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Using Big Data to Estimate Consumer Surplus: The Case of Uber

Author

Listed:
  • Peter Cohen
  • Robert Hahn
  • Jonathan Hall
  • Steven Levitt
  • Robert Metcalfe

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.

Suggested Citation

  • Peter Cohen & Robert Hahn & Jonathan Hall & Steven Levitt & Robert Metcalfe, 2016. "Using Big Data to Estimate Consumer Surplus: The Case of Uber," NBER Working Papers 22627, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:22627
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • H0 - Public Economics - - General
    • J0 - Labor and Demographic Economics - - General
    • L0 - Industrial Organization - - General

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