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

Heather L.R. Tierney () and Bing Pan

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Poisson Regression; Search Engine; Google Insights; Aggregation (search for similar items in EconPapers)
JEL-codes: C43 D83 C25 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ict
Date: 2009-11-04
View list of references

Downloads: (external link)
http://mpra.ub.uni-muenchen.de/18413/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:pra:mprapa:18413

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany
Address: Schackstr. 4, D-80539 Munich, Germany
Contact information at EDIRC.
Series data maintained by Ekkehart Schlicht ().