Input-Output Model for Pacific Coast Fisheries, 2013 Revisions and Extensions

IOPAC_SSC_Econ_Review_April_NWC.pdf

Economic Surveys for U.S. Commercial Fisheries

Input-Output Model for Pacific Coast Fisheries, 2013 Revisions and Extensions

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Input-Output Model for Pacific
Coast Fisheries, 2013 Revisions
and Extensions
Jerry Leonard
Northwest Fisheries Science Center
Fishery Resource Analysis and Monitoring Division
2725 Montlake Boulevard East
Seattle, Washington 98112

April 2013

Acknowledgments
There are several individuals to thank for their contributions to this effort. We thank
Scott Steinback, Northeast Fisheries Science Center, for advice in modeling economic effects of
recreational fishing; Brad Stenberg, Pacific Fisheries Information Network (PacFIN), who
supplied fish ticket landings data and consultations about PacFIN related data issues; Erin
Steiner and Abigail Hartley for assistance with EDC data; and Carl Lian for assistance with the
voluntary cost earnings survey data.

Abbreviations and Acronyms
AKFIN
BEA
CDFG
EDC
IMPLAN
IO
IO-PAC
NAICS
NERIOM
NMFS
NWFSC
ODFW
PSMFC
PacFIN
WDFW
WDOR

Alaska Fisheries Information Network
Bureau of Economic Analysis
California Department of Fish and Game
Economic Data Collection Program
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 States Marine Fisheries Commission
Pacific Fisheries Information Network
Washington Department of Fish and Wildlife
Washington Department of Revenue

iii

1. Introduction
The NWFSC’s Input-Output model for Pacific Coast Fisheries (IO-PAC) is designed to
estimate the changes in economic contributions and economic impacts resulting from policy,
environmental, or other changes that affect fishery harvest. IO-PAC was built by customizing
the Impact Analysis for Planning (IMPLAN) regional input-output software. The original
methodology employed in developing this model was similar to that used in the Northeast
Fisheries Science Center’s Northeast Region Commercial Fishing Input-Output Model
(Steinback and Thunberg, 2006). The development and design of IO-PAC is documented in
detail in Leonard and Watson (2011). This paper presents recent updates to IO-PAC. The
updates presented are part of an ongoing effort to continually improve the IO-PAC model with
the latest available data and improvements in regional impact modeling capabilities. The
updates of IO-PAC include incorporating more recent available data, the addition of a
recreational fishing component, the addition of separate catcher processor and mothership
sectors, and revisions to the model construction.
As it stands currently, the model is not in its anticipated state for use in the 2015-2016
groundfish harvest specifications process. Several data sources that the model uses will be
revised between the time of this writing and when the model is used in the groundfish harvest
specifications process. Further discussion of the planned data updates is contained below, but in
brief the planed updates include incorporating data collected through the Economic Data
Collection program (EDC), the 2011 Marine Recreational Expenditure Survey, the 2009 and
2010 Limited Entry Fixed Gear Survey, the 2011 and 2012 Open Access Survey. Additionally,
the planned updates will include 2012 Pacific Fisheries Information Network (PacFIN) fish
ticket data. Nevertheless, at the time of this writing, IO-PAC makes use of the most recent data
available, and the updates made since the first version of IO-PAC, provide insight into how these
upcoming data sources will be incorporated into the model.
The data updates made to date include the following. One, the underlying Impact
Analysis for Planning (IMPLAN) data is changed from the 2006 base year to 2010. Two, the
fish-ticket (landings) data from Pacific Fisheries Information Network (PacFIN) is changed from
2006 to 2010. Three, the commercial vessel production functions incorporate the latest data
from the voluntary Limited Entry and Open Access Surveys conducted by the Norwest Fisheries
Science Center. Four, it incorporates data collected as part of the EDC program for first
receivers and shorebased processors.
The addition of a recreational fishing component involves incorporating data collected on
marine recreational expenditures (Gentner and Steinback, 2006), charter vessel cost earnings
data collected by the Pacific States Marine Fisheries Commission and Southwest Fisheries
Science Center (Pacific States Marine Fisheries Commission, 2004) and the Northwest Fisheries
Science Center in 2006.

The revisions to IO-PAC construction are done to reduce effort involved in making
changes to fishing sector production functions over time and simplify the process of building
numerous port level models. 2010 IMPLAN data uses the Version 3 software update of
IMPLAN. The original version of IO-PAC modified IMPLAN Version 2 software.
Transitioning the unique fishing industry information in IO-PAC from IMPLAN Version 2 to
Version 3, provides numerous initial obstacles, but ultimately enables a more efficient method to
incorporate fishing sector production function changes and changing model study areas.

2. IMPLAN Data
IMPLAN collects, organizes, and econometrically estimates the data that is necessary to
construct regional economic impact models. 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 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
employment and wages covered by unemployment insurance data.
The current update to IO-PAC changes the underlying IMPAN data from 2006 to 2010.
The IMPLAN data are used in IO-PAC 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. A major revision in the industry
sectoring scheme was made in the 2008 IMPLAN data. In 2008 the IMPLAN data transitioned
to 440 unique industry sectors from the 509 used in 2006. This change necessitated a new
mapping of factor expenditures made by seafood harvesters and wholesalers into IMPLAN
sectors. The new mapping scheme for the 440 IMPLAN sectors is presented in detail in
Appendix A.

3. PacFIN Data
The current update changes the fish-ticket data utilized by IO-PAC from 2006 to 2010.
PacFIN data include fish ticket and vessel registration information that is supplied by California
Department of Fish and Game (CDFG), Oregon Department of Fish and Wildlife (ODFW), and
Washington Department of Fish and Wildlife (WDFW). Each time a commercial fishing vessel
lands fish along the West Coast, it is documented by a fish ticket. For all commercial landings
sold to shoreside 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. If a
5

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. These data, when aggregated into vessel classifications and commodity types,
comprise the total revenue or industry output estimates that are included in the model. PacFIN
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. 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 in 2010. Table 1 provides of a summary of the data that
is currently used in IO-PAC, and its application. For commercial fishing vessels, it indicates that
the PacFIN data are used in generating vessel production functions, estimates of total industry
output (revenue), and total vessel employment. For processors the data are used in generating
processor industry output and processor employment1.
The IO-PAC update makes two changes in how the PacFIN data are used in the model.
Previously, the length of the vessel, which is contained in PacFIN, was used in conjunction with
moorage rates by length at a sample of ports along the West Coast to estimate average annual
moorage expenditures by vessel classification. This approach to estimating moorage
expenditures is no longer necessary due to changes in the NWFSC’s cost earnings surveys. The
cost earnings surveys now directly query vessel owners about moorage expenditures.
Additionally, PacFIN data is no longer used exclusively to assign vessels to the Radtke and
Davis (2000) classification scheme. Because PacFIN contains fish-ticket data from only
shoreside landings made on the West Coast, there are no landings data for Alaska fisheries
vessels and at-sea vessels (motherships and catcher processors). In the last version of IO-PAC
both of these vessel classifications were blank, so impacts could not be estimated for these
sectors. In this update vessels are assigned to the Alaska category by using information derived
from the Alaska Fisheries Information Network (AKFIN). For vessel IDs that appear in PacFIN,
personnel from the Pacific States Marine Fishery Commission (PSMFC) provided data that
indicates whether a vessel had landings in Alaska in 2008. Vessels with landings in Alaska were
assigned to the Alaska fisheries vessel category.
While the PacFIN data currently included in IO-PAC is from 2010, the data will be
updated to 2012 prior to the use of the model for the 2015-2016 groundfish harvest specifications
process. The model’s usage for groundfish specifications is expected to occur around the end of
2013. Table 1 presents the timeframe of expected data changes. The table indicates that the
PacFIN data is expected to change to 2012 in the third quarter of 2013.

For a detailed discussion of how the PacFIN data fulfills these roles, see Leonard and Watson (2010).

Table 1. IO-PAC data sources and applications

Data Year
Expected Date
Application
Commercial Vessels
Production Functions
Vessel Industry Output
Vessel Employment

Open Access
Survey
(2009, 2008)

Limited Entry
Trawl Survey
(2007, 2008)

Limited Entry
Fixed Gear Survey
(2007, 2008)

Marine Rec.
Exp. Survey
(2006)

WA and OR
Charter Vessel
Survey (2006)

West Coast
Charter Vessel
Survey (2000)

EDC DATA
(2010)

2008

2006

2000

2010

Current

X
X

Processors
Production Functions
Processor Industry Output
Processor Employment

Recreational Fishing
Expenditures
Charter Prod. Functions
Charter Industry Output
Charter Employment
Non-Fishing Data

X
X
X

Table 1 (continued horizontally). IO-PAC data sources and applications

Data Year
Expected Date
Application
Commercial Vessels
Production Functions
Vessel Industry Output
Vessel Employment
Processors
Production Functions
Processor Industry Output
Processor Employment

IMPLAN

PacFIN Fish
Ticket

Limited Entry
Fixed Gear Survey
(2009, 2010)

Open Access Survey
(2011, 2012)

EDC Data
(2011)

PacFIN Fish
Ticket

2010

2011

2012

Current

2013 Q3

X
X
X

X
X

X
X
X

Recreational Fishing
Expenditures
Charter Prod. Functions
Charter Industry Output
Charter Employment
Non-Fishing Data

X
X

4. Commercial Fisheries Economic Data
Cost earnings surveys provide the data necessary to construct the commercial fishing
vessel and processor production functions. Since the last version of IO-PAC, the EDC program
has been established as a data source for IO-PAC. Previously, the model relied solely on the
voluntary limited entry trawl, limited entry fixed gear, and open access surveys for commercial
fishery cost data. Currently, the commercial vessel production functions still rely exclusively on
the most recent voluntary survey data. Following the schedule in Table 1, a transition will be
made to the EDC data for limited-entry trawl, catcher processors, motherships and shorebased
processors. For shorebased processors, processors, preliminary data from the EDC survey is
already incorporated into IO-PAC.

