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Spatial Equilibrium, Search Frictions, and Dynamic Efficiency in the Taxi Industry

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  • Nicholas Buchholz

Abstract

This article analyses the dynamic spatial equilibrium of taxicabs and shows how common taxi regulations lead to substantial inefficiencies as a result of search frictions and mis-allocation. To analyse the role of regulation on frictions and efficiency, I pose a dynamic model of spatial search and matching between taxis and passengers. Using a comprehensive dataset of New York City yellow medallion taxis, I use this model to compute the equilibrium spatial distribution of vacant taxis and estimate intraday demand given price and medallion regulations. My estimates show that the weekday New York market achieves about 5.7 million in daily welfare or about 27 per trip, but an additional 53 thousand customers fail to find cabs due to search frictions. Counterfactual analysis shows that implementing simple tariff pricing changes can enhance allocative efficiency and expand the market, offering daily consumer surplus gains of up to 227 thousand and up to 49 thousand additional daily taxi-passenger matches, a similar magnitude to the gain in matches generated by adopting a perfect static matching technology.

Suggested Citation

  • Nicholas Buchholz, 2022. "Spatial Equilibrium, Search Frictions, and Dynamic Efficiency in the Taxi Industry," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(2), pages 556-591.
    • Handle: RePEc:oup:restud:v:89:y:2022:i:2:p:556-591.
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    File URL: http://hdl.handle.net/10.1093/restud/rdab050
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    Citations

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    Cited by:

    1. Boffa, Federico & Fedele, Alessandro & Iozzi, Alberto, 2023. "Congestion and incentives in the age of driverless fleets," Journal of Urban Economics, Elsevier, vol. 137(C).
    2. Roman Zakharenko, 2024. "Who should not share? The merits of withholding unused vehicles," Working Papers 2024_07, Business School - Economics, University of Glasgow.
    3. Ron Yang, 2022. "(Don’t) Take Me Home: Home Preference and the Effect of Self-Driving Trucks on Interstate Trade," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    4. Yoshifumi Konishi & Akari Ono, 2024. "Is Ride-sharing Good for Environment?," Keio-IES Discussion Paper Series 2024-014, Institute for Economics Studies, Keio University.
    5. Fan, Ying & Fu, Yuqi & Yang, Zan & Chen, Ming, 2024. "Search frictions in rental markets: Evidence from urban China," China Economic Review, Elsevier, vol. 83(C).
    6. Saara Hämäläinen & Vaiva Petrikaitė, 2024. "Prediction algorithms in matching platforms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(3), pages 979-1020, November.
    7. Lehe, Lewis & Pandey, Ayush, 2022. "Taxi service with heterogeneous drivers and a competitive medallion market," Journal of Urban Economics, Elsevier, vol. 131(C).

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