Measuring Harvesting Productivity of Pollock Catcher-Processors
Traditional productivity measures have been much less prevalent in the fisheries economics literature than other measures of economic and biological performance. It has been increasingly recognized, however, that modeling and measuring fisheries' production relationships is central to understanding and ultimately correcting the repercussions of environmental impacts on fisheries and poorly designed regulations.
In this study, authors Ron Felthoven from the Economics & Social Sciences Research (ESSR) Program, and Catherine Morrison Paul and Marcelo Torres from the University of California, Davis, use a transformation function production model to estimate productivity and its components for catcher-processors operating in the Bering Sea and Aleutian Islands pollock fishery, before and after the introduction of the American Fisheries Act.
Among other things, the Act introduced a cooperative system that grants exclusive harvesting privileges and allows quota exchange. These aspects of the management system have led to innovations in fishing and targeting strategies not viable under the former Olympic-style fishery.
The model of the catcher-processors developed for this study recognizes the roles of externalities from pollock harvesting by incorporating data on climate, bycatch, and fish biomass. The results suggest that harvesting productivity has been increasing over time, that many productive contributions and interactions of climate, bycatch, and fishing strategies are statistically significant, and that regulatory changes have had both direct and indirect impacts on catch patterns and productivity.
A paper on the subject titled "Measuring Productivity Change and its Components for Fisheries: The Case of the Alaskan Pollock Fishery, 1994-2002" was published in a recent volume of the journal Natural Resource Modeling.
By Ron Felthoven
Alaska Fishery CGE Model Completed
To avoid the limitations of fixed-price models, a state-level computable general equilibrium (CGE) model for Alaska fisheries was developed. The model has 18 industries and 17 commodities. Using the model, we investigated the effects of three stylized exogenous shocks—1) a reduction in pollock total allowable catch (TAC), 2) an increase in fuel price, and 3) a reduction in world demand for Alaska seafood—on endogenous variables such as output, employment, value added, commodity prices, and factor prices. Changes in household welfare were also estimated. To model different assumptions on intersectoral and interregional movement of factors of production, we developed two different versions of the CGE model: Keynesian and neoclassical. There are very few CGE studies of fisheries in the literature. Unlike these previous CGE studies of fisheries, this study is unique in that it estimates effects of both supply-side shocks (i.e., change in TAC and change in price of a major productive input, fuel cost) and a demand-side shock (change in the rest of world demand for Alaska seafood). Some of the findings from this study are as follows.
First, this study shows that the CGE model has the capability to address the impact on regional fisheries of various scenarios affecting either the supply-side or demand-side.
Second, impacts estimated in Keynesian CGE variant are generally larger than those from the neoclassical CGE. This is because in the neoclassical CGE all labor released from seafood industries is absorbed into nonseafood industries while in the Keynesian CGE the released labor is not employed in the region.
Third, impacts of higher fuel price are much larger on average in percentage terms for seafood industries than for nonseafood industries because the average share of revenues expended as fuel costs by the seafood industries is higher than the average share of revenue in most non-seafood industries.
Finally, welfare loss is greatest for high income households under all experiments and in both CGE model versions due to their relatively greater participation in factor markets.
The results from this study were summarized in a manuscript which will be submitted to a scientific journal. A logical extension of the approach used in this study is to develop an interregional or multiregional CGE model (MRCGE) for the Alaskan economy and its seafood industries.
Much of the primary and intermediate inputs used in Alaska industries (including seafood harvesting and processing) are imported, especially from the west coast states of Washington and Oregon. Using an MRCGE, it would be possible to trace in much greater detail the effects of shocks such as those considered in this study not only on Alaska, but also on the regional economies that supply goods and services to the Alaska seafood industry.
By Chang Seung and Edward Waters
Amendment 80 Economic Data Report
ESSR Program staff completed preparations for administration of the annual economic data reporting (EDR) requirement in the Amendment 80 groundfish fishery. Data elements collected in the EDR form include cost, revenue, effort, and capacity measurements, and were specified for collection in the Amendment 80 implementing regulations.
Focus groups with Amendment 80 vessel owners were conducted during January and February 2009 to develop definitional and instructional text and revise the EDR form. These revisions will improve the consistency of interpretation by EDR submitters and minimize measurement error due to questionnaire effects.
In collaboration with Pacific States Marine Fisheries Commission (PSMFC), an accounting firm was selected to perform data validation audits. Staff also collaborated with PSMFC and Alaska Fisheries Information Network (AKFIN) personnel to design and implement electronic data entry forms with automated error checking and a relational database design that will be populated directly from electronic files emailed by submitters, largely eliminating manual data entry.
In addition to minimizing data quality errors, these steps will facilitate integration with other fisheries databases (e.g., CFEC e-landings and Commercial Operators Annual Report data) for rapid identification of outliers and other data quality concerns to address in the data validation audit. Insights gained by ESSRP staff through the Bering Sea-Aleutian Islands (BSAI) Crab EDR design, administration, and data quality assessment process were important in improving the Amendment 80 EDR design process, from eliciting more useful input from focus group participants to anticipating data user requirements in database design.
EDR submissions for 2008 calendar year fishing and processing operations are due from permit holders on 1 June 2009.
