Leaning against the wind in the New Keynesian model with heterogeneous expectations

IF 1.9 3区 经济学 Q2 ECONOMICS
Mikhail Anufriev , Fabio Lamantia , Davide Radi , Tomas Tichy
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Abstract

In this paper, we explore the efficiency of the Leaning Against the Wind (LAW) policy within the New Keynesian framework with heterogeneous expectations. To do this, we add a financial sector to the model, linking it with the real sector via the financial accelerator channel. We find that the range of parameters in the Taylor rule that enable the stability of the targeted equilibrium is reduced with the financial accelerator. However, expanding the Taylor rule via the LAW policy fails to counteract this effect and may even exacerbate it if the policy reacts to any mispricing. If applied conditionally on high mispricing, the LAW policy leads to co-existing stable targeted and non-targeted equilibria. Our simulations suggest that while the LAW policy can reduce the amplitude of endogenous fluctuations, it is inefficient in dealing with exogenous shocks and results in larger average deviations from the target.
在异质预期的新凯恩斯主义模型中逆风而行
在本文中,我们探讨了新凯恩斯主义框架下具有异质预期的逆风政策的效率。为此,我们在模型中加入了金融部门,通过金融加速器渠道将其与实体部门联系起来。我们发现,在金融加速器的作用下,使目标均衡稳定的泰勒规则的参数范围减小了。然而,通过法律政策扩大泰勒规则并不能抵消这种影响,如果政策对任何错误定价作出反应,甚至可能加剧这种影响。如果有条件地应用于高错定价,LAW政策会导致稳定的目标均衡和非目标均衡共存。我们的模拟表明,虽然LAW政策可以减少内生波动的幅度,但它在处理外生冲击方面效率低下,并且导致与目标的平均偏差较大。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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