Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217124 
Year of Publication: 
2018
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 9 [Issue:] 3 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2018 [Pages:] 1123-1151
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
I develop a computational method for solving and estimating heterogeneous agent macro models with aggregate shocks. The main challenge is that the aggregate state vector contains the distribution of agents, which is typically infinite-dimensional. I approximate the distribution with a flexible parametric family, reducing its dimensionality to a finite set of endogenous parameters, and solve for the dynamics of these endogenous parameters by perturbation. I implement the method in Dynare and show that it is fast, general, and easy to use. As an illustration, I use the method to perform a Bayesian estimation of a heterogeneous firm model with aggregate shocks to neutral and investment-specific productivity. I find that the behavior of investment at the firm level quantitatively shapes inference about the aggregate shock processes, suggesting an important role for micro data in estimating DSGE models.
Subjects: 
Heterogeneous agents
computational economics
estimation
lumpy investment
JEL: 
C63
E22
E32
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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