IDEAS home Printed from https://ideas.repec.org/a/eee/dyncon/v34y2010i1p28-35.html
   My bibliography  Save this article

Solving the incomplete markets model with aggregate uncertainty by backward induction

Author

Listed:
  • Reiter, Michael

Abstract

This paper describes a method to solve models with a continuum of agents, incomplete markets and aggregate uncertainty. I use backward induction on a finite grid of points in the aggregate state space. The aggregate state includes a small number of statistics (moments) of the cross-sectional distribution of capital. For any given set of moments, agents use a specific cross-sectional distribution, called "proxy distribution", to compute the equilibrium. Information from the steady state distribution as well as from simulations can be used to chose a suitable proxy distribution.

Suggested Citation

  • Reiter, Michael, 2010. "Solving the incomplete markets model with aggregate uncertainty by backward induction," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 28-35, January.
  • Handle: RePEc:eee:dyncon:v:34:y:2010:i:1:p:28-35
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165-1889(09)00130-4
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Den Haan, Wouter J, 1996. "Heterogeneity, Aggregate Uncertainty, and the Short-Term Interest Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 399-411, October.
    2. Algan, Yann & Allais, Olivier & Den Haan, Wouter J., 2008. "Solving heterogeneous-agent models with parameterized cross-sectional distributions," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 875-908, March.
    3. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, January.
    4. Carroll, Christopher D., 2006. "The method of endogenous gridpoints for solving dynamic stochastic optimization problems," Economics Letters, Elsevier, vol. 91(3), pages 312-320, June.
    5. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October.
    6. Den Haan, Wouter J., 2010. "Comparison of solutions to the incomplete markets model with aggregate uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 4-27, January.
    7. Algan, Yann & Allais, Olivier & Den Haan, Wouter J., 2008. "Solving heterogeneous-agent models with parameterized cross-sectional distributions," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 875-908, March.
    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. Aubhik Khan, 2016. "Aggregate Fluctuations in a Quantitative Overlapping Generations Economy with Unemployment Risk," 2016 Meeting Papers 1468, Society for Economic Dynamics.
    2. Michael C. Hatcher & Eric M. Scheffel, 2016. "Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 569-591, December.
    3. Tobias Grasl, 2013. "Solving Incomplete Markets Models by Derivative Aggregation," Birkbeck Working Papers in Economics and Finance 1302, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Den Haan, Wouter J. & Rendahl, Pontus, 2010. "Solving the incomplete markets model with aggregate uncertainty using explicit aggregation," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 69-78, January.
    5. Andreas Bachmann, 2015. "Lumpy investment and variable capacity utilization: firm-level and macroeconomic implications," Diskussionsschriften dp1510, Universitaet Bern, Departement Volkswirtschaft.
    6. Andrei Jirnyi & Vadym Lepetyuk, 2011. "A reinforcement learning approach to solving incomplete market models with aggregate uncertainty," Working Papers. Serie AD 2011-21, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    7. Grey Gordon, 2011. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," PIER Working Paper Archive 11-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    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:eee:dyncon:v:34:y:2010:i:1:p:28-35. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jedc .

    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 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.

    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.