IDEAS home Printed from https://ideas.repec.org/p/spo/wpmain/infohdl2441-5lc99v0teo898rban7bgs9reua.html
   My bibliography  Save this paper

Solving and Simulating Models with Heterogeneous Agents and Aggregate Uncertainty

Author

Listed:
  • Yann Algan

    (Département d'économie (ECON))

  • Olivier Allais

    (Laboratoire de Recherche sur la Consommation)

  • Wouter Den Haan

    (Department of Economics ( London School of Economics and Political Science, Tilburg University))

  • Pontus Rendahl

    (Centre for Macroeconomics)

Abstract

Although almost nonexistent 15 years ago, there are now numerous papers that analyze models with both aggregate uncertainty and a large number—typically a continuum—of heterogeneous agents. These models make it possible to study whether macroeconomic fluctuations affect different agents differently and whether heterogeneity in turn affects macroeconomic fluctuations. This chapter reviews different algorithms to solve and simulate these models. In addition, it highlights problems with popular accuracy tests and discusses more powerful alternatives.

Suggested Citation

  • Yann Algan & Olivier Allais & Wouter Den Haan & Pontus Rendahl, 2010. "Solving and Simulating Models with Heterogeneous Agents and Aggregate Uncertainty," Sciences Po publications info:hdl:2441/5lc99v0teo8, Sciences Po.
  • Handle: RePEc:spo:wpmain:info:hdl:2441/5lc99v0teo898rban7bgs9reua
    as

    Download full text from publisher

    File URL: https://spire.sciencespo.fr/hdl:/2441/5lc99v0teo898rban7bgs9reua/resources/2010-algan-allais-denhann-rendahl-solving-and-%25E2%2588%25BCulating-models-with-heterogeneous-agents.pdf
    Download Restriction: no

    File URL: https://spire.sciencespo.fr/hdl:/2441/5lc99v0teo898rban7bgs9reua/resources/2010-algan-allais-denhann-rendahl-solving-and-e2-88-bculating-models-with-heterogeneous-agents.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manuel S. Santos & Adrian Peralta-Alva, 2005. "Accuracy of Simulations for Stochastic Dynamic Models," Econometrica, Econometric Society, vol. 73(6), pages 1939-1976, November.
    2. Manuel S. Santos & Adrian Peralta-Alva, 2005. "Accuracy of Simulations for Stochastic Dynamic Models," Econometrica, Econometric Society, vol. 73(6), pages 1939-1976, November.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Takashi Kamihigashiw & John Stachurski, 2014. "Seeking Ergodicity in Dynamic Economies," Working Papers 2014-402, Department of Research, Ipag Business School.
    7. Balbus, Łukasz & Reffett, Kevin & Woźny, Łukasz, 2013. "A constructive geometrical approach to the uniqueness of Markov stationary equilibrium in stochastic games of intergenerational altruism," Journal of Economic Dynamics and Control, Elsevier, vol. 37(5), pages 1019-1039.
    8. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    9. 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.
    10. van Binsbergen, Jules H. & Fernández-Villaverde, Jesús & Koijen, Ralph S.J. & Rubio-Ramírez, Juan, 2012. "The term structure of interest rates in a DSGE model with recursive preferences," Journal of Monetary Economics, Elsevier, vol. 59(7), pages 634-648.
    11. repec:hal:spmain:info:hdl:2441/5lc99v0teo898rban7bgs9reua is not listed on IDEAS
    12. Fernández-Villaverde, Jesús & Guerrón-Quintana, Pablo & Rubio-Ramírez, Juan F., 2015. "Estimating dynamic equilibrium models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 216-229.
    13. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
    14. Guerrieri, Luca & Iacoviello, Matteo, 2015. "OccBin: A toolkit for solving dynamic models with occasionally binding constraints easily," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 22-38.
    15. Damián Pierri & Julián Martínez, 2020. "Accuracy in Recursive Minimal State Space Methods," Working Papers 147, Universidad de San Andres, Departamento de Economia, revised Aug 2020.
    16. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2014. "Lower Bounds on Approximation Errors: Testing the Hypothesis That a Numerical Solution Is Accurate?," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-06, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    17. Manuel Santos, 2007. "Consistency Properties of a Simulation-Based Estimator for Dynamic Processes," Working Papers 0705, University of Miami, Department of Economics.
    18. Cuong Van & John Stachurski, 2007. "Parametric continuity of stationary distributions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(2), pages 333-348, November.
    19. Agee, Mark D. & Crocker, Thomas D., 2013. "Operationalizing the capability approach to assessing well-being," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 46(C), pages 80-86.
    20. 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.
    21. Bobenrieth H., Eugenio S.A. & Bobenrieth H., Juan R.A. & Wright, Brian D., 2008. "A foundation for the solution of consumption-saving behavior with a borrowing constraint and unbounded marginal utility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 695-708, March.

    More about this item

    Keywords

    Incomplete Markets; Numerical Solutions; Projection Methods; Perturbation Methods; Parmeterized Densities; Accuracy Tests;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets

    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:spo:wpmain:info:hdl:2441/5lc99v0teo898rban7bgs9reua. 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: Spire @ Sciences Po Library (email available below). General contact details of provider: https://edirc.repec.org/data/ecspofr.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.