Open AccessEffects of Correlation between the Error Term and Autocorrelation on Some Estimators in a System of Regression Equations
Author(s) -
Samuel Olayemi Olanrewaju
Publication year - 2020
Publication title -
global journal of science frontier research
Language(s) - English
Resource type - Journals
eISSN - 2249-4626
pISSN - 0975-5896
DOI - 10.34257/gjsfrfvol20is4pg57
Subject(s) - multicollinearity , autocorrelation , mathematics , estimator , statistics , regression analysis , term (time) , regression , standard error , independence (probability theory) , correlation , linear regression , econometrics , physics , geometry , quantum mechanics
Seemingly unrelated regression model developed to handle the problem of correlation among the error terms of a system of the regression equations is still not without a challenge, where each regression equation must satisfy the assumptions of the standard regression model. When dealing with time-series data, some of these assumptions, especially that of independence of the regressors and error terms leading to multicollinearity and autocorrelation respectively, are often violated. This study examined the effects of correlation between the error terms and autocorrelation on the performance of seven estimators and identify the estimator that yields the most preferred estimates under the separate or joint influence of the two correlation effects considered by the researcher. A two-equation model was considered, in which the first equation had multicollinearity and autocorrelation problems while the second one had no correlation problem. The error terms of the two equations were also correlated. The levels of correlation between the error terms and autocorrelation were specified between -1 and +1 at interval of 0.2 except when it approached unity.