The Dixit–Pindyck and the Arrow–Fisher–Hanemann–Henry option values are not equivalent: a note on Fisher (2000)

Mensink, Paul; Requate, Till

doi:10.1016/j.reseneeco.2004.04.001

Cited by 31 publications

(4 citation statements)

References 7 publications

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“…Risks of foregone future benefits are managed. Option value encompasses two related forms (Mensink and Requate 2005). Quasi‐option value analysis focuses on the value from learning in delaying a decision, which is incorporated into a benefits function to be maximized (Arrow and Fisher 1974).…”

Section: Survey Of Risk Management Strategies In Use or Applicable Tomentioning

confidence: 99%

Risk management for fisheries

Sethi

2010

Fish and Fisheries

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Risk management methods provide means to address increasing complexity for successful fisheries management by systematically identifying and coping with risk. The objective of this study is to summarize risk management practices in use in fisheries and to present strategies that are not currently used but may be applicable. Available tools originate from a variety of disciplines and are as diverse as the risks they address, including algorithms to aid in making decisions with multiple stakeholders, reserves to buffer against economic or biological surprises, and insurance instruments to help fishermen cope with economic variability. Techniques are organized in a two‐stage framework. In the first stage, risks are identified and analysed. Strategies presented in this category focus on decision analysis, including multicriteria decision‐making tools, and the related concept of risk assessment. Then in the treatment stage, identified risks can be transferred, avoided, or retained using tools such as the Precautionary Approach, portfolio management, financial contracts to manage price risk and horizontal integration. Published fishery applications are reviewed, and some empirical examples of risks and risk management using US fisheries data are presented.

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Section: Survey Of Risk Management Strategies In Use or Applicable Tomentioning

confidence: 99%

Risk management for fisheries

Sethi

2010

Fish and Fisheries

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“…The Dixit‐Pindyck concept of option value is composed of the quasi‐option value developed in the environmental economics literature (Arrow and Fisher , Henry , Hanemann ) and the value of postponing a decision to take advantage of more favorable investment circumstances irrespective of uncertainty (Mensink and Requate , Fisher ).…”

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Climate Forecasts and Flood Mitigation

Sims¹,

Null²

2019

Southern Economic Journal

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There is growing evidence that flood mitigation is often inefficient because individuals misestimate flood risk. The propensity to misestimate flood risk is expected to rise because climate change ensures the past will be a poor predictor of the future. Greater reliance on downscaled climatological and hydrological forecasts has been suggested to address these information failures. This article combines stochastic dynamic programming with historical data and climate‐driven streamflow projections to determine how changes in flood risk forecasts influence optimal investments in flood mitigation infrastructure. Using upgrades in California's levee system as an example, we show that climate change is causing benefit–cost analysis to become increasingly biased in favor of flood mitigation infrastructure projects. We also show that using downscaled hydroclimate forecasts to achieve more accurate estimates of flood risk can decrease the efficiency of flood mitigation infrastructure investments, if flood risk is currently overestimated. JEL Classification: D81 Q25 Q54

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“…6 6 The Dixit–Pindyck concept of option value is composed of the quasi‐option value developed in the environmental economics literature (Arrow and Fisher [1974], Henry [1974], Hanemann [1989]) and the value of postponing a decision to take advantage of more favorable investment circumstances irrespective of uncertainty (Fisher [2000], Mensink and Requate [2005]). …”

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confidence: 99%

Optimal Timing of Salvage Harvest in Response to a Stochastic Infestation

Sims

2011

Natural Resource Modeling

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Following a catastrophic disturbance, forest managers may choose to perform a salvage harvest to recoup timber losses. When the disturbance process evolves stochastically, a unique option value arises associated with the salvage harvest decision. This option value represents the value of postponing a salvage harvest to gain more information about the disturbance process. This paper uses a real options approach to determine how much of a forested area must be infested to trigger a salvage harvest when the forest provides both timber and nontimber values. Analytical results indicate slower rates of forest recovery will optimally delay a salvage harvest while forested areas with large timber values and where nontimber values are more sensitive to the presence of dead and dying trees should be harvested more immediately. The model is applied to a mountain pine beetle outbreak in Idaho's Sawtooth National Forest using readily available aerial detection survey data.

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The Dixit–Pindyck and the Arrow–Fisher–Hanemann–Henry option values are not equivalent: a note on Fisher (2000)

Cited by 31 publications

References 7 publications

Risk management for fisheries

Risk management for fisheries

Climate Forecasts and Flood Mitigation

Optimal Timing of Salvage Harvest in Response to a Stochastic Infestation

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