Expectations, Learning and Macroeconomic Persistence
Expectations, Learning and Macroeconomic Persistence
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期望、学习和宏观经济持久性
DOI：
10.2139/ssrn.833945
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Fabio Milani
中科院分区：
文献类型：
--
作者：
Fabio Milani
本文给出了一个带有学习的估计模型，并证明了学习可以提高流行的货币动态随机一般均衡模型的拟合度，并内生产生现实的持续性水平。本文从一种不可知论的观点出发，开发了一个模型，该模型嵌套了学习和一些持久性的结构性来源，如消费习惯形成和通胀指数化，这些都是具有理性预期的货币模型中通常需要的，以匹配宏观经济变量的持久性。我用基于似然的贝叶斯方法来估计模型，这种方法允许结合经济的“深层”参数来估计学习增益系数。实证结果表明，当学习取代理性预期时，习惯的估计程度和指数化程度下降到接近于零。这表明，在模型经济中，持久性主要来自预期和学习。后验模型概率表明，带学习的规范比带理性预期的规范符合得更好。最后，如果学习而不是机械的持久力来源提供了更合适的经济表现，那么隐含的最优政策将不同。政策制定者还将因错误指定私人预期的形成而招致巨额成本。
This paper presents an estimated model with learning and provides evidence that learning can improve the fit of popular monetary DSGE models and endogenously generate realistic levels of persistence. The paper starts with an agnostic view, developing a model that nests learning and some of the structural sources of persistence, such as habit formation in consumption and inflation indexation, that are typically needed in monetary models with rational expectations to match the persistence of macroeconomic variables. I estimate the model by likelihood-based Bayesian methods, which allow the estimation of the learning gain coefficient jointly with the "deep" parameters of the economy. The empirical results show that when learning replaces rational expectations, the estimated degrees of habits and indexation drop near zero. This ?nding suggests that persistence arises in the model economy mainly from expectations and learning. The posterior model probabilities show that the specification with learning fits significantly better than does the specification with rational expectations. Finally, if learning rather than mechanical sources of persistence provides a more appropriate representation of the economy, the implied optimal policy will be different. The policymaker will also incur substantial costs from misspecifying private expectations formation.