State-Dependent Central Bank Communication with Heterogeneous Beliefs

Sylvérie Herbert
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引用次数: 2

Abstract

This paper studies the optimal disclosure strategy of a Sender who wants to influence hetero-geneous Receivers' expectations by providing public information. I introduce heterogeneous priors in an otherwise standard Bayesian persuasion model a la Gentzkow and Kamenica (2011) and characterize the dependence of optimal disclosure on the heterogeneity of beliefs. I show that heterogeneity matters in two ways: (i) it is optimal to send moderating signals, which implies sending signals with positive error probabilities in both states, and constitutes a non-trivial departure from the homogeneous beliefs case; (ii) higher dispersion in beliefs leads the information authority to send signals with lower error probabilities. I apply my framework to a central bank communication problem in which the policy maker communicates about aggregate conditions to influence rms' investment decisions. I empirically validate the model's predictions by showing that the FOMC unemployment rate forecasts are systematically biased in opposite directions in recessions and expansions. Also in line with the model's predictions, the forecast biases are decreasing in the degree of private sector disagreement for each state.
国家依赖的中央银行与异质信念的沟通
本文研究了发送者通过提供公开信息来影响异质接收者期望的最优披露策略。我在genzkow和Kamenica(2011)的标准贝叶斯说服模型中引入了异质先验,并描述了最优披露对信念异质性的依赖。我表明异质性在两个方面起作用:(I)发送调节信号是最优的,这意味着在两种状态下发送具有正误差概率的信号,并且构成了对同质信念情况的重大偏离;(ii)信念的高弥散导致信息权威以较低的错误概率发出信号。我将我的框架应用于一个央行沟通问题,在这个问题中,政策制定者就总体状况进行沟通,以影响rms的投资决策。我通过实证验证了模型的预测,表明联邦公开市场委员会的失业率预测在衰退和扩张中系统性地偏向相反的方向。同样与模型预测一致的是,各州私营部门分歧程度的预测偏差正在下降。
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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