This paper develops a new covariance-based test of orthogonality that may beattractive when regressors have roots close or equal to unity. In this case standard regression-based orthogonality tests can suffer from (i) size distortions and (ii) uncertainty regarding the appropriate model in which...

This paper develops a new covariance-based test of orthogonality that may be attractive when regressors have roots close or equal to unity. In this case standard regression-based orthogonality tests can suffer from (i) size distortions and (ii) uncertainty regarding the appropriate model in...

This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regression-based tests when conditioning variables have roots close or equal to unity. In this case standard...

This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regression-based tests when conditioning variables have roots close or equal to unity. In this case standard...

This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regression-based tests when conditioning variables have roots close or equal to unity. In this case standard...