NOAA Technical Memorandum NMFS-NWFSC-111 

Description of the Input-Output 

Model for Pacific Coast Fisheries 

June 2011 

U.S. DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration

National Marine Fisheries Service 
NOAA Technical Memorandum 

NMFS-NWFSC Series

The Northwest Fisheries Science Center of the National 

Marine Fisheries Service, NOAA, uses the NOAA Technical 

Memorandum NMFS-NWFSC series to issue scientific and 

technical publications. Manuscripts have been peer reviewed 

and edited. Documents published in this series may be cited 

in the scientific and technical literature. 

The NMFS-NWFSC Technical Memorandum series of the 

Northwest Fisheries Science Center continues the NMFSF/NWC series established in 1970 by the Northwest & Alaska 

Fisheries Science Center, which has since been split into the 

Northwest Fisheries Science Center and the Alaska Fisheries 

Science Center. The NMFS-AFSC Technical Memorandum 

series is now used by the Alaska Fisheries Science Center. 

Reference throughout this document to trade names does not 

imply endorsement by the National Marine Fisheries Service, 

NOAA. 

This document should be referenced as follows:

Leonard, J., and P. Watson. 2011. Description of the 

input-output model for Pacific Coast fisheries. U.S. Dept. 

Commer., NOAA Tech. Memo. NMFS-NWFSC-111, 64 p. 
NOAA Technical Memorandum NMFS-NWFSC-111 

Description of the Input-Output 

Model for Pacific Coast Fisheries 

Jerry Leonard and Phillip Watson* 

Northwest Fisheries Science Center 

Fishery Resource Analysis and Monitoring Division 

2725 Montlake Boulevard East 

Seattle, Washington 98112 

*University of Idaho 

Department of Agricultural Economics and Rural Sociology 

Moscow, Idaho 83844 

June 2011 

U.S. DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration

National Marine Fisheries Service
Most NOAA Technical Memorandums 

NMFS-NWFSC are available online at the 

Northwest Fisheries Science Center 

Web site (http://www.nwfsc.noaa.gov) 

Copies are also available from: 

National Technical Information Service 

5285 Port Royal Road 

Springfield, VA 22161 

phone orders (1-800-553-6847) 

e-mail orders (orders@ntis.fedworld.gov)

ii 
Table of Contents 

List of Figures...............................................................................................................................................v 

List of Tables ..............................................................................................................................................vii 

Executive Summary .....................................................................................................................................ix 

Acknowledgments........................................................................................................................................xi 

Abbreviations and Acronyms ....................................................................................................................xiii 

1. Introduction..............................................................................................................................................1 

2. Elements of IO Analysis..........................................................................................................................3 

2.1. IO Fundamentals...............................................................................................................................3 

2.2. IO Model Assumptions.....................................................................................................................5 

2.3. Study Area Considerations...............................................................................................................6 

2.4. Trade Flow Considerations...............................................................................................................6 

2.5. IO Models in a Fishery Context........................................................................................................6 

2.6. IMPLAN...........................................................................................................................................7 

3. Data..........................................................................................................................................................8 

3.1. IMPLAN Data ..................................................................................................................................8 

3.2. PacFIN Data .....................................................................................................................................9 

3.3. NWFSC Cost Earnings Survey Data ..............................................................................................10 

3.4. Landings Taxes and Moorage Rates...............................................................................................12 

4. The IO-PAC Model................................................................................................................................16 

4.1. Industry Additions..........................................................................................................................17 

4.2. Commodity Additions ....................................................................................................................18 

4.3. Study Area ......................................................................................................................................24 

4.4. Product Flow...................................................................................................................................31 

4.5. Vessel Production Functions..........................................................................................................32 

4.6. Processor and Wholesale Seafood Dealer Production Functions...................................................35 

4.7. Sales................................................................................................................................................37 

4.8. Employment....................................................................................................................................38 

5. Model Construction ...............................................................................................................................39 

5.1. Model Construction Steps ..............................................................................................................39 

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5.2. IMPLAN Table Adjustments..........................................................................................................41 

6. Impact Estimation ..................................................................................................................................44 

6.1. Estimation Procedure......................................................................................................................44 

6.2. Hypothetical Examples...................................................................................................................45 

7. Discussion..............................................................................................................................................52 

References...................................................................................................................................................55 

Appendix A: Bridge between Expenditures and IMPLAN Sectors............................................................57 

Harvester Expenditures...........................................................................................................................57 

Seafood Wholesale Dealer and Processor Expenditures ........................................................................62 

iv
List of Figures 

Figure 1. West Coast, state, and port study areas in IO-PAC......................................................................2 

Figure 2. IO-PAC product flows................................................................................................................33 

v
vi
List of Tables 

Table 1. Vessel sectors used in the IO-PAC..............................................................................................11 

Table 2. Moorage rates, 2009.....................................................................................................................13 

Table 3. Taxes on commercial fishing vessel landings..............................................................................14 

Table 4. Industry categories and associated IMPLAN codes ....................................................................18 

Table 5. Commodities added to IMPLAN and associated codes...............................................................19 

Table 6. Gear groupings and associated PacFIN variables........................................................................19 

Table 7. IO-PAC commodity groupings....................................................................................................20 

Table 8. Landings by vessel type and commodity code, 2006 value.........................................................25 

Table 9. IO-PAC port groups and names...................................................................................................29 

Table 10. Washington Enhanced Food Fish Tax by NAICS, calendar year 2006.....................................32 

Table 11. Percentage distribution of commercial fishing production functions........................................36 

Table 12. Seafood wholesale dealer production function ..........................................................................37 

Table 13. IMPLAN tables..........................................................................................................................40 

Table 14. Impact of reduced harvest among sablefish fixed gear vessels..................................................46 

Table 15. Impact of reduced sablefish harvest using fixed gear................................................................49 

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Executive Summary 

The input-output model for Pacific Coast Fisheries (IO-PAC) is designed to estimate the 

gross changes in economic contributions and economic impacts resulting from policy, 

environmental, or other changes that affect fishery harvest. IO-PAC was constructed by 

customizing Impact Analysis for Planning (IMPLAN) regional input-output software. The 

methodology employed in this model is similar to that used in the Northeast Region Commercial 

Fishing Input-output Model. IO-PAC is designed to estimate the economic effects of changes in 

fishing harvest for various types of vessels and fish species over multiple geographic areas along 

the Pacific Coast. Economic impact estimates in IO-PAC include the effects of changes in fish 

harvest to harvesting vessels, seafood wholesalers, and processors, and they can be exhibited as a 

change in total economic output, income, or employment. 

Data used to develop the fishing sectors were obtained from Pacific Fisheries Information 

Network (PacFIN) fish ticket data maintained by the Pacific States Marine Fisheries 

Commission, the Northwest Fisheries Science Center’s (NWFSC) cost earnings surveys, 

moorage rates from 19 ports along the West Coast, and collection statistics for the Washington 

Enhanced Food Fish Tax. PacFIN data include fish ticket and vessel registration information 

that are supplied by the California Department of Fish and Game, Oregon Department of Fish 

and Wildlife, and Washington Department of Fish and Wildlife. The 2006 PacFIN fish ticket 

data, when aggregated into vessel classifications and commodity types, comprise the sales 

estimates that are included in the model. Default IMPLAN 2006 data are used in IO-PAC for the 

regional nonfishing economy such as the agricultural, manufacturing, trade, and service sectors, 

as well as the various institutions in the region such as households and governments. NWFSC 

cost earnings surveys provide the majority of data necessary to construct the production 

functions in IO-PAC. Data on Washington Enhanced Food Fish Tax collections in 2006 are used 

to estimate the flow of fish landings. 

IO-PAC covers the commercial groundfish, salmon, crab, highly migratory species, 

coastal pelagic species, lobster, and shrimp fisheries on the West Coast. Commercial fishing 

vessel categories are classified by type using the 19 sector scheme. These 19 vessel categories 

are added as industry sectors into IMPLAN and they produce 32 unique species and gear 

commodity outputs. Because the 19 vessel industry sectors produce a variety of species and gear 

commodities, economic impact estimates can be made on both an industry and commodity basis. 

The IO-PAC approach to study area for impact estimation is to use a collection of regionspecific models. There are models for the entire West Coast and the states of Washington, 

Oregon, and California. Additionally, there are models for port areas that correspond to the port 

groups analyzed in the 2005–2006 Pacific Coast groundfish environmental impact statement. 

The IO-PAC approach of region-specific models is intended to be flexible enough to provide 

impact estimates for a wide variety of policy situations and analysis goals. It can provide coastwide, statewide, and port-area impacts. 

ix
x

Information on product flow from IMPLAN and data on Washington Enhanced Food 

Fish Tax collections in 2006 were used to broaden the economic effects beyond the harvesting 

vessels and include seafood wholesalers and processors. IMPLAN provides estimates of the 

flow of fish from harvesters to processors in all IO-PAC study areas. The amount of fish that 

flows to wholesalers was assumed to be a fixed percent of landings in all study areas and is based 

on Washington Enhanced Food Fish Tax collections data supplied by the Washington 

Department of Revenue. 

Production functions for the harvesting sectors included in the model were constructed 

primarily through the use of NWFSC cost earnings surveys data. The surveys were conducted 

for the limited entry trawl, limited entry fixed gear, and open access fleets. Data for 2004 were 

used from the limited entry surveys and data for 2005 were used from the open access survey. 

The production functions in the IO-PAC were developed by weighting the results of the three 

different NWFSC cost earnings surveys and incorporating information on landings taxes and 

moorage rates. Because the cost earnings surveys did not collect data on vessel moorage 

expenditures, these were estimated using 2009 data on moorage rates from 19 West Coast ports. 

Landings taxes paid by harvesters were estimated by applying the tax rate by state to the value of 

taxable landings in 2006. The cost earnings surveys do not cover all 19 vessel classification 

categories. Those vessel categories that lack direct survey coverage were given a weighted 

average production function of all categories with direct survey coverage. 

The use of IO-PAC is demonstrated with two examples of estimated changes in sablefish 

landings on the West Coast. The first example shows the change in economic output, income, 

and employment that results from a $500,000 decrease in landings by sablefish fixed gear 

vessels, which respectively are –$2,065,243, –$1,006,939 and –23 jobs. The second example 

also uses a decrease in sablefish landings of $500,000. However, the decrease in landings was 

not entered into the model as a change to only sablefish fixed gear vessels as classified by H. D. 

Radtke and S. W. Davis. Rather the effect was entered into the model as a change in the 

sablefish fixed gear commodity. Vessels in numerous classification categories have sablefish 

landings using fixed gear. The results of the commodity approach differ because the change in 

landings affects vessels in numerous classification categories. The change in output, income, 

and employment in the commodity approach are –$2,055,027, –$982,317 and –28.7 jobs, 

respectively. 

There are several areas where IO-PAC can potentially be improved. First, some 

simplifying assumptions were made regarding product flow and the wholesale seafood dealer 

markup and production function. Future research efforts will attempt to obtain better 

information about these components. Second, IO-PAC relies on economic relationships that 

existed in 2006; however, technology and prices change at relatively slow rates, so the model can 

likely be used for subsequent years with minimal error. Third, IO-PAC relies on a generic 

production function for all commercial vessels on the West Coast that is currently not covered by 

NWFSC cost earnings surveys. As a result, the model is likely more accurate for those sectors 

that have direct survey coverage. NWFSC is planning data collections that will reach vessels in 

classifications that currently lack coverage. As cost earnings data from these vessel 

classifications become available, they will be incorporated into the model.
Acknowledgments 

There are numerous individuals to thank for their contributions to this effort. We thank 

Brad Stenberg, Pacific Fisheries Information Network (PacFIN), who supplied fish ticket 

landings data and consultations about PacFIN related data issues; Dave Colpo, Pacific States 

Marine Fisheries Commission (PSMFC), who provided guidance on PacFIN data and landings 

taxes; Doreen Hansen, natural resources economist, who provided information about the 

proportion of groundfish landings made directly to the public in California; Greg Konkel, 

Washington Department of Fish and Wildlife (WDFW), who provided insight into Washington 

tribal landings; Lee Hoines, WDFW, who provided knowledge of commercial fishing in 

Washington; Marlene Bellman, PSMFC, who provided guidance with PacFIN data and 

constructed maps; Michelle Grooms, Oregon Department of Fish and Wildlife, who provided 

insight and data regarding landing fees and knowledge of commercial fishing in Oregon; Natalia 

Smagina, Jason Sayer, Julie Hoke, and Beth Leech, Washington Department of Revenue, for 

insight and data regarding the Washington Enhanced Food Fish Tax; Scott Steinback, Northeast 

Fisheries Science Center, who provided invaluable advice on how to construct a fisheries 

specific input-output model using IMPLAN software; Steve Freese, National Marine Fisheries 

Service, who provided project insight into federal excise taxes; and Terry Tillman and Gerry 

Kobylinski, California Department of Fish and Game, who provided insight into landings taxes 

and knowledge of commercial fishing in California. 

We also thank personnel at numerous harbors who supplied moorage rates: Cheryl 

Charitar, Coos Bay, Oregon; and in California, Kevin Rockwell, Oxnard; Anita Yao, San 

Francisco; Don Ashley, Long Beach; Lori Strong, Los Angeles; Jere Kleinbach, Fort Bragg; 

Bridget Kurz, Sonoma County; Mick Kronman, Santa Barbara; and Harry Jones, San Diego. 

xi
xii
Abbreviations and Acronyms 

BEA U.S. Bureau of Economic Analysis 

CDFG California Department of Fish and Game 

CGE computable general equilibrium 

FEAM Fisheries Economic Assessment Model 

IMPLAN Impact Analysis for Planning (regional input-output software) 

IO input-output 

IO-PAC input-output model for Pacific Coast fisheries 

NAICS North American Industry Classification System 

NERIOM Northeast Region Commercial Fishing Input-Output Model 

NMFS National Marine Fisheries Service 

NWFSC Northwest Fisheries Science Center 

ODFW Oregon Department of Fish and Wildlife 

PacFIN Pacific Fisheries Information Network 

RPC regional purchase coefficient 

SAM social accounting matrix 

WDFW Washington Department of Fish and Wildlife 

WDOR Washington Department of Revenue 

xiii
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1. Introduction 

When making decisions, federal fishery managers are required to consider the importance 

of fishery resources to fishing communities. National Standard 8 of the Magnuson-Stevens 

Fishery Conservation and Management Act (as amended through 12 January 2007) specifies that 

such considerations utilize economic and social data based on the best scientific information 

available to provide for sustained participation, and to the extent practicable, minimize adverse 

economic impacts on fishing communities. Policy changes involving fishery harvest affect 

individuals and businesses directly involved in the fishing industry. These decisions also affect 

gas stations that supply fuel to fishing vessels, grocery stores that supply provisions to vessel 

crew members, health care providers who service communities in which crew families reside, 

and even teachers whose salaries depend partially on sales and property taxes generated by 

fishing activity. This paper describes a new model developed by the Northwest Fisheries 

Science Center (NWFSC) to estimate these effects and provide information about the effects of 

fishing on regional economies. 

The NWFSC input-output model for Pacific Coast fisheries (IO-PAC) was designed to 

estimate the gross changes in economic contributions and economic impacts resulting from 

policy, environmental, or other changes that affect fishery harvest. The IO-PAC was constructed 

by customizing Impact Analysis for Planning (IMPLAN) regional input-output (IO) software 

(Minnesota IMPLAN Group Inc., Hudson, Wisconsin). The methodology employed in 

developing this model is similar to that used in Northeast Fisheries Science Center’s Northeast 

Region Commercial Fishing Input-Output Model (NERIOM) (Steinback and Thunberg 2006). 

The IO-PAC model was designed to estimate the economic effects of changes in fishing 

harvest for many types of vessels and fish species over multiple geographic areas along the 

Pacific Coast. Commercial fishing vessels are classified by type using the 19 sector scheme 

developed by Radtke and Davis (2000). Vessels produce 32 unique species/gear outputs in the 

model. Estimates are spatially flexible and can be calculated for the entire West Coast; the states 

of Washington, Oregon, and California and the port study areas are displayed in Figure 1. 

Data used to customize IMPLAN were derived from Pacific Fisheries Information 

Network (PacFIN) fish ticket data maintained by the Pacific States Marine Fisheries 

Commission; the NWFSC limited entry fixed gear, limited entry trawl, and open access surveys; 

and information obtained from the California Department of Fish and Game (CDFG), the Oregon 

Department of Fish and Wildlife (ODFW), and the Washington Department of Fish and Wildlife 

(WDFW). A critical component of IO-PAC is the estimation of unique production functions for 

each of the 19 vessel classifications included in the model. NWFSC cost earnings surveys were 

the primary source of information used to estimate these production functions. Because the 

surveys targeted vessels that had a minimum threshold of groundfish or troll-caught salmon 

landings, the model is likely most accurate for the groundfish-related and salmon-troll-related 

contribution and impact estimates. However, the surveys provided enough cost earnings data to 

build unique production functions for some vessel classification sectors that are not designated as 
Puget Sound 

N Washington 

Figure 1. West Coast, state, and port study areas in IO-PAC. 

S Washington 

Astoria 

Tillamook 

Newport 

Coos Bay 

Brookings 

Crescent City 

Eureka 

Fort Bragg 

Bodega Bay

San Francisco 

Monterey 

Morro Bay 

Santa Barbara 

Los Angeles 

San Diego 

groundfish or salmon-troll related. Other vessel classification sectors included in the model did 

not have sufficient data to estimate unique production functions. For these sectors, a weighted 

average production function was used. NWFSC plans to survey these vessel categories in the 

near future and the data will be incorporated into the model as it becomes available. In addition, 

NWFSC plans to add additional sectors (e.g., private recreational and charter recreational) in 

future versions of the model. 

This paper provides an overview of the IO-PAC model design, explains its operation, and 

displays the outputs generated by its use. The paper proceeds as follows. Section 2, Elements of 

IO Analysis, summarizes the procedures used in IO modeling and the required considerations for 

its use in a fishery management setting. Section 3, Data, presents the data used in building the 

customized sectors contained in the model. Section 4, The IO-PAC Model, describes the model 

in detail. Section 5, Model Construction, discusses the model’s incorporation into the default 

IMPLAN system. Section 6, Impact Estimation, explains application of the model to generate 

impact assessments and offers two hypothetical examples. Section 7, Discussion, reviews the 

IO-PAC model, discusses its limitations, and makes suggestions for further improvement. 

2
2. Elements of IO Analysis 

When a business or firm expands or contracts, there is a ripple effect through the 

economy. For example, when fishing vessels increase their landings, they purchase more fuel 

and increase payments to labor. This new economic activity also generates activity in related 

businesses that sell to the fishing fleet. The related businesses then buy more inputs and hire 

more labor. Some of the additional labor income is subsequently spent on goods and services in 

the community. Change in one industry, therefore, is multiplied throughout the economy 

following its linkages to other businesses and payments to workers. To capture these effects, it is 

necessary to use an economic model that contains these linkages. IO analysis is a method of 

modeling relationships among businesses and between businesses and consumers. 

The short discussion of IO models that follows is by no means exhaustive. More detailed 

descriptions of IO analysis are in Miller and Blair (1985) and Hewings (1985). A survey of IO 

studies is in Richardson (1985). 

2.1. IO Fundamentals 

The underpinning of IO analysis is a double-entry accounting framework that tracks the 

flow of dollars in the economy. Expenditures and receipts of businesses and households are 

tracked. The sum of all expenditures made by businesses and households in the economy must 

equal the sum of all income received. These transactions are expressed in matrix form, and IO 

multipliers are derived through the manipulation of this matrix as shown below. 

The multipliers in IO models describe the “backward” linkages among industries. As 

some exogenous economic event affects an industry under investigation, economic activity is 

then affected in input supply industries and from changes in personal income. Any economic 

changes found downstream, “stemming from” effects, must be exogenously incorporated into the 

model (Watson et. al 2008). 

The multipliers in IO models are separated into three types of effects. 

