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Self-justi ed equilibria: Existence and computation

Author

Listed:
  • Felix Kubler

    (University of Zurich)

  • Simon Scheidegger

    (University of Zurich)

Abstract

In this paper we introduce self-justi ed equilibrium as a solution concept in stochastic general equilibrium models with a large number of heterogeneous agents. In each period agents trade in assets to maximize the sum of current utility and forecasted future utility. Current prices ensure that markets clear and agents forecast the probability distribution of future prices and consumption on the basis of current endogenous variables and the current exogenous shock. The forecasts are self-justi ed in the sense that agents use forecasting functions that are optimal within a given class of functions and that can be viewed as optimally trading o the accuracy of the forecast and its complexity. We show that self-justi ed equilibria always exist and we develop a computational method to approximate them numerically. By restricting the complexity of agents' forecasts we can solve models with a very large number of heterogeneous agents. Errors can be directly interpreted.

Suggested Citation

  • Felix Kubler & Simon Scheidegger, 2018. "Self-justi ed equilibria: Existence and computation," 2018 Meeting Papers 694, Society for Economic Dynamics.
    • Handle: RePEc:red:sed018:694
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    References listed on IDEAS

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    1. Judd, Kenneth L. & Maliar, Lilia & Maliar, Serguei & Valero, Rafael, 2014. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 92-123.
    2. Citanna, Alessandro & Siconolfi, Paolo, 2012. "Recursive equilibrium in stochastic OLG economies: Incomplete markets," Journal of Mathematical Economics, Elsevier, vol. 48(5), pages 322-337.
    3. 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.
    4. Feldman, Mark & Gilles, Christian, 1985. "An expository note on individual risk without aggregate uncertainty," Journal of Economic Theory, Elsevier, vol. 35(1), pages 26-32, February.
    5. Truman F. Bewley, 1984. "Fiscal and Monetary Policy in a General Equilibrium Model," Cowles Foundation Discussion Papers 690, Cowles Foundation for Research in Economics, Yale University.
    6. Krueger, Dirk & Kubler, Felix, 2004. "Computing equilibrium in OLG models with stochastic production," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1411-1436, April.
    7. Johannes Brumm & Simon Scheidegger, 2017. "Using Adaptive Sparse Grids to Solve High‐Dimensional Dynamic Models," Econometrica, Econometric Society, vol. 85, pages 1575-1612, September.
    8. Ljungqvist, Lars & Sargent, Thomas J., 2012. "Recursive Macroeconomic Theory, Third Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262018748, April.
    9. Johannes Brumm & Dominika Kryczka & Felix Kubler, 2017. "Recursive Equilibria in Dynamic Economies With Stochastic Production," Econometrica, Econometric Society, vol. 85, pages 1467-1499, September.
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    Cited by:

    1. Laurence Kotlikoff & Felix Kubler & Andrey Polbin & Simon Scheidegger, 2021. "Pareto-improving carbon-risk taxation [The environment and directed technical change]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 36(107), pages 551-589.
    2. Jesús Fernández‐Villaverde & Samuel Hurtado & Galo Nuño, 2023. "Financial Frictions and the Wealth Distribution," Econometrica, Econometric Society, vol. 91(3), pages 869-901, May.
    3. Kubler, Felix & Scheidegger, Simon, 2023. "Uniformly self-justified equilibria," Journal of Economic Theory, Elsevier, vol. 212(C).
    4. Michael Reiter, 2019. "Solving Heterogeneous Agent Models with Non-convex Optimization Problems: Linearization and Beyond %," 2019 Meeting Papers 1048, Society for Economic Dynamics.

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