无理性预期的时刻条件模型的稳健推断

IF 9.9 3区 经济学 Q1 ECONOMICS
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引用次数: 0

摘要

使用理性预期(RE)结构模型的应用研究人员经常会遇到规范错误的经验证据。在本文中,我们考虑了一个通用动态模型,该模型是由一个无条件矩限制向量构成的。我们假定该模型在 RE 条件下存在全局性的规范错误,因此在经验上存在缺陷,而这种缺陷在计量经济学上并不明显。我们放宽 RE 限制,允许主观信念与数据生成概率(DGP)模型不同,同时仍保持矩条件在经济行为主体的主观信念下得到满足。我们使用相对于 RE 的发散统计量来约束主观概率集。这种形式的误规范在很大程度上改变了计量经济学的识别和推断,从而使我们为各种集合识别函数构建了稳健的置信集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust inference for moment condition models without rational expectations

Applied researchers using structural models under rational expectations (RE) often confront empirical evidence of misspecification. In this paper we consider a generic dynamic model that is posed as a vector of unconditional moment restrictions. We suppose that the model is globally misspecified under RE, and thus empirically flawed in a way that is not econometrically subtle. We relax the RE restriction by allowing subjective beliefs to differ from the data-generating probability (DGP) model while still maintaining that the moment conditions are satisfied under the subjective beliefs of economic agents. We use statistical measures of divergence relative to RE to bound the set of subjective probabilities. This form of misspecification alters econometric identification and inferences in a substantial way, leading us to construct robust confidence sets for various set identified functionals.

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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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