检验 Proxy-VARs 中的强外生性

IF 9.9 3区 经济学 Q1 ECONOMICS Journal of Econometrics Pub Date : 2024-10-01 DOI:10.1016/j.jeconom.2024.105876
Martin Bruns , Sascha A. Keweloh
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引用次数: 0

摘要

代理变量作为确定结构性 VAR 模型不可或缺的工具,已得到广泛重视。与工具变量类似,代理变量必须是外生的,即与所有非目标冲击无关。评估代理变量的外生性历来依赖于经济学论据而非统计检验。我们认为,构建常用替代变量的经济学原理与更强的外生性形式是一致的。具体来说,代理变量通常是作为不包含任何非目标冲击预期值信息的变量构建的。我们展示了无需额外识别假设即可检验这种增强的代理外生性概念的条件。
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Testing for strong exogeneity in Proxy-VARs
Proxy variables have gained widespread prominence as indispensable tools for identifying structural VAR models. Analogous to instrumental variables, proxies need to be exogenous, i.e. uncorrelated with all non-target shocks. Assessing the exogeneity of proxies has traditionally relied on economic arguments rather than statistical tests. We argue that the economic rationale underlying the construction of commonly used proxy variables aligns with a stronger form of exogeneity. Specifically, proxies are typically constructed as variables not containing any information on the expected value of non-target shocks. We show conditions under which this enhanced concept of proxy exogeneity is testable without additional identifying assumptions.
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来源期刊
Journal of Econometrics
Journal of Econometrics 社会科学-数学跨学科应用
CiteScore
8.60
自引率
1.60%
发文量
220
审稿时长
3-8 weeks
期刊介绍: The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.
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