When a finite order vector autoregressive model is fitted to VAR($\infty$) data the asymptotic distribution of statistics obtained via smooth functions of least-squares estimates requires care. L\"utkepohl and Poskitt (1991) provide a closed-form expression for the limiting distribution of (structural) impulse responses for sieve VAR models based on the Delta method. Yet, numerical simulations have shown that confidence intervals built in such way appear overly conservative. In this note I argue that these results stem naturally from the limit arguments used in L\"utkepohl and Poskitt (1991), that they manifest when sieve inference is improperly applied, and that they can be "remedied" by either using bootstrap resampling or, simply, by using standard (non-sieve) asymptotics.
翻译:当一个定序矢量自动递减模型与VAR($\infty$)数据相适应时,通过最不平和的平滑函数得出的统计数字的无规律分布需要小心谨慎。L\“utkepohl和Poskitt(1991年)为限制基于三角洲方法的筛选VAR模型的(结构性)脉冲反应的分布提供了封闭式表达方式。然而,数字模拟表明,以这种方式建立的信任间隔似乎过于保守。在本说明中,我争辩说,这些结果自然来自L\“utkepohl和Poskitt(1991年)”中使用的有限参数,它们表现在不适当地应用细微引用时,并且它们可以“补救”,要么使用靴式采样,要么简单地使用标准(非隐蔽)的安抚办法。