affect men and women’s propensities to migrate (Danzer & Dietz, 2014 ) as well as the types of migration networks and channels that are available and migrants’ use thereof (Heering et al., 2004 ; Hoang, 2011 ). People may both migrate to conform to gendered cultural norms (Hernández-Carretero & Carling, 2012 ; Kandel & Massey, 2002 ), but also to escape these norms (Rutten & Verstappen, 2014 ). Gender-based discrimination might hence be both an incentive and obstacle to migrate (Ruyssen & Salomone, 2018 ). In this context, marriage is an important factor in explaining migration patterns. While it has mostly been confined to women to look for or join their spouses (Czaika, 2012 ), in some contexts it is increasingly also men who migrate to urban areas or abroad to look for wives due to distorted sex ratios. Marriage is often used to circumvent other barriers to migration, such as poverty (Rao & Finnoff, 2015 ) or migration policies, and of the only opportunity to realise international migration (Böcker, 1994 ). At the same time, in families that are more egalitarian it is also the employment opportunities status of wives that drives migration decisions (Cooke, 2008 ).

Moreover, migrant networks and transnational communities have long been recognised as important drivers of migration, as they facilitate and sustain migration by providing information and hands-on assistance (Boyd, 1989 ). Migrant networks are often measured as the number (or, stock) of previous migrants from the same family, town, region, or country at the destination. The importance of networks and social ties has repeatedly been empirically confirmed for explaining alternative migration forms and patterns (Bertoli & Ruyssen, 2018 ; Düvell, 2018 ; Haug, 2008 ; Havinga & Böcker, 1999 ). However, people also migrate in the absence of networks, highlighting the importance of other migration drivers (Gilbert & Koser, 2006 ; Sue et al., 2018 ). The importance of networks increases with restrictive migration policies, as settled migrants may act as gatekeepers and bridgeheads (Carling, 2004 ). However, networks may be irrelevant if migration is deemed too difficult (Collyer, 2005 ). As already mentioned, networks do not necessarily increase migration, as new migrants may compete for jobs and other resources with already established migrants (Heitmueller, 2006 ). The relation between migration flows and stocks might hence follow an inverse U-shape (Bauer et al., 2009 ). Flows of migrants also affect subsequent migration, as potential migrants get inspired to follow prior migrant though a ‘herd effect’ (Epstein & Gang, 2006 ). Networks also affect the gender and skill composition of migration flows (Hoang, 2011 ; McKenzie & Rapoport, 2010 ).

With growing numbers of migrants worldwide, migrant networks also grow in prevalence. Migration often becomes self-perpetuating and a cultural norm (Alpes, 2012 ; Castle & Diarra, 2003 ), in particular when migration becomes ingrained in the local culture and a rite of passage (Massey et al., 1993 ). Emigrants are social role models and individuals migrate due to the inability to fill a social role (Hernández-Carretero & Carling, 2012 ). Because of social norms and pressure, people may migrate even if they would have greater economic opportunities at the place origin (Ali, 2007 ). However, those who stay put are often seen as lazy, losers, failed, undesirable as potential mates, and experience feelings of shame and embarrassment (Heering et al., 2004 ; Kandel & Massey, 2002 ). Men are disproportionately affected by this cultural shame, as migration is often linked to masculinity (Maroufof & Kouki, 2017 ).

3.4 Macro-structural and External Migration Drivers

The economy.

Historically, economic hardship and downturns in rural and semi-urban areas have led to internal migration to urban areas but has also resulted in international migration, for instance from Europe to the North America in the nineteenth century (Massey, 1988 ). Deteriorating economic conditions tend to push people to migrate (Kunuroglu et al., 2018 ). Short to medium-term changes and fluctuations in macroeconomic conditions, particularly growth of gross domestic product (GDP) and a country’s business cycle, are robust drivers of migration (Beine et al., 2019 ; Docquier et al., 2014 ). By trend, GDP growth in sending countries decreases migration while GDP growth in receiving countries increases migration. For instance, the 2008 financial crisis and its aftermath caused considerable but diverse macroeconomic changes and fluctuations in European Union countries. Its impact on migration varied with both a potential migrant’s main reason for migration and employment status (Beets, 2009 ). For instance, students preferred to study in countries less affected by the crisis and the wish to emigrate was stronger in countries that suffered more (Van Mol & Timmerman, 2014 ). However, the effect of negative economic shocks on migration is not necessarily the inverse of positive shocks. Their magnitudes might differ considerably, in line with a “migration prospect theory” by which potential migrants value losses more than equal-sized gains and respond accordingly in their migration propensity (Czaika, 2015 ).

Neoclassical migration theory suggests that individuals migrate due to economic opportunities at the destination and/or lack thereof at the origin in order to maximise expected income (or utility). Macro-level quantitative studies consistently find that bilateral migration flows respond to unemployment rates and differentials (Migali et al., 2018 ; Geis et al., 2013 ), job opportunities (Baizán & González-Ferrer, 2016 ), and wages (Beine et al., 2014 ; Grogger & Hanson, 2011 ). The magnitudes differ across individuals and countries. For instance, high-skilled migrants respond more strongly to wage differentials than low-skilled ones (Grossa & Schmitt, 2012 ) and higher origin wages decrease emigration from developed countries but not from developing countries (Ruyssen et al., 2014 ). Micro-level studies add that individual unemployment, employment satisfaction, and anticipated career opportunities drive migration (Hoppe & Fujishiro, 2015 ; Zaiceva & Zimmermann, 2008 ). However, when the effect on income dominates the spatial substitution effect, unemployment may also decrease emigration due to poverty constraints (DeWaard et al., 2012 ). A number of qualitative studies confirm the explanatory power of the economic factors in migration processes a variety of contexts (Afifi, 2011 ; Bal, 2014 ). While employment opportunities are per se primary drivers for economic migrants, they have also been found to affect migration decisions of other migrant groups including asylum seekers, refugees, and irregular migrants (Dimitriadi, 2017 ; Van Hear et al., 2018 ). For these groups, however, economic factors are often of secondary importance compared to other factors.

The migration-development nexus has been widely studied with a majority of studies concluding that development will not stop migration, at least not in the short term (Castles, 2009 ; de Haas, 2007 ). In fact, development - generally proxied by GDP per capita—might initially increase internal migration from rural to urban areas or across international borders, as immobile potential migrants overcome poverty constraints (Czaika & de Haas, 2012 , Clemens, 2014 ). According to this so-called migration hump –an inverse U-shaped relation between migration and development—rising income levels lead an increase in emigration from developing countries, that is in particularly from Asia and Africa, while the opposite is true from more developed countries (Czaika & de Haas, 2014 ; Hatton & Williamson, 2005 ; Sanderson & Kentor, 2009 , Migali et al., 2018 ). Wage differentials and higher income levels at destination attract migrants (Ortega & Peri, 2013 ; Palmer & Pytliková, 2015 ). This effect seems to be particularly strong for migrants from developing countries (Ruyssen et al., 2014 ), but the same logic applies to internal migration (Guriev & Vakulenko, 2015 ). Discrepancies in living costs and conditions, housing standards, as well as broader in the quality of life and lifestyles drive migration in a variety of forms, including both internal and international migrants, regular and irregular migration, of low-skilled as well as highly skilled migrants (Baizán & González-Ferrer, 2016 ; de Haas & Fokkema, 2011 ; Péridy, 2006 ).

While there is rather mixed evidence on the exact relation between migration and poverty (Black et al., 2006 ; Skeldon, 2002 ), consensus emerged regarding the fact that it is generally not the poorest who migrate. Similar to the migration-development nexus, poverty and migration might follow an inverse U-shape (Du et al., 2005 ). Material and non-material relocation costs are the reason why the poor are constrained to migrate, even in times of severe crisis (Danzer & Dietz, 2014 ). However, not just absolute deprivation and poverty shape migration patterns, but also relative deprivation and the feeling of being deprived in comparison to an internal or international peer or reference group (Czaika, 2013 ; Stark & Taylor, 1989 ). The relation between internal relative deprivation, or within-country inequality, and migration is ambiguous with studies suggesting that it is positive (Stark et al., 2009 ), negative (Czaika & de Haas, 2012 ), or, mirroring the migration-development nexus, following an inverse U-shape (Péridy, 2006 ). Relative inequality between sending and receiving countries has been found to affect the self-selection of migrants according to Borjas’ ( 1989 ) theoretical propositions (Mayda, 2010 ). Higher inequality in receiving countries may hereby attract migrants, as it signals social mobility (Czaika & de Haas, 2012 ) but might deter those who favour social justice and are averse to the risk of income losses. While neoclassical theory predicts that people migrate to places where returns to skills and education is highest, empirical evidence often finds that people migrate to places and countries with lower expected returns, suggesting that other drivers are also at play (Belot & Hatton, 2012 ; Brücker & Defoort, 2009 ).

