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A study using the real option theory, examines the price of crude oil for which the investment in field development and the loss of an amenity dividend, with respect to the drilling for oil in the Arctic National Wildlife Refuge (ANWR), is presented.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.reseneeco.2005.01.001 Byline: Jon M. Conrad, Koji Kotani Keywords: Resource development; Real option theory; ANWR Abstract: The social net benefit of drilling for oil in the Arctic National Wildlife Refuge (ANWR) has been a contentious policy issue since 1998. This paper applies real option theory to the issue and asks 'What price for crude oil would justify the investment in field development and the loss of an amenity (wilderness) dividend?' Trigger prices are identified for two stochastic processes; when crude oil prices evolve according to geometric Brownian motion (GBM) and when crude oil prices are mean-reverting (M-R). Author Affiliation: Department of Applied Economics and Management, 455, Warren Hall, Cornell University, Ithaca, NY, 14853, USA Article History: Received 31 March 2004; Revised 25 August 2004; Accepted 12 January 2005

The use of option-pricing in decisions concerning wilderness preservation, resource extraction, and development is discussed.

The commercial history and current economics of the northern anchovy fishery is modeled using an open-access framework. The proposed model involves a production function for the wetfish fleet and a net growth function for the anchovy stock, both of which are derived from US data. The model supports the existence of limit cycles and a long-term equilibrium. Extension with Mexican fisheries data allows the estimation of costs for both fleets. The results indicate that unless anchovy prcies increase, fishing costs decrease or vessel productivity rises materially, neither fleet is commercially viable.

Spotted wing drosophila (SWD) is an invasive pest with devastating effects on soft‐skinned fruit crops. Due to its high economic impacts, current SWD management strategies usually focus on preventive calendar‐based insecticide sprays. The industry is calling for adoption of monitoring‐based integrated pest management (IPM) strategies to reduce unnecessary insecticide applications. However, because traps are costly and do not provide perfect observations of the population size, most growers do not monitor. We develop a Bayesian state‐space bioeconomic framework to inform the optimal SWD management strategy when observational uncertainty exists. We use Bayesian inference via the Markov Chain Monte Carlo method to generate the posterior distribution of population model parameters, which we then use to simulate the economic performance of alternative SWD management strategies. We find that one of the monitoring‐based IPM strategies has a slightly lower total cost than the calendar‐based spray strategy. We also find evidence of misalignments between public and private incentives in the adoption of IPM strategies. Profit‐maximizing growers who ignore the negative externalities of insecticide spray have little incentive to adopt the IPM strategies. However, for environmentally conscious growers who take into account the external costs of insecticide sprays, IPM strategies are superior to calendar‐based spray strategy. Our results indicate that IPM strategies become more appealing to both types of growers as the trapping efficiency improves. Extension efforts, support for research to improve trapping efficiency, and monetary incentives can be used to encourage grower adoption of monitoring‐based IPM strategies to control SWD infestation. [ABSTRACT FROM AUTHOR]