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  • Published: 21 December 2021

Measuring migration 2.0: a review of digital data sources

  • Jasper Tjaden   ORCID: orcid.org/0000-0002-5054-3535 1 , 2  

Comparative Migration Studies volume  9 , Article number:  59 ( 2021 ) Cite this article

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The interest in human migration is at its all-time high, yet data to measure migration is notoriously limited. “Big data” or “digital trace data” have emerged as new sources of migration measurement complementing ‘traditional’ census, administrative and survey data. This paper reviews the strengths and weaknesses of eight novel, digital data sources along five domains: reliability, validity, scope, access and ethics. The review highlights the opportunities for migration scholars but also stresses the ethical and empirical challenges. This review intends to be of service to researchers and policy analysts alike and help them navigate this new and increasingly complex field.

Introduction

International interest in measuring human migration is at an all-time high. The number of people living in a country other than their country of birth reached an estimated 272 million in 2019, an increase of 51 million from 2010 (UN DESA, 2019 ). The number of forcibly displaced people due to conflicts and disasters is at its historic high (UNHCR 2020 ). International migration is expected to continue increasing given higher levels of interconnectedness in the world due to improved communication and transport systems, protracted crises producing displacement, and structural changes such as climate change and population growth in certain world regions.

Governments worldwide have a keen interest in anticipating future migration flows and understanding the drivers of migration to plan ahead, allocate funds, attract workers and students, use remittances, facilitate migrant integration, and manage public opinion, among other issues. The increased demand for systematic measurement from policymakers has also manifested itself in two landmark policy frameworks adopted in the last decade: The Global Compact on Migration (GCM) and the Sustainable Development Goals. Footnote 1

Second, in step with the increased salience of migration in policy circles, migration research output has grown dramatically (Pisarevskaya et al., 2019 ). Between 1960 and 1980, the number of academic journals on related subjects quadrupled. In 2020, the International Organization for Migration (IOM) identified over 130 migration-related journals publishing more than 2000 journal articles in English, French or Spanish (IOM, 2020 ).

Policy and scholarly interest both rely on fundamental measurements of migration, i.e. how many people migrate (flows) or have migrated (stocks) within a specific time frame. Yet, the popularity and relevance of migration has outpaced substantial improvements in the systematic measurement of migration, especially at the global level. Indeed, the demand for ‘evidence’ has revived long-standing calls for better data on international migration which experts have been lamenting for decades (Bilsborrow et al., 1997 ; Clemens et al., 2009 ; Laczko, 2016 ; Lemaitre, 2005 ; Willekens et al., 2017 ). Footnote 2

This is the context in which a set of new data sources emerged providing migration researchers of all disciplines with new opportunities to measure migration. The arrival of “innovative data sources”—often referred to as “Big Data” or “digital trace data”—have been described as a “migration data revolution” (Laczko & Rango, 2014 ) and bears much potential to complement traditional migration data (Cesare et al., 2018 ; Sîrbu et al., 2021). At the same time, digital data present a host of new ethical challenges for researchers that are of great concern (Beduschi, 2020 ; Brayne, 2018 ; Hayes, 2017 ; Latonero & Kift, 2018 ; Leese et al., 2021 ; Molnar, 2019 ; Zwitter, 2014 ).

As new researchers and policymakers flock to the field of migration and the empirical study of migration diversifies, there is a need to explain and review new migration data sources to provide a better understanding of their respective limitations and strengths. This paper reviews eight data sources in terms of their reliability, validity, scope for research, access and ethics. The aim is to familiarize experienced and incoming migration scholars with new approaches. The review should be considered an attempt to contribute towards a broader process of interdisciplinary dialogue and expanding the empirical toolbox in migration studies.

Analytical framework

Defining migration.

Before mapping novel data sources, it is important to first define migration for the purpose of this study and clearly delineate the scope of the review.

Important aspects of definitions of migration are space (internal or domestic vs. international/ cross-border migration), time (short term vs. long term), type (e.g. labour, irregular, forced, family, education) and form (flows vs. stocks) (Bilsborrow, 2016 ; UN DESA, 2017 ). This review takes a broad and inclusive view in line with its aim to describe a menu of novel data sources for diverse groups of migration scholars and research interests. Here, migration will be defined as the changing of residence of an individual within or outside the boundaries of a country for longer than three months. While this definition is broad, it excludes certain types of mobility such as travel for the purpose of recreation, holiday, visits to friends or relatives, business, medical treatment or religious pilgrimage (which usually do not imply a change of residence). Footnote 3 The review considers data sources providing information on both migration flows (i.e. the number of migrants entering and leaving (inflow and outflow) a country over the course of a specific period, for example, one year) and migration stocks (i.e. the total number of migrants present in a given location at a particular point in time) (see Global Migration Group, 2017 ). The review considers any form and channel of migration including, among others, labour, family, forced and irregular migration and is not restricted geographically. In addition, to actual observed migration, the review also considers proxies for migration; such as, migration intentions, plans, desires, or aspirations that are commonly used to predict a future change of residence (Tjaden et al., 2019 ). Footnote 4  The review does not include how novel data can be used to research other fields of interest to migration scholars such as integration, the causes of migration, communication, or the impact of migration on society. These fields are not primarily concerned with or rely on (directly or indirectly) inferring migration flows or stocks from data.

Defining “novel” data sources

What are these “new” data sources and what makes them “newer” than the “old” sources? Two popular concepts are helpful to delineate traditional from “innovative” data sources for migration: “big data” and “digital trace data”.

Big data is commonly defined by the “three V’s”: volume, velocity, variety. Volume refers to the magnitude of data. However, there is “little consensus around the fundamental question of how big the data has to be to qualify as “big data” (Gandomi & Haider, 2015 : 137). Velocity refers to the rate at which data are generated which has dramatically increased with the proliferation of digital devices such as smartphones and sensors. Variety refers to the type of data that is being generated. Big data often includes numerical data, text data, images, audio and geo-location data. These Vs are useful to describe many of the sources that are commonly associated with big data such as social media platforms (Facebook, Twitter, Twitter, Instagram etc.) and online search platforms (google). These data compile millions of records about their users ranging from location, online activity to demographic user profile information. At the same time, this information is accessible in real-time, sometimes even publicly through application programming interfaces (APIs). “Big data” includes social media data but is not limited to it. Google, for example, offers a search service which does not operate as a social platform.

Digital trace data are the “results of social interaction via digital tools and spaces as well as digital records of other culturally relevant materials, such as archived newspapers and Google searches including data from popular social networking sites (such as Facebook or Twitter), personal blogs, collaborative online spaces (such as Wikipedia), and data derived from mobile phone or credit card usage” (Cesare et al., 2018 : 1980).

The terms “big data” and “digital trace data” refer largely to the same type of sources. However, while term “big data” highlights the type of data that is produced, the term “digital trace” data focuses on how the data is produced, i.e. through using digital devices (Cesare et al., 2018 ; Hughes et al., 2016 ; Sîrbu et al., 2020 ).

New data sources are often collected by private companies for the purpose of offering services to customers. In contrast, “traditional” sources of migration data such as censuses, administrative data and surveys are traditionally collected or made available by government agencies or (publicly funded) research institutes. Footnote 5 This has far-reaching ethical and empirical implications which will be discussed in later sections.

Review criteria

The review will discuss new data sources along five domains: (1) Reliability—the consistency and reproducibility of migration measurements, (2) validity—the accuracy of migration measures and the extent to which data allows to capture the intended concepts used by migration researchers, (3) scope—the breadth and depth of migration-related research that could be explored based on the respective data source, (4) accessibility—the degree to which data is accessible to researchers, and lastly, (5) ethics –the potential risk of violations of data privacy, consent and data protection principles in the data generation process and potential risk of (unintended) harm for research subjects as a result of analysis produced based on new data sources (e.g. Beduschi, 2020 ; Brayne, 2018 ; Cesare et al., 2018 ; Hayes, 2017 ; Latonero & Kift, 2018 ; Leese et al., 2021 ; Molnar, 2019 ; Zwitter, 2014 ).

Review of innovative data sources to measure migration

Mobile phones: call detail records and gps data from smartphone operating systems.

Mobile phone Call Detail Records (CDR) can track the approximate location of individuals and, as a result, display movements across space by capturing the call signal sent to cell towers for each outgoing and incoming call (Williams et al., 2015 ). All caller details are anonymized. Some telecommunications providers are amenable to social research as well, and often provide documented and anonymized digital trace data from their customers to researchers interested in analysing these data (e.g. Cesare et al., 2018 ; Chi et al., 2020 ).

