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Recursive utility in a Markov environment with stochastic growth

Author

Listed:
  • Lars Peter Hansen

    (University of Chicago and NBER)

  • Jose A. Scheinkman

    (Princeton University and NBER)

Abstract

Recursive utility models of the type introduced by Kreps and Porteus (1978) are used extensively in applied research in macroeconomics and asset pricing in environments with uncertainty. These models represent preferences as the solution to a nonlinear forward-looking difference equation with a terminal condition. Such preferences feature investor concerns about the intertemporal composition of risk. In this paper we study infinite horizon specifications of this difference equation in the context of a Markov environment. We establish a connection between the solution to this equation and to an arguably simpler Perron-Frobenius eigenvalue equation of the type that occurs in the study of large deviations for Markov processes. By exploiting this connection, we establish existence and uniqueness results. Moreover, we explore a substantive link between large deviation bounds for tail events for stochastic consumption growth and preferences induced by recursive utility.

Suggested Citation

  • Lars Peter Hansen & Jose A. Scheinkman, 2012. "Recursive utility in a Markov environment with stochastic growth," Working Papers 1380, Princeton University, Department of Economics, Econometric Research Program..
  • Handle: RePEc:pri:metric:wp032_hansen-scheinkman-exist.pdf
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    References listed on IDEAS

    as
    1. Lars Peter Hansen & José A. Scheinkman, 2009. "Long-Term Risk: An Operator Approach," Econometrica, Econometric Society, vol. 77(1), pages 177-234, January.
    2. Michael Stutzer, 2011. "Portfolio choice with endogenous utility: a large deviations approach," World Scientific Book Chapters, in: Leonard C MacLean & Edward O Thorp & William T Ziemba (ed.), THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 43, pages 619-640, World Scientific Publishing Co. Pte. Ltd..
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    4. Larry G. Epstein & Stanley E. Zin, 2013. "Substitution, risk aversion and the temporal behavior of consumption and asset returns: A theoretical framework," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 12, pages 207-239, World Scientific Publishing Co. Pte. Ltd..
    5. William A. Brock & Leonard J. Mirman, 2001. "Optimal Economic Growth And Uncertainty: The Discounted Case," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 1, pages 3-37, Edward Elgar Publishing.
    6. Balaji, S. & Meyn, S. P., 2000. "Multiplicative ergodicity and large deviations for an irreducible Markov chain," Stochastic Processes and their Applications, Elsevier, vol. 90(1), pages 123-144, November.
    7. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    8. Marinacci, Massimo & Montrucchio, Luigi, 2010. "Unique solutions for stochastic recursive utilities," Journal of Economic Theory, Elsevier, vol. 145(5), pages 1776-1804, September.
    9. Hansen, Lars Peter & Heaton, John & Lee, Junghoon & Roussanov, Nikolai, 2007. "Intertemporal Substitution and Risk Aversion," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 61, Elsevier.
    10. Kreps, David M & Porteus, Evan L, 1978. "Temporal Resolution of Uncertainty and Dynamic Choice Theory," Econometrica, Econometric Society, vol. 46(1), pages 185-200, January.
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    Cited by:

    1. Stefan Nagel & Zhengyang Xu, 2022. "Asset Pricing with Fading Memory," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2190-2245.
    2. Jaroslav Borovička & John Stachurski, 2020. "Necessary and Sufficient Conditions for Existence and Uniqueness of Recursive Utilities," Journal of Finance, American Finance Association, vol. 75(3), pages 1457-1493, June.
    3. Drew D. Creal & Jing Cynthia Wu, 2020. "Bond risk premia in consumption‐based models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1461-1484, November.
    4. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    5. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers 37/14, Institute for Fiscal Studies.
    6. Hansen, Lars Peter, 2013. "Risk Pricing over Alternative Investment Horizons," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1571-1611, Elsevier.
    7. Xiaohong Chen & Jack Favilukis & Sydney C. Ludvigson, 2013. "An estimation of economic models with recursive preferences," Quantitative Economics, Econometric Society, vol. 4(1), pages 39-83, March.
    8. Guo, Jing & He, Xue Dong, 2017. "Equilibrium asset pricing with Epstein-Zin and loss-averse investors," Journal of Economic Dynamics and Control, Elsevier, vol. 76(C), pages 86-108.
    9. Christensen, Timothy M., 2022. "Existence and uniqueness of recursive utilities without boundedness," Journal of Economic Theory, Elsevier, vol. 200(C).
    10. Walter Pohl & Karl Schmedders & Ole Wilms, 2018. "Higher Order Effects in Asset Pricing Models with Long‐Run Risks," Journal of Finance, American Finance Association, vol. 73(3), pages 1061-1111, June.
    11. Timothy M. Christensen, 2020. "Existence and uniqueness of recursive utilities without boundedness," Papers 2008.00963, arXiv.org, revised Aug 2021.
    12. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers CWP37/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Stutzer, Michael, 2020. "Persistence of averages in financial Markov Switching models: A large deviations approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    14. Flint O'Neil, 2020. "Existence and Uniqueness of Recursive Utility Models in $L_p$," Papers 2005.07067, arXiv.org.
    15. Massimo Marinacci & Luigi Montrucchio, 2019. "Unique Tarski Fixed Points," Management Science, INFORMS, vol. 44(4), pages 1174-1191, November.
    16. Guanlong Ren & John Stachurski, 2018. "Dynamic Programming with Recursive Preferences: Optimality and Applications," Papers 1812.05748, arXiv.org, revised Jun 2020.
    17. Guo, Jing & He, Xue Dong, 2021. "A new preference model that allows for narrow framing," Journal of Mathematical Economics, Elsevier, vol. 95(C).
    18. Yu Chen & Thomas Cosimano & Alex Himonas & Peter Kelly, 2014. "An Analytic Approach for Stochastic Differential Utility for Endowment and Production Economies," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 397-443, December.
    19. Irina Zviadadze, 2021. "Term Structure of Risk in Expected Returns [Stock returns and volatility: Pricing the short-run and long-run components of market risk]," The Review of Financial Studies, Society for Financial Studies, vol. 34(12), pages 6032-6086.
    20. Deng, Binbin, 2015. "Regime Learning and Asset Prices in A Long-run Model: Theory," MPRA Paper 79960, University Library of Munich, Germany.

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    More about this item

    Keywords

    recursive utility; Markov process; stochastic growth; large deviations;
    All these keywords.

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General

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