Robust block bootstrap panel predictability tests*
Robust block bootstrap panel predictability tests*
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稳健的块引导面板可预测性测试*
作者：
Stephan Smeekes;J. Westerlund
摘要本文开发了两个基于块引导的面板可预测性检验程序，它们在非常一般的条件下是有效的。一些允许的功能，包括横截面的依赖性，异质性预测斜率，持久的预测，和复杂的错误动态，包括跨单位内。第一个测试程序测试是否存在任何可预测性，第二个程序确定可预测性在第一个程序拒绝的情况下保持的单位。通过一个弱单位根框架，允许持久的预测，和一个新的理论，建立渐近有效性的自助。模拟是用来评估我们的测试在小样本的性能，并说明其实施通过实证应用到股票收益。
Abstract This article develops two block bootstrap-based panel predictability test procedures that are valid under very general conditions. Some of the allowable features include cross-sectional dependence, heterogeneous predictive slopes, persistent predictors, and complex error dynamics, including cross-unit endogeneity. While the first test procedure tests if there is any predictability at all, the second procedure determines the units for which predictability holds in case of a rejection by the first. A weak unit root framework is adopted to allow persistent predictors, and a novel theory is developed to establish asymptotic validity of the proposed bootstrap. Simulations are used to evaluate the performance of our tests in small samples, and their implementation is illustrated through an empirical application to stock returns.