Reliability CDR provides reliable measures of migration in terms of consistency over time. Movements are recorded automatically as required by operating the telephone network. An advantage in terms of reliability is that the information on location does not rely on self-reports by individuals, which may be subject to response biases (a common issue in surveys). However, reliability issues may apply when using CDR data from different operators. This is a common issue because most countries have several telecommunication companies. As consumers switch services, measures of movement over time become less reliable. As a result, CDR is often used on narrowly defined locations and limited time frames.

Validity The key disadvantage is that such data refers to mobile devices, not individuals as such. It is possible that individuals will share the same device, or gift it to others. Furthermore, many migrants may change devices and/or SIM cards after migrating to other countries, given that service providers offer deals limited to particular countries. Therefore, most contributions using phone data have analysed mobility within narrow geographic units (cities, regions) rather than movements across borders. Furthermore, CDRs can be biased because locations are only recorded when calls are made leaving blank spots in the migration process. Footnote 6

Scope While CDR data are usually more helpful for identifying internal (sub-national) migration patterns, Footnote 7 in some cases they can also be used to measure international migration at the sub-regional level, particularly when combined with other sources. For example, CDR have been used to track internal displacement following natural disasters such as the Haiti and Nepal earthquakes (Bengtsson et al., 2011 ), and the combination of CDR with satellite data can help to map movements between cross-border communities (Hughes et al., 2016 ). Recent work has leveraged Google Location History data for analysis on migration flows. Google Location History is collected through smartphones that operate the Google Android system and through Google services used through smartphones (e.g. Google Maps or Gmail). Pilot research suggests that this novel source of information could provide information about international migration through ‘fine scale mobility with rare, long distance and international trips’ documented through changes in location by users (Ruktanonchai et al., 2018 ). Using the same data, Kraemer et al. ( 2020 ) described ‘global human mobility patterns, aggregated from over 300 million smartphone users’. According to the authors, the data cover nearly all countries and 65% of earth’s populated surface, including cross-border movements and international migration. The advantage of CDR and location data through smartphone use for measuring migration is the timeliness and detail regarding the location. As such, phone records are particularly useful for studying sudden movements in defined geographic locations. Fast evolving migration situations are difficult to capture with “traditional” data sources such as sample surveys and administrative data, and impossible using censuses.

Without linking mobile phone records to other data sources, CDR provides a limited scope for migration scholars. The only information available is time and location. The type, channel and motivation for a change in location remains unobserved. It thus remains unclear who moved, why people moved, where they wanted to go, who they travelled with, through which channel they travelled, and whether they are likely to stay in their current location. This lack of context information is a key shortcoming compared to “traditional” sample survey research.

Accessibility CDR data is not commonly available to researchers and access depends on willingness of telecommunication companies to collaborate. Different operators in different countries may need to comply with different data protection legislation limiting the extent and level of detail of data that can be shared. In addition, access is often tied to large fees.

Ethics CDR data poses serious ethical concerns. When entering a mobile phone contract or installing a smartphone operating system, many users may not be aware that their location data is collected and analysed for various purposes (Beduschi, 2020 ; Brayne, 2018 ; Molnar, 2019 ). Such data uses are often hidden in the fine print. Since telecommunication and smartphone operating system providers are often private companies, there is a lack of transparency of what companies do with the data. In many countries, governments can mandate companies to provide access to data, for example, for the purpose of criminal investigations (Brayne, 2018 ). In the field of migration, the granular CDR data can be used to target humanitarian assistance to specific populations in specific locations, however, it could also be used by authorities for enforcing immigration policies, border protection and identifying individuals entering or residing in a country with an irregular status.

Social media

Geo-located social media activity, such as activity on Facebook (Zagheni et al., 2017 ), Twitter (Chi et al., 2020 ; Fiori et al., 2017 ; Martin et al., 2020 ; UN Global Pulse, 2017 ; Zagheni et al., 2014 ), Skype (Kikas et al., 2015 ), or LinkedIn (State et al., 2014 ), have been used to infer migration flows and stocks based on the location where users log in or information on location provided by the users themselves through geo-tagged posts or profile information (e.g. nationality or birthplace).

Movement is usually inferred based on changes users make to their self-reported location on the respective platform, or changes in location of log-ins. For example, data from the Facebook advertising platform can yield information on ‘home country’ and country of current residence. This means that Facebook could be used as a ‘real-time census’ to estimate, among other things, the number of users classified by the social media platform as ‘expats’ (users living in a country other than their ‘home country’) at the national or global level at a certain point in time (Zagheni et al., 2017 ). Using changes in Facebook users’ locations over time, others have identified the increase in the number of Venezuelan migrants in Spain in early 2018, confirmed by official statistics from the Spanish National Statistical Office (Spyratos et al., 2019 ).

Reliability There are a host of reliability concerns involved in measuring migration using social media data. First, certain segments of the population may be over- or under-represented (for instance, on average, young people are more likely to use Facebook than older people). Footnote 8 Second, even frequent users may choose not to provide information on their past and current location. Certain types of migrants may deliberately avoid providing information on their location on social networks. Third, it is difficult to verify whether changes in location are accurate, given that this information is sometimes self-reported on a voluntary basis. Fourth, the user base of social media providers constantly changes, which complicates analysis of trends over time (see e.g. Cesare et al., 2018 ).

Validity With many kinds of social media data, there is a lack of transparency on key measures relevant for migration are generated. For example, there is limited information on how Facebook identifies who is an “expat” or how it labels users as speakers of a different language. This complicates meaningful interpretation of migration patterns observable in the data.

Scope The advantage of geo-located social media data is that, in many countries, certain social media platforms are wildly popular, so that real-time data on large volumes of movements can potentially be accessed. Such data may be particularly useful to study broader migration trends. The level of detail provided by geo-coded social media data is limited in many cases but more extensive compared to CDR data. For example, Facebook provides aggregate-level information on the number of users with specific characteristics such as age, gender, or even education and income proxies as well as a vast range of preferences (measured via users’ “likes” of particular pages). Changes in the characteristics of the number of people living in a specific place are used by researchers to infer ‘migration flows’, assuming that changes in the ‘stock’ of people that report that they live somewhere necessitates that people moves from countries with lower stock numbers to countries with higher stock numbers. Information on friendship networks across countries—recently made available by Facebook—may be used in the future to forecast cross-country migration trends (Tjaden et al., 2021 ). Despite availability of additional characteristics, the data provide no information about the causes, means, or consequences of migration. There are attempts by governments, law enforcement agencies, international organization and research institutes to monitor the social media activity of migrants before, during and after migration to understand changes in migration patterns (Brenner & Frouws, 2019 ; Dekker et al., 2018 ; Sanchez et al., 2018 ). Footnote 9

Access Many social media companies offer public APIs to allow access to certain parts of their data to researchers. In many cases (e.g. Facebook, Twitter), access can be obtained at no cost which is a substantial advantage over traditional sources such as censuses, administrative data and survey. However, access modalities can change at any given time because data is provided by private companies, rather than taxpayer-funded government or research bodies that are mandated to provide systematic data over time.

Ethics Users of social media are often unaware of the data that is being collected about them and there is a general lack of understanding how such data is and can be used by companies themselves or third parties (Cesare et al., 2018 ; Zwitter, 2014 ). Migration enforcement agencies may use such data for surveillance purposes, which are particularly serious in contexts of irregular migration and forced displacement. Agencies could monitor communication of specific groups or individuals on Twitter and Facebook to identify irregular migrants and track them during their journeys. Companies such as Facebook, however, only allow access to anonymized, aggregate level data to researchers which limits the possibility of using data to harm individuals. Any information on narrowly defined locations and groups becomes inaccessible if the underlying target population decreases beyond a threshold that risks identifying any specific individuals. However, this does not apply to attempts to monitor public communication in social media groups indicating changes in migration patterns. The European Asylum Support Office (EASO) has suspended its efforts to monitor communication of migrants on social media following concerns by the EU own data protection body. Footnote 10

Email IP addresses

Repeated logins to the same website and IP addresses from e-mail activity have also been used to estimate international mobility patterns and users’ likelihood to move to another country (Zagheni & Weber, 2012 ). Rather than self-reported location by the user, certain online services such as email providers collect data on where users log into their accounts.

