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二元 AR(1) 过程因果性检验的经验似然方法AI 解读

Testing for causality is of critical importance for many econometric applications. For bivariate AR(1) processes, the limit distributions of causality tests based on least squares estimation depend on the presence of nonstationary processes. When nonstationary processes are present, the limit distributions of such tests are usually very complicated, and the full-sample bootstrap method becomes inconsistent as pointed out in Choi (2005, Statistics and Probability Letters 75,…

非平稳双重 AR(1) 模型的渐近推断AI 解读

We investigate the nonstationary double ar(1) model, where ω > 0, α > 0, the ηt are independent standard normal random variables and Elog |