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    Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
    09 Dec 2015Working Paper Summaries

    Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life

    by Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
    Michael Luca, Scott Duke Kominers and colleagues describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities.
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    Author Abstract

    New, "big" data sources allow measurement of city characteristics and outcome variables higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big 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 image 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.

    Paper Information

    • Full Working Paper Text
    • Working Paper Publication Date: November 2015
    • HBS Working Paper Number: 16-065
    • Faculty Unit(s): Negotiation, Organizations & Markets
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    Scott Duke Kominers
    Scott Duke Kominers
    Professor of Business Administration (Leave of Absence)
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    Michael Luca
    Michael Luca
    Lee J. Styslinger III Associate Professor of Business Administration
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