Reliability and validity The same limitation in terms of reliability and validity apply compared to social media data. Similar to log-ins to social media, log-ins to emails are usually recorded via devices (IP addresses) not necessarily people. For example, it is possible—yet presumably rare—that various people use the same email account which will distort any aggregate measure of migration.

Scope The scope of potential migration analysis is further reduced in the case of email log-ins given that additional socio-demographic and socio-economic information about the users (which are available for Facebook) is lacking or not publicly accessible.

Access Most email providers also do not provide public APIs that make data available to researchers. Email communication is considered personal and private communication whereas some communication on social media platforms is (intentionally or unintentionally) made public by users.

Ethics Similar to social media data, there are issues concerning consent and data privacy. Users may not be aware that email providers track their location. In other cases, governmental enforcement agencies may mandate companies to share content of emails of specific individuals for the purpose of criminal investigations or intelligence which bears the potential for misuse also in case of migrants in irregular settings (Brayne, 2018 ).

Online search data

Online search data has also been used more recently to study migration. Records on Google searchers, for example, have been explored to forecast the number of arrivals of asylum-seekers in Europe (Connor 2017) or internal migration within the U.S. (Lin et al., 2019 ). Search data generated through Google’s online search platform for migration can be exploited to measure migration intentions and predict subsequent emigration flows (Böhme et al., 2018 ; UN Global Pulse, 2014 ). For example, researchers retrieve data on how many times individuals in country A have ‘googled’ a term that the researcher believes to indicate an intention to migrate (to country B)—for example, ‘jobs’, ‘visa’, or the name of the destination country.

Reliability Google Searches are recorded consistently and provide high reliability in terms of the measure as such. The main advantage to Search Data is that Google’s search engine is widely used across the globe and has been successfully used to study other social behaviours (e.g. flu outbreaks). Despite broad coverage, important countries (i.e. China) are missing entirely. Issues of reliability emerge regarding applicability across various country contexts, languages and specific populations. Preliminary research in this area suggests that online searches (e.g. via Goole searchers) are related to actual movement at the aggregate level, yet the selection of specific search terms in various country contexts appears to be highly important. Syrians looking for ways to flee to Europe ‘google’ different terms than Canadians looking for a job in the US. The meaning of the same search terms may also vary in different languages. Overall, this means that Google searches may be indicative of migration from a certain country to another country, but difficult to scale up to multiple migration contexts (see Tjaden et al., 2021 ).

Validity Online search data has one obvious shortcoming: ‘searching’ is not ‘doing’. Just because someone looks up information on another country or, more explicitly, gathers information on how to move to another country, does not mean that they will actually move. Search data (similarly to survey data on emigration intentions) are a ‘pre-behavioural’ proxy for actual migration. Some studies suggest that intentions are a good predictor for eventual migration (Van Dalen & Henkens, 2013 ; Tjaden et al., 2019 ), but research also suggests that the strength of the predictor varies considerably based on where migrants are from and where they want to go (Tjaden et al., 2019 ).

Scope A major disadvantage of Google search data is the high level of aggregation at which data is made available. Search data is made available at the population level for countries or, in certain countries like the US, for subregions. Search data does not include any additional information about those who show interest in migrating, and thus renders any individual-level analysis impossible.

Access Google search data is freely and publicly accessible via the Google Trends platform and API.

Ethics The potential risk of misuse of data is limited given the high level of aggregation and anonymity of data which the company makes available. Serious concerns would arise when data for specific locations and IP addresses is used to infer individual level migration behaviour. Google itself is analysing individual-level location data to provide targeted advertisements to users who use their search engine. However, there is a lack of transparency in terms of the conditions under which such data may be shared with governments or other third parties. In addition, usual concerns around unawareness among users about the usage of their data apply.

Bibliometric data

Bibliometrics is a field of research that uses statistical methods to systematically analyse publications records (books, articles etc.). One sub-field of bibliometrics—scientometrics—is the analysis of scientific publications. Detailed information about academic output is recorded and made accessible through scientific databases (e.g. Scopus, Web of Science, Google scholar and others). This information has been used to model the international mobility of academics (Czaika & Orazbayev, 2018 ; Laudel, 2003 ; Moed & Halevi, 2014 ; Sudakova & Tarasyev, 2019 ; Wang et al., 2019 ). Changes in the researchers’ affiliation to institutions located in different countries indicates migration.

Reliability Measuring migration through changes in affiliations is consistent and reliable. Scientists have an interest to publish their work in recognized journals and books, institutions have an interest that researchers indicate their home institution, and most research outlets make it mandatory for authors to provide this information. Nevertheless, the data is sensitive to the accuracy of self-reported data which can be outdated.

Validity Migration analysis based on bibliometric data has the potential to collect additional context information including socio-demographic characteristics of the professionals (age, gender, ethnic origin, for example, may be inferred based on name recognition algorithms and web scraping individual professionals’ web pages). Additional information about the universities, faculty and chair may be matched with additional effort.

Scope The drawback of this data source is its restriction to a narrowly defined group of professionals (i.e. academics) where public access to their affiliation is the norm. However, it may be possible to extend this approach to other fields of professionals where public information on affiliations is common (i.e. athletes, musicians etc.).

Access Bibliographic data has become available through the digitalization of entire libraries, records of publishers, academic journals, and ambitious projects such as Google Books and Google Scholar that aim to record any academic publications that is published. Most academics provide their affiliations publicly to gain visibility and broaden their reach.

Ethics Compared to previously described sources, ethical concerns are limited because the personal information used for analysis is provided voluntarily and knowingly. The population is restricted to regular labour migrants which limits the potential for misuse by authorities.

Remote sensing technologies

Remote sensing is an umbrella term for collecting information about something without making physical contact. In current usage, remote sensing refers to the use of satellite or aircraft-based sensor technologies (i.e. drones). Remote sensing is commonly used in geography, earth sciences, climate research, agricultural studies, wildlife studies, military, and intelligence gathering, but also increasingly for urban planning, tourism, commerce, and various humanitarian applications (Miller et al., 2019 ). Changes in human activity visible in the images (i.e. settlements, refugee camps, light emissions at night) can be used to infer mobility.

Reliability If applied consistently, the approach to measuring migration using remote sensing technology by averaging physical quantities over pixels can yield reliable migration measures. Algorithms automatically detect changes in visual patterns on satellite or drone images over time. For example, the population size of settlements can be estimated by counting rooftops visible on satellite/drone images. Depending on the proximity and resolution of the image, individuals within certain localities can be identified. Comparing images over time can be used to estimate immigration and emigration into a certain, narrowly defined, location.

Validity The obvious downside of satellite and drone images for measuring migration is that no additional individual-level information about migrants is available: Who is moving, from where, to where, how etc. By itself, remote sensing provides information on how many tents, rooftops or individuals are present in a certain locality, but no information about what happened when there are less dots and shadows the next time new images become available.

Scope There is a rapidly growing number of examples with relevance for migration studies. First, drones and satellite images inform policies and direct aid to refugees. For instance, the United Nations Institute for Training and Research (UNITAR) mapped refugee camps in Jordan and elsewhere with its Operational Satellite Applications Programme. Footnote 11 Civil society organizations such as Human Rights Watch or Amnesty International use satellite imagery to document humanitarian needs of displaced populations at borders or in refugee camps by measuring the growth of settlements. Footnote 12 In this case, satellite images are providing an indication of where aid and assistance are most needed (Bitelli et al., 2017 ; Quinn et al., 2018 ; Shatnawi et al., 2020 ; Tiede et al., 2017 ).

Satellite imagery also forms a key part of the ‘smart border’ agenda, which attempt to use modern technology to improve border management around the world and track ‘illegal’ crossings. Systems relying on remote sensing were developed “to assist border authorities with more effective surveillance and reliable decision-making support” (Al Fayez et al., 2019 ). In contrast, civil society organizations use the same technology to monitor deaths and violations of migrants' rights at the maritime borders of the EU. Footnote 13

For the moment, remote sensing appears to be most useful for informing operations on the ground (managing refugee camps, targeting humanitarian assistance, managing borders etc.) and less for research on migration per se. The technology can also be used to monitor slow onset emigration rates due to changes in climate which can also be inferred from images.

Access With improvements in the quality and accessibility of satellite imagery (Popkin, 2018 ) provided by the European Space Agency, NASA, and others, researchers are also exploring ways to use remote sensing data to measure human migration globally. Public and private bodies offer access to satellite imagery for research purposes and tech companies offer cloud computing power to conduct complex and demanding analyses within minutes. Footnote 14 Depending on the specific data provider, access can be free of charge to research institutes or come with a fee.

