Lecturer: Prof. Matthew Shum
     
Date: November 27th, 2018 (Tue.) 14:30-16:30
Venue: Mo-Huan Auditorium, Institute of Economics, Academia Sinica
Organizer: Institute of Economics, Academia Sincia

 
                      
DYNAMIC LABOR SUPPLY OF TAXICAB DRIVERS:
A SEMIPARAMETRIC OPTIMAL STOPPING MODEL
     

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.

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