It has been known since Elliott (1998) that standard methods of inference on cointegrating relationships break down entirely when autoregressive roots are near but not exactly equal to unity. We consider this problem within the framework of a structural VAR, arguing this it is as much a problem of identification failure as it is of inference. We develop a characterisation of cointegration based on the impulse response function, which allows long-run equilibrium relationships to remain identified even in the absence of exact unit roots. Our approach also provides a framework in which the structural shocks driving the common persistent components continue to be identified via long-run restrictions, just as in an SVAR with exact unit roots. We show that inference on the cointegrating relationships is affected by nuisance parameters, in a manner familiar from predictive regression; indeed the two problems are asymptotically equivalent. By adapting the approach of Elliott, M\"uller and Watson (2015) to our setting, we develop tests that robustly control size while sacrificing little power (relative to tests that are efficient in the presence of exact unit roots).
翻译:自从Elliott(1998)以来,已经知道当自回归根接近但不完全等于1时,协整关系的标准推断方法完全失效。我们在结构性VAR框架内考虑了这个问题,认为这既是一个识别失败的问题,也是一个推断问题。我们基于脉冲响应函数开发了一个协整特征描述,即使在没有确切单位根的情况下,仍可以保持长期均衡关系的识别。我们的方法还提供了这样一个框架,即驱动常见持久组成部分的结构性冲击通过长期限制仍然被识别,就像在具有确切单位根的SVAR中一样。我们表明,协整关系的推断受到干扰参数的影响,这种影响方式类似于预测回归;实际上,这两个问题在渐近意义下是等效的。通过调整Elliott,Müller和Watson(2015)的方法,我们开发出能够牺牲较少功率(相对于在具有确切单位根的情况下有效的测试)的抗干扰性测试。