Yakov Ben-Haim, 2010, Info-Gap Economics: An Operational Introduction, Palgrave-MacMillan.
Chapter 5: Topics in Public Policy
5.1 Emissions Compliance
5.2 Enforcing Pollution Limits
5.3 Climate Change
Ali Ranjbar and Najmeh Mahjouri, 2019, Multi-objective freshwater management in coastal aquifers under uncertainty in hydraulic parameters, Natural Resources Research, DOI: 10.1007/s11053-019-09585-3. Abstract.
Annika Carlsson Kanyama, Per Wikman-Svahn and Karin Mossberg Sonnek, 2019, “We want to know where the line is”: comparing current planning for future sea-level rise with three core principles of robust decision support approaches, Journal of Environmental Planning and Management, published online: 31 Jan 2019. Abstract.
Rodrigo A. Estevez, Felipe H. Alamos, Terry Walshe and Stefan Gelcich, 2017, Accounting for uncertainty in value judgements when applying multi-attribute value theory, Environmental Modeling & Assessment, DOI 10.1007/s10666-017-9555-5. Abstract.
Yakov Ben-Haim, Craig D. Osteen and L. Joe Moffitt, 2013, Policy Dilemma of Innovation: An Info-Gap Approach, Ecological Economics, 85: 130-138. Pre-print.Hebrew version.
New ideas or technologies are often advocated because of their purported improvements on existing methods. However, what is new is usually less well-known and less widely tested than what is old. New methods may entail greater unknown dangers as well as greater potential advantages. The policy maker who must choose between innovation and convention faces a dilemma of innovation. We present a methodology, based on info-gap robustness, to deal with the innovation dilemma. We illustrate the approach by examining the policy decisions for managing the Light Brown Apple Moth in California.
Innovation, policy selection, robustness to uncertainty, info-gaps, Light Brown Apple Moth.
Hiroyuki Yokomizo, Wataru Naito, Yoshinari Tanaka and Masashi Kamo, 2013, Setting the most robust effluent level under severe uncertainty: Application of information-gap decision theory to chemical management,Chemosphere, vol. 93, #10, pp.2224-2229.
Decisions in ecological risk management for chemical substances must be made based on incomplete information due to uncertainties. To protect the ecosystems from the adverse effect of chemicals, a precautionary approach is often taken. The precautionary approach, which is based on conservative assumptions about the risks of chemical substances, can be applied selecting management models and data. This approach can lead to an adequate margin of safety for ecosystems by reducing exposure to harmful substances, either by reducing the use of target chemicals or putting in place strict water quality criteria. However, the reduction of chemical use or effluent concentrations typically entails a financial burden. The cost effectiveness of the precautionary approach may be small. Hence, we need to develop a formulaic methodology in chemical risk management that can sufficiently protect ecosystems in a cost-effective way, even when we do not have sufficient information for chemical management. Information-gap decision theory can provide the formulaic methodology. Information-gap decision theory determines which action is the most robust to uncertainty by guaranteeing an acceptable outcome under the largest degree of uncertainty without requiring information about the extent of parameter uncertainty at the outset. In this paper, we illustrate the application of information-gap decision theory to derive a framework for setting effluent limits of pollutants for point sources under uncertainty. Our application incorporates a cost for reduction in pollutant emission and a cost to wildlife species affected by the pollutant. Our framework enables us to settle upon actions to deal with severe uncertainty in ecological risk management of chemicals.
Chemical management; Cost-effectiveness; Effluent limit; Information-gap decision theory; Robustness; Uncertainty
R.A. Chisholm and B.A Wintle, 2012, Choosing ecosystem service investments that are robust to uncertainty across multiple parameters, Ecological Applications, 22(2): 697-704.
Info-gap decision theory facilitates decision making for problems in which uncertainty is large and probability distributions of uncertain variables are unknown. The info-gap framework allows the decision maker to maximize robustness to failure in the presence of uncertainty, where uncertainty is in the parameters of the model and failure is defined as the model output falling below some minimally acceptable performance threshold. Info-gap theory has found particular application to problems in conservation biology and ecological economics. In this study, we applied info-gap theory to an ecosystem services tradeoff case study in which a decision maker aiming to maximize ecosystem service investment returns must choose between two alternative land uses: native vegetation conservation or the establishment of an exotic timber plantation. The uncertain variables are the carbon price and the water price. With a “no-information” uncertainty model that assumes equal relative uncertainty across both variables, info-gap theory identifies a minimally acceptable reward threshold above which conservation is preferred, but below which plantation establishment is preferred. However, with an uncertainty model that allows the carbon price to be substantially more uncertain than the water price, conservation of native vegetation becomes an economically more robust investment option than establishing alien pine plantations. We explored the sensitivity of the results to the use of alternative uncertainty models, including asymmetric uncertainty in individual variables. We emphasize the general finding that the results of info-gap analyses can be sensitive to the choice of uncertainty model and that, therefore, future applications to ecological problems should be careful to incorporate all available qualitative and quantitative information relating to uncertainties or should at least justify the no-information uncertainty model.
Asymmetric uncertainty; Carbon price; Fynbos conservation; Info-gap decision theory; Jonkershoek Valley, South Africa
John K. Stranlund and Yakov Ben-Haim, 2008, Price-based vs. quantity-based environmental regulation under Knightian uncertainty: An info-gap robust satisficing perspective, Journal of Environmental Management, 87: 443-449. pdf preprint.
Jason K. Levy, Keith W. Hipel and D. Marc Kilgour, 2000, Using environmental indicators to quantify the robustness of policy alternatives to uncertainty, Ecological Modelling, Volume 130, Issues 1-3, 1 June 2000, Pages 79-86.