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Accuracy in Simulations

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  • Den Haan, Wouter J
  • Marcet, Albert

Abstract

Since the actual solution to intertemporal rational expectations models is usually not known, it is useful to have criteria for judging the accuracy of a given numerical solution. In this paper, the authors propose a test for accuracy that is easy to implement and can be applied to a wide class of models without knowledge of the exact solution. They discuss the power of the test by simulating several models with the linear-quadratic approximation and with the method of parametrized expectations. The authors conclude that the test is powerful. Copyright 1994 by The Review of Economic Studies Limited.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Review of Economic Studies.

Volume (Year): 61 (1994)
Issue (Month): 1 (January)
Pages: 3-17

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Handle: RePEc:bla:restud:v:61:y:1994:i:1:p:3-17

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  1. Albert Marcet & Ramon Marimon, 1992. "Communication, commitment, and growth," Discussion Paper / Institute for Empirical Macroeconomics 74, Federal Reserve Bank of Minneapolis.
  2. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  3. 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.
  4. John B. Taylor & Harald Uhlig, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," NBER Working Papers 3117, National Bureau of Economic Research, Inc.
  5. Miller, Robert A, 1984. "Job Matching and Occupational Choice," Journal of Political Economy, University of Chicago Press, vol. 92(6), pages 1086-120, December.
  6. Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Cowles Foundation Discussion Papers 564, Cowles Foundation for Research in Economics, Yale University.
  7. 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.
  8. Cooley, T.F. & Hansen, G.D., 1988. "The Inflation Tax In A Real Business Cycle Model," RCER Working Papers 155, University of Rochester - Center for Economic Research (RCER).
  9. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  10. Coleman, Wilbur John, II, 1991. "Equilibrium in a Production Economy with an Income Tax," Econometrica, Econometric Society, vol. 59(4), pages 1091-1104, July.
  11. Christiano, Lawrence J, 1990. "Linear-Quadratic Approximation and Value-Function Iteration: A Comparison," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 99-113, January.
  12. Novales, Alfonso, 1990. "Solving Nonlinear Rational Expectations Models: A Stochastic Equilibrium Model of Interest Rates," Econometrica, Econometric Society, vol. 58(1), pages 93-111, January.
  13. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
  14. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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  1. > Schools of Economic Thought, Epistemology of Economics > Economic Methodology > Dynamic Stochastic General Equilibrium > Solution Methods for DSGE models
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