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Learning by Driving: Productivity Improvements by New York City Taxi Drivers

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  • Kareem Haggag
  • Brian McManus
  • Giovanni Paci

Abstract

We study learning by doing by New York City taxi drivers, who have substantial discretion over their driving strategies and receive compensation closely tied to their success in finding customers. In addition to documenting learning overall by these entrepreneurial agents, we exploit our data's breadth to investigate the factors that contribute to driver improvement across a variety of situations. New drivers lag further behind experienced drivers when in difficult situations. Drivers benefit from accumulating neighborhood-specific experience, which affects how they search for their next customers.

Suggested Citation

  • Kareem Haggag & Brian McManus & Giovanni Paci, 2017. "Learning by Driving: Productivity Improvements by New York City Taxi Drivers," American Economic Journal: Applied Economics, American Economic Association, vol. 9(1), pages 70-95, January.
    • Handle: RePEc:aea:aejapp:v:9:y:2017:i:1:p:70-95
    Note: DOI: 10.1257/app.20150059
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    4. Nirav Mehta, 2022. "A Partial Identification Approach to Identifying the Determinants of Human Capital Accumulation: An Application to Teachers," University of Western Ontario, Departmental Research Report Series 20221, University of Western Ontario, Department of Economics.
    5. Manikas, Andrew S. & Kroes, James R. & Gattiker, Thomas F., 2019. "Misalignment between societal well-being and business profit maximization: The case of New York taxis drivers’ incentive system," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 1-8.
    6. Nix, Emily, 2020. "A researcher’s guide to the Swedish compulsory school reform," Working Paper Series 2020:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    7. Kim, Youngsoo, 2022. "Taxi driver’s learning curves: An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 1-13.
    8. Alessandro Saia, 2022. "Trouble Underground: Demand Shocks and the Labor Supply Behavior of New York City Taxi Drivers," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(1), pages 1-27, March.
    9. Yingjie Zhang & Beibei Li & Sean Qian, 2023. "Ridesharing and Digital Resilience for Urban Anomalies: Evidence from the New York City Taxi Market," Information Systems Research, INFORMS, vol. 34(4), pages 1775-1790, December.
    10. Meng Liu & Erik Brynjolfsson & Jason Dowlatabadi, 2021. "Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis," Management Science, INFORMS, vol. 67(8), pages 4665-4685, August.
    11. Brodeur, Abel & Nield, Kerry, 2018. "An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 1-16.
    12. Shohfi, Thomas D. & White, Roger M., 2022. "Does native country turmoil predict immigrant workers’ honesty in markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 150-164.
    13. Kelly, E.; & Propper, C.; & Zaranko, B.;, 2022. "Team composition and productivity: evidence from nursing teams in the English National Health Service," Health, Econometrics and Data Group (HEDG) Working Papers 22/19, HEDG, c/o Department of Economics, University of York.
    14. Kenchington, David G. & Shohfi, Thomas D. & Smith, Jared D. & White, Roger M., 2022. "Do sin tax hikes spur cheating in interpersonal exchange?," Accounting, Organizations and Society, Elsevier, vol. 96(C).
    15. Rajgopal, Shivaram & White, Roger, 2019. "Cheating when in the hole: The case of New York city taxis," Accounting, Organizations and Society, Elsevier, vol. 79(C).
    16. Osborne Jackson, 2018. "The supply side of discrimination: evidence from the labor supply of Boston taxi drivers," Working Papers 18-2, Federal Reserve Bank of Boston.
    17. Yingjie Zhang & Beibei Li & Ramayya Krishnan, 2020. "Learning Individual Behavior Using Sensor Data: The Case of Global Positioning System Traces and Taxi Drivers," Information Systems Research, INFORMS, vol. 31(4), pages 1301-1321, December.
    18. Vikström, Johan & Söderström, Martin & Cederlöf, Jonas, 2021. "What makes a good caseworker?," Working Paper Series 2021:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    19. Scott French & Tess Stafford, 2017. "Returns to Experience and the Elasticity of Labor Supply," Discussion Papers 2017-15, School of Economics, The University of New South Wales.
    20. Lundborg, Petter & James, Stefan & Lagerqvist, Bo & Vikström, Johan, 2021. "Learning-by-Doing and Productivity Growth among High-Skilled Workers: Evidence from the Treatment of Heart Attacks," IZA Discussion Papers 14744, Institute of Labor Economics (IZA).
    21. John M. Barrios & Yael Hochberg & Hanyi Yi, 2020. "The Cost of Convenience: Ridehailing and Traffic Fatalities," NBER Working Papers 26783, National Bureau of Economic Research, Inc.
    22. Weiqiang Tan & Jian Zhang, 2021. "Good Days, Bad Days: Stock Market Fluctuation and Taxi Tipping Decisions," Management Science, INFORMS, vol. 67(6), pages 3965-3984, June.
    23. Cody Cook & Rebecca Diamond & Jonathan V Hall & John A List & Paul Oyer, 2021. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers [Measuring the Gig Economy: Current Knowledge and Open Issues]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(5), pages 2210-2238.
    24. Barrios, John M. & Hochberg, Yael V. & Yi, Hanyi, 2018. "The Cost of Convenience: Ridesharing and Traffic Fatalities," Working Papers 282, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    25. Yiyuan Ma & Ke Chen & Youzhi Xiao & Rong Fan, 2022. "Does Online Ride-Hailing Service Improve the Efficiency of Taxi Market? Evidence from Shanghai," Sustainability, MDPI, vol. 14(14), pages 1-16, July.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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