了解DSGE过滤器在预测和政策分析中的应用

Michal Andrle
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引用次数: 3

摘要

本文介绍了允许分析师(i)将未观察到的数量的估计分解为观察到的数据的方法,(ii)更好地理解模型的修正属性,以及(iii)对结构经济模型中未观察到的冲击的路径估计施加主观先验约束。例如,将弹性价格产出缺口或技术冲击分解为产出、通胀、利率和其他观察到的变量的贡献是可行的。所建议程序的直观性质和分析的明确性对与政策有关的模型和预测模型具有吸引力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding DSGE Filters in Forecasting and Policy Analysis
This paper introduces methods that allow analysts to (i) decompose the estimates of unobserved quantities into observed data, (ii) to better understand revision properties of the model, and (iii) to impose subjective prior constraints on path estimates of unobserved shocks in structural economic models. For instance, a decomposition of the flexible-price output gap, or a technology shock, into contributions of output, inflation, interest rates, and other observed variables' contribution is feasible. The intuitive nature and analytical clarity of the suggested procedures are appealing for policy-related and forecasting models.
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