Dynamic Labor Supply of Taxicab Drivers: a Semiparametric Optimal Stopping Model

35 Pages Posted: 1 Jan 2018 Last revised: 25 Mar 2018

Nicholas Buchholz

University of Texas at Austin

Matthew Shum

California Institute of Technology

Haiqing Xu

Department of Economics, University of Texas at Austin

Date Written: March 20, 2018

Abstract

We estimate an optimal stopping model for taxicab drivers' labor supply decisions, using a large sample of shifts for drivers of New York City taxicabs. Our results show that both ``behavioral'' and ``neoclassical'' wage responses are present in the data, with the behavioral income-targeting story explaining shorter shifts, and the standard neoclassical model explaining longer shifts. Hence these findings partially reconcile the divergent reduced-form results in the existing literature. A methodological contribution of this paper is to develop a new closed-form estimator for dynamic discrete choice models in a semiparametric setting, in which the distribution of utility shocks is left unspecified.

Keywords: Dynamic discrete choice model, Closed form estimator, Optimal stopping, Taxicab industry, Labor supply, Negative wage elasticities, Semiparametric average derivative estimation

JEL Classification: C14, D91, C41, L91

Suggested Citation

Buchholz, Nicholas and Shum, Matthew and Xu, Haiqing, Dynamic Labor Supply of Taxicab Drivers: a Semiparametric Optimal Stopping Model (March 20, 2018). Available at SSRN: https://ssrn.com/abstract=2748697 or http://dx.doi.org/10.2139/ssrn.2748697

Nicholas Buchholz

University of Texas at Austin ( email )

2317 Speedway
Austin, TX 78712
United States

Matthew Shum (Contact Author)

California Institute of Technology ( email )

Pasadena, CA 91125
United States

Haiqing Xu

Department of Economics, University of Texas at Austin ( email )

Austin, TX 78712
United States

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