Ethics Ethical issues are a key concern for remote censoring technologies because information is collected without the knowledge or consent of individuals. New high-resolution satellite imagery and drone images can identify individuals using face recognition technology. Law enforcement, policing and intelligence agencies use such approaches (Brayne, 2018 ; Hayes, 2017 ; Leese et al., 2021 ; Molnar, 2019 ) which raises serious concerns regarding the situation in undemocratic countries with low data protection standards and policies aiming to suppress and control groups in society. Drones may also be increasingly operated by companies in addition to governments which raises concerns over unknown privacy violations by non-governmental actors.

International air travel

Upon first view, international air passenger traffic belongs to the realm of tourism and transport studies, not migration (see Sect. 2.1.). However, there have been attempts to use this information to infer migration flows. For example. Gabrielli et al. ( 2019 ) used dyadic monthly air passenger traffic between 239 countries and territories worldwide from January 2010 to March 2018 to estimate the number of passengers on commercial flights operated globally. The study explored whether a surplus in travel (increase in travel from A to B but no increase in return travel from B to A within a year) can be linked to migration flows.

Reliability Air passenger data is highly standardized and consistent as it is subject to international industry standards.

Validity Passenger data does not measure migration directly and can only be used to infer different types of migration by inference. Since air passengers data does not allow to track individual passengers or specific cohorts on the basis of their date of entry, researchers need to make assumptions about the length of stay of the passengers. This is problematic because the publicly available data does not indicate who the passengers are, how long they will stay in the country, on which visa they are travelling etc. In addition, flight passenger data is a selective picture of global mobility. 44 percent of registered cross-border travels occur through commercial flights, and that this proportion increases at rising distances between countries (Recchi et al., 2019 ).

Scope Overall, the data may be used to estimate international migration flows if combined with additional data sources. At the moment, the research is still in its exploratory stage and the methods appear underdeveloped. In the future, this approach may bear the potential to measure the level of visa overstayers between countries, one indicator of irregular migration.

Access Air passenger data is collected by flight companies which some make available for purchase. The EU recently made a public and free dataset available. Footnote 15

Ethics Ethical concerns regarding flight data are limited in its current state of the available data. Flight data is aggregated at the country and month level and anonymized. Currently, any misuse for the disadvantage for individuals is unlikely.

Online news data

New advances in technology have made available online news aggregators such as Google News or the Global Database of Events, Language, and Tone (GDELT). Footnote 16 Such platforms monitor the world's news media from nearly every corner of every country in print, broadcast, and web formats. This data has the potential to capture acts of past or prospective migration that were not covered in traditional sources such as administrative data or surveys.

Reliability Migration measures based on online news aggregator data can be considered reliable to the extent that algorithms deriving information on migration apply consistently across all countries and news sources. The issue is that the success of the algorithm in detecting migration may vary by country, by quality of the news outlets, by language and type of migration to be covered. In addition, algorithms may capture the same migration events several times as the same event may have been covered by several news outlets.

Validity The large volume of news articles required to collect information on migration encourages researchers to use language processing algorithms. The emerging evidence is still unclear on how accurately such algorithms may detect events that actually capture migration.

Scope Approaches are still very recent but several uses of this data are available. Carammia et al., ( 2020 ) have used the GDELT database to measure political, social, economic “push factor” events that could motivate people to leave their country. In combination with other data sources, they attempt to forecast displacement and migration with a view to set up early warning systems currently under development in the EU. Footnote 17 In a similar vain, the Internal Displacement Monitoring Centre (IDMC) uses the GDELT database to track internal displacement. Footnote 18 The IOM is also experimenting with such data to improve analysis of the number of migrants that went missing along their journeys, such as the IOM’s missing migrants project (Borja & Black, 2021 ). Apart from eye-witness reports, news articles are the main way to systematically collect data on migrant fatalities and bring light to this tragic topic for policymakers.

Access GDELT and Google News can be accessed online free of charge for researchers.

Ethics Ethical concerns arise in countries with low standards of journalism and data privacy. It is possible, for example, that the identity of individual migrants is revealed in a news article and picked up by automated text analysis. In theory, this information could be used by enforcement agencies to press charges in case of irregular migration or used by smugglers for debt collection. Even when interviewees provide consent for their personal information to be used, they may not be aware that their information may enter migration databases. Such abuses are possible with traditional media sources, however, digital applications may exacerbate the problem by providing cheaper, faster and broader access to data.

Discussion and conclusion

This review highlighted both the enormous opportunity of “big data” and “digital trace data” to complement traditional sources of migration data (see Cesare et al., 2018 ; Hilbert, 2016 ; Hughes et al., 2016 ; Laczko & Rango, 2014 ; Rango & Vespe, 2017 ; Sîrbu et al., 2021 ) and the main challenges and risks associated with such data. Several broader conclusions can be drawn from the above discussion on the eight discussed sources (see Table 1 for a summary):

The main advantages of digital data sources for migration scholars are captured by the first two V’s of the “3 V’s definition” of big data introduced in Sect.  3.2 : Volume and velocity. In some cases, digital data sources provide information of millions of individuals in almost real-time. This provides migration researchers with the possibility explore migration trends where administrative data sources, surveys and censuses (sources traditionally used for inferring migration) are not available (such as in many low-income contexts), not accessible or too slow (for example in contexts of displacement and forced migration that are unfolding rapidly). Another key advantage is its granularity by providing “high-resolution” information. Digital data sources, especially approaches leveraging remote sensing technologies or mobile cell phones, often allow researchers to zoom into migration events at the sub-national, sub-regional or even local level. Nationally representative survey data, for example, often lacks sufficient sample size to disaggregate to the level of regions, districts or cities.

Unlike “traditional” sources, new data sources often make no distinction in terms of the “legal residence status” of individuals. Anyone using a digital service in included in the data. As a result, the volume, granularity and status-agnostics of many digital data sources offer new opportunities to collect information on “hard-to-reach” populations such as recent migrants, displaced or forced migrants and irregular migrants which are often excluded from ‘official’ data sources such as population registers or surveys (Cesare et al., 2018 ; Massey & Capoferro 2004 ; Reichel & Morales, 2017 ). Lastly, a key advantage to migration scholars is the fact that many data sources are accessible online and free of charge.

The review has also highlighted major challenges associated with using digital data sources for inferring migration. ‘Digital trace’ data is largely collected by private companies who offer services to their users and use user data to target advertisements or sell data to third parties. These data are not designed for research purposes. This has important implications both on ethical (Beduschi, 2020 , Brayne, 2018 ; Cesare et al., 2018 ; Hayes, 2017 , Latonero & Kift, 2018 ; Leese et al., 2021 ; Molnar, 2019 ; Sîrbu et al., 2020 ; Zwitter, 2014 ) and empirical grounds in terms of reliability and validity of migration measurement (Cesare et al., 2018 , Ruel et al., 2016 ; Sîrbu et al., 2020 ).

First, there are severe ethical concerns regarding the use of digital data sources including the limited awareness of users regarding the extent of and purposes for which their data is being used and the risk of harm for individual migrants in cases where information is used by law enforcement, border management, intelligence agencies or smugglers (Brayne, 2018 ; Hayes, 2017 ; Molnar, 2019 ). The first rule that a researcher must follow is to acknowledge that data are people and can do harm (Sîrbu et al., 2021 ). Data may include information on particular vulnerable groups such as refugees, irregular migrants, persons displaced by disasters. Some may be persecuted by authorities in origin and destination countries. Researchers must ensure ethical standards for data use that protect vulnerable groups from identification and possible discrimination (Cesare et al., 2018 ).

Violations of data privacy and protection standards are especially concerning in undemocratic countries with low data protection standards, limited rule-of-law, and a lack of democratic norms. In extreme cases, new technologies can enable “digital authoritarianism” and “Orwellian state surveillance” (Dragu & Lupu, 2020 ). Three examples illustrate the extent of real risks: China’s social credit system, for example, leverages smartphone location data, social media communication, travel records, purchase records, camera data and facial recognition, among others, in combination with various administrative records to assign a social credit to its citizen. Low scores could be used to prevent access to a passport or visa needed to leave the country. Footnote 19 After departure of US troops, the Taliban have reportedly considered using US-made digital identity technology to persecute Afghans who have worked with the international coalition. Funded by millions of donor funding, Afghanistan’s National Statistics and Information Authority launched a digital biometric identity card including fingerprints, iris scans and a photograph, as well as voter registration databases. Footnote 20 In 2018, Bangladesh shared hundreds of thousands of data of Rohingya refugees collected by UNHCR with Myanmar then used to facilitate potential repatriation. Footnote 21

Unlike states, researchers often do not have access to individual-level information from digital sources, however, they must be aware of the potential harms for individuals and groups when using digital data sources and must review the data providers’ data protection and privacy standards. Researchers are advised to seek ethical approval by a scientific committee when dealing with digital data and migration.