4.1. Voluntary Cost-Earnings Surveys
The vessel production functions are currently using data from the most recent voluntary
limited entry trawl survey, limited entry fixed gear survey, and open access survey. Since the
first version of IO-PAC was completed, all three surveys have been reprised. The updated
results have been incorporated into IO-PAC. Because of the expanded scope and increased
detail of the more recent surveys, incorporating the data has the added benefit of likely
increasing the accuracy of IO-PAC, especially for vessel classifications that were previously not
covered or partially covered. The expanded scope is the result of a changed target population of
the open access survey. The increased detail is the result of an increased number of cost
categories for all the voluntary surveys. These additional cost categories permit improved
specification of the production functions. Previous costs categories used in the model included
fuel and oil; food and crew provisions; ice; bait; repairs, maintenance, and improvements;
insurance; permit leases; permit purchases; interest and financial services; crew expense; and
captain expense. The new additional cost categories include moorage, enforcement, dues,
offloading, and trucking. 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 follows2.
The survey population for the limited entry trawl survey consisted of all vessels
with a limited entry trawl permit and at least $1,000 in landings in 2008. The survey collected
information for 2007 and 2008 through in-person interviews. There were 73 completed
responses out of a total of 127 vessels for a response rate of 57%. Using a modified version of
the vessel classification scheme suggested by Radtke and Davis (2000), shown in Table 3, the
2

For a more detailed description of the survey programs and summary statistics used in constructing the production
functions, see the forthcoming NOAA Technical Memoranda by Lian.

principle classification of respondents was large groundfish trawler, and other vessel
classifications covered were Alaska, whiting, crabber and shrimper.
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 2008. This survey also
collected information for 2007 and 2008, and used in-person interviews. There were 57
completed responses out of a total of 125 vessels for a response rate of 46%. The principle
classification of respondents was sablefish (Anoplopoma fimbria) fixed gear, and other vessel
classifications covered were Alaska, crabber, other groundfish fixed gear, and other < $15,000.
The survey population for the open access survey consisted of all commercial fishing
vessels that: 1) landed at least $1,000 of salmon, groundfish, crab or shrimp at West Coast ports
during 2008, 2) had at least one trip on which groundfish, salmon, crab or shrimp accounted for a
majority of revenue from landings, and 3) did not hold a limited entry permit. Survey data was
collected via in-person interviews and mail questionnaires. The population of targeted vessels
for the most recent survey was expanded considerably from the 2005 and 2006 version because
of the addition of crab and shrimp to the first two requirements. There were 1,712 vessels that
met the above three requirements. There were 1,098 vessels for which a telephone and address
was obtainable. There were 437 completed responses for a response rate of 39.8% among those
vessels where contact information was available. Responses came from vessels classified as
Alaska, crabber, sablefish fixed gear, other groundfish, salmon troller, salmon netter, shrimper,
and other less than $15,000.

4.2. Mandatory EDC Surveys
In January 2011, the West Coast groundfish trawl fishery transitioned to a new,
management approach known as a Catch Share Program. The Catch Share Program consists of
an individual fishing quota (IFQ) program for the shorebased trawl fleet and cooperative
programs for the at-sea mothership and catcher/processor trawl fleets. The economic benefits of
the West Coast groundfish trawl fishery and their distribution will likely change under trawl
rationalization. To monitor these changes, the rationalization program includes a mandatory
economic data collection program. Using data collected from industry members, the EDC
program monitors whether the goals of the Catch Share Program have been met. The EDC
program will also help meet the requirements of the Magnuson-Stevens Act for catch share
evaluation. The regulations detailing the Economic Data Collection program are available in
50CFR 660.114.
The EDC program collects vessel/plant characteristics, capitalized investments, annual
expenses, annual earnings, crew/labor payments, and quota and permit expenses from the
following types of businesses.
Limited Entry Trawl Catcher Vessels - All owners, lessees, and charterers of a catcher
vessel registered to a limited entry trawl endorsed permit.

Motherships - All owners, lessees, and charterers of a mothership vessel registered to a
mothership permit.
Catcher/Processors - All owners, lessees, and charterers of a catcher processor vessel
registered to a catcher/processor-endorsed limited entry trawl permit.
First Receivers/Shorebased Processors - All owners and lessees of a shorebased processor
that received round or headed-and-gutted IFQ species groundfish or whiting from a first
receiver, and all owners of a first receiver site license in 2011 and beyond.

The inclusion of data collected through the EDC program in IO-PAC is currently
underway. When fully implemented following the schedule in Table 1 the EDC data will be
used for several purposes in IO-PAC. For the shoreside trawl catcher vessel fleet, the EDC data
will replace the voluntary trawl survey data currently in use. Additionally, it will provide the
first cost earnings data to permit the inclusion of the at-sea fleet (motherships and catcher
processors) in the model. Lastly, it will provide the data necessary to replace the default
IMPLAN approach to generating shorebased processing employment, industry output (revenue),
and production function used in the previous version IO-PAC. The last of these purposes, is
currently operational in IO-PAC. The default IMPLAN processor approach used in the previous
version of IO-PAC had notable disadvantages, particularly that all species contained in IO-PAC
were limited to the same markup to develop processor impacts. Consequently, improving the
processor specification in IO-PAC was given priority.

5. The IO-PAC Model
Several aspects of the IO-PAC model are modified in the revision. To the existing vessel
classification scheme in IO-PAC, the revision adds vessel sectors for motherships, catcher
processors, and charter recreational fishing vessels. The underlying product flow assumptions
are changed. The commercial vessel production functions are changed through the inclusion of
more recent cost earnings data. Processor sector production functions and estimates of
appropriate processor markups for different species are altered through the use of EDC data.
Lastly, a recreational module is added to enable impact and contribution estimates of recreational
fishing.

5.1. Industry/Commodity Scheme
The revised industry classification scheme modifies the Radtke and Davis (2000) vessel
classification scheme by separating motherships and catcher processors and adding a sector for
recreational charter vessels. In the Radtke and Davis (2000) sector scheme motherships and
catcher processors are grouped together. In the revision they are separated into two industry
3

classifications. The addition of a sector for recreational charter vessels is discussed in detail in
Section 5.5 below. The IO-PAC codes for the industry sectors included in the model are
displayed in Table 2. The classification rules for the commercial fleet are presented in Table 3.
The classification scheme is hierarchical. Working from the top down, the rule description of the
category that is met, is the classification for a vessel.
Table 2. Industry categories and associated IMPLAN codes.
IO-PAC Code
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
561
563
570

Category description
Catcher processor
Mothership
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
Recreational charter

Table 3. Vessel sectors used in the IO-PAC. Modified from Radtke and Davis (2000).
Order
1
2
3
4

Vessel sector
Catcher processor
Mothership
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

19
20

Other > $15,000
Other ≤ $15,000

Rule description
Vessel registered to a catcher processor permit.
Vessel registered to a mothership permit.
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.

The IO-PAC revision does not alter the commodities added to IMPLAN. The
commodities are displayed in Table 4, and include 32 different species/gear combinations as well
as one bait commodity. The gear type portion of the commodity classification was constructed
by grouping PacFIN fish ticket data with the gear categories presented in Table 5.
Table 4. Commodities added to IMPLAN and associated codes.
IO-PAC 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 5. 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

The total landings by vessel type and species/gear combinations are displayed in Table 6.
Landings are classified in the species/gear classifications even if species for particular gear types
are considered bycatch.

Table 6. Landings by vessel type and commodity code, 2010 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

509
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—

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

511

Vessel classification
512
513

514

515

$4,651,749

$4,252,637

$819,717

$193,316

$509,429
$1,882,378
$248,490
$7,761
$219,327
$17,446

$306,187
$175,820
$256,511
$238
$261,608
$266

$58,540

$2,574,985

$335,784

$9,586,355
$318,032
$6,825,393
$4
$7,171,143
$880
$1,478
$550
$5,527,716
$8,810

$285,748
$691
$1,411
$1,198
$44,282
$3,380

$297,531

$58,581

$3,205,428

$5,314

$18,449
$132,135
$202,436

$47,262
$244
$10,298
$759

516
$91

$6,255
$897,014
$56,973

$17,245,631

$390,801

$499,013
$431
$742,018
$0

$1,459,018
$502
$1,778,712

$6,097,718

$706,010

$4,878
$4,773
$21,169

$321

$905,142
$497,963
$599,921

$22,032
$24,764
$113,702
$143

$1,645

$1,206

$3,635
$1,012,898

$38
$2,736,461
$212
$1
$67,496
$8,046
$184
$7,309,739

$33,886

$3,430
$70
$1,538,448
$5,727
$1,013
$1,707

$2,642

$12,916,233

$5,653,704

$901,739
$35,892
$92,185
$94,573
$554
$10,969

$293,171
$11,043
$67,189
$58,817
$1,240
$62,545

$34,954,438

$1,180,402

$211
$82,822
$1,178
$94,978
$27,816,025

Table 6 continued horizontally. Landings by vessel type and commodity code, 2010 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

517

518

519

Vessel classification
520

521

522

523

$75,375

$61,822

$424

$538

$39,826

$1,881
$76
$914,489

$6,674
$145

$93,967
$71,041
$140,366
$3
$68,998
$15,547
$738
$995
$5,708,325

$102,250,685

$49,369

$11,810,093
$4,222,313

$53,646
$345,734
$1,245,050

$4,557

$50,232
$932,428
$1,860
$23,936,734
$55,430

$46
$59,222
$71,357
$5,853
$35

$2,447,369
$6,035,306
$4,099,394

$3,647,338
$108,360
$237,555

$120,968
$109

$45
$660
$562,560
$185

$1,569,625
$54,673
$209

$12,611
$14
$5,504,969
$52

$626
$5,040

$13,440,855
$392
$8,303
$13,293
$39,196
$71,143,799
$86,833,939

$49,187
$4,052,348
$12,630
$3,214
$239,975
$165,632

$57,981
$29,675
$3,929
$328,537
$298,467
$666,325

$1,611,343
$191,171
$65,830
$32,541,679

$36,803
$64,248
$383
$108,068
$877,854
$88,306
$892
$23,445,453

$434
$170,607

$27
$13
$55,673
$73,203
$1,100,042

$182,066
$29,065,941

$39,749
$146,846

$161,830

$4,148
$820,951
$185,773

$394

$20
$370,701

$123,246,673

$4,310,045

$30,970,157

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

524

526

Vessel classification
527

$11,016
$13

$6,068

$2,060
$65,808
$52
$1,048

$59,206

$9,714

$438,579
$188

$54,056

$158,147

$3,636
$149,770
$5,715

$58,444
$645
$7,675
$696
$15,391
$35,767
$168,020
$203
$306,862
$3,370,252
$4,137,277

