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  1. Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity
    Author: Austin, Paul; Marini, Marco; Sanchez, Alberto; Simpson-Bell, Chima; Tebrake, James
    Published: Dec 2021
    Publisher:  International Monetary Fund, Washington, DC

    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest... more

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    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators

     
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  2. Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity
    Author: Austin, Paul; Marini, Marco; Sanchez, Alberto; Simpson-Bell, Chima; Tebrake, James
    Published: Dec 2021
    Publisher:  International Monetary Fund, Washington, DC

    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest... more

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
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    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
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    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators

     
    Export to reference management software   RIS file
      BibTeX file