Structural Estimation Combining Micro and Macro Data

Luca Neri
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Abstract

This paper introduces a novel approach for estimating heterogeneous-agent macroeconomic models adding information from micro data. The methodology covers both panels and repeated cross sections, with applications to a wide class of dynamic structural models used in macroeconomics. The routine involves the estimation of dynamic moments over subgroups of the cross-sectional dimension of agents. Micro moments differ from each other in the informative content that they carry for point estimation of the structural parameters. For instance, variability of moments over the cross-sectional distribution of households' wealth contain relevant information for the correct estimation of the subjective discount rate. However, data from the cross section are not relevant for the identification of a technology shock.
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微观与宏观数据相结合的结构估计
本文介绍了一种利用微观数据信息估计异质主体宏观经济模型的新方法。该方法涵盖了面板和重复横截面,并应用于宏观经济学中使用的各种动态结构模型。该例程涉及对代理横截面尺寸的子群上的动态矩的估计。微矩对结构参数点估计的信息量不同。例如,家庭财富横截面分布上的矩变异性包含了正确估计主观贴现率的相关信息。然而,来自横截面的数据与技术冲击的识别无关。
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