Using Big Data to Estimate Consumer Surplus: The Case of Uber
Steven Levitt () and
Robert Metcalfe ()
No 22627, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: H0 J0 L0 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mkt, nep-pay, nep-sog and nep-tre
Note: IO LS PE
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:22627
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().