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Estimating linearized heterogeneous agent models using panel data

机译:使用面板数据估算线性化异构代理模型

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We develop a method to estimate heterogeneous agent models that uses not only time series of macroeconomic aggregates, but can also incorporate micro level data (repeated cross-section or panel). The micro data may be collected at lower frequency and time-aggregated. The method is based on the linearization approach of Reiter (2009), combined with optimal state aggregation as in Reiter (2010). The model may contain decision problems with both continuous and discrete choice. Linearity of the model solution allows fast computation of second moments and likelihood. We discuss various computational devices to maximize the speed of the estimation. (C) 2020 Published by Elsevier B.V.
机译:我们开发一种估计异构代理模型的方法,不仅使用时间序列的宏观经济聚集体,而且还可以包含微级数据(重复的横截面或面板)。可以在较低频率和时间聚合以较低的频率收集微数据。该方法基于Reiter(2009)的线性化方法,与Reiter(2010)中的最佳状态聚合组合。该模型可能包含连续和离散选择的决策问题。模型解决方案的线性允许快速计算第二时刻和可能性。我们讨论各种计算设备以最大化估计的速度。 (c)2020由elsevier b.v发布。

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