$60

$1,936

$9,897,530
$74,503
$77,842
$10,926,681

$431,702
$4,939
$15,967
$712,117
$1,152

$42

$40,616
$101,290
$6,480

$252

$72,491
$489,636
$70,200

$414,247
$1,916,609
$322,656

$10,178

$168
$50,827
$1
$23,300
$435,256
$24,870
$4,511
$450,556
$232,412
$429,818
$7,225,366

$17
$34,432
$173,358
$4,807

$13,899
$33,905
$3,454
$2,039
$7,359
$7,877
$71
$1,612
$253,599

$1,514,385
$1,169
$49,634
$5,579
$172,460

$1,425
$837
$13,366

528

$30,887

$29,164
$44,708

$12,616
$7,466
$42
$7,919,127
$8,104,596

$263,883
$2,440,575
$142,203
$108,510,837
$112,546,073

Total all classifications
$0
$9,935,110
$111
$10,619,625
$25,083,923
$7,520,781
$1,984,416
$8,271,059
$3,564,469
$9,235
$4,355
$132,687,282
$19,497
$155,077
$15,885,826
$5,851,547
$0
$8,695,124
$40,857,123
$29,779,359
$75,109
$3,491
$13,227
$13,622,302
$1
$1,376,443
$7,586,057
$395,643
$568,692
$16,609,802
$76,212,145
$117,397,975
$534,784,804

5.2. Commercial Catcher-Vessel Production Functions
The vessel production functions in IO-PAC rely on the 2008 data from the voluntary
limited entry trawl, fixed gear, and open access surveys. Table 7 presents the vessel production
functions included in IO-PAC. Because these voluntary surveys do not extend to the at-sea
fishery, the mothership and catcher processor production functions are left blank at this time.
The expenditure categories shown in Table 7 must be mapped into IMPLAN commodity codes
for inclusion in the model. The mapping of the expenditure categories into IMPLAN commodity
codes is presented in detail in Appendix A. While the expenditure categories have changed little
in the IO-PAC update, the mapping to IMPLAN commodity codes has changed considerably due
to the shift in the IMPLAN industry classification scheme from 509 unique sectors to 440.

5.3. Motherships and Catcher Processor Production Functions
The EDC is currently collecting data applicable to the at-sea fleet: motherships and
catcher processors. Cost earnings surveys necessary to create production functions for these
vessels were previously unavailable. These production functions will be assigned the EDC data
following the schedule in Table 1.

Table 7. 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
Enforcement
Dues
Freight Supplies
Offloading
Trucking
Other miscellaneous
Proprietary income
Total (%)

Catcher
processor
—
—
—
—
—
—
—

Mothership
—
—
—
—
—
—
—

—
—
—
—
—
—
—
—
—
—
—
—
—

Alaska
13.4
19.6
13.2
1.4
0.1
0.8

Pacific
whiting
trawler
12.3
17.8
12.8
1.6
0.8
1.0

Large
groundfish
trawler
17.5
21.6
16.8
1.5
1.4
0.8

Small
groundfish
trawler
17.5
21.6
16.8
1.5
1.4
0.8

Sablefish
fixed
gear
21.6
23.7
7.4
2.0
1.2
4.4

Other
groundfish
fixed gear
18.3
21.5
7.5
1.9
1.1
4.3

Migratory
liner
16.6
18.1
8.3
1.2
0.7
2.8

Pelagic
netter
16.6
18.1
8.3
1.2
0.7
2.8

8.7
3.2
0.4
1.7
0.6
0.8
0.7
0.5
0.1
0.0
0.0
0.0
1.1
33.6
100.0

11.3
5.4
1.7
0.1
0.0
0.7
4.3
1.1
0.3
0.0
0.0
0.0
1.1
27.7
100.0

14.3
4.6
1.1
0.5
0.5
0.7
4.4
0.4
0.9
0.0
0.0
0.0
2.8
10.2
100.0

10.7
2.8
2.1
0.5
2.1
2.4
0.1
1.1
0.3
0.0
0.0
0.0
2.4
15.0
100.0

12.4
5.9
1.8
2.6
0.2
1.6
0.0
0.7
0.0
0.6
1.0
1.1
6.7
10.8
100.0

10.4
3.6
1.1
0.9
0.5
1.2
1.1
0.4
0.3
0.1
0.2
0.2
4.7
27.5
100.0

Table 7 continued horizontally. Percentage distribution of commercial fishing production functions by expenditure categories

Expenditure categories (column
Migratory
list repeated from above)
netter
Shrimper
Captain
16.6
20.8
Crew
18.1
17.7
Fuel, lubricants
8.3
2.3
Food, crew provisions
1.2
13.4
Ice
0.7
1.2
Bait
2.8
2.2
Repair and maintenance: vessel,
gear, and equipment
10.4
7.5
Insurance
3.6
4.4
Interest and financial services
1.1
0.0
Purchases of permits
0.9
0.0
Leasing of permits
0.5
0.0
Moorage
1.2
3.0
Landings taxes
1.1
1.2
Enforcement
0.4
0.3
Dues
0.3
0.2
Freight Supplies
0.1
0.4
Offloading
0.2
0.5
Trucking
0.2
0.0
Other miscellaneous
4.7
0.4
Proprietary income
27.5
24.4
Total (%)
100.0
100.0
*Percentages not shown due to confidentiality restrictions

Crabber
21.4
21.6
6.9
1.1
0.4
4.4

Salmon
troller
7.5
17.2
9.9
3.0
0.3
0.2

Salmon
netter
19.0
8.2
1.4
4.3
0.0
0.0

Other
netter
16.6
18.1
8.3
1.2
0.7
2.8

Lobster
16.6
18.1
8.3
1.2
0.7
2.8

Diver
16.6
18.1
8.3
1.2
0.7
2.8

Other
>15,000
16.6
18.1
8.3
1.2
0.7
2.8

Other
<15,000
17.9
13.3
17.6
3.6
1.0
2.7

11.3
4.2
1.0
1.2
0.4
1.2
0.1
0.1
0.2
0.1
0.4
0.2
8.2
15.6
100.0

15.6
5.0
3.1
3.2
0.3
3.2
0.0
0.3
0.8
0.0
0.0
0.6
10.7
19.1
100.0

17.7
2.2
0.0
0.2
0.3
0.8
1.0
0.0
0.5
0.0
0.5
1.7
3.3
38.9
100.0

10.4
3.6
1.1
0.9
0.5
1.2
1.1
0.4
0.3
0.1
0.2
0.2
4.7
27.5
100.0

10.4
3.6
1.1
0.9
0.5
1.2
1.1
0.4
0.3
0.1
0.2
0.2
4.7
27.5
.100.0

10.4
3.6
1.1
0.9
0.5
1.2
1.1
0.4
0.3
0.1
0.2
0.2
4.7
27.5
100.0

27.0
4.7
0.6
5.9
0.3
8.4
0.0
0.7
0.8
0.0
0.1
1.1
6.5
-12.1
100.0

5.4. Shoreside processor production functions and mark-ups
For shoreside processors located on the West Coast, the EDC data permits the building of
a production function and mark-up by species. The Benchmark Input-Output data produced by
the Bureau of Economic Analysis (BEA) contains a production function for seafood processors,
which is used in IMPLAN for the default seafood processing sector. This production function is
not specific to processors on the West Coast, so to the extent that processors on the West Coast
differ from seafood processors nationally, the use of the Benchmark Input-Output production
function will be a source of error. In the last version of IO-PAC, shoreside processor sales of
seafood were made by using the markup margin information imbedded in the IMPLAN default
seafood processing production function. Additionally, the output per-employee information in
the default production function was used to make employment estimates. This previous
approach has a couple of notable disadvantages. First, it is derived from data on all U.S.
processors. The national data is heavily influenced by the processing activity that occurs in
Alaska, where the production costs for fish and output per employee are likely different than
shoreside seafood processors on the West Coast. To the extent that West Coast shoreside
processors deviate from the processors nationally, there will be errors in both income and
employment impact estimates. Second, the markup margin in the default approach is not species
specific. While this approach will approximate the markup received by processors for all species
on average, it lacks species specific detail. Based on the EDC data, markups differ substantially
among different species.
The EDC data permits the specification of a production function specific to processors on
the West Coast, and perhaps more importantly, it provides information on species specific markup for different fish species. IO-PAC uses data collected through the EDC to represent all
shoreside processors on the West Coast. Using the EDC data in this application is a potential
source of error, because not all processors of on the West Coast are required to complete a
survey. An EDC survey is required of all owners and lessees of a shorebased processor that
received round or headed-and-gutted IFQ species groundfish or whiting from a first receiver, and
3
all owners of a first receiver site license in 2011 and beyond. Processors that do not receive fish
fitting this description are not included in the EDC program. Thus, no cost data is available for
them. Because the lack of available data, we assume that all West Coast shoreside processors are
represented by those who complete an EDC survey.
The processor production function was generated through dividing each of the
expenditures displayed in Table 8 by total revenue. The production function is built using 2010
data. The mapping of the cost categories into the appropriate IMPLAN sectors is detailed in
Appendix A. The default production function in IMPLAN, which is based on the BEA’s inputoutput table, is useful in mapping expenditure categories covered in the EDC to the appropriate
commodity codes.

For a complete definition see 50 CFR 660.114. Under NAICS some of these entities may be classified as fish and
seafood merchant wholesalers, frozen specialty food manufacturing, or something else. For the purposes of IO-PAC
they are considered processors.

