Google Econometrics and Unemployment Forecasting
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 4201.
Length: 25 pages
Date of creation: Jun 2009
Date of revision:
Publication status: published in: Applied Economics Quarterly, 2009, 55 (2), 107-120. [Open Access]
Contact details of provider:
Postal: IZA, P.O. Box 7240, D-53072 Bonn, Germany
Phone: +49 228 3894 223
Fax: +49 228 3894 180
Web page: http://www.iza.org
Postal: IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Other versions of this item:
- Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
- Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Discussion Papers of DIW Berlin 899, DIW Berlin, German Institute for Economic Research.
- 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).
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
- E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-06-03 (All new papers)
- NEP-ECM-2009-06-03 (Econometrics)
- NEP-FOR-2009-06-03 (Forecasting)
- NEP-ICT-2009-06-03 (Information & Communication Technologies)
You can help add them by filling out this form.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:CitEc Project, subscribe to its RSS feed for this item.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading lists or Wikipedia pages:Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Fallak).
If references are entirely missing, you can add them using this form.