1. Direct effect refers to the production change associated with a variation in final demand 

for the good itself. It is the initial activity that occurs in the economy, which is 

exogenous to the model. 

2. Indirect effect refers to secondary activity caused by changing input needs of directly 

affected industries (e.g., additional input purchases to produce additional output). 

3. Induced effect is caused by changes in household spending due to additional employment 

generated by direct and indirect effects. 

The fundamental equation of IO analysis, central to understanding multipliers, is 

3
X = (I-A)–1Y (1) 

where X is a J × 1 vector of industry outputs, or sales, for each of J sectors, (I-A)–1 is collectively 

referred to as the Leontief inverse, with I being a J × J identity matrix, while Y is a J × 1 vector 

of final demands for all J sectors’ production. A is the matrix of technical coefficients, which 

describes the flow of inputs from sector i to sector j. For a simple two sector economy, the A 

matrix of interindustry linkages would be 

A = (2) ⎥

⎦

⎤ ⎢

⎣

⎡

2221

1211

aa

aa

with 11 showing purchases by industry 1 from firms in the same sector, while a 21 represents 

inputs that industry 1 buys from industry 2. The other elements are defined accordingly (These 

values are usually reported per dollar of sales. Thus 21 = 0.15 means that for each dollar of 

sales by sector 1, sector 1 would purchase $0.15 worth of inputs from sector 2). The Leontief 

inverse of the A matrix is represented as 

a

a

(I-A)–1 = (3) ⎥

⎦

⎤ ⎢

⎣

⎡

2221

1211

αα

αα

The elements in the Leontief inverse matrix represent the total direct and indirect changes 

in output (in dollars) within the row industry resulting from an additional dollar’s worth of final 

demand initiated in the column industry. To calculate an output multiplier for a region, a change 

in final demand for a given sector is hypothesized, which can come from added spending by 

consumers, exporters, investors, or government. (For simplicity, we calculate the total effect of a 

$1 change in final demand for a given industry.) This is calculated as 

ΔX1 = (I-A)–1ΔY1j = (4) ⎥

⎦

⎤ ⎢

⎣

⎡

21

11

α

α

where ΔX1 is a vector of changes in total industry output from a $1 change in final demand for 

sector 1, (I-A)–1 is the Leontief inverse, and ΔY1j is a column vector that contains a 1 in the first 

row to show the dollar change in final demand for sector 1 and 0 in all other positions. The 

result is equal to the first column of the Leontief inverse. The direct effect is α11, while indirect 

effects relate to the off-diagonal elements, which is α21 in this case. The total output multiplier 

then is the sum of all changes in output that result from the increase in final demand for industry 

j and is calculated as 

Oj = ∑ (5) =

n

i

ij

1

α

for all j, where Oj is the output multiplier for industry j, which comes from the column sum of 

the αij values in the Leontief inverse. 

4
The types of multipliers in IO models differ depending on what parts of the economy are 

endogenous in the A matrix. For a Type I multiplier, only interindustry linkages are included, 

so, as in the example above, only direct effects of the change in final demand for industry j and 

the indirect effects on other sectors are included. The effects that arise as employees receive 

increased income and spend it are not included in the Type I multiplier. Thus the Type I 

multiplier is defined as: Type I = (direct effects + indirect effects) / direct effects. 

Type II multipliers make household spending and wages endogenous. In this case, the 

modified A matrix is 

Α = (6)

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎣

⎡

333231

232221

131211

aaa

aaa

aaa

The new third column adds households as an endogenous sector that purchases products and 

services from other sectors, based on their increased wages that are found in the added third row 

(a33 shows the hiring of laborers directly by households, which might be a variety of personal 

services). 

The additional spending that occurs in the economy due to new household income is 

called an induced effect. The direct, indirect, and induced effects together yield a “Type II” 

multiplier. The Type II multiplier is defined as follows: Type II = (direct effects + indirect 

effects + induced effects) / direct effects.1

Social accounting matrix (SAM) multipliers allow for further endogenization of accounts 

such as state and local government, federal government, savings and investment, corporations, 

and commuting patterns. In IMPLAN the difference between the Type II multiplier and the type 

SAM multiplier that is only closed with respect to households is that the SAM multiplier 

accounts for commuting patterns where labor’s place of residence and place of occupation differ. 

In IO-PAC the models for the substate regions use SAM multipliers that endogenize only 

households. For the state and West Coast models, households and state and local government 

are also endogenized. 

2.2. IO Model Assumptions 

There are several key assumptions of IO models. First, IO models are demand driven and 

assume that the supply of outputs is unlimited. As a result, an increase in demand is always met 

by an increase in supply. Second, IO models assume that commodity and factor prices are fixed 

regardless of any change in demand. Due to these assumptions, IO models tend to overestimate 

the effects of policy changes (Miller and Blair 1985). Third, IO models assume zero substitution 

elasticities in production and consumption. For producers, the technical coefficients (aij) are 

fixed. For consumers, the proportions of their total expenditures made on different commodities 

are fixed. As a result of the fixed factor ratios, IO models are less appropriate for studying 

 

1

 Other multipliers, such as social accounting matrix (SAM) multipliers, endogenize additional sectors, such as 

government expenditure or other institutions. 

5
economies that are facing factor constraints or changes in production technology (Seung and 

Waters 2005). 

2.3. Study Area Considerations 

Selection of the appropriate study area is an important dimension in IO analysis. 

Generally, larger geographic areas have larger multipliers in an IO model. The level of 

economic interdependence among entities in larger geographic areas is greater than that in 

smaller geographic areas. Smaller geographic areas tend to have lower economic diversity and 

must import a larger portion of goods and services (Miller and Blair 1985). Consequently, 

businesses in larger geographic areas likely derive a higher proportion of their inputs from within 

the area than businesses in smaller geographic areas. Likewise, households in larger geographic 

areas likely source a higher share of consumed goods and services from within the area than 

households in smaller geographic areas. Thus in IO models, greater interdependence among 

entities results in larger multipliers. 

While choosing a larger study area will likely produce larger multipliers, it also may 

reduce the relative importance of a particular industry. The larger the study area, the more likely 

the effects of a change in economic activity will be masked by other activity that is occurring 

within the area; hence, the relative importance of a particular industry will be diluted (Watson et 

al. 2007). 

The appropriate size of the analysis region depends heavily on the purpose of the analysis 

and the particular policy issue being addressed. For example, if the question is how the output 

from the fishing industry in a small port in Oregon ripples through the Oregon economy, then a 

statewide study area is appropriate. However, if the question is how a change in fishing 

regulations will affect the income of inhabitants of the same small port, then a smaller, port-level 

study area is more appropriate. 

2.4. Trade Flow Considerations 

Location quotients, supply-demand pooling, and regional purchase coefficients (RPCs) 

are the varieties of methods used to estimate trade flows into and out of a study region. The IOPAC model uses an RPC approach to estimate regional trade flows. Using RPCs is the approach 

generally suggested by makers of IMPLAN.2

 The RPCs used in the model are generated by 

IMPLAN software through a series of econometric equations. An RPC for a given commodity 

indicates the proportion of local demand for the commodity that is met by local production. 

2.5. IO Models in a Fishery Context 

There are numerous studies that examine the economic contribution and impacts of 

recreational and commercial fisheries. Seung and Waters (2006) provided a detailed overview of 

the use of IO models in a fisheries context. 

 

2

 See the IMPLAN professional software, analysis, and data guide, online at http://www.implan.com. 

6
Steinback (2004) points out an important consideration that IO models must address 

before they are appropriate for use in a fishery management context. IO models are designed to 

estimate the backward linked effects of an exogenous change in final demand. However, fishery 

managers do not control the sale of fishery resources in final markets such as grocery stores, 

restaurants, etc. Rather, fishery managers control harvest of fishery resources. Management is 

imposed at the point of production. If the standard IO framework is not modified to account for 

this and changes in production are entered as if they were changes in final demand, the estimates 

of economic impacts will be overstated. 

There are several approaches to handling production changes rather than final demand 

changes in an IO framework. The approach in the IO-PAC model is the same as that used by 

Steinback and Thunberg (2006). The RPCs of the directly impacted sectors are set to zero, then 

production changes are modeled as if they originated from final demand. This approach permits 

the utilization of the ready-made IO system IMPLAN. The directly impacted sectors added to 

IMPLAN are all given an RPC of 0 except for the bait supplying sector. The bait sector supplies 

the commodity of bait to the fish harvesters that are added to the model. No other sector 

purchases bait in the model. As a result, not setting the RPC to 0 for the bait supplying sector 

avoids the feedback effect that necessitates the RPCs be set to 0 as discussed in Steinback 

(2004). By setting the RPCs to 1 for the bait sector, we are assuming that harvesters will 

purchase 100% of bait from suppliers within the study area. The wholesale seafood trade sector 

that is added to the model is also assigned an RPC of 0. The default fish processing sector 

(IMPLAN Sector 71) is assigned an RPC of 0 because it will be modeled as a directly impacted 

sector in the same manner as the harvesting sectors. The default fishing sector in IMPLAN 

(Sector 16) is assigned an RPC of 0 to avoid double counting of harvester-level impacts when 

impacts on the seafood processing sector are entered. 

2.6. IMPLAN 

IMPLAN is a commercially available data collection and regional modeling system that 

was developed by the U.S. Forest Service with cooperation of the Federal Emergency 

Management Agency and the U.S. Bureau of Land Management for use in land and resource 

management planning. It has been in use since 1979. The IMPLAN system has appeal due to its 

widespread use and availability of support literature. Integrating gear-specific and speciesspecific commercial fishing data into the IMPLAN framework permits anyone with knowledge 

of how to use IMPLAN to assess the impact of fishery specific management actions. 

Additionally, by using IMPLAN, the interrelationships among newly created fishing-related 

sectors and other industrial sectors are explicitly detailed. 

7
3. Data 

Data for the model come from three primary sources: IMPLAN, PacFIN, and the 

NWFSC cost earnings surveys. In addition to these primary data sources, data on landing tax 

rates and moorage rates are described at the end of the section. 

3.1. IMPLAN Data 

IMPLAN collects, organizes, and econometrically estimates the data that are necessary to 

construct regional economic impact models.3 These data, collectively referred to as the region’s 

social accounts, consist of purchases of inputs, labor, and capital by the respective sectors of the 

economy, the output production of each sector, household demands in the region, sources of 

income of households in the region, taxes paid and government spending in the region, and the 

region’s imports and exports. 

IMPLAN constructs county-level social accounts based on a variety of data sources 

including the U.S. Census Bureau, U.S. Bureau of Economic Analysis (BEA), and ES-202 

employment data. The procedure that IMPLAN uses to generate the social accounts consists of 

two main components. The first is national make and use transaction tables and the second is 

county specific data on industry output, employment, income, and final demands. Final demands 

in turn consist of household, government, and export purchases. The national make and use 

transaction tables are based on the 1997 Benchmark Input-Output Study conducted by BEA. 

An absorption table is then created by dividing each of the elements of the use matrix by 

the respective industry’s total output. This yields the percent of each dollar of output spent on 

intermediate inputs from other sectors. A column, then, represents the industry’s production 

function or the proportion of intermediate inputs used to produce $1 of output. 

The actual industry mix or the size of each industry in a region is specific to the study 

area. IMPLAN uses county specific ES-202 data, county business patterns data from the U.S. 

Census Bureau, Bureau of Labor Statistics, and BEA’s Regional Economic Information System 

data to estimate employment for every sector in the region. Value-added components such as 

employee compensation, proprietor’s income, and other property income are derived from 

BEA’s National Income and Product Accounts data. Estimates of total industry output primarily 

come from BEA’s output series and from its Annual Survey of Manufacturers. 

The default IMPLAN 2006 data are used to characterize the nonfishing economy of the 

regions such as the agricultural, manufacturing, trade, and service sectors, as well as the various 

institutions in the region such as households and governments. 

 

3

 See footnote 2. 

8
3.2. PacFIN Data 

IO-PAC utilizes 2006 fish ticket data from PacFIN.4 PacFIN data include fish ticket and 

vessel registration information that is supplied by CDFG, ODFW, and WDFW. Each time a 

commercial fishing vessel lands fish along the West Coast, it is documented on a fish ticket. For 

all commercial landings sold to wholesale fish dealers or processors, the fish buyers are required 

to fill out a fish ticket that describes the species, weight, and total price paid for the fish 

purchased. It also contains information on the vessel identification of the seller, gear type used 

to catch the fish, date of transaction, and port where the fish were landed. If a commercial 

fishing harvester sells directly to consumers, the harvester is responsible for recording the 

receipts, filling out fish tickets, and remitting the information to the appropriate state agency. 

Vessel registration information supplied by the states includes some physical characteristics such 

as length and engine horsepower. For this project, PacFIN personnel supplied data on pounds 

landed and revenue received by species, gear type, and port for each vessel that landed more than 

$1,000 in 2006. 

These data, when aggregated into vessel classifications and commodity types, comprise 

the sales estimates that are included in the model. The vessel classification scheme and 

commodity types are discussed further in the IO-PAC Model section. PacFIN contains shoreside 

landings along the West Coast. There are no landings data for two of the vessel classifications: 

Alaska fisheries vessels and mother ship catcher/processors. As a result, the current version of 

IO-PAC cannot be used for estimating impacts resulting from harvest changes in these sectors. 

In addition to landings data, PacFIN data contain vessel physical characteristics and 

permit information. The physical characteristics that come from vessel registrations include 

length and engine horsepower. Special endorsements and permit information such as federal 

limited entry trawl and limited entry fixed gear are also included. Vessel length information is 

used in calculating moorage rates. 

A PacFIN vessel identification issue affects some estimates in IO-PAC. Fish ticket data 

are linked to individual vessels through an identification variable called Derived ID in PacFIN. 

Derived ID is generated primarily through the use of U.S. Coast Guard and state agency 

registration numbers. There are some instances when a fish ticket contains a vessel identifier 

that does not have a valid Coast Guard or state registration identification. These records are 

assigned a Derived ID that begins with “ZZZ.” In 2006, 9% of landings by value on the West 

Coast were attributable to fish tickets with a ZZZ identifier. This percentage is substantially 

higher when narrowing the scope to Washington alone. In Washington, fish tickets with a 

Derived ID beginning with ZZZ are almost entirely tribal fishing vessels. In 2006, 91% of fish 

tickets with ZZZ IDs were from Indian tribal vessels in Washington.5

In a given year, ZZZ identifiers are intended to be unique to an individual vessel. Every 

fish ticket with the same vessel identification number that is not a valid Coast Guard or state 

registration number is given a single, consistent ZZZ ID. However, uniquely identifying an 

individual vessel is problematic for tribal vessels. Each fish ticket from a tribal vessel in 

 

4

 See http://pacfin.psmfc.org/index.php. 

5

 Based on a PacFIN data query. 

9
Washington has a unique tribe identifier in the first two digits of the tribal ID that is remitted to 

PacFIN. Following the first two digits, some tribal IDs have a number for an individual member 

of the tribe. Some tribe IDs do not include a number for an individual tribe member. When tribe 

IDs do not include a number for individual tribe member following the first two digits, a single 

ZZZ value within PacFIN can represent more than one vessel. Even in cases when the tribe IDs 

do include a number for individual tribe members, a single ZZZ ID in PacFIN is sometimes 

attributable to more than one vessel because an individual fisherman within a tribe may operate 

more than one vessel.6

IO-PAC does not exclude the fish ticket data from vessels with ZZZ IDs. Vessels with 

ZZZ IDs are important for estimates of commercial fishing revenue, especially in Washington. 

In instances where a unique ZZZ identifier represents more than one vessel, vessel classification 

as displayed in Table 1 may be affected; however, in IO-PAC it is assumed that misclassifying 

revenue by type of vessel is less problematic than excluding the revenue altogether. 

Additionally, failure to uniquely identify vessels results in a different approach to employment 

estimates in Washington, which is discussed in greater detail in the IO-PAC Model section. 

3.3. NWFSC Cost Earnings Survey Data 

NWFSC cost earning surveys provide the data necessary to construct the production 

functions in IO-PAC. Three cost earning surveys were used in developing the production 

functions: the limited entry trawl survey, the limited entry fixed gear survey, and the open access 

survey. The costs categories from the surveys that were used in the model include fuel and oil; 

food and provisions; ice; bait; repairs, maintenance, and improvements; insurance; leased 

permits; purchased permits; interest; crew expense; captain expense; vessel length; and vessel 

market value. Responses to the surveys can be easily matched to vessel landings by species, gear 

type, physical characteristics, and permit information contained in PacFIN. A short description 

of the surveys follows. For a more detailed description of the survey programs and summary 

statistics used in constructing the production functions, see Lian.7

The survey population for the limited entry trawl survey consisted of all vessels with a 

limited entry trawl permit and at least $5,000 in landings in 2004. The survey collected 

information for 2003 and 2004 through in person interviews. There were 91 completed 

responses out of a total of 143 vessels for a response rate of 64%. Using the vessel classification 

scheme suggested by Radtke and Davis (2000), shown in Table 1, the principle classification of 

respondents was large groundfish trawler, with a sizable number of responses among vessels 

classified as whiting and crabber. There were five responses from vessels classified as small 

groundfish trawler and a few responses classified as Alaska fisheries vessel, shrimper, and other. 

The survey population for the limited entry fixed gear survey consisted of all vessels with 

a limited entry fixed gear permit and at least $1,000 in landings in 2004. This survey also 

collected information for 2003 and 2004, and used in person interviews. There were 61 

completed responses out of a total of 121 vessels for a response rate of 51%. The principle 

 

6

 G. Konkel, WDFW, Olympia. Pers. commun., 14 July 2009. 

7

 See tables 4, 5, 6, 10, 11, and 12 in Lian 2010, tables 3, 4, 5, and 6 in Lian in press. 

10
Table 1. Vessel sectors used in the IO-PAC (Radtke and Davis 2000). 

Order Vessel sector Rule description 

1 Mother ship 

catcher/processor 

Identified by vessel documentation. 

2 Alaska fisheries vessel Alaska revenue is > 50% of vessel’s total revenue. 

3 Pacific whiting offshore 

and onshore trawler 

Pacific whiting (Merluccius productus) PacFIN revenue plus U.S. 

West Coast offshore revenue is > 33% of vessel total revenue and 

total revenue is > $100,000. 

4 Large groundfish 

trawler 

Groundfish (including sablefish, halibut, and California halibut 

[Paralichthys californicus]) revenue from other than fixed gear is > 

33% of vessel total revenue and total revenue is > $100,000. 

5 Small groundfish 

trawler 

Groundfish (including sablefish, halibut, and California halibut) 

revenue from other than fixed gear is > 33% of vessel total revenue 

and total revenue is > $15,000. 

6 Sablefish fixed gear Sablefish revenue from fixed gear is > 33% of vessel total revenue 

and total revenue is > $15,000. 

7 Other groundfish fixed 

gear 

Groundfish (including halibut and California halibut), other than 

sablefish, revenue from fixed gear is > 33% of vessel total revenue 

and total revenue is > $15,000. 

8 Pelagic netter Pelagic species revenue is > 33% of vessel total revenue and total 

revenue is > than $15,000. 

9 Migratory netter Highly migratory species revenue from gear other than troll or line 

gear is > 33% of vessel total revenue and total revenue is > 

$15,000. 

10 Migratory liner Highly migratory species revenue from troll or line gear is > 33% 

of vessel total revenue and total revenue is > $15,000. 

11 Shrimper Shrimp revenue is > 33% of vessel total revenue and total revenue 

is > $15,000. 

12 Crabber Crab revenue is > 33% of vessel total revenue and total revenue is > 

$15,000. 

13 Salmon troller Salmon revenue from troll gear is > 33% of vessel total revenue and 

total revenue is > $5,000. 

14 Salmon netter Salmon revenue from gill or purse seine gear is > 33% of vessel 

total revenue and total revenue is > $5,000. 

15 Other netter Other species revenue from net gear is > 33% of vessel total 

revenue and total revenue is > $15,000. 