Table 8. Percentage distribution of processor production functions by expenditure categories.
Expenditure categories
Employee and Worker Payroll
Additives
Custom Processing
Electricity
Freight
Insurance
Natural Gas
Offsite storage and freezing
Packaging
Production Supplies
Propane
Rental or lease of buildings, job-site trailers, and other structures
Rental or lease of processing machinery or equipment
Repair and maintenance on facility buildings, machinery, and
equipment
Sewer and Waste
Shoreside monitor
Water
Fish purchases
Other
Proprietary Income
Total (%)

Allocation
Percent
14.02
0.22
1.19
1.31
0.57
0.97
0.34
1.25
3.99
0.84
0.29
0.89
0.18
1.75
0.31
0.15
0.65
59.93
1.99
9.15
100.0

Costs by category in Table 8 were allocated to relevant cost categories in the default
production function in proportion to their share in the default production function. The
Benchmark Input-Output Table (BIOT) may have more than one category relevant to each EDC
cost category. In other words, BIOT has greater detail about a specific cost category than is
captured by the EDC. Information related to the use of these commodities by seafood processors
is contained in their default production function in IMPLAN. For example, commodity codes
relevant to the EDC category “Packaging” are shown in Table 9. The default production
function contains five categories that are applicable. These are the five industry categories that
are involved in the production of a commodity that is likely used to make “Packaging.” The
default absorption numbers in the table are the allocation percentages of total industry output
(revenue) to the respective expenditure categories. These percentages are used to guide the
allocation of the EDC category “Packaging.” The IO-PAC allocation is done in proportion to the
default absorption.
Table 9. IO-PAC distribution of processor cost example.
IMPLAN
Code

Expenditure categories

3107
3108
3105
3146

Paperboard containers
Coated and laminated paper, packaging paper and plastics film
Paper from pulp
Polystyrene foam products

Default
Absorption

IO-PAC
Allocation
Percent

1.668
0.289
0.019
0.010

80.335
13.924
0.910
0.477
100.0

The markups by species groups contained in IO-PAC are shown in Table 10. The
markups were generated using 2010 EDC data. The markups shown on the basis of revenue
earned by processors for every dollar spent on the respective species.
Table 10. IO-PAC processor markups by species group.
Expenditure categories
Whiting
Sablefish
Dover/thornyhead
Other groundfish
Crab
Shrimp
Salmon
HMS
CPS
Halibut

Markup
3.63
1.61
2.33
1.60
1.48
1.91
1.28
1.16
2.23
1.28

5.5. Recreational Fishing
The IO-PAC revision includes a new module to estimate economic impacts and
contributions related to recreational fishing trips. Recreational expenditures by type and by
fishing mode were obtained from Gentner and Steinback (2008). Table 11 shows the
recreational expenditures by type and mode.
Table 11. Estimated 2006 Recreational Expenditures by Mode (Thousands of 2006 dollars)
California
Expenditure Category
Access and Parking
Auto Rental
Bait
Boat and Equipment Rental
Boat Fuel
Catch Processing
Charter Crew Tips
Charter Fees
Food from Grocery Stores
Food from Restaurants
Gifts
Ice
Lodging
Private Transport
Public Transport
Tackle
Tournament Fees
Trip Total

Oregon

Charter
771
1,976
223
24
0
157
4,355
47,790
6,084
7,081
2,244
892
6,851
15,950
2,130
12,039
1,643

Private
995
0
4,893
8,021
22,587
0
0
0
10,846
5,698
1,243
1,602
4,505
19,182
1,382
16,010
250

Charter
21
15
13
25
0
24
191
6,095
526
1,059
268
50
1,138
1,638
158
90
3

110,210

97,214

11,316

Washington

Private Charter
173
8
8
0
1,663
24
1,668
9
5,783
0
324
70
0
353
0
6,223
4,764
828
3,423
941
650
266
666
56
5,897
1,113
8,652
1,709
666
86
4,388
132
62
110
38,786

11,929

West Coast

Private Charter
59
800
101
1,991
298
260
721
58
2,064
0
7
251
0
4,899
0
60,108
948
7,438
625
9,081
105
2,778
126
998
632
9,102
1,216
19,297
220
2,374
895
12,261
72
1,756
8,087

133,455

Private
1,227
109
6,854
10,410
30,434
331
0
0
16,558
9,746
1,998
2,394
11,034
29,050
2,268
21,293
384
144,087

Angler expenditures in Table 11 were used to create expenditure vectors for calculating
economic contribution and impacts associated with changes in recreational spending.
Expenditures by category were divided by total trip expenditures by mode and state to apportion
recreational spending among different IMPLAN and IO-PAC sectors. The expenditure vectors
for West Coast charter and private boat anglers along with their associated IMPLAN and IOPAC sectors are displayed in Table 124. The percentages represent the proportion of total
recreational expenditures by mode on each expenditure category. For example, for each dollar of
spending on charter boat fishing on the West Coast, $0.45 is spent on charter fees and $0.068 is
spent on lodging.
Table 12. West Coast Expenditure Vector by Mode and Associated IMPLAN/IO-PAC Sectors
West Coast (%)
Expenditure Category
Access and Parking
Auto Rental
Bait
Boat and Equipment Rental
Boat Fuel
Catch Processing
Charter Crew Tips
Charter Fees
Food from Grocery Stores
Food from Restaurants
Gifts
Ice
Lodging
Private Transport
Public Transport
Tackle
Tournament Fees

IMPLAN/IO-PAC Sector (Basis)

Charter
Private
0.6
0.9 Other amusement and recreation (Industry)
1.5
0.1 Automotive equipment rental and leasing (Industry)
0.2
4.8 Animal production, except cattle and poultry and eggs (Commodity)
0.0
7.2 General and consumer goods rental (Industry)
0.0
21.1 Petroleum refineries (Commodity)
0.2
0.2 Seafood product preparation and packaging (Industry)
3.7
0.0 Charter vessels (Industry)
45.0
0.0 Charter vessels (Industry)
5.6
11.5 Personal consumption expenditure vector 1111
6.8
6.8 Food services and drinking places (Industry)
2.1
1.4 All other miscellaneous manufacturing (Commodity)
0.7
1.7 Soft drink and ice manufacturing (Commodity)
6.8
7.7 Hotels and motels, including casino hotels (Industry)
14.5
20.2 Petroleum refineries (Commodity)
1.8
1.6 Transit and ground passenger transportation (Industry)
9.2
14.8 Sporting goods and athletic goods mfg. (Commodity)
1.3
0.3 Other amusement and recreation (Industry)

The expenditure vectors can be used to calculate contribution and impact estimates from
recreational trip spending. To use the expenditure vector, effort estimates must be transformed
to recreational spending. Effort estimates are mapped into recreational spending for each state
using the expenditure estimates in Table 11 in conjunction with effort measured in number of
trips obtained from Gentner and Steinback (2008). Expenditures by state were divided by trips
to obtain state level mean expenditures per trip and mode. The mean expenditures by trip are
then adjusted to meet the year of analysis by using Consumer Price Index data for the following
goods and services: recreation, car rental, processed fish, motor fuel, food and beverages,
4

The same procedure for charter and private boat anglers could be performed for shoreside anglers, which would
enable economic impact estimates for this segment. This has not been done because there has not been a need, as
yet, to make impact estimates for shoreside anglers.

sporting goods, lodging, private transportation, public transportation, and miscellaneous
personal. Using mean expenditures by trip in conjunction with total recreational trip estimates
yields expected changes in recreational spending.
The expenditure vectors and mean recreational expenditures can be used for contribution
and impact estimates for the sub-state level port areas in IO-PAC under the assumption that
recreational spending within a port area does not differ from the state averages. For example,
this assumes a recreational angler in Puget Sound purchases the same basket of goods and
services as a recreational angler who fishes off the Washington coast. There is therefore a
potential source of error in applying the expenditure vectors to all port areas within each state.
Expenditures in some port areas could deviate from the state-level expenditure vectors.
However, to make sub-state level estimates this assumption is necessary because it is unknown
how expenditures differ among port areas. By assuming the same expenditure profile for each
port area in a state, differences in the economic effects of changes in recreational spending are
driven by changes in recreational fishing trips in each area and differences in their respective
regional economies rather than differences in the types of goods purchased in each region.
A "charter vessel" is not contained in the default version of IMPLAN. In the standard
IMPLAN model, the charter vessel industry is included in “Other amusement, gambling, and
recreation industries” (IMPLAN sector 410), along with many other diverse industries. This
IMPLAN sector includes charter vessel operations, but it also includes other important industries
such as skiing. It was added using an approach similar to that used for adding the commercial
fishing sectors. The results from surveys of charter vessels in CA, OR, and WA were used to
create production functions for charter businesses. In addition, survey results were used to create
total industry output, employment, employee compensation, proprietor income and taxes paid.
For every dollar of output, amounts are paid to providers of inputs from other sectors, so that
every dollar of charter vessel output can be broken into material input costs and value above
costs of inputs, which is value-added
The WA and OR charter sectors were created using the results of a 2006 survey of marine
charter fishing businesses in WA and OR by the Northwest Fisheries Science Center5. The
marine charter survey collected information about cost and revenue, vessel characteristics,
operator characteristics, and current market conditions in the industry. The marine charter
fishing industry in Washington and Oregon consisted of an estimated 217 vessels in 2006 with
$15.4 million in direct revenue and employed an estimated 345 individuals. Completed surveys
were received from 95 ocean going vessels in 2006. Seven surveys were incorrectly completed
and were treated as nonresponses. The effective sample was 53 vessels in Oregon and 35 vessels
in Washington for a total survey response rate of 41%.
Total revenues estimated from the survey were adjusted by effort changes from 2006 to
2008 and were added to the model as total industry output. To bring estimated industry revenue
to the 2008 base year of the revised IO-PAC model, effort changes of for-hire fishing trips from
2006 to 2008 from “Fisheries Economics of the United States 2009” were used. Total industry
5

The survey methodology and complete results will appear in a forthcoming manuscript by Leonard and Watson:
“The role of charter boat operations in fishing communities: a social and economic analysis of the marine charter
boat fleets in Oregon and Washington.” The manuscript is obtainable from the author by request.

output was apportioned to value added and material components as displayed in Table 13 along
with their associated IMPLAN sectors. Some of the associated sectors indicate “Margined.” In
I/O models, expenditures are expressed in terms of producer prices, which is the value of goods
at the point of production rather than at the retail level. Consequently, for goods that are not
produced at the time of service, such as gasoline, the prices paid by final consumers must be
allocated to the portion going to the retailer, wholesaler, transportation, and manufacturing
(Olson and Lindall, 1999).
According to the production function, an average of 53% of each dollar generated by
charter vessel operations is spent on inputs from other sectors. The remaining 47% is value
added, which goes to employee compensation, proprietary income, taxes, and other income. The
intermediate expenditures were translated into absorption coefficients, which are the percentages
of each dollar of revenue spent on each input. For example, an absorption coefficient of 0.05
was calculated for insurance expenses, meaning that, on average, charter businesses spend 5
cents of each dollar of revenue on inputs from the insurance sector. In this same way, absorption
coefficients were calculated for each input sector.
Table 13. Estimated 2006 Average WA and OR Charter Industry Production Function and Associated IMPLAN
Sectors

Outlay Categories
Vessel Related
Proprietary Income
Captain's Payments
Other Crew Payments
Office Labor and Other Labor
Engine Overhaul
All Other Vessel Maintenance
Electronics Maintenance
Haulout
Moorage
Purchase of New Gear
Vessel Insurance
Vessel Professional Services
Vessel Advertising
Fuel
Fishing Supplies
Bait Expenses
Food and Drink
Taxes and Government Fees Domestic
Taxes and Government Fees Foreign
Commissions for Booking Agents
Telephone and Other Communications

