Taylor-type rules versus optimal policy in a Markov-switching economy
Taylor-type rules versus optimal policy in a Markov-switching economy
复制标题
马尔可夫转换经济中的泰勒型规则与最优政策
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
V. Gabriel
中科院分区：
文献类型：
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作者：
Fernando Alexandre;P. Bação;V. Gabriel
我们分析了资产价格变动状态和性质的不确定性对最优货币政策反应的影响。通过将马尔可夫转换冲击添加到具有资本积累的 DSGE 模型中，对不确定性进行建模。在我们的分析中，我们考虑泰勒型规则和最优策略。事实证明，泰勒规则可以很好地描述美国的货币政策。偏离隐含利率与金融混乱的风险有关。泰勒型规则中的利率只响应一小部分信息，而最优政策则考虑所有状态变量和冲击。我们的结果表明，当泡沫破裂时，泰勒规则无法实现软着陆，这与最优政策相反。
We analyse the effect of uncertainty concerning the state and the nature of asset price movements on the optimal monetary policy response. Uncertainty is modelled by adding Markov-switching shocks to a DSGE model with capital accumulation. In our analysis we consider both Taylor-type rules and optimal policy. Taylor rules have been shown to provide a good description of US monetary policy. Deviations from its implied interest rates have been associated with risks of financial disruptions. Whereas interest rates in Taylor-type rules respond to a small subset of information, optimal policy considers all state variables and shocks. Our results suggest that, when a bubble bursts, the Taylor rule fails to achieve a soft landing, contrary to the optimal policy.