Google Econometrics and Unemployment Forecasting

Nikos Askitas () and Klaus Zimmermann ()

No 899, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

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: Google; internet; keyword search; search engine; unemployment; predictions; timeseries analysis (search for similar items in EconPapers)
JEL-codes: C22 C82 E17 E24 E37 (search for similar items in EconPapers)
Pages: 22 p.
Date: 2009
New Economics Papers: this item is included in nep-for and nep-ict
References: Add references at CitEc
Citations: View citations in EconPapers (253)

Downloads: (external link)
https://www.diw.de/documents/publikationen/73/diw_01.c.99158.de/dp899.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)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:diw:diwwpp:dp899

Access Statistics for this paper

More papers in Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research Contact information at EDIRC.
Bibliographic data for series maintained by Bibliothek ().