IDEAS home Printed from https://ideas.repec.org/a/wly/quante/v9y2018i3p1123-1151.html
   My bibliography  Save this article

A method for solving and estimating heterogeneous agent macro models

Author

Listed:
  • Thomas Winberry

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.

Suggested Citation

  • Thomas Winberry, 2018. "A method for solving and estimating heterogeneous agent macro models," Quantitative Economics, Econometric Society, vol. 9(3), pages 1123-1151, November.
    • Handle: RePEc:wly:quante:v:9:y:2018:i:3:p:1123-1151
    DOI: 10.3982/QE740
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/QE740
    Download Restriction: no
    File URL: https://libkey.io/10.3982/QE740?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:quante:v:9:y:2018:i:3:p:1123-1151. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.