Towards Empirical Assessments of Controlled Cointegrated Models
从计量经济学家的视角，探讨如何在协整向量自回归模型中应用控制理论和稳定化政策，提出将控制理论导出的新过程视为可观测序列，并引入数据驱动方法对政策目标进行分类，通过新西兰货币政策数据的反事实分析验证了方法的实用性。
ABSTRACT This paper explores control theory and stabilisation policy within the framework of a cointegrated vector autoregressive (VAR) model from the perspective of an econometrician concerned with inference and identification. We demonstrate that a new process derived from control theory should be treated as a series of observables rather than as a latent series. This process can be viewed as being driven by a vector autoregressive moving‐average (VARMA) model, which can, in turn, be interpreted within the framework of structural vector equilibrium correction. We also introduce a data‐driven procedure for classifying intermediate and final policy targets within the model. The practicality and effectiveness of this procedure are demonstrated through a counterfactual policy analysis based on observations of the new process simulated from actual New Zealand monetary policy data.