Abstract

To alleviate many parking-related externalities, several rapidly growing cities globally are optimizing parking through "smart-parking" programs, involving measures such as adjusting parking prices based upon demand, making payments easier, and significantly improving parking-related information dissemination. There are few rigorous empirical estimates regarding the efficacy of these policies, particularly for outcomes such as transit ridership or traffic flow, which are of key policy relevance. Exploiting features of the roll out of SFpark, a smart-parking program for the city of San Francisco, we are able to estimate its effect upon public transit usage and traffic flow. Using a difference-in-difference strategy and a rich micro data-set on transit bus ridership along with data from SFpark, we find that SFpark led to a significant increase in bus ridership and a reduction in traffic flow. A back-of-the-envelope calculation suggests that the economic benefits resulting from avoided pollution and reduced congestion consequent to SFpark is larger than the approximate nominal costs of the program. Overall, our results suggest that smart-parking programs can help mitigate many traffic-related externalities, yielding significant economic benefits. (C) 2019 Elsevier Inc. All rights reserved.

Keywords

Parking policy; Transportation; Mass transit; Air pollution; Smart-parking

Published in

Journal of Environmental Economics and Management
2020, volume: 99, article number: 102273
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE

Authors' information