Climate Change and Human Migration in the Developing World. Clark Gray UNC-CH Geography

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1 Climate Change and Human Migration in the Developing World Clark Gray UNC-CH Geography

2 Outline Demographic approaches to migration Definitions Global and local patterns Climate and migration in the developing world Climate refugees? A way forward with 2-3 examples Conclusions

3 My perspective Demography Uses survey and statistical methods to understand the patterns and drivers of migration at the population-scale Population-environment research Combines demographic methods and environmental data sources Livelihoods research Views migration as part of portfolio of strategies

4 Intro to migration Migration = change of residence that crosses an administrative boundary Most moves: Are short-distance and many are temporary. Are to find work or to live with family. Migration is selective on age, gender, wealth and social networks. Migration has led to a world that is >50% urban with growing migrant populations.

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13 Climate refugees? Human migration is predicted to be one of the key social outcomes of climate change: The greatest single impact of climate change could be on human migration. (IPCC 1990) The impacts of climate change are already causing migration and displacement. (UN 2009) This makes sense: Agricultural productivity may decline and natural disasters may increase with climate change.

14 Climate refugees? Theoretical problems: Ignores the potential for adaptation. Ignores economic and social barriers to migration. Empirical problems: Adequate data on migration are hard to obtain. Few quantitative studies have been conducted. An alternative set of hypotheses: Migration is likely to be adopted selectively, and will include temporary and short-distance moves. Climate change might undermine possibilities for migration.

15 Demography to the rescue! 1. Measure migration using longitudinal or retrospective household surveys. 2. Measure climate variability using data from weather stations or satellites. 3. Link the two using Geographic Information Systems. 4. Analyze the data using multivariate statistical models which account for other influences on migration.

16 Three examples Gray, C., and V. Mueller. (2012a). Drought and population mobility in rural Ethiopia. World Development 40(1): Gray, C., and V. Mueller. (2012b). Natural disasters and population mobility in Bangladesh. Proceedings of the National Academy of Sciences 109(16): Gray, C. and R. Bilsborrow. (In press). Environmental influences on human migration in rural Ecuador. Demography.

17 Ethiopia October 2008

18 The Ethiopian Rural Household Survey Design: Longitudinal survey of 1,100 households with rounds in 99, 04 and 09 Sampling: 15 rural communities selected to be broadly representative Migration data: Household reports of migrant departures Environmental data sources: Household reports of drought Satellite-derived measures of rainfall

19 Proportion reporting drought by year and community

20 Ethiopia: Analysis Data: Person-year dataset on 3,100 individuals Multinomial outcomes: Distance of move: In/out of district Reason for move: Labor/marriage/other Drought measures: Reported and rainfall Controls: Demographic, wealth and networks Model: Discrete-time multinomial event history model with fixed effects for year and community Estimated separately for men and women

22 Ethiopia: Results Men s long-distance migration increased with drought, particularly for land-poor households. Women s marriage-related moves decreased with drought, reflecting resource constraints.

23 Bangladesh

24 The Bangladesh Chronic Poverty Study Design: Three separate longitudinal surveys that were merged in 2006 ( ) Sampling: 1,700 households in 100 rural communities Environmental data sources: Household reports of flooding and crop failure Aggregated to the subdistrict level Satellite-derived measures of rainfall Analysis: Same approach as for Ethiopia

25 Propensities of migration and shocks Annual rainfall / median rainfall 14% 120% 12% 100% 10% 8% 6% 4% Migration Flooding Crop failures Rainfall 80% 60% 40% 2% 20% 0% 0% Year

26 Bangladesh: Results Flooding had weak and non-significant effects on mobility. Crop failures increased mobility at the county level but decreased mobility at the household level. Poor households were not more vulnerable.

27 Ecuador

28 Ecuador: Data Collection Design: Retrospective survey in 2008 Sampling: Multi-stage cluster sample 850 households in 105 rural communities Questionnaires: Individual, household and community histories Environmental data sources: Historical climate data (WorldClim) Monthly rainfall data (INAMHI) Self-reported land quality (household survey)

29 Historical mean rainfall Within-year seasonality Yearly rainfall Land quality score

30 Ecuador: Analysis Dataset: Person-year dataset on 1670 individuals at risk of migration Outcome: Local/internal/international migration, reference = no migration Predictors: Demographic characteristics, household assets, migrant networks, and environmental factors Model: Discrete-time multinomial event history analysis with canton and year controls

31 Ecuador: Results Local and international migration increased with drought. Internal migration peaked at medium-high rainfall. Poor households were most vulnerable.

32 Other studies Burkina Faso: Rural-rural migration increased during drought but international migration decreased (Henry et al 2003). El Salvador: International migration declined with earthquake damage (Halliday 2004). Indonesia: Mobility increased with tsunami damage, but mostly short-term and shortdistance (Gray et al. under review). More: Nigeria, Mexico, Ecuador, Kenya, Nepal

33 Conclusions Adverse environmental conditions tend to increase rural out-migration, but can also create barriers to migration. Contextually dependent Dire predictions of millions of displaced climate refugees are probably not realistic, except under worst-case scenarios. Applying methods from one area to another can provide important insights.

Implementation of the FDES 2013 and the Environment Statistics Self-Assessment Tool (ESSAT)

Implementation of the FDES 2013 and the Environment Statistics Self-Assessment Tool (ESSAT) 6. Protection, Management and Engagement 2. Resources and their Use 5. Human Settlements and Health 1. Conditions