Abstract
In linear regression model, the superiority of ordinary least squares estimator (OLSE) will be failed when there exist multi-collinearity problems. Based on the class of generalized shrunken least squares (GSLS) estimators suggested by Wang (1990), this article proposes a two-stage shrunken least squares estimator and discusses its superiority theoretically, and finally verifies the results by numerical simulations.
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