Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Some ridge regression estimators for the zero-inflated Poisson model
Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistik)
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistik)
2013 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 40, no 4, 721-735 p.Article in journal (Refereed) Published
Abstract [en]

The zero-inflated Poisson regression model is commonly used when analyzing economic data that come in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression (RR) estimators and some methods for estimating the ridge parameter k for a non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error and mean absolute error are considered as the performance criteria. The simulation study shows that some estimators are better than the commonly used maximum-likelihood estimator and some other RR estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for practitioners.

Place, publisher, year, edition, pages
2013. Vol. 40, no 4, 721-735 p.
Keyword [en]
count data, estimation, MSE, MAE, multicollinearity, ridge regression, simulation, zero-inflated Poisson
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:hj:diva-20145DOI: 10.1080/02664763.2012.752448Local ID: IHHEFSISOAI: oai:DiVA.org:hj-20145DiVA: diva2:580630
Available from: 2012-12-23 Created: 2012-12-23 Last updated: 2014-03-06Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Shukur, GhaziMånsson, Kristofer
By organisation
JIBS, Economics, Finance and Statistics
In the same journal
Journal of Applied Statistics
Social Sciences

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 263 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf