Google Econometrics and Unemployment Forecasting

Nikos Askitas and Klaus Zimmermann ()

No 4201, IZA Discussion Papers from IZA Network @ LISER

Abstract: The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data and exhibits a strong potential for the method used.

Keywords: unemployment; time-series analysis; internet; Google; keyword search; search engine; predictions (search for similar items in EconPapers)
JEL-codes: C22 C82 E17 E24 E37 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2009-06
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ict
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (247)

Published - published in: Applied Economics Quarterly, 2009, 55 (2), 107-120

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https://docs.iza.org/dp4201.pdf (application/pdf)

Related works:
Journal Article: Google Econometrics and Unemployment Forecasting (2009)
Working Paper: Google Econometrics and Unemployment Forecasting (2009)
Working Paper: Google Econometrics and Unemployment Forecasting (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp4201

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