Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/170233
Title: STUDYING IMMIGRATION PATTERNS OF MEXICANS INTO THE U.S. USING A NESTED LOGIT MODEL.
Authors: GUO JIA
Keywords: International migration
migrant networks
wage differentials
Issue Date: 13-Apr-2020
Citation: GUO JIA (2020-04-13). STUDYING IMMIGRATION PATTERNS OF MEXICANS INTO THE U.S. USING A NESTED LOGIT MODEL.. ScholarBank@NUS Repository.
Abstract: Mexican immigration to the United States has been a constant and evolving issue in U.S. politics. With an interest in the effects of individual characteristics, this paper applies a state-of-the-art discrete-choice model to study the patterns of Mexican migration to the United States. Using individual-level data from Princeton University’s Mexican Migration Project, the model consists of two stages. First, a Mincer wage regression is used to predict an individual’s counterfactual wages in locations other than their choice. Next, migration choice and choice of region in the U.S. are regressed against the predicted wages and individual characteristics using a nested logit model. Special attention is paid to the prior migration of other family members, which can be taken as a proxy for familial networks. The results show a neutral selection of education level into migration and a positive effect of past household migration experience on the probability of location choice, amongst other findings.
URI: https://scholarbank.nus.edu.sg/handle/10635/170233
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