Fisheries Economics of the United States — Methods

The following information provides additional details on the technical methods employed in the creation of the Fisheries Economics of the United States report series. For more information on the FEUS 2022 methods, please see contact information by topic:

• Commercial fisheries statistics: Ben Fissel (ben.fissel@noaa.gov).
• Recreational fisheries statistics: Sabrina Lovell (sabrina.lovell@noaa.gov).
• Other sections:  Ben Fissel (ben.fissel@noaa.gov) will direct you to the appropriate author.

FEUS 2022 Methods

Commercial Fisheries

Economic Impacts

The premise behind economic impact modeling is that every dollar spent in a regional economy (direct impact) is either saved or re-spent on additional goods or services. If those dollars are re-spent on other goods and services in the regional economy, this spending generates additional economic activity in the region.

Four different measures are commonly used to show how commercial fisheries landings affect the economy in a region (state or nationwide): sales, income, value-added, and employment. The first three measures are calculated in terms of dollars, whereas employment impacts are measured in numbers of jobs. Note that sales, income, value-added impacts are not additive as they represent distinct measures of economic activity. The term sales refers to the gross value of all sales by regional businesses affected by an activity, such as commercial fishing. The category includes both the direct sales of fish landed and sales made between businesses and households resulting from the original sale. Income includes personal income (wages and salaries) and proprietors' income (income from self-employment). Value-added is the contribution made to the gross domestic product in a region. Employment is specified on the basis of full-time and part-time jobs supported directly or indirectly by the sales of seafood or purchases of inputs to commercial fishing. The United States seafood industry is defined here as the commercial fishing sector, seafood processors and dealers, seafood wholesalers and distributors, importers, and seafood retailers.

Economic impacts are calculated using the NMFS Commercial Fishing & Seafood Industry Input / Output Model (CFSI I/O Model). This model uses IMPLAN (IMpact analysis for PLANning), a software package for conducting the input-output analyses. The scope of the model includes the activities of commercial fishermen (i.e., harvesters), processors, wholesalers/distributors, retail grocers, and restaurants. The model estimates impacts of the seafood industry and retail outlets based solely on the value that each segment adds to the fish and seafood products that it purchases to estimate economic impacts. By only valuing each segment, product impacts that were created from upstream segments of the seafood industry or by harvesters are not double counted.

The model disaggregates the impacts into 20 species (e.g., halibut) or species groups (e.g., west coast groundfish) for which different multipliers are calculated for harvesters and each seafood industry activity. These “multipliers'' are used to estimate the economic impacts associated with each initial dollar of direct spending. After running the model in IMPLAN in 2016, the multipliers were exported into R (version 4.0.4). In R, commercial data are aggregated into the same 20 species or species groups used in IMPLAN. Commercial revenue data for each species or group is then broken up by harvesters or seafood industry activity and each multiplier is applied to calculate the direct, indirect, induced, and total impacts for sales, income, value-added, and employment impacts.

This report provides estimates of total economic impacts for the nation and for each of the 23 coastal states. Total economic impacts for each state and the nation represent the sum of direct impacts; indirect impacts (in this case, the impact from suppliers to the seafood industry); and induced impacts (spending by employees on personal and household expenditures, where employees of both the seafood industry and its full supply chain are included). That is, the total economic impact estimates reported here measure jobs, sales, value-added, and income impacts from the seafood industry as well as the economic activity generated throughout each region's broader economy from this industry.

Notes

• “National Accounts: National Accounts Deflators: Gross Domestic Product: GDP Deflator for United States.” Federal Reserve Bank of St. Louis.

Recreational Fisheries

Economic Impacts

The economic contributions for both trip and durable expenditures from recreational fishing in 2022 were estimated using IMPLAN version 7, with base year data from 2022. Models for each state and for the nation were created in IMPLAN using trip expenditures (based on 2022 NMFS  survey data on average trip expenditures and total 2022 angler trips). For durable expenditures, estimates were based on 2019 NMFS survey data on average U.S. level durable expenditures and an estimate of the number of 2022 U.S. saltwater recreational fishing participants obtained from the U.S. Fish and Wildlife Service (12,700,000 anglers, a notable increase from previous 2018 estimates that were used from 2018-2021 due to lack of updated data during those years).

The economic contribution of recreational fishing activities is based on spending by recreational anglers.  Total annual trip expenditures are estimated at the state level by multiplying mean trip expenditures by the estimated number of adult trips in each trip mode (for-hire, private boat, and shore). After 2018, state level durable expenditures and durable impacts are  no longer available due to changes in the availability of angler participation data at the state level.

Four different measures are commonly used to show how angler expenditures affect the economy in a region (state or nationwide): sales, income, value-added, and employment. The term sales refers to the gross value of all sales by regional businesses affected by an activity, such as recreational fishing. The category includes both the direct sales made by the angler and sales made between businesses and households resulting from that original sale by the angler. Income includes personal income (wages and salaries) and proprietors' income (income from self-employment). Value-added is the contribution made to the gross domestic product in a region. Employment is specified on the basis of full-time and part-time jobs supported directly or indirectly by the purchases made by anglers. The first three measures are calculated in terms of dollars, whereas employment impacts are measured in number of jobs. Note that these categories are not additive. NOAA Fisheries uses a regional impact modeling software, called IMPLAN, to estimate these four types of impacts.

Caveats

Due to changes in data availability after 2018, angler participation data is not being reported at the state level for years after 2018. 

