Genaro Basulto
I am a fifth-year PhD student in Economics at the Tepper School of Business, Carnegie Mellon University, where I am increadibly thankful to be advised by Aniko Öry. My research is in industrial organization and applied microeconomics, with a focus on digital markets and competition policy. I study how platform design, ranking algorithms, and vertical integration shape firm behavior, market competition, and consumer welfare. I am on the 2026–27 economics job market.
Retail platforms can tie visibility to sellers' purchase of the platform's vertically integrated complementary services, such as warehousing and delivery. The FTC, European Commission, and Mexico's COFECE are investigating this practice, but its welfare effects remain unquantified. Using a panel of more than 415,000 observations from Amazon and Mercado Libre, Mexico's two largest retail platforms, I estimate a structural model of consumer platform choice, search, seller pricing and delivery choices, and platform ranking. I find that integrated delivery is higher quality than third-party alternatives but up to 84% more expensive, and receives systematically better rankings. Barring platforms from favoring their integrated delivery in rankings reduces its adoption by up to 5.4%, lowers prices by up to 7.7%, and raises total surplus by 4.6%, with Amazon's consumer surplus rising 12.1% against only 2.1% for Mercado Libre. Separating Mercado Libre's delivery service from the platform lowers total surplus by 4.4% and consumer surplus on Amazon by 10.6%, showing that rival-platform competition disciplines self-preferencing even without regulation.
Working Papers & Publications
Working Papers
Platforms as Search Technologies: Seller Selection and Price Spillovers
We study a market in which producers sell their products both through a platform and through a direct channel, and set prices on both channels simultaneously. Off-platform, consumers engage in costly sequential search. The platform improves consumer-seller matching but weakens price competition by concentrating consumer attention. Consumers decide whether to join based on the expected utility gain from improved matching, while sellers decide whether to list based on the incremental profit from platform sales net of diverted off-platform demand. We study platform fee design and then extend the framework to competition between two symmetric platforms, highlighting tensions between participation, pricing, producer surplus, and consumer welfare.
Keynesian Search in Stochastic Overlapping Generations Models
Revise & Resubmit — American Economic Journal: MacroeconomicsWe study how beliefs about future wealth are disciplined in a stochastic overlapping generations economy with incomplete labor markets and Keynesian search in the tradition of Roger Farmer. We show that rational expectations must reproduce the endogenous wealth distribution, disciplining an otherwise indeterminate steady state. We calibrate a 58-period lifecycle economy with dual labor markets and matching-efficiency shocks, solve it using a neural network, and recover equilibrium expectations.
Strategic Pricing and Adoption Dynamics for Hydrogen Mobility Technologies
This paper develops a dynamic model of technology adoption under uncertainty and network effects, focusing on how a hydrogen supplier decides when to enter markets and how to price and design contracts for heterogeneous trucking customers. We calibrate the model using New York Advanced Clean Fleets reporting data and Bizminer industry profiles of New York trucking operators. We use the model to study subsidies for station construction and customer adoption costs and to compare personalized contracts with single-price benchmarks.