Allocation
(%)

IMPLAN Sector

27.2
8.6
3.2
1.1
3.7
3.8
0.8
1.4
2.0
1.5
5.0
0.6
2.1
10.8
3.0
1.2
0.1
6.6
0.0
5.7
1.1

Proprietary Income
Employee Compensation
Employee Compensation
Employee Compensation
Ship building and repairing
Ship building and repairing
Electronic equipment repair and maintenance
Ship building and repairing
Other amusement and recreation
Sporting goods, hobby, book stores (Margined)
Insurance carriers
Other miscellaneous prof. and tech. services
Advertising and related services
Petroleum refineries (Margined)
Sporting goods and athletic goods mfg. (Margined)
Animal prod., except cattle, poultry (Margined)
PCE vector 1111
Indirect Business Taxes
Indirect Business Taxes
Travel arrangement and reservation services
Telecommunications
19

Other Vessel Related
Booking Operation Related
Labor for Shorebased Personnel
Advertising
Insurance
Professional Service
Association Fees
Telephones
Other Office Expenses
Lease/Loan Payments on Vehicles
Legal/Financial Services
Other Booking Related

8.4

Monetary authorities and depository credit

0.15
0.40
0.44
0.07
0.01
0.39
0.65
0.04
0.01
0.01

Employee Compensation
Advertising and related services
Insurance carriers
All other miscellaneous prof. and tech.
Civic, social, professional organizations
Telecommunications
All other miscellaneous mfg. (Margined)
Monetary authorities and depository credit
All other miscellaneous prof. and tech.
All other miscellaneous mfg. (Margined)

The CA charter sector was created using the results of a survey conducted by Pacific
States Marine Fisheries Commission (PSMFC) and Southwest Fisheries Science Center. The
survey collected cost and earnings information for the year 2000 from the West coast charter and
head boat fleet (PMFC, 2004). The population targeted by the survey consisted of vessels operating
out of California, Oregon and Washington that provided ocean recreational fishing trips on a
commercial basis during 1997-1998. Approximately 12% of the charter and head boats licensed to
operate in California, Oregon and Washington were sampled using a stratified random sampling
approach. Each stratum consisted of a particular combination of region and size class. Vessels were
categorized according to the region of their home port: southern California (for homeports from the
Mexican border to Point Conception), northern California (for homeports north of Point Conception
to the Oregon border), Oregon, and Washington. Vessel size class was defined in terms of vessel
length: "small" for lengths of 15-30 feet, "medium" for lengths of 31-49 feet, and "large" for
lengths greater than 49 feet.
To develop a single production function for charter vessel businesses in CA, a weighted
average of the survey results was used. The cost and earnings data collected in the survey was
weighted by category for Northern CA Large, Northern CA Medium, Northern CA Small, Southern
CA Large etc. based on the relative frequency of the cohort in the total population. The weighted
average cost function for CA charter businesses along with the assigned IMPLAN categories appears
in Table 14.

Table 14. Estimated 2000 Average California Charter Industry Production Function and Associated IMPLAN
Sectors

Outlay Categories
Proprietary Income
Captain and crew
Labor for Shorebased Personnel
Engine Overhaul
All Other Vessel Maintenance
Electronics Maintenance
Haulout
Moorage
Purchase of Gear or Equipment
Insurance
Professional Services
Advertising
Fuel
Supplies
Bait
Food and Drink
Fees Paid to Domestic Governments
Fees Paid to Foreign Governments
Commissions Paid for Booking Trips
Telephones
Other
Other Office Expenses
Landing Taxes
Mortgage for Vessel
Association Fees
Lease or Loan of Motor Vehicles

Allocation
(%)
45.21
12.19
1.25
1.21
3.57
0.22
1.09
1.89
3.50
1.16
0.37
1.31
7.20
2.27
5.18
2.59
1.72
2.00
5.02
0.60
0.15
0.32
0.41
4.32
0.23
0.25

IMPLAN Sector
Proprietary Income
Employee Compensation
Employee Compensation
Ship building and repairing
Ship building and repairing
Electronic equipment repair and maintenance
Ship building and repairing
Other amusement and recreation
Sporting goods and athletic goods mfg. (Margined)
Insurance carriers
Other miscellaneous prof. and tech. services
Advertising and related services
Petroleum refineries (Margined)
Sporting goods and athletic goods mfg. (Margined)
Animal prod., except cattle, poultry (Margined)
PCE vector 1111
Indirect Business Taxes
Indirect Business Taxes
Travel arrangement and reservation services
Telecommunications
All other miscellaneous mfg. (Margined)
All other miscellaneous mfg. (Margined)
Indirect Business Taxes
Monetary authorities and depository credit
Civic, social, professional organizations
Monetary authorities and depository credit

Total industry output for charter vessels in CA were estimated using weighted revenues
from the survey. Average revenue in each stratum was weighted in the same manner as costs.
The weighted average revenue estimate was then multiplied by the total number of charter
vessels in CA in 2000 to estimate total industry revenue. The year 2000 estimate of industry
output was then adjusted to 2008 by using effort changes of for-hire fishing trips in CA from
2000 to 2008 from Fisheries Economics of the United States 2009 (U.S. Dept. Commerce., 2011).
Employment by charter vessels in CA was estimated by dividing total industry output in 2008 by
the weighted average output per employee collected in the survey. The weighted average output
per employee was estimated through the same stratum weighting method discussed above.

5.6. Product Flow
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. Product flow
refers to the flow of fish from harvesters to processors, wholesale seafood dealers, restaurants,
households, and other sources of demand for fish. Like other fishery IO models (Kirkley et al.
2004, Steinback and Thunberg 2006), IO-PAC relies on simplifying assumptions. The
assumptions about the flow of fish in IO-PAC are changed in the revision. For the state and
West Coast level study areas, the revisions involve different product flow assumptions for
groundfish trawl fish from other gear/species combinations. For port level models, groundfish
trawl fish is treated the same as all other fish, and a new approach of using IMPLAN to develop
product flow assumptions is used. The collections data by the Washington Department of
Revenue (WDOR) Enhanced Food Fish Tax is no longer used.
For fish harvested with groundfish individual fishing quota (IFQ), the assumptions about
product flow are driven by data collected through the EDC program. Under trawl rationalization,
all IFQ fish sold by harvesters must be received by an entity with a First Receivers License.
Those with Licenses are required to complete an EDC survey, so there is no harvested fish that is
bypassing these first receivers. As described above, these first receivers are treated as
processors. Hence, for the West Coast as whole and the state level study areas, all groundfish
trawl quota fish flows to “processors” as defined here. None goes directly to other businesses
and households that demand fish without going through the processing channel.
Due to cross hauling, it is possible that fish landed in a port, will not be processed therein.
At this time we are unable to quantify this cross-hauling activity for either IFQ or non-IFQ fish.
Consequently, we handle both in the same manner. Because we currently cannot quantify the
cross-hauling activity, IMPLAN data about processor demand for fish within a study area (port
group) are utilized. The IMPLAN commodity balance sheets were used in the last version of IOPAC for this same purpose.
The revision uses the trade flow information in IMPLAN differently because the previous
approach underestimates the amount of fish that flows from harvesters to processors. In the last
version of IO-PAC, it was assumed that processor demand for fish from harvesters followed the
econometrically derived regional purchase coefficient (RPC) in IMPLAN. The primary issue
with this approach is that processor demand for fish from harvesters is equivalent to all other
sources of fish demand (households, restaurants, grocery stores, hospitals, etc.). All agents of
demand are treated the same. They all source the same proportion of their demand for fish from
harvesters within the study area. This issue is exemplified by examining the demand for
harvested fish in Oregon. Figure 1 was generated by constructing a default IMPLAN model for
each study area, then viewing the Industry/Institution RPC tab under the Edit Trade Flows
function in IMPLAN. Figure 1 indicates that Gross Commodity Demand for fish among
processors in the state of Oregon is $154,402,400. Essentially, this indicates that in order to
support their level of production in Oregon, processors needed $154 million in raw fish. The
Local Commodity Demand column indicates that $20 million of this demand for raw fish was
sourced from harvesters in Oregon. The reason 12.9% of demand was fulfilled by harvesters in
Oregon, is that the RPC of 0.129738 applies to all sources of demand, which are shown in the

figure as Other animal food manufacturing, Frozen food manufacturing, Poultry processing, and
all the household income groups.
Given the nature of the fish harvester and processor relationship on the West Coast, we
contend that it is more appropriate to assume that harvesters will satiate demand for fish among
processors before they sell fish to any other type of buyer. Due to Trawl Rationalization, this is
certainly the case with groundfish, where fish landed with trawl quota must be sold to a licensed
First Receiver and we contend that this approach is more accurate even for non-trawl quota
species as well. Hence, for all port group study areas, IO-PAC assumes that landings from the
fish harvesting sectors flow to seafood processors in the same proportion as the ratio of default
IMPLAN processor demand (sector 61) to the available fish harvesting sector (17) supply. This
proportion can be determined using Figure 1. The Gross Commodity Demand of seafood
processors in Oregon is $154 million. The Total Commodity Supply in the figure of $241.7
million represents the total fish landings in Oregon. Utilizing this assumption, the amount that
flows to processors is (154.40/241.72) ≈ 0.639. Since this is a state level model, the 63.9%
would apply to of all non-IFQ fish. For IFQ fish at the port level, the same approach is used.
Figure 1. IMPLAN trade flow of fish in Oregon (2010)

6. Model Construction
The revisions to IO-PAC construction are done to reduce effort involved in making
changes to fishing sector production functions over time and simplify the process of building
numerous port level models. The original version of IO-PAC modified IMPLAN Version 2
software. IMPLAN Version 3 software is used for in the IO-PAC revision. Version 3 provides a
new method for importing changes in expenditures made by fishing vessels and recreational
anglers. Expenditure changes can now be imported into IMPLAN using EXCEL templates
provided by IMPLAN. Model construction in IO-PAC is constructed through the use of several
of these EXCEL templates. With the change, the modeling is done primarily using spreadsheets
rather than with modifications to the IMPLAN database. The change permits easy modification
of production functions used in the model, and also changes in study areas can be accomplished
easily. The ease in changing production functions is important because the survey data from
which they are built are continually being updated. The ease in changing study areas is
important because study areas of interest often deviate from those used in groundfish
management. For example, the new approach permits an easy shift to study areas of interest in
salmon management. The following discussion borrows content from the Version 3.0 User’s
Guide (MIG, 2010).
In IMPLAN Version 3, contributions and impacts are estimated by setting up activities of
different types. Activities are groupings of one or more Events that represent spending changes
within a study area. Activities come in six different types: industry change, commodity change,
labor income change, household spending change, industry spending pattern, and institutional
spending pattern. Each activity type is appropriate for different types of analysis. By enabling
spending changes of six different types, IMPLAN Version 3 is more flexible than Version 2, but
skill by the analyst is more critical in determining which type of activity is most appropriate for a
particular estimate. The activity types used in IO-PAC are briefly described below.

