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Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models

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  • Toda, Alexis Akira
  • Walsh, Kieran James

Abstract

The standard generalized method of moments (GMM) estimation of Euler equations in heterogeneous-agent consumption-based asset pricing models is inconsistent under fat tails because the GMM criterion is asymptotically random. To illustrate this, we generate asset returns and consumption data from an incomplete-market dynamic general equilibrium model that is analytically solvable and exhibits power laws in consumption. Monte Carlo experiments suggest that the standard GMM estimation is inconsistent and susceptible to Type II errors (incorrect non-rejection of false models). Estimating an overidentified model by dividing agents into age cohorts appears to mitigate Type I and II errors.

Suggested Citation

  • Toda, Alexis Akira & Walsh, Kieran James, 2016. "Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models," MPRA Paper 78980, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:78980
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    References listed on IDEAS

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    1. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692106, January.
    2. Basu, Parantap & Semenov, Andrei & Wada, Kenji, 2011. "Uninsurable risk and financial market puzzles," Journal of International Money and Finance, Elsevier, vol. 30(6), pages 1055-1089, October.
    3. Krueger, Dirk & Lustig, Hanno, 2010. "When is market incompleteness irrelevant for the price of aggregate risk (and when is it not)?," Journal of Economic Theory, Elsevier, vol. 145(1), pages 1-41, January.
    4. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871549, January.
    5. Toda, Alexis Akira, 2017. "A Note On The Size Distribution Of Consumption: More Double Pareto Than Lognormal," Macroeconomic Dynamics, Cambridge University Press, vol. 21(6), pages 1508-1518, September.
    6. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871532, January.
    7. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692090, January.
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    Cited by:

    1. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    2. repec:cdl:ucsdec:qt9k5027d0 is not listed on IDEAS
    3. Warusawitharana, Missaka, 2018. "Time-varying volatility and the power law distribution of stock returns," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 123-141.
    4. repec:cdl:ucsdec:qt90n2h2bb is not listed on IDEAS
    5. Wilson, Matthew S., 2020. "Disaggregation and the equity premium puzzle," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 1-18.
    6. Alexis Akira Toda & Yulong Wang, 2021. "Efficient minimum distance estimation of Pareto exponent from top income shares," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 228-243, March.
    7. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    8. Emilien Gouin-Bonenfant & Alexis Akira Toda, 2019. "Pareto Extrapolation: Bridging Theoretical and Quantitative Models of Wealth Inequality," 2019 Meeting Papers 152, Society for Economic Dynamics.
    9. Toda, Alexis Akira, 2019. "Wealth distribution with random discount factors," Journal of Monetary Economics, Elsevier, vol. 104(C), pages 101-113.
    10. Abootaleb Shirvani & Stoyan V. Stoyanov & Frank J. Fabozzi & Svetlozar T. Rachev, 2021. "Equity premium puzzle or faulty economic modelling?," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1329-1342, May.
    11. repec:cdl:ucsdec:qt5n29f260 is not listed on IDEAS
    12. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    13. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.

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    Keywords

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    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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