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A meta-analysis of country-level studies on environmental change and migration

Nature Climate Change volume 10, pages 904–912 (2020)Cite this article

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Abstract

The impact of climate change on migration has gained both academic and public interest in recent years. Here we employ a meta-analysis approach to synthesize the evidence from 30 country-level studies that estimate the effect of slow- and rapid-onset events on migration worldwide. Most studies find that environmental hazards affect migration, although with contextual variation. Migration is primarily internal or to low- and middle-income countries. The strongest relationship is found in studies with a large share of countries outside the Organisation for Economic Co-operation and Development, particularly from Latin America and the Caribbean and sub-Saharan Africa, and in studies of middle-income and agriculturally dependent countries. Income and conflict moderate and partly explain the relationship between environmental change and migration. Combining our estimates for differential migration responses with the observed environmental change in these countries in recent decades illustrates how the meta-analytic results can provide useful insights for the identification of potential hotspots of environmental migration.

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Fig. 1: Primary quantitative country-level studies testing for a relationship between environmental factors and international and internal migration.
Fig. 2: Distribution of the precision-weighted standardized effects by type of environmental hazard.
Fig. 3: Predicted environmental effects on migration by country sample compositions.
Fig. 4: Predicted environmental migration worldwide measured in standard deviation changes in migration.

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Data availability

The meta-data and country-level data generated during and/or analysed during the current study are available in the Harvard Dataverse repository107, https://dataverse.harvard.edu/dataverse/Meta-Analysis_EnvironmentalMigration.

Code availability

The data analysis was carried out in R108. The complete codes used to generate and visualize the results reported in this study are available in the Harvard Dataverse repository107, https://dataverse.harvard.edu/dataverse/Meta-Analysis_EnvironmentalMigration. All used packages are acknowledged and cited in the source code file.

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Acknowledgements

We thank the authors of the papers included in the meta-analysis who kindly shared their data and codes with us. This research was funded by the Austrian Science Fund, grant number Z171-G11.We also thank the IIASA for funding, as well as the National Member Organizations that support the institute. Further funding was provided by the International Climate Initiative (IKI: www.international-climate-initiative.com) and the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU). The Potsdam Institute for Climate Impact Research is a member of the Lebniz Association.

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Authors and Affiliations

  1. Vienna Institute of Demography/Austrian Academy of Sciences, Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Vienna, Austria

    Roman Hoffmann, Anna Dimitrova & Jesus Crespo Cuaresma

  2. Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany

    Roman Hoffmann

  3. International Institute for Applied Systems Analysis (IIASA), Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Laxenburg, Austria

    Anna Dimitrova, Raya Muttarak, Jesus Crespo Cuaresma & Jonas Peisker

  4. School of International Development, University of East Anglia, Norwich, UK

    Raya Muttarak

  5. Department of Economics, Vienna University of Economics and Business, Vienna, Austria

    Jesus Crespo Cuaresma

  6. Austrian Institute of Economic Research (WIFO), Vienna, Austria

    Jesus Crespo Cuaresma

  7. Center for Economic Studies (CESifo), Munich, Germany

    Jesus Crespo Cuaresma

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Contributions

R.H. and R.M. conceived the project and designed research; A.D., R.H. and R.M. collected and reviewed the literature; J.C.C. helped with statistical techniques and procedures; A.D., R.H. and J.P. collected, compiled and analysed data; J.C.C., A.D., R.H., R.M. and J.P. interpreted the results and wrote the manuscript.

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Extended data

Extended Data Fig. 1 Relationships between environmental hazards and migration for different parts of the world.

Blue lines show climate trends and dark gray bars show population movement variables. Lines for temperature and drought are smoothed moving averages. Temperature and rainfall anomalies are yearly deviations from the long-term average (1901–2016). The standardized precipitation and evapotranspiration index (SPEI) is measured at a 3-month scale. Rapid-onset disasters include climatological, hydrological and meteorological disasters. Sources: a) North Africa, SPEIbase (Beguería et al., Bull. Am. Meteorol. Soc. 91, 2010) and Cai et al. (J. Environ. Econ. Manage. 7922); b) Syria, SPEIbase and UNHCR Refugee Statistics; c) South Asia, CRU TS 3.25 (Harris et al., Int. J. Climatol. 34104) and Cai et al22; d) Central America and Mexico, CRU TS 3.25 and Cai et al22; e) Angola, CRU TS 3.25 and UN World Urbanization Prospects 2018; f) Philippines, EM-DAT and IDMC Global Internal Displacement Database.

Extended Data Fig. 2 Density distributions of standardized effects.

Panel a shows the distribution of (unweighted) standardized effects of all model estimates (k = 1803) across studies (displayed range −1 to +1). Positive effects are highlighted in darker grey. Panel b shows the mean effect distribution on study level (n = 30, between-study variation). Panel c shows the distribution of the deviations of the individual estimates (k = 1803) from the study mean effects (within-study variation).

Extended Data Fig. 3 Differences in sample composition by study cases.

Panel a shows boxplots of the share of countries in the model samples belonging to a specific category of countries. Panel b shows the regional focus of the study models. SSA, Sub Saharan Africa, MENA, Middle East North Africa, LAC, Latin America and the Caribbean, OECD, Organization for Economic Co-Operation and Development. Conflict countries are countries with a recurring conflict for at least five years in the period of 1960 to 2000 (Major Episodes of Political Violence database).

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Hoffmann, R., Dimitrova, A., Muttarak, R. et al. A meta-analysis of country-level studies on environmental change and migration. Nat. Clim. Chang. 10, 904–912 (2020). https://doi.org/10.1038/s41558-020-0898-6

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