The estimation uncertainty of permanent-transitory decompositions in co-integrated systems
研究了协整向量自回归框架下Stock-Watson和Gonzalo-Granger永久-暂时分解的估计不确定性，提出通过条件于观测数据构建暂时成分估计的置信区间，并用美国产出缺口数据演示。
The topic of this article is the estimation uncertainty of the Stock–Watson and Gonzalo–Granger permanent-transitory decompositions in the framework of the co-integrated vector autoregression. We suggest an approach to construct the confidence interval of the transitory component estimate in a given period (e.g., the latest observation) by conditioning on the observed data in that period. To calculate asymptotically valid confidence intervals, we use the delta method and two bootstrap variants. As an illustration, we analyze the uncertainty of (U.S.) output gap estimates in a system of output, consumption, and investment.