代理(统计)
计量经济学
符号(数学)
自回归模型
推论
工具变量
贝叶斯概率
变量(数学)
计算机科学
计算
鉴定(生物学)
经济
数学
算法
人工智能
数学分析
机器学习
生物
植物
作者
Robin Braun,Ralf Brüggemann
标识
DOI:10.1080/07350015.2022.2104857
摘要
We discuss combining sign restrictions with information in external instruments (proxy variables) to identify structural vector autoregressive (SVAR) models. In one setting, we assume the availability of valid external instruments. Sign restrictions may then be used to identify further orthogonal shocks, or as an additional piece of information to pin down the shocks identified by the external instruments more precisely. In a second setting, we assume that proxy variables are only “plausibly exogenous” and suggest various types of inequality restrictions to bound the relation between structural shocks and the external variable. This can be combined with conventional sign restrictions to further narrow down the set of admissible models. Within a proxy-augmented SVAR, we conduct Bayesian inference and discuss computation of Bayes factors. They can be useful to test either the sign- or IV restrictions as overidentifying. We illustrate the usefulness of our methodology in estimating the effects of oil supply and monetary policy shocks.
科研通智能强力驱动
Strongly Powered by AbleSci AI