The Value of Time: Evidence from Auctioned Cab Rides

We recover valuations of time using detailed data from a large ride-hail platform, where drivers bid on trips and consumers choose between a set of rides with different prices and waiting times. We estimate demand as a function of prices and waiting times and find that price elasticities are substantially 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. We find that the value of time during non-work hours is 16% lower than during work hours. Most of the heterogeneity in the value of time, however, is explained by individual differences. We apply our estimates to study optimal time incentives in highway procurement. Standard industry practices, which set incentives based on a uniform value of time, lead to mis-priced time costs by up to ninety percent.

[1]  Nicholas Buchholz,et al.  Spatial Equilibrium, Search Frictions, and Dynamic Efficiency in the Taxi Industry , 2021, The Review of Economic Studies.

[2]  Vasiliki Skreta,et al.  Purchase History and Product Personalization , 2021, EC.

[3]  Gabriel E. Kreindler,et al.  Measuring Commuting and Economic Activity inside Cities with Cell Phone Records , 2021, Review of Economics and Statistics.

[4]  J. List,et al.  The Value of Time in the United States: Estimates from Nationwide Natural Field Experiments , 2020, SSRN Electronic Journal.

[5]  J. Castillo,et al.  Who Benefits from Surge Pricing? , 2020 .

[6]  Myrto Kalouptsidi,et al.  Search Frictions and Efficiency in Decentralized Transport Markets , 2020, The Quarterly Journal of Economics.

[7]  A. Bento,et al.  Avoiding Traffic Congestion Externalities? The Value of Urgency , 2020, SSRN Electronic Journal.

[8]  Yeon-Koo Che,et al.  The Effect of Privacy Regulation on the Data Industry: Empirical Evidence from Gdpr , 2020 .

[9]  Gregory Lewis,et al.  Voluntary Disclosure and Personalized Pricing , 2019, EC.

[10]  Yichen Su.  The Rising Value of Time and the Origin of Urban Gentrification , 2019, Federal Reserve Bank of Dallas, Working Papers.

[11]  S. Misra,et al.  Personalized Pricing and Customer Welfare , 2019 .

[12]  Erik Hurst,et al.  Income Growth and the Distributional Effects of Urban Spatial Sorting , 2019, SSRN Electronic Journal.

[13]  Chenyu Yang,et al.  The Efficiency of A Dynamic Decentralized Two-Sided Matching Market , 2019, SSRN Electronic Journal.

[14]  Costas Arkolakis,et al.  The Welfare Effects of Transportation Infrastructure Improvements , 2019 .

[15]  Q. Vuong,et al.  Structural Analysis of Nonlinear Pricing , 2018, Journal of Political Economy.

[16]  Raj Chetty,et al.  The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility , 2018 .

[17]  G. Duranton,et al.  Speed , 2018, Review of Economics and Statistics.

[18]  S. Redding,et al.  The Making of the Modern Metropolis: Evidence from London , 2018 .

[19]  Myrto Kalouptsidi,et al.  Geography, Search Frictions and Endogenous Trade Costs , 2017 .

[20]  Peter E. Rossi,et al.  The Value of Flexible Work: Evidence from Uber Drivers , 2017, Journal of Political Economy.

[21]  Pablo D. Fajgelbaum,et al.  Optimal Transport Networks in Spatial Equilibrium , 2017, Econometrica.

[22]  Steven D. Levitt,et al.  Using Big Data to Estimate Consumer Surplus: The Case of Uber , 2016 .

[23]  L. Engelson,et al.  The cost of travel time variability: three measures with properties , 2016 .

[24]  Alexandre Mas,et al.  Valuing Alternative Work Arrangements , 2016 .

[25]  John A. List,et al.  Quantity discounts on a virtual good: The results of a massive pricing experiment at King Digital Entertainment , 2016, Proceedings of the National Academy of Sciences.

[26]  Florian Heiss,et al.  Discrete Choice Methods with Simulation , 2016 .

[27]  Alessandro Lizzeri,et al.  Frictions in a Competitive, Regulated Market: Evidence from Taxis , 2015, American Economic Review.

[28]  Jonathan D. Hall.  Pareto Improvements from Lexus Lanes: The effects of pricing a portion of the lanes on congested highways , 2015 .

[29]  Iain Dunning,et al.  JuMP: A Modeling Language for Mathematical Optimization , 2015, SIAM Rev..

[30]  Aviv Nevo,et al.  Usage-Based Pricing and Demand for Residential Broadband , 2015 .

[31]  M. Eichenbaum,et al.  The Elasticity of Substitution between Time and Market Goods: Evidence from the Great Recession , 2015, International Economic Review.

[32]  Jeroen M. Swinkels,et al.  On the analysis of asymmetric first price auctions , 2014, J. Econ. Theory.

[33]  Benjamin Shiller.  First Degree Price Discrimination Using Big Data , 2013 .

[34]  Benjamin A. Brooks,et al.  The Limits of Price Discrimination , 2013 .

[35]  Nicholas Bloom,et al.  Does Working from Home Work? Evidence from a Chinese Experiment , 2013 .

[36]  Kenneth A. Small,et al.  Valuation of Travel Time , 2012 .

[37]  Mark Aguiar,et al.  Recent Developments in the Economics of Time Use , 2012 .

[38]  Maria Börjesson,et al.  On the income elasticity of the value of travel time , 2012 .

