Bootstrap and Asymptotic Tests of Long‐run Relationships in Cointegrated Systems
针对协整向量假设检验在小样本下偏差严重的问题，本文提出一种自助法替代方案，并通过蒙特卡洛实验评估其表现，进而设计一种结合渐近检验与自助法的联合检验，以同时控制第一类错误和第二类错误。
Hypothesis testing on cointegrating vectors based on the asymptotic distributions of the test statistics are known to suffer from severe small sample size distortion. In this paper an alternative bootstrap procedure is proposed and evaluated through a Monte Carlo experiment, finding that the Type I errors are close to the nominal signficance levels but power might be not entirely adequate. It is then shown that a combined test based on the outcomes of both the asymptotic and the bootstrap tests will have both correct size and low Type II error, therefore improving the currently available procedures.