Biased
estimation methods are more desirable than two stage least squares estimation
for simultaneous equations models suffering from the problem of
multicollinearity. This problem is also handled by using some prior information.
Taking account of this knowledge, we recommend two stage modified ridge
estimator. The new estimator can also be evaluated as an alternative to the
previously proposed two stage ridge estimator. The widespread performance
criterion, mean square error, is taken
into consideration to compare the two stage modified ridge, two stage ridge and
two stage least squares estimators. A real life data analysis is investigated
to prove the theoretical results in practice. In addition, the
intervals of the biasing parameter which provide the superiority of the two
stage modified ridge estimator are determined
with the help of figures. The
researchers who deal with simultaneous systems with multicollinearity can opt for
the two stage modified ridge estimator.
Modified ridge estimator Multicollinearity Simultaneous equations model Two stage least squares
Primary Language | English |
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Subjects | Mathematical Sciences |
Journal Section | Research Articles |
Authors | |
Publication Date | December 1, 2018 |
Submission Date | January 11, 2018 |
Acceptance Date | March 26, 2018 |
Published in Issue | Year 2018 Volume: 22 Issue: 6 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.