Mobility and the Return to Education: Testing a Roy Model with Multiple Markets
迁移与教育回报:多市场 Roy 模型的检验AI 解读 ↓
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AI 根据所提供的论文材料归类:摘要以多个居住与工作地点构成离散选择,并建立收入与迁移的 Roy 结构模型及选择校正方法,对应离散选择和结构估计。
迁移与教育回报:多市场 Roy 模型的检验AI 解读 ↓
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Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile.To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work.Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process.This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993).The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems.The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions.The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets.While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states.Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college-versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.
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