International Migration and Weather Disasters: Econometric Modeling vs. Bayesian Network Analysis

International Migration and Weather Disasters: Econometric Modeling vs. Bayesian Network Analysis

To be presented at the 2024 BayesiaLab Conference in Cincinnati on April 12, 2024.


Although in multiple episodes, Weather Disasters (WDs) are found to be potentially important factors promoting migration between countries and regions, it is unclear if their role is systematic or idiosyncratic. This issue is of great public attention and importance since the severity, frequency, and coverage of WDs are expected to grow as climate change progresses under business as usual. Recent studies suggest that large migration flows may be associated with violence, economic and demographic factors in the countries of origin while paying less attention to the effect of socio-economic conditions in the destination countries. Our research has twofold objectives. First, this study develops a Bayesian Network Analytic (BNA) framework that anticipates the potential for varied migration responses to WDs across countries and over time, and examines policy levers that might alter these responses, the complex interaction between different factors, and overcomes some limitations of econometric models routinely used in modeling of international migration. The network structure is learned from data for migration flows between 190 origins and 190 destinations from 1980 to 2009. Secondly, we compare and discuss the advantages, disadvantages, and results of both BNA and conventional econometric modeling, which were previously done on the same data.

About the Presenter

Alexander Alexeev earned a Ph.D. in Public Affairs from Indiana University in 2010, with specializations in policy analysis and business economics. He also holds a Ph.D. in Physics from Odessa National University (Ukraine, 1996). Starting in 1997, Alexander taught physics, modeling, and radioecology for the Department of Physics at Odessa Hydrometeorological Institute. In 2001, he came to the United States to study environmental management and stayed for doctoral study. Since 2017, Alexeev has been a lecturer at Indiana University, teaching data analysis and statistical modeling courses. His interdisciplinary research interests include quantitative policy analysis, risk and security modeling, and decision-making.

Alexander Alexeev, Ph.D.

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