Publications
Competition in Pricing Algorithms
with
Zach Y. Brown
American Economic Journal: Microeconomics, Vol. 15, No. 2 (2023), 109-56.
[
Working paper |
SSRN |
NBER WP 28860]
Using high-frequency data, we document new facts about pricing behavior by online retailers. Based on these facts, we model firm behavior when firms compete by choosing algorithms. Compared to simultaneous price-setting behavior, even simple (linear) algorithms support higher prices in competitive equilibrium.
Self-Preferencing at Amazon: Evidence from Search Rankings
with
Chiara Farronato and
Andrey Fradkin
AEA Papers and Proceedings, Vol. 113 (2023), 239-43.
[
Working paper |
SSRN |
NBER WP 30894]
We study whether Amazon engages in self-preferencing on its marketplace by favoring its own brands (e.g., Amazon Basics) in search. We find that Amazon branded products are ranked higher in consumer search results than observably similar products.
Recovering Investor Expectations from Demand for Index Funds
with
Mark Egan and
Hanbin Yang
Review of Economic Studies, Vol. 89, No. 5 (2022), 2559-2599.
[
Working paper |
SSRN |
NBER WP 26608]
We propose a revealed-preference approach to estimate investor expectations of stock market returns. We construct a time-varying distribution of beliefs that allows for heterogeneity among investors. Investors have persistent beliefs that reflect past returns, and a large fraction are contrarians.
Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response
with
Samuel Weinstein
Wash. U. Law Review, Vol. 100, No. 1 (2022), 111–174.
[
Working paper |
SSRN]
We explore the implications of the price effects of competitive high-frequency algorithms for competition policy, and we address the potential for antitrust and regulation.
Contract Duration and the Costs of Market Transactions
American Economic Journal: Microeconomics, Vol. 14, No. 3 (2022), 164-212.
[
Working paper |
SSRN]
I describe a fundamental tradeoff in buyer-seller transactions: shorter contracts select more efficient sellers, but longer contracts avoid additional transaction costs. I provide an empirical model to account for this tradeoff and to estimate transaction costs, which are often unobserved.
The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation
with
Tatyana Deryugina and
Julian Reif
American Economic Journal: Applied Economics, Vol. 12, No. 1 (2020), 86–114.
[
Working paper |
SSRN |
NBER WP 23483]
Using a natural experiment and a dynamic model, we estimate large differences between the short-run and the long-run demand elasticities for electricity. These dynamics have important market implications, as they affect investment in new generation and the response to a carbon tax.
Challenges for Empirical Research on RPM
with David Aron Smith
Review of Industrial Organization, Vol. 50, No. 2 (2017), 209–220.
We show that the quantity test that was suggested by Posner (1977; 1981) does not identify the change to welfare when demand-enhancing effects are considered generally. We outline other challenges and potential solutions to evaluating the effects of resale price maintenance (RPM).
Bias in Reduced-Form Estimates of Pass-Through
with
Nathan H. Miller,
Marc Remer,
and
Gloria Sheu
Economics Letters, Vol. 123, No. 2 (2014), 200–202.
[
Working paper]
We show that a reduced-form regression of price on costs - the usual approach to estimating pass-through - may not provide a consistent estimate even when cost is a valid instrument. We provide a formal approximation to the bias and the additional conditions needed for consistency.