Tepper School of Business
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213
Institutional Affiliation: Carnegie Mellon University
NBER Working Papers and Publications
|September 2019||Optimal Ratings and Market Outcomes|
with Hugo Hopenhayn: w26221
This paper considers the design of an optimal rating system, in a market with adverse selection. We address two critical questions about rating design: First, given a number of categories, what are the criteria for setting the boundaries between them? Second, what are the gains from increasing the number of categories? A rating system helps reallocate sales from lower- to higher-quality producers, thus mitigating the problem of adverse selection. We focus on two main sources of market heterogeneity that determine the extent and effect of this reallocation: the distribution of firm qualities and the responsiveness of sellers' supply to prices. We provide a simple characterization for the optimal rating system as the solution to a standard k-means clustering problem, and discuss its connecti...
|August 2018||Certification, Reputation and Entry: An Empirical Analysis|
with Xiang Hui, Giancarlo Spagnolo, Steven Tadelis: w24916
Markets with asymmetric information will often employ third-party certification labels to distinguish between higher and lower quality transactions, yet little is known about the effects of certification policies on the evolution of markets. How does the stringency in quality certification affect the intensity and composition of entry, incumbents' reactions, and market outcomes? We use detailed administrative data and exploit a policy change on eBay to explore how a more selective certification policy affects entry and behavior across a rich set of online market segments. We find that after the policy change, entry increases and does so more intensely in markets where it is harder to become certified. The average quality of entrants also increases more in the more affected markets, while t...
|October 2016||Bidding Dynamics in Auctions|
with Hugo Hopenhayn: w22716
This paper studies bidding dynamics where values and bidding opportunities follow an unrestricted joint Markov process, independent across agents. Bids cannot be retracted, as is frequently the case in auctions. Our main methodological contribution is that we construct a mapping from this general stochastic process into a distribution of values that is independent of the type of auction considered. The equilibria of a static auction with this distribution of values is used to characterize the equilibria of the dynamic auction, making this general class very tractable. As a result of the option of future rebidding, early bids are shaded and under mild conditions increase toward the end of the auction. Our results are consistent with repeated bidding and skewness of the time distribution of ...