Big Data and Environmental Migration: Can Google Trends Explain Migration Drivers?
Creator
Tromblay, Lilith
Advisor
Hisnanick, John
Abstract
This study analyzes the effect of climate variability on human mobility—specifically how extreme weather conditions impact a person’s intent to migrate. The body of empirical research exploring climate-induced migration has been minimal to date, with the majority of empirical evidence coming from the past five to ten years. This research endeavor is guided by an original methodological approach to studying the climate-migration nexus; employing Google Trends search term data to measure one’s intent to migrate. The intent to migrate index is constructed using principal component analysis to reduce a set of eight migration-specific Google Trends search terms to a single unit of analysis. The climate effects are measured by precipitation and average temperature, in deviations from the mean. The use of climate deviations allows for the interpretation of extreme weather events, while the use of Google Trends search term data allows for a temporally and spatially granular unit of analysis. The results show a significant impact of precipitation on migration, whereby positive effects are seen within both positive and negative deviations from the mean of precipitation and positive deviations from the mean of temperature. These results suggest an association between the intent to migrate index and abnormal weather patterns. The results from the study support the use of Google Trends search terms as a unit of analysis in migration studies, providing a unified data source for the cross-sectional study of global migration patterns. From a policy perspective, the evidence justifies the introduction of climate policy to support immigration and migration policy.
Description
M.P.P.
Permanent Link
http://hdl.handle.net/10822/1062267Date Published
2021Subject
Type
Embargo Lift Date
2022-08-11
Publisher
Georgetown University
Extent
45 leaves
Metadata
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