外生不确定性与使用外部工具变量的结构向量自回归模型的识别

Exogenous uncertainty and the identification of structural vector autoregressions with external instruments

Journal of Applied Econometrics · 2019
被引 49
人大 AABS 3

中文导读

研究了用外部工具变量识别结构向量自回归模型的充要条件,并应用于分析金融和宏观经济不确定性是否是美国实际经济活动的外生驱动因素。

Abstract

Summary We provide necessary and sufficient conditions for the identification (point‐identification) of structural vector autoregressions (SVARs) with external instruments considering the case in which r instruments are used to identify g structural shocks of interest, r ≥ g ≥ 1. Novel frequentist estimation methods are discussed by considering both a “partial shocks” identification strategy, where only g structural shocks are of interest and are instrumented, and a “full shocks” identification strategy, where despite g structural shocks being instrumented, all n = g +( n − g ) structural shocks of the system can be identified under certain conditions. The suggested approach is applied to investigate empirically whether financial and macroeconomic uncertainty can be approximated as exogenous drivers of US real economic activity, or rather as endogenous responses to first moment shocks, or both. We analyze whether the dynamic causal effects of nonuncertainty shocks on macroeconomic and financial uncertainty are significant in the period after the global financial crisis.

外生不确定性结构向量自回归外部工具冲击识别