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Accuracy of stochastic perturbation methods: The case of asset pricing models

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  • Collard, Fabrice
  • Juillard, Michel

Abstract

This paper investigates the accuracy of a perturbation method in approximating the solution to stochastic equilibrium models under rational expectations. As a benchmark model, we use a version of asset pricing models proposed by Burnside [1988] which admits a closed-form solution while not making the assumptions of certainty equivalence. We then check the accuracy of perturbation methods -extended to a stochastic environment- against the closed form solution. Second an especially fourth order expansions are then found to be more efficient than standard linear approximation, as they are able to account for higher order moments of the distribution.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 25 (2001)
Issue (Month): 6-7 (June)
Pages: 979-999

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Handle: RePEc:eee:dyncon:v:25:y:2001:i:6-7:p:979-999

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Web page: http://www.elsevier.com/locate/jedc

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  1. R. Mehra & E. Prescott, 2010. "The equity premium: a puzzle," Levine's Working Paper Archive 1401, David K. Levine.
  2. Burnside, Craig, 1998. "Solving asset pricing models with Gaussian shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 22(3), pages 329-340, March.
  3. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
  4. den Haan, Wouter J & Marcet, Albert, 1990. "Solving the Stochastic Growth Model by Parameterizing Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 31-34, January.
  5. Mehra, Rajnish & Prescott, Edward C., 1988. "The equity risk premium: A solution?," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 133-136, July.
  6. Hall, S G & Stephenson, M J, 1990. "An Algorithm for the Solution of Stochastic Optimal Control Problems for Large Nonlinear Econometric Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(4), pages 393-99, Oct.-Dec..
  7. Hercovitz, Z. & Sampson, M., 1989. "Output Growth, The Real Wage, And Employment Fluctuations," RCER Working Papers 179, University of Rochester - Center for Economic Research (RCER).
  8. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  9. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
  10. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, January.
  11. Bennett T. McCallum, 1988. "Real Business Cycle Models," NBER Working Papers 2480, National Bureau of Economic Research, Inc.
  12. Collard, Fabrice & Juillard, Michel, 2001. "A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Nonlinear Phillips Curve Model," Computational Economics, Society for Computational Economics, vol. 17(2-3), pages 125-39, June.
  13. Lucas, Robert E, Jr, 1978. "Asset Prices in an Exchange Economy," Econometrica, Econometric Society, vol. 46(6), pages 1429-45, November.
  14. Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-96, March.
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