Alkhamisi, Mahdi A. (Department of Mathematics, Salahaddin University; Department of economics and Statistics, Jönköping University) Shukur, Ghazi () (Centre for Labour Market Policy Research (CAFO))
Abstract
A number of procedures have been developed for finding biased estimators of regression parameters. One of these procedures is the ridge regression. In this paper, a new approach to obtain the ridge parameter (K) is suggested and then evaluated by Monte Carlo simulations. A large number of different models were investigated, where the number of observations, the strength of correlation between the explanatory variables and the distribution of the error terms have been varied. The mean squared of error (MSE) is used as criterion to examine the performance of the proposed estimators when compared with other well-known estimators. Under certain conditions, it is shown that at least one of the proposed estimators have a smaller (MSE) than the ordinary least squared estimator (OLS) and Hoerl and Kennard (1970a) estimator (HK).
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Centre for Labour Market Policy Research (CAFO), School of Management and Economics, Växjö University in its series CAFO Working Papers with number
2006:1.
Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation