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A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries

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Author Info
Tierney, Heather L. R.
Pan, Bing

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Abstract

A new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. 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. Daily and weekly data are used to discuss the effects that normalization, scaling, and aggregation have on the empirical findings, which are frequency-dependent.

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File URL: http://mpra.ub.uni-muenchen.de/18413/
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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 18413.

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Date of creation: 04 Nov 2009
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Handle: RePEc:pra:mprapa:18413

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Related research
Keywords: Poisson Regression; Search Engine; Google Insights; Aggregation;

Find related papers by JEL classification:
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

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References listed on IDEAS
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  1. Rossana, Robert J & Seater, John J, 1995. "Temporal Aggregation and Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 441-51, October.
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This page was last updated on 2009-12-9.

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