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Economics & Social Sciences Research Program

Gulf of Alaska Trawl Fishery Social Survey: Preliminary Results

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Summer 2014
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The North Pacific Fishery Management Council is considering implementing a new bycatch management program for the Gulf of Alaska groundfish trawl fishery. Any change in how the fishery is managed will likely affect the people and communities participating in the fishery. In anticipation of such changes, the Alaska Fisheries Science Center developed a survey to collect baseline information about the social dimensions of the fishery. Data were collected before program implementation in order to provide a baseline description of the industry as well as to allow for analysis of changes the bycatch management program may bring for individuals and communities once implemented. Having a detailed baseline description will allow for a greater understanding of the social impacts the program may have on the individuals and communities affected by the new management program. When combined with data to be collected in planned post-program implementation follow-up surveys, this information will inform changes in the social characteristics over time and assist in a more comprehensive program evaluation and more informed consideration of potential post-implementation modifications of the program, if needed. Additionally, the survey asked for opinions on a range of elements that may or may not be included in the final bycatch management program to assess different participant’s preferences for various management options, which may change over time as well.

Data were collected using a multiple methods approach in order to obtain the highest response rates possible and to make the survey available to a wide variety of respondent types. Fieldwork was completed in Kodiak, Sand Point, King Cove, Seattle, and Petersburg in an attempt to maximize the use of in-person survey administration, given budget constraints. The survey was conducted with participants in the Gulf of Alaska groundfish trawl fishery, including vessel owners, vessel operators, groundfish vessel crew, catcher/processor owners, catcher/processor crew, shoreside and inshore floating processors, and tender owners and operators. The study also included other individuals who are stakeholders in the trawl fishery including any businesses that are directly tied to the groundfish trawl industry through the supply of commercial items, including but not limited to gear suppliers, fuel suppliers, and equipment suppliers. The results of the survey highlight the differences in the people, sectors, and communities engaged in the fishery. Data from the survey demonstrate how different individuals and sectors depend on the Gulf of Alaska groundfish trawl fishery to sustain their businesses and families and how they may be interconnected with one another. We will be presenting preliminary results of the 2014 survey at the October North Pacific Fishery Management Council (NPFMC) meeting. The full preliminary analysis report can be found on the NPFMC’s October 2014 agenda, item C-7.

By Amber Himes-Cornell and Stephen Kasperski

A Unified Framework to Estimate Fish and Crab Prices

The Economic and Social Sciences Research (ESSR) program is developing new methods to estimate fish and crab prices. Primary economic data for Alaska fisheries consists of revenues and quantities from a census dataset (e.g., fish tickets). These data are used for a variety of purposes including the calculation of “standard” ex-vessel prices to assess observer fees. The standard method is non-statistical; it simply adds up revenues and quantities and uses the ratio of these totals to define the standard price. We extended the standard method to calculate statistics such as the standard ratio-of-means (RoM), mean-of-ratios (MoR), and ordinary least-squares (OLS) estimates of the price. All three are quantity-weighted averages but there are non-trivial differences in the prices calculated depending on the procedure. For example, the RoM and MoR are not equal except if complete symmetry prevails and all production units are equal, which is not realistic. When the dataset is a census of the population, what does the application of these ratio-based calculations (and others) imply about the relationship between aggregate value and quantity?  These and other estimators can be compared within the context of a statistical framework by hypothesizing a super-population. An advantage of a statistical framework is that we can determine the statistical properties of price estimates. For example, if the assumptions for OLS regression are satisfied then the coefficient on quantity is an unbiased estimate of the marginal change in revenues with respect to quantity, i.e., the price. In addition, a statistical framework gives us tools to evaluate uncertainty in price estimates. In this case, the notion that the actual price paid in the market is random with a distribution is more consistent with Bayesian framework, in contrast to classical regression where quantity is related to value through a constant but unknown price. We are currently developing methods of Bayesian price estimation.

By Mike Dalton and Ben Fissel

 

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