[39]  I. Hendel,et al.  Intertemporal Price Discrimination in Storable Goods Markets , 2011 .

[40]  Ali Hortaçsu,et al.  Mechanism Choice and Strategic Bidding in Divisible Good Auctions: An Empirical Analysis of the Turkish Treasury Auction Market , 2010, Journal of Political Economy.

[41]  Juanjuan Meng,et al.  research platform to scholars worldwide. New York City Cabdrivers ’ Labor Supply Revisited: Reference-Dependent Preferences with Rational-Expectations Targets for Hours and Income , 2008 .

[42]  K. Train,et al.  A Control Function Approach to Endogeneity in Consumer Choice Models , 2010 .

[43]  Simon Cowan,et al.  Monopoly Price Discrimination and Demand Curvature , 2009 .

[44]  J. Henderson,et al.  Measuring Economic Growth from Outer Space , 2009, The American economic review.

[45]  Gregory Lewis,et al.  Procurement Contracting with Time Incentives: Theory and Evidence , 2009 .

[46]  Sergio R. Jara-Díaz,et al.  Estimating the value of leisure from a time allocation model , 2008 .

[47]  H. Farber.  Reference-Dependent Preferences and Labor Supply: The Case of New York City Taxi Drivers , 2008 .

[48]  Erik T. Verhoef,et al.  Value of Time by Time of Day: A Stated-Preference Study , 2007 .

[49]  Peter E. Rossi,et al.  Bayesian Statistics and Marketing , 2005 .

[50]  Mark Aguiar,et al.  Lifecycle Prices and Production , 2005 .

[51]  Henry S. Farber,et al.  Is Tomorrow Another Day? The Labor Supply of New York City Cabdrivers , 2005, Journal of Political Economy.

[52]  Kay W. Axhausen,et al.  Evidence on the distribution of values of travel time savings from a six-week diary , 2004 .

[53]  J. List.  The nature and extent of discrimination in the marketplace: Evidence from the field , 2004 .

[54]  D. Schrank,et al.  2012 Urban Mobility Report , 2002 .

[55]  Martin Pesendorfer,et al.  Estimation of a Dynamic Auction Game , 2001 .

[56]  Q. Vuong,et al.  Optimal Nonparametric Estimation of First-price Auctions , 2000 .

[57]  R. Thaler,et al.  Labor Supply of New York City Cabdrivers: One Day at a Time , 1997 .

[58]  Peter E. Rossi,et al.  The Value of Purchase History Data in Target Marketing , 1996 .

[59]  Eugenio J. Miravete.  Screening consumers through alternative pricing mechanisms , 1996 .

[60]  J. Waldfogel,et al.  The Selection Hypothesis and the Relationship between Trial and Plaintiff Victory , 1993, Journal of Political Economy.

[61]  T. Miller.  The Value of Time and the Benefit of Time Saving: A Literature Synthesis and Recommendations on Values , 1989 .

[62]  C. N. Morris,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[63]  D. McFadden,et al.  URBAN TRAVEL DEMAND - A BEHAVIORAL ANALYSIS , 1977 .

[64]  D. McFadden.  MEASUREMENT OF URBAN TRAVEL DEMAND , 1974 .

[65]  G. Becker.  Chapter Title: a Theory of Marriage a Theory of Marriage , 2022 .

[66]  S. Vasserman,et al.  Online Appendix for Scaling Auctions as Insurance: A Case Study in Infrastructure Procurement , 2023, SSRN Electronic Journal.

[67]  Milena Almagro,et al.  Location Sorting and Endogenous Amenities: Evidence from Amsterdam , 2024, SSRN Electronic Journal.

[68]  Renata Gaineddenova.  Pricing and Efficiency in a Decentralized Ride-Hailing Platform* , 2021 .

[69]  Nicola Rosaia.  Competing Platforms and Transport Equilibrium: Evidence from New York City , 2020 .

[70]  Will Dobbie,et al.  Pricing Efficiently in Designed Markets: The Case of Ride-Sharing∗ , 2019 .

[71]  J. Eeckhout,et al.  Assortative Matching With Large Firms , 2018 .

[72]  P. Kehoe,et al.  Dynamic Competition in the Era of Big Data , 2018 .

[73]  Gabriel E. Kreindler,et al.  The Welfare Effect of Road Congestion Pricing : Experimental Evidence and Equilibrium Implications ∗ , 2017 .

[74]  Christoph Bauner.  Mechanism choice and the buy-it-now auction: A structural model of competing buyers and sellers , 2015 .

[75]  P. Chiappori,et al.  A Theory of the Allocation of Time " , 2014 .

[76]  Mark Wardman,et al.  Meta-analysis of UK values of travel time: An update , 2011 .

[77]  M. Fosgerau,et al.  The Danish Value of Time Study , 2008 .

[78]  Lones Smith,et al.  Assortative Matching and Search , 2000 .

[79]  A. Palma,et al.  A STRUCTURAL MODEL OF PEAK-PERIOD CONGESTION: A TRAFFIC BOTTLENECK WITH ELASTIC DEMAND. IN: RECENT DEVELOPMENTS IN TRANSPORT ECONOMICS , 1993 .

[80]  Kenneth A. Small,et al.  THE SCHEDULING OF CONSUMER ACTIVITIES: WORK TRIPS , 1982 .

[81]  W. Vickrey.  Congestion Theory and Transport Investment , 1969 .