We propose generalized DWH specification tests which simultaneously compare three or more likelihood-based estimators in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for Garch models and in many empirically relevant macro and finance applications involving Vars and multivariate regressions. We determine the rank of the differences between the estimators' asymptotic covariance matrices under correct specification, and take into account that some parameters remain consistently estimated under distributional misspecification. We provide finite sample results through Monte Carlo simulations. Finally, we analyze a structural Var proposed to capture the relationship between macroeconomic and financial uncertainty and the business cycle.

中文翻译：

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非高斯最大似然估计量的规范测试

我们提出了广义 DWH 规范测试，它同时比较多元条件异方差动态回归模型中的三个或更多基于似然的估计量。我们的测试对于Garch模型以及许多涉及Var和多元回归的经验相关的宏观和金融应用都很有用。我们确定在正确规范下估计量的渐近协方差矩阵之间差异的等级，并考虑到在分布错误规范下某些参数保持一致估计。我们通过蒙特卡罗模拟提供有限样本结果。最后，我们分析一个结构Var 建议捕捉宏观经济和金融不确定性与商业周期之间的关系。