Nicol, Christopher: Shrinkage Estimators for the Nonlinear Regression Model
World Conference Econometric Society, 2000, Seattle

S. E. Ahmed, University of Regina
Christopher Nicol, University of Regina
Shrinkage Estimators for the Nonlinear Regression Model
Session: C-8-10  Monday 14 August 2000  by Nicol, Christopher
In this paper, we discuss various large sample estimation techniques in a nonlinear regression model. We propose estimators on the basis of preliminary tests of significance and James-Stein rule. The properties of these estimators are studied in the problem of estimating regression coefficients in the multiple regression model when it is a priori suspected that the coefficients may be restricted to a subspace.
A simulation based on a demand for money model shows the superiority of the positive-part shrinkage estimator over a range of economically meaningful parameter values. This indicates that this estimator can be usefully employed in important practical situations.
Submitted paper full-text in .pdf


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