Revision as of 15:50, 21 January 2021

Abstract

This paper uses a popular web mapping and transportation service to generate information for more than 22 million counterfactual trip instances in 154 large Indian cities. It then develops a methodology to estimate robust indices of mobility for these cities. The estimation allows for an exact decomposition of overall mobility into uncongested mobility and the congestion delays caused by traffic. The paper first documents wide variation in mobility across Indian cities. It then shows that this variation is driven primarily by uncongested mobility. Finally, the paper investigates correlates of mobility and congestion. Denser and more populated cities are slower, in part because of congestion, especially close to their centers. Urban economic development is generally correlated with better uncongested mobility, worse congestion, and overall with better mobility.

Document type: Book

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1596/1813-9450-8546 under the license https://creativecommons.org/licenses/by

• http://dx.doi.org/10.3386/w25218

• http://hdl.handle.net/10986/30236

• https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf under the license http://creativecommons.org/licenses/by/3.0/igo

• https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf under the license cc-by

• https://www.nber.org/papers/w25218,

https://openknowledge.worldbank.org/handle/10986/30236,

http://documents.worldbank.org/curated/en/811261533850020988/Mobility-and-congestion-in-urban-India,

https://www.scipedia.com/public/Akbar_et_al_2018a,

https://ideas.repec.org/p/tuf/tuftec/0829.html,

https://EconPapers.repec.org/RePEc:ess:wpaper:id:12949,

http://www.nber.org/papers/w25218.pdf,

https://m.nber.org/papers/w25218,

https://academic.microsoft.com/#/detail/2890565219 under the license cc-by

DOIS: 10.1596/1813-9450-8546 10.3386/w25218