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Solving the Stochastic Growth Model by Deterministic Extended Path

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  • Gagnon, Joseph E

Abstract

This article describes the use of the deterministic version of the extended-path algorithm to solve the simple stochastic growth model. The article also discusses the two sources of approximation error inherent in this method. It is demonstrated that the error due to numerical iterations is small. No general conclusion can be reached on the error that arises from the algorithm's treatment of expectations. In at least two specific cases, however, this error appears to be small.

Suggested Citation

  • Gagnon, Joseph E, 1990. "Solving the Stochastic Growth Model by Deterministic Extended Path," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 35-36, January.
    • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:1:p:35-36
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    Cited by:

    1. 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.
    2. Dissou, Yazid & Karnizova, Lilia, 2016. "Emissions cap or emissions tax? A multi-sector business cycle analysis," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 169-188.
    3. Shantayanan Devarajan & Yazid Dissou & Delfin S. Go & Sherman Robinson, 2017. "Budget Rules and Resource Booms and Busts: A Dynamic Stochastic General Equilibrium Analysis," The World Bank Economic Review, World Bank, vol. 31(1), pages 71-96.
    4. David R.F. Love, 2009. "Accuracy of Deterministic Extended-Path Solution Methods for Dynamic Stochastic Optimization Problems in Macroeconomics," Working Papers 0907, Brock University, Department of Economics.
    5. Ajevskis, Viktors, 2019. "Nonlocal Solutions To Dynamic Equilibrium Models: The Approximate Stable Manifolds Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 23(6), pages 2544-2571, September.
    6. David R. F. Love, 2011. "Aggregate Comovements, Anticipation, and Business Cycles," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(1), pages 93-110.
    7. Istvan Konya, 2023. "Catching up or getting stuck: convergence in Eastern European economies," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 237-258, June.
    8. David R.F. Love, 2010. "Revisiting deterministic extended-path: a simple and accurate solution method for macroeconomic models," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 1(3/4), pages 309-316.
    9. Schmidt, Sebastian & Wieland, Volker, 2013. "The New Keynesian Approach to Dynamic General Equilibrium Modeling: Models, Methods and Macroeconomic Policy Evaluation," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 1439-1512, Elsevier.
    10. Adda, Jerome & Boucekkine, Raouf, 1995. "Liquidity constraints and time non-separable preferences: simulating models with large state spaces," UC3M Working papers. Economics 3911, Universidad Carlos III de Madrid. Departamento de Economía.
    11. ADJEMIAN Stéphane & JUILLARD Michel, 2010. "Dealing with ZLB in DSGE models An application to the Japanese economy," ESRI Discussion paper series 258, Economic and Social Research Institute (ESRI).
    12. Larin, Benjamin, 2016. "Bubble-driven business cycles," Working Papers 143, University of Leipzig, Faculty of Economics and Management Science.
    13. David R.F. Love, 2008. "A Note on the Accuracy of Extended-Path Solution Methods for Dynamic General Equilibrium Economies," Working Papers 0801, Brock University, Department of Economics, revised Apr 2008.
    14. Dissou, Yazid & Mac Leod, Carolyn & Souissi, Mokhtar, 2002. "Compliance costs to the Kyoto Protocol and market structure in Canada: a dynamic general equilibrium analysis," Journal of Policy Modeling, Elsevier, vol. 24(7-8), pages 751-779, November.
    15. Devarajan, Shantayanan & Dissou, Yazid & Go, Delfin S. & Robinson, Sherman, 2014. "Budget rules and resource booms : a dynamic stochastic general equilibrium analysis," Policy Research Working Paper Series 6984, The World Bank.
    16. Einarsson, Tor & Marquis, Milton H., 1998. "An RBC model with growth: the role of human capital," Journal of Economics and Business, Elsevier, vol. 50(5), pages 431-444, September.
    17. Jeffrey C. Fuhrer & C. Hoyt Bleakley, "undated". "Computationally Efficient Solution and Maximum Likelihood Estimation of Nonlinear Rational Expectations Models," Computing in Economics and Finance 1997 35, Society for Computational Economics.
    18. Daniel Baksa & Istvan Konya, 2019. "Convergence, productivity and debt: the case of Hungary," CERS-IE WORKING PAPERS 1916, Institute of Economics, Centre for Economic and Regional Studies.
    19. David R.F. Love & Jean-Francois Lamarche, 2004. "Anticipation and Real Business Cycles," Working Papers 0703, Brock University, Department of Economics, revised Sep 2007.
    20. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
    21. Larin, Benjamin, 2016. "A Quantitative Model of Bubble-Driven Business Cycles," VfS Annual Conference 2016 (Augsburg): Demographic Change 145817, Verein für Socialpolitik / German Economic Association.
    22. Benjamin Larin, 2018. "A Quantitative Model of Bubble-Driven Business Cycles," 2018 Meeting Papers 662, Society for Economic Dynamics.

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