A note on testing the nested structure in multivariate regression models

In this article we propose a simple method of identifying, at an earlier st age of analysis, the nested structure among the coefficient matrices in mul tivariate regression models. When the limiting distribution of the estimato rs of the coefficient matrices are jointly normal, the Wald type statistics based on the proposed method is asymptotically a chi-squared random variab le. A numerical example that arises in cointegration analysis is provided t o illustrate the method and a small simulation study is provided to illustr ate its effectiveness.