Public Policies

The claim that the welfare state affects the scale and composition of migration flows (Borjas, 1999 ) has been at the heart of many political and academic debates. The ‘welfare magnet effect’ assumes to attract low-skilled migrants—due to generous social benefits of a well-established welfare state—but to deter high-skilled migrants—due to high income and wealth taxation for funding public spending. There is some evidence for such a selection and attraction effect (Belot & Hatton, 2012 ; De Jong et al., 2005 ; Fafchamps & Shilpi, 2013 ). However, while higher welfare spending at both origin and destination increases migration from developing to developed countries, as they relax financial constraints and provide a safety net, they rather decrease migration between affluent countries due to high tax rates (Palmer & Pytliková, 2015 ; Ruyssen et al., 2014 ; Yoo & Koo, 2014 ). Other studies rather question the centrality of the welfare state and highlight the importance of other economic and socio-cultural drivers (Giulietti, 2014 ; Nannestad, 2007 ). Labour market protection and social insurance systems may for instance rather deter immigration as they create insiders and outsiders (Geis et al., 2013 ). Overall, the effects of welfare systems differ across countries as it depends much on the type and structure of those systems.

The effect of public infrastructure on migration is also rather ambiguous. A well-developed and functioning public infrastructure might increase migration (and mobility) by decreasing the cost of transportation but may also decrease migration propensities by providing more and better economic opportunities (Gachassin, 2013 ). Contentment with local public services has been found to explain variations in migration intentions in developing countries (Dustmann & Okatenko, 2014 ).

The educational infrastructure, in particular the quality of higher education, is a primary but not the only driver of student mobility . Students migrate internally or internationally due to the quality and reputation of universities but also due to available scholarship and costs of living (Beine et al., 2014 ; Findlay et al., 2011 ). Cities and regions with good universities attract students and retain graduates, potentially due to available jobs and employer-university interactions (Ciriaci, 2014 ). Educational opportunities for oneself or one’s children in receiving countries, and lack thereof in sending countries, drive international migration of students (Timmerman et al., 2016 ), unaccompanied migrant minors (Vervliet et al., 2015 ), and asylum seekers, refugees, and irregular migrants (Day & White, 2001 ; McAuliffe, 2017 ). However, study opportunities are often secondary to other factors, including security or labour market considerations, or prospects for residency and citizenship (Dimitriadi, 2017 ). Professional training and professional education to advance one’s career are the main driving factors for high-skilled migrants, such as health professionals (Awases et al., 2004 ), academics (Czaika & Toma, 2017 ) and consistently rank among the top reasons mentioned for emigration (Bartolini et al., 2017 ).

We have not identified a study that mentions the healthcare system as the sole or main driver of migration. However, there is ample evidence that the situation of the healthcare system acts as a push factor for healthcare professionals from developing countries plagued by HIV/AIDS (Aiken et al., 2004 ). Health risks, such as malaria and dengue, drive emigration from developing countries (Marchiori et al., 2012 ). Health considerations, often associated with a better climate and the availability of quality healthcare, are central to retirement migration for residents of developed countries, such as North-South migration in Europe or retirement in Mexico for US Americans (Rodriguez et al., 2004 ; Sunil et al., 2007 ). Well-developed healthcare systems can act as attracting factors for different forms of migration (Narayan & Smyth, 2006 ).

Migration Policies and Human Rights

Migration scholars often argue that social transformations, globalisation , and transnationalism, as well as political regime transitions drive migration processes and are therefore rather sceptical about the ability of more specific migration policies to affect the volume and composition of migration flows (Castles, 2004a , 2004b ). Empirical studies find rather mixed evidence in favour or against this proposition, partly due to difficulties measuring migration policies (Migali et al., 2018 ; De Haas & Czaika, 2013 ). Restrictive migration policy is generally associated with fewer asylum applications (Hatton & Moloney, 2017 ; Thielemann, 2006 ) and less international migrants (Fitzgerald et al., 2014 ). Migration policies may also deflect some migrants to alternative destinations (Barthel & Neumayer, 2015 ; Crawley & Hagen-Zanker, 2019 ) or merely change their migration route while they are not important for other migrants (Gilbert & Koser, 2006 ). Migration restrictions seem to reduce emigration and circular migration and promote permanent settlement of migrants, which may even result in the unintended consequence of even higher net migration (Czaika & de Haas, 2017 ). The deterrence effect of migration policies varies with specific policy instruments: visa restrictions, for instance, may simultaneously deter regular entries while increasing attempts for irregular entry (Czaika & Hobolth, 2016 ).

Besides policies that aim to deter unwanted immigration, many countries have implemented policies that target certain types of migrants including skilled workers or students (Czaika & Parsons, 2017 ). Despite the continuous proliferation of such skill-selective migration policies, the degree to which such policies are effective remains contested (Bhagwati & Hanson, 2009 ). Czaika and Parsons ( 2017 ) find that supply-driven systems (points-based systems) increase both the absolute numbers of high-skill migrants and the skill composition of international labour flows. Conversely, demand-driven systems—usually based on the principle of job contingency—are shown to have a rather small, even negative effect. Doomernik et al. ( 2009 ) suggest that the potential of attracting high-skilled migrants largely depends on broader socio-economic and professional factors rather than immigration policies per se. More generally, a generous and welcoming treatment of migrants and lenient migration policies attracts migrants (McAuliffe & Jayasuriya, 2016 ). Other migration-facilitating policies such as free movement areas (Beine et al., 2019 ), or prospects for (dual) citizenship (Fitzgerald et al., 2014 ) affect migration propensities positively, even though such policies may disproportionately affect low-skilled migrants (Grossa & Schmitt, 2012 ). In addition, emigration policies may affect migration propensity, but seem equally secondary to more fundamental economic and socio-cultural drivers (de Haas & Vezzoli, 2011 ).

Entitlements for civil and political rights or lack thereof, in origin, transit, and destination countries play a significant role in migration and destination choices. Concerns with their legal status drive asylum seekers and refugees from host and transit countries in expectation of (easier) access to refugee status or citizenship (Crawley & Hagen-Zanker, 2019 ; Düvell, 2018 ). Discrimination and a lack of civil and political rights in origin countries increases the number of individuals who seek asylum in developed countries (Erdal & Oeppen, 2018 ; Hatton & Moloney, 2017 ). Migrants’ rights in receiving countries also encourage labour migration (Ruhs, 2013 ) while gender-based discrimination, as we have discussed before, can both constrain and encourage migration (Ruyssen & Salomone, 2018 ). Racism, anti-immigrant attitudes, discrimination and other integration obstacles in potential destination countries deter migrants, and in particular, highly skilled migrants who are often privileged by having alternative migration opportunities (Duch et al., 2019 ; Gorinas & Pytliková, 2017 ).

The so-called ‘ migration industry ’—agents that mediate migration processes—is closely connected to but separate from migration policies and migrant networks. Such agents facilitate migration and smugglers frequently decide both route and destination (Crawley, 2010 ; Hugo et al., 2017 ; Koser, 1997 ). While there is little empirical evidence on the effect of smugglers on migration (Sanchez, 2017 ), states have increasingly tried to deter the use of smugglers to curb irregular migration (Watkins, 2017 ). Recruitment agencies are other actors that facilitate migration. Historically, they attracted guest workers post-WWII and nowadays they focus on both high-skilled individuals, such as nurses, and low-skilled ones, such as domestic workers and seasonal agricultural workers, mostly from developing countries or poorer countries within the European Union (Massey, 1988 ; Labonté et al., 2015 ). Multinational and transnational corporations have been recognised as other actors that drive migration, particularly of high-skilled labour migrants (Beaverstock, 1994 ).

Conflict and Security

Civil, ethnic, and religious conflict, war, torture, and human rights violations are drivers of migration, particularly of asylum seekers, refugees, irregular migrants, unaccompanied migrant minors, and internal displacement. Safety and security concerns might initially decrease migration, as it is unsafe to prepare for exit and individuals often hope for an improving security situation. However, migration might increase once insecurity or crime levels exceed a certain threshold (Bohra-Mishra & Massey, 2011 ). Individuals migrate both due to personal experience of threat and violence but also as a consequence of broader feeling of insecurity (Lundquist & Massey, 2005 ) and there is ample evidence for the link between insecurity in sending countries and large-scale emigration (Castles et al., 2003 ; Davenport et al., 2003 ; Migali et al., 2018 ; Moore & Shellman, 2007 ). However, war and conflict also drive migration indirectly through its effect on infrastructure, economic opportunities, and ultimately livelihoods (Khavarian-Garmsir et al., 2019 ). While conflict might trigger migration, environmental or political drivers might cause conflict itself (Moore & Shellman, 2004 ; Naudé, 2010 ). Most studies in this area have focused on sending countries in Africa and the Middle East, particularly Afghanistan, Iraq, and Syria, with a substantial number also examining European destinations.

