BOOTSTRAPPING THE TRACE STATISTIC IN VAR MODELS: MONTE CARLO RESULTS AND APPLICATIONS
通过蒙特卡洛实验比较了普通自助法和平稳自助法在VAR模型迹统计量中的表现，发现平稳自助法在动态设定不足时能改善检验的实证大小，并建议将其用作诊断工具。
ABSTRACT This paper investigates through Monte Carlo experiments both size and power properties of a bootstrapped trace statistic in two prototypical DGPs. The Monte Carlo results indicate that the ordinary bootstrap has similar size and power properties as inference procedures based on asymptotic critical values. Considering empirical size, the stationary bootstrap is found to provide a uniform improvement over the ordinary bootstrap if the dynamics is underspecified. The use of the stationary bootstrap as a diagnostic tool is suggested. In two illustrative examples this seems to work, and again it appears that the bootstrap incorporates the finite‐sample correction required for the asymptotic critical values to apply.