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The Predictive Performance Evaluation of Biased Regression Predictors With Correlated Errors
Author(s) -
Dawoud Issam,
Kaçiranlar Selahattin
Publication year - 2015
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2337
Subject(s) - multicollinearity , estimator , regression , statistics , regression analysis , econometrics , sample (material) , cross sectional regression , regression diagnostic , linear regression , mathematics , computer science , polynomial regression , chemistry , chromatography
When the interdependence of disturbances is present in a regression model, the pattern of sample residuals contains information which is useful in the prediction of post‐sample drawings and when multicollinearity among regressors is also present, it is useful to use biased regression estimators. This information is exploited in the biased predictors derived here. Also, the predictive performance of various biased predictors with correlated errors is discussed and all pair‐wise comparisons are made among these predictors. The theoretical results are illustrated by a numerical example. Copyright © 2015 John Wiley & Sons, Ltd.