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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 ([email protected])
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

iii

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

List of Figures
Figure 1. West Coast, state, and port study areas in IO-PAC ...................................................................... 2
Figure 2. IO-PAC product flows................................................................................................................ 33

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

vii

viii

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

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.

xii

Abbreviations and Acronyms
BEA
CDFG
CGE
FEAM
IMPLAN
IO
IO-PAC
NAICS
NERIOM
NMFS
NWFSC
ODFW
PacFIN
RPC
SAM
WDFW
WDOR

U.S. Bureau of Economic Analysis
California Department of Fish and Game
computable general equilibrium
Fisheries Economic Assessment Model
Impact Analysis for Planning (regional input-output software)
input-output
input-output model for Pacific Coast fisheries
North American Industry Classification System
Northeast Region Commercial Fishing Input-Output Model
National Marine Fisheries Service
Northwest Fisheries Science Center
Oregon Department of Fish and Wildlife
Pacific Fisheries Information Network
regional purchase coefficient
social accounting matrix
Washington Department of Fish and Wildlife
Washington Department of Revenue

xiii

xiv

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
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

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

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. 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

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
a12 ⎤
a 22 ⎥⎦

⎡a
A = ⎢ 11
⎣a 21

(2)

with a 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 a 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

α12 ⎤
⎡α
(I-A)–1 = ⎢ 11
⎥
⎣α 21 α 22 ⎦

(3)

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
⎡α ⎤
ΔX1 = (I-A)–1ΔY1j = ⎢ 11 ⎥
⎣α 21 ⎦

(4)

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
n

Oj =

∑α
i =1

(5)

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.

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
⎡ a11
Α = ⎢a 21
⎢
⎢⎣a31

a12
a 22
a32

a13 ⎤
a 23 ⎥
⎥
a 33 ⎥⎦

(6)

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.

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.

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

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.

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.

See footnote 2.

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
5

See http://pacfin.psmfc.org/index.php.
Based on a PacFIN data query.

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
7

G. Konkel, WDFW, Olympia. Pers. commun., 14 July 2009.
See tables 4, 5, 6, 10, 11, and 12 in Lian 2010, tables 3, 4, 5, and 6 in Lian in press.

Table 1. Vessel sectors used in the IO-PAC (Radtke and Davis 2000).
Order
1
2
3

Vessel sector
Mother ship
catcher/processor
Alaska fisheries vessel
Pacific whiting offshore
and onshore trawler

Large groundfish
trawler

Small groundfish
trawler

Sablefish fixed gear

Other groundfish fixed
gear

Pelagic netter

Migratory netter

Migratory liner

Shrimper

Crabber

Salmon troller

Salmon netter

Other netter

Lobster vessel

Diver vessel

18
19

Other > $15,000
Other ≤ $15,000

Rule description
Identified by vessel documentation.
Alaska revenue is > 50% of vessel’s total revenue.
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.
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.
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.
Sablefish revenue from fixed gear is > 33% of vessel total revenue
and total revenue is > $15,000.
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.
Pelagic species revenue is > 33% of vessel total revenue and total
revenue is > than $15,000.
Highly migratory species revenue from gear other than troll or line
gear is > 33% of vessel total revenue and total revenue is >
$15,000.
Highly migratory species revenue from troll or line gear is > 33%
of vessel total revenue and total revenue is > $15,000.
Shrimp revenue is > 33% of vessel total revenue and total revenue
is > $15,000.
Crab revenue is > 33% of vessel total revenue and total revenue is >
$15,000.
Salmon revenue from troll gear is > 33% of vessel total revenue and
total revenue is > $5,000.
Salmon revenue from gill or purse seine gear is > 33% of vessel
total revenue and total revenue is > $5,000.
Other species revenue from net gear is > 33% of vessel total
revenue and total revenue is > $15,000.
Lobster revenue is > 33% of vessel total revenue and total revenue
is > $15,000.
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.
All other vessels not above with total revenue > $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.

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).

California
Crescent City
Humboldt Bay
Port of Los Angeles
San Francisco Fisherman’s Wharf
San Francisco Hyde Street
Half Moon Bay
Morro Bay
Moss Landing
San Diego B Street Pier
Bodega Bay
California average
Oregon
Astoria
Newport
Coos Bay
Oregon average
Washington
Westport Grays Harbor
Seattle Fishermen’s Terminal
Ilwaco
Bellingham Squalicum Harbor
Bellingham Blaine Harbor
Washington average
West Coast average

Length of vessel (feet)
70
65
60
50

—
3,315
4,325
—
—
—
—
5,523
3,258
—
4,105

—
3,120
4,070
—
4,688
—
—
5,198
3,066
5,659
4,300

2,381
2,730
3,562
—
4,688
—
2,797
4,549
2,683
4,952
3,543

2,381
2,535
3,307
—
4,688
6,677
2,597
4,224
2,491
4,598
3,722

2,041
2,340
3,053
—
4,688
6,178
2,398
3,899
2,300
4,244
3,460

1,706
1,950
2,544
1,065
2,930
5,178
1,998
3,249
1,916
3,537
2,607

1,450
1,560
2,035
959
2,344
4,178
1,598
2,599
1,533
2,830
2,109

1,195
1,170
1,526
639
2,344
3,179
1,439
1,949
1,150
2,122
1,671

2,295
3,304
2,295
2,631

2,160
3,128
2,160
2,483

1,890
2,583
1,890
2,121

1,755
2,420
1,755
1,977

1,620
2,145
1,620
1,795

1,350
1,701
1,350
1,467

1,080
1,306
1,080
1,155

810
1,056
827
898

3,146
9,792
1,597
—
—
4,845
3,860

2,961
9,216
1,503
—
—
4,560
3,781

2,591
4,544
1,315
—
—
2,817
2,827

2,406
4,220
1,221
—
—
2,616
2,771

2,221
3,895
1,127
—
4,760
3,001
2,752

1,851
3,246
635
3,967
3,967
2,733
2,269

1,480
2,597
508
3,174
3,174
2,186
1,817

1,110
1,948
381
2,380
2,380
1,640
1,403

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
California (levied on landing pounds)
All species of fish and shellfish unless otherwise specified
Mollusks and crustaceans, excluding squid and crab
Crab
Squid
Salmon, based only on weight in the round
Lobster
Abalone
Anchovy
Sardine
Mackerel
Halibut
Angel shark, based only on weight in the round
Swordfish, based only on weight in the round
Thresher shark, based only on weight in the round
Bonito shark, based only on weight in the round
Herring
Sea urchin
Barracuda, flying fish, frogs, giant sea bass, saltwater worms, white
sea bass, yellowtail (Seriola lalandi)
Oregon (levied on landing dollars)
All species of fish and shellfish unless otherwise specified
Salmon and steelhead
Black/blue rockfish and nearshore fish
Washington (levied on landing dollars)
Food fish or eggs unless otherwise specified
Chinook, coho, and chum salmon, anadromous game fish and eggs
Sea urchins and cucumbers
Pink and sockeye salmon fish or eggs
Oysters
Federal (levied on landing dollars)
Pacific coast groundfish (using trawl gear)
California coastal Dungeness crab
California pink shrimp
Oregon coastal Dungeness crab
Oregon pink shrimp
Washington coastal Dungeness crab
Washington pink shrimp

Rate/pound ($)
0.0013
0.0125
0.0019
0.0019
0.0500
0.0125
0.0125
0.0013
0.0063
0.0013
0.0125
0.0113
0.0125
0.0113
0.0113
0.0125
0.0013
0.0125
Rate/dollar (%)
1.09
3.15
5.00
2.30
5.60
4.90
3.40
0.10
5.00
1.24
5.00
0.55
4.70
0.16
1.50

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.

L. Hoines, WDFW, Olympia. Pers. commun., 8 July 2009.
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.
10

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.

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.

Table 4. Industry categories and associated IMPLAN codes.
IMPLAN code
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
561
563

Category description
Mother ship catcher/processor
Alaska fisheries vessel
Pacific whiting trawler
Large groundfish trawler
Small groundfish trawler
Sablefish fixed gear
Other groundfish fixed gear
Pelagic netter
Migratory netter
Migratory liner
Shrimper
Crabber
Salmon troller
Salmon netter
Other netter
Lobster vessel
Diver vessel
Other, more than $15,000
Other, less than $15,000
Bait ship
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
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
562

Species and gear combinations
Whiting, at sea
Whiting, trawl
Whiting, fixed gear
Sablefish, trawl
Sablefish, fixed gear
Dover/thornyhead, trawl
Dover/thornyhead, fixed gear
Other groundfish, trawl
Other groundfish, fixed gear
Other groundfish, net
Crab, trawl
Crab, fixed gear
Crab, net
Crab, other gear
Shrimp, trawl
Shrimp, fixed gear
Salmon, trawl
Salmon, fixed gear
Salmon, net
Highly migratory species, fixed gear
Highly migratory species, net
Coastal pelagic species, trawl
Coastal pelagic species, fixed gear
Coastal pelagic species, net
Coastal pelagic species, other gear
Halibut, trawl
Halibut, fixed gear
Halibut, net
Other species, trawl
Other species, fixed gear
Other species, net
Other species, other gear
Bait

Table 6. Gear groupings and associated PacFIN variables.
IO-PAC
Trawl
Trawl
Fixed gear
Fixed gear
Fixed gear
Fixed gear
Net
Other gear
Other gear

Gear ID
TWL
TWS
NTW
HKL
TLS
POT
NET
MSC
DRG

Description
Trawls except shrimp trawls
Shrimp trawls
Nontrawl gear
Hook and line gear except troll
Troll gear
Pot and trap gear
Net gear except trawl
Other miscellaneous gear
Dredge gear

Table 7. IO-PAC commodity groupings. SPID = species identification, NA = not applicable,
Nom. = nominal.
IO-PAC
CPS
CPS
CPS
CPS
CPS
CPS
CPS
Crab
Crab
Crab
Crab
Crab
Crab
Dover/thornyhead
Dover/thornyhead
Dover/thornyhead
Dover/thornyhead
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish

SPID
CMCK
JMCK
MSQD
NANC
PBNT
PSDN
UMCK
BTCR
DCRB
OCRB
RCRB
UCRB
UKCR
DOVR
LSP1
SSP1
THDS
ARR1
ART1
ARTH
BCC1
BGL1
BLK1
BLU1
BNK1
BRW1
BRZ1
BSOL
BYL1
CBZ1
CBZN
CHN1
CLP1
CNR1
COP1
CSOL
CWC1
DBR1
DSRK
DVR1
EGL1
EGLS
FLG1
FSOL
GBL1
GPH1
GRDR

Common name
Pacific mackerel
Jack mackerel
Market squid
Northern anchovy
Pacific bonito
Pacific sardine
Mackerel, unspecified
Bairdi tanner crab
Dungeness crab
Other crab
Red rock crab
Crab, unspecified
King crab, unspecified
Dover sole
Nom. longspine thornyhead
Nom. shortspine thornyhead
Thornyheads, mixed
Nom. aurora rockfish
Nom. arrowtooth flounder
Arrowtooth flounder
Nom. bocaccio
Nom. blackgill rockfish
Nom. black rockfish
Nom. blue rockfish
Nom. bank rockfish
Nom. brown rockfish
Nom. bronzespotted rockfish
Butter sole
Nom. black and yellow rockfish
Nom. cabezon
Cabezon
Nom. china rockfish
Nom. chilipepper
Nom. canary rockfish
Nom. copper rockfish
Curlfin sole
Nom. cowcod rockfish
Nom. darkblotched rockfish
Spiny dogfish
Nom. Dover sole
Nom. English sole
English sole
Nom. flag rockfish
Flathead sole
Nom. greenblotched rockfish
Nom. gopher rockfish
Grenadier, unspecified

Scientific name
Scomber japonicus
Trachurus symmetricus
Loligo opalescens
Engraulis mordax
Sarda chiliensis
Sardinops sagax
NA
Chionoecetes bairdi
Cancer magister
NA
Cancer productus
NA
NA
Microstomus pacificus
NA
NA
Sebastolobus spp.
NA
NA
Atheresthes stomias
NA
NA
NA
NA
NA
NA
NA
Isopsetta isolepis
NA
NA
Scorpaenichthys marmoratus
NA
NA
NA
NA
Pleuronichthys decurrens
NA
NA
Squalus acanthias
NA
NA
Parophrys vetulus
NA
Hippoglossoides elassodon
NA
NA
NA

Table 7 continued. IO-PAC commodity groupings. SPID = species identification, Nom. = nominal,
NA = not applicable, Nor. = northern.
IO-PAC
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish

SPID
GRS1
GSP1
GSR1
HNY1
KGL1
KLP1
LCOD
LCD1
LSRK
MXR1
NUSF
NUSP
NUSR
OFLT
OGRN
OLV1
PCOD
PDAB
PDB1
PLCK
PNK1
POP2
PTR1
PTRL
QLB1
RATF
RCK2
RCK4
RCK5
RCK6
RCK7
RDB1
REX
REX1
ROS1
RSOL
RST1
SBL1
SCR1
SFL1
SNS1
SPK1
SSO1
SSOL
SSRK
STR1
STRY

Common name
Nom. grass rockfish
Nom. greenspotted rockfish
Nom. greenstriped rockfish
Nom. honeycomb rockfish
Nom. kelp greenling
Nom. kelp rockfish
Lingcod
Nom. lingcod
Leopard shark
Nom. Mexican rockfish
Nor. shelf rockfish, unspecified
Nor. slope rockfish, unspecified
Nor. nearshore rockfish, unspecified
Other flatfish
Other groundfish
Nom. olive rockfish
Pacific cod
Pacific sanddab
Nom. Pacific sanddab
Walleye pollock
Nom. pink rockfish
Nom. Pacific ocean perch
Nom. petrale sole
Petrale sole
Nom. quillback rockfish
Spotted ratfish
Bolina rockfish, unspecified
Reds rockfish, unspecified
Sm. red rockfish, unspecified
Rosefish rockfish, unspecified
Gopher rockfish, unspecified
Nom. redbanded rockfish
Rex sole
Nom. rex sole
Nom. rosy rockfish
Rock sole
Nom. rosethorn rockfish
Nom. shortbelly rockfish
Nom. California scorpionfish
Nom. starry flounder
Nom. splitnose rockfish
Nom. speckled rockfish
Nom. sand sole
Pacific sand sole
Soupfin shark
Nom. starry rockfish
Starry flounder

Scientific name
NA
NA
NA
NA
NA
NA
Ophiodon elongatus
NA
Triakis semifasciata
NA
NA
NA
NA
NA
NA
NA
Gadus macrocephalus
Citharichthys sordidus
Citharichthys spp.
Theragra chalcogramma
NA
NA
NA
Eopsetta jordani
NA
Hydrolagus colliei
NA
NA
NA
NA
NA
NA
Glyptocephalus zachirus
NA
NA
Lepidopsetta bilineata
NA
NA
NA
NA
NA
NA
NA
Psettichthys melanostictus
Galeorhinus galeus
NA
Platichthys stellatus

Table 7 continued. IO-PAC commodity groupings. SPID = species identification, Nom. = nominal,
NA = not applicable.
IO-PAC
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Other groundfish
Halibut
Halibut
Halibut
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
HMS
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other

SPID
SWS1
TGR1
TRE1
UDAB
UDNR
UFLT
UPOP
URCK
USHR
USLF
USLP
UTRB
VRM1
WDW1
YEY1
YTR1
CHL1
CHLB
PHLB
ALBC
BSRK
BTNA
DRDO
ETNA
ISRK
MAKO
PSRK
STNA
SWRD
TSRK
UTNA
YLTL
YTNA
ASRK
BCLM
BMSL
BTRY
CKLE
CMSL
CUDA
EELS
ESTR
EULC
EURO
GBAS
GCLM
GDUK

Common name
Nom. swordspine rockfish
Nom. tiger rockfish
Nom. treefish
Sanddabs, unspecified
Deep nearshore rockfish, unspecified
Flatfish, unspecified
Pacific ocean perch group, unspec’d
Rockfish, unspecified
Nearshore rockfish, unspecified
Shelf rockfish, unspecified
Slope rockfish, unspecified
Turbots, unspecified
Nom. vermillion rockfish
Nom. widow rockfish
Nom. yelloweye rockfish
Nom. yellowtail rockfish
Nom. California halibut
California halibut
Pacific halibut
Albacore tuna
Blue shark
Bluefin tuna
Dorado
Bigeye tuna
Bigeye thresher shark
Shortfin mako shark
Pelagic thresher shark
Skipjack tuna
Swordfish
Common thresher shark
Tuna, unspecified
Yellowtail jack
Yellowfin tuna
Pacific angel shark
Washington butter clam
Blue or bay mussel
Bat ray
Basket cockle
California mussel
Pacific barracuda
Eels, unspecified
Eastern oyster
Eulachon
European oyster
Giant sea bass
Gaper clam
Geoduck

Scientific name
NA
NA
NA
Citharichthys spp.
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Paralichthys californicus
Hippoglossus stenolepis
Thunnus alalunga
Prionace glauca
Thunnus thynnus
Coryphaena hippurus
Thunnus obesus
Alopias superciliosus
Isurus oxyrinchus
Alopias pelagicus
Katsuwonus pelamis
Xiphias gladius
Alopias vulpinus
NA
Seriola lalandi
Thunnus albacares
Squatina californica
Saxidomus giganteus
Mytilus edulus
Myliobatis californica
Clinocardium nuttallil
Mytilus californianus
Sphyraena argentea
NA
Crassostrea virginica
Thaleichthys pacificus
Ostrea edulis
Stereolepis gigas
Tresus capax
Panopea abrupta

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

SPID
GSTG
HCLM
KSTR
LCLM
LOBS
LSTR
MACL
MCLM
MEEL
MISC
MSC2
MSHP
OABL
OBAS
OCRK
OCTP
OMSK
OSKT
OSRK
OURC
PHRG
PROW
PSTR
RCLM
RURC
SCLM
SCLP
SHAD
SHP1
SMLT
SQID
SRFP
UCLM
UECH
UHAG
UMSK
USCU
USKT
USRK
WBAS
WCRK
WEEL
WSTG
CHNK
CHUM
COHO
PINK
SOCK

Common name
Green sturgeon
Horse clams
Kumamoto oyster
Native littleneck
California spiny lobster
Olympia oyster
Mud clams
Manila clam
Monkeyface prickleback
Misc. fish/animals
Misc. fish
Plainfin midshipman
Other abalone
Other bass
Other croaker
Octopus, unspecified
Other mollusks
Other skates
Other sharks
Other sea urchins
Pacific herring
Prowfish
Pacific oyster
Razor clam
Red sea urchin
Soft-shelled clam
Sculpin, unspecified
Shad, unspecified
Nom. California sheephead
Smelt, unspecified
Squid, unspecified
Surfperch spp.
Clam, unspecified
Echinoderm, unspecified
Hagfish, unspecified
Mollusks, unspecified
Sea cucumbers, unspecified
Skates, unspecified
Sharks, unspecified
White seabass
White croaker
Wolf-eel
White sturgeon
Chinook salmon
Chum salmon
Coho salmon
Pink salmon
Sockeye salmon

Scientific name
Acipenser medirostris
Tresus spp.
Crassostrea gigas kumamoto
Protothaca staminea
Panulirus interruptus
Ostrea conchaphila
Macoma spp.
Ruditapes philippinarum
Cebidichthys violaceus
NA
NA
Porichthys notatus
NA
NA
NA
NA
NA
Other Rajidae
NA
NA
Clupea harengus pallasii
Zaprora silenus
Crassostrea gigas
Siliqua patula
Strongylocentrotus franciscanus
Mya arenaria
Cottidae spp.
NA
NA
NA
Decapoda
Surfperch spp.
NA
NA
Eptatretus spp.
NA
NA
Rajidae, unspecified
NA
Atractoscion nobilis
Genyonemus lineatus
Anarrichthys ocellatus
Acipenser transmontanus
Oncorhynchus tshawytscha
O. keta
O. kisutch
O. gorbuscha
O. nerka

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

SPID
STLH
USMN
SABL
BSRM
GPRW
GSRM
MSRM
OSRM
PSHP
RPRW
SPRW
USRM
PWHT

Common name
Steelhead
Salmon, unspecified
Sablefish
Bait shrimp, unspecified
Yellowleg shrimp
Bay ghost shrimp
Blue mud shrimp
Other shrimp
Pink shrimp
Ridgeback prawn
Spot shrimp
Ocean shrimp, unspecified
Pacific whiting

Scientific name
O. mykiss
NA
Anoplopoma fimbria
NA
Penaeus californiensis
Callianassa californiensis
Upogebia pugettensis
NA
Pandaulus jordani
Sicyonia ingentus
Pandalus platyceros
NA
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
code
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560

Species and gear
combinations
Whiting, at sea
Whiting, trawl
Whiting, fixed gear
Sablefish, trawl
Sablefish, fixed gear
Dover/thornyhead, trawl
Dover/thornyhead, fixed gear
Other groundfish, trawl
Other groundfish, fixed gear
Other groundfish, net
Crab, trawl
Crab, fixed gear
Crab, net
Crab, other gear
Shrimp, trawl
Shrimp, fixed gear
Salmon, trawl
Salmon, fixed gear
Salmon, net
HMS, fixed gear
HMS, net
CPS, trawl
CPS, fixed gear
CPS, net
CPS, other gear
Halibut, trawl
Halibut, fixed gear
Halibut, net
Other species, trawl
Other species, fixed gear
Other species, net
Other species, other gear
Total

510
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—

511
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—

512
—
16,049,437
—
1,068,257
138,319
551,623
21
665,810
235
—
35
3,349,458
—
—
21,632
—
35,861
—
—
3,629
—
6,422
—
—
—
4,257
13,817
—
66,680
865
—
—
21,976,357

Vessel classification
513
514
515
—
—
—
1,135,712
126,452
—
—
—
76
5,730,702
138,606
53,272
28,729
38,053
7,919,824
4,604,122
83,753
47,975
2,423
45
269,410
9,788,725
352,668
72,835
17,014
3,888
499,699
3,284
45,670
—
1,850
77
—
6,782,547
36,395
2,822,517
6,090
1,894
—
—
—
—
1,300,335
1,182
40,758
—
—
5,175
1,326
1,147
—
87,169
82,705
913,815
—
—
97,408
123,084
—
248,577
46
1,724
—
446
—
—
—
—
7
7
1,342
482
—
—
—
1,112,077
597,291
2,167
31,021
41,902
1,937,697
77,175
198,605
—
355,360
39,601
580
487
41,364
103,281
36,319
169,934
294
—
—
2,176
31,226,049
2,004,297
15,038,025

516
—
—
564
—
661,001
—
951,126
—
1,711,622
—
—
787,886
—
—
—
—
—
119,999
30,329
15,015
—
—
1,383
—
—
191
4,419,302
—
—
35,273
23,352
22,474
8,779,517

517
—
—
—
—
40,726
—
—
—
2,111
24
—
608,683
—
—
—
—
—
11,461
431,989
1,464
99,204
—
14,157
13,428,930
130
—
374
4,532
—
14,958
26,808,914
—
41,467,657

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

IMPLAN
code
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560

Species and gear
combinations
Whiting, at sea
Whiting, trawl
Whiting, fixed gear
Sablefish, trawl
Sablefish, fixed gear
Dover/thornyhead, trawl
Dover/thornyhead, fixed gear
Other groundfish, trawl
Other groundfish, fixed gear
Other groundfish, net
Crab, trawl
Crab, fixed gear
Crab, net
Crab, other gear
Shrimp, trawl
Shrimp, fixed gear
Salmon, trawl
Salmon, fixed gear
Salmon, net
HMS, fixed gear
HMS, net
CPS, trawl
CPS, fixed gear
CPS, net
CPS, other gear
Halibut, trawl
Halibut, fixed gear
Halibut, net
Other species, trawl
Other species, fixed gear
Other species, net
Other species, other gear
Total

518
—
—
—
—
23
—
—
—
7,336
20,694
—
—
64
—
—
—
—
63,198
—
326,417
28,216
—
10
2,525
—
578
57
24,823
—
5,768
2,481,457
556,267
3,517,434

519
—
—
—
—
164,342
—
85
—
5,537
—
738
2,456,793
—
—
26,239
—
—
819,124
—
17,765,249
2,424
—
2,884
38
—
—
140,159
—
—
116,537
160,485
80,051
21,740,683

