IDEAS home Printed from https://ideas.repec.org/p/red/sed014/1233.html
   My bibliography  Save this paper

Estimation and Counterfactuals in Dynamic Structural Models Using an Euler-Equations Policy-Iteration Mapping

Author

Listed:
  • Arvind Magesan

    (University of Calgary)

  • Victor Aguirregabiria

    (University of Toronto)

Abstract

The development of two-step econometric methods for dynamic structural models has afforded researchers the ability to estimate models with large state spaces without having to compute a full solution of the model even once. However, regardless of the method used for estimation, the implementation of counterfactual experiments using the estimated model does require the full solution and thus still faces the well-known curse of dimensionality in the solution of dynamic programming models. This paper proposes an approach to compute consistent estimates of counterfactual experiments that avoids the full solution of the model and breaks the curse of dimensionality. We illustrate the computational gains associated with our model and methods using Monte Carlo experiments. Finally we illustrate our method using real data, by studying the effects of a counterfactual increase in the cost of entry in several industries in Chile.

Suggested Citation

  • Arvind Magesan & Victor Aguirregabiria, 2014. "Estimation and Counterfactuals in Dynamic Structural Models Using an Euler-Equations Policy-Iteration Mapping," 2014 Meeting Papers 1233, Society for Economic Dynamics.
  • Handle: RePEc:red:sed014:1233
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:red:sed014:1233. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christian Zimmermann). General contact details of provider: http://edirc.repec.org/data/sedddea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.