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dc.contributor.authorChong, Shi Kai
dc.contributor.authorBahrami, Mohsen
dc.contributor.authorChen, Hao
dc.contributor.authorBalcisoy, Selim
dc.contributor.authorPentland, Alex
dc.date.accessioned2021-03-30T19:53:21Z
dc.date.available2021-03-30T19:53:21Z
dc.date.issued2020-06-24
dc.identifier.urihttps://hdl.handle.net/1721.1/130289
dc.description.abstractMuch recent work has illuminated the growth, innovation, and prosperity of entire cities, but there is relatively less evidence concerning the growth and prosperity of individual neighborhoods. In this paper we show that diversity of amenities within a city neighborhood, computed from openly available points of interest on digital maps, accurately predicts human mobility (“flows”) between city neighborhoods and that these flows accurately predict neighborhood economic productivity. Additionally, the diversity of consumption behaviour or the diversity of flows together with geographic centrality and population density accurately predicts neighborhood economic growth, even after controlling for standard factors such as population, etc. We develop our models using geo-located purchase data from Istanbul, and then validate the relationships using openly available data from Beijing and several U.S. cities. Our results suggest that the diversity of goods and services within a city neighborhood is the largest single factor driving both human mobility and economic growth.en_US
dc.language.isoenen_US
dc.publisherEPJ Data Scienceen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.titleEconomic outcomes predicted by diversity in citiesen_US
dc.typeArticleen_US
dc.identifier.citationChong, S. K., Bahrami, M., Chen, H., Balcisoy, S., Bozkaya, B., & Pentland, A. (2020). Economic outcomes predicted by diversity in cities. EPJ Data Science, 9(1), 17.en_US
dc.contributor.departmentMIT Connection Science (Research institute)


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