Quota prices in fisheries managed with individual transferable quotas (ITQs) can reveal information about the fishery that can be useful to participants and fishery managers. However, there has been relatively little study of quota markets and no published analysis of market transactions that involve barter (quota for quota) transactions which are frequently observed in multispecies ITQ systems. I propose a modified hedonic method for estimating implicit prices from these transactions and test it with Monte Carlo experiments before applying it to quota market data. The empirical analysis of implicit quota pound values from barter trades in the British Columbia groundfish ITQ supports anecdotal evidence that quota pound values do not rise above ex-vessel values even for “bycatch” species that are constraining catch of other species.

JEL Codes: Q22, D40, L10

We use a contingent valuation approach to estimate the economic value assigned to Iranian households for the preservation of coral reefs at Kish Island. These coral reefs survive in extreme weather conditions and, therefore, are used as a natural laboratory to study impacts of climate change. A one-and-one-half-bound elicitation process was implemented through a face-to-face survey. The vehicle payment is the purchase of a family pass to visit Kish Island. This pass is valid for five years. The collected funds would be used for conservation purposes. Total willingness to pay for five years of services provided by coral reefs at Kish Island is estimated in the range of US$20 to US$155 million, and from US$1.21 to US$9.13 on a per-household basis. This value is interpreted as a non-use value assigned by Iranian visitors and non-visitors of Kish Island.

JEL Codes: Q50, Q51, Q57

Professor Rögnvaldur Hannesson's influence on the development and history of fisheries economics is unquestionable. Also, he has strongly pointed out the potential gains from a more active use of fisheries economics in fisheries management. In light of this, one may ask if fisheries economists have spent too much time on fundamentals in fisheries economics at the expense of the development of applicable models for fisheries managers? Of course, this question is relevant only IF fisheries economics and fisheries economists have a role to play in fisheries management.

JEL Codes: Q22, Q28, C61

The evolution of a fishery is not controlled by the fisheries management system. Neither is it controlled by fisheries management measures selected under that system. These are merely words on paper. The actual control of the fishery is by enforcement of the fisheries management measures selected. In this sense, fisheries enforcement is the real fisheries management. This observation raises the question of the optimal path of fisheries enforcement over time. Given the initial state of the fishery, a time path of fisheries management measures, and a set of enforcement tools and penalty levels, what would be the optimal enforcement effort over time?

This article deals with that issue. Given an efficient fisheries management system, it attempts to characterize the solution to the problem of optimal enforcement of fisheries management measures over time. Not surprisingly, it turns out that the optimal enforcement effort would normally not be constant over time and usually not produce 100% compliance. On the contrary, the optimal level of enforcement and, therefore, compliance is generally a function of the state of the fish stocks at each point in time. More specifically, it appears that optimal enforcement effort may typically be a monotonically declining function of the size of the fish stocks. The article proceeds to investigate optimal paths of other enforcement controls such as penalty levels and allowable catches (announced TACs) and their dependence on the size of the fish stocks.

JEL Codes; K4, K42, Q2, Q22

Economists are interested in the relationship between fishing effort and stock size and their impact on catch levels. The interest lies in stock elasticity, where it is thought that for pelagic fish species it is close to zero; for demersal fish stocks, closer to one. We statistically model and estimate the relationship between stock size and catch for two species, Northeast Arctic cod and saithe. In doing so we are able to recover estimates of stock elasticity but also estimates of catchability coefficients for different age classes and importantly an implicit index of fishing effort. Data on observed catch and a measure of biomass-at-age are available from the International Council for the Exploration of the Sea. The generated stock data are econometrically problematic, and we use an IV estimator with bootstrapping in estimation. Time-series techniques applied to panel data are used to statistically motivate the estimation, which is carried out within a two-way panel framework.

JEL Codes: C72, Q22

JEL Codes: Q2, N5, H7