Model Uncertainty, Ambiguity and the Precautionary Principle: Implications for Biodiversity Management

Vardas, Giannis; Xepapadeas, Anastasios

doi:10.2139/ssrn.1221102

Cited by 15 publications

(17 citation statements)

References 22 publications

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“…Chichilnisky (2000) and Bretteville Froyn (2005), as well as dynamic models using a robust control approach with applications to e.g. water management Roseta-Palma and Xepapadeas (2004), climate change Hennlock (2008b) and biodiversity management Vardas and Xepapadeas (2008). In climate change policy, the maximin criterion may be used to model uncertainty aversion and precautionary concerns when the decision-maker has doubts about imperfect measurements of uncertainty in climate modeling and impact damage outcomes.…”

Section: Probmentioning

confidence: 99%

Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

Hennlock

2009

SSRN Journal

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Imperfect measurement of uncertainty (deeper uncertainty) in climate sensitivity is introduced in a two-sectoral integrated assessment model (IAM) with endogenous growth, based on an extension of DICE. The household expresses ambiguity aversion and can use robust control via a 'shadow ambiguity premium' on social carbon cost to identify robust climate policy feedback rules that work well over a range such as the IPCC climate sensitivity range (IPCC, 2007a). Ambiguity aversion, in combination with linear damage, increases carbon cost in a similar way as a low pure rate of time preference. However, ambiguity aversion in combination with non-linear damage would also make policy more responsive to changes in climate data observations. Perfect ambiguity aversion results in an infinite expected shadow carbon cost and a zero carbon consumption path. Dynamic programming identifies an analytically tractable solution to the IAM.

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Section: Probmentioning

confidence: 99%

Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

Hennlock

2009

SSRN Journal

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“…Gonzales [9] applied robust control to the regulation of a stock pollutant under multiplicative uncertainty (first introduced by Hoel and Karp [12]). Roseta-Palma and Xepapadeas [20] studied water management under ambiguity, while Vardas and Xepapadeas [25] did the same in the context of biodiversity management. Both these contributions focused on determining the "cost of precaution," that is, the decrease in utility that model misspecification leads to.…”

Section: Introductionmentioning

confidence: 99%

Pollution Control: When, and How, to Be Precautious

Athanassoglou

Xepapadeas

2011

SSRN Journal

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SummaryThe precautionary principle (PP) applied to environmental policy stipulates that, in the presence of physical uncertainty, society must take robust preventive action to guard against worst-case outcomes. It follows that the higher the degree of uncertainty, the more aggressive this preventive action should be. This normative maxim is explored in the case of a stylized dynamic model of pollution control under Knightian uncertainty. At time 0 a decision-maker makes a one-time investment in damage-control technology and subsequently decides on a desirable dynamic emissions policy. Adopting the robust control framework of Hansen and Sargent [10], we investigate optimal damage-control and mitigation policies. We show that optimal investment in damage control is always increasing in the degree of uncertainty, thus confirming the conventional PP wisdom. Optimal mitigation decisions, however, need not always comport with the PP and we provide analytical conditions that sway the relationship one way or the other. This result is interesting when contrasted to a model with fixed damage-control technology, in which it can be easily shown that a PP vis-a-vis mitigation unambiguously holds. We conduct a set of numerical experiments to determine the sensitivity of our results to specific functional forms of damage-control cost. We find that when the cost of damage-control technology is low enough, damage-control investment and mitigation may act as substitutes and a PP with respect to the latter can be unambiguously irrational. Keywords AbstractThe precautionary principle (PP) applied to environmental policy stipulates that, in the presence of physical uncertainty, society must take take robust preventive action to guard against worst-case outcomes. It follows that the higher the degree of uncertainty, the more aggressive this preventive action should be. This normative maxim is explored in the case of a stylized dynamic model of pollution control under Knightian uncertainty. At time 0 a decisionmaker makes a one-time investment in damage-control technology and subsequently decides on a desirable dynamic emissions policy. Adopting the robust control framework of Hansen and Sargent [10], we investigate optimal damage-control and mitigation policies. We show that optimal investment in damage control is always increasing in the degree of uncertainty, thus confirming the conventional PP wisdom. Optimal mitigation decisions, however, need not always comport with the PP and we provide analytical conditions that sway the relationship one way or the other. This result is interesting when contrasted to a model with fixed damage-control technology, in which it can be easily shown that a PP vis-a-vis mitigation unambiguously holds. We conduct a set of numerical experiments to determine the sensitivity of our results to specific functional forms of damage-control cost. We find that when the cost of damage-control technology is low enough, damage-control investment and mitigation may act as substitutes and a PP with respect to the ...

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“…The importance of biodiversity management is discussed in several contributions in economic literature (see, e.g.,Rauscher and Barbier, 2010;Vardas and Xepapadeas, 2010).…”

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confidence: 99%

Land use and pollution in a two-sector evolutionary model

Antoci

Borghesi

Iannucci

et al. 2019

Structural Change and Economic Dynamics

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This paper proposes an evolutionary dual model in order to study heterogeneity of agriculture from an environmental perspective. In standard visions, land use changes are driven by productivity differentials across agricultural subsectors. Our model adds other two factors which can indirectly affect land allocation patterns: differences in environmental impact intensity and environmental vulnerability. By including these two dimensions in a parsimonious model, we shed new light on constraints or ability for an economy to reach a sectoral land allocation which efficiently balances environmental burden, environmental constraints and productivity.We find that, in case of trade-off between the three dimensions, farmers' welfare grows along structural changes which allocate increasingly more land to the agricultural subsector with lower pollution intensity regardless its resilience and land productivity performance.

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Model Uncertainty, Ambiguity and the Precautionary Principle: Implications for Biodiversity Management

Cited by 15 publications

References 22 publications

Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

Pollution Control: When, and How, to Be Precautious

Land use and pollution in a two-sector evolutionary model

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