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Do Google Searches Help in Nowcasting Private Consumption? A Real-Time Evidence for the US

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Author Info

  • Konstantin A. Kholodilin

    ()
    (DIW Berlin, Germany)

  • Maximilian Podstawski

    ()
    (Universität Potsdam, Wirtschafts- und Sozialwissen- schaftliche Fakultät, Potsdam, Germany)

  • Boriss Siliverstovs

    ()
    (KOF Swiss Economic Institute, ETH Zurich, Switzerland)

Abstract

In this paper, we investigate whether the Google search activity can help in nowcasting the year-on-year growth rates of monthly US private consumption using a real-time data set. The Google-based forecasts are compared to those based on a benchmark AR(1) model and the models including the consumer surveys and financial indicators. According to the Diebold-Mariano test of equal predictive ability, the null hypothesis can be rejected suggesting that Google-based forecasts are significantly more accurate than those of the benchmark model. At the same time, the corresponding null hypothesis cannot be rejected for models with consumer surveys and financial variables. Moreover, when we apply the test of superior predictive ability (Hansen, 2005) that controls for possible data-snooping biases, we are able to reject the null hypothesis that the benchmark model is not inferior to any alternative model forecasts. Furthermore, the results of the model confidence set (MCS) procedure (Hansen et al., 2005) suggest that the autoregressive benchmark is not selected into a set of the best forecasting models. Apart from several Google-based models, the MCS contains also some models including survey-based indicators and financial variables. We conclude that Google searches do help improving the nowcasts of the private consumption in US.

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Bibliographic Info

Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 10-256.

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Length: 28 pages
Date of creation: Apr 2010
Date of revision:
Handle: RePEc:kof:wpskof:10-256

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Keywords: Google indicators; real-time nowcasting; principal components; US private consumption.;

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References

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  1. repec:ese:iserwp:2009-32 is not listed on IDEAS
  2. Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
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As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Nowcasting consumption with Google
    by Adam Ozimek in Modeled Behavior on 2010-06-07 11:26:11
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Cited by:
  1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
  2. David Iselin & Boriss Siliverstovs, 2013. "Mit Zeitungen Konjunkturprognosen erstellen: Eine Vergleichsstudie für die Schweiz und Deutschland," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 7(3), pages 104-117, September.
  3. Rose, Andrew K. & Spiegel, Mark M., 2012. "Dollar illiquidity and central bank swap arrangements during the global financial crisis," Journal of International Economics, Elsevier, vol. 88(2), pages 326-340.
  4. Konstantin A. Kholodilin & Boriss Siliverstovs, 2010. "Measuring Regional Inequality by Internet Car Price Advertisements: Evidence for Germany," KOF Working papers 10-261, KOF Swiss Economic Institute, ETH Zurich.
  5. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
  6. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle: A comparative study for Germany and Switzerland," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.

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