6.1. IMPLAN Activity Types
Industry Change is used to estimate the economic impact or contribution of a particular
industry, where industry refers to a group of establishments that engage in similar types of
economic activity. The most widespread industry classification scheme is the North American
Industrial Classification System (NAICS). IMPLAN has its own industry classification scheme
where each group consists of one or more NAICS categories. An example of an industry change
is to estimate the effect of a $1 million change in demand among “wood window and door”
manufacturers in a particular study area.
Commodity Change is used to estimate the economic impact or contribution of a
particular good or service. Commodities may be produced by one or more industries and
institutions, where institutions are households and governments. All industries in IMPLAN have
a primary commodity of the same name as the industry. Thus, the primary commodity of wood
window and door manufacturers is the commodity “Wood windows and doors”. However, wood
window and door manufacturers also produce the commodity “Wood kitchen cabinets and
24

countertops.” An impact or contribution estimate due to a demand change for a particular
commodity will affect all industries that produce the commodity. For example, shocking the
commodity “wood windows and doors” will affect wood window and door manufacturers, but it
will also affect the industry “sawmills and wood preservation.”
It is important to note that multipliers used to develop estimates are produced for each
endogenous industry or institution in IMPLAN. The effective multiplier for a commodity-based
estimate is a weighted combination of the multipliers of the affected industries and institutions.
The weighting among industries for a particular commodity is the respective market share for the
commodity. The government institutional sectors (State and Local Government, Federal Govt.
Non-Defense, etc.) are often treated as exogenous. As a result, their institutional contribution to
production is treated as a leakage in impact/contribution estimates. This is a principle difference
between industry-based versus commodity-based estimates.
Labor Income Change is used to estimate how changes in employee compensation or
proprietor income will affect the economy. This would be the appropriate approach if one
wanted to estimate the impact of increased payments to employees in a study area.
Industry Spending Patterns are particularly useful in modeling the fishing industry with
primary cost earnings data collected from participants. The following was taken from Version
3.0 User’s Guide (MIG, 2010).
“Industry Spending Patterns allow you to import an Industry’s production function, or build
an Industry from data about its expenditures. This Activity type works with coefficients of
total budget spending, allowing you to use Level to create a series of estimates about the
impacts of different expenditures to a single Industry. One thing to remember when using
Industry Spending patterns is that their coefficients typically do not include their labor
income spending, and therefore the coefficients sum to less than 1.00. To ensure that the full
impact of spending in an Industry is captured, you will need to create a Labor Income impact
to compliment your Industry Spending pattern.”

Institution Spending Patterns are useful in modeling the change in households or
government spending. In IO-PAC, we use the State and Local Government Non-Education
spending pattern to model the effect of taxes paid by fishing industry participants. This marks a
departure from the last version of IO-PAC in which taxes were shifted to the value-added
account “Indirect business taxes.” Because of changes in the IMPLAN software, this approach is
no longer possible.

6.1. Importing Fishery-Specific Information
All of the above activity types can be created in EXCEL and imported into the IMPLAN
software. For the industry additions in IO-PAC, the procedure involves mapping the production
function information in Tables 7, 8, 13 and 14 into IMPLAN commodities using the bridge
information displayed in Appendix A. Recreational effort is mapped into IMPLAN commodities and
industries as shown in Table 12.

Figure 2 displays an example of an Industry Spending Pattern activity EXCEL template that
is imported into IMPLAN. After the activity is imported into IMPLAN the “Local Direct Purchase”
that is set to 100% on the import must be set to the “SAM Model Value” using the IMPLAN
interface. All of these SAM model values will be unique to the study area in question. The Large
Groundfish Trawler activity is now ready to estimate the indirect and induced effects of goods and
services purchased by the Large Groundfish Trawl vessels. The effects of payments to captain, crew,
and proprietors using the analysis by parts approach.

Figure 2. Large Groundfish Trawler industry spending pattern example
Activity Type
Industry Spending Pattern

Sector
3001
3002
3003
3004
3005
3006
3010
3013
3015
3017
3027
3041
3042
3043
3044
3045
3046
3047
3048
3050
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3062
3063
3064
3065
3066
3067
3068
3069
3070
3083
3085
3105

Activity Name
Large Groundfish Trawler

Actiity Level
1

Event Value
0.00000093
0.00000553
0.00033032
0.00020865
0.00001093
0.00000951
0.00000296
0.00009052
0.00000200
0.00775418
0.00000015
0.00024154
0.00003284
0.00005496
0.00003994
0.00000112
0.00006533
0.00023512
0.00007519
0.00005003
0.00022556
0.00019185
0.00051625
0.00074862
0.00061542
0.00021462
0.00012303
0.00007312
0.00164051
0.00040442
0.00075784
0.00042171
0.00003310
0.00032730
0.00018928
0.00007958
0.00022747
0.00027572
0.00976184
0.00024055
0.00021683
0.00112477

Local Direct
Purchase
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%

Figure 2. Large Groundfish Trawler industry spending pattern example (Continued)
Activity Type
Industry Spending Pattern

Sector
3107
3109
3115
3138
3141
3142
3149
3150
3216
3225
3227
3256
3259
3266
3271
3283
3290
3319
3321
3323
3324
3326
3329
3330
3332
3333
3334
3335
3337
3339
3340
3354
3357
3393
3394
3410
3416
3425
3436

Activity Name
Large Groundfish Trawler

Event Value
0.00508185
0.00066741
0.06619659
0.00245623
0.00000244
0.00152794
0.00023378
0.00018634
0.00020329
0.00210726
0.00012873
0.00021006
0.00034217
0.00014568
0.00028796
0.00133483
0.14267499
0.06811651
0.00000141
0.00005121
0.01079769
0.03849354
0.00048528
0.00118954
0.00000710
0.00120790
0.00002567
0.00028480
0.00083260
0.00002267
0.00001297
0.01136448
0.04634027
0.00087277
0.00145541
0.00677249
0.00414619
0.00867350
0.00009212

Actiity Level
1

Activity Year
2010

6.1. Analysis by Parts
In typical IO analysis, a shock to aggregate demand is placed on one of the industry sectors
or commodities that are included in the model. Total economic impacts or contributions are then
estimated as the backward linked effect of a demand change on the target industry or commodity.
To calculate the estimate, the direct effect of the demand change is multiplied with the respective
industry multipliers.
As explained by Manshel (2012) “Analysis-by-parts (ABP) does not start with an impact on a
target industry sector or commodity. Instead, we will specify the goods and services the target
industry purchases in order to satisfy a demand or production level. The purchase of these goods and
services from local sources actually represent the first round of indirect purchases by the target
industry. In addition to the goods and services (first part) we need to analyze the impact of the
payroll (second part) of our target industry necessary to meet the new demand or production level.”
In ABP the indirect and induced effects of goods and services purchased by a fishing vessel
sector is the “first part” of calculating the economic impact of a given level fishery harvest. The
“second part” is payments to captain, crew, and proprietors. The impact of payments to captain,
crew, and owners for a given level of harvest is estimated separately using the Labor Income Activity
described above. The sum of these two impacts is the total indirect and induced effects of a given
level of fishery harvest. To these indirect and induced effects the direct effects must be added to
reach the total effects of a given level of harvest. An example of the approach is shown below.
In IO-PAC, there are a few additional wrinkles in the ABP approach. First, on the
commercial side because we are modeling the effect to both processors and harvesters, the ABP must
be done for both. Additionally, the treatment tax revenue paid by harvesters is one additional “part”
needed to estimate each impact for state and West Coast level study areas. Taxes are part of the
production function of the commercial fishing harvesters. These taxes paid are not part of their
industry spending patterns. For state and West Coast study areas, these taxes are assumed to be
endogenous. The implication is that government spending will be affected by changes in tax
payments from fishery participants. These payments are assumed to be subsequently spent by state
and local governments. State and local government spending is expected to follow the State and
Local Government Non-Education institutional spending pattern that is contained in IMPLAN.

7. Impact Estimation
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. On the commercial side, economic
impacts can be made on a commodity or industry basis.
29

IO models are designed to estimate the backward linked effects of a change in demand on
a given industry or change in demand for a given commodity. For commercial vessel landings,
IO-PAC utilizes a technique outlined by Steinback (2004) to use IO models for a change in
production rather than a change in demand. If we were using the IO model in the standard way
to estimate the backward linked impact of a shock to processed seafood demand, we would run a
single direct commodity effect on processed seafood. The backward linked effect of that change
in processed seafood demand would hit every firm involved in the production and distribution of
seafood. A margin would hit the retailers, wholesalers, and processors. Harvesters would be hit
as an indirect effect, because they supply the processors with a production input. The processor
multiplier would have an embedded indirect effect of a change in harvester landings. The
approach outlined by Steinback (2004) involves exogenously shocking the relevant seafood
sectors (harvesters and processors) and setting their regional purchase coefficients (RPCs) to 0 to
avoid double counting and feedback effects. By following this approach we are tricking the IO
model to give us the economic impact of a change in "demand" for seafood at the processor and
harvester stages of production separately. Because the RPC on harvesters is set to 0, there is no
indirect effect on harvesters from a change in processor production. Because the indirect effect
on harvesters of a shock to processors is absent, the two effects can be summed without double
counting.
With a given change in commercially harvested fish, how are the economic impacts
estimated? One must decide whether a shock is more appropriately targeted on a commodity or
industry sector included in the model. The appropriateness of commodity versus industry shocks
depends on the research question.6 Assuming the appropriate target is the Large Groundfish
Trawlers (LGT) industry sector, the impacts are estimated as follows. First, the LGT revenue is
run through their production function. The LGT production function is in the form of an
industry spending pattern imported into IMPLAN. The function can be seen using the “Setup
Activities” screen in IMPLAN (Figure 3). The activity is named “Large Groundfish Trawler.”
Choosing the activity will cause the production function information specific to LGTs to show
up in the events window. The “Sum of Event Values” at the bottom of Figure 3 shows the total
share of LGT output that is used for factors of production excluding labor, so 45% of LGT
revenue is used for inputs such as fuel, insurance, etc. The exogenous change in LGT harvest is
entered in the “Level” cell. In this example, $1 million in revenue is entered.

