Google Econometrics and Unemployment Forecasting
SSRN Electronic JournalPublished 1 January 2009Open access
Nikos Askitas, Klaus F. Zimmermann
Citations143
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
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
MathematicsMedicineEconomics, Econometrics and Finance
EconometricaCo-Integration and Error Correction: Representation, Estimation, and Testing
31,933 Citations1987Robert F. Engle, C. W. J. Granger
NatureDetecting influenza epidemics using search engine query data
4,406 Citations2008Jeremy Ginsberg, Matthew H. Mohebbi +4 more
A method of analysing large numbers of Google search queries to track influenza-like illness in a population and accurately estimate the current level of weekly influenza activity in each region of the United States with a reporting lag of about one day is presented.
Econstor (Econstor)Im Angesicht der Krise: US-Präsidentschaftswahlen in transnationaler Sicht
11 Citations2008Amélie F. Constant, Klaus F. Zimmermann
Econstor (Econstor)Schadensbegrenzung oder Kapriolen wie im Finanzsektor?
5 Citations2008Klaus F. Zimmermann