Evaluating the Car Ownership Control Policy in Shanghai: A Structural Vector Auto-Regression Approach

Transportation, January 2018

Posted: 6 Aug 2015 Last revised: 6 Sep 2019

See all articles by Suwei Feng

Suwei Feng

Shanghai University of Finance and Economics - School of Public Economics & Administration

Qiang Li

National University of Singapore (NUS) - Department of Real Estate

Date Written: July 30, 2015

Abstract

Beginning in 1986, Shanghai has implemented an interesting car ownership policy, namely an auction of the right to register private cars. The auction was modified several times over the years. Most recently since April 2013, the authority added price caps to mitigate rapid price run-ups. In this paper, we propose a structural vector auto-regression (SVAR) approach to evaluate the performance of the Shanghai auction since 2002. The SVAR is flexible enough to incorporate alterations to the auction system into the modelling structure. We find three key results: (1) at least before 2008, short-term price fluctuations can be managed by varying the quota; (2) the number of bidders, or demand, ultimately drives the price in later years; (3) the impact of one standard deviation increase in demand takes 6 months to one year to dissipate, casting doubt on the viability of the new auction procedure, which has accumulated more than 150,000 bidders in waiting since April 2013. We also analyze how socio-economic factors affect quota, price, and the number of bidders using a simultaneous equations model. Due to data limitations, such an analysis is less conclusive. We argue that the SVAR framework can be improved and applied to other cities in evaluating their car ownership practices.

Keywords: Car ownership control, Structural VAR, License plate quota auction, Efficiency

JEL Classification: L92, L98, R48

Suggested Citation

Feng, Suwei and Li, Qiang, Evaluating the Car Ownership Control Policy in Shanghai: A Structural Vector Auto-Regression Approach (July 30, 2015). Transportation, January 2018, Available at SSRN: https://ssrn.com/abstract=2639496 or http://dx.doi.org/10.2139/ssrn.2639496

Suwei Feng

Shanghai University of Finance and Economics - School of Public Economics & Administration ( email )

Shanghai, 200433
China

Qiang Li (Contact Author)

National University of Singapore (NUS) - Department of Real Estate ( email )

4 Architecture Drive
Singapore 117566
Singapore

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