Properties of the ordinary least squares and stein-rule predictions in linear regression models with proxy variables |
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Authors: | V K Srivastava M Dube |
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Institution: | 1. Department of Statistics, Lucknow University, 226007, Lucknow, INDIA 2. Department of Statistics, Maharshi Dayanand University, 124001, Rohtak, INDIA
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Abstract: | This article considers a linear regression model in which misspecification relates to the use of a stochastic proxy variable.
The analysis indicates the decline in efficiency of the predictions arising from the ordinary least squares and the Stein-rule
estimation procedures when a proxy variable is used in the place of an unobservable variable. However, the performance of
the Stein-rule predictions is still found to be better than the ordinary least squares predictions over a broad range of k,
the characterizing scalar of the Stein-rule estimator. |
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Keywords: | |
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