IDEAS home Printed from https://ideas.repec.org/p/mia/wpaper/2012-5.html
   My bibliography  Save this paper

Ergodic Invariant Distributions for Non-optimal Dynamic Economics

Author

Listed:
  • Manuel S. Santos

    (Department of Economics, University of Miami)

  • Adrian Peralta-Alva

    (Research Department, Federal Reserve Bank of Saint Louis)

Abstract

In this paper we are concerned with the simulation of non-optimal dynamic economies. The equilibrium laws of motion of these economies cannot be characterized by the methods of dynamic programming and may not be described by continuous policy functions. We prove existence of an invariant distribution for the equilibrium law of motion, and establish some convergence and accuracy properties for the simulated moments. We obtain these results without resorting to artificial randomizations of the equilibrium correspondence or discretizations of the state space.

Suggested Citation

  • Manuel S. Santos & Adrian Peralta-Alva, 2012. "Ergodic Invariant Distributions for Non-optimal Dynamic Economics," Working Papers 2012-5, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2012-5
    as

    Download full text from publisher

    File URL: https://www.herbert.miami.edu/_assets/files/repec/WP2012-05.pdf
    File Function: First version, 2012
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Duffie, Darrell, et al, 1994. "Stationary Markov Equilibria," Econometrica, Econometric Society, vol. 62(4), pages 745-781, July.
    2. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(1), pages 53-82.
    3. Manuel S. Santos & Adrian Peralta-Alva, 2005. "Accuracy of Simulations for Stochastic Dynamic Models," Econometrica, Econometric Society, vol. 73(6), pages 1939-1976, November.
    4. Blume, Lawrence E., 1982. "New techniques for the study of stochastic equilibrium processes," Journal of Mathematical Economics, Elsevier, vol. 9(1-2), pages 61-70, January.
    5. Manuel S. Santos & Adrian Peralta-Alva, 2005. "Accuracy of Simulations for Stochastic Dynamic Models," Econometrica, Econometric Society, vol. 73(6), pages 1939-1976, November.
    6. Karl Schmedders, Felix Kubler, 2001. "Asset Pricing in Models with incomplete markets and default," Computing in Economics and Finance 2001 58, Society for Computational Economics.
    7. Patrick J. Kehoe & Fabrizio Perri, 2002. "International Business Cycles with Endogenous Incomplete Markets," Econometrica, Econometric Society, vol. 70(3), pages 907-928, May.
    8. Felix Kubler & Karl Schmedders, 2003. "Stationary Equilibria in Asset-Pricing Models with Incomplete Markets and Collateral," Econometrica, Econometric Society, vol. 71(6), pages 1767-1793, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pierri Damian, 2024. "Accuracy in Recursive Minimal State Space Methods," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 263-305, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manuel S. Santos & Adrian Peralta-Alva, 2012. "Analysis of Numerical Errors," Working Papers 2012-6, University of Miami, Department of Economics.
    2. Zhigang Feng & Jianjun Miao & Adrian Peralta‐Alva & Manuel S. Santos, 2014. "Numerical Simulation Of Nonoptimal Dynamic Equilibrium Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(1), pages 83-110, February.
    3. Pierri, Damian Rene & Reffett, Kevin, 2021. "Memory, multiple equilibria and emerging market crises," UC3M Working papers. Economics 32871, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Pierri Damian, 2024. "Accuracy in Recursive Minimal State Space Methods," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 263-305, July.
    5. Adrian Peralta-Alva & Manuel S. Santos, 2010. "Problems in the Numerical Simulation of Models with Heterogeneous Agents and Economic Distortions," Journal of the European Economic Association, MIT Press, vol. 8(2-3), pages 617-625, 04-05.
    6. Datta, Manjira & Mirman, Leonard J. & Morand, Olivier F. & Reffett, Kevin L., 2005. "Markovian equilibrium in infinite horizon economies with incomplete markets and public policy," Journal of Mathematical Economics, Elsevier, vol. 41(4-5), pages 505-544, August.
    7. Jaime McGovern & Olivier Morand & Kevin Reffett, 2013. "Computing minimal state space recursive equilibrium in OLG models with stochastic production," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(3), pages 623-674, November.
    8. Cao, Dan, 2020. "Recursive equilibrium in Krusell and Smith (1998)," Journal of Economic Theory, Elsevier, vol. 186(C).
    9. Takashi Kamihigashiw & John Stachurski, 2014. "Seeking Ergodicity in Dynamic Economies," Working Papers 2014-402, Department of Research, Ipag Business School.
    10. YiLi Chien & Hanno Lustig, 2010. "The Market Price of Aggregate Risk and the Wealth Distribution," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1596-1650, April.
    11. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2017. "Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models," Econometrica, Econometric Society, vol. 85, pages 991-1012, May.
    12. Kamihigashi, Takashi & Stachurski, John, 2016. "Seeking ergodicity in dynamic economies," Journal of Economic Theory, Elsevier, vol. 163(C), pages 900-924.
    13. Manuel Santos & Jianjun Miao, 2005. "Numerical Solution of Dynamic Non-Optimal Economies," 2005 Meeting Papers 266, Society for Economic Dynamics.
    14. Timothy Cogley & Thomas J. Sargent & Viktor Tsyrennikov, 2014. "Wealth Dynamics in a Bond Economy with Heterogeneous Beliefs," Economic Journal, Royal Economic Society, vol. 124(575), pages 1-30, March.
    15. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    16. Takashi Kamihigashi & John Stachurski, 2011. "Existence, Stability and Computation of Stationary Distributions: An Extension of the Hopenhayn-Prescott Theorem," Discussion Paper Series DP2011-32, Research Institute for Economics & Business Administration, Kobe University.
    17. RUGE-MURCIA, Francisco J., 2010. "Estimating Nonlinear DSGE Models by the Simulated Method of Moments," Cahiers de recherche 2010-10, Universite de Montreal, Departement de sciences economiques.
    18. Cao, Dan & Evans, Martin & Lua, Wenlan, 2020. "Real Exchange Rate Dynamics Beyond Business Cycles," MPRA Paper 99054, University Library of Munich, Germany, revised 10 Mar 2020.
    19. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    20. Kubler, Felix & Scheidegger, Simon, 2023. "Uniformly self-justified equilibria," Journal of Economic Theory, Elsevier, vol. 212(C).

    More about this item

    Keywords

    Markov Equilibrium; Invariant Distribution; Computed Solution; Simulated Moments;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mia:wpaper:2012-5. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Daniela Valdivia (email available below). General contact details of provider: https://edirc.repec.org/data/demiaus.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.