16 Lobster vessel Lobster revenue is > 33% of vessel total revenue and total revenue 

is > $15,000. 

17 Diver vessel Revenue from sea urchins, geoduck (Panopea abrupta), or other 

species by diver gear is > 33% of vessel total revenue and total 

revenue is > $5,000. 

18 Other > $15,000 All other vessels not above with total revenue > $15,000. 

19 Other ≤ $15,000 All other vessels not above with total revenue ≤ $15,000. 

classification of respondents was sablefish (Anoplopoma fimbria) fixed gear, with a sizable 

number of responses from vessels classified as crabber and other groundfish fixed gear. 

The survey population for the open access survey consisted of all active commercial 

fishing vessels that 1) landed at least $1,000 of salmon and groundfish at West Coast ports 

11
during 2005 and 2006, 2) had at least one trip on which groundfish and salmon accounted for a 

majority of revenue from landings, and 3) did not hold a limited entry permit. All survey data 

were collected by in person or telephone interviews. There were 532 vessels that met the above 

three requirements for which a telephone number was obtainable. This survey collected 

information for years 2005 and 2006. There were 168 completed responses out of a total of 532 

vessels for a response rate of 32%. Responses came from vessels classified as crabber, sablefish 

fixed gear, other less than $15,000, other greater than $15,000, other groundfish fixed gear, and 

salmon trollers. 

The production functions in IO-PAC rely on only the 2004 data from the limited entry 

trawl and fixed gear surveys and only on the 2005 data from the open access survey. The survey 

results differ considerably depending on which year is chosen for several reasons. 

In the limited entry trawl sector, differences between 2003 and 2004 reflect the 

implementation of the groundfish fishing capacity reduction program Congress enacted in 2003. 

The National Marine Fisheries Service (NMFS) invited program bids in July 2003. Bids were 

accepted during August 2003. Bids were submitted by 108 groundfish permit owners and NMFS 

accepted bids involving 92 vessels. On 4 December 2003, accepted bidders were required to 

permanently stop all further commercial fishing with their vessels and permits (Federal Register 

2003). 

The reduction in capacity had a sizable impact on average vessel costs and revenue. For 

the purposes of IO-PAC, it is assumed that the survey results from 2004 are more representative 

of current operations and are therefore used to construct the production functions. 

Differences in open access survey results between 2005 and 2006 reflect the fishery 

failure for Pacific salmon. In August 2006 the Secretary of Commerce declared a fishery 

resource disaster for the California and Oregon salmon fisheries, pursuant to section 312(a) of 

the Magnuson-Stevens Fishery Conservation and Management Act (Upton 2008). The Pacific 

salmon fisheries failure had a sizable impact on average vessel revenue for some vessel 

classifications. The change in revenue is relatively the greatest for vessels classified as sablefish 

fixed gear, other less than $15,000, and other greater than $15,000. Because of the salmon 

failure, 2006 is a major transitional year for open access fishing vessels. A high percentage of 

vessels classified as salmon trollers in 2005 shift into other vessel categories in 2006. It is 

unknown whether the transitional changes experienced in 2006 will become the new standard. 

For the purposes of IO-PAC, it is assumed that the nonfailure year provides better representation 

of the status quo for average costs and revenues of the open access fleet, hence the 2005 results 

are used to develop the production functions.8

3.4. Landings Taxes and Moorage Rates 

The voluntary cost earnings surveys listed above were not designed to capture all 

possible cost sources that commercial fishing vessels encounter. Attempting to capture all 

potential costs would have resulted in more lengthy questionnaires and possibly lower response 

 

8

 An updated cost earnings survey for the open access fleet is under way to collect data for years 2008 and 2009. 

This assumption will be analyzed when 2008 and 2009 data become available. 

12
rates. To improve response rates and data accuracy, some cost categories were not captured. 

Two such categories are moorage and landings taxes. As a result, they were estimated with data 

obtained from other sources. 

Commercial fishing moorage rates for vessels of various lengths were obtained from 

numerous West Coast ports. Annual moorage rates for 2009 are displayed in Table 2. Ports 

often handle moorage costs differently. Some charge a straight cost per foot, while others charge 

an increasing cost per foot as the vessel surpasses specified thresholds. Some ports charge by the 

length of slip, regardless of the length of the vessel. If available information indicated that the 

maximum slip length in a port is smaller than a given vessel size, no rate is reported in the table. 

An average for each vessel size in each state is developed by calculating the mean of ports with 

values displayed in the table. The West Coast average is the mean of the California, Oregon, and 

Washington averages. Because California has noticeably more harbors listed, taking the mean of 

all the harbors would increase the influence of the California harbors on the overall total. By 

using the mean of the California, Oregon, and Washington averages, each has the same weight in 

the West Coast average. 

Table 2. Moorage rates, 2009 ($ per year). 

Length of vessel (feet) 

85 80 70 65 60 50 40 30 

California 

Crescent City — — 2,381 2,381 2,041 1,706 1,450 1,195

Humboldt Bay 3,315 3,120 2,730 2,535 2,340 1,950 1,560 1,170

Port of Los Angeles 4,325 4,070 3,562 3,307 3,053 2,544 2,035 1,526

San Francisco Fisherman’s Wharf — — — — — 1,065 959 639

San Francisco Hyde Street — 4,688 4,688 4,688 4,688 2,930 2,344 2,344

Half Moon Bay — — — 6,677 6,178 5,178 4,178 3,179

Morro Bay — — 2,797 2,597 2,398 1,998 1,598 1,439

Moss Landing 5,523 5,198 4,549 4,224 3,899 3,249 2,599 1,949

San Diego B Street Pier 3,258 3,066 2,683 2,491 2,300 1,916 1,533 1,150

Bodega Bay — 5,659 4,952 4,598 4,244 3,537 2,830 2,122

California average 4,105 4,300 3,543 3,722 3,460 2,607 2,109 1,671

Oregon 

Astoria 2,295 2,160 1,890 1,755 1,620 1,350 1,080 810

Newport 3,304 3,128 2,583 2,420 2,145 1,701 1,306 1,056

Coos Bay 2,295 2,160 1,890 1,755 1,620 1,350 1,080 827

Oregon average 2,631 2,483 2,121 1,977 1,795 1,467 1,155 898

Washington 

Westport Grays Harbor 3,146 2,961 2,591 2,406 2,221 1,851 1,480 1,110

Seattle Fishermen’s Terminal 9,792 9,216 4,544 4,220 3,895 3,246 2,597 1,948

Ilwaco 1,597 1,503 1,315 1,221 1,127 635 508 381

Bellingham Squalicum Harbor — — — — — 3,967 3,174 2,380

Bellingham Blaine Harbor — — — — 4,760 3,967 3,174 2,380

Washington average 4,845 4,560 2,817 2,616 3,001 2,733 2,186 1,640

West Coast average 3,860 3,781 2,827 2,771 2,752 2,269 1,817 1,403

13
Commercial fishing vessels also incur federal and state taxes. These rates are presented 

in Table 3. Landings taxes at the federal level partially fund the groundfish fishing capacity 

reduction program. Tax programs in the three states differ in how they are administered and the 

rates that are levied by species. These taxes are referred to as landings taxes in California and 

landing fees in Oregon. The tax program in Washington is referred to as the enhanced food fish 

tax. Technically, the levy in Washington is on the first commercial possession by an owner of 

fish within the state. For the purposes of this discussion, all of these levies are referred to as 

Table 3. Taxes on commercial fishing vessel landings (see Table 7 for species scientific names). 

Jurisdiction and species taxed Rate/pound ($) 

California (levied on landing pounds)

All species of fish and shellfish unless otherwise specified 0.0013 

Mollusks and crustaceans, excluding squid and crab 0.0125 

Crab 0.0019 

Squid 0.0019 

Salmon, based only on weight in the round 0.0500 

Lobster 0.0125 

Abalone 0.0125 

Anchovy 0.0013 

Sardine 0.0063 

Mackerel 0.0013 

Halibut 0.0125 

Angel shark, based only on weight in the round 0.0113 

Swordfish, based only on weight in the round 0.0125 

Thresher shark, based only on weight in the round 0.0113 

Bonito shark, based only on weight in the round 0.0113 

Herring 0.0125 

Sea urchin 0.0013 

Barracuda, flying fish, frogs, giant sea bass, saltwater worms, white 

sea bass, yellowtail (Seriola lalandi) 

0.0125 

Oregon (levied on landing dollars) Rate/dollar (%) 

All species of fish and shellfish unless otherwise specified 1.09 

Salmon and steelhead 3.15 

Black/blue rockfish and nearshore fish 5.00 

Washington (levied on landing dollars)

Food fish or eggs unless otherwise specified 2.30 

Chinook, coho, and chum salmon, anadromous game fish and eggs 5.60 

Sea urchins and cucumbers 4.90 

Pink and sockeye salmon fish or eggs 3.40 

Oysters 0.10 

Federal (levied on landing dollars)

Pacific coast groundfish (using trawl gear) 5.00 

California coastal Dungeness crab 1.24 

California pink shrimp 5.00 

Oregon coastal Dungeness crab 0.55 

Oregon pink shrimp 4.70 

Washington coastal Dungeness crab 0.16 

Washington pink shrimp 1.50 

14
landings taxes. Information on landings taxes was obtained from the ODFW, CDFG, and the 

Washington Department of Revenue (WDOR). In Washington, the taxes are administered by 

WDOR with some assistance by WDFW. 

Landings taxes are typically paid by individuals or companies licensed as commercial 

fish receivers. These licensed fish receivers include wholesale fish dealers, seafood processors, 

and in the case of Oregon, licensed bait dealers. However, in all three states, in the event that a 

commercial fisherman sells fish directly to the ultimate consumer, thereby bypassing the transfer 

of fish to a licensed receiver, the commercial fisherman becomes liable for the tax (ODFW 2006, 

California Codes 2009, RCW 2009). 

In addition to landings tax liabilities for selling directly to the final consumer, it is 

common in Washington for fish receivers to shift some of the tax liability they face back to 

commercial fishermen. It is written in the Washington tax code (RCW 2009) that fish receivers 

can shift half of the landings tax back to fish sellers. As a result, fishermen and receivers 

typically negotiate the price that appears on the fish ticket that is the basis of the revenue in 

PacFIN. However, when receivers pay fishermen, one half of the receivers’ tax liabilities are 

deducted from the amount paid. This does not happen in every transaction, but it is reported to 

occur in a substantial majority of cases.9

Neither the Oregon tax code (ORS 2009) nor the California tax code (California Codes 

2009) include the provision to shift some of the tax back to harvesters. It may occur in some 

cases, but according to ODFW and CDFG personnel, the price paid to fish harvester by receivers 

that appears on the fish ticket is net of any tax agreement.10 As a result, the revenue received by 

harvesters that is reflected in fish tickets is considered net of tax in California and Oregon. For 

California and Oregon, the only occurrence of state-level landings taxes paid by fish harvesters is 

when sales are made to the final consumer. 

As noted, the federal government also places fees on certain fish landings to partially 

fund the groundfish fishing capacity reduction program. The fees are legally placed on the fish 

harvesters who sell the fish (CFR 2009), but fish buyers are directed to collect the fee and deduct 

it from the net trip proceeds that fish buyers pay to the fish sellers. The letter sent out to fish 

buyers (NMFS 2009) clearly indicates that the full amount of the tax should be paid by fish 

sellers. We therefore assume that fish harvesters pay the full amount of the federal landings fee 

and harvester proceeds on fish tickets are not net of these fees. 

 

9

 L. Hoines, WDFW, Olympia. Pers. commun., 8 July 2009. 

10 T. Tillman, CDFG, Woodland. Pers. commun., 14 July 2009. M. Grooms, ODFW, Salem. Pers. commun., 14 

July 2009. Both Tillman and Grooms indicated that this is not fully understood, but their understanding combined 

with that of the authors supported this assumption. 

15
4. The IO-PAC Model

The IO-PAC model is a fisheries-specific IO model, where 19 unique vessel 

classification sectors, one wholesale seafood dealer sector, and one bait supplying sector are 

incorporated into IMPLAN regional IO software. The 19 fishing vessel classifications (Table 1) 

are based on rules developed by Radtke and Davis (2000). The vessel sectors produce 32 unique 

species/gear commodity outputs. The bait sector produces a single commodity, bait. The 

methodology employed to develop IO-PAC is modified from the Northeast Fisheries Science 

Center’s NERIOM, developed by Steinback and Thunberg (2006). The approach differs from 

that of the Fisheries Economic Assessment Model (FEAM) currently being used in fisheries 

management along the West Coast. 

FEAM is also based on an underlying IMPLAN IO model and begins by extracting the 

regional economic multipliers from a pregenerated IMPLAN model. The IMPLAN multipliers 

are then applied to the estimates of the expenditures made by the respective fishing sectors to 

determine the total economic impact of the fishing sectors. In this way, the ripple effects of 

expenditures made by the fishing vessel sectors are accounted for by externally multiplying the 

expenditures by their regional and industry specific multipliers. A similar process is used in 

FEAM to determine the economic impacts of the seafood processing sectors. This method is 

similar to the method used by Kirkley (2004) in the mid-Atlantic regional impact model. When 

the multipliers are calculated through the regional absorption table inversion, the fishing sectors 

are not present in the model. This method requires relatively less effort to construct than the 

NERIOM approach. However, because this approach does not internalize the fishery sectors into 

the IO model framework, it does not explicitly detail the relationships between the fisheryrelated sectors and other industrial sectors (Seung and Waters 2006). 

The method employed by NERIOM and IO-PAC is to directly modify the sectors 

contained within the IMPLAN system. The regional linkages between the customized fishery 

sectors are established before the regional absorption table is inverted and the IO model is 

calculated. This method fully takes into account the effects of personal income generated by the 

fishing industry and the feedback interactions in the regional economy. Additionally, the 

approach of building the model in IMPLAN will also aid in the construction of a computable 

general equilibrium (CGE) model in the future. Information contained in the underlying SAM in 

IMPLAN can be used as the starting point for building a CGE model. 

The IO-PAC model is constructed by first generating a default IMPLAN model based on 

the geographical area to be analyzed. New data for the 21 new industry sectors, 32 species/gear 

commodity outputs, and a single bait commodity are entered into the model. Next the model is 

rerun with the new data to generate the fully customized regional IO model. The model is then 

ready to complete economic impact estimates. 

16
4.1. Industry Additions 

The industrial sectors added to IMPLAN include 19 vessel sectors, a single bait sector, 

and a wholesale seafood dealers sector. The vessel sectors entered in the model follow the vessel 

classification scheme of Radtke and Davis (2000). Each vessel was assigned to 1 of the 19 

vessel sectors based on Table 1 criteria. The classifications are rank dependent so that a vessel is 

classified into the highest ranking sector in which it meets the classification rule. For example, if 

a vessel meets the rule to be classified as Sector 1 (mother ship catcher/processor), then it is 

classified as mother ship catcher/processor regardless of whether it meets any additional 

classifications. Likewise, if a vessel satisfies the classification rule for Sector 4, Sector 12, and 

Sector 18, then the vessel would be classified as Sector 4 because that is the highest ranking 

vessel sector to which it belongs. Classification of vessels was performed by PacFIN personnel 

and appended to the fish ticket data that were supplied for the purposes of this project. 

Alternative categorization schemes were considered, but this scheme has some historical 

precedence, so there is general familiarity with it by fishery managers on the West Coast. 

Additionally, it is a classification scheme that can be used with data from a variety of different 

sources with relative ease. 

A wholesale seafood dealers sector is included in the model to account for economic 

effects of changes in the flow of fish to wholesale seafood dealers. Some fish flows from fish 

harvesters to parties other than seafood processors. This is necessary because some fish flows to 

wholesale seafood dealers, where it subsequently flows to restaurants, retailers, seafood 

processors, or is exported. In the default IMPLAN, wholesale seafood dealers are included in the 

default wholesale trade sector (Sector 390). Wholesale seafood dealers comprise a small portion 

of all wholesale dealers that are included in this IMPLAN sector. Consequently, the production 

functions, trade flows, and income estimates in the default wholesale trade sector, which includes 

everything from electronics to lumber, could differ from those of wholesales seafood dealers 

(Steinback and Thunberg 2006). Hence a wholesale seafood dealer sector was developed. The 

amount of fish that is expected to flow from harvesters to wholesale seafood dealers is detailed in 

the Product Flow subsection. 

A bait supplying sector is included in the model to provide a sector to allocate bait 

purchases made by fish harvesters. Recall that the RPCs of all directly impacted sectors are set 

to 0 in IO-PAC, so directing bait purchases to any of these sectors would have effectively forced 

bait purchases to be sourced from outside the study area. The bait supplying sector that is 

included is a stand-alone sector that only supplies bait to fish harvesters. No other sector 

purchases bait. As a result, the sector avoids the feedback problems that necessitate setting the 

RPC to 0 (see discussion in Steinback 2004). The inclusion of a stand-alone bait supplying 

sector enables bait purchases to be sourced from within the study area while avoiding the 

feedback effects. 

Vessel classifications along with the bait and wholesale seafood dealer sectors represent 

the industries added to IMPLAN. The IMPLAN codes for these classifications are displayed in 

Table 4. 

17
Table 4. Industry categories and associated IMPLAN codes. 

IMPLAN code Category description 

510 Mother ship catcher/processor 

511 Alaska fisheries vessel 

512 Pacific whiting trawler 

513 Large groundfish trawler 

514 Small groundfish trawler 

515 Sablefish fixed gear 

516 Other groundfish fixed gear 

517 Pelagic netter 

518 Migratory netter 

519 Migratory liner 

520 Shrimper 

521 Crabber 

522 Salmon troller 

523 Salmon netter 

524 Other netter 

525 Lobster vessel 

526 Diver vessel 

527 Other, more than $15,000 

528 Other, less than $15,000 

561 Bait ship 

563 Wholesale seafood dealers 

4.2. Commodity Additions 

The commodities added to IMPLAN include 32 different species/gear combinations and 

one bait commodity. The commodities are displayed in Table 5. The gear type portion of the 

commodity classification was made by grouping PacFIN fish ticket data along the gear 

categories presented in Table 6. The species classifications portion of the commodity 

classification was made by grouping the PacFIN data into the categories displayed in Table 7. 

The total landings by vessel type and species/gear combinations are displayed in Table 8. 

Landings are classified in the species/gear classifications even if species for particular gear types 

are considered bycatch. 

Use of species/gear combinations increases the flexibility of IO-PAC, permitting impact 

estimates to be made for harvest changes on a commodity basis. In practice, most impact 

estimates will likely be desired for particular gear classifications because regulations are often 

made based on vessels with particular permit authorization or gear type. However, there may be 

instances when impacts on a commodity basis will be preferable. 

Impacts on a commodity basis, unlike impact estimates on a vessel classification basis, 

will affect all vessels with landings of a particular species, regardless of vessel classifications. 

For example, suppose there is an area closure or some other regulation change that is expected to 

reduce fixed gear sablefish landings. Vessels classified in several categories have appreciable 

fixed gear sablefish landings. In 2006 these included sablefish fixed gear (51%), crabbers 

18
Table 5. Commodities added to IMPLAN and associated codes. 

IMPLAN code Species and gear combinations 

529 Whiting, at sea 

530 Whiting, trawl 

531 Whiting, fixed gear 

532 Sablefish, trawl 

533 Sablefish, fixed gear 

534 Dover/thornyhead, trawl 

535 Dover/thornyhead, fixed gear 

536 Other groundfish, trawl 

537 Other groundfish, fixed gear 

538 Other groundfish, net 

539 Crab, trawl 

540 Crab, fixed gear 

541 Crab, net 

542 Crab, other gear 

543 Shrimp, trawl 

544 Shrimp, fixed gear 

545 Salmon, trawl 

546 Salmon, fixed gear 

547 Salmon, net 

548 Highly migratory species, fixed gear 

549 Highly migratory species, net 

550 Coastal pelagic species, trawl 

551 Coastal pelagic species, fixed gear 

552 Coastal pelagic species, net 

553 Coastal pelagic species, other gear 

554 Halibut, trawl 

555 Halibut, fixed gear 

556 Halibut, net 

557 Other species, trawl 

558 Other species, fixed gear 

559 Other species, net 

560 Other species, other gear 

562 Bait 

Table 6. Gear groupings and associated PacFIN variables. 

