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On the stability of the constant relative risk aversion (CRRA) utility under high degrees of uncertainty

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  • Ñíguez, Trino-Manuel
  • Paya, Ivan
  • Peel, David
  • Perote, Javier

Abstract

Growth models under uncertainty and constant relative risk aversion (CRRA) utility are fragile in explaining consumers’ choice, as equilibrium consumption is dependent on distributional assumptions. We show that, under semi-nonparametric distributions, general equilibrium models are stable, as the existence of expected utility is guaranteed.

Suggested Citation

  • Ñíguez, Trino-Manuel & Paya, Ivan & Peel, David & Perote, Javier, 2012. "On the stability of the constant relative risk aversion (CRRA) utility under high degrees of uncertainty," Economics Letters, Elsevier, vol. 115(2), pages 244-248.
  • Handle: RePEc:eee:ecolet:v:115:y:2012:i:2:p:244-248
    DOI: 10.1016/j.econlet.2011.12.049
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    References listed on IDEAS

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    5. Cogley, Timothy, 2009. "Is the market price of risk infinite?," Economics Letters, Elsevier, vol. 102(1), pages 13-16, January.
    6. Bakshi, Gurdip & Skoulakis, Georgios, 2010. "Do subjective expectations explain asset pricing puzzles?," Journal of Financial Economics, Elsevier, vol. 98(3), pages 462-477, December.
    7. Bidarkota, Prasad V. & Dupoyet, Brice V. & McCulloch, J. Huston, 2009. "Asset pricing with incomplete information and fat tails," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1314-1331, June.
    8. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    9. Yoon, Gawon, 2004. "On the existence of expected utility with CRRA under STUR," Economics Letters, Elsevier, vol. 83(2), pages 219-224, May.
    10. Leon, Angel & Rubio, Gonzalo & Serna, Gregorio, 2005. "Autoregresive conditional volatility, skewness and kurtosis," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 599-618, September.
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    12. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
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    Citations

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    Cited by:

    1. Lina Cortés & Juan M. Lozada & Javier Perote, 2019. "Firm size and concentration inequality: A flexible extension of Gibrat’s law," Documentos de Trabajo CIEF 017205, Universidad EAFIT.
    2. repec:spr:comaot:v:23:y:2017:i:3:d:10.1007_s10588-016-9231-3 is not listed on IDEAS
    3. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017. "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 35-47.
    4. Trino-Manuel Niguez & Ivan Paya & David Peel & Javier Perote, 2013. "Higher-order moments in the theory of diversification and portfolio composition," Working Papers 18297128, Lancaster University Management School, Economics Department.
    5. Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2017. "Multivariate approximations to portfolio return distribution," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 347-361, September.
    6. Lina M. Cortés & Javier Perote & Andrés Mora-Valencia, 2017. "Implicit probability distribution for WTI options: The Black Scholes vs. the semi-nonparametric approach," Documentos de Trabajo CIEF 015923, Universidad EAFIT.
    7. Lina M. Cortés & Andrés Mora-Valencia & Javier Perote, 2016. "The productivity of top researchers: a semi-nonparametric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 891-915, November.

    More about this item

    Keywords

    Bayesian learning; Rational expectations; Semi-nonparametric distributions;

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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