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A Comparison of Parametric Approximation Techniques to Continuous-Time Stochastic Dynamic Programming Problems

Author

Listed:
  • Tom Kompas

    (Crawford School of Public Policy, and The Australian Centre for Biosecurity and Environmental Economics, Australian National University)

  • Long Chu

    (Crawford School of Public Policy, Australian National University)

Abstract

We compare three parametric techniques to approximate Hamilton-Jacobi-Bellman equations via unidimensional and multidimensional problems. The linear programming technique is very efficient for unidimensional problems and offers a balance of speed and accuracy for multidimensional problems. A comparable projection technique is shown to be slow, but has stable accuracy, whereas a perturbation technique has the least accuracy although its speed suffers least from the curse of dimensionality. The linear programming technique is also shown to be suitable for problems in resource management, including applications to biosecurity and marine reserve design.

Suggested Citation

  • Tom Kompas & Long Chu, 2010. "A Comparison of Parametric Approximation Techniques to Continuous-Time Stochastic Dynamic Programming Problems," Environmental Economics Research Hub Research Reports 1071, Environmental Economics Research Hub, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:eenhrr:1071
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    File URL: https://crawford.anu.edu.au/research_units/eerh/pdf/EERH_RR71.pdf
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    References listed on IDEAS

    as
    1. Judd, Kenneth L., 1996. "Approximation, perturbation, and projection methods in economic analysis," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 12, pages 509-585, Elsevier.
    2. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
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    Cited by:

    1. Parra-Alvarez, Juan Carlos, 2018. "A Comparison Of Numerical Methods For The Solution Of Continuous-Time Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 22(6), pages 1555-1583, September.

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    More about this item

    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
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery

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