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Constructing Daily Economic Sentiment Indices Based on Google Trends

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Abstract

Google Trends have become a popular data source for social science research. We show that for small countries or sub-national regions like U.S. states, underlying sampling noise in Google Trends can be substantial. The data may therefore be unreliable for time series analysis and is furthermore frequency-inconsistent: daily data differs from weekly or monthly data. We provide a novel sampling technique along with the R-package trendecon in order to generate stable daily Google search results that are consistent with weekly and monthly queries of Google Trends. We use this new approach to construct long and consistent daily economic indices for the (mainly) German-speaking countries Germany, Austria, and Switzerland. The resulting indices are significantly correlated with traditional leading indicators, with the advantage that they are available much earlier.

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  • Vera Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2020. "Constructing Daily Economic Sentiment Indices Based on Google Trends," KOF Working papers 20-484, KOF Swiss Economic Institute, ETH Zurich.
    • Handle: RePEc:kof:wpskof:20-484
    DOI: 10.3929/ethz-b-000423548
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    Cited by:

    1. Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
    2. Santiago E. Alvarez & Sarah M. Lein, 2020. "Tracking inflation on a daily basis," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-13, December.
    3. Simionescu, Mihaela & Cifuentes-Faura, Javier, 2022. "Can unemployment forecasts based on Google Trends help government design better policies? An investigation based on Spain and Portugal," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 1-21.

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    More about this item

    Keywords

    Google Trends; measurement; high frequency; forecasting; Covid-19 Market; Euro; sectoral heterogeneity;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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