Research

Working Papers

1. Input-Price Responses to Horizontal Mergers and the Bargaining-Leverage Defense (with Todd Lensman), Sep 2022 [Paper]
   Abstract

   We study the implications of endogenous input prices for horizontal merger policy when input prices are set before goods prices. Generalizing the first-order approach of Farrell and Shapiro (2010) and Jaffe and Weyl (2013), we derive a measure of unilateral incentives to adjust input prices after a downstream merger, Input Pricing Pressure. We use this measure to show that mergers often incentivize higher input prices, and that these incentives hinge on changes in downstream pass-through rates and marginal cost efficiencies generated by the merger. By implication, consumer surplus-maximizing antitrust policy may be too lax when input prices are assumed fixed, and it should be biased against claims that input prices will fall after a downstream merger. In an empirical application to local retail beer markets, endogenizing input prices substantially raises the consumer harm from mergers of retailers.
2. Market Power Spillovers Across Airline Routes (with Roi Orzach), Jan 2023 [Paper]
   Abstract

   Airlines often route connecting passengers through hubs. Despite the prevalence of connecting service, research analyzing the welfare effects of changes in competition focuses on nonstop routes. We show that when firms face capacity constraints or adjustment costs, a price decrease on a direct route may incentivize firms to decrease prices on indirect routes using this route as a leg. We call this relationship pass-through and document positive pass-through after entry by low-cost carriers and mergers. We show that ignoring these effects results in underestimating the consumer surplus effects of changes in competition between 9 and 115% across different competition shocks.

Resting Papers

1. Myopia in Dynamic Spatial Games (with Shane Auerbach), May 2019 [Paper - WSC Version - Slides]
   Abstract

   We design an experiment to evaluate behavior in a dynamic spatial game representing the incentives faced by drivers for a ride-sharing service while waiting to be matched with a rider. The design is unique in that it allows us to observe not only participants’ choices, but also the considerations that went into those choices. The results of the experiment show that a large majority of player choices are consistent with myopic best responding. A myopic best response maximizes a player’s flow payoff at the time of the decision but is not necessarily optimal as it ignores strategic considerations regarding the future choices of opponents. Given the observed prevalence of this behavior and the challenges of equilibrium analysis, which we detail, we argue in favor of computational models of spatial competition built upon myopic agents. Myopic behavior in our model results in quite efficient outcomes, suggesting that ride-sharing companies may benefit from sharing with drivers the locations of other nearby drivers to allow them to compete spatially.
2. A Neighborhood Search Heuristic for the p-Median Problem with Continuous Demand (with Shane Auerbach), May 2019 [Paper - Slides]
   Abstract

   Computing optimal spatial allocations is important for two reasons. First, one may wish to implement them. Second, without a sense of an optimal spatial allocation, one cannot evaluate the efficiency of an observed spatial allocation. Suppose you have p facilities and wish to place them in a city to minimize the average distance between a consumer and her nearest facility. We develop a neighborhood search heuristic for this p-median problem with continuous demand. We discuss challenges to implementing the heuristic, propose solutions, and describe how it can be embedded in hybrid heuristics. We then apply the heuristic to computing optimal spatial allocations of facilities in Chicago, Atlanta, and Los Angeles. In comparing these optimal allocations to the actual ones, we find that allocations of supermarkets do relatively poorly in minimizing transportation costs for consumers.