Conference Proceedings
Price as a Signal for Transport Policy Fine-Tuning

Responding to China’s astronomical growth in car ownership, several Chinese cities are actively controlling car ownership to reduce congestion and air pollution. Shanghai pioneered car ownership control by adopting a license auction policy that requires purchasers to bid for license quota in monthly public auctions. This paper focuses on one specific parameter of the auction policy design: the mechanism of determining the month quota by the government. Officially, the quota is calculated each month based on road capacity in order to maximize the efficiency of the transportation network. However, we suggest in this paper a more complicated story: in addition to the stated efficiency rationale, the quota setting process incorporates public attitude into consideration implicitly. We use Shanghai’s historical auction data from 2002 to 2012 to test this hypothesis. A structural multivariate autoregressive moving average (M-ARMA) model is developed to represent the interactions between three key variables and their co-movement simultaneously: the quota set by the government each month, the number of bidders, and the bidding price. The model result suggests that during the license auction process, the government adjusts the quota to release the pressure of high bidding price and mollify the public. Effectively Shanghai embraces the market mechanism to gauge the public and fine-tune the policy responding to market price signal. The auction policy combines state control (capping the quota) and market allocation (auction process), and allows certain degrees of flexibility (adjustable quota responsive to bidding price). 

Title
Publication TypeConference Proceedings
Year of Conference2015
AuthorsCastro M, Zhao J
Conference NameTransportation Research Board (TRB) Annual Conferenceerence
Conference LocationWashington, D.C.
Keywordscar license auction, Policy Fine-tuning, Price Signal, structural multivariate autoregressive moving average model
Abstract

Responding to China’s astronomical growth in car ownership, several Chinese cities are actively controlling car ownership to reduce congestion and air pollution. Shanghai pioneered car ownership control by adopting a license auction policy that requires purchasers to bid for license quota in monthly public auctions. This paper focuses on one specific parameter of the auction policy design: the mechanism of determining the month quota by the government. Officially, the quota is calculated each month based on road capacity in order to maximize the efficiency of the transportation network. However, we suggest in this paper a more complicated story: in addition to the stated efficiency rationale, the quota setting process incorporates public attitude into consideration implicitly. We use Shanghai’s historical auction data from 2002 to 2012 to test this hypothesis. A structural multivariate autoregressive moving average (M-ARMA) model is developed to represent the interactions between three key variables and their co-movement simultaneously: the quota set by the government each month, the number of bidders, and the bidding price. The model result suggests that during the license auction process, the government adjusts the quota to release the pressure of high bidding price and mollify the public. Effectively Shanghai embraces the market mechanism to gauge the public and fine-tune the policy responding to market price signal. The auction policy combines state control (capping the quota) and market allocation (auction process), and allows certain degrees of flexibility (adjustable quota responsive to bidding price). 

URLhttp://trid.trb.org/view/2015/C/1336949