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Performance of Some Ridge Parameters for Probit Regression: With Application to Swedish Job Search Data
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. (Nationalekonomi och Statistik)
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. (Nationalekonomi och Statistik)ORCID iD: 0000-0002-3416-5896
2013 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 42, no 3, p. 698-710Article in journal (Refereed) Published
Abstract [en]

In ridge regression the estimation of the ridge parameter is an important issue. This paper generalizes some methods for estimating the ridge parameter for probit ridge regression (PRR) model based on the work of Kibria et al. (2011). The performance of these new estimators are judged by calculating the mean square error (MSE) usingMonte Carlo simulations.  In the design of the experiment we chose to vary the sample size and the number of regressors. Furthermore, we generate explanatory variables that are linear combinations of other regressors, which is a common situation in economics. In an empirical application regarding Swedish job search data we also illustrate the benefits of the new method.

Place, publisher, year, edition, pages
2013. Vol. 42, no 3, p. 698-710
Keywords [en]
probit regression; maximum likelihood; multicollinearity; ridge regression; MSE;
National Category
Economics and Business
Research subject
Social Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-16201DOI: 10.1080/03610918.2011.654032ISI: 000311694900014Scopus ID: 2-s2.0-84870266096OAI: oai:DiVA.org:lnu-16201DiVA, id: diva2:466889
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2020-01-24Bibliographically approved

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Locking, HåkanShukur, Ghazi

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CiteExportLink to record
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