Political factors in sending and receiving countries that drive migration include repression, persecution, political terror, and political freedom (Hatton & Moloney, 2017 ; Narayan & Smyth, 2006 ), military conscription (Mallett et al., 2017 ), political instability (Naudé, 2010 ), democracy differentials and satisfaction with democracy (Moore & Shellman, 2004 ), corruption (Lapshyna, 2014 ), and regime transitions, political protests, and dissidents (Davenport et al., 2003 ). Individuals migrate because they are directly affected (e.g. through conscription), fear that they might be affected in the future, or due to the insecurity created by the general political situation. Factors more closely linked with conflict and with implications for physical security, such as political terror, and forced military conscription seem to better explain migration intentions and behaviour than lack of democratic rights. The latter have been linked to non-conflict induced migration and might be particularly relevant for the young and high-skilled migrants who face fewer barriers to emigration (Etling et al., 2018 ). Political factors in receiving countries that have been looked at are right-wing populism and electoral outcomes, which result in fewer asylum applications (Neumayer, 2004 ) and smaller bilateral migration flows (Fitzgerald et al., 2014 ).

Environmental Change

Climate change and environmental degradation as a fundamental predisposing driver of internal and international migration has been studied extensively at the macro- and micro-levels by qualitative and quantitative research, although almost exclusively for countries in the global South (Migali et al., 2018 ). The majority of quantitative studies find that slow-onset changes in temperatures and precipitation are associated with emigration, particularly from more agricultural countries and rural areas (Berlemann & Steinhardt, 2017 ; Neumann & Hermans, 2017 ). However, if climatic factors are evaluated alongside economic factors, the latter affect migration in a stronger and more direct way (Joseph & Wodon, 2013 ). Those most adversely affected by environmental degradation are also those most financially constrained and therefore unable to move (Veronis & McLeman, 2014 ). That is, migration as an adaptation strategy is not available to this deprived and therefore trapped group (Cattaneo et al., 2019 ). Some studies conclude that climatic factors do not directly explain migration intentions and behaviour (Beine & Parsons, 2015 ; Mortreux & Barnett, 2009 ). Climate change affects migration mostly indirectly through multiple transmission channels including its impact on economic factors, such as incomes, livelihood opportunities, and food security (Black et al., 2014 ; Khavarian-Garmsir et al., 2019 ), health-related risks, such as malaria and dengue (Marchiori et al., 2012 ), or conflict (Abel et al., 2019 ). While climatic factors are often analysed merely as detrimental factor potentially uprooting larger populations, but a favourable climate in certain countries or regions is often attracting immigrants, and in particular, retirees (Gottlieb & Joseph, 2006 ; Sunil et al., 2007 ; Van der Geest, 2011 ).

Natural disasters and environmental shocks , such as floods, storms, droughts, or earthquakes, but also human-made disasters and accidents, trigger mostly immediate and often large-scale population displacements. Natural disasters lead to an increase in internal, particularly rural-to-urban, and also international emigration (Beine & Parsons, 2015 ). At the same time, incidence of natural disasters discourages immigration (Ruyssen & Rayp, 2014 ). However, again, these factors may be secondary to more fundamental economic drivers, such as employment prospects in cities (Warner et al., 2010 ). Some studies do not find a significant effect of disasters on internal migration (Bohra-Mishra et al., 2014 ) or on the number of asylum seekers (Neumayer, 2005 ). However, natural disasters might lead to temporary displacement and indirectly affect migration through increasing the likelihood of conflict (Naudé, 2010 ). Whether disasters really trigger migration depends on a number of factors, such as adaptability and the presence or absence of broader socio-economic opportunities elsewhere. As for climate change, the overwhelming majority of studies examining the effects of natural disasters focus on developing countries.