Vessel classification
521
522
—
—
248
120,114
—
—
75
—
—
404,879
—
22,474
5,692,071
325,330
—
265,548
—
—
6,655
1,133
5,046
428,986
—
20,897
382,240
94,442
—
2,321
—
149
—
—
3,265,246 120,966,903
156,663
212
10,137
—
—
23,912
1,677
5,068,270
685,320
—
4,073,820
784,724
—
—
4
—
9,952
2,857,295
4,633,803
85,904
3,952,646
21,664
123,245
4,887,944
204,346
—
2,803
146
40
11
—
36
894
357
—
262,979
11
—
2,152
—
20,490
10,972
—
49,680
2,536,750
279,460
582
—
—
69,948
13,421
—
575,411
434,165
372
1,918
397,151
514
263
39,955
—
13,393,830 145,173,028
5,719,919
520
—

523
—
—
—
—
11,554
—
—
—
160
3,006
—
492,963
—
—
8,032
89,887
—
17,435
18,003,891
28
—
—
—
7,316
—
—
14,731
—
—
744
524,956
—
19,174,704

524
—
—
—
—
—
—
—
—
5,379
19,625
—
50,117
—
—
—
—
—
6,087
18,040
—
13,205
—
—
459
—
96
827
79,352
45
165,103
1,607,932
—
1,966,268

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

IMPLAN
code
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560

Species and gear
combinations
Whiting, at sea
Whiting, trawl
Whiting, fixed gear
Sablefish, trawl
Sablefish, fixed gear
Dover/thornyhead, trawl
Dover/thornyhead, fixed gear
Other groundfish, trawl
Other groundfish, fixed gear
Other groundfish, net
Crab, trawl
Crab, fixed gear
Crab, net
Crab, other gear
Shrimp, trawl
Shrimp, fixed gear
Salmon, trawl
Salmon, fixed gear
Salmon, net
HMS, fixed gear
HMS, net
CPS, trawl
CPS, fixed gear
CPS, net
CPS, other gear
Halibut, trawl
Halibut, fixed gear
Halibut, net
Other species, trawl
Other species, fixed gear
Other species, net
Other species, other gear
Total

525
—
—
—
—
17,637
—
33
—
65,764
758
40
190,637
365
—
—
19,811
—
10,338
—
5,946
—
—
5,894
18,440
—
224
225,269
22,218
84
6,818,270
39,449
71,345
7,512,522

526
—
—
—
—
—
—
—
—
51,480
—
—
587
—
148
—
—
—
—
—
58
—
—
—
—
—
—
46,328
—
58
34,364
1,730
5,264,819
5,399,571

Vessel classification
527
528
—
—
—
—
—
12
323
2,810
122,157
424,009
467
1,973
1,193
36,329
5,084
16,031
10,211
804,012
107
13,314
—
235
101,143
1,705,317
193
1,937
250
36,397
16,300
26,905
1,168
82,518
—
—
64,544
461,978
628,156
1,470,652
5,452
390,513
—
4,008
2
—
1,859
11,647
—
285,975
—
—
16,092
27,270
185,968
312,887
4,238
54,062
92,431
7,696
592,652
277,637
190,355
247,098
80,754,211
417,122
82,794,555
7,120,343

Total all classifications
—
17,431,963
727
7,398,850
15,606,247
5,555,461
1,268,452
11,335,185
3,682,029
108,804
3,125
143,773,854
20,892
62,383
7,194,972
5,057,102
38,338
10,158,902
24,740,680
24,100,967
151,777
6,920
39,129
14,008,503
2,282
1,791,705
10,236,229
465,586
645,904
9,217,251
32,691,859
87,208,682
434,004,758

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

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

IO-PAC port group
Bodega Bay
Bodega Bay
Bodega Bay
Bodega Bay
Bodega Bay

PCID
BDG
RYS
SLT
TML
OSM

CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA

Crescent City
Eureka
Eureka
Eureka
Eureka
Fort Bragg
Fort Bragg
Fort Bragg
Fort Bragg
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Los Angeles
Monterey
Monterey
Monterey
Monterey
Morro Bay
Morro Bay
Morro Bay
San Diego
San Diego
San Diego
San Francisco
San Francisco
San Francisco
San Francisco

CRS
ERK
FLN
OHB
TRN
ALB
ARE
BRG
OMD
DNA
LGB
NWB
OLA
SP
TRM
WLM
CRZ
MNT
MOS
OCM
AVL
MRO
OSL
OCN
OSD
SD
ALM
BKL
OAK
OSF

CA
CA
CA
CA
CA

San Francisco
San Francisco
San Francisco
Santa Barbara
Santa Barbara

PRN
RCH
SF
HNM
OBV

CA
CA
CA
OR

Santa Barbara
Santa Barbara
Santa Barbara
Astoria

OXN
SB
VEN
AST

Port name (PNAME)
Bodega Bay
Point Reyes
Sausalito
Tomales Bay
Other Sonoma, Marin County outer coast
ports
Crescent City
Eureka
Fields Landing
Other Humboldt County ports
Trinidad
Albion
Point Arena
Fort Bragg
Other Mendocino County ports
Dana Point
Long Beach
Newport Beach
Other Los Angeles, Orange County ports
San Pedro
Terminal Island
Wilmington
Santa Cruz
Monterey
Moss Landing
Other Santa Cruz, Monterey County ports
Avila
Morro Bay
Other San Luis Obispo County ports
Oceanside
Other San Diego County ports
San Diego
Alameda
Berkeley
Oakland
Other San Francisco Bay, San Mateo
County ports
Princeton/Half Moon Bay
Richmond
San Francisco
Port Hueneme
Other Santa Barbara, Ventura County
ports
Oxnard
Santa Barbara
Ventura
Astoria

AGID
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
O

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

IO-PAC port group
Astoria
Astoria
Astoria
Tillamook
Tillamook
Tillamook
Tillamook
Brookings
Brookings
Brookings
Columbia River
Coos Bay
Coos Bay
Coos Bay
Coos Bay
Newport
Newport
Newport
North WA coast
North WA coast
North WA coast
North WA coast
North WA coast
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
Puget Sound
South and central WA coast
South and central WA coast
South and central WA coast
South and central WA coast
South and central WA coast
South and central WA coast

PCID
CNB
CRV
GSS
NHL
NTR
PCC
TLL
BRK
GLD
ORF
CRV
BDN
COS
FLR
WIN
DPO
NEW
WLD
LAP
NEA
PAG
SEQ
TNS
ANA
BLL
BLN
EVR
FRI
LAC
OLY
ONP
SEA
SHL
TAC
CPL
GRH
LWC
OCR
WLB
WPT

Port name (PNAME)
Cannon Beach
Pseudo port code for Columbia River
Gearhart/Seaside
Nehalem Bay
Netarts Bay
Pacific City
Tillamook/Garibaldi
Brookings
Gold Beach
Port Orford
Columbia River pseudo port code
Bandon
Charleston (Coos Bay)
Florence
Winchester Bay
Depoe Bay
Newport
Waldport
La Push
Neah Bay
Port Angeles
Sequim
Port Townsend
Anacortes
Bellingham Bay
Blaine
Everett
Friday Harbor
La Conner
Olympia
Other north Puget Sound ports
Seattle
Shelton
Tacoma
Copalis Beach
Grays Harbor
Ilwaco/Chinook
Other Columbia River ports
Willapa Bay
Westport

AGID
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
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.

B. Leech, WDOR, Olympia. Pers. commun., 10 July 2009.

Table 10. Washington Enhanced Food Fish Tax by NAICS, calendar year 2006.
NAICS code
114111
114112
311711
311712
423910
424460
424490
445220
451110
454390
713930
999999

Title
Fin fishing
Shellfish fishing
Seafood canning
Fresh and frozen seafood processing
Sporting and recreational goods and supplies merchant wholesalers
Fish and seafood merchant wholesalers
Other grocery and related products merchant wholesalers
Fish and seafood markets
Sporting goods stores
Other direct selling establishments
Marinas
Miscellaneous
Total

Tax share (%)
12.6
1.1
12.1
30.1
0.1
30.2
4.2
4.6
0.1
1.3
0.7
2.9
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.

