Advances and Applications in Statistics
Volume 31, Issue 2, Pages 103 - 124
(December 2012)
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AN APPLICATION OF GENERALIZED MAXIMUM ENTROPY AND SOME BIASED ESTIMATION METHODS FOR THE ALMON DISTRIBUTED LAG MODEl: BOOTSTRAP EFFICIENCY
H. Altan Çabuk and Fikri Akdeniz
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Abstract: In this study, an unrestricted finite distributed lag model is used to obtain the parameter estimates of an econometric model when the matrix is ill-conditioned. For this aim, linear regression model is reparameterized and polynomial distributed lag model or Almon model is used and unknown parameters are estimated using maximum entropy principle, ridge regression, Liu estimation methods. Mean squared error values of the estimators are estimated by the bootstrap method. We compared the generalized maximum entropy (GME) estimator, Almon estimator, ridge regression estimator and Liu estimator with OLS estimator on the widely analyzed dataset on consumption function. |
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