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Solving the Stochastic Growth Model by Backsolving with a Particular Nonlinear Form for the Decision Rule

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  • Sims, Christopher A

Abstract

Backsolving is a class of methods that generate simulated values for exogenous forcing processes in a stochastic equilibrium model from specified assumed distributions for Euler-equation disturbances. It can be thought of as a way to force the approximation error generated by inexact choice of decision rule or boundary condition into distortions of the distribution of the exogenous shocks in the simulations rather than into violations of the Euler equations as with standard approaches. Here it is applied to a one-sector neoclassical growth model with decision rule generated from a linear-quadratic approximation.

Suggested Citation

  • Sims, Christopher A, 1990. "Solving the Stochastic Growth Model by Backsolving with a Particular Nonlinear Form for the Decision Rule," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 45-47, January.
    • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:1:p:45-47
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    1. David de la Croix & Frédéric Docquier, 2007. "School Attendance and Skill Premiums in France and the US: A General Equilibrium Approach," Fiscal Studies, Institute for Fiscal Studies, vol. 28(4), pages 383-416, December.
    2. Boucekkine, Raouf, 1992. "Quelques idées simples pour la simulation stochastique des modèles non-linéaires à anticipations rationnelles et méthodes de validation," CEPREMAP Working Papers (Couverture Orange) 9215, CEPREMAP.
    3. de la Croix, David & Docquier, Frederic & Liegeois, Philippe, 2007. "Income growth in the 21st century: Forecasts with an overlapping generations model," International Journal of Forecasting, Elsevier, vol. 23(4), pages 621-635.
    4. Xavier Chojnicki & Lionel Ragot, 2016. "Impacts of Immigration on an Ageing Welfare State: An Applied General Equilibrium Model for France," Fiscal Studies, Institute for Fiscal Studies, vol. 37, pages 258-284, June.
    5. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
    6. Sargent, Thomas J & Velde, Francois R, 1999. "The Big Problem of Small Change," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(2), pages 137-161, May.
    7. Hanno Lustig & Stijn Van Nieuwerburgh, 2002. "Housing Collateral, Consumption Insurance and Risk Premia," Macroeconomics 0211008, University Library of Munich, Germany.
    8. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2017. "Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models," Econometrica, Econometric Society, vol. 85, pages 991-1012, May.
    9. Alfonso Novales & Javier J. PÈrez, 2004. "Is It Worth Refining Linear Approximations to Non-Linear Rational Expectations Models?," Computational Economics, Springer;Society for Computational Economics, vol. 23(4), pages 343-377, June.
    10. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    11. Cogley, Timothy, 2001. "Estimating and testing rational expectations models when the trend specification is uncertain," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1485-1525, October.
    12. José Mô Martín Moreno & Jesús Ruiz, "undated". "Bienes comerciables y no comerciables en la economía espanola: Un enfoque de ciclo real," Studies on the Spanish Economy 206, FEDEA.
    13. Kenneth L. Judd, 1991. "Minimum weighted residual methods for solving aggregate growth models," Discussion Paper / Institute for Empirical Macroeconomics 49, Federal Reserve Bank of Minneapolis.
    14. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2014. "Lower Bounds on Approximation Errors: Testing the Hypothesis That a Numerical Solution Is Accurate?," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-06, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    15. Chojnicki, Xavier & Docquier, Frédéric & Ragot, Lionel, 2005. "Should the U.S. Have Locked the Heaven's Door? Reassessing the Benefits of the Postwar Immigration," IZA Discussion Papers 1676, Institute of Labor Economics (IZA).

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