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

46 Pages Posted: 20 Jun 2014 Last revised: 22 Nov 2014

See all articles by Kareem Haggag

Kareem Haggag

Carnegie Mellon University - Department of Social and Decision Sciences

Brian McManus

University of North Carolina (UNC) at Chapel Hill - Department of Economics

Giovanni Paci

New York University (NYU) - Center for Neuroeconomics

Date Written: November 1, 2014

Abstract

We study learning by doing (LBD) 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 significant learning by these entrepreneurial agents, we exploit our data’s breadth to investigate heterogeneity in performance and the mechanisms of driver improvement. New drivers vary in their individual learning rates and as a group lag farther behind experienced drivers when in difficult situations. Drivers benefit from accumulating neighborhood-specific experience, which affects how they search for their next customers.

Keywords: learning by doing, specific human capital, taxis, big data

JEL Classification: D24, D83, J24, L92

Suggested Citation

Haggag, Kareem and McManus, Brian and Paci, Giovanni, Learning by Driving: Productivity Improvements by New York City Taxi Drivers (November 1, 2014). Available at SSRN: https://ssrn.com/abstract=2456733 or http://dx.doi.org/10.2139/ssrn.2456733

Kareem Haggag

Carnegie Mellon University - Department of Social and Decision Sciences ( email )

Pittsburgh, PA 15213-3890
United States

Brian McManus (Contact Author)

University of North Carolina (UNC) at Chapel Hill - Department of Economics ( email )

Chapel Hill, NC 27599
United States

Giovanni Paci

New York University (NYU) - Center for Neuroeconomics ( email )

4 Washington Place, Room 809
New York, NY 10003
United States

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