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Analysis Of Rangeland Degradation Using Stochastic Dynamic Programming

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  • Passmore, J.G.
  • Brown, Colin G.

Abstract

Degradation of arid rangeland, and efforts to control that degradation, have become topical issues. However, the inherent characteristics of the rangeland, and the intertemporal nature of the problem, complicate the analysis of degradation issues in the search for more appropriate rangeland policies. Stochastic dynamic programming is examined as one means of allowing for those complexities. Using the case of the Queensland mulga rangelands, optimal stocking rates are shown to rise with lower property sizes, higher discount rates, higher wool prices and declining risk aversion. Importantly, the analysis reveals that a strategy of high stocking rates with the potential for rangeland degradation is an optimal response to the economic and social factors that confront graziers and is not an intertemporal information problem alone.

Suggested Citation

  • Passmore, J.G. & Brown, Colin G., 1991. "Analysis Of Rangeland Degradation Using Stochastic Dynamic Programming," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 35(2), pages 1-27, August.
    • Handle: RePEc:ags:ajaeau:22765
    DOI: 10.22004/ag.econ.22765
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    4. Johnson Kakeu, 2023. "Concerns for Long-Run Risks and Natural Resource Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 1051-1093, April.
    5. Janssen, Marco A. & Anderies, John M. & Walker, Brian H., 2004. "Robust strategies for managing rangelands with multiple stable attractors," Journal of Environmental Economics and Management, Elsevier, vol. 47(1), pages 140-162, January.

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