利用向量自回归估计结构震级的研究进展

IF 1 4区 经济学 Q3 ECONOMICS
C. Baumeister, James D. Hamilton
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引用次数: 9

摘要

本文综述了从向量自回归(VAR)中得出结构结论的最新进展,为先验知识的作用提供了一个统一的视角。我们将传统的识别方法描述为声称拥有关于结构模型的精确先验信息,并提出贝叶斯推理作为承认先验信息不完美或存在错误的一种方式。我们从频率学家和贝叶斯的角度提出了对VAR的结果报告方式的担忧,VAR是使用符号和其他限制进行设置识别的。我们提请注意在估计结构弹性时一个常见但以前未被识别的错误,并展示了如何正确估计弹性,即使在只知道单个结构冲击的影响的情况下也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ADVANCES IN USING VECTOR AUTOREGRESSIONS TO ESTIMATE STRUCTURAL MAGNITUDES
This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.
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来源期刊
Econometric Theory
Econometric Theory MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
1.90
自引率
0.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Since its inception, Econometric Theory has aimed to endow econometrics with an innovative journal dedicated to advance theoretical research in econometrics. It provides a centralized professional outlet for original theoretical contributions in all of the major areas of econometrics, and all fields of research in econometric theory fall within the scope of ET. In addition, ET fosters the multidisciplinary features of econometrics that extend beyond economics. Particularly welcome are articles that promote original econometric research in relation to mathematical finance, stochastic processes, statistics, and probability theory, as well as computationally intensive areas of economics such as modern industrial organization and dynamic macroeconomics.
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