Apart from ethics, the review has highlighted many empirical challenges. Reliability and validity of digital data sources for inferring migration must be considered when engaging in research. It is often not transparent how exactly key measures of migration are generated (i.e. Facebook, Google). There are also concerns regarding “generalizability” of digital data as the user base of various digital services is often selective and does not represent the general population at large (Cesare et al., 2018 ; Sîrbu et al., 2020 ). Digital data is often made available at highly aggregated levels. This severely limits the analytical potential for migration scholars who are often interested in measuring migration at the individual (micro) level. Moreover, digital data often remains “thin” offering very few additional information beyond time and location such as socio-demographic or socio-economic characteristics of migration, the reasons and channels of migration or the expected duration of stay. This further limits its analytical use especially if the data is not combined with other data sources. Traditional surveys usually do not face these issues (but many others) as they are tailored for answering specific research questions.

Lastly, many populations are excluded from a variety of digital data sources despite technological advances worldwide. For those data relying in digital traces such as social media or online searches, it is still a long way to obtain a comprehensive picture of global mobility as smartphone user penetration reached 38.5 percent in 2020 and half the world population is still offline today. Footnote 22

Looking ahead, several trends are already unfolding. First, new breakthroughs in measuring migration research will stem from a combination of different sources (e.g. Alexander et al., 2020 ; Sîrbu et al., 2020 ; Snijders et al., 2012 ). Given the ‘representativeness’ issue of digital trace data, traditional data is needed for “ground truthing” (i.e. cross-validating data by comparing it with other ‘official’ data sources). To address, the “thinness” of digital data, combining data provides large opportunities to add richness to the analysis. One example is using social media, online search, or mobile phone data to locate migration events or patterns and then target surveys in certain geographies or adjust administrative data collection accordingly (Alexander et al., 2020 ).

The second trend is further convergence and integration of academic disciplines around the issue of measuring migration (e.g. Miller et al., 2019 ). Different disciplines such as earth sciences, climate research, security studies, tourism and transport studies, computer science, sociology, economics, demography, ethnography, library sciences and political science bring different tools, methodologies and technologies to the table which will likely see the field become even more interdisciplinary. As a result, more interdisciplinary dialogue is needed to advance the field.

As the field is changing at a dizzying speed, this paper attempted to provide a brief overview and reflection on the main new digital data sources. The aim of this review was to provide incoming migration researchers with a menu of options and seasoned researchers with an update on new approaches. The information provided assists researchers in making difficult trade-offs when approaching their research question and policy analysts with a broad understanding of the limitations of the data they use.

The review has two obvious limitations. First, given the complex and rapidly growing field it seems near impossible to cover every existing approach and to cover the literature in all its breath. The review is focused on the main approaches without any claim to be exhaustive. Second, the field is rapidly evolving. This means that new research will have become available already by the time of publication.

The toolbox for migration researchers will become bigger, more diverse, but also more powerful due to new opportunities of digital data. Despite the ‘gold rush’ on big and digital data, the review also cautioned migration scholars in view of the many ethical and empirical obstacles for inferring migration based on digital data sources. The review aimed to contribute to a balanced understanding of these new data sources to facilitate knowledge accumulation and interdisciplinary dialogue in the field of migration studies.

Availability of data and materials

Not applicable.

Change history

13 may 2022.

In the online version of this article, there was a typo in the funding note. The article has been updated.

The GCM is the first comprehensive, inter-governmentally negotiated (non-binding) treaty on migration adopted in 2018 by 152 countries, highlights the importance of data and evidence throughout its 23 objectives. The first goal of the GCM itself is improving migration data across the board. The SDGs are the follow-up to the UN Millennium Goals and feature several migration-relevant goals and include indicators to measure progress towards them. New approaches to measuring migration based on “innovative” data sources have mainly been pioneered by academic scholars, yet some of this work has long caught the attention of key national and international governmental stakeholders. In 2009, the United Nations Global Pulse initiative was launched to use new data sources for analysis of development projects and processes, including migration issues. In 2018, the European Commission, in partnership with the IOM Global Migration Data Analysis Centre, launched the ‘Big Data for Migration Alliance’ with the aim of sharing knowledge on data innovation in the field of migration, providing technical support to local and national administrations interested in using new data sources, and testing new data applications for specific policy needs.

There are exceptions. The collection, harmonisation and estimation of migration data within the EU (Poulain et al., 2006 ; Raymer et al., 2013 ) and compilation of data on migration flows in Latin America (Lemaitre, 2005 ) are key achievements. Data on migration in many non-OECD countries remains limited.

Mobility (migration regardless of distance and borders) more broadly has traditionally been the focus of transport studies and urban planning (e.g. Pappalardo et al., 2015 ; Song et al., 2010 ).

There has been some indication that intentions (also expressed in Google searches) are in fact a relevant predictor of future migration both at the national and international levels (e.g. Van Dalen & Henkens, 2013 ; Tjaden et al., 2019 ; Böhme et al., 2018 ).

Censuses are population counts and are used to calculate ‘stocks’ of migrants (Bilsborrow et al., 1997 ; Global Migration Group, 2017 ; White, 2016 ). Administrative data are collected by governments for the purpose of providing certain services or enforcing certain laws and, thus, may include records of migrants subject to a particular law or service. They may include population registers; visas; immigration, expatriation and asylum records; border entries; work permit registers; tax records, and health insurance or social insurance records (Bilsborrow, 2016 ; Global Migration Group, 2017 ; Lemaitre, 2005 ; Poulain et al., 2006 ; Willekens et al., 2017 ). Sample surveys are a common approach to measuring migration, especially in research, given its’ flexible choice of location, target group and thematic scope (Bilsborrow, 2016 ; Bilsborrow et al., 1997 ; Fawcett & Arnold, 1987 ; Goldstein & Goldstein, 1981 ).

Extended Detail Records (XDRs) and Control Plane Records (CPRs) also record locations when something is downloaded or phones are switching antennas providing more complete coverage.

Measuring human mobility (within countries, regions or cities) is an exploding field of research spanning physics and network science, to data mining, and has fueled advances from public health to transportation engineering, urban planning, official statistics and the design of smart cities (see e.g. Song et al., 2010 ; Pappalardo et al., 2015 ).

Researchers are working to address the methodological challenges associated with such (‘self-selection’) bias, and results look promising (Spyratos et al., 2019 ; Zagheni et al., 2017 ; Hughes et al., 2016 ).

Europol, Fontex and EASO as well as EU member states have been actively been monitoring communication in Facebook groups relevant for organizing migration, for example, from the Middle East and Africa to the EU. Information on prices of forged documents or sea transform offered by smugglers provide indication on changes in the volume and direction of migration flows. EASO was stopped collecting the data by the EU’s own data protection watchdog, see https://euobserver.com/investigations/146856 . In theory, it is possible to collect information on users’ profiles and monitor where those users report their location online a year later. This controversial approach has been tried successfully, yet no public evidence has been released.

https://euobserver.com/investigations/146856

https://unitar.org/sustainable-development-goals/satellite-analysis-and-applied-research

https://earthi.space/blog/satellite-solution-refugee-crisis/

https://www.hrw.org/news/2016/09/07/jordan-new-satellite-images-syrians-stranded-border

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For example, governments use drone imagery to monitor immigration attempts in the Mediterranean Sea and at Europe’s land borders (Bhadwal et al., 2019 ; Dijstelbloem, 2017 ) or to monitor border crossing attempts at the Mexican-US border (see https://www.gao.gov/assets/690/682842.pdf ). Greek and EU authorities use satellite imagery to monitor crossing attempts (ibid.). NGOs and universities also use the same information to document human rights abuses by, for example, using satellite imagery and other evidence to reconstruct the journey of a boat with migrants that lost dozens passengers upon its return to Tripoli (Dijstelbloem, 2017 ). Although the boat had been spotted by several aircraft and vessels, no rescue operation had been mounted.

