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Essays in applied econometrics

University of British Columbia

Chapter 1 develops an empirical two-sided matching model with endogenous pre-investment. The model can be used to measure the impact of frictions in labour markets using a single cross-section of matched employer-employee data. The observed matching of workers to firms is the outcome of a discrete, two-sided matching process where firms with heterogeneous preferences over education sequentially choose workers according to an index correlated with worker preferences over firms. The distribution of education arises in equilibrium from a Bayesian game: workers, knowing the distribution of worker and firm types, invest in education prior to the matching process. I propose an inference procedure combining discrete choice methods with simulation. Counterfactual analysis using Canadian data shows that changes in matching frictions can lead to economically significant equilibrium changes in both inequality and the probability of investing in higher education. These effects are more pronounced when worker and firm attributes are complements in the match surplus function. In many economic settings, agents behave similarly because they share information with one another. Information-sharing relations among agents can be modeled as a network, and the strategic interactions among them as a game on a network. Chapter 2, coauthored with Kyungchul Song and Nathan Canen, develops a tractable empirical model of social interactions where each agent - without seeing the full information network - shares information with their neighbors and best responds to the other players based on simple beliefs about their strategies. We provide conditions on the information networks and beliefs of agents such that their best responses exhibit economically intuitive features and desirable external validity relative to equilibrium models of social interaction. Moreover, the setup admits asymptotic inference without requiring that the researcher observes all the players in the game, nor that the they know precisely the sampling process. Chapter 3 discusses how discrete distributions of unobserved heterogeneity can be identified using information on sample attrition. Although attrition is often seen as a source of selection problems, we argue that it can also be used to solve selection problems - even in the absence of covariates or panel data.

Text

2018-09-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/67126

Economics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/