Google Econometrics and Unemployment Forecasting
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Google Econometrics and Unemployment Forecasting
Askitas, Nikolaos | Zimmermann, Klaus F
Applied Economics Quarterly, Vol. 55 (2009), Iss. 2 : pp. 107–120
296 Citations (CrossRef)
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1Nikolaos Askitas, Bonn University, IZA, 53072 Bonn, Germany.
2Klaus F. Zimmermann, Bonn University, IZA, 53072 Bonn, Germany, and DIW Berlin, Germany.
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https://doi.org/10.1145/2996196 [Citations: 12] -
Periodicity analysis and a model structure for consumer behavior on hotel online search interest in the US
Liu, Juan | Li, Xue | Guo, YaInternational Journal of Contemporary Hospitality Management, Vol. 29 (2017), Iss. 5 P.1486
https://doi.org/10.1108/IJCHM-06-2015-0280 [Citations: 6] -
Workopolis or The Pirate Bay: what does Google Trends say about the unemployment rate?
Dilmaghani, Maryam
Journal of Economic Studies, Vol. 46 (2019), Iss. 2 P.422
https://doi.org/10.1108/JES-11-2017-0346 [Citations: 14] -
Methoden der Journalismusforschung
Messung der Publikumsagenda mittels Nutzungsstatistiken von Suchmaschinenanfragen
Vogelgesang, Jens | Scharkow, Michael2011
https://doi.org/10.1007/978-3-531-93131-9_17 [Citations: 1] -
Using the Internet to Understand Angler Behavior in the Information Age
Martin, Dustin R. | Pracheil, Brenda M. | DeBoer, Jason A. | Wilde, Gene R. | Pope, Kevin L.Fisheries, Vol. 37 (2012), Iss. 10 P.458
https://doi.org/10.1080/03632415.2012.722875 [Citations: 33]
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.
JEL Classification: C22, C82, E17, E24, E37