See for example https://earth.esa.int/eogateway/ ; https://search.earthdata.nasa.gov/search ; https://earthexplorer.usgs.gov/

See the EU Knowledge Centre for Migration and Demography’s Dynamic Data Hub, at:  https://bluehub.jrc.ec.europa.eu/migration/app/?state=5d6005b30045242cabd750a2 .

GDELT is a repository of 316 types of geolocated event reported in the world’s broadcast, print and web media, in 100 languages.

Frontex, EASO and JRC are all developing early warning, forecasting and foresight approaches.

https://www.internal-displacement.org/expert-opinion/idetect-how-technology-and-collaboration-between-innovators-can-help-ensure-no-one

The system has reportedly been used to suppress and control the Uighur minority in China’s Xinjiang region. Analysis to linked data from various digital data sources alerts enforcement agencies at checkpoints when Uighurs approach the limits of their neighbourhood. (see Ross Andersen in the Atlantic: “The panopticon is already here”, available at https://www.theatlantic.com/magazine/archive/2020/09/china-ai-surveillance/614197/

See Emrys Schoemaker, 7 September 2021 in the Guardian: “The Taliban are showing us the dangers of personal data falling into the wrong hands “, available at https://www.theguardian.com/global-development/2021/sep/07/the-taliban-are-showing-us-the-dangers-of-personal-data-falling-into-the-wrong-hands

See Human Rights Watch on 21 June 2021: “UN Shared Rohingya Data Without Informed Consent”, available from https://www.hrw.org/news/2021/06/15/un-shared-rohingya-data-without-informed-consent

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Acknowledgements

The author would like to thank Marzia Rango (IOM), Emilio Zagheni (Max Planck Institute for Demographic Research), Ingmar Weber (Qatar Computing Research Institute) and Teddy Wilkin (EASO) for numerous discussions and presentations on the potential of digital trace data for measuring migration which motivated the idea for this paper.

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Tjaden, J. Measuring migration 2.0: a review of digital data sources. CMS 9 , 59 (2021). https://doi.org/10.1186/s40878-021-00273-x

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Article Contents

Definition of migrants, drivers of migration, health challenges in the destination country, conclusions, conflict of interest.

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Drivers of migration: why do people move?

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More than 244 million international migrants were estimated to live in a foreign country in 2015, leaving apart the massive number of people that have been relocated in their own country. Furthermore, a substantial proportion of international migrants from southern countries do not reach western nations but resettle in neighbouring low-income countries in the same geographical area. Migration is a complex phenomenon, where ‘macro’-, ‘meso’- and ‘micro’-factors act together to inform the final individual decision to migrate, integrating the simpler previous push–pull theory.

Among the ‘macro-factors’, the political, demographic, socio-economic and environmental situations are major contributors to migration. These are the main drivers of forced migration, either international or internal, and largely out of individuals’ control.

Among the ‘meso-factors’, communication technology, land grabbing and diasporic links play an important role. In particular, social media attract people out of their origin countries by raising awareness of living conditions in the affluent world, albeit often grossly exaggerated, with the diaspora link also acting as an attractor. However, ‘micro-factors’ such as education, religion, marital status and personal attitude to migration also have a key role in making the final decision to migrate an individual choice. The stereotype of the illiterate, poor and rural migrant reaching the borders of affluent countries has to be abandoned. The poorest people simply do not have the means to escape war and poverty and remain trapped in their country or in the neighbouring one.

Once in the destination country, migrants have to undergo a difficult and often conflictive integration process in the hosting community. From the health standpoint, newly arrived migrants are mostly healthy (healthy migrant effect), but they may harbour latent infections that need appropriate screening policies. Cultural barriers may sometimes hamper the relation between the migrant patient and the health care provider. The acquisition of western lifestyles is leading to an increase of non-communicable chronic diseases that require attention.

Destination countries have to reconsider the positive medium/long-term potential of migration and need to be prepared to receive migrants for the benefit of the migrants themselves and their native population.

According to the International Organization for Migration (IOM), as many as 244 million people were international migrants in 2015 1 and the UN Department of Economics and Social Affairs estimates that the figure is as high as 257.7 million in 2017. 2 Importantly, out of the 244 million claimed by IOM in 2015, 90.2 million moved from a southern country to another southern country, while only 85.3 million were people migrating from the south to the north, the remaining being individuals from the north migrating to the south (13.6 million) or from the north to the north (55.1 million). At present, most international migrants are of working-age and live in Europe, Asia and North America (Figure 1 ). Apart from international migrants, an astonishing figure of 740 million people is estimated to have migrated internally within their origin country. 1

International migrants by region of residence, 2015 Source: UN DESA, 2015. www.un.org/en/development/desa/population/migration/data/estimates2/estimates15.shtml, modified

International migrants by region of residence, 2015 Source: UN DESA, 2015. www.un.org/en/development/desa/population/migration/data/estimates2/estimates15.shtml , modified

Migration is as old as humankind. People have always moved in search of better living conditions for themselves and for their loved ones or escaping dramatic situations in their homeland. These two major drivers were the fundamentals of the ‘push and pull’ theory that was first proposed by Lee in 1966, 3 encompassing economic, environmental, social and political factors pushing out from the individual homeland and attracting him/her towards the destination country.

Lee’s theory has the merit of being one of the first trying to identify in a modern and scientific way the drivers of such a complex phenomenon after Ravenstein first addressed them in Scotland in 1885. 4 The main elements of the ‘push and pull’ theory will also be considered in this article for didactic purposes, but the Author recognizes that in the current global world reality is certainly much more complex and faceted, involving both local national realities and macro-level causes as well as meso-level and micro-level causes related to the link of the individual to his/her ethnic or religious group and the personal characteristic of the individuals respectively. 5 (Figure 2 ) Recently, the ‘pull-push plus’ theory has also been proposed, which considers predisposing, proximate, precipitating and mediating drivers of migration. 6

Complex drivers of migration: macro-, meso- and micro-factors Source: Foresight: Migration and Global Environmental Change (2011) Final Project Report The Government Office for Science, London, modified

Complex drivers of migration: macro-, meso- and micro-factors Source: Foresight: Migration and Global Environmental Change (2011) Final Project Report The Government Office for Science, London, modified

Regardless of the theoretical framework adopted, the topic addressed by this article is difficult because sound scientific data are scarce, existing literature is mainly qualitative and often presented as grey literature. In addition, geographical and cultural elements may influence the weight of the single determinant in different continents and in different periods. Finally, although the various drivers will be presented separately, we recognize that they are part of a unique complex scenario where they strongly interact.

Labour (or economic) migrants (and family reunification) and

Forced migrants (asylum seekers and refugees);

In this respect, it is useful to report below the synthetic definitions of asylum seekers and refugees from IOM. 7

Asylum seeker

A person who seeks safety from persecution or serious harm in a country other than his or her own and awaits a decision on the application for refugee status under relevant international and national instruments. In case of a negative decision, the person must leave the country and may be expelled, unless permission to stay is provided on humanitarian grounds.

A person who, ‘ owing to a well-founded fear of persecution for reasons of race, religion, nationality, membership of a particular social group or political opinions, is outside the country of his nationality and is unable or, owing to such fear, is unwilling to avail himself of the protection of that country (Geneva Convention, 1951, Art. 1A).’

The factors acting together and determining the final decision of an individual to migrate may be subdivided in macro-elements (largely independent from the individual), meso-elements (more closely related to the individual but not completely under the individual's control) and micro-element (personal characteristics and attitudes). Those that have been more extensively studied will be discussed in this article.

Inadequate human and economic development

Human development is enormously unbalanced in the various regions of the planet and the gap is increasingly wide. The economic and political reasons underlying this sad situation are beyond the scope of this article and will not be addressed here. The Human Development Index (HDI) is a composite index combining the performances of the different countries on health (life-expectancy), education (years of schooling) and economics ( per capita income) proposed by the United Nations Development Program (UNDP).

The 2016 HDI top ranking includes 15 western countries (11 European, 2 North American, 2 in Oceania) and 5 Asian countries among the first 20 ranked nations. 8 At the opposite extremity of the list, 19 out of the last 20 nations with the lowest HDI indexes are from Africa, a striking difference. However, during the first decade of the new millennium, many African countries experienced a remarkable economic growth, with gross domestic product (GDP) increases exceeding 5% in average according to the International Monetary Fund. Unfortunately, the consequent relative wealth has not been equitably distributed in the population and the subsequent world economic crisis since 2011 has slowed down the economic performances of most African countries to a bare 2% yearly GDP increase. As a consequence, most jobs in developing countries are still in the informal sector, with little salary and social protection, thus nurturing the willing to find better job conditions elsewhere. Low performances in the health, education and economic sectors are a reflex of the vulnerability of the health, education and productive systems which is caused by the lack of economic and human resources. With particular regard to the health sector, such situations that provide little professional and economic motivation pave the way for qualified health professionals to leave their origin countries, a phenomenon known as ‘brain drain’ and creating a vicious circle.

