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Computation of Business Cycle Models: A Comparison of Numerical Methods

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  • Burkhard Heer
  • Alfred Maussner

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 except for the volatility of investment. Furthermore, these results are robust with regard to the choice of the functional form of the utility function and the model’s parameterization. In conclusion, the simplest and fastest method, the log-linearization of the model around the steady state, is found to be most convenient and appropriate for the standard business cycle model.

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  • Burkhard Heer & Alfred Maussner, 2004. "Computation of Business Cycle Models: A Comparison of Numerical Methods," CESifo Working Paper Series 1207, CESifo.
    • Handle: RePEc:ces:ceswps:_1207
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    1. David Domeij & Martin Floden, 2006. "The Labor-Supply Elasticity and Borrowing Constraints: Why Estimates are Biased," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(2), pages 242-262, April.
    2. Altonji, Joseph G, 1986. "Intertemporal Substitution in Labor Supply: Evidence from Micro Data," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 176-215, June.
    3. 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.
    4. Duffy, John & McNelis, Paul D., 2001. "Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1273-1303, September.
    5. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
    6. Ligita Gasparėnienė & Rita Remeikienė & Colin C. Williams, 2022. "Introduction," SpringerBriefs in Economics, in: Unemployment and the Informal Economy, chapter 0, pages 1-6, Springer.
    7. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
    8. Heer, Burkhard & Trede, Mark, 2003. "Efficiency and distribution effects of a revenue-neutral income tax reform," Journal of Macroeconomics, Elsevier, vol. 25(1), pages 87-107, March.
    9. Wright, Brian D & Williams, Jeffrey C, 1982. "The Economic Role of Commodity Storage," Economic Journal, Royal Economic Society, vol. 92(367), pages 596-614, September.
    10. Brian D. Wright & Jeffrey C. Williams, 1984. "The Welfare Effects of the Introduction of Storage," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 99(1), pages 169-192.
    11. Greenwood, Jeremy & Hercowitz, Zvi & Huffman, Gregory W, 1988. "Investment, Capacity Utilization, and the Real Business Cycle," American Economic Review, American Economic Association, vol. 78(3), pages 402-417, June.
    12. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
    13. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Christopher Heiberger & Alfred Maussner, 2018. "Business Cycle Uncertainty and Economic Welfare Revisited," Discussion Paper Series 335, Universitaet Augsburg, Institute for Economics.
    10. 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.
    11. 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.
    12. Larin, Benjamin, 2016. "Bubble-driven business cycles," Working Papers 143, University of Leipzig, Faculty of Economics and Management Science.
    13. Viktors Ajevskis, 2019. "Generalised Impulse Response Function as a Perturbation of a Global Solution to DSGE Models," Working Papers 2019/04, Latvijas Banka.
    14. 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.
    15. 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.
    16. Burkhard Heer & Alfred Maußner, 2013. "Asset Returns, the Business Cycle and the Labor Market," German Economic Review, Verein für Socialpolitik, vol. 14(3), pages 372-397, August.
    17. Paul Pichler, 2005. "Evaluating Approximate Equilibria of Dynamic Economic Models," Vienna Economics Papers 0510, University of Vienna, Department of Economics.
    18. 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.
    19. 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.
    20. 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.
    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.
    23. 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.

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    More about this item

    Keywords

    log-linearization; projection methods; extended path; value function iteration; parameterized expectations; genetic search;
    All these keywords.

    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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