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== Abstract == | == 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. | + | 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 | Document type: Book | ||
== Full document == | == Full document == | ||
− | <pdf>Media: | + | <pdf>Media:Akbar_et_al_2018a-beopen557-7619-document.pdf</pdf> |
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The different versions of the original document can be found in: | The different versions of the original document can be found in: | ||
− | * [http://dx.doi.org/10.1596/1813-9450-8546 http://dx.doi.org/10.1596/1813-9450-8546] | + | * [http://dx.doi.org/10.1596/1813-9450-8546 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://dx.doi.org/10.3386/w25218] | * [http://dx.doi.org/10.3386/w25218 http://dx.doi.org/10.3386/w25218] | ||
− | * [http://hdl.handle.net/10986/30236 http://hdl.handle.net/10986/30236] under the license http://creativecommons.org/licenses/by/3.0/igo | + | * [http://hdl.handle.net/10986/30236 http://hdl.handle.net/10986/30236] |
+ | |||
+ | * [https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf 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 https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf] under the license cc-by | * [https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf https://openknowledge.worldbank.org/bitstream/10986/30236/1/WPS8546.pdf] under the license cc-by | ||
+ | |||
+ | * [https://www.nber.org/papers/w25218 https://www.nber.org/papers/w25218], | ||
+ | : [https://openknowledge.worldbank.org/handle/10986/30236 https://openknowledge.worldbank.org/handle/10986/30236], | ||
+ | : [http://documents.worldbank.org/curated/en/811261533850020988/Mobility-and-congestion-in-urban-India http://documents.worldbank.org/curated/en/811261533850020988/Mobility-and-congestion-in-urban-India], | ||
+ | : [https://www.scipedia.com/public/Akbar_et_al_2018a https://www.scipedia.com/public/Akbar_et_al_2018a], | ||
+ | : [https://ideas.repec.org/p/tuf/tuftec/0829.html https://ideas.repec.org/p/tuf/tuftec/0829.html], | ||
+ | : [https://EconPapers.repec.org/RePEc:ess:wpaper:id:12949 https://EconPapers.repec.org/RePEc:ess:wpaper:id:12949], | ||
+ | : [http://www.nber.org/papers/w25218.pdf http://www.nber.org/papers/w25218.pdf], | ||
+ | : [https://m.nber.org/papers/w25218 https://m.nber.org/papers/w25218], | ||
+ | : [https://academic.microsoft.com/#/detail/2890565219 https://academic.microsoft.com/#/detail/2890565219] under the license cc-by | ||
+ | |||
+ | |||
− | DOIS: | + | DOIS: 10.1596/1813-9450-8546 10.3386/w25218 |
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
The URL or file path given does not exist.
The different versions of the original document can be found in:
DOIS: 10.1596/1813-9450-8546 10.3386/w25218
Published on 01/01/2018
Volume 2018, 2018
DOI: 10.3386/w25218
Licence: CC BY-NC-SA license
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