Poor health services, little educated and qualified work force and poverty are a fertile background promoting migration of individuals in search of better life. New communication technologies, largely available in urban settings even in developing countries, allows people to compare the western lifestyle with the local situations where the luxurious houses and cars of expatriates (and local authorities…) often contrast with the poor living conditions of the local populations. The gradient of prosperity.

Migration and development are strictly linked and influence each other. Paradoxically enough, in fact, migration may be driven by both a lack of development and by an increasing socio-economic development in a specific country, at least in the initial phase. 9

Demographic increase, urbanization

The world's living population has increased in an unprecedented way during the last two centuries, from 1 billion estimated to live in the year 1800 to the more than 6 billion living at the beginning of the second millennium, to the roughly 11 billion that will probably inhabit the earth in 2100. 10 The bulk of this massive increase is taking place in Asia and Africa, where high fertility rates, driven by infant mortality, and poor birth control programmes result in high annual population increase rates. On the contrary, the fertility rate in western industrialized countries is shrinking. According to the World Bank, the average fertility rates in high income countries was 1.7 children per woman in 2015, while it was 4.8 per woman in low-income countries. 11 As a global result, the population of western industrialized countries is reducing in size and getting progressively old (aging population), while the young working-age population of the developing countries is rapidly increasing. The African continent offers a striking example. From 493 million in 1990, the African population grew to 1 billion in 2015 and it is expected to rise to 2.2 billion in 2050 and to 4 billion in 2100! 12

With particular regard to the African continent, the increasingly young population will probably exceed by far the otherwise improving—but not equitably distributed—economy, giving origin to the so-called ‘jobless generation’ phenomenon. This means that the increasing global wealth is not mirrored by a proportional number of jobs to satisfy the increasing expectations of the growing skilled young generation, at least in the short-medium term. 13

As a matter of fact, the flow of migration in relation to demographic increase could also be regarded in the opposite way, raising the question ‘ why do so few people migrate? ’ 14 In fact, even if the stereotype of migration proposes a model of ‘mass’ invasion of rich countries by migrants from low-income countries in terms of absolute numbers, the proportion of migrating people is quite stable (3.3% of the world population in 2015, 2.4% of the world population in 1960).

Climate changes

It is now almost universally accepted that the climate is becoming warmer and warmer at an increasing speed, causing health inequalities across the world 15 apart from other unwanted effects. It is also accepted that the driving causes of such climate changes started with the industrial revolution, are mainly anthropogenic in nature and are largely due to the emission of greenhouse gases (in particular CO 2 , methane and nitrous oxide) by industrial activities from carbon-based energy. It has been estimated that 97% of such emissions occur in industrialized rich countries, leaving a mere 3% emission coming out from low-income countries. 16 The impact of climate changes is astonishingly severe in the south of the world, where 150000 are estimated to have died in 2000 from the consequences of the planet warming. 17 Drought, flooding, increases in arthropod borne infections due to vector spreading in regions where the contrast measures are difficult to implement due to scarcity of means also indirectly impact on morbidity and economic agricultural revenues. The case of Lake Chad is extreme but enlightening. From the nearly 25000 square kilometres Lake Chad had in 1963, its water now covers a bare one-twentieth of its original extension, with severe impact on the fertility of the surrounding land. This shortage of water, food and agricultural resources forces people and livestock to move in search of a less hostile environment. 1 Examples of land degradation induced by climate changes are multiple and represent a driving force for people to migrate by producing food insecurity and risk of health-related crisis. 18

According to the IOM, environmental migrants are those ‘ persons or groups of persons who, for reason of sudden or progressive changes in the environment that adversely affect their lives or living conditions, are obliged to leave their habitual homes, or choose to do so, either temporarily or permanently, and who move either within their country or abroad ’. 19

It has been suggested that the environment may impact on migration flows by directly affecting the hazardousness of place but also indirectly changing the economic, political, social and demographic context with very complex interrelationships. 20

The ‘climatic migrants’, as they are sometime called, might possibly reach the astonishing figure of 200 million by the year 2050, according to the IOM. 21 However, forecasts are difficult to make because sound scientific data on this topic are extremely scarce and do not permit reliable estimates. 22 The assessment of the real impact of worsening environmental conditions, albeit logical, would greatly benefit from sound research studies.

Wars and dictatorship

Even now, at the beginning of the third millennium, many areas of the world—in virtually all continents—host bloody conflicts and social instability where armed parties fight or where rude dictatorships are ruling and denying social rights. Some are well-known to the public (i.e. Syria and Afghanistan), while others are not as is the case of the Horn of Africa (Eritrea, Somalia) and some areas of West Africa (Mali, Gambia) and the Sahelian region or in Central and Southern America. 1 People may be denied basic human rights and the access to education and to a dignified life may be prevented, especially for females. Fundamentalism is such countries may easily grow, as it is the case with the deadly activities of Boko Haram in Northern Nigeria, that it is estimated to have caused the internal displacement of nearly 2 million people. 23 It is to be noted that the majority of displaced people in warring nations are relocated within national borders, thus officially they are not considered international migrants, but rather internal refugees.

Land grabbing

Land grabbing is a phenomenon that has become increasingly important since the beginning of the new millennium. The term ‘land grabbing’ refers to the intensive exploitation of vast areas of land in rural areas of low-income countries by private international enterprises or even by foreign governments in order to implement large-scale intensive cultivations (mainly biofuels and food crops) or to exploit minerals, forestry or the touristic industry. This happens to the detriment of the poor local population, which is poorly (and often forcedly) compensated and virtually obliged to leave the rural areas to reach the degraded urban peripheries within their own countries, where they often live a difficult life in a different setting from the one they and their families have experienced for centuries. Psychological and physical impairment is frequent in such communities and international migration may then occur. Apart from this direct impact, the economic benefit of small-scale agricultural industry is of advantage of the local communities, while the intensive exploitation of lands as a consequence of land grabbing is mainly to the benefit of the private enterprise stock owners and the international market, 24 leading to the progressive impoverishment of the increasingly resource-poor country. Together with environmental damages due to climate changes, the loss of small-scale land property and its turning into intensive exploitation causes a progressive land degradation, which leads to a progressive abandonment of native lands by a mass of people. 25

This issue will only be briefly alluded to, as it is too wide and complex to be adequately addressed in such context. The history of humankind offers many examples of mass population movements caused by religion persecution or following the dream of a land where individual faith could be freely preached. However, these movements have often been the consequence of a political will as it has been the case of the conflictive Muslim, Hindu and Sikh movement across the newly created border between India and East Pakistan (now Bangladesh) in 1947. Similarly, Jews flowed to Palestine after the Second World War, also attracted by the law of return, favouring migration of Jewish people to the new state of Israel. In many other instances, religion has been the pretext for ethnic persecution and expulsion, as is possibly the case for the Rohingya Muslim population from Myanmar or the mass movements caused by armed fundamentalists groups such as Daesh or Boko Haram in the Middle East and sub-Saharan West Africa, respectively.

