Scandinavian Working Papers in Economics

HUI Working Papers,
HUI Research

No 56: Performance of Some Ridge Parameters for Probit Regression: with Application on Swedish Job Search Data

Håkan Locking, Kristofer Månsson () and Ghazi Shukur
Additional contact information
Håkan Locking: Linnaeus University, Postal: Department of Economics and Statistics, Linnaeus University, Sweden
Kristofer Månsson: Department of Economics, Postal: Finance and Statistics, Jönköping University, Sweden
Ghazi Shukur: Linnaeus University, Postal: Department of Economics and Statistics, Linnaeus University, Sweden and, Department of Economics, Finance and Statistics, Jönköping University, Sweden.

Abstract: 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) using Monte 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.

Keywords: probit regression; maximum likelihood; multicollinearity; ridge regression; MSE; job search

JEL-codes: C21

18 pages, February 16, 2012

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