A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries
AbstractA new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. This new source of data holds both many advantages as well as disadvantages, which are discussed through the use of daily and weekly data. Daily and weekly data are employed to show the effect of aggregation as it pertains to Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship between the online traffic to a specific website and the search volumes for certain keyword search queries, along with the rankings of that specific website for those queries. The purpose of this paper is to point out the benefits and the pitfalls of a potential new source of data that lacks transparency in regards to the original level data, which is due to the normalization and scaling procedure utilized by Google.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 18899.
Date of creation: 11 Nov 2009
Date of revision: 27 Nov 2009
Poisson Regression; Search Engine; Google Insights; Aggregation; Normalization Effects; Scaling Effects;
Other versions of this item:
- Heather R. Tierney & Bing Pan, 2012. "A poisson regression examination of the relationship between website traffic and search engine queries," Netnomics, Springer, vol. 13(3), pages 155-189, October.
- Tierney, Heather L.R. & Pan, Bing, 2010. "A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries," MPRA Paper 32117, University Library of Munich, Germany, revised 08 Jul 2011.
- Tierney, Heather L. R. & Pan, Bing, 2009. "A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries," MPRA Paper 18413, University Library of Munich, Germany.
- Tierney, Heather L.R. & Pan, Bing, 2009. "A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries," MPRA Paper 19895, University Library of Munich, Germany, revised 10 Jan 2010.
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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- Joseph E. Gagnon, 2008.
"Inflation regimes and inflation expectations,"
Federal Reserve Bank of St. Louis, issue May, pages 229-243.
- Joseph E. Gagnon, 1997. "Inflation regimes and inflation expectations," International Finance Discussion Papers 581, Board of Governors of the Federal Reserve System (U.S.).
- Joseph E. Gagnon, 1997. "Inflation Regimes and Inflation Expectations," RBA Research Discussion Papers rdp9701, Reserve Bank of Australia.
- Askitas, Nikos & Zimmermann, Klaus F., 2009.
"Google Econometrics and Unemployment Forecasting,"
IZA Discussion Papers
4201, Institute for the Study of Labor (IZA).
- 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," Research Notes of the German Council for Social and Economic Data 41, German Council for Social and Economic Data (RatSWD).
- Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Discussion Papers of DIW Berlin 899, DIW Berlin, German Institute for Economic Research.
- Michener, Ron & Tighe, Carla, 1992. "A Poisson Regression Model of Highway Fatalities," American Economic Review, American Economic Association, vol. 82(2), pages 452-56, May.
- Rapach, David E, 2003. " International Evidence on the Long-Run Impact of Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(1), pages 23-48, February.
- Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
- John J. Seater & Robert J. Rossana, .
"Temporal Aggregation and Economic Time Series,"
Working Paper Series
19, North Carolina State University, Department of Economics.
- Cameron, A.C. & Windmeijer, F.A.G., 1993.
"R-Squared Measures for Count Data Regression Models with Applications to Health Care Utilization,"
93-24, California Davis - Institute of Governmental Affairs.
- Cameron, A Colin & Windmeijer, Frank A G, 1996. "R-Squared Measures for Count Data Regression Models with Applications to Health-Care Utilization," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 209-20, April.
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