Behavioral Learning Equilibria in the New Keynesian Model

C. Hommes, K. Mavromatis, Tolga Ozden, Mei Zhu
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引用次数: 11

Abstract

We introduce the concept of behavioral learning equilibrium (BLE) into a high dimensional linear framework and apply it to the standard New Keynesian model. For each endogenous variable, boundedly rational agents use a simple, but optimal AR(1) forecasting rule with parameters consistent with the observed sample mean and autocorrelation of past data. The main contributions of our paper are fourfold: (1) we derive existence and stability conditions of BLE in a general linear framework, (2) we provide a general method for Bayesian likelihood estimation of BLE, (3) we estimate the baseline NK model based on U.S. data and show that the relative model fit is better under BLE than REE, (4) we analyze optimal monetary policy under BLE and show that it differs from REE. In particular, we find that the transmission channel of monetary policy is stronger under BLE at the estimated parameter values.
新凯恩斯模型中的行为学习均衡
我们将行为学习均衡(BLE)的概念引入高维线性框架,并将其应用于标准的新凯恩斯主义模型。对于每个内生变量,有界理性智能体使用一个简单但最优的AR(1)预测规则,其参数与观察到的样本均值和过去数据的自相关一致。本文的主要贡献有四个方面:(1)我们在一般线性框架下推导了BLE的存在性和稳定性条件;(2)我们提供了BLE的贝叶斯似然估计的一般方法;(3)我们基于美国数据估计了基准NK模型,并表明BLE下的相对模型拟合优于REE;(4)我们分析了BLE下的最优货币政策,并表明它与REE不同。特别是,我们发现在估计的参数值下,BLE下货币政策的传导通道更强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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