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Using Nonlinear Model Predictive Control for Dynamic Decision Problems in Economics

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  • Willi Semmler
  • Lars Grüne
  • Marleen Stieler

Abstract

This paper presents a new approach to solve dynamic decision models in economics. The proposed procedure, called Nonlinear Model Predictive Control (NMPC), relies on the iterative solution of optimal control problems on finite time horizons and is well established in engineering applications for stabilization and tracking problems. Only quite recently, extensions to more general optimal control problems including those appearing in economic applications have been investigated. Like Dynamic Programming (DP), NMPC does not rely on linearization techniques but uses the full nonlinear model and in this sense provides a global solution to the problem. However, unlike DP, NMPC only computes one optimal trajectory at a time, thus avoids to grid the state space and for this reason the computational demand grows much more moderate than for DP. In this paper we explain the basic idea of NMPC together with some implementational details and illustrate its ability to solve dynamic decision problems in economics by means of numerical simulations for various examples, including stochastic problems, models with multiple equilibria and regime switches in the dynamics. See above See above

Suggested Citation

  • Willi Semmler & Lars Grüne & Marleen Stieler, 2013. "Using Nonlinear Model Predictive Control for Dynamic Decision Problems in Economics," EcoMod2013 5782, EcoMod.
  • Handle: RePEc:ekd:004912:5782
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    File URL: http://ecomod.net/system/files/usingNMPCFeb21.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Gevorkyan, Arkady & Semmler, Willi, 2016. "Oil price, overleveraging and shakeout in the shale energy sector — Game changers in the oil industry," Economic Modelling, Elsevier, vol. 54(C), pages 244-259.
    2. Lilia Maliar & Serguei Maliar & John B. Taylor & Inna Tsener, 2015. "A Tractable Framework for Analyzing a Class of Nonstationary Markov Models," Economics Working Papers 15105, Hoover Institution, Stanford University.
    3. Christian R. Proaño & Christian Schoder & Willi Semmler, 2013. "Financial Stress, Sovereign Debt and Economic Activity in Industrialized Countries: Evidence from Nonlinear Dynamic Panels," Working Papers 1304, New School for Social Research, Department of Economics.
    4. Willi Semmler & Alexander Haider, 2016. "The perils of debt deflation in the Euro area: a multi regime model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 43(2), pages 257-278, May.
    5. Schleer, Frauke & Semmler, Willi, 2015. "Financial sector and output dynamics in the euro area: Non-linearities reconsidered," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 235-263.
    6. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    7. Proaño, Christian R. & Schoder, Christian & Semmler, Willi, 2014. "Financial stress, sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions," Journal of International Money and Finance, Elsevier, vol. 45(C), pages 17-37.
    8. Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    9. repec:eee:ecosta:v:6:y:2018:i:c:p:44-56 is not listed on IDEAS
    10. repec:eee:dyncon:v:81:y:2017:i:c:p:115-139 is not listed on IDEAS
    11. Anthony Bonen & Prakash Loungani & Willi Semmler & Sebastian Koch, 2016. "Investing to Mitigate and Adapt to Climate Change; A Framework Model," IMF Working Papers 16/164, International Monetary Fund.
    12. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2017. "Debt-deflation, financial market stress and regime change – Evidence from Europe using MRVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 115-139.
    13. Semmler, Willi & Gross, Marco, 2017. "Mind the output gap: the disconnect of growth and inflation during recessions and convex Phillips curves in the euro area," Working Paper Series 2004, European Central Bank.
    14. Herbert Dawid & Michel Y. Keoula & Peter M. Kort, 2017. "Numerical Analysis of Markov-Perfect Equilibria with Multiple Stable Steady States: A Duopoly Application with Innovative Firms," Dynamic Games and Applications, Springer, vol. 7(4), pages 555-577, December.
    15. repec:eee:streco:v:41:y:2017:i:c:p:29-42 is not listed on IDEAS
    16. Gross, Marco & Henry, Jérôme & Semmler, Willi, 2017. "Destabilizing effects of bank overleveraging on real activity - an analysis based on a threshold MCS-GVAR," Working Paper Series 2081, European Central Bank.
    17. Mutschler, Willi, 2018. "Higher-order statistics for DSGE models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 44-56.
    18. Di Bartolomeo Giovanni & Saltari Enrico & Semmler Willi, 2017. "Inattention and pollution regulation policies," wp.comunite 00130, Department of Communication, University of Teramo.
    19. Semmler, Willi & Tahri, Ibrahim, 2017. "Current account imbalances: A new approach to assess external debt sustainability," Economic Modelling, Elsevier, vol. 62(C), pages 161-170.
    20. Serguei Maliar & John Taylor & Lilia Maliar, 2016. "The Impact of Alternative Transitions to Normalized Monetary Policy," 2016 Meeting Papers 794, Society for Economic Dynamics.
    21. Charpe, Matthieu & Kühn, Stefan, 2015. "Demand and supply effects of bargaining power shocks," Economic Modelling, Elsevier, vol. 51(C), pages 21-32.
    22. repec:eee:riibaf:v:42:y:2017:i:c:p:468-479 is not listed on IDEAS

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    Keywords

    NA; Modeling: new developments; Modeling: new developments;

    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

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