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Solving the incomplete markets model with aggregate uncertainty by backward induction

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  • 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
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    4. 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.
    5. repec:hal:spmain:info:hdl:2441/41rhqgovpp8hnq9i7ndtl26ltm is not listed on IDEAS
    6. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
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    Citations

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    Cited by:

    1. Jesús Fernández‐Villaverde & Samuel Hurtado & Galo Nuño, 2023. "Financial Frictions and the Wealth Distribution," Econometrica, Econometric Society, vol. 91(3), pages 869-901, May.
    2. Aubhik Khan, 2016. "Aggregate Fluctuations in a Quantitative Overlapping Generations Economy with Unemployment Risk," 2016 Meeting Papers 1468, Society for Economic Dynamics.
    3. Gouin-Bonenfant, Emilien & Toda, Alexis Akira, 2018. "Pareto Extrapolation: Bridging Theoretical and Quantitative Models of Wealth Inequality," University of California at San Diego, Economics Working Paper Series qt90n2h2bb, Department of Economics, UC San Diego.
    4. 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.
    5. Nils M. Gornemann & Keith Kuester & Makoto Nakajima, 2016. "Doves for the Rich, Hawks for the Poor? Distributional Consequences of Monetary Policy," International Finance Discussion Papers 1167, Board of Governors of the Federal Reserve System (U.S.).
    6. Tobias Grasl, 2013. "Solving Incomplete Markets Models by Derivative Aggregation," Birkbeck Working Papers in Economics and Finance 1302, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. Takeki Sunakawa, 2020. "Applying the Explicit Aggregation Algorithm to Heterogeneous Macro Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 845-874, March.
    8. Chipeniuk, Karsten O. & Katz, Nets Hawk & Walker, Todd B., 2022. "Households, auctioneers, and aggregation," European Economic Review, Elsevier, vol. 141(C).
    9. 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.
    10. Michael Reiter, 2019. "Solving Heterogeneous Agent Models with Non-convex Optimization Problems: Linearization and Beyond %," 2019 Meeting Papers 1048, Society for Economic Dynamics.
    11. Heejeong Kim, 2022. "Inequality, Disaster risk, and the Great Recession," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 187-216, July.
    12. Andreas Bachmann, 2015. "Lumpy investment and variable capacity utilization: firm-level and macroeconomic implications," Diskussionsschriften dp1510, Universitaet Bern, Departement Volkswirtschaft.
    13. 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).
    14. Grey Gordon, 2020. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," Economic Quarterly, Federal Reserve Bank of Richmond, issue 2Q, pages 61-95.
    15. Cao, Dan, 2020. "Recursive equilibrium in Krusell and Smith (1998)," Journal of Economic Theory, Elsevier, vol. 186(C).
    16. Aubhik Khan & Ben Lidofsky, 2019. "Growth, Uncertainty and Business Cycles in an Overlapping Generations Economy," 2019 Meeting Papers 1459, Society for Economic Dynamics.
    17. Aubhik Khan & Julia Thomas & Tatsuro Senga, 2018. "The Persistent Effects of Entry and Exit," 2018 Meeting Papers 707, Society for Economic Dynamics.
    18. Karsten O. Chipeniuk & Nets Hawk Katz & Todd Bruce Walker, 2022. "Households, Auctioneers, and Aggregation," CAEPR Working Papers 2022-005 Classification-E, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    19. Nobuhide Okahata, 2019. "An Alternative Solution Method for Continuous-Time Heterogeneous Agent Models with Aggregate Shocks," 2019 Meeting Papers 1470, Society for Economic Dynamics.
    20. Karsten O. Chipeniuk, 2020. "Optimal Grid Selection for the Numerical Solution of Dynamic Stochastic Optimization Problems," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 883-928, December.
    21. Aubhik Khan & Julia Thomas & Tatsuro Senga, 2019. "Business Formation and Economic Growth Beyond the Great Recession," 2019 Meeting Papers 1453, Society for Economic Dynamics.
    22. Emoto, Masakazu & Sunakawa, Takeki, 2021. "Applying the explicit aggregation algorithm to heterogeneous agent models in continuous time," Economics Letters, Elsevier, vol. 206(C).
    23. Aubhik Khan, 2017. "Large Recessions in an Overlapping Generations with Unemployment," 2017 Meeting Papers 1559, Society for Economic Dynamics.

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