ON THE ALTERNATIVE LONG-RUN VARIANCE RATIO TEST FOR A UNIT ROOT
研究了长期方差的一致和不一致估计对基于冯·诺依曼比推广的单位根检验的影响，发现不一致估计能减少尺寸扭曲但损失检验功效，并指出结合两种估计可平衡尺寸与功效。
This paper investigates the effects of consistent and inconsistent long-run variance estimation on a test for a unit root, based on the generalization of the von Neumann ratio. The results from the Monte Carlo experiments suggest that the unit root tests based on an inconsistent estimator have less size distortion and more stability of size across different autocorrelation specifications as compared to the tests based on a consistent estimator. This improvement in size property, however, comes at the cost of a loss in power. The finite-sample power, in addition to the local asymptotic power, of the tests with an inconsistent estimator is shown to be much lower than that of conventional tests. This finding can be well generalized to the test for cointegration in a multivariate system. The paper also points out that combining consistent and inconsistent estimators in the long-run variance ratio test is one possibility of balancing the size and power.The authors thank two anonymous referees, Pentti Saikkonen, and participants of the 2004 Midwest Econometrics Group meetings, 2005 Spring Meetings of The Japanese Economic Association, and a workshop at Vanderbilt University for helpful comments and suggestions.