Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm and non-stochastic simulations

Eric R. Young

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Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm and non-stochastic simulations

机译：使用Krusell-Smith算法和非随机模拟求解具有总不确定性的不完全市场模型

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摘要

This article describes the approach to computing the version of the stochastic growth model with idiosyncratic and aggregate risk that relies on collapsing the aggregate state space down to a small number of moments used to forecast future prices. One innovation relative to most of the literature is the use of a non-stochastic simulation routine.

机译：本文介绍了一种用于计算具有特殊风险和汇总风险的随机增长模型版本的方法，该方法依赖于将汇总状态空间压缩到用于预测未来价格的少量时刻。相对于大多数文献而言，一项创新是使用非随机模拟例程。

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来源
《Journal of Economic Dynamics and Control》 |2010年第1期|36-41|共6页
作者
Eric R. Young;
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作者单位

Department of Economics, University of Virginia, PO Box 400182, Charlottesville, VA 22904, USA;

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原文格式 PDF
正文语种 eng
中图分类
关键词
idiosyncratic risk; business cycles; numerical methods;

机译：特质风险商业周期;数值方法;

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Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm and non-stochastic simulations

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