IDEAS home Printed from https://ideas.repec.org/p/sce/scecf0/89.html
   My bibliography  Save this paper

Sustainable Fiscal Policy: Numerical Computation Of Markov Equilibria In A Dynamic Game

Author

Listed:
  • Sabit T. Khakimzhanov

    (Bilkent University)

Abstract

We characterize the optimal fiscal policy in a dynamic stochastic general equilibrium model of an economy consisting a government and the continuum of consumers. The key features of the model are the optimizing government unable to commit itself to ex-ante optimal policies and individually rational competitive consumers. The model demonstrates that the debt reduction policy may be a better alternative to immediate tax reduction because of the possibility of multiple Markov equilibria. In such equilibria, for every state in the space of aggregate capital and public debt, both the government and the consumers make sequentially rational decisions given inferred responses of the other participants. The equilibria are characterized by the regions in the state of public debt levels for which the optimal tax rates depend on the aggregate stock of capital. When the government choses debt in excess of this level, multiple Markov equilibria may realize. In order to compute the equilibrium in this economy, we emplyed both analitical and numerical methods. For simple cases of zero probability and probability one sunspots, the extrinsic stochastic variables that coordinate the equilibrium, both methods are applicable. For non trivial distribution of the sunspots, only numerical methods allow to find the equilibrium. The model is calibrated to the US data.

Suggested Citation

  • Sabit T. Khakimzhanov, 2000. "Sustainable Fiscal Policy: Numerical Computation Of Markov Equilibria In A Dynamic Game," Computing in Economics and Finance 2000 89, Society for Computational Economics.
  • Handle: RePEc:sce:scecf0:89
    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:sce:scecf0:89. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.