Roman Zakharenko |
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Placement Director: Vijay Krishna
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Graduate Secretary & Placement Assistant: Lynn Sebulsky (814)865-1458 lms50@psu.edu |
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Curriculum Vitae |
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THESIS ABSTRACT Essay 1. Migration, Learning, and DevelopmentUS-educated Indian engineers played a major role in the establishment of the "Silicon Valley of Asia" in Bangalore. The experience of India and other countries shows that returning well-educated emigrants, despite their small numbers, can make a difference. This paper builds a model of "local" knowledge spillovers, in which migration of a small number of highly skilled individuals greatly affects country-level human capital accumulation. All economic activity occurs in pairs of individuals randomly matched to each other. Each pair produces the consumption good; the skills of the two partners are complementary. At the same time, the less skilled partner increases human capital by learning from the more skilled colleague. In the presence of search frictions, highly skilled individuals may have an incentive to leave poor home countries because they expect a better match abroad, thus the home country loses its best teachers. On the contrary, improved institutions may foster return migration of the highly skilled. These return migrants greatly amplify the positive effect of better institutions. The model is calibrated and solved numerically.
Essay 2: Estimating return migration flows In the recent years, researchers have constructed large global datasets which measure the numbers of immigrants by country of birth, by education, and by country of residence. Yet, little is known about cross-country patterns of return migration: who are the returnees and how do they change while living abroad? This paper estimates how many foreign-born individuals emigrate from the United States, and how much education they acquire while in the US. The estimates are made by comparing large cross-section datasets collected at different dates. I also estimate how many of these emigrants return to their country of birth, by using data collected in their home countries.
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