Leon Zhang
Job Market Candidate

Stanford University
Department of Economics
579 Jane Stanford Way
Stanford, CA 94305
203-927-7071
leonz@stanford.edu

Curriculum Vitae

Fields:
Industrial Organization, Econometrics
Expected Graduation Date:
June, 2020

Thesis Committee:
Frank Wolak (Primary):
wolak@stanford.edu

Han Hong:
doubleh@stanford.edu

Brad Larsen:
bjlarsen@stanford.edu

Research

What Happens When The Big-Box Store Leaves Town? (Job Market Paper)
Abstract Over the past few decades, big-box chains have grown rapidly in sectors such as discount retail, home improvement, groceries, and electronics. Due to their size, local consumers and businesses alike tend to be significantly impacted when these big-box chains open or close a store. In this paper, I study the effect of a big-box chain, which competes in discount retail and groceries, closing several stores in early 2016. I find significant increases in grocery spending after the stores closed, with spending in other categories decreasing. I also find that mom-and-pop stores had overall increased revenue, although this effect was not significant until a year after the closings.

On the Empirical Relevance of Myerson's Neutral Bargaining Solution (with Brad Larsen)
This study compares a real-world bilateral bargaining game to a theoretically "fair" or "neutral" bargaining solution proposed by Myerson (1984). The neutral bargaining solution generalizes the Nash bargaining solution to incomplete information settings. We implement an algorithm for computing a neutral bargaining solution given estimates of buyer and seller valuation distributions. We then apply this procedure using estimates of buyer and seller valuation distribution from data on dealer-to-dealer bargaining over used cars. We find that the real-world bargaining outcomes differ starkly from those in the neutral bargaining solution, suggesting that real-world bargaining falls short of achieving "fairness" or "neutrality" in the Myerson sense.

Recovering Equilibrium Mechanisms in Two Player Entry Games
Estimation of static and discrete entry games is important for understanding economic markets such as prescription drug markets, airline markets, and big-box retailers, which are characterized by oligopolistic competition. A common problem in estimating these models is multiplicity of equilibria, where one entrant is predicted, but it is not known which one. Bresnahan and Reiss (1991) developed an influential methodology that obtains point estimates of entry parameters without assuming one particular entry selection mechanism. I extend their methodology by deriving a procedure that uses conditional entry probabilities to recover features of the equilibrium selection mechanism. This enables researchers to perform counterfactuals on models estimated using Bresnahan and Reiss' method.