This paper studies seemingly unrelated linear models with integrated regressors and stationary errors.

In this paper we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts.

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients...