MIT Deparatment of Economics
77 Massachusetts Avenue, E52-404
Cambridge, MA 02139
NBER Program Affiliations:
NBER Affiliation: Faculty Research Fellow
Institutional Affiliation: Massachusetts Institute of Technology
NBER Working Papers and Publications
|May 2020||The Value of Time: Evidence From Auctioned Cab Rides|
with Nicholas Buchholz, Laura Doval, Jakub Kastl, Filip Matějka: w27087
We estimate valuations of time using detailed consumer choice data from a large European ride hail platform, where drivers bid on trips and consumers choose between a set of potential rides with different prices and waiting times. We estimate consumer demand as a function of prices and waiting times. While demand is responsive to both, price elasticities are on average four times higher than waiting-time elasticities. We show how these estimates can be mapped into values of time that vary by place, person, and time of day. Regarding variation within a day, the value of time during non-work hours is 16% lower than during work hours. Regarding the spatial dimension, our value of time measures are highly correlated both with real estate prices and urban GPS travel flows. A variance decomposit...
|March 2020||The Economic Consequences of Data Privacy Regulation: Empirical Evidence from GDPR|
with Guy Aridor, Yeon-Koo Che: w26900
This paper studies the effects of the EU’s General Data Protection Regulation (GDPR) on the ability of firms to collect consumer data, identify consumers over time, accrue revenue via online advertising, and predict their behavior. Utilizing a novel dataset by an intermediary that spans much of the online travel industry, we perform a difference-in-differences analysis that exploits the geographic reach of GDPR. We find a 12.5% drop in the intermediary-observed consumers as a result of the new opt-in requirement of GDPR. At the same time, the remaining consumers are observable for a longer period of time. We provide evidence that this pattern is consistent with the hypothesis that privacy-conscious consumers substitute away from less efficient privacy protection (e.g, cookie deletion) to e...
|February 2020||Estimating Dynamic Games of Oligopolistic Competition: An Experimental Investigation|
with Emanuel Vespa: w26765
We evaluate dynamic oligopoly estimators with laboratory data. Using a stylized en-try/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov-perfect equilibrium (MPE) and use the estimates to predict counterfactual behavior. The concern is that if the Markov assumption was violated one would mispredict counterfactual outcomes. The experimental method allows us to compare predicted behavior for counterfactuals to true counterfactuals implemented as treatments. Our main finding is that counterfactual prediction errors due to collusion are in most cases only modest in size.
|August 2018||Frictions in a Competitive, Regulated Market: Evidence from Taxis|
with Guillaume R. Fréchette, Alessandro Lizzeri: w24921
This paper presents a dynamic general equilibrium model of a taxi market. The model is estimated using data from New York City yellow cabs. Two salient features by which most taxi markets deviate from the efficient market ideal are, first, matching frictions created by the need for both market sides to physically search for trading partners, and second, regulatory limitations to entry. To assess the importance of these features, we use the model to simulate the effect of changes in entry, alternative matching technologies, and different market density. We use the geographical features of the matching process to back out unobserved demand through a matching simulation. This function exhibits increasing returns to scale, which is important to understand the impact of changes in this market a...
Published: Guillaume R. Fréchette & Alessandro Lizzeri & Tobias Salz, 2019. "Frictions in a Competitive, Regulated Market: Evidence from Taxis," American Economic Review, vol 109(8), pages 2954-2992. citation courtesy of