Estimation of Seemingly Unrelated Regressions with Vector Autoregressive Errors

Publisher Website
Google Scholar
Abstract
We derive an asymptotically efficient method of estimating the coefficients of systems of seemingly unrelated regression equations when a first-order vector autoregressive error specification is hypothesized. This error specification is shown to contain several commonly used specifications as special cases. A Monte Carlo experiment was performed to examine the finite sample performance of our estimator in comparison with several other estimators. The general results were that the new estimator performed relatively well.

This publication has 0 references indexed in Scilit: