Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity /

Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity /

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Bibliographic Details
Author / Creator:	Austin, Paul, author.
Imprint:	[Washington, District of Columbia] : International Monetary Fund, 2021. ©2021.
Description:	1 online resource (47 pages) : illustrations.
Language:	English
Series:	IMF Working Paper ; WP/21/295 IMF working paper ; WP/21/295.
Subject:	Google Places. Google Places. COVID-19 (Disease) -- Economic aspects. Internet searching. COVID-19 (Disease) -- Economic aspects. Internet searching.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/13515922

Hidden Bibliographic Details
Other authors / contributors:	Marini, Marco, author. Sanchez, Alberto, author. Simpson-Bell, Chima, author. Tebrake, James, author. International Monetary Fund.
ISBN:	9781616355432 1616355433
Notes:	Title from title page (viewed on April 13, 2022). "Authorized for distribution by J. R. Rosales" --T.p. Includes bibliographical references.
Summary:	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.

Description
Summary:	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.
Item Description:	Title from title page (viewed on April 13, 2022). "Authorized for distribution by J. R. Rosales" --T.p.
Physical Description:	1 online resource (47 pages) : illustrations.
Bibliography:	Includes bibliographical references.
ISBN:	9781616355432 1616355433