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Forecasting Consumer Purchases Using Google Trends

Author

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  • Torsten Schmidt
  • Simeon Vosen

Abstract

Torsten Schmidt and Simeon Vosen have done extensive research on the potential benefits of using Google TrendsÕ product search data for forecasting economic behavior. Their results point strongly to the predictive value of using Google indicators in forecasting models. Here, they provide an introduction to the Google indicators of personal consumption expenditures (PCE) and compare the performance of PCE forecasting models that use the Google data with those that donÕt. Copyright International Institute of Forecasters, 2013

Suggested Citation

  • Torsten Schmidt & Simeon Vosen, 2013. "Forecasting Consumer Purchases Using Google Trends," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 30, pages 38-41, Summer.
    • Handle: RePEc:for:ijafaa:y:2013:i:29:p:38-41
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    Cited by:

    1. Yong Zhang & Miner Zhong & Nana Geng & Yunjian Jiang, 2017. "Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
    2. Naccarato, Alessia & Falorsi, Stefano & Loriga, Silvia & Pierini, Andrea, 2018. "Combining official and Google Trends data to forecast the Italian youth unemployment rate," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 114-122.

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