Pacific Data

Prior to 2022, effort and catch estimates for California, Oregon, and Washington were supplied to NMFS directly from staff at RecFin (Oregon and Washington) and California Department of Fish and Wildlife. Included were California effort and catch estimates for salmon and highly migratory species (HMS) that are not generally included in the regular RecFin databases. For Oregon and Washington, estimates for sampling gaps (e.g., estuary, shore) were based on historical estimates with adjustments. After 2021, data comes directly from databases maintained by the Recreational Fisheries Information Network (RecFIN) and does not include CA salmon or HMS estimates or estimates of shore and estuary effort and catch for Oregon and Washington.

Expenditures

Angler trip expenditure data was collected as part of the National Marine Recreational Fishing Expenditure Survey, a nationwide survey of marine recreational anglers in 2022 in all coastal states. The survey was conducted using in-person interviews in some states, and a mixed web/mail mode in other states. The target population for the 2022 NES was marine recreational anglers, 16 years of age and older, who fished in coastal states during 2022. As there is no consistent national sample frame of marine anglers across all coastal states, different sampling strategies had to be employed to identify potential marine anglers in the different states. Three different methods of identifying and contacting anglers were used.

From Maine to Mississippi, expenditure questions were added onto the Access Point Angler Intercept Survey (APAIS) conducted by NOAA Fisheries,which is an ongoing intercept creel survey that is conducted by both NMFS and its state partners.  In Alaska, California, Louisiana, Oregon, Texas and Washington, state fishing license frames were utilized to contact anglers via a mail and/or online survey depending on the availability of angler email addresses in the license frames. In Hawaii, there is no state saltwater fishing license that can be used to identify anglers, instead the state recreational boating license frame was used.

All anglers were asked to estimate their expenditures for their most recent fishing trip . These included costs for auto fuel, auto rental, public transportation (airfare, bus, taxi, subway, ferry), lodging, food (from grocery stores and from restaurants), bait, ice, boat fuel, boat rental, guide fees, tips to crew, fish processing, and gifts or souvenirs. Respondents were also asked to estimate the proportion of their total expenditure that was spent in the state of the fishing trip.  Using the survey data, average trip expenditures were estimated for each coastal state.  Expenditures were estimated  by mode of fishing (for-hire, private boat, and shore) at the state level.

Notes

Inflation adjustments for 2019 durable expenditure data was calculated in IMPLAN using specific industry deflators provided by IMPLAN.

Spotlight Topic — Processed Products

U.S. seafood processed products data are collected annually from seafood processors via a national survey that focuses on the domestic seafood processing industry. This survey provides information on quantity and value for processed seafood products, as well as employment data for processors. Because the survey is voluntary, the NOAA Seafood Inspection Program also includes estimated data from companies that have not reported but are included in the inspection program. Imputation is used to estimate data from the remaining missing companies. Data from Alaskan processors are collected by Alaska Department of Fish and Game and provided by Alaska Fisheries Information Network.

One-hundred different product forms were aggregated into 15 categories. Categories were designed to aggregate species-specific product forms into broad groups (e.g., fillets, shucked meat, breaded, to name a few) for data analysis. Several data checks were performed prior to analyses to ensure the validity of the voluntary survey data. Because processors located in states in the North Pacific and New England regions are required to participate in the survey for state permitting, data from those regions were assumed to be 100% accurate and were used to validate data from other states not in those regions. Number of unique product forms, number of unique species, and species overlap within and across regions were compared between validated and other states. Employment data from all states were also compared to Quarterly Census for Employment and Wages (QCEW) data using the NAICS code 3117 (i.e., “seafood product preparation and packaging”). Visual aids and descriptive analyses were used to confirm accurate data from states not required to participate in the survey and were thus included in this report.

Nine key U.S. species were selected to evaluate differences between ex-vessel price (landings revenue / landings; dollars per pound) and processed product price (product revenue / product weight; dollars per pound). A linear mixed model was used to explore correlations between average ex-vessel price and average processed product price from 1992 to 2022. Ex-vessel price was the dependent variable for this model and product price was the independent variable with species (e.g., Halibut) or species group (e.g., Pacific salmon) included as a random factor. Species or species group was included as a random factor to account for the natural variability in price within a species or species group.

Spotlight Topic — Direct Seafood Marketing

To identify individuals or businesses engaged in direct seafood marketing, a short postcard survey was first sent to 39,511 active commercial seafood harvesters (almost all seafood harvesters, state and federal combined, in the United States) out of about 56,149 commercial harvesters with 2019 permits nationwide. Of those surveyed, 3,633 self-identified as engaged in direct seafood marketing. These figures were combined with all 2019 harvesters holding direct seafood marketing permits. This process identified 6,625 known individuals or businesses engaging in direct seafood marketing across the United States in 2019. Of those harvesters engaged in direct seafood marketing, 19% are federal fishing permit holders, 79% are state permit holders, and 2% have both federal and state permits.

A second and more detailed survey was then sent to these 6,625 individuals or businesses to further characterize this population. With an 18% response rate, 604 valid survey responses were collected. This is the first collation of this type of information. Survey results detail the five most common direct seafood marketing channels used nationally and regionally and the percentage of respondents engaged in each. “Direct to Consumer” was identified as the most cited pathway, with “Direct to Institutions” being the least. Survey results also provide employment characteristics of the respondents in the direct seafood sector, including the number of employees, their full or part time status and gender breakdown. More than 60% of the reported direct seafood workforce were full-time employees, with the rest being part-time or unpaid labor. Eighteen percent of the reported direct seafood workforce were female, with the majority working part-time. Florida and Washington state had the largest direct seafood workforce among the U.S. states.

Direct seafood marketing channel descriptions are based on focus groups carried out prior to 2023 survey implementation. Direct seafood marketing can be broadly classified into five types of marketing channels which are briefly described with examples in the FEUS 2022 report.

Additional details will be found in upcoming publications which will be linked here.