Comparisons of the alternative biased estimators for the distributed lag models

ABSTRACT The finite distributed lag models include highly correlated variables as well as lagged and unlagged values of the same variables. Some problems are faced for this model when applying the ordinary least squares (OLS) method or econometric models such as Almon and Koyck models. The primary aim of this study is to compare performances of alternative estimators to the OLS estimator defined by combining the Almon estimator with some estimators using Almon (1965) data. A simulation study with different model parameters is performed and the estimators are compared according to the root mean square error (RMSE) and prediction mean square error (PMSE).

[1]  B. M. Kibria,et al.  Performance of Some New Ridge Regression Estimators , 2003 .

[2]  G. Maddala.  Ridge Estimators for Distributed Lag Models , 1974 .

[3]  Selahattin Kaçıranlar,et al.  COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR , 2001 .

[4]  Jakob B. Madsen.  Book review: Basic Econometrics, Damodar N. Gujarati, McGraw-Hill, New York, 1995 , 1998 .

[5]  P. Trivedi,et al.  On Using Ridge-Type Estimators for a Distributed Lag Model , 2009 .

[6]  A. E. Hoerl,et al.  Ridge regression: biased estimation for nonorthogonal problems , 2000 .

[7]  Michael R. Baye,et al.  Combining ridge and principal component regression:a money demand illustration , 1984 .

[8]  P. Frost.  Some Properties of the Almon Lag Technique When One Searches for Degree of Polynomial and Lag , 1975 .

[9]  Liu Kejian,et al.  A new class of blased estimate in linear regression , 1993 .

[10]  Hrishikesh D. Vinod,et al.  Recent Advances in Regression Methods. , 1983 .

[11]  Tanja Neumann,et al.  Introduction To The Theory And Practice Of Econometrics , 2016 .

[12]  A. E. Hoerl,et al.  Ridge Regression: Applications to Nonorthogonal Problems , 1970 .

[13]  B. M. Golam Kibria,et al.  Please Scroll down for Article Communications in Statistics -simulation and Computation on Some Ridge Regression Estimators: an Empirical Comparisons on Some Ridge Regression Estimators: an Empirical Comparisons , 2022 .

[14]  Shirley Almon.  The Distributed Lag Between Capital Appropriations and Expenditures , 1965 .

[15]  Aslam Muhammad,et al.  Performance of Kibria's Method for the Heteroscedastic Ridge Regression Model: Some Monte Carlo Evidence , 2014, Commun. Stat. Simul. Comput..

[16]  Ji Fu,et al.  A New Class of Biased Estimate , 2013 .

[17]  J. Viel,et al.  Some methods to address collinearity among pollutants in epidemiological time series. , 1997, Statistics in medicine.

[18]  E. Ziegel.  Introduction to the Theory and Practice of Econometrics , 1989 .

[19]  Dwight M. Jaffee,et al.  A note on the estimation of polynomial distributed lags , 1971 .

[20]  I. Fisher.  Income in theory and income taxation in practice , 1937 .

[21]  B. M. Golam Kibria,et al.  Journal of Modern Applied Statistical Methods Some Ridge Regression Estimators and Their Performances Some Ridge Regression Estimators and Their Performances , 2022 .

[22]  Hu Yang,et al.  A new Liu-type estimator in linear regression model , 2012 .

[23]  W. Massy.  Principal Components Regression in Exploratory Statistical Research , 1965 .

[24]  D. Lindley,et al.  Bayes Estimates for the Linear Model , 1972 .

[25]  B. F. Swindel.  Good ridge estimators based on prior information , 1976 .

[26]  Fikri Akdeniz,et al.  On the almost unbiased generalized liu estimator and unbiased estimation of the bias and mse , 1995 .

[27]  Ridge Estimators for Distributed Lag Models , 1974 .

[28]  Singiresu S. Rao.  Engineering Optimization : Theory and Practice , 2010 .