Using Big Data to Estimate Consumer Surplus: The Case of Uber / Peter Cohen, Robert Hahn, Jonathan Hall, Steven Levitt, Robert Metcalfe.

Format:

Book

Author/Creator:

Cohen, Peter.

Contributor:

National Bureau of Economic Research.

Hahn, Robert.

Hall, Jonathan.

Levitt, Steven.

Metcalfe, Robert.

Series:

Working Paper Series (National Bureau of Economic Research) no. w22627.

NBER working paper series no. w22627

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Other Title:

Using Big Data to Estimate Consumer Surplus

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2016.

Summary:

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.

Notes:

Print version record

September 2016.