Simulation Evidence on Theory‐based and Statistical Identification under Volatility Breaks
通过蒙特卡洛模拟，评估基于理论和统计识别方法在货币政策标准模型中量化真实结构关系的准确性，并讨论如何结合两种识别信息。
Abstract Beside a priori theoretical assumptions on instantaneous or long‐run effects of structural shocks, sign restrictions have become a prominent means for structural vector autoregressive (SVAR) analysis. Moreover, changes in second order moments of systems of time series can be fruitfully exploited for identification purposes in SVARs. By means of Monte Carlo studies, we examine to what degree theory‐based and statistical identification approaches offer an accurate quantification of the true structural relations in a standard model for monetary policy analysis. Subsequently, we discuss how identifying information from theory‐based and statistical approaches can be combined on the basis of a low‐dimensional empirical model of US monetary policy.