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Adaptive learning, forecast-based instrument rules and monetary policy

机译:自适应学习,基于预测的工具规则和货币政策

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This paper argues that recently popular forecast-based instrument rules for monetary policy may fail to stabilize economic fluctuations. In a New Keynesian model of output gap and inflation determination in which private agents face multi-period decision problems, but have non-rational expectations and learn over time, if the monetary authority adopts a forecast-based instrument rule and responds to observed private forecasts then this class of policies frequently induce divergent learning dynamics. A central bank that correctly understands private behavior can mitigate such instability by responding to the determinants of private forecasts. This suggests gathering information on the determinants of expectations to be useful.
机译:本文认为,最近流行的基于预测的货币政策工具规则可能无法稳定经济波动。在新凯恩斯主义的产出缺口和通货膨胀确定模型中,如果货币当局采用基于预测的工具规则并响应观察到的私人预测,则私人代理人会面临多个时期的决策问题,但具有非理性预期并随着时间的推移而学习那么这类政策经常会引发不同的学习动力。正确理解私人行为的中央银行可以通过响应私人预测的决定因素来减轻这种不稳定性。这表明收集有关期望的决定因素的信息是有用的。

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