IO-PAC Gear ID Description 

Trawl TWL Trawls except shrimp trawls 

Trawl TWS Shrimp trawls 

Fixed gear NTW Nontrawl gear 

Fixed gear HKL Hook and line gear except troll 

Fixed gear TLS Troll gear 

Fixed gear POT Pot and trap gear 

Net NET Net gear except trawl 

Other gear MSC Other miscellaneous gear 

Other gear DRG Dredge gear 

19
Table 7. IO-PAC commodity groupings. SPID = species identification, NA = not applicable, 

Nom. = nominal. 

IO-PAC SPID Common name Scientific name 

CPS CMCK Pacific mackerel Scomber japonicus 

CPS JMCK Jack mackerel Trachurus symmetricus 

CPS MSQD Market squid Loligo opalescens 

CPS NANC Northern anchovy Engraulis mordax 

CPS PBNT Pacific bonito Sarda chiliensis 

CPS PSDN Pacific sardine Sardinops sagax 

CPS UMCK Mackerel, unspecified NA 

Crab BTCR Bairdi tanner crab Chionoecetes bairdi 

Crab DCRB Dungeness crab Cancer magister 

Crab OCRB Other crab NA 

Crab RCRB Red rock crab Cancer productus 

Crab UCRB Crab, unspecified NA 

Crab UKCR King crab, unspecified NA 

Dover/thornyhead DOVR Dover sole Microstomus pacificus 

Dover/thornyhead LSP1 Nom. longspine thornyhead NA 

Dover/thornyhead SSP1 Nom. shortspine thornyhead NA 

Dover/thornyhead THDS Thornyheads, mixed Sebastolobus spp. 

Other groundfish ARR1 Nom. aurora rockfish NA 

Other groundfish ART1 Nom. arrowtooth flounder NA 

Other groundfish ARTH Arrowtooth flounder Atheresthes stomias 

Other groundfish BCC1 Nom. bocaccio NA 

Other groundfish BGL1 Nom. blackgill rockfish NA 

Other groundfish BLK1 Nom. black rockfish NA 

Other groundfish BLU1 Nom. blue rockfish NA 

Other groundfish BNK1 Nom. bank rockfish NA 

Other groundfish BRW1 Nom. brown rockfish NA 

Other groundfish BRZ1 Nom. bronzespotted rockfish NA 

Other groundfish BSOL Butter sole Isopsetta isolepis 

Other groundfish BYL1 Nom. black and yellow rockfish NA 

Other groundfish CBZ1 Nom. cabezon NA 

Other groundfish CBZN Cabezon Scorpaenichthys marmoratus 

Other groundfish CHN1 Nom. china rockfish NA 

Other groundfish CLP1 Nom. chilipepper NA 

Other groundfish CNR1 Nom. canary rockfish NA 

Other groundfish COP1 Nom. copper rockfish NA 

Other groundfish CSOL Curlfin sole Pleuronichthys decurrens 

Other groundfish CWC1 Nom. cowcod rockfish NA 

Other groundfish DBR1 Nom. darkblotched rockfish NA 

Other groundfish DSRK Spiny dogfish Squalus acanthias 

Other groundfish DVR1 Nom. Dover sole NA 

Other groundfish EGL1 Nom. English sole NA 

Other groundfish EGLS English sole Parophrys vetulus 

Other groundfish FLG1 Nom. flag rockfish NA 

Other groundfish FSOL Flathead sole Hippoglossoides elassodon 

Other groundfish GBL1 Nom. greenblotched rockfish NA 

Other groundfish GPH1 Nom. gopher rockfish NA 

Other groundfish GRDR Grenadier, unspecified NA 

20
Table 7 continued. IO-PAC commodity groupings. SPID = species identification, Nom. = nominal, 

NA = not applicable, Nor. = northern. 

IO-PAC SPID Common name Scientific name 

Other groundfish GRS1 Nom. grass rockfish NA 

Other groundfish GSP1 Nom. greenspotted rockfish NA 

Other groundfish GSR1 Nom. greenstriped rockfish NA 

Other groundfish HNY1 Nom. honeycomb rockfish NA 

Other groundfish KGL1 Nom. kelp greenling NA 

Other groundfish KLP1 Nom. kelp rockfish NA 

Other groundfish LCOD Lingcod Ophiodon elongatus 

Other groundfish LCD1 Nom. lingcod NA 

Other groundfish LSRK Leopard shark Triakis semifasciata 

Other groundfish MXR1 Nom. Mexican rockfish NA 

Other groundfish NUSF Nor. shelf rockfish, unspecified NA 

Other groundfish NUSP Nor. slope rockfish, unspecified NA 

Other groundfish NUSR Nor. nearshore rockfish, unspecified NA 

Other groundfish OFLT Other flatfish NA 

Other groundfish OGRN Other groundfish NA 

Other groundfish OLV1 Nom. olive rockfish NA 

Other groundfish PCOD Pacific cod Gadus macrocephalus 

Other groundfish PDAB Pacific sanddab Citharichthys sordidus 

Other groundfish PDB1 Nom. Pacific sanddab Citharichthys spp. 

Other groundfish PLCK Walleye pollock Theragra chalcogramma 

Other groundfish PNK1 Nom. pink rockfish NA 

Other groundfish POP2 Nom. Pacific ocean perch NA 

Other groundfish PTR1 Nom. petrale sole NA 

Other groundfish PTRL Petrale sole Eopsetta jordani 

Other groundfish QLB1 Nom. quillback rockfish NA 

Other groundfish RATF Spotted ratfish Hydrolagus colliei 

Other groundfish RCK2 Bolina rockfish, unspecified NA 

Other groundfish RCK4 Reds rockfish, unspecified NA 

Other groundfish RCK5 Sm. red rockfish, unspecified NA 

Other groundfish RCK6 Rosefish rockfish, unspecified NA 

Other groundfish RCK7 Gopher rockfish, unspecified NA 

Other groundfish RDB1 Nom. redbanded rockfish NA 

Other groundfish REX Rex sole Glyptocephalus zachirus 

Other groundfish REX1 Nom. rex sole NA 

Other groundfish ROS1 Nom. rosy rockfish NA 

Other groundfish RSOL Rock sole Lepidopsetta bilineata 

Other groundfish RST1 Nom. rosethorn rockfish NA 

Other groundfish SBL1 Nom. shortbelly rockfish NA 

Other groundfish SCR1 Nom. California scorpionfish NA 

Other groundfish SFL1 Nom. starry flounder NA 

Other groundfish SNS1 Nom. splitnose rockfish NA 

Other groundfish SPK1 Nom. speckled rockfish NA 

Other groundfish SSO1 Nom. sand sole NA 

Other groundfish SSOL Pacific sand sole Psettichthys melanostictus 

Other groundfish SSRK Soupfin shark Galeorhinus galeus 

Other groundfish STR1 Nom. starry rockfish NA 

Other groundfish STRY Starry flounder Platichthys stellatus 

21
Table 7 continued. IO-PAC commodity groupings. SPID = species identification, Nom. = nominal, 

NA = not applicable. 

IO-PAC SPID Common name Scientific name 

Other groundfish SWS1 Nom. swordspine rockfish NA 

Other groundfish TGR1 Nom. tiger rockfish NA 

Other groundfish TRE1 Nom. treefish NA 

Other groundfish UDAB Sanddabs, unspecified Citharichthys spp. 

Other groundfish UDNR Deep nearshore rockfish, unspecified NA 

Other groundfish UFLT Flatfish, unspecified NA 

Other groundfish UPOP Pacific ocean perch group, unspec’d NA 

Other groundfish URCK Rockfish, unspecified NA 

Other groundfish USHR Nearshore rockfish, unspecified NA 

Other groundfish USLF Shelf rockfish, unspecified NA 

Other groundfish USLP Slope rockfish, unspecified NA 

Other groundfish UTRB Turbots, unspecified NA 

Other groundfish VRM1 Nom. vermillion rockfish NA 

Other groundfish WDW1 Nom. widow rockfish NA 

Other groundfish YEY1 Nom. yelloweye rockfish NA 

Other groundfish YTR1 Nom. yellowtail rockfish NA 

Halibut CHL1 Nom. California halibut NA 

Halibut CHLB California halibut Paralichthys californicus 

Halibut PHLB Pacific halibut Hippoglossus stenolepis 

HMS ALBC Albacore tuna Thunnus alalunga 

HMS BSRK Blue shark Prionace glauca 

HMS BTNA Bluefin tuna Thunnus thynnus 

HMS DRDO Dorado Coryphaena hippurus 

HMS ETNA Bigeye tuna Thunnus obesus 

HMS ISRK Bigeye thresher shark Alopias superciliosus 

HMS MAKO Shortfin mako shark Isurus oxyrinchus 

HMS PSRK Pelagic thresher shark Alopias pelagicus 

HMS STNA Skipjack tuna Katsuwonus pelamis 

HMS SWRD Swordfish Xiphias gladius 

HMS TSRK Common thresher shark Alopias vulpinus 

HMS UTNA Tuna, unspecified NA 

HMS YLTL Yellowtail jack Seriola lalandi 

HMS YTNA Yellowfin tuna Thunnus albacares 

Other ASRK Pacific angel shark Squatina californica 

Other BCLM Washington butter clam Saxidomus giganteus 

Other BMSL Blue or bay mussel Mytilus edulus 

Other BTRY Bat ray Myliobatis californica 

Other CKLE Basket cockle Clinocardium nuttallil 

Other CMSL California mussel Mytilus californianus 

Other CUDA Pacific barracuda Sphyraena argentea 

Other EELS Eels, unspecified NA 

Other ESTR Eastern oyster Crassostrea virginica 

Other EULC Eulachon Thaleichthys pacificus 

Other EURO European oyster Ostrea edulis 

Other GBAS Giant sea bass Stereolepis gigas 

Other GCLM Gaper clam Tresus capax 

Other GDUK Geoduck Panopea abrupta 

22
Table 7 continued. IO-PAC commodity groupings. SPID = species identification, NA = not applicable. 

IO-PAC SPID Common name Scientific name 

Other GSTG Green sturgeon Acipenser medirostris 

Other HCLM Horse clams Tresus spp. 

Other KSTR Kumamoto oyster Crassostrea gigas kumamoto 

Other LCLM Native littleneck Protothaca staminea 

Other LOBS California spiny lobster Panulirus interruptus 

Other LSTR Olympia oyster Ostrea conchaphila 

Other MACL Mud clams Macoma spp. 

Other MCLM Manila clam Ruditapes philippinarum 

Other MEEL Monkeyface prickleback Cebidichthys violaceus 

Other MISC Misc. fish/animals NA 

Other MSC2 Misc. fish NA 

Other MSHP Plainfin midshipman Porichthys notatus 

Other OABL Other abalone NA 

Other OBAS Other bass NA 

Other OCRK Other croaker NA 

Other OCTP Octopus, unspecified NA 

Other OMSK Other mollusks NA 

Other OSKT Other skates Other Rajidae 

Other OSRK Other sharks NA 

Other OURC Other sea urchins NA 

Other PHRG Pacific herring Clupea harengus pallasii 

Other PROW Prowfish Zaprora silenus 

Other PSTR Pacific oyster Crassostrea gigas 

Other RCLM Razor clam Siliqua patula 

Other RURC Red sea urchin Strongylocentrotus franciscanus 

Other SCLM Soft-shelled clam Mya arenaria 

Other SCLP Sculpin, unspecified Cottidae spp. 

Other SHAD Shad, unspecified NA 

Other SHP1 Nom. California sheephead NA 

Other SMLT Smelt, unspecified NA 

Other SQID Squid, unspecified Decapoda 

Other SRFP Surfperch spp. Surfperch spp. 

Other UCLM Clam, unspecified NA 

Other UECH Echinoderm, unspecified NA 

Other UHAG Hagfish, unspecified Eptatretus spp. 

Other UMSK Mollusks, unspecified NA 

Other USCU Sea cucumbers, unspecified NA 

Other USKT Skates, unspecified Rajidae, unspecified 

Other USRK Sharks, unspecified NA 

Other WBAS White seabass Atractoscion nobilis 

Other WCRK White croaker Genyonemus lineatus 

Other WEEL Wolf-eel Anarrichthys ocellatus 

Other WSTG White sturgeon Acipenser transmontanus 

Salmon CHNK Chinook salmon Oncorhynchus tshawytscha 

Salmon CHUM Chum salmon O. keta 

Salmon COHO Coho salmon O. kisutch 

Salmon PINK Pink salmon O. gorbuscha 

Salmon SOCK Sockeye salmon O. nerka 

23
24

Table 7 continued. IO-PAC commodity groupings. SPID = species identification, NA = not applicable. 

IO-PAC SPID Common name Scientific name 

Salmon STLH Steelhead O. mykiss 

Salmon USMN Salmon, unspecified NA 

Sablefish SABL Sablefish Anoplopoma fimbria 

Shrimp BSRM Bait shrimp, unspecified NA 

Shrimp GPRW Yellowleg shrimp Penaeus californiensis 

Shrimp GSRM Bay ghost shrimp Callianassa californiensis 

Shrimp MSRM Blue mud shrimp Upogebia pugettensis 

Shrimp OSRM Other shrimp NA 

Shrimp PSHP Pink shrimp Pandaulus jordani 

Shrimp RPRW Ridgeback prawn Sicyonia ingentus 

Shrimp SPRW Spot shrimp Pandalus platyceros 

Shrimp USRM Ocean shrimp, unspecified NA 

Whiting PWHT Pacific whiting Merluccius productus 

(36%), other groundfish fixed gear (4%), other less than 15,000 (3%), and salmon trollers (2%). 

The remaining 4% of fixed gear sablefish landings was spread across the remaining vessel 

classifications. In this example, entering an exogenous reduction in the fixed gear sablefish 

harvest would result in a negative impact on all of these vessel classifications. The size of the 

impact in each vessel classification is determined by the specifics of its production function and 

its respective share of total sablefish fixed gear landings. 

The overall impact would be different for a scenario in which the same exogenous 

reduction in harvest affects only vessels classified as sablefish fixed gear. The greater the 

differences between the production functions of all the other vessel classifications with fixed 

gear sablefish landings from those categorized as sablefish fixed gear, the greater the difference 

in the results. Assuming the production functions differ considerably, similar results using the 

vessel classification approach would require separate exogenous harvest estimates for each 

vessel classification. Prior to entering the downturn in fixed gear sablefish landings into model, 

the total downturn would require apportionment among the different vessel classifications and 

each expected change would be entered separately. For example, the total downturn in fixed 

gear sablefish landings would first require apportionment among sablefish fixed gear, crabbers, 

other groundfish fixed gear, etc. Then each of those expected changes would be entered in the 

model separately and the impacts estimated simultaneously. 

4.3. Study Area 

The IO-PAC model is a collection of region-specific models. There are models for 

Washington, Oregon, California, and the entire West Coast. Additionally, there are models for 

port areas, which consist of a collection of ports in a substate geographic area. Because each of 

the state, port, and port-area models are subregions of the West Coast region, they will all be 

referred to as subregions in the following discussion. This follows the terminology used by 

Steinback and Thunberg (2006) in the NERIOM.
Table 8. Landings by vessel type and commodity code, 2006 value ($). 

IMPLAN Vessel classification 

code 

Species and gear combinations 510 511 512 513 514 515 

529 Whiting, at sea — — — — — — 530 Whiting, trawl — — 16,049,437 1,135,712 126,452 — 

531 Whiting, fixed gear — — — — — 76 

532 Sablefish, trawl — — 1,068,257 5,730,702 138,606 53,272 533 Sablefish, fixed gear — — 138,319 28,729 38,053 7,919,824 

534 Dover/thornyhead, trawl — — 551,623 4,604,122 83,753 47,975 

535 Dover/thornyhead, fixed gear — — 21 2,423 45 269,410 

536 Other groundfish, trawl — — 665,810 9,788,725 352,668 72,835 

537 Other groundfish, fixed gear — — 235 17,014 3,888 499,699 1

538 Other groundfish, net — — — 3,284 45,670 — 

539 Crab, trawl — — 35 1,850 77 — 

540 Crab, fixed gear — — 3,349,458 6,782,547 36,395 2,822,517 

541 Crab, net — — — 6,090 1,894 — 

542 Crab, other gear — — — — — — 543 Shrimp, trawl — — 21,632 1,300,335 1,182 40,758 

544 Shrimp, fixed gear — — — — — 5,175 

545 Salmon, trawl — — 35,861 1,326 1,147 — 

546 Salmon, fixed gear — — — 87,169 82,705 913,815 

547 Salmon, net — — — — — 97,408 

548 HMS, fixed gear — — 3,629 123,084 — 248,577 

549 HMS, net — — — 46 1,724 — 

550 CPS, trawl — — 6,422 446 — — 

551 CPS, fixed gear — — — — — 7 

552 CPS, net — — — 7 1,342 482 553 CPS, other gear — — — — — — 

554 Halibut, trawl — — 4,257 1,112,077 597,291 2,167 

555 Halibut, fixed gear — — 13,817 31,021 41,902 1,937,697 4

556 Halibut, net — — — 77,175 198,605 — 

557 Other species, trawl — — 66,680 355,360 39,601 580 

558 Other species, fixed gear — — 865 487 41,364 103,281 

559 Other species, net — — — 36,319 169,934 294 

560 Other species, other gear — — — — — 2,176 

Total 21,976,357 31,226,049 2,004,297 15,038,025 8

25
Table 8 continued horizontally. Landings by vessel type and commodity code, 2006 value ($). 

IMPLAN Vessel classification 

code 

Species and gear combinations 518 519 520 521 522 

529 Whiting, at sea — — — — — 530 Whiting, trawl — — 248 120,114 — 

531 Whiting, fixed gear — — — 75 — 

532 Sablefish, trawl — — — 404,879 — 

533 Sablefish, fixed gear 23 164,342 22,474 5,692,071 325,330 

534 Dover/thornyhead, trawl — — — 265,548 — 

535 Dover/thornyhead, fixed gear — 85 — 6,655 1,133 

536 Other groundfish, trawl — — 5,046 428,986 — 537 Other groundfish, fixed gear 7,336 5,537 20,897 382,240 94,442 

538 Other groundfish, net 20,694 — — 2,321 — 

539 Crab, trawl — 738 149 — — 

540 Crab, fixed gear — 2,456,793 3,265,246 120,966,903 156,663 

541 Crab, net 64 — 212 10,137 — 

542 Crab, other gear — — — 23,912 1,677 

543 Shrimp, trawl — 26,239 5,068,270 685,320 — 544 Shrimp, fixed gear — — 4,073,820 784,724 — 

545 Salmon, trawl — — — 4 — 

546 Salmon, fixed gear 63,198 819,124 9,952 2,857,295 4,633,803 

547 Salmon, net — — 85,904 3,952,646 21,664 18,

548 HMS, fixed gear 326,417 17,765,249 123,245 4,887,944 204,346 

549 HMS, net 28,216 2,424 — 2,803 146 

550 CPS, trawl — — 40 11 — 551 CPS, fixed gear 10 2,884 36 894 357 

552 CPS, net 2,525 38 — 262,979 11 553 CPS, other gear — — — 2,152 — 554 Halibut, trawl 578 — 20,490 10,972 — 

555 Halibut, fixed gear 57 140,159 49,680 2,536,750 279,460 

556 Halibut, net 24,823 — 582 — — 557 Other species, trawl — — 69,948 13,421 — 

558 Other species, fixed gear 5,768 116,537 575,411 434,165 372 

559 Other species, net 2,481,457 160,485 1,918 397,151 514 

560 Other species, other gear 556,267 80,051 263 39,955 — 

Total 3,517,434 21,740,683 13,393,830 145,173,028 5,719,919 19,

26
27

Table 8 continued horizontally. Landings by vessel type and commodity code, 2006 value ($). 

