In this paper stochastic dynamic programming is used to investigate land conversion decisions taken by a multitude of landholders under uncertainty about the value of environmental services and irreversible development. We study land conversion under competition on the market for agricultural products when voluntary and mandatory measures are combined by the Government to induce habitat conservation. We show that land conversion can be delayed by paying landholders for the provision of environmental services and by limiting the individual extent of developable land. It is found, instead, that the presence of ceilings on aggregate conversion may lead to runs which rapidly exhaust the targeted amount of land. We study the impact of uncertainty on the optimal conversion policy and discuss conversion dynamics under different policy scenarios on the basis of the relative long-run expected rate of deforestation. Interestingly, we show that uncertainty, even if it induces conversion postponement in the short-run, increases the average rate of deforestation and reduces expected time for total conversion in the long run. Finally, we illustrate our findings through some numerical simulations. © 2013 Springer-Verlag Wien.

Land conversion pace under uncertainty and irreversibility: Too fast or too slow?

DI CORATO, Luca;
2013-01-01

Abstract

In this paper stochastic dynamic programming is used to investigate land conversion decisions taken by a multitude of landholders under uncertainty about the value of environmental services and irreversible development. We study land conversion under competition on the market for agricultural products when voluntary and mandatory measures are combined by the Government to induce habitat conservation. We show that land conversion can be delayed by paying landholders for the provision of environmental services and by limiting the individual extent of developable land. It is found, instead, that the presence of ceilings on aggregate conversion may lead to runs which rapidly exhaust the targeted amount of land. We study the impact of uncertainty on the optimal conversion policy and discuss conversion dynamics under different policy scenarios on the basis of the relative long-run expected rate of deforestation. Interestingly, we show that uncertainty, even if it induces conversion postponement in the short-run, increases the average rate of deforestation and reduces expected time for total conversion in the long run. Finally, we illustrate our findings through some numerical simulations. © 2013 Springer-Verlag Wien.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/192529
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