TY - JOUR
T1 - Optimal management of an ecosystem with an unknown threshold
AU - Brozovic, Nicholas
AU - Schlenker, Wolfram
N1 - Funding Information:
This work was supported in part by the USDA National Institute of Food and Agriculture under Hatch project number ILLU-470-316 .
PY - 2011/2/15
Y1 - 2011/2/15
N2 - We consider an ecosystem with two distinct equations of motion that are separated by a threshold value of the state variable. We find that increasing uncertainty (both uncertainty embedded in the natural system and uncertainty of the decisionmaker about the location of the threshold) can lead to nonmonotonic changes in precaution: a reduction in uncertainty can first increase and then decrease optimal precautionary activity. This nonmonotonicity can help to explain why regulators often give conflicting arguments about optimal abatement policies in the face of uncertainty. For example, some regulators argue for an immediate reduction in pollutant loading until uncertainty about the underlying process is reduced while others call for no costly reductions in pollutant loading until the same uncertainty is reduced. These statements can be consistent even if both sides agree on both economic objectives and the system dynamics, but have different priors on the uncertainty involved.
AB - We consider an ecosystem with two distinct equations of motion that are separated by a threshold value of the state variable. We find that increasing uncertainty (both uncertainty embedded in the natural system and uncertainty of the decisionmaker about the location of the threshold) can lead to nonmonotonic changes in precaution: a reduction in uncertainty can first increase and then decrease optimal precautionary activity. This nonmonotonicity can help to explain why regulators often give conflicting arguments about optimal abatement policies in the face of uncertainty. For example, some regulators argue for an immediate reduction in pollutant loading until uncertainty about the underlying process is reduced while others call for no costly reductions in pollutant loading until the same uncertainty is reduced. These statements can be consistent even if both sides agree on both economic objectives and the system dynamics, but have different priors on the uncertainty involved.
KW - Ecosystem management
KW - Stochastic dynamic programming
KW - Threshold
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U2 - 10.1016/j.ecolecon.2010.10.001
DO - 10.1016/j.ecolecon.2010.10.001
M3 - Article
AN - SCOPUS:79451473523
SN - 0921-8009
VL - 70
SP - 627
EP - 640
JO - Ecological Economics
JF - Ecological Economics
IS - 4
ER -