4.7 Article

The impact of Uber and Lyft on vehicle ownership, fuel economy, and transit across U.S. cities

期刊

ISCIENCE
卷 24, 期 1, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.isci.2020.101933

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资金

  1. National Bureau of Economic Research
  2. Carnegie Mellon University's Scott Institute for Energy Innovation
  3. Carnegie Mellon University's Steinbrenner Institute for Environmental Education and Research
  4. Presidential Heinz Fellowship
  5. National Science Foundation [SES-0949710, SES-1463492]
  6. Carnegie Mellon University [SES-0949710, SES-1463492]
  7. U.S. Environmental Protection Agency [R835873]
  8. U.S. Department of Transportation Dwight David Eisenhower Transportation Fellowship

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The study found that the entry of TNC companies such as Uber and Lyft leads to an increase in vehicle registrations in urban areas, but does not have a significant impact on fuel economy and transit use. There is heterogeneity in the effects of TNC entry across urban areas, with car-dependent cities and areas with lower population growth being more affected.
We estimate the effects of transportation network companies (TNCs) Uber and Lyft on vehicle ownership, fleet average fuel economy, and transit use in U.S. urban areas using a set of difference-in-difference propensity score-weighted regression models that exploit staggered market entry across the U.S. from 2011 to 2017. We find evidence that TNC entry into urban areas causes an average 0.7% increase in vehicle registrations with significant heterogeneity in these effects across urban areas: TNC entry produces larger vehicle ownership increases in urban areas with higher initial ownership (car-dependent cities) and in urban areas with lower population growth (where TNC-induced vehicle adoption outpaces population growth). We also find no statistically significant average effect of TNC entry on fuel economy or transit use but find evidence of heterogeneity in these effects across urban areas, including larger transit ridership reductions after TNC entry in areas with higher income and more childless households.

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