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A Poisson ridge regression Estimator
Jönköping University.
Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics. Jönköping University. (Nationalekonomi och Statistik)ORCID iD: 0000-0002-3416-5896
2011 (English)In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 28, no 4, 1475-1481 p.Article in journal (Refereed) Published
Abstract [en]

The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression estimator (PRR) as a remedy to the problem of instability of the traditional ML method. To investigate the performance of the PRR and the traditional ML approaches for estimating the parameters of the Poisson regression model, we calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR method outperforms the traditional ML estimator in all of the different situations evaluated in this paper.

Place, publisher, year, edition, pages
2011. Vol. 28, no 4, 1475-1481 p.
Keyword [en]
Poisson regression, Maximum likelihood, Ridge regression, MSE, Monte Carlo simulations, Multicollinearity
National Category
Economics and Business
Research subject
Economy
Identifiers
URN: urn:nbn:se:lnu:diva-16191DOI: 10.1016/j.econmod.2011.02.030OAI: oai:DiVA.org:lnu-16191DiVA: diva2:466874
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2016-12-14Bibliographically approved

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Shukur, Ghazi
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