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A poisson regression examination of the relationship between website traffic and search engine queries

  • Heather R. Tierney

    ()

  • Bing Pan

    ()

A new area of research involves the use of normalized and scaled Google search volume data to predict economic activity. This new source of data holds both many advantages as well as disadvantages. Daily and weekly data are employed to show the effect of aggregation in 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 search queries, along with the rankings of that 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 raw data, which is due to the normalization and scaling procedures utilized by Google. Copyright Springer Science+Business Media New York 2012

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File URL: http://hdl.handle.net/10.1007/s11066-013-9072-x
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Article provided by Springer in its journal NETNOMICS: Economic Research and Electronic Networking.

Volume (Year): 13 (2012)
Issue (Month): 3 (October)
Pages: 155-189

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Handle: RePEc:kap:netnom:v:13:y:2012:i:3:p:155-189
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=102537

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  1. Joseph E. Gagnon, 1997. "Inflation regimes and inflation expectations," International Finance Discussion Papers 581, Board of Governors of the Federal Reserve System (U.S.).
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  5. 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.
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