"Google it!" Forecasting the US unemployment rate with a Google job search index

Francesco D'Amuri () and Juri Marcucci ()

MPRA Paper from University Library of Munich, Germany

Abstract: We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. We find that models augmented with the GI outperform the traditional ones in predicting the monthly unemployment rate, even in most state-level forecasts and in comparison with the Survey of Professional Forecasters.

Keywords: Google econometrics; Forecast comparison; Keyword search; US unemployment; Time series models. (search for similar items in EconPapers)
JEL-codes: C53 J60 E27 J64 C22 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for
Date: 2009-10-30, Revised 2009-11-19
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Downloads: (external link)
http://mpra.ub.uni-muenchen.de/18248/ orginal version
http://mpra.ub.uni-muenchen.de/18732/ revised version

Related works:
Working Paper: "Google it!" Forecasting the US unemployment rate with a Google job search index (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:pra:mprapa:18248

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