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Financial Frictions and the Wealth Distribution

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  • Fernández-Villaverde, Jesús
  • Hurtado, Samuel
  • Nuño, Galo

Abstract

This paper investigates how, in a heterogeneous agents model with financial frictions, idiosyncratic individual shocks interact with exogenous aggregate shocks to generate time-varying levels of leverage and endogenous aggregate risk. To do so, we show how such a model can be efficiently computed, despite its substantial nonlinearities, using tools from machine learning. We also illustrate how the model can be structurally estimated with a likelihood function, using tools from inference with diffusions. We document, first, the strong nonlinearities created by financial frictions. Second, we report the existence of multiple stochastic steady states with properties that differ from the deterministic steady state along important dimensions. Third, we illustrate how the generalized impulse response functions of the model are highly state-dependent. In particular, we find that the recovery after a negative aggregate shock is more sluggish when the economy is more leveraged. Fourth, we prove that wealth heterogeneity matters in this economy because of the asymmetric responses of household consumption decisions to aggregate shocks.

Suggested Citation

  • Fernández-Villaverde, Jesús & Hurtado, Samuel & Nuño, Galo, 2019. "Financial Frictions and the Wealth Distribution," CEPR Discussion Papers 14002, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:14002
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    Cited by:

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    2. Papp, Tamás K. & Reiter, Michael, 2020. "Estimating linearized heterogeneous agent models using panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    3. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie 21.14, Université de Lausanne, Faculté des HEC, Département d’économie.
    4. Ebrahimi Kahou, Mahdi & Fernández-Villaverde, Jesús & Perla, Jesse & Sood, Arnav, 2021. "Exploiting Symmetry in High-Dimensional Dynamic Programming," CEPR Discussion Papers 16285, C.E.P.R. Discussion Papers.
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    6. Aryan Eftekhari & Simon Scheidegger, 2022. "High-Dimensional Dynamic Stochastic Model Representation," Papers 2202.06555, arXiv.org.
    7. Lee, Seungcheol & Luetticke, Ralph & Ravn, Morten O, 2020. "Financial Frictions: Macro vs Micro Volatility," CEPR Discussion Papers 15133, C.E.P.R. Discussion Papers.
    8. Lepetyuk, Vadym & Maliar, Lilia & Maliar, Serguei, 2019. "When the U.S. catches a cold, Canada sneezes: a lower-bound tale told by deep learning," CEPR Discussion Papers 14025, C.E.P.R. Discussion Papers.
    9. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.
    10. Jesus Fernandez-Villaverde, 2020. "Simple Rules for a Complex World with Arti?cial Intelligence," PIER Working Paper Archive 20-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    11. Lepetyuk, Vadym & Maliar, Lilia & Maliar, Serguei, 2020. "When the U.S. catches a cold, Canada sneezes: A lower-bound tale told by deep learning," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    12. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2021. "Estimating DSGE Models: Recent Advances and Future Challenges," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 229-252, August.
    13. Emoto, Masakazu & Sunakawa, Takeki, 2021. "Applying the explicit aggregation algorithm to heterogeneous agent models in continuous time," Economics Letters, Elsevier, vol. 206(C).
    14. Artem Kuriksha, 2021. "An Economy of Neural Networks: Learning from Heterogeneous Experiences," Papers 2110.11582, arXiv.org.
    15. Carlos Montes-Galdón & Eva Ortega, 2022. "Skewed SVARs: tracking the structural sources of macroeconomic tail risks," Working Papers 2208, Banco de España.
    16. Michael Reiter, 2019. "Solving Heterogeneous Agent Models with Non-convex Optimization Problems: Linearization and Beyond %," 2019 Meeting Papers 1048, Society for Economic Dynamics.
    17. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation: With an Application to Option Pricing," Papers 2102.09209, arXiv.org.
    18. Peri, Alessandro, 2020. "A hardware approach to value function iteration," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    19. Vladimir Skavysh & Sofia Priazhkina & Diego Guala & Thomas Bromley, 2022. "Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning," Staff Working Papers 22-29, Bank of Canada.
    20. Maliar, Lilia & Maliar, Serguei & Winant, Pablo, 2021. "Deep learning for solving dynamic economic models," Journal of Monetary Economics, Elsevier, vol. 122(C), pages 76-101.
    21. Ben Moll, 2020. "The Research Agenda: Ben Moll on the Rich Interactions between Inequality and the Macroeconomy," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 21(2), November.
    22. Jesús Fernández-Villaverde, 2021. "Has machine learning rendered simple rules obsolete?," European Journal of Law and Economics, Springer, vol. 52(2), pages 251-265, December.
    23. Duarte, Victor & Duarte, Diogo & Fonseca, Julia & Montecinos, Alexis, 2020. "Benchmarking machine-learning software and hardware for quantitative economics," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).

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    Keywords

    Aggregate shocks; continuous-time; Heterogeneous Agents; Machine Learning; structural estimation;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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