Calculating carbon: The value of information in precision for blue carbon restoration projects

Coastal wetland restoration projects can receive payments for ecosystem services but often occur in regions with limited data, and additional data collection can be financially prohibitive. Value of Information analysis can quantify the difference between the expected value of an action before and after new information has been collected, aiming to understand how much data is required to make decisions that balance the costs of implementation versus the benefits of the project. The Australian carbon market provides a method that uses reintroduction of tidal flows to restore coastal wetland ecosystems for their carbon sequestration functions. The method requires a hydrological assessment of prospective sites, which is employed to estimate carbon sequestration potential. This research investigates how different amounts of data collection and different levels of complexity in the hydrological assessment influence the carbon abatement emissions estimated using the method. The results indicate that tidal restoration for blue carbon credits on grazing land may not be financially viable. We found that tidal data collected onsite were important for decision-making while complex hydrological models have low value compared to more simplistic approaches. While investing in data collection provides more value than increasing the complexity of modelling approaches, the value of information was still low. Additionally, restoration of coastal wetlands is unlikely to be financially attractive at current carbon prices, and the land would have to be unsuitable for cattle to become profitable for restoration. This work provides a framework for evaluating the financial benefit of collecting on-site data and using robust methods for estimating inundation, that can be used to guide decision-making to achieve optimal income.

Valuation of Research and Development Projects Using Buying and Selling Prices: Generalized Definitions

This paper develops generalized versions of the concepts of buying price, selling price, and short selling price by employing abelian groups. Such generalized pricing concepts are especially useful for the valuation of research and development (R&D) projects, which are often characterized by unquantifiable uncertainties and nonnumeric inputs and outputs, such as know-how and intellectual property. Moreover, the generalized definitions are also applicable to the valuation of other kinds of features in the decision setting, such as decision opportunities embedded in R&D projects. To motivate the use of these pricing concepts, we show that the general definitions exhibit several consistency properties. The application of the generalized price definitions to the valuation of R&D projects and decision opportunities embedded in such projects is illustrated through an example.