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Predicting unemployment in short samples with internet job search query data

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  • Francesco, D'Amuri
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    Abstract

    This article tests the power of a novel indicator based on job search related web queries in predicting quarterly unemployment rates in short samples. Augmenting standard time series specifications with this indicator definitely improves out-of-sample forecasting performance at nearly all in-sample interval lengths and forecast horizons, both when compared with models estimated on the same or on a much longer time series interval.

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    File URL: http://mpra.ub.uni-muenchen.de/18403/
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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 18403.

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    Date of creation: 30 Oct 2009
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    Handle: RePEc:pra:mprapa:18403

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    Related research

    Keywords: Google econometrics; Forecast comparison; Keyword search; Unemployment; Time series models.;

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    References

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    1. Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Research Notes of the German Council for Social and Economic Data 41, German Council for Social and Economic Data (RatSWD).
    2. Betsey Stevenson, 2009. "The Internet and Job Search," NBER Chapters, in: Studies of Labor Market Intermediation, pages 67-86 National Bureau of Economic Research, Inc.
    3. D'Amuri, Francesco & Marcucci, Juri, 2009. "'Google it!' Forecasting the US unemployment rate with a Google job search index," ISER Working Paper Series 2009-32, Institute for Social and Economic Research.
    4. Klaus Abberger, 2005. "Qualitative Business Surveys and theAssessment of Employment A Case Study for Germany," Ifo Working Paper Series Ifo Working Paper No. 11, Ifo Institute for Economic Research at the University of Munich.
    5. Proietti, Tommaso, 2003. "Forecasting the US unemployment rate," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 451-476, March.
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    Cited by:
    1. D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
    2. McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.

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