International Connections and Relations

Transnational connections between countries and societies are often rooted in a common history and expressed by linguistic, cultural, geographic, and religious ties that transcend national or societal boundaries connecting two or more countries. A common or similar official language increases bilateral migration flows (Kim & Cohen, 2010 ). Other studies find evidence of English as the main spoken language in migrants’ destination choice (Adserà & Pytliková, 2015 ), while other studies rather discount the importance of language (Ruyssen & Rayp, 2014 ). Geographical distance generally decreases migration flows, as with distance, monetary and non-monetary migration costs increase, while proximity, proxied by a shared border, does rather increase migration (Wang et al., 2016 ). Distance is also associated with ‘positive’ skill selection, indicating that high-skilled migrants are able to travel farther than low-skilled migrants, asylum seekers, or refugees, who mostly migrate to neighbouring or near-by countries (Belot & Hatton, 2012 ; Grogger & Hanson, 2011 ; Yoo & Koo, 2014 , Özden et al., 2018 ). Cultural factors often have more explanatory power than traditional economic factors when it comes to migration between developed countries (Belot & Ederveen, 2012 ). However, the effect of culture does change over time as moving towards greater cultural proximity is usually associated with larger migration flows (Lanati & Venturini, 2018 ).

Major geopolitical shifts have historically affected the direction and magnitude of migration flows (Czaika & de Haas, 2014 ). Such events include, for instance, the end of World War II, the Cold War, the dissolution of the USSR, the end of communism and the fall of the Berlin wall, or the breakup of Yugoslavia, to name a few. Geopolitical shocks and shifts have been widely acknowledged as central to major changes in international migration patterns. At the same time, it is argued that international relations drive migration rather indirectly if deteriorating inter-state relations might result in war or the breakup of colonial empires or multi-ethnic states that may end up with larger displacements (Weiner, 1996 ). International relations may also affect migration through its influence on immigration and emigration policymaking (Massey, 1999 ). For instance, the lifting of the Iron Curtain removed emigration restrictions, which resulted in increased emigration (Salt & Clarke, 2000 ). International relations also affect aid, trade, and investment policies, all of which are shown above to drive migration (Berthélemy et al., 2009 ; Parsons & Winters, 2014 ). Economic integration and postcolonial ties are linkages between countries that make migration more likely and migration flows are up to three times higher between former colonies (Fitzgerald et al., 2014 ; Kim & Cohen, 2010 ; Robinson & Carey, 2000 ). Emigrants from former colonised to former colonial powers are often less skilled compared to the origin population, potentially reflecting the ease of migration and less stringent migration policies (Grogger & Hanson, 2011 ). The effects of globalisation on migration manifest themselves via trade, foreign direct investment (FDI), exchange rates, and aid or official development assistance. Against neoclassical propositions, trade and migration are rather complements than substitutes as increasing trade volumes seem to be associated with larger migration (Campaniello, 2014 ). This is mostly due to the dominance of the income effect and pre-existing cultural linkages between countries. Evidence on the effect of foreign investment on emigration is rather mixed and can have a negative effect, in particular in the secondary sector (e.g. manufacturing), whereas FDI in the primary sector (e.g. mining, farming) is rather accelerating emigration (Sanderson & Kentor, 2009 ). Aid, through its effects on incomes and transnational ties, increases found to increase rather than to deter emigration (Berthélemy et al., 2009 ). However, aid targeted at rural development, the health sector or educational services might actually decrease emigration, as improvements in public services may outweigh the migration-inducing income effect (Gamso & Yuldashev, 2018 ; Lanati & Thiele, 2018a , 2018b ).

4 Conclusion

This chapter has set out to give an overview of the conceptual understanding of migration drivers as well as the state of knowledge in the empirical assessment of migration drivers based on a comprehensive evidence assessment of the drivers of migration. We propose a migration typology based on 9 driver dimensions and 24 driving factors of migration and emphasise the fundamental importance of studying migration driver environments as complex configurations of drivers. Scholarship on complex driver configurations is still in its infancy as most studies—although, as we have seen, they assess on average 2.5 drivers per study—hardly consider complex interaction, nor cascading and feedback effects between multiple drivers. Thematically, besides rising research output on environmental drivers, research exploring individual-level factors such as migration aspirations, experience, and decision-making have gained increasing prominence in the literature. However, economic and social-cultural drivers are still the dominant focus in a large part of the literature. Some more specific areas are still relatively understudied, such as the role of family ties in migration, or constraining and facilitating effects of various technologies. The meta-analysis has revealed current research trends and several research gaps in the migration drivers literature. The focus on drivers at the origin and destinations and the relative neglect of those operating in transit, i.e. on the migration journey, as well as their shifting significance over time and space has recently received more attention but remains an understudied area (Crawley & Skleparis, 2018 ).