See Leonard and Watson (2011) for a more detailed discussion of commodity versus industry impacts.

Figure 3. Large Groundfish Trawler industry spending pattern activity

Second, employee compensation and proprietary income is shocked with the same $1
million. The labor effect is contained in the activity “LGT Labor.” It is imported as a Labor Income
Change. The labor income in the event is set to the proportion of total industry output (TIO) among
LGTs that is paid to employees (captain and crew) and proprietors (vessel owners). Figure 4
indicates that among LGTs the shares paid to employees and proprietor are 0.39 and 0.11
respectively. Importing labor income as a share of TIO, allows the “Level” to be shocked with the
same exogenous revenue run through the LGT spending pattern. In this example, we shocked LGT
revenue by $1 million.

Figure 4. Large Groundfish Trawler labor income

Third, since the study area for this model is the whole West Coast, we import the
institution spending pattern for State and Local Government Non-Education (SLG). The share of
industry output paid in taxes is treated as endogenous in the state level and West Coast study areas.
The base institution spending pattern for SLG is put in EXCEL and coefficients for each of the
commodity purchases’ are scaled so that the sum of commodity purchases equals the share of TIO
paid in taxes among LGTs. This enables the “Level” to be shocked with the same exogenous
revenue run through the LGT spending pattern. In this example, we shocked LGT revenue by $1
million.

Figure 5. Large Groundfish Trawler state and local govt. non-education

To complete the intermediate and induced effect of a $1 million change in LGT revenue
the Large Groundfish Trawler spending pattern, LGT labor income, and LGT S/L NonEducation are all combined in a single analysis scenario dubbed “LGT” in Figure 6.

Figure 6. Large Groundfish Trawler impact scenario

The analysis by parts results indicate the total indirect and induced effects of a $1 million
change in LGT revenue. The impact results for the West Coast study are for an increase in
output of $1.37 million and an employment change of 9.5 jobs. This is the total indirect and
induced effect of a $1.0 million change in LGT harvest. To this amount, the direct effects on
harvesters must be added (Steinback et. al, 2008). The direct output and employment of LGTs
are $1.0 million and 8.4, respectively. Altogether, the direct, indirect, and induced effect on
output is $2.37 million and on employment is 17.9 jobs.
After estimating sales by seafood processors, the analysis by parts approach must be
conducted in the same manner as for harvesters. Estimated sales changes for seafood processors
are made by using product flow in IMPLAN for the default seafood processing sector (71) and
markup margin information obtained through the EDC program. For all port level study areas, it
is assumed that landings from the fish harvesting sectors flows to seafood processors in the same
proportion as the default IMPLAN intermediate processor demand (sector 61) to fish harvesting
supply (17) ratio. This value is determined by constructing a default IMPLAN model for the
study area of interest, then examining the commodity balance sheet for the harvested fish
(commodity 3017). For the West Coast example here, it is assumed that 100% is processed.
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 EDC data (Table 10). These
producer values are then entered as the change in direct sales for the seafood processing sector.
For each study area, ΔLk represents the change in total fish landings among vessel classification
k, p represents the ratio of processor demand (sector 61) of the commodity fish to the available
fish harvesting supply (sector 17), and mj represents the markup for species j, then the change in
sales for seafood processors (ΔPS) is given by
(11) PS   Lk ( p)(m j )
k

In our example of a $1.0 million change for LGT, assume that the landings are
comprised only of sablefish. For the West Coast it is assumed that 100% of the sablefish is
processed. Table 10 indicates that the markup for sablefish is 1.61, so for a $1.0 million increase
in sablefish delivered to processors, processor revenue is $1.61 million. The analysis by parts
approach is used to estimate the impact of the $1.61 million in the same manner as for
harvesters. The total output and employment change resulting from a $1.61 million change in
processor revenue are $2.6 million and 18.53, respectively.
The results from the analysis by parts results for both LGTs and processors are combined
to reach the total change resulting from $1.0 million change on LGT sablefish landings. Because
LGTs and processor effects are separated as a result of our breaking the link between processors
and harvesters, the results of each can be added together without double counting. The sum of
both the LGT and processor effects is $4.95 million in economic output and 36 jobs.
On the recreational side, recreational spending vectors for private and charter vessel
effort are created in EXCEL and imported into IMPLAN as commodity and industry change
vectors. The commodity change and industry change vectors are scaled so that the sum of all
affected commodities and industries equals one. Because the vectors are scaled, a change in
recreational spending is entered using the “Level” under “Set Up Activities” in IMPLAN A
snapshot of private boat recreational commodity purchases is shown Figure 7. A hypothetical
expenditure change of $1.0 million is entered in the “Level.” Notice that the sum of event values
near the bottom of the figure is 0.75. This indicates that 75% of every dollar in expenditure
entered in the “Level” will be distributed to the commodity categories. The other 25% is
accounted for in the industry changes for private boat recreational fishing. 25% of each dollar in
the “Level” will be distributed to one of the industry categories. The total effect of the $1.0
million change is done by creating an “Activity Scenario” that includes both the commodity
changes and industry changes. In this $1.0 million example, the total economic output estimate
is $1.88 million and 14.5 jobs.

Figure 7. Private Recreation Commodity Purchases

8. Discussion
The revision of IO-PAC is intended to make use of the latest commercial fishery cost
earnings data collected by the Northwest Fisheries Science Center, incorporate more recent
IMPLAN data, add a recreational component that can be used for contribution and impact
estimates resulting from recreational fishing trips, add separate mothership and catcher-processor
sectors, and migrate IO-PAC to IMPLAN version 3.
Since the first version of IO-PAC was completed (Leonard and Watson, 2010), the
voluntary cost earning surveys used to develop the production functions for the commercial
fishing sectors in the model have been reprised. The IO-PAC revision incorporates these latest
survey results. Because of the expanded scope and increased detail of the more recent surveys,
incorporating the more recent data has the added benefit of likely increasing the accuracy of IOPAC, especially for vessel classifications that were previously not covered or partially covered.
The revision to IO-PAC increases the baseline IMPLAN data from 2006 to 2010. The
IMPLAN data are based on economic relationships in 2010 as opposed to 2006 before the
revision. Impacts of management actions in succeeding years are determined by converting the
estimated changes in gross revenues to year 2010 dollars before the impacts are estimated.
IMPLAN then converts the impact estimates back to the year of the input data (through 2030).
This process accounts for the effects of inflation on the impact estimates. The economy wide
data that is contained in IMPLAN is slow to change. Technical change and demand remain in
the economy as a whole remain relatively stable. As a result, the 2010 IMPLAN data will be
suitable for use in IO-PAC for several years to come7.
The inclusion of a recreational component permits the revised version of IO-PAC to be
used for recreational fishing contribution and impact estimates. The inclusion of the recreational
component was enabled through the use of recreational expenditure data for 2006 (Gentner and
Steinback, 2008) and charter vessel cost earnings data collected by the PSMFC (2004) and the
NWFSC in 2006.
The revision also includes shoreside processor data collected through the EDC program
and changes the method of assessing the proportion of harvested fish that is passed to processors.
The inclusion of the EDC data likely reduces the error in estimating processor impacts. Prior to
the EDC, estimates where made using non-species specific production function margins (markup) for seafood processors. A limitation to the prior approach is that a dollar of any species will
generate the same revenue to processors. While less obvious, the prior approach was also prone
to error because the default production functions contained in IMPLAN are based on Economic
7

Opinions differ as to how frequently the input output data should be update. Based on the CIE review of IO-PAC
completed in October 2009, the opinion of reviewers was every 3-5 years. The Benchmark Input-Output Table
constructed by Bureau of Economic Analysis is updated every five years.

Census data for processors in the entire United States. If seafood production practices on the
West Coast differ from those of the United States as a whole, this approach is prone to error.
The current revision includes a substantial change in model construction that migrates
IO-PAC to IMPLAN version 3 software. This migration reduces the effort in making production
function changes when newer cost earnings data are available and in creating models for
different study areas. The real advantage of the new approach is that once the production
functions for the different fishery sectors are completed in a model for one study area, such as
the West Coast, they can be imported into an alternative study area with click of a button.
Models for all 22 study areas included in the model can be completed in a couple of days rather
than weeks. Additionally, the new approach permits customised study areas to be completed
with minimal effort.
There are several areas where the revised IO-PAC can potentially be further improved.
First, IO-PAC relies on a weighted average production function for the shoreside commercial
vessels on the West Coast that are not currently covered by NWFSC cost earnings surveys.
Second, for the at-sea fleet, which includes motherships and catcher-processors, IO-PAC does
not currently include a production function due to their historical exclusion from the NWFSC’s
voluntary cost earnings surveys.
On the recreational side, IO-PAC’s expenditure estimates are not port specific and were
made based on expenditures that occurred in 2006. For port level impacts, estimates from IOPAC may understate or overstate the effects of changes in recreational fishing effort if port area
expenditures of recreational anglers differ from state level estimates. Additionally, recreational
expenditures may have changed since 2006, both in the level of spending per trip and the basket
of goods and services purchased. To the extent that mean recreational trip expenditures have
changed since 2006, there is potential for error in the estimates.
Lastly, the charter vessel sector created for CA is based on cost earnings data from 2000
while WA and OR are based on cost earnings data from 2006. Although this represents the most
recent data available, there is the potential for error if the cost and earnings of vessels operating
as charter vessels has changed since the data were collected.
There are several improvements planned for IO-PAC to address these issues. Many of
the planned improvements to IO-PAC will be enabled through the use of data collected in the
mandatory EDC program.8 It is expected that data collected through the EDC will lead to
improvements in the vessel production functions in IO-PAC. Unlike the voluntary cost earnings
surveys, nearly all of the vessels that participate in the West Coast groundfish fishery are
expected to complete an EDC survey. This will lead to improvements in the specification of
production functions currently covered by the voluntary cost earnings surveys, and increased
coverage to sectors not previously covered by the voluntary efforts such as motherships and
catcher-processors. Additionally, the EDC will provide the data necessary to construct unique
production functions for mothership and catcher-processor sectors.

