Welfare Implications of Congestion Pricing: Evidence from SF park

Pnina Feldman (), Jun Li () and Hsin-Tien Tsai ()
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Pnina Feldman: Questrom School of Business, Boston University, Boston, Massachusetts 02215
Jun Li: Stephen M. Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109
Hsin-Tien Tsai: Department of Economics, National University of Singapore, Singapore 119077

Manufacturing & Service Operations Management, 2022, vol. 24, issue 2, 1091-1109

Abstract: Problem definition : Congestion pricing offers an appealing solution to urban parking problems—charging varying rates across time and space as a function of congestion may shift demand and improve allocation of limited resources. It aims to increase the accessibility of highly desired public goods and to reduce traffic caused by drivers who search for available parking spaces. At the same time, complex policies make it harder for consumers to make search-based decisions. We investigate the effect of congestion pricing on consumer and social welfare. Academic/practical relevance : This paper contributes to the theory and practice of the management of scarce resources in the public sector, where welfare is of particular interest. Methodologically, we contribute to the literature on structural estimation of dynamic spatial search models. Methodology : Using data from the City of San Francisco, both before and after the implementation of a congestion-pricing parking program, SF park , we estimate the welfare implications of the policy. We use a dynamic spatial search model to structurally estimate consumers’ search costs, distance disutilities, price sensitivities, and trip valuations. Results : We find that congestion pricing increases consumer and social welfare by more than 4% and reduces search traffic by more than 10% in congested regions compared with fixed pricing. However, congestion pricing may hurt welfare in uncongested regions, in which the focus should be on increasing utilization. Moreover, an unnecessarily complex congestion-pricing scheme makes it difficult for consumers to make search-based decisions. We find that a simpler pricing policy may yield higher welfare than a complex one. Lastly, compared with a policy that imposes limits on parking durations, congestion pricing increases social welfare by allocating the scarce resource to consumers who value it most. Managerial implications : The insights from SF park offer important implications for local governments that consider alternatives for managing parking and congestion and for public-sector managers who evaluate the tradeoffs between approaches to manage public resources.

Keywords: congestion pricing; dynamic spatial search model; public sector; traffic management (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:24:y:2022:i:2:p:1091-1109

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