Working Papers
“Markups and Costs under Capacity Constraints: the Welfare Effects of Hotel Mergers,” Job Market Paper [link].
Hotel chain mergers increase markups through market concentration, but also stand to decrease average costs through added efficiencies. The pass-through of these cost reductions to consumers - versus rising markups - leads to ambiguous welfare effects. This paper constructs an equilibrium model of the U.S. hospitality sector, incorporating a flexible model of costs which captures firm capacity constraints. I show that firms with larger hotel portfolios face lower average costs and softer capacity constraints when approaching full occupancy. In hypothetical merger scenarios, I provide evidence for when efficiencies result in pro-competitive effects. A merger of large chains decreases average costs for merging firms (-12.7%) but harms consumer surplus (-2.0%), while the acquisition of an independent hotel modestly decreases average costs (-2.8%) while raising consumer surplus (0.1%) as efficiencies are passed through.
“Triplet Embeddings for Demand Estimation” with Lorenzo Magnolfi and Alan Sorensen. Conditionally accepted at American Economic Journal: Microeconomics. Available at [SSRN].
We propose a method to augment conventional demand estimation approaches with crowd-sourced data on the product space. Our method obtains triplets data ("product A is closer to B than it is to C") from an online survey to compute an embedding---i.e., a low-dimensional representation of the latent product space. The embedding can either (i) replace data on observed characteristics in mixed logit models, or (ii) provide pairwise product distances to discipline cross-elasticities in log-linear models. We illustrate both approaches by estimating demand for ready-to-eat cereals; the information contained in the embedding leads to more plausible substitution patterns and better fit.
Research in Progress
“Using Online Recommendation Data for Differentiated Product Demand Estimation.”
Online recommendation platforms aid consumers in making decisions amidst large choice sets by suggesting commonly-chosen alternatives to a given product. I treat these recommendations as ordinal rankings of conditional choice probabilities observed by the platforms. Using collected data on recommendations for hotels, I construct an embedding of the latent utility space for the mean consumer. I combine these data with aggregate price and quantity data and estimate typical distance-based linear and mixed logit demand models, and show that I can recover substitution patterns in the absence of observed characteristics.
“Demand and Competition in the Market for Mobile Apps” with Lorenzo Magnolfi and Alan Sorensen.
The flourishing market for mobile apps has been fertile ground for mergers and acquisitions, and some notable acquisitions have attracted antitrust attention for being cases where the target was a potential competitor of the acquirer. This paper develops and estimates a demand model for mobile apps---where the relevant consumer choice is time rather than money---in order to measure the degree of substitutability between a given pair of apps. We position apps in a latent product space using an embedding derived from surveyed product comparisons. From the estimated substitution patterns, we investigate how many of the 140+ mobile app acquisitions since 2008 were of close substitutes to the acquirer.
Other Publications
“Workplace Bans On Sugar-Sweetened Beverages.” Health Affairs, 40(3), p. 543. 2021. https://doi.org/10.1377/hlthaff.2020.02362
“Dragons, Giants, Elephants and Mice: Evolution of the MFN Free Rider Problem in the WTO Era” with Rodney Ludema and Anna Maria Mayda. CEPR Discussion Papers 10961, C.E.P.R. Discussion Papers. 2015. Available at [SSRN].