Sexual identity

A number of countries have a quite restrictive policy on sexual identity and LTGB people (lesbians, gay, transgender and bisexual people) face psychological and even physical violence, forcing them to hide their sexual identity. The impact of such policies on international migration has recently been the subject of some investigation that is in its infancy. No doubt, however, that an impact exists, especially from countries where ‘machismo’ is considered a value. 26 , 27 A comprehensive overview of the issues related to the protection of social rights in those people forced to migrate due to their sexual orientation may be found in the 2013 thematic issue of Forced Migration Review. 28

A final note has to be dedicated to the education level of migrants. International migrants are often regarded as illiterate and poor people escaping poverty from remote rural areas. This stereotype is far from being true in most instances for both economic and forced migrants. Migrants in search of a better future usually have a more pronounced initiative, attitude and boldness than the average person, with some skills and financial resources needed to plan and fund a long-distance journey as it is the case for international migration. 29 In most instances, they are more educated than their peers left behind in their origin country. 30 Sometimes they are even more educated than their peers in the destination country. 31 In addition, individuals from families or communities that already positively experienced migration in previous years are more inclined to migrate as their travel abroad is regarded as of possible benefit to the origin society. 5 For such individuals, the existence of ethnic or family links in the destination country is a further driver of migration. The relationship between education and migration are twofold. From one side, the migration of educated people from low-middle income countries to OECD countries constitute a net loss of human qualified resources for the origin countries and a gain for the host country. A phenomenon known as ‘brain drain’. From the other side, the financial and ideational remittances from destination countries may also have an impact on the education of non-migration children and adolescents in their origin countries. 30

Personal willingness to migrate

All the above drivers of migration act, with different strength in different places, to build the general frame at the macro-level of each specific geographical, economic and political situation. However, the meso- or even micro-levels are also important in driving the final choice of the individual to migrate. The influence of the ethnic group, the family support—both economic and societal—is of the upmost importance for a specific individual to make the final choice to migrate or to stay. Educational level and access to financial means permitting to afford the migration travel have already been discussed above, but other factors such as ethnic and social customs are also important. The aspiration and desire to migrate is a crucial key factor that interacts with other external drivers of migration to build the final decision to actually migrate. 32

Regardless of the mix of drivers leading to migration in any individual person, migrants usually undergo a difficult integration process in the hosting community. Conversely, the receiving country could also be obliged to adapt its social and health systems to face the needs of the hosted population. In many instances, this process is not without conflict for the cultural and economic adaptations that it implies.

From the health point of view, although generalization is inappropriate due to the heterogeneity of provenance and epidemiology of diseases in the origin countries, newly arrived migrants are usually healthy (the ‘healthy migrant’ effect) but more affected by latent infections than the host populations, 33 requiring screening policies and links to care. Crowded and inadequate living conditions in hosting camps may also lead to infectious diseases outbreaks, as recently reported in France. 34 However, despite the reported higher prevalence of selected infections in migrants, including potentially diffusive respiratory tract infections, the risk of significant spread in the receiving populations has been reported to be negligible, if any. 35

Once resettled in the host country, foreign-borne individuals may face infectious exposure when travelling back—often accompanied by children born in the host country—to their countries of origin. They are then referred as VFRs (Visiting Friends and Relatives), and represent a significant proportion of imported diseases in western countries, as in is the case for imported malaria. 36 Pre-travel advice in such VFR populations poses significant challenges to optimally address adequate preventive measures. 37 However, even the non-communicable diseases burden (diabetes, hypertension, metabolic disorders, cardio-vascular diseases, etc.) is increasing among migrants, as a result of changing alimentary habits in developing countries and to the progressive acquisition of western lifestyles after a few years in the receiving country. 38

Finally, the cultural interaction between the migrant patient and the care provider is often not without conflicts. The emphasis on the possible exotic nature of otherwise ubiquitous illnesses or, on the contrary, the underestimation of culturally bound complaints (cultural barriers) are often aggravated by linguistic barriers leading to potential medical errors. The knowledge of culturally sensitive medical issues, such as genital mutilations, is generally poor in western physicians, requiring specific training and research. 39

In conclusion, the migration flow is now a structural phenomenon that is likely to continue in the next decades. While many migrants from low-income countries aim to reach more affluent areas of the world, it is to be appreciated that a similar, or even bigger, mass of people migrates to neighbouring low-income countries in the same geographical area.

Migration is always the result of a complex combination of macro-, meso- and micro- factors, the former acting at the society level and the latter acting at the family or even individual level. The prevalence of a factor over the other is unpredictable.

Among the ‘macro-factors’, the inadequate human and economic development of the origin country, demographic increase and urbanization, wars and dictatorships, social factors and environmental changes are the major contributors to migration. These are the main drivers of forced migration, both international or internal.

Among the ‘meso-factors’, linking the individual to his/her ethnic group or religious community, land grabbing, communication technology and diasporic links play an important role. The role of communication technologies and social media to attract people out of their origin countries is indisputable today. Awareness of living conditions in the affluent world—albeit often grossly exaggerated—contributes to nurture the myth of western countries as Eldorado. The ease of communication with the diaspora and family members who migrated previously reinforces the desire of escaping from poverty to a challenging new life abroad.

However, ‘micro-factors’ such as education, religion, marital status and personal attitude to migration also have a key role to make the final decision to migrate that is an individual's choice.

In any case, the stereotype of the illiterate poor migrant coming from the most remote rural areas and reaching the borders of affluent countries does not stand. The poorest people simply do not have the means to escape war and poverty and remain trapped in his/her country or in the neighbouring one. Some degree of entrepreneurship, educational level, social and financial support is usually requested for international south–north economic migration and personal characteristics and choices also play a role. This phenomenon has a positive aspect, as the possibility of success of migrants increases as do remittances, but also a negative one, as the most active part of the origin country may be drained preventing local development.

Usually, even if generalization is inappropriate, newly arrived migrants are in good health, despite a higher prevalence of latent chronic infections (‘healthy migrant’ effect). However, marginalization in the host country may lead to a deterioration of such health status, a phenomenon known as the ‘exhaust migrant’ effect.

Host countries, which may have also an economic benefit from migration in the medium long-term, have to be prepared to receive migrants for the benefit of the migrants themselves and their native population.

None declared.

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The Effects of Immigration in a Developing Country: Brazil in the Age of Mass Migration

The effects of immigration are reasonably well understood in developed countries, but they are far more poorly understood in developing ones despite the importance of these countries as immigrant destinations. We address this shortcoming by studying the effects of immigration to Brazil during the Age of Mass Migration on its agricultural sector in 1920. This context benefits from the widely recognized value of historical perspective in studies of the effects of immigration. But unlike studies that focus on the United States to understand the effects of migration from poor to rich countries, our context is informative of developing countries' experience because Brazil in this period was unique among major migrant destinations as a low-income country with a large agricultural sector and weak institutions. Instrumenting for a municipality's immigrant share using the interaction of aggregate immigrant inflows and the expansion of Brazil's railway network, we find that a greater immigrant share in a municipality led to an increase in farm values. We show that the bulk of the effect of immigration can be explained by more intense cultivation of land, which we attribute to temporary immigrants exerting greater labor effort than natives. Finally, we find that it is unlikely that immigration's effect on agriculture slowed Brazil's structural transformation.

For helpful comments, we thank William Collins, Martín Fernández Sánchez, David Jaeger, Aldo Musacchio, Blanca Sanchez-Alonso, Sandra Sequeira, João Tampellini; seminar participants at the University of Bonn, University of York, University of Newcastle, Wageningen University, and Vanderbilt University; and conference participants at the 2021 Markets and Policy in History Workshop, 2022 Economic History Society Conference, 2022 European Historical Economics Society Conference, and the 2022 World Economic History Congress. Jared Katz and Víctor Luna provided excellent research assistance. Renato Colistete kindly shared data with us. Financial support was provided by Vanderbilt University and the University of St Andrews. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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A systematic review of climate migration research: gaps in existing literature

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  • Published: 16 April 2022
  • Volume 2 , article number  47 , ( 2022 )

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

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Introduction

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

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

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

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

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

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

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

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

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

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

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

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

Methodology

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

figure 1

Systematic review flowchart

Article search

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

Article selection

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

Article review

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

Article analysis

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

Spatial and temporal trend

General information.

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

Reviewed study areas

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

Climatic zones of the reviewed studies

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

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

figure 2

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

Migration types and sources of climate migrants

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

Disciplinary foci

Research discipline.

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

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

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

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

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

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

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

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

Primary research themes

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

Methodological approaches

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

Triggering forces of migration

Climatic causes of migration.

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

Influencing causes of migration

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

Other key issues

  • Impacts of climate migration

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

Discussed communities

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

Livelihoods of climate migrants

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

Discussion and research gaps

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

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

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

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

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

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

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

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

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

Limitations and future research scope

Limitations of this study.

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

Toward a research agenda for climate migration

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

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

Data availability

Data are available from the corresponding author upon reasonable request.

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Acknowledgements

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

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

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Both authors have contributed to the study conception and design. RCG performed the literature search, collected and analyzed the data, and prepared the first draft of the manuscript. CO critically reviewed the manuscript. Both authors have read and approved the final manuscript.

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Ghosh, R.C., Orchiston, C. A systematic review of climate migration research: gaps in existing literature. SN Soc Sci 2 , 47 (2022). https://doi.org/10.1007/s43545-022-00341-8

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