Essays On Machine Learning And Labor Economics

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Degree type
Doctor of Philosophy (PhD)
Graduate group
Economics
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Economics
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2022-09-17T20:22:00-07:00
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Xin, Jianhong
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Abstract

Observed worker and firm characteristics only explain a small wage variation. Beyond characteristics that are directly observed from the data, my thesis develops new empirical methods aimed at identifying unobserved heterogeneity in the labor market. Chapter 1 proposes an empirical method to measure the effects of coworkers on wages. I take advantage of the recent cutting-edge clustering method that combines machine-learning and economic theory to identify groups of workers with similar latent productivity type. I further apply the cluster-based method to identify the effects of coworkers on wages and evaluate their economic implications in empirical-relevant simulations. The proposed method has proven potential to be applied to the real-world data to improve our ability to understand the role of coworkers in substantive questions where existing methods have limitations.

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Iourii Manovskii
Date of degree
2022-01-01
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