BIG DATA AND BIG CITIES: THE PROMISES AND LIMITATIONS OF IMPROVED MEASURES OF URBAN LIFE.

New, 'big data' sources allow measurement of city characteristics and outcome variables at higher collection frequencies and more granular geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big urban data has the most value for the s...

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Publicado en:Economic Inquiry Vol. 56; no. 1; pp. 114 - 138
Autores principales: Glaeser, Edward L., Kominers, Scott Duke, Luca, Michael, Naik, Nikhil
Formato: Artículo
Publicado: Wiley-Blackwell Jan2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: BIG DATA AND BIG CITIES: THE PROMISES AND LIMITATIONS OF IMPROVED MEASURES OF URBAN LIFE.
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          Glaeser, Edward L.
          Kominers, Scott Duke
          Luca, Michael
          Naik, Nikhil
        affil:
          Department of Economics, Harvard University, Cambridge, MA, 02138
          John F. Kennedy School of Government, Harvard University, Cambridge, MA, 02138
          National Bureau of Economic Research, Cambridge, MA, 02138.
          Center of Mathematical Sciences and Applications, Harvard University, Cambridge, MA, 02138
          Center for Research on Computation and Society, Harvard University, Cambridge, MA, 02138
          Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138
          Entrepreneurial Management, Harvard Business School, Boston, MA, 02163
          Society of Fellows, Harvard University, Cambridge, MA, 02138.
          Negotiation, Organizations & Markets, Harvard Business School, Boston, MA, 02163
          Media Lab, Massachusetts Institute of Technology, Cambridge, MA, 02139
      su:
        Google Maps
        Google Earth (Web resource)
        Urban life
        Income
        Poverty
        Big data
      sug:
        subj:
          Urban life
          Income
          Poverty
          Big data
          Google Maps
          Google Earth (Web resource)
      ab: New, 'big data' sources allow measurement of city characteristics and outcome variables at higher collection frequencies and more granular geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big urban data has the most value for the study of cities when it allows measurement of the previously opaque, or when it can be coupled with exogenous shocks to people or place. We describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities. We first show how Google Street View images can be used to predict income in New York City, suggesting that similar imagery data can be used to map wealth and poverty in previously unmeasured areas of the developing world. We then discuss how survey techniques can be improved to better measure willingness to pay for urban amenities. Finally, we explain how Internet data is being used to improve the quality of city services. ( JEL R1, C8, C18)
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    language: English
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