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Population and Environment
Published in: Population and Environment 3/2020

13-12-2019 | Original Paper

Spatial and temporal dimensions of weather shocks and migration in Nepal

Authors: Nathalie E. Williams, Clark Gray

Published in: Population and Environment | Issue 3/2020

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Abstract

Research shows that environmental shocks can influence migration. However, studies vary widely in the shocks and type of migration measured, the context, and the strength and direction of environmental effects. In addition, existing theories provide opposing predictions for this relationship. There is a clear need for further theoretical development in the climate-migration literature. This study, in rural Nepal, examines four types of weather shocks, over various time frames, on four types of migration. Results suggest that the most substantial influence of weather shocks is not in a wholesale increase or decrease in migration. Instead, weather shocks are related to changes in the type of migration used, resulting in less long-term and more short-term migrations in the population. We use the ready-willing-and-able perspective to make sense of these patterns.
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Appendix
Available only for authorised users
Footnotes
1
In some places, there are social and normative restrictions on women’s migration. In these cases, women’s and men’s migration might be analyzed separately.
 
2
This discussion is intended as a general theoretical treatment of how RWA might help us to think about the relationship between weather shocks and migration. The empirical reality of the weather-migration relationship is undoubtedly more complex. For example, Riosmena et al. (2018) find that climate shocks in Mexico reduced migration in general, but increased migration for those with the lowest vulnerability. Indeed, the RWA framework is ideal for helping to interpret those results. In the empirical portion of this study, we also interact household wealth with weather shocks. Regardless, the reader should approach this section as a general discussion of what might happen on average.
 
3
There was a protocol change in data collection in February 2000 that affected how migration was recorded. This results in an inordinately high migration rate for that 1 month, after which records of migration resume more usual rates. For this reason, we delete February 2000 from our data analysis, so that all our data are collected under the same system are comparable across months.
 
4
We also tested models where short- and long-term migrations were defined by 6-month, 9-month, and 15-month durations. Results, which are presented in the supplementary material, are substantively equivalent to those we present here.
 
5
We choose July as the reference because it is the height of the monsoon and rice season.
 
6
We also tested models with a dichotomous outcome of any migration (including short- and long-term and close and far distance) or no migration. Results (not shown here) for linear and quadratic specifications of weather shocks (linear, quadratic, and threshold measures) are not statistically significant (to p < 0.05), indicating that there is no evidence that weather changes influence overall likelihoods of migration.
 
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Metadata
Title
Spatial and temporal dimensions of weather shocks and migration in Nepal
Authors
Nathalie E. Williams
Clark Gray
Publication date
13-12-2019
Publisher
Springer Netherlands
Published in
Population and Environment / Issue 3/2020
Print ISSN: 0199-0039
Electronic ISSN: 1573-7810
DOI
https://doi.org/10.1007/s11111-019-00334-5

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