The Dynamic Efficiency in Resource Allocation: Evidence from Vehicle License Lotteries in Beijing

64 Pages Posted: 9 Apr 2020

See all articles by Youming Liu

Youming Liu

Cornell University

Shanjun Li

Cornell University - School of Applied Economics and Management

Caixia Shen

Shanghai University of Finance and Economics

Multiple version iconThere are 2 versions of this paper

Date Written: March 2, 2020

Abstract

The efficiency of resource allocation is often analyzed in static frameworks with a focus on the cross-sectional heterogeneity in the willingness to pay among users. When the resource is durable in nature, the temporal heterogeneity could be important in assessing the efficiency properties of different allocation mechanisms. This paper uses a dynamic model to empirically quantify the efficiency outcome of using lotteries to allocate scarce resources among forward-looking consumers. In the context of the lottery policy for vehicle licenses in Beijing, our analysis shows that lotteries significantly affect intertemporal decisions in that households participate in lotteries at least four years earlier on average than they would be in a counterfactual environment of no quantity constraint. The welfare loss due to temporal heterogeneity and resulting changes in participation decisions accounts for over half of the total welfare loss from the lottery policy. The analysis highlights the importance of taking dynamic efficiency into account in designing resource allocation mechanisms.

Keywords: Allocation Efficiency, Auction, Lottery, Dynamic Demand

JEL Classification: Q58, R48

Suggested Citation

Liu, Youming and Li, Shanjun and Shen, Caixia, The Dynamic Efficiency in Resource Allocation: Evidence from Vehicle License Lotteries in Beijing (March 2, 2020). Available at SSRN: https://ssrn.com/abstract=3547563 or http://dx.doi.org/10.2139/ssrn.3547563

Youming Liu

Cornell University ( email )

Ithaca, NY 14853
United States

Shanjun Li (Contact Author)

Cornell University - School of Applied Economics and Management ( email )

248 Warren Hall
Ithaca, NY 14853
United States

Caixia Shen

Shanghai University of Finance and Economics ( email )

777 Guoding Road
Shanghai, AK Shanghai 200433
China

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