Effects of the American Fisheries Act on Capacity, Utilization and Technical Efficiency

Felthoven, Ronald G.

doi:10.1086/mre.17.3.42629363

Cited by 79 publications

(49 citation statements)

References 13 publications

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“…However, by the late 1980s (earlier for some fisheries) fishery managers began to limit access to fisheries by putting moratoriums on new licenses. In several cases licenses or vessels were bought back and retired to reduce fishing capacity (40)(41)(42), and in many cases, inactive or part-time fishermen were forced to forfeit licenses or were limited to small amounts of catch or very low productivity gear (e.g., hand reels).…”

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confidence: 99%

Income diversification and risk for fishermen

Kasperski

Holland

2013

Proc. Natl. Acad. Sci. U.S.A.

213

169

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Catches and prices from many fisheries exhibit high interannual variability, leading to variability in the income derived by fishery participants. The economic risk posed by this may be mitigated in some cases if individuals participate in several different fisheries, particularly if revenues from those fisheries are uncorrelated or vary asynchronously. We construct indices of gross income diversification from fisheries at the level of individual vessels and find that the income of the current fleet of vessels on the US West Coast and in Alaska is less diverse than at any point in the past 30 y. We also find a dome-shaped relationship between the variability of individuals' income and income diversification, which implies that a small amount of diversification does not reduce income risk but that higher levels of diversification can substantially reduce the variability of income from fishing. Moving from a single fishery strategy to a 50-25-25 split in revenues reduces the expected coefficient of variation of gross revenues between 24% and 65% for the vessels included in this study. The increasing access restrictions in many marine fisheries through license reductions and moratoriums have the potential to limit fishermen's ability to diversify their income risk across multiple fisheries. Catch share programs often result in consolidation initially and may reduce diversification. However, catch share programs also make it feasible for fishermen to build a portfolio of harvest privileges and potentially reduce their income risk. Therefore, catch share programs create both threats and opportunities for fishermen wishing to maintain diversified fishing strategies.F ishing is a risky business. Not only do fishermen face the highest rate of work-related fatalities of any US industry, with a fatality rate more than 30 times higher than average (1), they face high financial risk as a result of high year-to-year variation in their income (2). In this article we focus on the latter form of risk. High annual variation in income is a problem that is common to a variety of occupations dependent on natural resources, and there has been extensive study of income risk-coping mechanisms, particularly for farmers in developing countries (3-10). Riskreduction strategies used in agriculture might also be effective in fisheries. Crop diversification is a common means of reducing risk in agriculture, taking advantage of asynchronous variation in yield-response and prices to minimize idiosyncratic risk (11-13). Another common strategy in agriculture, particularly in semiarid regions with high fine-scale variation in rainfall, is to farm a number of geographically separated plots to ensure some will be in areas with sufficient rainfall (6). McCloskey (14) argues that risk reduction was the motivation of English farmers for "scattering each man's holdings in dozens of small strips" which, although inefficient, was widely practiced. Farmers can also plant a combination of crops adapted to wet or dry conditions to mitigate the risk assoc...

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confidence: 99%

Income diversification and risk for fishermen

Kasperski

Holland

2013

Proc. Natl. Acad. Sci. U.S.A.

213

169

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“…The magnitude of these differences determines the degree to which a homogeneous estimate of capacity will over/under measure heterogeneous capacity for a given vessel. Figures 1 and 2 illustrate these differences when one assumes a homogeneous versus heterogeneous model and the degree of over/under measure of capacity generated by the homogeneous model assumption, when there exists two distinct production technologies, 10 There are number of issues that must be addressed when defining capacity measures, for a more detailed discussion of these issues see [20]. 11 Alternatively, we could estimate capacity utilization…”

Section: Defining and Estimating Heterogeneous Capacitymentioning

confidence: 99%

“…1 Currently, there are two primary methods used to estimate fishery production technologies: data envelope analysis (DEA) [21,19,30] and stochastic production frontier (SPF) models [31,10,39,15,22]. DEA does not assume a parametric form for the production technology and is therefore a more general and flexible model.…”

Section: Introductionmentioning

confidence: 99%

“…2 The purpose of this paper is not to compare and contrast DEA and SPF models. For a more complete analysis and discussion of these alternative methods see [10] and [20].…”

Section: Introductionmentioning

confidence: 99%

“…Addressing the former concern is readily achieved using ray production functions [10] or distance functions [26]. 3 In our example, the flatfish fishery within the Bering Sea and Aleutian Islands (BSAI), we use distance functions to account for the multi-species nature of this fishery, 4 to control for unobservable variation in the production frontier, and to generate our new measure of fleet capacity.…”

Section: Introductionmentioning

confidence: 99%

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Estimating heterogeneous capacity and capacity utilization in a multi-species fishery

2009

Self Cite

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We use a stochastic production frontier model to investigate the presence of heterogeneous production and its impact on fleet capacity and capacity utilization in a multi-species fishery. Furthermore, we propose a new fleet capacity estimate that incorporates complete information on the stochastic differences between each vessel-specific technical efficiency distribution.Results indicate that ignoring heterogeneity in production technologies within a multi-species fishery, as well as the complete distribution of a vessel's technical efficiency score, may yield erroneous fleet-wide production profiles and estimates of capacity. Furthermore, our new estimate of capacity enables out-of-sample production predictions predicated on either homogeneity or heterogeneity modeling which may be utilized to facilitate policy.

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Identifying technically efficient fishing vessels: a non‐empty, minimal subset approach

Flores‐Lagunes

Horrace

Schnier

2007

J of Applied Econometrics

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There is a growing resource economics literature, concerning the estimation of the technical efficiency of fishing vessels utilizing the stochastic frontier model. In these models, vessel output is regressed on a linear function of vessel inputs and a random composed error. Using parametric assumptions on the regression residual, estimates of vessel technical efficiency are calculated as the mean of a truncated normal distribution and are often reported in a rank statistic as a measure of a captain's skill and used to estimate excess capacity within fisheries. We demonstrate analytically that these measures are potentially flawed, and extend the results of Horrace (2005) to estimate captain skill for thirty nine vessels in the Northeast Atlantic herring fleet, based on homogenous and heterogeneous production functions within the fleet. When homogenous production is assumed, we find inferential inconsistencies between our methods and the methods of ranking the means of the technical inefficiency distributions for each vessel. When production is allowed to be heterogeneous, these inconsistencies are mitigated.

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Effects of the American Fisheries Act on Capacity, Utilization and Technical Efficiency

Cited by 79 publications

References 13 publications

Income diversification and risk for fishermen

Income diversification and risk for fishermen

Estimating heterogeneous capacity and capacity utilization in a multi-species fishery

Identifying technically efficient fishing vessels: a non‐empty, minimal subset approach

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