Harvesters

Wholesale dealers

Processors

Intermediate
demand other
than processing

Final
consumers

Intermediate
demand

Exports

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 ( i ) 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

Piks =

Ciks
Rks

(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

WCks

(8)

∑WC

Altogether, the survey portion of the production function for all vessel classifications (k)
and all expenditure categories (i) is given by

Piks

WCks

(9)

∑WC

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

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 at
this time supports this assumption. As improved data for other species groups are added, these
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).

Based on data of landings by license type in 2006 supplied by M. Grooms, ODFW, Salem.
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)
Captain
Crew
Fuel, lubricants
Food, crew provisions
Ice
Bait
Repair and maintenance: vessel,
gear, equipment
Insurance
Interest and financial services
Purchases of permits
Leasing of permits
Moorage
Landings taxes
Other miscellaneous
Proprietary income
Total (%)

Expenditure categories (column
list repeated from above)
Captain
Crew
Fuel, lubricants
Food, crew provisions
Ice
Bait
Repair and maintenance: vessel,
gear, and equipment
Insurance
Interest and financial services
Purchases of permits
Leasing of permits
Moorage
Landings taxes
Other miscellaneous
Proprietary income
Total (%)

Mother ship
catcher/
processor
—
—
—
—
—
—
—

Alaska
—
—
—
—
—
—
—

—
—
—
—
—
—
—
—

Shrimper
20.1
20.2
9.3
1.8
1.0
2.4
15.5
3.8
1.1
1.1
1.0
1.3
2.0
5.0
14.5
100.0

Pacific
whiting
trawler
14.3
18.4
12.0
1.4
0.1
0.4
19.8

Large
groundfish
trawler
18.9
20.9
12.4
1.1
1.9
1.2
18.2

Small
groundfish
trawler
18.9
20.9
12.4
1.1
1.9
1.2
18.2

Sablefish
fixed
gear
18.2
33.6
4.5
1.6
0.3
4.5
8.0

Other
groundfish
fixed gear
30.1
18.1
12.0
2.8
0.7
5.6
17.2

Migratory
liner
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Pelagic
netter
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Migratory
netter
20.1
20.2
9.3
1.8
1.0
2.4
15.5

*
*
1.0
0.0
0.3
3.7
5.0
13.9
100.0

5.7
1.7
1.8
1.2
0.8
4.1
5.0
5.2
100.0

5.7
1.7
1.8
1.2
0.8
1.1
5.0
8.2
100.0

2.2
0.9
0.6
5.8
1.0
0.9
5.0
12.9
100.0

1.0
1.0
0.5
0.1
2.0
0.6
5.0
3.4
100.0

3.8
1.1
1.1
1.0
1.3
2.0
5.0
14.5
100.0

Crabber
17.3
22.7
5.7
1.1
0.5
3.1
12.0

Salmon
troller
30.2
12.1
11.6
4.0
1.8
1.4
20.3

Salmon
netter
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Other
netter
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Lobster
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Diver
20.1
20.2
9.3
1.8
1.0
2.4
15.5

Other
>15,000
*
*
*
*
*
*
*

Other
<15,000
10.8
1.9
11.1
2.1
0.7
0.3
9.5

3.1
0.5
0.7
0.4
0.7
1.0
5.0
26.2
100.0

2.7
1.4
1.5
0.0
3.1
1.3
5.0
3.6
100.0

3.8
1.1
1.1
1.0
1.3
2.0
5.0
14.5
100.0

*
*
*
*
*
*
*
*
100.0

1.2
0.5
0.8
0.0
3.3
0.7
5.0
52.1
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
Ice
Packaging, boxes
Shipping
Storage
Advertising
Rent
Repair and maintenance, building
Vehicle
Utilities, electric
Utilities, gas
Utilities, telephone
Insurance
Professional fees
Building principal payment
Interest payment, building
Bank service charge
Taxes
Employee compensation
Proprietary income
Total

Seafood wholesale dealer (%)
2.80
2.70
4.10
14.70
4.00
6.80
6.90
4.10
1.37
1.37
1.37
4.10
0.70
4.00
1.40
0.08
2.12
33.35
4.05
100.00

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.

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

See Census Bureau county business patterns, online at http://www.census.gov/econ/cbp/index.html.
Because earnings per employee was not reported for Oregon, the Oregon models utilize the $36,057 weighted
average earnings.
16

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.

Table 13. IMPLAN tables (adapted from Steinback and Thunberg 2006).
Table name

Description

*Industry/Commodity Codes
*Type Codes
Margins Codes
*U.S. Absorption
*U.S. Absorption Totals
*U.S. Byproducts
*SACommodity Sales
*SAEmployment
*SAFinal Demands
*SAForeign Exports
*SAOutput
*SAValue Added
SA Transfers
*Observed RPCs
*RPC Methods
Margins
*Deflators
General Information
Model Specs.
Multiplier Specs.
SARatios
IMCommodity Transactions
IMEvents
IMFactor Transactions
IMGroups
IMIndustry Transactions
IMInstitutions Transactions
IMMargins
IMProjects
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
rptEC Multipliers
rptEmployment Multipliers
rptIBT Multipliers
rptOPTI Multipliers
rptOutput Multipliers
rptPersonal Income Multipliers
rptPropInc Multipliers
rptTotal VA Multipliers
rptSAFinal Demands
rptSAIndustry Data
SAM Rollup
Tax Impacts
Type Code Rollup
CGE Account

Codes (modified)
Codes
Raw input data (modified)

Raw input study area data
Raw input data (modified)
Raw input data
Model-building information
Ratios for impact and multiplier calculations
Impact report data (empty before impact analysis)

Output/report data for regional I-O model (empty before impact analysis)

Output reports

Data from SAFinal Demands and SAForeign Exports (modified)
Data from SAOutput, SAEmployment & SAValue Added (modified)
SAM report data
Tax report data
Type code report data
Output data for computable general equilibrium models

*The construction of IO-PAC entailed modifying the table.

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.

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.

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
⎤
⎡⎛ K
⎞
⎢ ⎜ ∑ ΔLk ⎟(0.3) ⎥
K
k
⎠
⎥ − ⎛⎜ ∑ ΔL ⎞⎟(0.3)
ΔWS = ⎢ ⎝
k
⎥ ⎝ k
⎢
0.84
⎠
⎥
⎢
⎦
⎣

(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
⎡⎛ K
⎞ ⎤
⎢ ⎜ ∑ ΔLk ⎟( p ) ⎥
⎠ ⎥
ΔPS = ⎢ ⎝ k
⎢ (1 − m) ⎥
⎢
⎥
⎣
⎦

(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

Table 14. Impact of reduced harvest among sablefish fixed gear vessels.
NAICS code and industry
11 Ag, forestry, fish, and hunting
21 Mining
22 Utilities
23 Construction
31–33 Manufacturing
42 Wholesale trade
48–49 Transportation and warehousing
44–45 Retail trade
51 Information
52 Finance and insurance
53 Real estate and rental
54 Professional-scientific and tech services
55 Management of companies
56 Administrative and waste services
61 Educational services
62 Health and social services
71 Arts-entertainment and recreation
72 Accommodation and food services
81 Other services
92 Government and non-NAICS
Sablefish fixed gear
Bait ship
Wholesale seafood
Total

Aggregated output impact report (2009 dollars)
Direct Indirect Induced
Total
0
–9,189
–4,005
–13,194
0
–2,229
–2,112
–4,341
0
–8,096
–9,876
–17,972
0
–7,388
–10,325
–17,713
–530,932
–38,810
–72,538
–642,279
0
–93,158
–33,725
–126,883
0
–23,552
–15,870
–39,421
0
–18,719
–65,957
–84,676
0
–9,329
–21,692
–31,021
0
–28,451
–51,503
–79,954
0
–15,959
–30,963
–46,922
0
–30,340
–29,408
–59,748
0
–33,378
–7,393
–40,771
0
–10,766
–13,325
–24,091
0
–167
–8,892
–9,059
0
–7
–79,517
–79,524
0
–7,256
–8,416
–15,672
0
–4,139
-30,893
–35,032
0
–7,053
–23,247
–30,300
0
–5,298 –110,492
–115,790
–500,000
0
0
–500,000
0
–22,309
0
–22,309
–28,571
0
0
–28,571
–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.

