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Solution of continuous-time dynamic models with inequality constraints

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  • Trimborn, Timo

Abstract

I propose a simple method to compute the transition process in continuous-time dynamic equilibrium models with occasionally binding inequality constraints. By augmenting the dynamic system with an auxiliary variable standard algorithms are able to solve the extended dynamic system taking the inequality into account. The procedure can handle any sequence of regimes with binding and non-binding constraints and determines the exact pattern of regimes endogenously.

Suggested Citation

  • Trimborn, Timo, 2013. "Solution of continuous-time dynamic models with inequality constraints," Economics Letters, Elsevier, vol. 119(3), pages 299-301.
    • Handle: RePEc:eee:ecolet:v:119:y:2013:i:3:p:299-301
    DOI: 10.1016/j.econlet.2013.02.026
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    References listed on IDEAS

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    1. Brunner, Martin & Strulik, Holger, 2002. "Solution of perfect foresight saddlepoint problems: a simple method and applications," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 737-753, May.
    2. Trimborn, Timo & Koch, Karl-Josef & Steger, Thomas M., 2008. "Multidimensional Transitional Dynamics: A Simple Numerical Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 12(3), pages 301-319, June.
    3. Carroll, Christopher D., 2006. "The method of endogenous gridpoints for solving dynamic stochastic optimization problems," Economics Letters, Elsevier, vol. 91(3), pages 312-320, June.
    4. Hintermaier, Thomas & Koeniger, Winfried, 2010. "The method of endogenous gridpoints with occasionally binding constraints among endogenous variables," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2074-2088, October.
    5. Michael Grill & Johannes Brumm, 2010. "Computing Equilibria in Dynamic Models with Occasionally Binding Constraints," 2010 Meeting Papers 695, Society for Economic Dynamics.
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    Cited by:

    1. Schünemann, Johannes & Strulik, Holger & Trimborn, Timo, 2017. "Going from bad to worse: Adaptation to poor health health spending, longevity, and the value of life," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 130-146.
    2. Schünemann, Johannes & Trimborn, Timo, 2023. "Boosting taxes for boasting about houses? Status concerns in the housing market," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 120-143.
    3. Strulik, Holger & Trimborn, Timo, 2018. "Hyperbolic discounting can be good for your health," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 44-57.
    4. Strulik, Holger & Trimborn, Timo, 2014. "Natural disasters and macroeconomic performance: The role of residential investment," University of Göttingen Working Papers in Economics 194 [rev.], University of Goettingen, Department of Economics.
    5. Holger Strulik & Timo Trimborn, 2019. "Natural Disasters and Macroeconomic Performance," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(4), pages 1069-1098, April.
    6. Trimborn, Timo, 2018. "On the analysis of endogenous growth models with a balanced growth path," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 40-50.
    7. Strulik Holger & Trimborn Timo, 2017. "The Spending Multiplier in the Medium Run," German Economic Review, De Gruyter, vol. 18(2), pages 154-181, May.
    8. Klaus Prettner & Timo Trimborn, 2017. "Demographic Change and R&D-based Economic Growth," Economica, London School of Economics and Political Science, vol. 84(336), pages 667-681, October.
    9. Anna M. Dugan & Timo Trimborn, 2020. "The Optimal Extraction of Non-Renewable Resources under Hyperbolic Discounting," Economics Working Papers 2020-17, Department of Economics and Business Economics, Aarhus University.

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    More about this item

    Keywords

    Inequality constraint; Continuous-time dynamic models; Transitional dynamics; Ramsey model;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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