This dissertation develops a network model of migration. While the importance of ties between family members and friends in migration has been long recognized by anthropologists and sociologists and is increasingly confirmed by econometric studies, few economic models of networks in migration exist. This dissertation introduces a new, flexible tool, agent-based modeling, which it applies to the case of migration between Ecuador and the United States. The agent-based model makes it possible not only to reproduce a wider range of stylized facts for Ecuadorian migration, but also to investigate little-researched phenomena such as clustering and distributions.
The first chapter reviews stylized facts for migration world-wide as well as for the case of Ecuador and the U.S. that serve as a guide to the empirical regularities migration models should explain. It outlines the history of economic thought on migration, and discusses prevalent models of migration and their shortcomings with respect to stylized facts, providing a methodological rationale for using agent-based modeling in economic migration research.
The second chapter develops an artificial economy, in which the population moves between three locations, rural and urban Ecuador, and New York. The decision to migrate is determined within a multinomial logit framework by a range of factors identified in the economic literature of migration, including income differences, overlapping generation elements, and budget and liquidity constraints. However, the key elements in migration decisions are network effects. The simulations generate stable patterns and detailed information on distributions, which reproduce the available data for the geographical population distribution, wealth, debt, and remittances. More innovatively, the model shows the clustering of migrants both at the origin and at the destination that is one of the most pervasive and resilient stylized facts of migration research.
The third chapter applies six remittance theories distilled from the literature to the model. It demonstrates that the various theories fit different aspects of the data, including age-wealth profiles as well as the distribution of the population, and of wealth and remittances. The chapter concludes that a combination of theories is most likely to have the best overall fit to the data.
|Advisor:||Foley, Duncan K.|
|Commitee:||Milberg, Will, Semmler, Willi|
|School:||New School University|
|School Location:||United States -- New York|
|Source:||DAI-A 73/10(E), Dissertation Abstracts International|
|Keywords:||Agent-based model, Complexity, Computational economics, Development, Migration, Remittances|
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