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Computation Of Business Cycle Models: A Comparison Of Numerical Methods

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  • Heer, Burkhard
  • Maußner, Alfred

Abstract

We compare the numerical methods that are most widely applied in the computation of the standard business cycle model with flexible labor. The numerical techniques imply economically insignificant differences with regard to business cycle summary statistics. Furthermore, these results are robust with regard to the choice of the functional form of the utility function and the model's parameterization. In addition, the extended path approach, albeit time-consuming, and the Galerkin projection are found to be the most accurate methods, given that we have not used function approximations beyond the second degree.

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  • Heer, Burkhard & Maußner, Alfred, 2008. "Computation Of Business Cycle Models: A Comparison Of Numerical Methods," Macroeconomic Dynamics, Cambridge University Press, vol. 12(5), pages 641-663, November.
    • Handle: RePEc:cup:macdyn:v:12:y:2008:i:05:p:641-663_07
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    Cited by:

    1. 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.
    2. Heer Burkhard & Maußner Alfred, 2011. "Value Function Iteration as a Solution Method for the Ramsey Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(4), pages 494-515, August.
    3. 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.
    4. Larin, Benjamin, 2016. "Bubble-driven business cycles," Working Papers 143, University of Leipzig, Faculty of Economics and Management Science.
    5. Burkhard Heer & Alfred Maußner, 2009. "Computation of business‐cycle models with the Generalized Schur method," Indian Growth and Development Review, Emerald Group Publishing Limited, vol. 2(2), pages 173-182, September.
    6. Paul Pichler, 2005. "Evaluating Approximate Equilibria of Dynamic Economic Models," Vienna Economics Papers 0510, University of Vienna, Department of Economics.
    7. Heiberger, Christopher & Klarl, Torben & Maußner, Alfred, 2015. "On the uniqueness of solutions to rational expectations models," Economics Letters, Elsevier, vol. 128(C), pages 14-16.
    8. Hull, Isaiah, 2015. "Approximate dynamic programming with post-decision states as a solution method for dynamic economic models," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 57-70.
    9. Devarajan, Shantayanan & Dissou, Yazid & Go, Delfin S. & Robinson, Sherman, 2014. "Budget rules and resource booms: A dynamic stochastic general equilibrium analysis," Conference papers 332455, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    10. Christophe Gouel, 2013. "Comparing Numerical Methods for Solving the Competitive Storage Model," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 267-295, February.
    11. Heer Burkhard & Maußner Alfred, 2013. "Asset Returns, the Business Cycle and the Labor Market," German Economic Review, De Gruyter, vol. 14(3), pages 372-397, August.
    12. 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.
    13. Burkhard Heer & Alfred Maussner, 2011. "Asset Returns, the Business Cycle, and the Labor Market: A Sensitivity Analysis for the German Economy," CESifo Working Paper Series 3391, CESifo.
    14. Kollmann, Robert & Maliar, Serguei & Malin, Benjamin A. & Pichler, Paul, 2011. "Comparison of solutions to the multi-country Real Business Cycle model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 186-202, February.
    15. Heiberger, Christopher & Maußner, Alfred, 2020. "Perturbation solution and welfare costs of business cycles in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    16. 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.
    17. Cheng-Wei Chang & Ching-Chong Lai & Juin-Jen Chang, 2018. "Fiscal Stimulus and Endogenous Firm Entry in a Monopolistic Competition Macroeconomic Model," The Japanese Economic Review, Springer, vol. 69(2), pages 207-225, June.
    18. Christopher Heiberger & Alfred Maussner, 2018. "Business Cycle Uncertainty and Economic Welfare Revisited," Discussion Paper Series 335, Universitaet Augsburg, Institute for Economics.
    19. 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.
    20. Atolia, Manoj & Gibson, John & Marquis, Milton, 2018. "Asymmetry And The Amplitude Of Business Cycle Fluctuations: A Quantitative Investigation Of The Role Of Financial Frictions," Macroeconomic Dynamics, Cambridge University Press, vol. 22(2), pages 279-306, March.
    21. Viktors Ajevskis, 2019. "Generalised Impulse Response Function as a Perturbation of a Global Solution to DSGE Models," Working Papers 2019/04, Latvijas Banka.
    22. Christopher Heiberger & Torben Klarl & Alfred Maussner, 2012. "A Note on the Uniqueness of Solutions to Rational Expectations Models," Discussion Paper Series 319, Universitaet Augsburg, Institute for Economics.
    23. Benjamin Larin, 2018. "A Quantitative Model of Bubble-Driven Business Cycles," 2018 Meeting Papers 662, Society for Economic Dynamics.

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    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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