Optimal Monetary Policy in Markov-Switching Models with Rational Expectations Agents
Optimal Monetary Policy in Markov-Switching Models with Rational Expectations Agents
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DOI：
10.2139/ssrn.932567
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发表时间：
2006-06
期刊：
影响因子：
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通讯作者：
A. Blake;Fabrizio Zampolli
中科院分区：
文献类型：
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作者：
A. Blake;Fabrizio Zampolli
本文研究了具有马尔可夫机制转移和前瞻智能体的模型的最优控制问题。这些模型是建模模型不确定性的非常通用和灵活的工具。设计了一种算法来计算具有随机参数或制度转移的线性理性预期模型的解。该算法还可以应用于任意仪表规则的优化。第二种算法计算时间一致策略和由此产生的纳什-斯塔克尔伯格均衡。类似的方法可以很容易地用来计算承诺下的最优策略。此外，该算法还可以处理决策者和私营部门持有不同信念的情况。我们应用这些方法来计算一个小型开放经济体的最优(非线性)货币政策，该经济体的一些关键参数受到随机结构突变的约束。
In this paper we consider the optimal control problem of models with Markov regime shifts and forward-looking agents. These models are very general and flexible tools for modelling model uncertainty. An algorithm is devised to compute the solution of a linear rational expectations model with random parameters or regime shifts. This algorithm can also be applied in the optimisation of any arbitrary instrument rule. A second algorithm computes the time-consistent policy and the resulting Nash-Stackelberg equilibrium. Similar methods can be easily employed to compute the optimal policy under commitment. Furthermore, the algorithms can also handle the case in which the policymaker and the private sector hold different beliefs. We apply these methods to compute the optimal (non-linear) monetary policy in a small open economy subject to random structural breaks in some of its key parameters.