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Friday, May 24, 2019

Modelling and Management

Session Chair: Minling Pan, NMFS Pacific Islands Fisheries Science Center;

10:00 – 10:18  |  3567727

Landing with the crowd

Andreea L. Cojocaru1; Frank Asche2;
1Center for Innovation Research, University of Stavanger Business School, Stavanger, Norway; 2Institute for Sustainable Food Systems and School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA;

There is a growing body of literature that focuses on fishing behavior and choice of fishing location. However, this is only part of what a fishing trip entails. Limited attention has been given to fishers behavior once the fish have been brought onboard. This is particularly important when fishers can choose between landing locations that differ in characteristics, such as number and type of buyers, in combination with distance to and from fishing location. Given the emphasis on coastal communities for policy-makers in many fisheries management systems, it is consequential to investigate the presence of agglomeration effects, and if these intensify over time. In the current study, we use a rich dataset of fishing locations, catches, and transactions at all landing ports in Norway over 15 years, enriched with spatial information such as accessibility by rail-roads, driving roads, air connectivity and proximity to large cities. Our empirical study measures effects from a variety of factors in the context of the random utility multi-site model proposed by Timmins and Murdock (2007). This approach allows us to control for endogeneity by separating the alternative landing sites into the exogenous attribute space, and to therefore accurately value landing locations.

10:18 – 10:36  |  3573630

Bargaining power, competition, and location choice in the resource harvesting sector

Keita Abe1; Linda Nøstbakken1;
1Norwegian School of Economics, Bergen, Norway;

We investigate bargaining power in the resource harvesting seller-buyer relationship. Specifically, in the fisheries sector, previous studies find that the individual transferable quotas (ITQ) management system gives harvesters more bargaining power and resource rent. Such bargaining power is conditional on heterogeneous characteristics, such as vessel range (size, speed), landing quantity and harvesting technology. Each buyers bargaining power is also conditional on characteristics such as geographic location, number of competing buyers, and processing technology. We empirically investigate what yields bargaining power on both sides of the seller-buyer relationship, and evaluate to which extent the management policy affects the relationship and thus the landings pattern. Results indicate that the harvesters choice of both landing site and prices are affected by vessel size and distance from thefishing location to shore (range), suggesting that large vessels tend to have more bargaining power than smaller vessels.

10:36 – 10:54  |  3574309

Running to stand still? Common property induced inertia in the spatial commons

Yutaro Sakai1; Joshua Abbott2;
1Graduate School of Agricultural and Life Sciences, the University of Tokyo, Tempe, United States; 2Arizona State University, Tempe, AZ, United States;

The metaphor of the race to fish is powerful, effectively conveying the overinvestments in fixed and variable harvesting inputs in fisheries for which seasonal harvesting rights are insecure. We contribute an additional insight to understanding the linkage between management institutions and harvester behavior by proposing and empirically validating a new effect of common-pool management that contrasts with the usual race to fish metaphor. We propose that fishers in a common-pool fishery may be less mobile than in a system with secure catch rights.

We build a stylized game-theoretic model to demonstrate how competition for fish under a common-pool quota increases the opportunity cost of time for individual fishers relative to under an individualized quota system. This wedge distorts fishers time allocation on the grounds by skewing the relative prices of harvest and non-harvest (i.e. time spent in moving between grounds) time. If the marginal cost of time spent in harvest activities is greater than that of non-harvest activities, then insecure property rights to catch induce fishermen to delay the decision to move to new grounds. Paradoxically, the race to fish manifests itself in an intense, yet relatively stationary, fishery. The implications of this perverse incentive may include reductions in the average productivity of fishing, reduced incentives to engage in prospective searching, or greater localized depletion and habitat damage. This phenomenon may also help explain the large shadow values of distance and significant habit persistence found in fishing location choice models.

We demonstrate the empirical relevance of this effect by analyzing fishing behavior before and after a transition to a catch share in the Eastern Bering Sea mixed species groundfish trawl fishery. Using detailed observer data at the individual trawl level, we demonstrate that the propensity to move to new fishing grounds increased in statistically and economically significant ways after the policy change. We also use quantile regression techniques to demonstrate that the entire distribution of distance of movement experienced an upward shift. These findings validate the predictions of our theoretical model, deepening our knowledge of the connections between management institutions and fisher behavior.

10:54 – 11:12  |  3580772

Development of a simulated fishing fleet in response to environmental and market variability

Andrew Scheld1; Stephane Thanassekos2;
1Virginia Institute of Marine Science, Gloucester Point, Virginia, United States; 2Commission for the Conservation of Antarctic Marine Living Resources, Hobart, Tasmania, Australia;

A representative fishing fleet agent-based model was developed to explore the effects of environmental and market variability on fisher entry, exit, and investment behavior. In the model, heterogeneous individual agents make daily fishing decisions and annual entry, exit, and investment decisions by assessing expectations regarding fishing profits as well as individual opportunity costs and risk preferences. Daily market prices are endogenously determined by an isoelastic market demand curve. The influence of environmental and market variability on industry development and fish stock biomass was evaluated during ten-year simulations of industry dynamics. Environmental variability was explored by adjusting variability in fishing success while market variability was evaluated through adjustments to the price elasticity of demand. Long-term stability in fishing success and market prices tended to produce large, small-scale and moderately profitable fleets who had minimal impacts on the resource. Highly variable fishing success, meanwhile, produced small fleets of larger, heterogenous, and less profitable vessels who removed greater amounts of biomass. Changes in demand elasticity were found to influence fleet profitability but not size, capacity, or stock biomass, though responses were dependent on the level of environmental variability. Across simulations, fleet responses to shifts in variability were frequently non-linear and characterized by thresholds. Results from this research are useful in understanding the organization and structure of commercial fishing industries and may be informative when considering strategies to reduce community exposure to environmental or market risk.


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