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

Tom Kompas and Long Chu

No 95044, Research Reports from Australian National University, Environmental Economics Research Hub

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.

Keywords: Research Methods/ Statistical Methods; Resource/Energy Economics and Policy (search for similar items in EconPapers)
Pages: 33
Date: 2010-09
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: A Comparison of Parametric Approximation Techniques to Continuous-Time Stochastic Dynamic Programming Problems (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:eerhrr:95044

DOI: 10.22004/ag.econ.95044

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