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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.

Macroeconomics --- Economics: General --- Statistics --- Web Services & APIs --- Diseases: Contagious --- Information Management --- Industries: Manufacturing --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- General Financial Markets: General (includes Measurement and Data) --- Information and Internet Services --- Computer Software --- Health Behavior --- Large Data Sets: Modeling and Analysis --- Industry Studies: Manufacturing: General --- Economic & financial crises & disasters --- Economics of specific sectors --- Econometrics & economic statistics --- Web services --- Infectious & contagious diseases --- Data capture & analysis --- Manufacturing industries --- Economic and financial statistics --- APIs --- Technology --- COVID-19 --- Health --- Big data --- Manufacturing --- Economic sectors --- Currency crises --- Informal sector --- Economics --- Economic statistics --- Application program interfaces --- Computer software --- Communicable diseases --- Australia