Using Big Data to Estimate Consumer Surplus: The Case of Uber
By Peter Cohen (Uber Technologies Inc.), Robert W. Hahn (University of Oxford), Jonathan Hall (Uber Technologies Inc.), Steven D. Levitt (University of Chicago) & Robert D. Metcalfe (University of Chicago)
Abstract: Estimating consumer surplus is challenging because it requires identification of the entire demand curve. We rely on Uber’s “surge” pricing algorithm and the richness of its individual level data to first estimate demand elasticities at several points along the demand curve. We then use these elasticity estimates to estimate consumer surplus. Using almost 50 million individual-level observations and a regression discontinuity design, we estimate that in 2015 the UberX service generated about $2.9 billion in consumer surplus in the four U.S. cities included in our analysis. For each dollar spent by consumers, about $1.60 of consumer surplus is generated. Back-of-the-envelope calculations suggest that the overall consumer surplus generated by the UberX service in the United States in 2015 was $6.8 billion.
Full Article: Social Science Research Network