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A Closed-Form Estimator for Dynamic Discrete-Choice Models: Assessing Taxicab Drivers' Dynamic Labor Supply

34 Pages Posted: 17 Mar 2016 Last revised: 19 Nov 2017

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: February 2, 2017

Abstract

We propose a new closed-form estimator for dynamic discrete choice models in a semiparametric setting, in which the per-period utility functions are known up to a finite number of parameters, but the distribution of utility shocks is left unspecified. Compared to other existing estimators for these models, our estimator requires no iterative nonlinear optimization, rendering issues of starting values or convergence criteria irrelevant. Using our approach, we estimate an optimal stopping model for taxicab drivers’ labor supply decisions. Our results show that, once the inherent dynamic in taxicab drivers’ work decisions are accounted for, it is possible to obtain “nonstandard” (i.e., negative) wage elasticities from a model in which drivers’ utility functions do not have any explicitly “nonstandard” features, such as reference dependence or loss aversion.

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, A Closed-Form Estimator for Dynamic Discrete-Choice Models: Assessing Taxicab Drivers' Dynamic Labor Supply (February 2, 2017). Available at SSRN: https://ssrn.com/abstract= or http://dx.doi.org/10.2139/ssrn.2748697

Nicholas Buchholz

University of Texas at Austin ( email )

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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