Different migration drivers affect distinct societal groups in different ways. To advance our understanding of the relative importance of different migration drivers in specific contexts, future research on migration drivers should further disaggregate and specify driver analyses along more complex intersections of age, gender, geography, sector of employment, and socio-economic status. The migration driver literature is also relatively silent with regard to the transitory character of drivers during migration. Migration drivers are not static but may change dynamically; while some drivers rapidly change (‘shocks’), other drivers may change only gradually over time. However, even when drivers are slow changing, they may still be perceived very differently during a migration journey or a life cycle. In addition, individual perceptions of migration drivers have hardly been explored so far. Future research on ‘migration driver complexes’ should further refine conceptualisation and empirical validation regarding the changing nature of migration drivers as predisposing, mediating, enabling, and triggering factors that may change dynamically over time and over the course of a migration journey.

At this point, we acknowledge that the vast majority of the world’s population never migrates, at least not internationally. While this may be partly due to the absence of one or a combination of the migration drivers reviewed in this study, there may also exist drivers of immobility (Schewel, 2019 ). However, we only review and synthesise existing knowledge of the circumstances under which people do, or intend to, migrate.

This figure is based on a calculation of the total population of journal articles covering migration drivers in the IMISCOE Migration Research Hub ( http://migrationresearch.com/ ) database since 2000.

The synthesis of research on migration drivers is based on a widely organized collection and assessment of over 660 research documents that we collated between February and April 2019. The compilation of this comprehensive (though not exhaustive) repository of English-language studies includes articles in peer-reviewed journals, particularly empirical ones, but also books, book chapters, reports, and working papers published and indexed. Other rapid evidence assessments of migration studies include Cummings et al., 2015 (138 documents, focus on irregular migration to Europe) and EASO, 2016 (195 documents, focus on asylum migration).

A key selection criterion was that these studies present empirical evidence or have been influential in the migration studies field and/or come from respected organizations (e.g. King, 2012 ; EASO, 2016 ). Of the 660 studies that we identified using various search engines (such as Google Scholar and Scopus), authors’ literature databases, documents’ cross-references, and through an expert workshop in June 2019, about 200 documents have been excluded, as they were not relevant or inaccessible. As a consequence, we reviewed a sample of 463 studies, of which 293 were empirical ones using primary and/or secondary data (72 studies employing qualitative methods, 198 studies using quantitative methods, and 23 mixed methods studies). The remaining studies were either theoretical (64), experimental (3), or qualitative but non-empirical (125). The total number exceeds 463, as studies can be both theoretical and qualitative or quantitative. For each study we coded the type and year of publication, driver dimensions (9 codes), driving factors (24 codes), methodology, type of data source, migration form addressed, locus of study, level of analysis, observation period, and geographical coverage of study. We further extracted the main findings of each study to synthesize the state of evidence-based knowledge on migration drivers. Obviously, studies are of different quality in terms of the justification and application of the methodological approaches, but also with regard to their external and internal validity and reliability.

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Czaika, M., Reinprecht, C. (2022). Migration Drivers: Why Do People Migrate?. In: Scholten, P. (eds) Introduction to Migration Studies. IMISCOE Research Series. Springer, Cham. https://doi.org/10.1007/978-3-030-92377-8_3

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Why Do People Migrate? A Review of the Theoretical Literature

Maastrcht Graduate School of Governance Working Paper No. 2008/WP002

25 Pages Posted: 14 Mar 2008

Jessica Hagen‐Zanker

Maastricht University; Overseas Development Institute (ODI)

Date Written: January 2008

Massey et al. (1994) is a ground-breaking paper in the migration literature that discusses and unifies different migration theories. However, their review and synthesis is incomplete and fairly brief for researchers interested in a deeper understanding of the migration theory literature. This paper therefore aims to review the complete spectrum of economic migration theory from the 1950s until today and to show the differences and complementarities between the different approaches.

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