IMPLAN Vessel classification 

code 

Species and gear combinations 525 526 527 528 Total all classifica

529 Whiting, at sea — — — — — 530 Whiting, trawl — — — — 17,43

531 Whiting, fixed gear — — — 12 532 Sablefish, trawl — — 323 2,810 7,39

533 Sablefish, fixed gear 17,637 — 122,157 424,009 15,60534 Dover/thornyhead, trawl — — 467 1,973 5,55535 Dover/thornyhead, fixed gear 33 — 1,193 36,329 1,26536 Other groundfish, trawl — — 5,084 16,031 11,33

537 Other groundfish, fixed gear 65,764 51,480 10,211 804,012 3,68538 Other groundfish, net 758 — 107 13,314 10

539 Crab, trawl 40 — — 235 

540 Crab, fixed gear 190,637 587 101,143 1,705,317 143,77

541 Crab, net 365 — 193 1,937 2

542 Crab, other gear — 148 250 36,397 6

543 Shrimp, trawl — — 16,300 26,905 7,19

544 Shrimp, fixed gear 19,811 — 1,168 82,518 5,05545 Salmon, trawl — — — — 3546 Salmon, fixed gear 10,338 — 64,544 461,978 10,15

547 Salmon, net — — 628,156 1,470,652 24,74

548 HMS, fixed gear 5,946 58 5,452 390,513 24,10

549 HMS, net — — — 4,008 15

550 CPS, trawl — — 2 — 

551 CPS, fixed gear 5,894 — 1,859 11,647 3

552 CPS, net 18,440 — — 285,975 14,00

553 CPS, other gear — — — — 

554 Halibut, trawl 224 — 16,092 27,270 1,79

555 Halibut, fixed gear 225,269 46,328 185,968 312,887 10,23556 Halibut, net 22,218 — 4,238 54,062 46

557 Other species, trawl 84 58 92,431 7,696 64

558 Other species, fixed gear 6,818,270 34,364 592,652 277,637 9,21

559 Other species, net 39,449 1,730 190,355 247,098 32,69

560 Other species, other gear 71,345 5,264,819 80,754,211 417,122 87,20

Total 7,512,522 5,399,571 82,794,555 7,120,343 434,00
The collection of regional models is displayed in Figure 1. A detailed list of how the port 

areas were constructed using PacFIN data is in Table 9. The port areas were designed to 

correspond to the location and composition of port groups present in the 2005–2006 Pacific 

Coast groundfish environmental impact statement (Table 8-1 of Appendix A in PFMC 2004). 

The IO-PAC approach of region-specific models is intended to be flexible enough to 

provide impact estimates for a wide variety of policy situations and analysis goals. It can 

provide coast-wide, statewide, and port-level impacts. The appropriate study area is dependent 

on the nature of the policy change, the goals of the analysis, and the resolution of the exogenous 

change in fish harvest that is expected. 

If a policy change will only affect a few ports along the West Coast, then depending on 

the intent of the analysis, it may be preferable to use study areas for only those subregions. For 

example, assume that a given policy will reduce fish harvest in only Astoria and Westport, and 

estimating changes in income in these communities is the objective of the analysis. If exogenous 

estimates of the changes in harvest are known for Astoria and Westport, it will likely be 

preferable to estimate the impacts of the changes by using only Astoria and South Washington 

study areas. The multipliers from the Astoria and South Washington study areas will likely 

result in better estimates of income effects than using the entire West Coast as the study area. 

Additionally, performing an analysis on these smaller study areas will likely better depict the 

relative importance of the fishing industry. 

However, estimated impacts are often desired that follow political or administrative 

boundaries. For example, estimated impacts may be needed for states or for the entire West 

Coast. In these cases, the state level and West Coast models will likely be more appropriate. In 

the example of a downturn in fish harvest in Astoria, the effects of the reduction will have a 

greater total income impact on the state of Oregon as a whole than in Astoria alone. The 

economy of Oregon is more diversified than the economy of Astoria, so the multiplier will be 

larger. 

While the impact of using the Oregon study area will be greater, the relative importance 

of the fishing industry will be less. Obtaining results at the state level or for the entire West 

Coast will come at the expense of obtaining a clear picture of the effects at a particular port. An 

advantageous feature of the IO-PAC model is that it is flexible enough to estimate the effects of 

changes in fishing regulations at many different levels of geographic resolution. 

An underlying assumption in the downturn of fish sales in the Astoria and Westport 

example is that the exogenous effects are known for a relatively small geographic area. For 

some policy or other effect on harvest, this may not be the case. However, the IO-PAC approach 

is also flexible enough to handle scenarios in which exogenous impacts are not known for 

individual ports. If a given policy is expected to result in a loss in fish sales across the entire 

West Coast, but no port level exogenous estimates are known, then the West Coast study area 

could be used to estimate the impacts of such a change. These West Coast impacts could then be 

apportioned to the state and port level of detail based on some metric of relative importance of 

the different regions to the whole. One such metric might be the proportion of landings of a 

particular species in the different geographic areas. Another approach used in NERIOM is to 

28
Table 9. IO-PAC port groups and names (PCID = port-county ID, AGID = agency ID). 

State IO-PAC port group PCID Port name (PNAME) AGID 

CA Bodega Bay BDG Bodega Bay C 

CA Bodega Bay RYS Point Reyes C 

CA Bodega Bay SLT Sausalito C 

CA Bodega Bay TML Tomales Bay C 

CA Bodega Bay OSM Other Sonoma, Marin County outer coast 

ports 

C 

CA Crescent City CRS Crescent City C 

CA Eureka ERK Eureka C 

CA Eureka FLN Fields Landing C 

CA Eureka OHB Other Humboldt County ports C 

CA Eureka TRN Trinidad C 

CA Fort Bragg ALB Albion C 

CA Fort Bragg ARE Point Arena C 

CA Fort Bragg BRG Fort Bragg C 

CA Fort Bragg OMD Other Mendocino County ports C 

CA Los Angeles DNA Dana Point C 

CA Los Angeles LGB Long Beach C 

CA Los Angeles NWB Newport Beach C 

CA Los Angeles OLA Other Los Angeles, Orange County ports C 

CA Los Angeles SP San Pedro C 

CA Los Angeles TRM Terminal Island C 

CA Los Angeles WLM Wilmington C 

CA Monterey CRZ Santa Cruz C 

CA Monterey MNT Monterey C 

CA Monterey MOS Moss Landing C 

CA Monterey OCM Other Santa Cruz, Monterey County ports C 

CA Morro Bay AVL Avila C 

CA Morro Bay MRO Morro Bay C 

CA Morro Bay OSL Other San Luis Obispo County ports C 

CA San Diego OCN Oceanside C 

CA San Diego OSD Other San Diego County ports C 

CA San Diego SD San Diego C 

CA San Francisco ALM Alameda C 

CA San Francisco BKL Berkeley C 

CA San Francisco OAK Oakland C 

CA San Francisco OSF Other San Francisco Bay, San Mateo 

County ports 

C 

CA San Francisco PRN Princeton/Half Moon Bay C 

CA San Francisco RCH Richmond C 

CA San Francisco SF San Francisco C 

CA Santa Barbara HNM Port Hueneme C 

CA Santa Barbara OBV Other Santa Barbara, Ventura County 

ports 

C 

CA Santa Barbara OXN Oxnard C 

CA Santa Barbara SB Santa Barbara C 

CA Santa Barbara VEN Ventura C 

OR Astoria AST Astoria O 

29
Table 9 continued. IO-PAC port groups and names (PCID = port-county ID, AGID = agency ID). 

State IO-PAC port group PCID Port name (PNAME) AGID 

OR Astoria CNB Cannon Beach O 

OR Astoria CRV Pseudo port code for Columbia River O 

OR Astoria GSS Gearhart/Seaside O 

OR Tillamook NHL Nehalem Bay O 

OR Tillamook NTR Netarts Bay O 

OR Tillamook PCC Pacific City O 

OR Tillamook TLL Tillamook/Garibaldi O 

OR Brookings BRK Brookings 

OR Brookings GLD Gold Beach O 

OR Brookings ORF Port Orford O 

OR Columbia River CRV Columbia River pseudo port code O 

OR Coos Bay BDN Bandon O 

OR Coos Bay COS Charleston (Coos Bay) O 

OR Coos Bay FLR Florence O 

OR Coos Bay WIN Winchester Bay O 

OR Newport DPO Depoe Bay O 

OR Newport NEW Newport O 

OR Newport WLD Waldport O 

WA North WA coast LAP La Push W 

WA North WA coast NEA Neah Bay W 

WA North WA coast PAG Port Angeles W 

WA North WA coast SEQ Sequim W 

WA North WA coast TNS Port Townsend W 

WA Puget Sound ANA Anacortes W 

WA Puget Sound BLL Bellingham Bay W 

WA Puget Sound BLN Blaine W 

WA Puget Sound EVR Everett W 

WA Puget Sound FRI Friday Harbor W 

WA Puget Sound LAC La Conner W 

WA Puget Sound OLY Olympia W 

WA Puget Sound ONP Other north Puget Sound ports W 

WA Puget Sound SEA Seattle W 

WA Puget Sound SHL Shelton W 

WA Puget Sound TAC Tacoma W 

WA South and central WA coast CPL Copalis Beach W 

WA South and central WA coast GRH Grays Harbor W 

WA South and central WA coast LWC Ilwaco/Chinook W 

WA South and central WA coast OCR Other Columbia River ports W 

WA South and central WA coast WLB Willapa Bay W 

WA South and central WA coast WPT Westport W 

apportion the indirect effects based on the relative importance of subregional economies to the 

total regional economy. 

The IO-PAC approach is intended to be flexible enough to handle numerous different 

types of analyses. For policies that only affect a few ports and the exogenous effects are known 

30
at that level, then models for port specific study areas can be used. For policies that will affect 

all ports along the West Coast, the model for the West Coast is available. Additionally, the statelevel study areas are available to develop state-level impact estimates for cases in which 

exogenous impacts are state or port specific. 

4.4. Product Flow 

Product flow considerations are important for fishing industry impact and contribution 

models. Generally, as long as fish harvester sales are not to final consumers or exported from 

the study area, they continue to affect economic activity within the study area. Each firm that 

purchases the seafood may add value in the production of its own goods or services. Hence a 

fish processor may add value to raw fish by filleting, packaging, cooking, canning, or icing. 

Wholesalers may add value by freezing, warehousing, providing an auction market, or shipping 

services. Retailers may add value by storing, icing, and displaying the product for purchase by 

final consumers. Restaurants may add value by cooking and preparing the seafood for patrons. 

At any of these stages, there is the potential that a change in fishery regulations will have an 

economic impact. 

The product flow of fishery resources is complex and there are few sources of data that 

can be used to accurately account for these transactions in an economic model. Like other 

fishery IO models (Kirkley et al. 2004, Steinback and Thunberg 2006), the IO-PAC model relies 

on simplifying assumptions. There are data available to help guide these assumptions, and while 

by no means extensive, the data are the best available at this time. The assumptions about the 

flow of fish in IO-PAC were derived by utilizing data from WDOR and the absorption of fish 

made by the IMPLAN default seafood product preparation and manufacturing sector (Sector 71). 

The Washington form of a landing tax, the Enhanced Food Fish Tax, is administered by 

WDOR. Because the tax is levied on the individual or entity that first retains possession of the 

fish in Washington, the tax records are useful in understanding the flow of fish between different 

types of buyers. When a commercial vessel sells fish directly to the public, the vessel pays the 

tax. Every business entity in Washington must file a master business application with the 

WDOR Licensing Division. On this application, the business explains the type of commercial 

activity in which it will be involved. The business is then analyzed and classified by North 

American Industry Classification System (NAICS) code based on its principle source of revenue. 

Revisions to business classifications are made through time based on reported activity contained 

in tax returns.11 The proportion of the tax paid by businesses thus classified provides insight into 

the flow of harvested fish. 

Table 10 presents the proportion of Enhanced Food Fish Tax paid by type of business and 

six digit NAICS code in 2006. It indicates that the fish and seafood merchant wholesalers sector 

paid 30.2% of the tax. Based on this proportion, IO-PAC assumes that 30% of all fish landed in 

each study area along the West Coast will pass through fish and seafood merchant wholesalers. 

Fish purchased by wholesale seafood dealers will subsequently be purchased by final consumers, 

purchased by fish processors, or exported out of the region. 

 

11 B. Leech, WDOR, Olympia. Pers. commun., 10 July 2009. 

31
Table 10. Washington Enhanced Food Fish Tax by NAICS, calendar year 2006. 

NAICS code Title Tax share (%) 

114111 Fin fishing 12.6 

114112 Shellfish fishing 1.1 

311711 Seafood canning 12.1 

311712 Fresh and frozen seafood processing 30.1 

423910 Sporting and recreational goods and supplies merchant wholesalers 0.1 

424460 Fish and seafood merchant wholesalers 30.2 

424490 Other grocery and related products merchant wholesalers 4.2 

445220 Fish and seafood markets 4.6 

451110 Sporting goods stores 0.1 

454390 Other direct selling establishments 1.3 

713930 Marinas 0.7 

999999 Miscellaneous 2.9 

Total 100.0 

The proportion of fish landings in each study area that will flow to fish processors is 

determined by constructing a default IMPLAN model for each study area, then viewing the 

commodity balance sheet for the commercial fishing sector. For the West Coast region as a 

whole, approximately 45% of all the default commercial fishing sector sales are made to the 

seafood product preparation and manufacturing sector. This is similar to the 42.3% that flows to 

the seafood canning and fresh and frozen seafood processing sectors according to Enhanced 

Food Fish Tax records in Washington. 

The flow of fish in IO-PAC is displayed in Figure 2. Each solid line between the 

different entities in the harvesting and product distribution schematic is included as a calculated 

impact in IO-PAC. Those represented with a dashed line are not incorporated in IO-PAC. 

Similar to the approach by Steinback and Thunberg (2006), there are expected to be a number of 

seafood substitutes available beyond fish and seafood merchant wholesalers and seafood 

processors. Hence the impacts of most fishery management actions on final consumers and other 

intermediate demand industries are likely to be negligible.

4.5. Vessel Production Functions 

The production functions in IO-PAC were developed by weighting the results of the three 

different NWFSC cost earnings surveys and incorporating information on landings taxes and 

moorage rates. Survey results provided the majority of the information used to construct the 

production functions. Results were weighted to produce a single production function that 

represents the vessels contained in each of the vessel classifications. Moorage and landings 

taxes were estimated using external sources and added to the production functions. There are 

some vessel classifications that have not yet been included in the cost earnings surveys. The 

assignment of production functions for these sectors is addressed in two ways. All of these 

sectors, with the exception of small groundfish trawlers, were assigned a weighted average 

production function. Small groundfish trawlers were assigned the production function of large 

groundfish trawlers. 

32
Harvesters 

Wholesale dealers 

Figure 2. IO-PAC product flows. Product flows with solid lines are captured in IO-PAC; those with 

dashed lines are excluded. 

Cost Earnings Surveys 

The following steps describe how the results from the three cost earnings surveys were 

used to generate cost estimates for the production functions. First, the average expenditures by 

cost category from the three surveys were converted to a proportion of average revenue for each 

of the vessel classifications. If Cik equals the average cost of each expenditure category ( ) for 

vessel classification (k) and Rk is equal to the average revenue for vessel classification (k), then 

the proportion in each expenditure category from each survey (s) can be represented as 

i

Rks

C P iks

iks = (7) 

Second, three of the vessel classifications shown in Table 1 (crabber, sablefish fixed gear, and 

other groundfish fixed gear), have survey results from more than one cost earnings survey. For 

these categories a weighting mechanism was used to combine the results from the surveys. 

Total West Coast landings for each of the vessel classifications were converted to 

constant 2006 dollars using the Producer Price Index for unprocessed and packaged fish. West 

Coast landings by vessel classification (k) from each survey (s) is represented by WCks. The 

weights to combine the results of the three different surveys are given by 

Processors 

Final 

consumers 

Intermediate 

demand other 

than processing 

Final 

consumers 

Intermediate 

demand 

Exports 

33
∑

S

s

ks

ks

WC

WC (8) 

Altogether, the survey portion of the production function for all vessel classifications (k) 

and all expenditure categories (i) is given by 

∑

S

s

ks

ks

iks

WC

WC P (9) 

There are some vessel classifications that have no data from any of the NWFSC cost 

earnings surveys. These include mother ship catcher/processors, Alaska fishery vessels, small 

groundfish trawlers, pelagic netters, migratory netters, migratory liners, shrimpers, salmon 

netters, other netters, lobster vessels, and diver vessels. For all but small groundfish trawlers, 

these categories incorporate the survey data in the form of a weighted average production 

function. The production functions for all of the covered classifications were weighted based on 

their respective West Coast landings and included in this weighted average production function. 

Small groundfish trawlers are assumed to have the same production function as large groundfish 

trawlers. As additional data become available, specific production functions for these categories 

will be developed and incorporated into IO-PAC. 

Moorage 

Moorage was calculated by converting the moorage cost data presented in Table 2 to 

dollars per foot, multiplying dollars per foot by the average length of vessel by classification and 

survey population, and weighting the moorage expenditures of the different survey populations 

in the same manner described above. Annual dollars per foot from Table 2 for the West Coast 

range from $40.40 to $47.30, with an overall average of $44.90 in 2009 dollars. This per-foot 

amount was converted to 2006 dollars by using the consumer price index and equals $41.80. 

Landings Taxes 

Average federal taxes by vessel classification were estimated by multiplying the average 

value of landings by species and state within each vessel classification by the federal tax rates 

shown in Table 3. The federal tax rates are applied by species and state to all of the average 

landings made in each of the vessel classifications. The tax rate multiplied by the average 

landings by species is borne 100% by harvesters. 

Average Washington taxes were estimated in two parts. First, Table 10 indicates that 

Washington commercial fishermen were responsible for 12.6% of landings taxes collections in 

2006. Hence it is assumed that for all vessel classifications, 12.6% of average landings by 

species is sold directly to the public. On 12.6% of average landings by vessel classification by 

species, the full tax rate is assumed to be paid by harvesters. Second, because of the tax shifting 

arrangement in Washington, harvesters are estimated to pay half of the tax rate displayed in 

34
35

at 

d, these 

 

Table 3 on the remaining 87.4% of average landings by species. Total average taxes by vessel 

classification are created by summing the direct to consumer and tax shifted components. 

Average Oregon taxes were estimated by applying the tax rates by species in Table 3 to 

12.6% of the vessel landings for each classification. Oregon is assumed to have the same 

proportion of fish sold directly to consumers as Washington. It is possible to segment sales by 

species for commercial fishing harvesters holding Limited Fish Seller Licenses in Oregon. 

These licenses permit harvesters to sell directly to the public off their vessels. Sales by 

harvesters with these licenses are a much smaller proportion of all landings than 12.6%. It is 

reported to be closer to 1%.12 However, some harvesters have Wholesale Dealer Licenses, as 

they are required for harvesters who wish to sell landings directly to consumers and retail 

businesses from a location other than their vessel. The amount of landings sold in this manner is 

unknown, which necessitated an assumption that the flow of fish in Oregon is similar to 

Washington. 

For each vessel classification, average California taxes were estimated by applying the 

tax rates by species in Table 3 to 2% of trawl gear landings and 21% of fixed gear landings. 

Approximately 2% of trawl caught groundfish and 21% of fixed gear groundfish bypassed 

wholesalers and processors and were purchased by final consumers in 2006.13 These 

percentages are applied to all commodities in the model. The groundfish focus of the model 

this time supports this assumption. As improved data for other species groups are adde

proportions will be adjusted. 

The West Coast model includes an additional step that is not performed on any of the 

models for smaller study areas. For each vessel classification, it sums the federal and state taxes 

that were calculated separately, then divides the sum by total West Coast landings. This 

provides the percent of total revenue for each vessel classification that is used to pay landings 

taxes. 

Table 11 presents the final production functions included in the West Coast model. The 

state and port-level models differ slightly in the moorage and tax component, but the production 

functions for the other categories are identical. The production function for other greater than 

$15,000 is not shown due to confidentiality restrictions. The expenditure categories shown in 

Table 11 must be mapped into IMPLAN commodity codes for inclusion in the model. The 

mapping of the expenditure categories in Table 11 into IMPLAN commodity codes is presented 

in detail in Appendix A. 

4.6. Processor and Wholesale Seafood Dealer Production Functions 

The processor production function is the default IMPLAN production function for 

seafood product preparation and packaging (Sector 71).

12 Based on data of landings by license type in 2006 supplied by M. Grooms, ODFW, Salem. 13 D. Hansen, who worked with CDFG on development of the California Ocean Fish Harvester Economic (COFHE) 

model, provided information on the proportion of groundfish sales made directly to consumers. These numbers as 

direct sales to the public in 2006 were confirmed by T. Tillman, CDFG, Woodland. Pers. commun., 23 June 2009. 
Table 11. Percentage distribution of commercial fishing production functions by expenditure categories. 

Expenditure categories (table continued horizontally below) 

Mother ship 

catcher/ 

processor Alaska 

Pacific 

whiting 

trawler 

Large 

groundfish 

trawler 

Small 

groundfish 

trawler 

Sablefish 

fixed 

gear 

Other 

groundfish 

fixed gear 

Migratory 

liner 

Captain — — 14.3 18.9 18.9 18.2 30.1 20.1 Crew — — 18.4 20.9 20.9 33.6 18.1 20.2 Fuel, lubricants — — 12.0 12.4 12.4 4.5 12.0 9.3 

Food, crew provisions — — 1.4 1.1 1.1 1.6 2.8 1.8 Ice — — 0.1 1.9 1.9 0.3 0.7 1.0 

Bait — — 0.4 1.2 1.2 4.5 5.6 2.4 

Repair and maintenance: vessel, gear, equipment 

— — 19.8 18.2 18.2 8.0 17.2 15.5 

Insurance — — * 5.7 5.7 2.2 1.0 3.8 

Interest and financial services — — * 1.7 1.7 0.9 1.0 1.1 Purchases of permits — — 1.0 1.8 1.8 0.6 0.5 1.1 

Leasing of permits — — 0.0 1.2 1.2 5.8 0.1 1.0 Moorage — — 0.3 0.8 0.8 1.0 2.0 1.3 

Landings taxes — — 3.7 4.1 1.1 0.9 0.6 2.0 Other miscellaneous — — 5.0 5.0 5.0 5.0 5.0 5.0 

Proprietary income — — 13.9 5.2 8.2 12.9 3.4 14.5 

36

Total (%) 100.0 100.0 100.0 100.0 100.0 100.0 

Expenditure categories (column list repeated from above) Shrimper Crabber 

Salmon 

troller 

Salmon 

netter 

Other netter Lobster Diver 

Other 

>15,000 

Other 

<15,000 

Captain 20.1 17.3 30.2 20.1 20.1 20.1 20.1 * 10.8 Crew 20.2 22.7 12.1 20.2 20.2 20.2 20.2 * 1.9 

Fuel, lubricants 9.3 5.7 11.6 9.3 9.3 9.3 9.3 * 11.1 

Food, crew provisions 1.8 1.1 4.0 1.8 1.8 1.8 1.8 * 2.1 

Ice 1.0 0.5 1.8 1.0 1.0 1.0 1.0 * 0.7 

Bait 2.4 3.1 1.4 2.4 2.4 2.4 2.4 * 0.3 

Repair and maintenance: vessel, gear, and equipment 

15.5 12.0 20.3 15.5 15.5 15.5 15.5 * 9.5 

Insurance 3.8 3.1 2.7 3.8 3.8 3.8 3.8 * 1.2 

Interest and financial services 1.1 0.5 1.4 1.1 1.1 1.1 1.1 * 0.5 

Purchases of permits 1.1 0.7 1.5 1.1 1.1 1.1 1.1 * 0.8 

Leasing of permits 1.0 0.4 0.0 1.0 1.0 1.0 1.0 * 0.0 

Moorage 1.3 0.7 3.1 1.3 1.3 1.3 1.3 * 3.3 

Landings taxes 2.0 1.0 1.3 2.0 2.0 2.0 2.0 * 0.7 Other miscellaneous 5.0 5.0 5.0 5.0 5.0 5.0 5.0 * 5.0 

Proprietary income 14.5 26.2 3.6 14.5 14.5 14.5 14.5 * 52.1 

Total (%) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

*Percentages not shown due to confidentiality restrictions. 
Wholesale seafood dealer production functions are assumed to equal those developed by 

Kirkley (2004), and subsequently used by Steinback and Thunberg (2006). This production 

function is presented in Table 12. The mapping of the expenditure categories included in the 

production function into IMPLAN commodity codes is presented in detail in Appendix A. 

4.7. Sales 

Baseline sales for all but two of the vessel classifications are derived from PacFIN fish 

ticket data. There are no landings data for Alaska fisheries vessels and mother ship 

catcher/processors contained in the model. 

Baseline sales for the wholesale seafood dealer sector are estimated by margining the 

30% of harvested fish that is estimated to flow to wholesale seafood dealers. IO-PAC utilizes a 

16% markup margin, which is consistent with the margin from the 1997 Economic Census.14 

Table 12. Seafood wholesale dealer production function. 

Expenditure category

Seafood wholesale dealer (%) 

Ice 2.80 

Packaging, boxes 2.70 

Shipping 4.10 

Storage 14.70 

Advertising 4.00 

Rent 6.80 

Repair and maintenance, building 6.90 

Vehicle 4.10 

Utilities, electric 1.37 

Utilities, gas 1.37 

Utilities, telephone 1.37 

Insurance 4.10 

Professional fees 0.70 

Building principal payment 4.00 

Interest payment, building 1.40 

Bank service charge 0.08 

Taxes 2.12 

Employee compensation 33.35 

Proprietary income 4.05 

Total 100.00 

 

14 The most recently published markup margin for fish and seafood wholesalers (NAICS code 4226) is from the 

1997 Economic Census. It is contained in Table 7, Gross margin and its components for merchant wholesalers for 

the United States: 1997. This table is available for the 2002 Economic Census, however, the markup margin is not 

published for fish and seafood wholesalers due to disclosure considerations. Evidence of the approximate range of 

the markup margin in 2002 can be calculated with the census’s preliminary tables, and the margin published in 1997 

is within this range. For additional information, contact J. Leonard, NWFSC, 2725 Montlake Blvd. E., Seattle, WA 

98112. 

37
Total sales are entered as the margin only, which excludes the costs of raw fish. This practice is 

analogous to the default IMPLAN treatment of the wholesale trade sector. 

Baseline sales for the seafood processing sector are those contained in the default 

IMPLAN model for seafood product preparation and packaging (Sector 71). 

4.8. Employment 

In Oregon and California, employment estimates for the vessel classifications are made 

by multiplying the weighted average number of crew plus captain by the number of unique 

vessel IDs. In Washington, the ZZZ IDs necessitated an adjustment to the employment 

estimates. First, employment estimates for the vessel classifications are made by multiplying the 

weighted average number of crew plus captain by the number of unique non-ZZZ vessel IDs. 

The non-ZZZ employment estimates are then inflated to adjust for the ZZZ landings. It is 

assumed employees on vessels with ZZZ IDs are of equal productivity as those on vessels 

without a ZZZ ID. Thus the number of ZZZ employees will be the same share of total 

employees as the value of ZZZ landings is of total landings. 

The cost earnings surveys capture the average number of crew members on each vessel 

not including the captain while performing five different activities: trawling, longlining, 

shrimping, crabbing, and trolling. IO-PAC uses the average number of crew for each vessel 

classification that best corresponds to the primary activity of the classification. For example, the 

applicable average number of crew for large groundfish trawlers is assumed to be the average 

number of crew while the vessel is engaged in trawling. 

For the three vessel classifications that are covered by more than one cost earnings 

survey, a weighted average is used. The weighting scheme follows the approach used to weight 

the different elements of the production function. Essentially, for each vessel classification, the 

weights are comprised of the share of total inflation-adjusted West Coast landings attributable to 

vessels covered by the respective surveys. 

Employment for wholesale seafood dealers is calculated by dividing the portion of total 

value-added paid to employees by the average wage paid to fish and seafood merchant 

wholesalers (NAICS Code 42446) from County Business Pattern data for 2006.15 Average 

earnings per employee in Washington and California were $42,300 and $36,051, respectively. 

Average earnings per employee were not disclosed for Oregon, so the average for the West Coast 

was created by using the weighted mean for Washington and California, where the weights are 

the proportion of total employment in Washington and California that exists in each respective 

state. The number of paid employees was 1,015 in Washington and 4,429 in California, so the 

weighted average earnings per employee is $36,057.16

 

15 See Census Bureau county business patterns, online at http://www.census.gov/econ/cbp/index.html. 16 Because earnings per employee was not reported for Oregon, the Oregon models utilize the $36,057 weighted 

average earnings. 

38
5. Model Construction 

The following discussion details the steps used to construct the model in the IMPLAN 

system. Much of this discussion is drawn from Steinback and Thunberg (2006). IMPLAN 

contains more than 60 Microsoft Access tables. Table 13 lists the underlying data tables in the 

IMPLAN system and a short descriptor of the type of data contained therein. The construction 

of IO-PAC entailed modifying 14 of these tables, as noted in Table 13. 

The modification procedure consists of the following steps. First, Microsoft Excel 

worksheets that mirror the layout of the Access tables that needed to be modified were created. 

Second, all of the new data necessary to modify the Access tables were entered into the Excel 

worksheets. Third, the data were copied from the Excel worksheets and pasted at the bottom of 

the relevant Access table. Lastly, the Access tables were sorted based on the necessary variables 

to maintain the records format. 

5.1. Model Construction Steps 

These nine steps describe the creation of the IO-PAC model. The steps are repeated for 

each geographic area displayed in Figure 1. 

1. A default West Coast region model was created with IMPLAN software. 

2. The default model was opened using Access 2003. 

3. Three of the U.S. tables and the Observed RPCs table were then deleted. This step was 

necessary because all IMPLAN Pro models share the following five tables: U.S. 

Absorption Table, U.S. Absorption Totals, U.S. Byproducts Table, Observed RPCs, and 

Margin Codes. Deletion of these tables breaks the link so that any subsequent changes 

made in Access will not affect other IMPLAN models. No changes were made to the 

Margin Codes table so it was not necessary to remove the link to that table. 

4. The deleted tables (the three U.S. tables and the Observed RPCs table) were then 

replaced with the same tables contained in the 2005 IMPLAN structural matrix file 

06NAT509.IMS through the import feature in Access. 

5. For each of the 14 tables that needed to be modified, Excel worksheets were created that 

mirror the layout of the tables in Access. 

6. Data in these 14 tables were modified to better reflect the sector linkages among 

fisheries-related industries. 

7. After the new data for 14 tables were created in Excel, the data were copied from the 

Excel worksheets and pasted at the bottom of the relevant Access table. 

8. The Access tables were resorted to follow the original format. 

39
Table 13. IMPLAN tables (adapted from Steinback and Thunberg 2006). 

Table name Description 

*Industry/Commodity Codes 

*Type Codes 

Codes (modified) 

Margins Codes Codes 

*U.S. Absorption 

*U.S. Absorption Totals 

*U.S. Byproducts 

*SACommodity Sales 

*SAEmployment 

*SAFinal Demands 

*SAForeign Exports 

*SAOutput 

*SAValue Added 

Raw input data (modified) 

SA Transfers Raw input study area data 

*Observed RPCs 

*RPC Methods 

Raw input data (modified) 

Margins 

*Deflators 

Raw input data 

General Information 

Model Specs. 

Multiplier Specs. 

Model-building information 

SARatios Ratios for impact and multiplier calculations 

IMCommodity Transactions 

IMEvents 

IMFactor Transactions 

IMGroups 

IMIndustry Transactions 

IMInstitutions Transactions 

IMMargins 

IMProjects 

Impact report data (empty before impact analysis) 

Regional Absorption 

Regional Byproducts 

Regional Commodity Balances 

Regional Direct Institutional Requirements 

Regional Factor Balances 

Regional Industry Balances 

Regional Institution Balances 

Regional Institution Demand 

Regional IxI 

Regional Market Shares 

Regional Multipliers Induced 

Regional Multipliers Type I 

Regional SAM Balances 

Regional SAM Balances Aggregated 

Regional SAM Balances Industry Detail 

Regional SAM Balances IxI 

Regional SAM Balances IxI Industry Detail 

Regional SAM Distribution 

Regional Value Added Coefficients 

Output/report data for regional I-O model (empty before impact analysis) 

rptEC Multipliers 

rptEmployment Multipliers 

rptIBT Multipliers 

rptOPTI Multipliers 

rptOutput Multipliers 

rptPersonal Income Multipliers 

rptPropInc Multipliers 

rptTotal VA Multipliers 

Output reports 

rptSAFinal Demands Data from SAFinal Demands and SAForeign Exports (modified) 

rptSAIndustry Data Data from SAOutput, SAEmployment & SAValue Added (modified) 

SAM Rollup SAM report data 

Tax Impacts Tax report data 

Type Code Rollup Type code report data 

CGE Account Output data for computable general equilibrium models 

*The construction of IO-PAC entailed modifying the table.

40
9. The modified model was then opened in IMPLAN; the model was reconstructed and 

multipliers were reestimated. IMPLAN will not recognize changes made to the 

underlying data tables unless the model is reconstructed using the updated data. 

5.2. IMPLAN Table Adjustments 

The following provides a more detailed discussion of modifications to certain Access 

tables. 

Industry and Commodity Codes 

This table contains unique code numbers for industries and commodities, which share the 

same name and number in an IMPLAN model. Modifications included adding 21 different 

industry classifications: 19 different vessel categories, a bait ship category, and a wholesale 

seafood dealer category. Additionally, 33 different commodity sectors were added: 32 different 

gear/species commodity sectors and a single sector for bait. These industry sectors identify the 

19 different vessel classification categories developed by Radtke and Davis (2000). The industry 

and commodity sectors that are added along with their IMPLAN code numbers are displayed in 

Table 4 and Table 5. 

Type Codes 

This table contains coding information on all transaction types in the data sets. For it we 

added the 54 industry and commodity code designations discussed above and the associated 54 

SAM commodity codes. Transaction codes associated with factors, households, institutions, 

transfers, employment, output, and trade remained the same. 

U.S. Absorption 

This table contains the U.S. absorption matrix which, in IO terminology, is the coefficient 

form of the Use Table, that contains the dollar value of goods and services purchased by each 

industry for use in its production process. Essentially, the U.S. absorption matrix contains each 

industry’s production function. We added 1,720 rows of data that contained the production 

functions of each of the 19 fisheries-related vessel categories, the bait ship category, and the 

wholesale seafood dealer category that were added to the model. 

U.S. Absorption Totals 

This table contains the sum of the absorption coefficients for each industry sector. We 

added the appropriate absorption coefficients for the 21 new industry sectors in the model. The 

sum of the coefficients from each sector in the U.S. Absorption table must match the coefficients 

in the U.S. Absorption Totals table. 

U.S. Byproducts 

This table contains estimates of the proportions of each commodity that an industry 

produces. In IO terminology, it is the coefficient form of the Make Table derived by dividing 

each element by the table row totals. This table contains the value of each good or service 

41
produced by each industry. A single industry can produce more than one category of goods and 

services and this information is contained in the Make Table. For the U.S. Byproducts table, we 

added the commodity proportions for the 21 industries added to the model. The commodities 

produced by these industries include the 32 gear and species commodities and the bait 

commodity. 

SACommodity Sales 

This table shows sales of commodities by households and institutions in the study area. 

We assumed that no households or institutions sold any of the 33 commodities that were added. 

We also assumed that there was no institutional (federal and state governments) production in 

any of the industries or commodities added to the model and that there would be no inventory 

additions. The table was modified by adding rows of zeros for the institutions and inventory 

additions for each of the industries and commodities added. 

SAEmployment 

This table delineates average annual jobs for each industry in the study area. Jobs are 

measured in terms of both full-time and part-time workers combined. Employment estimates for 

all industry categories added to the model were included here. 

SAFinal Demands 

This table consists of purchases of commodities for final consumption by households and 

institutions. The objective of modifying this table is to assign final demands for each of the 

commodities added to the model. This was accomplished by using information about final 

demand for the default fishing sector contained in IMPLAN. Final demand for the default 

fishing sector is apportioned among households of different incomes, government entities, and 

inventory. These are referred to as data type codes in IMPLAN. We assume that the demand for 

the new species and gear commodities entered into the model will follow the same final demand 

distribution as the default fishing sector (sector 16). Demand totals for each of the type codes 

(households earning less than $10,000, $15,000–$25,000, federal nondefense, etc.) are generated 

by multiplying the proportion of default fishing sector demand (sector 16) attributable to the 

different types by the total production of the new commodities entered into the model. Since the 

RPCs for the newly added sectors are set to zero, effectively there is no distribution of fish 

harvested to the final demand categories in the study area. IMPLAN will fulfill demand with 

imports to the study area.

SAForeign Exports 

This table shows demand made for goods and services by consumers and industries 

outside the United States. For it we estimated exports of the 32 commodities added to the model 

by assuming the same proportion of each would be exported as appears for the default fishing 

sector in IMPLAN. 

42
SAOutput 

This table is a vector of output values in millions of dollars that represents an industry’s 

total production. There is a single value for each of the 21 industrial sectors entered into the 

model. 

SAValue Added 

This table details payments made and received by each industry to employee 

compensation (wage and salary payments, insurance, retirement, etc.), proprietary income (all 

income received), other property type income (payments from interest, rents, royalties, 

dividends, corporate profits, etc.), and indirect business taxes (primarily excise and sales taxes). 

The value-added transactions associated with the 21 industrial sectors were added to the table. 

Observed RPCs 

This table contains forced RPC values for all states in the model. We added the 21 

industrial sectors to the table and included a RPC value of 0 for all sectors except the bait sector, 

which was assigned an RPC of 1. We also added a RPC of 0 for the default IMPLAN fishing 

sector 16 and default seafood processing sector 71. 

RPC Methods 

This table contains information for creation of the RPCs. We added each of the newly 

created industry and commodities to the table, and set the method variable of each added sector 

to “observed.” Additionally, we changed the default seafood processing sector and default fish 

harvesting sector method from “regress” to “observed.” 

Deflator1 

This table contains deflators that account for relative price changes over time. The 

IMPLAN deflators are derived from the U.S. Bureau of Labor Statistics Growth Model. The 

2006 IMPLAN database contains deflators from 1977 to 2020 for each commodity in the model. 

We replicated the deflators IMPLAN contains for the default fish harvesting sector for all of the 

newly created sectors except wholesale seafood dealers, for which we used the deflator for the 

default wholesale trade sector in IMPLAN. 

43
6. Impact Estimation 

6.1. Estimation Procedure 

IO-PAC can be used to assess the impact of a given fishery management action when an 

externally derived, exogenous assessment of how the action will affect the gross output of 

industries or commodities that are included in the model is available. With an exogenous 

estimate of the effect of a management action on fish harvest, IO-PAC will estimate the 

backward-linked impacts of the action on the economy. 

Entering an exogenous impact on sales by fish harvesters is the first step in calculating an 

impact. However, doing so will have no impact on the businesses that rely on the supply of fish 

as input in production, such as seafood processors. Since the RPC for all fishing related sectors 

has been set to zero, all supply of fish to these establishments will be sourced from outside the 

study area in the model. If the backward-linked impact of the fishery management action on 

seafood processors and wholesale seafood dealers is included, estimated changes in sales for 

these sectors must also be entered into the model. 

With an exogenous estimate of a change in dollar value of sales by harvesters, the 

estimated change in sales of wholesale seafood dealers in the study area is made by utilizing the 

product flow and wholesale dealer markup margin assumptions discussed in subsections 4.6 and 

4.7 above. It is assumed that 30% of harvested fish in the study area flow to wholesale seafood 

dealers and that their markup margin is 16%. Because the wholesale seafood dealers are treated 

as margin sectors, the cost of fish purchased by wholesalers is excluded from estimated sales 

impacts. If ΔLk represents the change in total fish landings among vessel classification (k) within 

the study area, then the change in sales for wholesale seafood dealers in the study area (ΔWS) is 

given by 

)3.0( 84.0

)3.0(

⎟

⎠

⎞ ⎜

⎝

⎛ Δ−

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ Δ

=Δ ∑

∑ K

k

k

K

k

k

L

L

WS (10) 

Estimated sales changes for seafood processors are made by using product flow and 

markup margin information contained in IMPLAN for the default seafood processing sector (71). 

IO-PAC assumes that landings from the fish harvesting sectors that are added to the model flow 

to seafood processors in the same proportion as the default IMPLAN flow of sales from the 

default fish harvesting sector (16) to the default processing sector (71). This value can be 

determined by constructing a default IMPLAN model for the study area of interest, then 

examining the commodity balance sheet for the default commercial fishing sector. In 2006 the 

commodity balance sheet indicated that seafood processors purchased approximately 32% of the 

sales produced by the commercial fishing sector on the West Coast. In IO-PAC it is assumed 

44
that seafood processors will purchase the same share of fish landings directly from the harvesting 

sectors that were created. 

Fish landings that are purchased by the processing sector in each study area are converted 

into revenue changes by applying the margins derived from the production function for 

processors in the area. For the West Coast, the margin for processors in 2006 was 70%. This 

value can be determined by constructing a default IMPLAN model for the study area, then 

examining the industry balance sheet for the default seafood processing sector. These producer 

values are then entered as the change in direct sales for the seafood processing sector. For each 

study area, if (p) represents the proportion of landings purchased by the default seafood 

processing sector and (m) represents the margin among seafood processors, then the change in 

sales for seafood processors (ΔPS) is given by 

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡

−

⎟

⎠

⎞ ⎜

⎝

⎛ Δ

=Δ

∑

)1(

)(

m

pL

PS

K

k

k

 (11) 

The total effect on economic activity in the study area is derived by simultaneously 

multiplying the estimated exogenous gross output changes for the harvesting sectors, wholesale 

seafood dealers, and seafood processing sectors by their corresponding model-generated 

multipliers. This will capture the backward-linked effects associated with a change in 

commercial fishing harvest within the study area. This is accomplished by entering all three 

values in the IMPLAN impact analysis window. 

6.2. Hypothetical Examples 

Two hypothetical reductions in harvest are used to illustrate the outputs produced by IOPAC. Scenario one will illustrate the impact of a reduction in sales of a particular vessel 

classification. Scenario two will illustrate the impact of a reduction in sales for a particular 

commodity (species/gear type). 

For scenario one, assume that the fishery management action will result in a $500,000 

decline in total ex-vessel West Coast landings for sablefish fixed gear vessels. If $500,000 is the 

change in total ex-vessel revenue on the West Coast, then the decline in sales of wholesale 

seafood dealers is $28,571 and the decline in sales for seafood processors is $756,412. All three 

of these effects are entered on the main impact analysis window in IMPLAN, then the impact 

results are analyzed. Table 14 displays the resulting effects on total output, income, and 

employment. The results are aggregated at the two digit NAICS code level for all sectors that 

were not added to the default IMPLAN model. The added sectors appear individually. 

For scenario two, assume that the fishery management action will result in a $500,000 

decline in total ex-vessel West Coast landings for sablefish caught using fixed gear. This is the 

commodity classification, not the vessel classification. Vessels of numerous classifications have 

sablefish landings while using fixed gear. If $500,000 is the reduction in total ex-vessel revenue 

of the sablefish fixed gear commodity on the West Coast, then the decline in sales of wholesale 

45
Table 14. Impact of reduced harvest among sablefish fixed gear vessels. 

Aggregated output impact report (2009 dollars) 

NAICS code and industry Direct Indirect Induced Total

11 Ag, forestry, fish, and hunting 0 –9,189 –4,005 –13,194

21 Mining 0 –2,229 –2,112 –4,341

22 Utilities 0 –8,096 –9,876 –17,972

23 Construction 0 –7,388 –10,325 –17,713

31–33 Manufacturing –530,932 –38,810 –72,538 –642,279

42 Wholesale trade 0 –93,158 –33,725 –126,883

48–49 Transportation and warehousing 0 –23,552 –15,870 –39,421

44–45 Retail trade 0 –18,719 –65,957 –84,676

51 Information 0 –9,329 –21,692 –31,021

52 Finance and insurance 0 –28,451 –51,503 –79,954

53 Real estate and rental 0 –15,959 –30,963 –46,922

54 Professional-scientific and tech services 0 –30,340 –29,408 –59,748

55 Management of companies 0 –33,378 –7,393 –40,771

56 Administrative and waste services 0 –10,766 –13,325 –24,091

61 Educational services 0 –167 –8,892 –9,059

62 Health and social services 0 –7 –79,517 –79,524

71 Arts-entertainment and recreation 0 –7,256 –8,416 –15,672

72 Accommodation and food services 0 –4,139 -30,893 –35,032

81 Other services 0 –7,053 –23,247 –30,300

92 Government and non-NAICS 0 –5,298 –110,492 –115,790

Sablefish fixed gear –500,000 0 0 –500,000

Bait ship 0 –22,309 0 –22,309

Wholesale seafood –28,571 0 0 –28,571

Total –1,059,503 –375,592 –630,148 –2,065,243

seafood dealers and processors is the same as scenario one. All three of these effects are entered 

on the main impact analysis window in IMPLAN, then the impact results are analyzed. Table 15 

displays the resulting effects on total output, income, and employment. The major difference in 

the two scenarios is that numerous vessel classifications are affected in the commodity run. The 

effects are still the greatest for vessels classified as sablefish fixed gear because they have the 

largest landings of this commodity, but sizable effects are also seen for vessels classified as 

crabbers in the model. Which approach one should use depends on the specifics of the issue 

being analyzed. 

46
Table 14 continued horizontally. Impact of reduced harvest among sablefish fixed gear vessels. 

NAICS code and industry Aggregated income impact report (2009 dollars)

(column list repeated from previous page) Direct Indirect Induced Total

11 Ag, forestry, fish, and hunting 0 –1,503 –1,417 –2,919

21 Mining 0 –1,160 –1,098 –2,258

22 Utilities 0 –3,613 –5,195 –8,808

23 Construction 0 –3,431 –5,526 –8,957

31–33 Manufacturing –105,975 –7,276 –16,613 –129,864

42 Wholesale trade 0 –49,052 –17,758 –66,810

48–49 Transportation and warehousing 0 –13,888 –8,489 –22,378

44–45 Retail trade 0 –10,078 –34,885 –44,961

51 Information 0 –4,282 –9,862 –14,144

52 Finance and insurance 0 –16,076 –27,855 –43,930

53 Real estate and rental 0 –8,674 –17,159 –25,833

54 Professional-scientific and tech services 0 –15,844 –16,241 –32,084

55 Management of companies 0 –19,737 –4,371 –24,108

56 Administrative and waste services 0 –6,528 –8,181 –14,710

61 Educational services 0 –95 –5,315 –5,410

62 Health and social services 0 –4 –50,076 –50,080

71 Arts-entertainment and recreation 0 –3,852 –4,693 –8,545

72 Accommodation and food services 0 –2,141 –14,488 –16,628

81 Other services 0 –3,416 –11,813 –15,229

92 Government and non-NAICS 0 –2,797 –89,935 –92,732

Sablefish fixed gear –356,014 0 0 –356,014

Bait ship 0 -8,709 0 –8,709

Wholesale seafood –11,828 0 0 –11,828

Total –473,817 –182,152 –350,970 –1,006,939

47
Table 14 continued horizontally. Impact of reduced harvest among sablefish fixed gear vessels. 

Aggregated employment impact report 

NAICS code and industry (full and part-time) 

(column list repeated from previous page) Direct Indirect Induced Total

11 Ag, forestry, fish, and hunting 0 –0.2 0 –0.2

21 Mining 0 0 0 0

22 Utilities 0 0 0 0

23 Construction 0 –0.1 –0.1 –0.1

31–33 Manufacturing –1.7 –0.1 –0.2 –1.9

42 Wholesale trade 0 –0.5 –0.2 –0.6

48–49 Transportation and warehousing 0 –0.2 –0.1 –0.3

44–45 Retail trade 0 –0.2 –0.8 –1.0

51 Information 0 0 –0.1 –0.1

52 Finance and insurance 0 –0.1 –0.2 –0.3

53 Real estate and rental 0 –0.1 –0.2 –0.2

54 Professional-scientific and tech services 0 –0.2 –0.2 –0.4

55 Management of companies 0 –0.1 0 –0.2

56 Administrative and waste services 0 –0.2 –0.2 –0.4

61 Educational services 0 0 –0.2 –0.2

62 Health and social services 0 0 –0.8 –0.8

71 Arts-entertainment and recreation 0 –0.1 –0.1 –0.2

72 Accommodation and food services 0 –0.1 –0.5 –0.5

81 Other services 0 –0.1 –0.4 –0.4

92 Government and non-NAICS 0 0 –0.6 –0.6

Sablefish fixed gear –14.2 0 0 –14.2

Bait ship 0 0 0 0

Wholesale seafood –0.2 0 0 –0.2

Total –16.1 –2.1 –4.7 –23.0

48
Table 15. Impact of reduced sablefish harvest using fixed gear (commodity scenario). 

Aggregated output impact report (2009 dollars) 

NAICS code and industry Direct Indirect Induced Total

11 Ag, forestry, fish, and hunting 0 –9,185 –3,904 –13,089

21 Mining 0 –2,438 –2,061 –4,499

22 Utilities 0 –8,137 –9,634 –17,771

23 Construction 0 –6,999 –10,205 –17,203

31–33 Manufacturing –530,932 –41,488 –70,745 –643,166

42 Wholesale trade 0 –95,544 –32,872 –128,416

48–49 Transportation and warehousing 0 –23,531 –15,477 –39,008

44–45 Retail trade 0 –20,302 –64,249 –84,551

51 Information 0 –9,437 –21,147 –30,584

52 Finance and insurance 0 –29,431 –50,193 –79,625

53 Real estate and rental 0 –16,116 –30,182 –46,299

54 Professional-scientific and tech services 0 –30,542 –28,696 –59,239

55 Management of companies 0 –33,529 –7,205 –40,734

56 Administrative and waste services 0 –10,877 –13,004 –23,882

61 Educational services 0 –170 –8,663 –8,833

62 Health and social services 0 –7 –77,454 –77,461

71 Arts-entertainment and recreation 0 –7,310 –8,199 –15,508

72 Accommodation and food services 0 –4,170 –30,104 –34,274

81 Other services 0 –7,081 –22,659 –29,739

92 Government and non-NAICS 0 –5,317 –108,418 –113,735

Pacific whiting trawler –4,428 0 0 –4,428

Large groundfish trawler –920 0 0 –920

Small groundfish trawler –1,219 0 0 –1,219

Sablefish fixed gear –253,732 0 0 –253,732

Other groundfish fixed gear –21,177 0 0 –21,177

Pelagic netter –1,302 0 0 –1,302

Migratory liner –5,266 0 0 –5,266

Shrimper –721 0 0 –721

Crabber –182,366 0 0 –182,366

Salmon troller –10,423 0 0 –10,423

Salmon netter –369 0 0 –369

Lobster vessel –565 0 0 –565

Other, more than $15,000 –3,926 0 0 –3,926

Other, less than $15,000 –13,584 0 0 –13,584

Bait ship 0 –18,839 0 –18,839

Wholesale seafood –28,571 0 0 –28,571

Total –1,059,503 –380,451 –615,073 –2,055,027

49
Table 15 continued horizontally. Impact of reduced sablefish harvest using fixed gear 

(commodity scenario). 

NAICS code and industry Aggregated income impact report (2009 dollars) 

(column list repeated from previous page) Direct Indirect Induced Total

11 Ag, forestry, fish and hunting 0 –1,502 –1,381 –2,882

21 Mining 0 –1,269 –1,072 –2,340

22 Utilities 0 –3,632 –5,068 –8,701

23 Construction 0 –3,252 –5,465 –8,718

31–33 Manufacturing –105,975 –7,629 –16,200 –129,804

42 Wholesale trade 0 –50,309 –17,308 –67,617

48–49 Transportation and warehousing 0 –13,859 –8,280 –22,140

44–45 Retail trade 0 –10,929 –33,981 –44,911

51 Information 0 –4,331 –9,615 –13,946

52 Finance and insurance 0 –16,439 –27,147 –43,586

53 Real estate and rental 0 –8,763 –16,725 –25,488

54 Professional-scientific and tech services 0 –15,954 –15,850 –31,804

55 Management of companies 0 –19,825 –4,260 –24,086

56 Administrative and waste services 0 –6,597 –7,985 –14,583

61 Educational services 0 –97 –5,178 –5,275

62 Health and social services 0 –4 –48,777 –48,781

71 Arts-entertainment and recreation 0 –3,881 –4,572 –8,453

72 Accommodation and food services 0 –2,157 –14,118 –16,274

81 Other services 0 –3,430 –11,514 –14,943

92 Government and non-NAICS 0 –2,809 –88,384 –91,194

Pacific whiting trawler –2,101 0 0 –2,101

Large groundfish trawler –442 0 0 –442

Small groundfish trawler –620 0 0 –620

Sablefish fixed gear –180,664 0 0 –180,664

Other groundfish fixed gear –11,028 0 0 –11,028

Pelagic netter –741 0 0 –741

Migratory liner –2,997 0 0 –2,997

Shrimper –411 0 0 –411

Crabber –122,782 0 0 –122,782

Salmon troller –4,947 0 0 –4,947

Salmon netter –210 0 0 –210

Lobster vessel –322 0 0 –322

Other, more than $15,000 –1,433 0 0 –1,433

Other, less than $15,000 –8,909 0 0 –8,909

Bait ship 0 –7,354 0 –7,354

Wholesale seafood –11,828 0 0 –11,828

Total –455,411 –184,024 –342,881 –982,317

50
Table 15 continued horizontally. Impact of reduced sablefish harvest using fixed gear 

(commodity scenario). 

Aggregated employment impact report 

NAICS code and industry (full and part-time) 

(column list repeated from previous page) Direct Indirect Induced Total

11 Ag, forestry, fish and hunting 0 –0.2 0 –0.2

21 Mining 0 0 0 0

22 Utilities 0 0 0 0

23 Construction 0 0 –0.1 –0.1

31–33 Manufacturing –1.7 –0.1 –0.1 –1.9

42 Wholesale trade 0 –0.5 –0.2 –0.6

48–49 Transportation and warehousing 0 –0.2 –0.1 –0.3

44–45 Retail trade 0 –0.2 –0.7 –1.0

51 Information 0 0 –0.1 –0.1

52 Finance and insurance 0 –0.1 –0.2 –0.3

53 Real estate and rental 0 –0.1 –0.1 –0.2

54 Professional-scientific and tech services 0 –0.2 –0.2 –0.4

55 Management of companies 0 –0.1 0 –0.2

56 Administrative and waste services 0 –0.2 –0.2 –0.4

61 Educational services 0 0 –0.1 –0.1

62 Health and social services 0 0 –0.8 –0.8

71 Arts-entertainment and recreation 0 –0.1 –0.1 –0.2

72 Accommodation and food services 0 –0.1 –0.5 –0.5

81 Other services 0 –0.1 –0.4 –0.4

92 Government and non-NAICS 0 0 –0.6 –0.6

Pacific whiting trawler 0 0 0 0

Large groundfish trawler 0 0 0 0

Small groundfish trawler –0.1 0 0 –0.1

Sablefish fixed gear –7.2 0 0 –7.2

Other groundfish fixed gear –0.7 0 0 –0.7

Pelagic netter 0 0 0 0

Migratory liner –0.2 0 0 –0.2

Shrimper 0 0 0 0

Crabber –3.8 0 0 –3.8

Salmon troller –0.8 0 0 –0.8

Salmon netter 0 0 0 0

Lobster vessel 0 0 0 0

Other, more than $15,000 0 0 0 0

Other, less than $15,000 –7.1 0 0 –7.1

Bait ship 0 0 0 0

Wholesale seafood –0.2 0 0 –0.2

Total –21.9 –2.2 –4.6 –28.7

51
7. Discussion 

IO-PAC is designed to estimate the backward-linked multiplier effects of policy changes 

that affect gross revenues of commercial fish harvesters, wholesale seafood dealers, and seafood 

processors. The IO-PAC model is a fisheries-specific IO model in which 19 unique harvesting 

sectors, one wholesale seafood dealer sector, and one bait sector are incorporated into a 

customized IMPLAN regional IO model. 

IO-PAC is similar in many respects to the NERIOM model developed by Steinback and 

Thunberg (2006). IO-PAC is incorporated into the ready-made IO IMPLAN system. Building 

the model directly in IMPLAN permits an analyst to trace the effects with a high level of 

industry detail and generate disaggregated estimates of indirect and induced multiplier effects. 

As Steinback and Thunberg (2006) pointed out, this approach differs from the mixed 

exogenous/endogenous variables models and spreadsheet-type models based on limited IO 

multipliers. These approaches derive backward linked multiplier effects by aggregating or 

condensing the same ready-made models. The approach of building the model in IMPLAN will 

also aid in the construction of a CGE model in the future. Information contained in the 

underlying SAM in IMPLAN can be used as the starting point for building a CGE model. 

The study areas used in IO-PAC are intended to be flexible enough to provide impact 

estimates for a wide variety of policy situations and analysis goals. It can provide coast-wide, 

statewide, and port-level impacts. The appropriate study area is dependent on the nature of the 

policy change, the goals of the analysis, and the resolution of the exogenous changes in fish 

harvest that are anticipated. 

The multiplier effects generated by IO-PAC are static and should be viewed as the 

immediate/short-term impacts of an analyzed policy change. There are several assumptions built 

into the model that diminish its accuracy in modeling change over an extended period of time. 

Underlying assumptions such as fixity of prices and zero-substitution elasticities in consumption 

and production are more applicable to shorter than longer periods of time. In reality, harvesters, 

seafood dealers, and seafood processors will all likely shift production practices to mitigate 

losses from changes in policy that result in reduced harvest, and maximize opportunities from 

changes in policy that will increase harvest. These longer term behavioral adjustments are not 

captured in IO-PAC. 

IO-PAC does not include impacts beyond seafood wholesalers and processors. It is 

possible that West Coast restaurants and food service establishments could experience a 

reduction in local supply because of a restrictive fishery management action. This is likely to be 

particularly true in isolated port communities that source a high proportion of seafood demand 

from local producers. Following the approach of Steinback and Thunberg (2006), we assumed 

that consumers would choose from among the many other close substitutes (e.g., other fish 

species, poultry, beef, etc.). As a result, retail level gross revenues would remain unchanged. 

52
IO-PAC can accept input data for the years 2006 through 2020. Data contained in 

IMPLAN are based on economic relationships in 2006; the impacts of management actions in 

succeeding years are determined by converting the estimated changes in gross revenues to year 

2006 dollars before the impacts are estimated. IO-PAC then converts the impact estimates back 

to the year of the input data (through 2020). This process accounts for the effects of inflation on 

the impact estimates. 

IO-PAC is likely more accurate for estimating impacts resulting from changes in 

groundfish harvest than other species. Vessels pursuing groundfish are captured in all three 

NWFSC cost earning surveys, so the production functions for these vessels are likely to be more 

accurate. However, the cost earnings surveys capture a sizable number of crab vessels and 

salmon trollers, so IO-PAC is likely to be reasonably accurate for these sectors as well. 

