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A Tobit Ridge Regression Estimator
Department of Mathematics, King Khalid University, Saudi Arabia.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistics)
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistics)
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 1, 131-140 p.Article in journal (Refereed) Published
Abstract [en]

This article analyzes the effects of multicollienarity on the maximum likelihood (ML) estimator for the Tobit regression model. Furthermore, a ridge regression (RR) estimator is proposed since the mean squared error (MSE) of ML becomes inflated when the regressors are collinear. To investigate the performance of the traditional ML and the RR approaches we use Monte Carlo simulations where the MSE is used as performance criteria. The simulated results indicate that the RR approach should always be preferred to the ML estimation method.

Place, publisher, year, edition, pages
2014. Vol. 43, no 1, 131-140 p.
Keyword [en]
Multicollinearity, Ridge regression, Tobit model
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:hj:diva-17327DOI: 10.1080/03610926.2012.655881ISI: 000327587100009Scopus ID: 2-s2.0-84889638880Local ID: IHHEFSISOAI: oai:DiVA.org:hj-17327DiVA: diva2:480759
Available from: 2012-01-19 Created: 2012-01-19 Last updated: 2016-11-29Bibliographically approved

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Månsson, KristoferSjölander, PärShukur, Ghazi
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