Table 14 continued horizontally. Impact of reduced harvest among sablefish fixed gear vessels.
NAICS code and industry
(column list repeated from previous page)
11 Ag, forestry, fish, and hunting
21 Mining
22 Utilities
23 Construction
31–33 Manufacturing
42 Wholesale trade
48–49 Transportation and warehousing
44–45 Retail trade
51 Information
52 Finance and insurance
53 Real estate and rental
54 Professional-scientific and tech services
55 Management of companies
56 Administrative and waste services
61 Educational services
62 Health and social services
71 Arts-entertainment and recreation
72 Accommodation and food services
81 Other services
92 Government and non-NAICS
Sablefish fixed gear
Bait ship
Wholesale seafood
Total

Aggregated income impact report (2009 dollars)
Direct Indirect Induced
Total
0
–1,503
–1,417
–2,919
0
–1,160
–1,098
–2,258
0
–3,613
–5,195
–8,808
0
–3,431
–5,526
–8,957
–105,975
–7,276
–16,613
–129,864
0
–49,052
–17,758
–66,810
0
–13,888
–8,489
–22,378
0
–10,078
–34,885
–44,961
0
–4,282
–9,862
–14,144
0
–16,076
–27,855
–43,930
0
–8,674
–17,159
–25,833
0
–15,844
–16,241
–32,084
0
–19,737
–4,371
–24,108
0
–6,528
–8,181
–14,710
0
–95
–5,315
–5,410
0
–4
–50,076
–50,080
0
–3,852
–4,693
–8,545
0
–2,141
–14,488
–16,628
0
–3,416
–11,813
–15,229
0
–2,797
–89,935
–92,732
–356,014
0
0
–356,014
0
-8,709
0
–8,709
–11,828
0
0
–11,828
–473,817 –182,152 –350,970 –1,006,939

Aggregated employment impact report
(full and part-time)
Direct
Indirect Induced
Total
0
–0.2
0
–0.2
0
0
0
0
0
0
0
0
0
–0.1
–0.1
–0.1
–1.7
–0.1
–0.2
–1.9
0
–0.5
–0.2
–0.6
0
–0.2
–0.1
–0.3
0
–0.2
–0.8
–1.0
0
0
–0.1
–0.1
0
–0.1
–0.2
–0.3
0
–0.1
–0.2
–0.2
0
–0.2
–0.2
–0.4
0
–0.1
0
–0.2
0
–0.2
–0.2
–0.4
0
0
–0.2
–0.2
0
0
–0.8
–0.8
0
–0.1
–0.1
–0.2
0
–0.1
–0.5
–0.5
0
–0.1
–0.4
–0.4
0
0
–0.6
–0.6
–14.2
0
0
–14.2
0
0
0
0
–0.2
0
0
–0.2
–16.1
–2.1
–4.7
–23.0

Table 15. Impact of reduced sablefish harvest using fixed gear (commodity scenario).
NAICS code and industry
11 Ag, forestry, fish, and hunting
21 Mining
22 Utilities
23 Construction
31–33 Manufacturing
42 Wholesale trade
48–49 Transportation and warehousing
44–45 Retail trade
51 Information
52 Finance and insurance
53 Real estate and rental
54 Professional-scientific and tech services
55 Management of companies
56 Administrative and waste services
61 Educational services
62 Health and social services
71 Arts-entertainment and recreation
72 Accommodation and food services
81 Other services
92 Government and non-NAICS
Pacific whiting trawler
Large groundfish trawler
Small groundfish trawler
Sablefish fixed gear
Other groundfish fixed gear
Pelagic netter
Migratory liner
Shrimper
Crabber
Salmon troller
Salmon netter
Lobster vessel
Other, more than $15,000
Other, less than $15,000
Bait ship
Wholesale seafood
Total

Aggregated output impact report (2009 dollars)
Direct
Indirect Induced
Total
0
–9,185
–3,904
–13,089
0
–2,438
–2,061
–4,499
0
–8,137
–9,634
–17,771
0
–6,999
–10,205
–17,203
–530,932
–41,488
–70,745
–643,166
0
–95,544
–32,872
–128,416
0
–23,531
–15,477
–39,008
0
–20,302
–64,249
–84,551
0
–9,437
–21,147
–30,584
0
–29,431
–50,193
–79,625
0
–16,116
–30,182
–46,299
0
–30,542
–28,696
–59,239
0
–33,529
–7,205
–40,734
0
–10,877
–13,004
–23,882
0
–170
–8,663
–8,833
0
–7
–77,454
–77,461
0
–7,310
–8,199
–15,508
0
–4,170
–30,104
–34,274
0
–7,081
–22,659
–29,739
0
–5,317 –108,418
–113,735
–4,428
0
0
–4,428
–920
0
0
–920
–1,219
0
0
–1,219
–253,732
0
0
–253,732
–21,177
0
0
–21,177
–1,302
0
0
–1,302
–5,266
0
0
–5,266
–721
–721
0
0
–182,366
0
0
–182,366
–10,423
0
0
–10,423
–369
0
0
–369
–565
0
0
–565
–3,926
0
0
–3,926
–13,584
0
0
–13,584
0
–18,839
0
–18,839
–28,571
0
0
–28,571
–1,059,503 –380,451 –615,073 –2,055,027

Table 15 continued horizontally. Impact of reduced sablefish harvest using fixed gear
(commodity scenario).
NAICS code and industry
(column list repeated from previous page)
11 Ag, forestry, fish and hunting
21 Mining
22 Utilities
23 Construction
31–33 Manufacturing
42 Wholesale trade
48–49 Transportation and warehousing
44–45 Retail trade
51 Information
52 Finance and insurance
53 Real estate and rental
54 Professional-scientific and tech services
55 Management of companies
56 Administrative and waste services
61 Educational services
62 Health and social services
71 Arts-entertainment and recreation
72 Accommodation and food services
81 Other services
92 Government and non-NAICS
Pacific whiting trawler
Large groundfish trawler
Small groundfish trawler
Sablefish fixed gear
Other groundfish fixed gear
Pelagic netter
Migratory liner
Shrimper
Crabber
Salmon troller
Salmon netter
Lobster vessel
Other, more than $15,000
Other, less than $15,000
Bait ship
Wholesale seafood
Total

Aggregated income impact report (2009 dollars)
Direct
Indirect Induced
Total
0
–1,502
–1,381
–2,882
0
–1,269
–1,072
–2,340
0
–3,632
–5,068
–8,701
0
–3,252
–5,465
–8,718
–105,975
–7,629
–16,200
–129,804
0
–50,309
–17,308
–67,617
0
–13,859
–8,280
–22,140
0
–10,929
–33,981
–44,911
0
–4,331
–9,615
–13,946
0
–16,439
–27,147
–43,586
0
–8,763
–16,725
–25,488
0
–15,954
–15,850
–31,804
0
–19,825
–4,260
–24,086
0
–6,597
–7,985
–14,583
0
–97
–5,178
–5,275
0
–4
–48,777
–48,781
0
–3,881
–4,572
–8,453
0
–2,157
–14,118
–16,274
0
–3,430
–11,514
–14,943
0
–2,809
–88,384
–91,194
–2,101
0
0
–2,101
–442
0
0
–442
–620
0
0
–620
–180,664
0
0
–180,664
–11,028
0
0
–11,028
–741
0
0
–741
–2,997
0
0
–2,997
–411
0
0
–411
–122,782
0
0
–122,782
–4,947
0
0
–4,947
–210
0
0
–210
–322
0
0
–322
–1,433
0
0
–1,433
–8,909
0
0
–8,909
0
–7,354
0
–7,354
–11,828
0
0
–11,828
–455,411 –184,024 –342,881
–982,317

Aggregated employment impact report
(full and part-time)
Direct
Indirect
Induced
Total
0
–0.2
0
–0.2
0
0
0
0
0
0
0
0
0
0
–0.1
–0.1
–1.7
–0.1
–0.1
–1.9
0
–0.5
–0.2
–0.6
0
–0.2
–0.1
–0.3
0
–0.2
–0.7
–1.0
0
0
–0.1
–0.1
0
–0.1
–0.2
–0.3
0
–0.1
–0.1
–0.2
0
–0.2
–0.2
–0.4
0
–0.1
0
–0.2
0
–0.2
–0.2
–0.4
0
0
–0.1
–0.1
0
0
–0.8
–0.8
0
–0.1
–0.1
–0.2
0
–0.1
–0.5
–0.5
0
–0.1
–0.4
–0.4
0
0
–0.6
–0.6
0
0
0
0
0
0
0
0
–0.1
0
0
–0.1
–7.2
0
0
–7.2
–0.7
0
0
–0.7
0
0
0
0
–0.2
0
0
–0.2
0
0
0
0
–3.8
0
0
–3.8
–0.8
0
0
–0.8
0
0
0
0
0
0
0
0
0
0
0
0
–7.1
0
0
–7.1
0
0
0
0
–0.2
0
0
–0.2
–21.9
–2.2
–4.6
–28.7

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.

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

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.

References
California Codes. 2009. Division 6. Part 3 Commercial fishing. Chapter 1 generally. Article 7.5
Landing taxes, section 8040–8070. Online at http://www.leginfo.ca.gov/cgi-bin/displaycode
?section=fgc&group=08001-09000&file=8040-8070 [accessed 11 March 2011].
CFR (Code of Federal Regulations). 2009. 50 CFR § 600.1102. Pacific Coast groundfish fee. Online at
http://ecfr.gpoaccess.gov/cgi/t/text/text-idx?c=ecfr&sid=663df55facbaecff8457ed4696b60a2e&
rgn=div8&view=text&node=50:8.0.1.1.1.13.1.3&idno=50 [accessed 1 June 2011].
Federal Register. 2003. Vol. 68, No. 213, Tuesday, 4 November 2003. Online at http://edocket.access
.gpo.gov/2003/03-27712.htm [accessed 1 June 2011].
Hewings, G. 1985. Regional input-output analysis. Sage Publications, Beverly Hills, CA.
Kirkley, J. E., W. Ryan, and J. Duberg. 2004. Assessing the economic importance of commercial
fisheries in the mid-Atlantic region: A user’s guide to the mid-Atlantic input/output model.
NOAA Cooperative Marine Education and Research Award. Virginia Institute of Marine
Science, Gloucester Point.
Lian, C. 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.
Lian, C. In press. West Coast open access groundfish and salmon troller survey: Protocol and results for
2005 and 2006. U.S. Dept. Commer., NOAA Tech. Memo NMFS-NWFSC.
MSFCMA (Magnuson-Stevens Fishery Conservation and Management Act). 2009. Public Law 94-265.
Online at http://www.nmfs.noaa.gov/msa2005/docs/MSA_amended_msa%20_20070112
_FINAL.pdf [accessed 1 June 2011].
Miller, R. E., and P. D. Blair. 1985. Input-output analysis: Foundations and extensions. Prentice-Hall,
London.
NMFS (National Marine Fisheries Service). 2009. Pacific Coast groundfish fee collection report. NMFS
Office of Management and Budget. Online at http://www.nmfs.noaa.gov/mb/financial
_services/buyback.htm [accessed 28 February 2011].
ODFW (Oregon Dept. Fish and Wildlife). 2006. 2006 Synopsis Oregon Commercial Fishing
Regulations. Online at http://oregonsalmon.org/2006%20OR%20commercial%20regs.pdf
[accessed 11 March 2011].
ORS (Oregon Revised Statutes). 2009. Chapter 508.505. Licenses and permits. Additional fees based
on volume of fish at time of landing; exceptions. Online at http://www.leg.state.or.us/ors
/508.html [accessed 11 March 2011].
PFMC (Pacific Fishery Management Council). 2004. Acceptable biological catch and optimum yield
specification and management measures for the 2005–2006 Pacific Coast groundfish fishery.
Final environmental impact statement and regulatory analysis. PFMC, Portland, OR.

Radtke, H. D., and S. W. Davis. 2000. Description of the U.S. West Coast commercial fishing fleet and
seafood processors. Report prepared for Pacific States Marine Fisheries Commission, Portland,
OR.
RCW (Revised Code of Washington). 2009. Title 82 Excise taxes, Chapter 82.27 Tax on enhanced food
fish. Online at http://apps.leg.wa.gov/rcw/default.aspx?cite=82.27 [accessed 11 March 2011].
Richardson, H. 1985. Input-output and economic base multipliers: Looking backward and forward. J.
Regional Sci. 25:607–661.
Steinback, S. R. 2004. Using ready-made regional input-output models to estimate backward-linkage
effects of exogenous output shocks. The Rev. Reg. Stud. 34(1):57–71.
Steinback, S. R., and E. M. Thunberg. 2006. Northeast regional commercial fishing input-output model.
U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NEFSC-188.
Seung, C. K., and E. C. Waters. 2005. A review of regional economic models for Alaska fisheries. U.S.
Dept. Commer., Alaska Fisheries Science Center Processed Rep. 2005-01.
Seung, C. K., and E. C. Waters. 2006. A review of regional economic models for fisheries management
in the U.S. Mar. Resour. Econ. 21:101–124.
Upton, H. F. 2008. Commercial fishery disaster assistance. Congressional Research Service order code
RL34209. Online at http://nationalaglawcenter.org/assets/crs/RL34209.pdf [accessed 1 June
2011].
Watson, P., J. Wilson, S. Davies, and D. Thilmany. 2008. Determining economic contributions in a
recreational industry: An application to Colorado’s golf industry. J. Sport. Econ. 9(6):571–591.
Watson, P., J. Wilson, D. Thilmany, and S. Winter. 2007. Determining economic contributions and
impacts: What is the difference and why do we care? J. Reg. Anal. Policy 37(2):140–146.

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
142
390
392
393
394
396
407

Title
Petroleum refineries
Wholesale trade
Rail transportation
Water transportation
Truck transportation
Pipeline transportation
Gasoline stations
Total

Proportion
0.393794
0.361077
0.006754
0.005192
0.008658
0.004953
0.219571
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
1
2
3
4
5
6
10
12
15
26
46
47
48

Title
Oilseed farming
Grain farming
Vegetable and melon farming
Tree nut farming
Fruit farming
Greenhouse and nursery production
All other crop farming
Poultry and egg production
Forest nurseries, forest products, and timber
Other nonmetallic mineral mining
Dog and cat food manufacturing
Other animal food manufacturing
Flour milling
57

Proportion
6.36E-05
0.000379
0.022642
0.000749
0.014302
0.000652
0.000203
0.006205
0.000137
1E-05
0.016556
0.002251
0.002340

Groceries list continued
Sector Title
49
Rice milling
51
Wet corn milling
52
Soybean processing
54
Fats and oils refining and blending
55
Breakfast cereal manufacturing
56
Sugar manufacturing
57
Confectionery manufacturing from cacao beans
58
Confectionery manufacturing from purchased chocolate
59
Nonchocolate confectionery manufacturing
60
Frozen food manufacturing
61
Fruit and vegetable canning and drying
62
Fluid milk manufacturing
63
Creamery butter manufacturing
64
Cheese manufacturing
65
Dry, condensed, and evaporated dairy products
66
Ice cream and frozen dessert manufacturing
67
Animal, except poultry, slaughtering
68
Meat processed from carcasses
70
Poultry processing
72
Frozen cakes and other pastries manufacturing
73
Bread and bakery product, except frozen, manufacturing
74
Cookie and cracker manufacturing
75
Mixes and dough made from purchased flour
76
Dry pasta manufacturing
77
Tortilla manufacturing
78
Roasted nuts and peanut butter manufacturing
79
Other snack food manufacturing
80
Coffee and tea manufacturing
81
Flavoring syrup and concentrate manufacturing
82
Mayonnaise, dressing, and sauce manufacturing
83
Spice and extract manufacturing
84
All other food manufacturing
85
Soft drink and ice manufacturing
171
Other miscellaneous chemical product manufacturing
390
Wholesale trade
391
Air transportation
392
Rail transportation
393
Water transportation
394
Truck transportation
399
Couriers and messengers
400
Warehousing and storage
402
Furniture and home furnishings stores
404
Building material and garden supply stores
405
Food and beverage stores
407
Gasoline stations
410
General merchandise stores
411
Miscellaneous store retailers
500
Noncomparable imports
Total
58

Proportion
0.001427
0.002738
7.65E-05
0.004478
0.016116
0.005154
0.003429
0.015461
0.013150
0.035386
0.051314
0.040036
0.002148
0.014711
0.008433
0.005012
0.057514
0.054934
0.027721
0.005509
0.046437
0.016265
0.009065
0.003576
0.002269
0.004765
0.017670
0.012974
0.005455
0.008480
0.007112
0.018899
0.060190
0.000167
0.098877
0.000487
0.002832
0.001729
0.013268
0.001554
0.000889
9.66E-05
0.001584
0.196583
0.016591
0.006296
0.008340
0.006314
1.000000

Ice expenses were allocated based on the IMPLAN default margin table for sector 85
(soft drink and ice manufacturing).
Sector
85
390
392
393
394
405
407

Title
Soft drink and ice manufacturing
Wholesale trade
Rail transportation
Water transportation
Truck transportation
Food and beverage stores
Gasoline stations
Total

Proportion
0.628331
0.102750
0.000222
3.14E-05
0.006453
0.193154
0.069058
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
16
43
68
85
103
125
126
129
130
131
132
133
136
138
142
145
163
164
170
172
177
179
278
325
333
338
350
383
390
391
392
393
394

Title
Fishing
Maintenance and repair of nonresidential buildings
Meat processed from carcasses
Soft drink and ice manufacturing
Other miscellaneous textile production
Paper and paperboard mills
Paperboard container manufacturing
Coated and laminated paper
Coated and uncoated paper bag manufacturing
Die-cut paper office supplies manufacturing
Envelope manufacturing
Stationery and related products
Manifold business forms printing
Blank-book and loose-leaf binders
Petroleum refineries
Petroleum lubricating oil and gas manufacturing
Soap and other detergent manufacturing
Polish and other sanitation goods manufacturing
Photographic film and chemicals
Plastics, packaging materials
Plastics, plumbing fixtures
Tire manufacturing
AC, refrigeration and forced air
Electric lamp bulb and part manufacturing
Electric power and specialty transmission
Primary battery manufacturing
Motor vehicle parts manufacturing
Office supplies except paper manufacturing
Wholesale trade
Air transportation
Rail transportation
Water transportation
Truck transportation
59

Proportion
0.001894
0.102952
0.000061
0.010734
0.007470
0.000970
0.000022
0.000017
0.000212
0.000028
0.000016
0.000067
0.000038
0.000006
0.022730
0.047874
0.000744
0.000303
0.000008
0.001415
0.000044
0.000120
0.000171
0.000097
0.000407
0.000214
0.000715
0.000027
0.051741
0.000780
0.006179
0.008966
0.006553

Default fishing list continued
Sector
Title
396
Pipeline transportation
397
Scenic and sightseeing transport
398
Postal service
401
Motor vehicle and parts dealers
402
Furniture and home furnishings
403
Electronics and appliance stores
404
Building material and garden supplies
405
Food and beverage stores
406
Health and personal care stores
407
Gasoline stations
408
Clothing and clothing accessory
409
Sporting goods, hobby, book stores
410
General merchandise stores
411
Miscellaneous store retailers
412
Nonstore retailers
425
Nondepository credit intermediaries
426
Securities, commodity contracts
427
Insurance carriers
430
Monetary authorities and depository institutions
431
Real estate
432
Automotive equipment rental
434
Machinery and equipment rental
435
General and consumer goods rental
437
Legal services
439
Architectural and engineering services
445
Environmental and other technical services
447
Advertising and related services
450
All other miscellaneous professions
457
Investigation and security services
459
Other support services
478
Other amusement, gambling, and recreation industries
479
Hotels and motels, including casinos
500
Noncomparable imports
Total

Proportion
0.000325
0.055514
0.000641
0.000350
0.000083
0.000100
0.000153
0.000257
0.000149
0.000083
0.000116
0.000042
0.000265
0.000146
0.000107
0.000254
0.002401
0.009664
0.005333
0.000403
0.000259
0.012181
0.000055
0.000292
0.000577
0.001204
0.000650
0.000424
0.001708
0.000468
0.010884
0.000023
0.001524
1.000000

Repair and maintenance expenses for vessel gear and equipment were allocated to sector
357, which includes ship building and repairing.
Sector
357

Title
Ship building and repairing
Total

Proportion
1.00
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
478

Title
Other amusement, gambling, and recreation industries
Total

Proportion
1.00
1.00

Insurance expenses for vessels were allocated to sector 427, which includes
establishments primarily engaged in underwriting and assuming the risk of insurance policies.
Sector
427

Title
Insurance carriers
Total

Proportion
1.00
1.00

Interest and financial services were allocated to sector 430, which includes
establishments primarily engaged in financial services.
Sector
430

Title
Monetary authorities and depository credit institutions
Total

Proportion
1.00
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
Value-added

Title
Indirect business taxes
Total

Proportion
1.00
1.00

Payments received by vessel owners as income were classified as value-added sector,
proprietary income.
Sector
Value-added

Title
Proprietary income
Total

Proportion
1.00
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
100
103
125
126
130
163
164
172
177
179
278
286

Title
Curtain and linen mills
Other miscellaneous textiles
Paper and paperboard mills
Paperboard container manufacturing
Coated and uncoated paper bag manufacturing
Soap and other detergent manufacturing
Polish and other sanitation goods manufacturing
Plastics packaging materials
Plastic plumbing fixtures and all other plastics
Tire manufacturing
Air conditioning, refrigeration
Other engine equipment manufacturing

Proportion
0.008560
0.007716
0.040025
0.180838
0.023750
0.047259
0.040146
0.054372
0.008319
0.006631
0.007234
0.074987

Other vessel expenditures list continued
Sector
Title
289
Air and gas compressor manufacturing
321
Watch, clock, and other measuring and controlling devices
325
Electric lamp bulb and part manufacturing
333
Electric power and specialty transformer manufacturing
338
Primary battery manufacturing
350
Motor vehicle parts manufacturing
392
Rail transportation
390
Wholesale trade
404
Building material and gardening supplies
405
Food and beverage stores
407
Gasoline stations
410
General merchandise stores
411
Miscellaneous store retailers
Total

Proportion
0.004581
0.007475
0.012176
0.005184
0.010247
0.047500
0.001000
0.161000
0.001000
0.185000
0.013000
0.014000
0.038000
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
Value-added

Title
Indirect business taxes
Total

Proportion
1.00
1.00

Wages and salaries of employees (captain and crew) were allocated to the value-added
sector, employee compensation.
Sector
Value-added

Title
Employee compensation
Total

Proportion
1.00
1.00

Vessel residuals were allocated to the value-added sector, proprietary income.
Sector
Value-added

Title
Proprietary income
Total

Proportion
1.00
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
447

Title
Advertising and related services
Total

Proportion
1.00
1.00

Packaging (boxes) expenses were allocated using the default IMPLAN margin table for
sector 126 (paperboard container manufacturing).
Sector
126
390
391
392
394
411

Title
Paperboard container manufacturing
Wholesale trade
Air transportation
Rail transportation
Truck transportation
Miscellaneous store retailers
Total

Proportion
0.581083
0.016356
0.000463
0.026539
0.130381
0.245178
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
431

Title
Real estate
Total

Proportion
1.00
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
458

Title
Services to buildings and dwellings
Total

Proportion
1.00
1.00

Shipping expenses were allocated to sector 394, comprised of establishments primarily
engaged in providing general freight trucking.
Sector
394

Title
Truck transportation
Total

Proportion
1.00
1.00

Storage expenses were allocated to sector 400, comprised of establishments primarily
engaged in operating warehousing and storage facilities for general merchandise.
Sector
400

Title
Warehousing and storage
Total

Proportion
1.00
1.00

Electrical utility expenses were allocated to sector 30, comprised of establishments
primarily engaged in generating, transmitting, or distributing electric power.
Sector
30

Title
Power generation and supply
Total

Proportion
1.00
1.00

Natural gas utility expenses were allocated to sector 31, comprised of establishments
primarily engaged in transmitting and distributing gas to final consumers.
Sector
31

Title
Natural gas distribution
Total

Proportion
1.00
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
422

Title
Telecommunications
Total

Proportion
1.00
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 PB2011102712.
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).

File Type	application/pdf
File Title	NOAA Technical Memorandum NMFS-NWFSC-111. Description of the Input-Output Model for Pacific Coast Fisheries
Author	Jerry Leonard and Phillip Watson
File Modified	2017-07-11
File Created	2011-07-22