There are a few areas where IO-PAC can potentially be improved. First, some 

simplifying assumptions were made regarding product flow. Because of the assumptions 

regarding product flow in IO-PAC, it is not set up to capture impacts of sales of seafood by 

harvesters to wholesalers and processors operating in different port study areas. The effect of 

excluding these interarea effects is unknown. The greater the cross-hauling of fish landed in one 

area to other port areas for processing, the greater the error of using the assumption included in 

IO-PAC. The inclusion of these interarea effects would ideally be accomplished with input from 

seafood processors and wholesalers about where fish are processed when they are landed in 

different ports. However, there are other approaches that may be used to include at least some 

interarea effects. These approaches are being examined and will be included in IO-PAC if they 

prove worthwhile. 

Second, IO-PAC relies on the default IMPLAN production function for seafood 

processors, which is based on data from the entire United States. The more production practices 

differ on the West Coast than in the United States as a whole, the more error will result from 

using this assumption. Future research efforts will attempt to obtain better information about 

production practices of seafood processors on the West Coast. 

Third, IO-PAC relies on economic relationships that existed in 2006; however, 

technology and prices change at relatively slow rates, so the model can likely be used for 

subsequent years with minimal error. Fourth, IO-PAC relies on a generic production function for 

all commercial vessels on the West Coast that are currently not covered by NWFSC cost 

earnings surveys. As a result, the model is likely to be more accurate for those sectors that have 

direct survey coverage. 

There are several planned improvements to IO-PAC to address these issues, including 

updating the production functions, adding recreational fisheries, adjusting the product flow 

assumptions, potentially changing the processor production function, and moving to the newest 

version of IMPLAN. The production functions included in IO-PAC will be adjusted as data 

from updated and expanded cost earnings surveys are collected and analyzed. NWFSC recently 

completed another survey of the limited entry trawl fleet. An expanded open access survey is 

currently underway. A new limited entry fixed gear survey will be completed in fall 2011. A 

for-hire recreational fishing sector (charter vessels) will be added to the Oregon and Washington 

models using data from a survey of for-hire vessels that was completed in 2007. The product 

53
flow assumptions and processor production functions will be updated as better data become 

available. Better data may arise as a result of the mandatory Economic Data Collection, which is 

part of the Groundfish Trawl Rationalization Catch Share Program. Lastly, a new version of 

IMPLAN was recently released and IO-PAC will be updated to use the new IMPLAN. 

54
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Appendix A: Bridge between Expenditures and 

IMPLAN Sectors 

Factor expenditures by harvesters and seafood wholesalers were allocated to IMPLAN 

sectors. The following lists represent the bridge between harvester and seafood wholesaler 

expenditures and IMPLAN sectors. These allocations often follow the scheme developed by 

Steinback and Thunberg (2006). 

Harvester Expenditures 

Fuel and lubricant expenses were allocated based on the IMPLAN default margin table 

for sector 142 (petroleum refineries). 

Sector Title Proportion 

142 Petroleum refineries 0.393794 

390 Wholesale trade 0.361077 

392 Rail transportation 0.006754 

393 Water transportation 0.005192 

394 Truck transportation 0.008658 

396 Pipeline transportation 0.004953 

407 Gasoline stations 0.219571 

Total 1.000000 

Food and beverage expenses were allocated based on the IMPLAN personal consumption 

expenditure vector 1111. This vector represents the national average expenditure pattern for 

groceries. However, following the approach of Steinback and Thunberg (2006), purchases 

associated with the two default seafood sectors (i.e., commercial fishing and seafood product 

preparation and packaging) were reallocated to sector 60 (frozen food manufacturing), believed 

to better reflect likely consumption habits aboard commercial fishing vessels. 

Sector Title Proportion 

1 Oilseed farming 6.36E-05 

2 Grain farming 0.000379 

3 Vegetable and melon farming 0.022642 

4 Tree nut farming 0.000749 

5 Fruit farming 0.014302 

6 Greenhouse and nursery production 0.000652 

10 All other crop farming 0.000203 

12 Poultry and egg production 0.006205 

15 Forest nurseries, forest products, and timber 0.000137 

26 Other nonmetallic mineral mining 1E-05 

46 Dog and cat food manufacturing 0.016556 

47 Other animal food manufacturing 0.002251 

48 Flour milling 0.002340 

57
Groceries list continued

Sector Title Proportion 

49 Rice milling 0.001427 

51 Wet corn milling 0.002738 

52 Soybean processing 7.65E-05 

54 Fats and oils refining and blending 0.004478 

55 Breakfast cereal manufacturing 0.016116 

56 Sugar manufacturing 0.005154 

57 Confectionery manufacturing from cacao beans 0.003429 

58 Confectionery manufacturing from purchased chocolate 0.015461 

59 Nonchocolate confectionery manufacturing 0.013150 

60 Frozen food manufacturing 0.035386 

61 Fruit and vegetable canning and drying 0.051314 

62 Fluid milk manufacturing 0.040036 

63 Creamery butter manufacturing 0.002148 

64 Cheese manufacturing 0.014711 

65 Dry, condensed, and evaporated dairy products 0.008433 

66 Ice cream and frozen dessert manufacturing 0.005012 

67 Animal, except poultry, slaughtering 0.057514 

68 Meat processed from carcasses 0.054934 

70 Poultry processing 0.027721 

72 Frozen cakes and other pastries manufacturing 0.005509 

73 Bread and bakery product, except frozen, manufacturing 0.046437 

74 Cookie and cracker manufacturing 0.016265 

75 Mixes and dough made from purchased flour 0.009065 

76 Dry pasta manufacturing 0.003576 

77 Tortilla manufacturing 0.002269 

78 Roasted nuts and peanut butter manufacturing 0.004765 

79 Other snack food manufacturing 0.017670 

80 Coffee and tea manufacturing 0.012974 

81 Flavoring syrup and concentrate manufacturing 0.005455 

82 Mayonnaise, dressing, and sauce manufacturing 0.008480 

83 Spice and extract manufacturing 0.007112 

84 All other food manufacturing 0.018899 

85 Soft drink and ice manufacturing 0.060190 

171 Other miscellaneous chemical product manufacturing 0.000167 

390 Wholesale trade 0.098877 

391 Air transportation 0.000487 

392 Rail transportation 0.002832 

393 Water transportation 0.001729 

394 Truck transportation 0.013268 

399 Couriers and messengers 0.001554 

400 Warehousing and storage 0.000889 

402 Furniture and home furnishings stores 9.66E-05 

404 Building material and garden supply stores 0.001584 

405 Food and beverage stores 0.196583 

407 Gasoline stations 0.016591 

410 General merchandise stores 0.006296 

411 Miscellaneous store retailers 0.008340 

500 Noncomparable imports 0.006314 

Total 1.000000 

58
Ice expenses were allocated based on the IMPLAN default margin table for sector 85 

(soft drink and ice manufacturing). 

Sector Title Proportion 

85 Soft drink and ice manufacturing 0.628331 

390 Wholesale trade 0.102750 

392 Rail transportation 0.000222 

393 Water transportation 3.14E-05 

394 Truck transportation 0.006453 

405 Food and beverage stores 0.193154 

407 Gasoline stations 0.069058 

Total 1.000000 

Bait expenses were allocated to a fishing bait sector that was created and added to the 

model. The production function for the bait sector that was created mirrors the production 

function in the default fishing sector.

Sector Title Proportion 

16 Fishing 0.001894 

43 Maintenance and repair of nonresidential buildings 0.102952 

68 Meat processed from carcasses 0.000061 

85 Soft drink and ice manufacturing 0.010734 

103 Other miscellaneous textile production 0.007470 

125 Paper and paperboard mills 0.000970 

126 Paperboard container manufacturing 0.000022 

129 Coated and laminated paper 0.000017 

130 Coated and uncoated paper bag manufacturing 0.000212 

131 Die-cut paper office supplies manufacturing 0.000028 

132 Envelope manufacturing 0.000016 

133 Stationery and related products 0.000067 

136 Manifold business forms printing 0.000038 

138 Blank-book and loose-leaf binders 0.000006 

142 Petroleum refineries 0.022730 

145 Petroleum lubricating oil and gas manufacturing 0.047874 

163 Soap and other detergent manufacturing 0.000744 

164 Polish and other sanitation goods manufacturing 0.000303 

170 Photographic film and chemicals 0.000008 

172 Plastics, packaging materials 0.001415 

177 Plastics, plumbing fixtures 0.000044 

179 Tire manufacturing 0.000120 

278 AC, refrigeration and forced air 0.000171 

325 Electric lamp bulb and part manufacturing 0.000097 

333 Electric power and specialty transmission 0.000407 

338 Primary battery manufacturing 0.000214 

350 Motor vehicle parts manufacturing 0.000715 

383 Office supplies except paper manufacturing 0.000027 

390 Wholesale trade 0.051741 

391 Air transportation 0.000780 

392 Rail transportation 0.006179 

393 Water transportation 0.008966 

394 Truck transportation 0.006553 

59
Default fishing list continued 

Sector Title Proportion 

396 Pipeline transportation 0.000325 

397 Scenic and sightseeing transport 0.055514 

398 Postal service 0.000641 

401 Motor vehicle and parts dealers 0.000350 

402 Furniture and home furnishings 0.000083 

403 Electronics and appliance stores 0.000100 

404 Building material and garden supplies 0.000153 

405 Food and beverage stores 0.000257 

406 Health and personal care stores 0.000149 

407 Gasoline stations 0.000083 

408 Clothing and clothing accessory 0.000116 

409 Sporting goods, hobby, book stores 0.000042 

410 General merchandise stores 0.000265 

411 Miscellaneous store retailers 0.000146 

412 Nonstore retailers 0.000107 

425 Nondepository credit intermediaries 0.000254 

426 Securities, commodity contracts 0.002401 

427 Insurance carriers 0.009664 

430 Monetary authorities and depository institutions 0.005333 

431 Real estate 0.000403 

432 Automotive equipment rental 0.000259 

434 Machinery and equipment rental 0.012181 

435 General and consumer goods rental 0.000055 

437 Legal services 0.000292 

439 Architectural and engineering services 0.000577 

445 Environmental and other technical services 0.001204 

447 Advertising and related services 0.000650 

450 All other miscellaneous professions 0.000424 

457 Investigation and security services 0.001708 

459 Other support services 0.000468 

478 Other amusement, gambling, and recreation industries 0.010884 

479 Hotels and motels, including casinos 0.000023 

500 Noncomparable imports 0.001524 

Total 1.000000 

Repair and maintenance expenses for vessel gear and equipment were allocated to sector 

357, which includes ship building and repairing. 

Sector Title Proportion 

357 Ship building and repairing 1.00 

Total 1.00 

Moorage expenses were allocated to sector 478, which includes the activities of marinas. 

Marinas usually offer mooring, dockage, and haul out services for a fee.

Sector Title Proportion 

478 Other amusement, gambling, and recreation industries 1.00 

Total 1.00 

60
Insurance expenses for vessels were allocated to sector 427, which includes 

establishments primarily engaged in underwriting and assuming the risk of insurance policies. 

Sector Title Proportion 

427 Insurance carriers 1.00 

Total 1.00 

Interest and financial services were allocated to sector 430, which includes 

establishments primarily engaged in financial services. 

Sector Title Proportion 

430 Monetary authorities and depository credit institutions 1.00 

Total 1.00 

Permit and license fees were allocated to IMPLAN’s value-added sector, indirect 

business taxes. These fees are paid during the normal operation of a business. 

Sector Title Proportion 

Value-added Indirect business taxes 1.00 

Total 1.00 

Payments received by vessel owners as income were classified as value-added sector, 

proprietary income. 

Sector Title Proportion 

Value-added Proprietary income 1.00 

Total 1.00 

All other vessel expenditures were allocated according to proportions contained in the 

production function of the default commercial fishing sector in IMPLAN. This allocation 

scheme is identical to that developed by Steinback and Thunberg (2006) for the miscellaneous 

trip supplies cost category in the Northeast Region Commercial Fishing Input-Output Model. 

They summed the absorption coefficients associated with the manufacturing sectors that produce 

the commodities used in the commercial fishing production function and allocated the 

commodity expenditures to the appropriate manufacturing industries. Additionally, their 

estimates include average wholesale, transportation, and retail margins across all the 

manufacturing sectors since the majority of these purchases occur at the retail level. 

Sector Title Proportion 

100 Curtain and linen mills 0.008560 

103 Other miscellaneous textiles 0.007716 

125 Paper and paperboard mills 0.040025 

126 Paperboard container manufacturing 0.180838 

130 Coated and uncoated paper bag manufacturing 0.023750 

163 Soap and other detergent manufacturing 0.047259 

164 Polish and other sanitation goods manufacturing 0.040146 

172 Plastics packaging materials 0.054372 

177 Plastic plumbing fixtures and all other plastics 0.008319 

179 Tire manufacturing 0.006631 

278 Air conditioning, refrigeration 0.007234 

286 Other engine equipment manufacturing 0.074987 

61
Other vessel expenditures list continued 

Sector Title Proportion 

289 Air and gas compressor manufacturing 0.004581 

321 Watch, clock, and other measuring and controlling devices 0.007475 

325 Electric lamp bulb and part manufacturing 0.012176 

333 Electric power and specialty transformer manufacturing 0.005184 

338 Primary battery manufacturing 0.010247 

350 Motor vehicle parts manufacturing 0.047500 

392 Rail transportation 0.001000 

390 Wholesale trade 0.161000 

404 Building material and gardening supplies 0.001000 

405 Food and beverage stores 0.185000 

407 Gasoline stations 0.013000 

410 General merchandise stores 0.014000 

411 Miscellaneous store retailers 0.038000 

Total 1.000000 

Tax expenditures were allocated to IMPLAN’s value-added sector, indirect business 

taxes. This sector consists of excise taxes, property taxes, and sales taxes, but excludes income 

taxes paid by businesses. 

Sector Title Proportion 

Value-added Indirect business taxes 1.00 

Total 1.00 

Wages and salaries of employees (captain and crew) were allocated to the value-added 

sector, employee compensation. 

Sector Title Proportion 

Value-added Employee compensation 1.00 

Total 1.00 

Vessel residuals were allocated to the value-added sector, proprietary income. 

Sector Title Proportion 

Value-added Proprietary income 1.00 

Total 1.00 

Seafood Wholesale Dealer and Processor Expenditures 

Wholesale seafood dealers purchase many of the same commodities and services as 

commercial harvesters. To avoid duplication, detailed descriptions of wholesale dealer 

expenditures are only provided for products and services not purchased by commercial 

harvesters. 

Advertising fees were allocated to IMPLAN sector 447. 

Sector Title Proportion 

447 Advertising and related services 1.00 

Total 1.00 

62
Packaging (boxes) expenses were allocated using the default IMPLAN margin table for 

sector 126 (paperboard container manufacturing). 

Sector Title Proportion 

126 Paperboard container manufacturing 0.581083 

390 Wholesale trade 0.016356 

391 Air transportation 0.000463 

392 Rail transportation 0.026539 

394 Truck transportation 0.130381 

411 Miscellaneous store retailers 0.245178 

Total 1.000000 

Rental payments were allocated to the sector 431, which includes establishments that are 

primarily engaged in the renting or leasing real estate to others, including the leasing of 

miniwarehouses and storage buildings. 

Sector Title Proportion 

431 Real estate 1.00 

Total 1.00 

Building repair and maintenance payments were allocated to sector 458, which includes 

establishments primarily engaged in cleaning and maintaining building interiors and providing 

landscape care and maintenance. 

Sector Title Proportion 

458 Services to buildings and dwellings 1.00 

Total 1.00 

Shipping expenses were allocated to sector 394, comprised of establishments primarily 

engaged in providing general freight trucking. 

Sector Title Proportion 

394 Truck transportation 1.00 

Total 1.00 

Storage expenses were allocated to sector 400, comprised of establishments primarily 

engaged in operating warehousing and storage facilities for general merchandise. 

Sector Title Proportion 

400 Warehousing and storage 1.00 

Total 1.00 

Electrical utility expenses were allocated to sector 30, comprised of establishments 

primarily engaged in generating, transmitting, or distributing electric power. 

Sector Title Proportion 

30 Power generation and supply 1.00 

Total 1.00 

63
64

Natural gas utility expenses were allocated to sector 31, comprised of establishments 

primarily engaged in transmitting and distributing gas to final consumers. 

Sector Title Proportion 

31 Natural gas distribution 1.00 

Total 1.00 

Telephone utility expenses were allocated to the sector 422, comprised of establishments 

that are primarily engaged in operating, maintaining, or providing access to facilities for the 

transmission of voice, data, text, sound, and video. 

Sector Title Proportion 

422 Telecommunications 1.00 

Total 1.00 

For seafood processor expenditures, the default production function for Sector 71 

(seafood product preparation and packaging) was used to allocate purchases by seafood 

processors. This production function includes more than 140 industry sectors that sell 

commodities and services to processors.
Recent NOAA Technical Memorandums

published by the

Northwest Fisheries Science Center 

NOAA Technical Memorandum NMFS-NWFSC110 Ainsworth, C.H., I.C. Kaplan, P.S. Levin, R. Cudney-Bueno, E.A. Fulton, M. Mangel, P. TurkBoyer, J. Torre, A. Pares-Sierra, and H.N. Morzaria Luna. 2011. Atlantis model development for the 

northern Gulf of California. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-110, 293 p. 

NTIS number pending. 

109 Levin, P.S., and F.B. Schwing (eds.). 2011. Technical background for an integrated ecosystem 

assessment of the California Current: Groundfish, salmon, green sturgeon, and ecosystem health. U.S. 

Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-109, 330 p. NTIS number PB2011-112724. 

108 Drake, J.S., E.A. Berntson, J.M. Cope, R.G. Gustafson, E.E. Holmes, P.S. Levin, N. Tolimieri, R.S. 

Waples, S.M. Sogard, and G.D. Williams. 2010. Status review of five rockfish species in Puget Sound, 

Washington: Bocaccio (Sebastes paucispinis), canary rockfish (S. pinniger), yelloweye rockfish (S. 

ruberrimus), greenstriped rockfish (S. elongatus), and redstripe rockfish (S. proriger). U.S. Dept. 

Commer., NOAA Tech. Memo. NMFS-NWFSC-108, 234 p. NTIS number PB2011-107576. 

107 Lian, C.E. 2010. West Coast limited entry groundfish trawl cost earnings survey protocols and results for 

2004. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-107, 35 p. NTIS number PB2011-

102712. 

106 Harvey, C.J., K.K. Bartz, J. Davies, T.B. Francis, T.P. Good, A.D. Guerry, B. Hanson, K.K. 

Holsman, J. Miller, M.L. Plummer, J.C.P. Reum, L.D. Rhodes, C.A. Rice, J.F. Samhouri, G.D. 

Williams, N. Yoder, P.S. Levin, and M.H. Ruckelshaus. 2010. A mass-balance model for evaluating 

food web structure and community-scale indicators in the central basin of Puget Sound. U.S. Dept. Commer., 

NOAA Tech. Memo. NMFS-NWFSC-106, 180 p. NTIS number PB2011-102711.

105 Gustafson, R.G., M.J. Ford, D. Teel, and J.S. Drake. 2010. Status review of eulachon (Thaleichthys 

pacificus) in Washington, Oregon, and California. U.S. Dept. Commer., NOAA Tech. Memo. NMFSNWFSC-105, 360 p. NTIS number PB2011-102710.

104 Horne, P.J., I.C. Kaplan, K.N. Marshall, P.S. Levin, C.J. Harvey, A.J. Hermann, and E.A. Fulton. 

2010. Design and parameterization of a spatially explicit ecosystem model of the central California Current. 

U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-104, 140 p. NTIS number PB2010-110533.

103 Dufault, A.M., K. Marshall, and I.C. Kaplan. 2009. A synthesis of diets and trophic overlap of marine 

species in the California Current. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-103, 81 p. 

NTIS number PB2010-110532.

Most NOAA Technical Memorandums NMFS-NWFSC are available online at the 

Northwest Fisheries Science Center Web site (http://www.nwfsc.noaa.gov).