Model and Analysis of Labor Supply for Ride-Sharing Platforms in the Presence of Sample Self-Selection and Endogeneity

Posted: 7 May 2019

See all articles by Hao Sun

Hao Sun

Tsinghua University - School of Economics and Management

Hai Wang

Carnegie Mellon University - Heinz College of Information Systems and Public Policy; Singapore Management University - School of Information Systems

Zhixi Wan

The University of Hong Kong - Faculty of Business and Economics

Date Written: April 20, 2019

Abstract

With the popularization of ride-sharing services, drivers working as freelancers on ride-sharing platforms can design their schedules flexibly. They make daily decisions regarding whether to participate in work, and if so, how many hours to work. Factors such as hourly income rate affect both the participation decision and working-hour decision, and evaluation of the impacts of hourly income rate on labor supply becomes important. To test the reference-dependent preference theory, we propose an econometric framework with closed-form measures to estimate both the participation elasticity (i.e., extensive margin elasticity) and working-hour elasticity (i.e., intensive margin elasticity) of labor supply. We model the sample self-selection bias of labor force participation and endogeneity of income rate and show that failure to control for sample self-selection and endogeneity leads to biased estimates. Taking advantage of a natural experiment with exogenous shocks on a ride-sharing platform, we identify the driver incentive called “income multiplier” as exogenous shock and an instrumental variable. We empirically analyze the impacts of hourly income rates on labor supply along both extensive and intensive margins. We find both the participation elasticity and working-hour elasticity of labor supply are positive and significant in the dataset of this ride-sharing platform. Interestingly, in the presence of driver heterogeneity, we also find that participation elasticity decreases along both the extensive and intensive margins; working-hour elasticity decreases along the intensive margin.

Keywords: Ride-sharing platforms, Labor supply, Income elasticity, Sample selection, Endogeneity

Suggested Citation

Sun, Hao and Wang, Hai and Wan, Zhixi, Model and Analysis of Labor Supply for Ride-Sharing Platforms in the Presence of Sample Self-Selection and Endogeneity (April 20, 2019). Available at SSRN: https://ssrn.com/abstract=3375263

Hao Sun

Tsinghua University - School of Economics and Management ( email )

China

Hai Wang (Contact Author)

Carnegie Mellon University - Heinz College of Information Systems and Public Policy ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Singapore Management University - School of Information Systems ( email )

School of Information Systems
80 Stamford Road
Singapore 178902, 178899
Singapore

Zhixi Wan

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

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