The regulations detailing the Economic Data Collection program (50 CFR 660.114) are available online at:
http://www.nwfsc.noaa.gov/research/divisions/fram/economic_data.cfm.

Additional planned improvements include updated recreational expenditure estimates and
updated charter cost earnings data. The 2011 National Marine Recreational Fishing Expenditure
Survey9 is currently being compiled. The data is expected to be available in the next couple of
months. On the charter recreational front, in 2013 cost earnings surveys of California vessels
will be completed by the Southwest Fisheries Science Center and the NWFWSC will complete a
survey of those in WA and OR.

See additional information online at http://www.st.nmfs.noaa.gov/st5/documents/Nationwide_brochure.pdf

References
CFR (Code of Federal Regulations). 2010. 50 CFR § 660.114. Trawl fishery—economic data collection
program. Online at http://ecfr.gpoaccess.gov/cgi/t/text/textidx?c=ecfr&sid=6e3adf5fe27
94843765901aa0c829f4c&rgn=div8&view=text&node=50:11.0.1.1.1.4.1.5&idno=50 [accessed
29 December 2011].
Gentner, Brad, and Scott Steinback. 2008. The Economic Contribution of Marine Angler
Expenditures in the United States, 2006. U.S. Dep. Commerce, NOAA Tech. Memo. NMFSF/
SPO-94, 301 p.
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.
MIG. 2010. Version 3.0 User’s Guide. 502 2nd St., Ste 301, PO Box 837, Hudson, WI 54016.
PSMFC (Pacific States Marine Fisheries Commission). 2004. West Coast Charter Boat Survey Summary
Report, 2000. 205 SE Spokane St., Suite 100, Portland, OR 97202.
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.
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.
U.S. Dept. Commerce. 2011. Fisheries Economics of the United States, 2009. NOAA Tech. Memo.
NMFS-NWFSC-118, 172 p.
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. The main difference between these allocations and those
presented in Leonard and Watson (2011) is the movement to a new industry classification system
in IMPLAN.

Harvester Expenditures
Fuel and lubricant expenses were allocated based on the IMPLAN default margin table
for sector 115 (petroleum refineries).
Sector
3115
3319
3333
3334
3335
3337
3326

Title
Refined petroleum products
Wholesale trade distribution
services
Rail transportation services
Water transportation services
Truck transportation services
Pipeline transportation services
Retail Services - 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 (2005), 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
3001
3002
3003
3005
3004
3006
3010
3013

Title
Oilseeds
Grains
Vegetables and melons
Tree nuts
Fruit
Greenhouse, nursery, and floriculture products
All other crop farming products
Poultry and egg products

Proportion
6.36E-05
0.000379
0.022642
0.000749
0.014302
0.000652
0.000203
0.006205

3015
3027
3041
3042
3043
3044
3045
3046
3047
3048
3050
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3062
3063
3064
3065
3066
3067
3068
3069
3070
3141
3319
3332
3333
3334
3335
3339
3340
3321
3323
3324
3326
3329
3330
3436

Forest, timber, and forest nursery products
Other nonmetallic minerals
Dog and cat food
Other animal food
Flour and malt
Corn sweetners, corn oils, and corn starches
Soybean oil and cakes and other oilseed products
Shortening and margarine and other fats and oils products
Breakfast cereal products
Raw and refined sugar from sugar cane
Chocolate cacao products and chocolate confectioneries
Chocolate confectioneries from purchased chocolate
Nonchocolate confectioneries
Frozen foods
Canned, pickled and dried fruits and vegetables
Fluid milk and butter
Cheese
Dry, condensed, and evaporated dairy products
Ice cream and frozen desserts
Processed animal (except poultry) meat and rendered byproducts
Processed poultry meat products
Bread and bakery products
Cookies, crackers, and pasta
Tortillas
Snack foods including nuts, seeds and grains, and chips
Coffee and tea
Flavoring syrups and concentrates
Seasonings and dressings
All other manufactured food products
Soft drinks and manufactured ice
All other chemical products and preparations
Wholesale trade distribution services
Air transportation services
Rail transportation services
Water transportation services
Truck transportation services
Couriers and messengers services
Warehousing and storage services
Retail Services - Furniture and home furnishings
Retail Services - Building material and garden supply
Retail Services - Food and beverage
Retail Services - Gasoline stations
Retail Services - General merchandise
Retail Services - Miscellaneous
Noncomparable foreign imports

0.000137
1.00E-05
0.016556
0.002251
0.003767
0.002738
7.65E-05
0.004478
0.016116
0.005154
0.003429
0.015461
0.01315
0.035386
0.051314
0.042184
0.014711
0.008433
0.005012
0.112448
0.027721
0.051946
0.028906
0.002269
0.022435
0.012974
0.005455
0.015592
0.018899
0.06019
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
0.00834
0.006314

Ice expenses were allocated based on the IMPLAN default margin table for sector 70
(soft drink and ice manufacturing).
Sector

Title

Proportion

3070
3319
3333
3334
3335
3324
3326

Soft drinks and manufactured ice
Wholesale trade distribution services
Rail transportation services
Water transportation services
Truck transportation services
Retail Services - Food and beverage
Retail Services - Gasoline stations
Total

0.628331
0.10275
0.000222
3.14E-05
0.006453
0.193154
0.069058
1.000000

Repair and maintenance expenses for vessel gear and equipment were allocated to sector
290, which includes ship building and repairing.
Sector
3290

Title
Ships

Total

Proportion
1.00
1.00

Moorage expenses were allocated to sector 410, which includes the activities of marinas.
Marinas usually offer mooring, dockage, and haul out services for a fee.
Sector
3410

Title
Other amusement and recreation
Total

Proportion
1.00
1.00

Insurance expenses for vessels were allocated to sector 357, which includes
establishments primarily engaged in underwriting and assuming the risk of insurance policies.
Sector
3357

Title
Insurance
Total

Proportion
1.00
1.00

Interest and financial services were allocated to sector 354, which includes
establishments primarily engaged in financial services.
Sector
3354

Title
Monetary authorities and depository credit services
Total

Proportion
1.00
1.00

Purchases and leases of permits were allocated to IMPLAN’s value-added sector, other
income.
Sector
Value-added

Title
Other Income
Total

Proportion
1.00
1.00

Enforcement expenses were allocated to sector 416, which includes electronic and
precision equipment repair and maintenance.
Sector
3416

Title
Electronic and precision equipment repairs and
maintenance

Proportion
1.00

Total

1.00

Dues were allocated to sector 425, which includes civic, social, professional, and similar
organizations.
Sector
3425

Title
Civic, social, and professional services
Total

Proportion
1.00
1.00

Moorage expenses were allocated to sector 410, which includes the activities of marinas.
Marinas usually offer mooring, dockage, and haul out services for a fee.
Sector
3410

Title
Other amusement and recreation
Total

Proportion
1.00
1.00

Freight supplies expenses were allocated using the default IMPLAN margin table for
sector 126 (paperboard container manufacturing).
Sector
3107
3319
3332
3333
3335
3330

Title
Paperboard containers
Wholesale trade distribution services
Air transportation services
Rail transportation services
Truck transportation services
Retail Services - Miscellaneous
Total

Proportion
0.581083
0.016356
0.000463
0.026539
0.130381
0.245178
1.000000

Offloading expenses were allocated to sector 410, which includes the activities of
marinas. Marinas usually offer mooring, dockage, and haul out services for a fee.
Sector
3410

Title
Other amusement and recreation
Total

Proportion
1.00
1.00

Truck transportation was allocated to sector 335, truck transportation.
Sector
3335

Title
Truck transportation services
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
44

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
3083
3085
3105
3107
3109
3138
3138
3142
3149
3150
3216
3225
3227
3256
3259
3266
3271
3283
3333
3319
3323
3324
3326
3329
3330

Title
Curtains and linens
All other textile products
Paper from pulp
Paperboard containers
All other paper bag and coated and treated paper
Soaps and cleaning compounds
Soaps and cleaning compounds
Plastics packaging materials and unlaminated films and
sheets
Other plastics products
Tires
Air conditioning, refrigeration, and warm air heating
equipment
Other engine equipment
Air and gas compressors
Watches, clocks, and other measuring and controlling
devices
Electric lamp bulbs and parts
Power, distribution, and specialty transformers
Primary batteries
Motor vehicle parts
Rail transportation services
Wholesale trade distribution services
Retail Services - Building material and garden supply
Retail Services - Food and beverage
Retail Services - Gasoline stations
Retail Services - General merchandise
Retail Services - Miscellaneous
Total

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
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 for state and West Coast models were allocated to IMPLAN’s State and
Local Government Non-Education expenditure vector.
Sector
Institution Spending Pattern

Title
State and Local Government Non-Education
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 Processors
Seafood processor purchases were allocated as follows.

Additives
Commodity
3046
3059
3045
3044
3126

Title
Shortening and margarine and other fats and oils products
Processed animal (except poultry) meat and rendered
byproducts
Soybean oil and cakes and other oilseed products
Corn sweeteners, corn oils, and corn starches
Other basic organic chemicals

Proportion
0.5860

Total

Custom processing was allocated to the processed seafood commodity.
Sector
3061

Title
Seafood products
Total

Proportion
1.0000
1.00

Electrical utility expenses
Sector
3031

Title
Electricity, and distribution services
Total

Proportion
1.0000
1.00

Title
Truck transportation services
Rail transportation services
Air transportation services

Proportion
0.853
0.039
0.108
1.00

Freight expenses
Sector
3335
3333
3332

Total

Insurance expenses
Sector
3357

Title
Insurance
Total
46

Proportion
1.0000
1.00

0.1989
0.1428
0.0077
0.0647
1.000000

Natural gas and propane gas expenses
Sector
3032
3020

Title
Natural gas, and distribution
services
Oil and natural gas

Proportion
0.9924
0.0076
1.00

Total

Offsite storage and freezing
Sector
3340

Title
Warehousing and storage services
Total

Proportion
1.000
1.00

Packaging
Sector
3107
3108
3105
3146
3142

Title
Paperboard containers
Coated and laminated paper, packaging paper and plastics film
Paper from pulp
Polystyrene foam products
Plastics packaging materials and unlaminated films and sheets
Total

Proportion
0.8034
0.1392
0.0091
0.0048
0.0435
1.000000

Total

Proportion
0.2941
0.2206
0.4853
1.000000

Production supplies
Sector
3327
3325
3329

Title
Retail Services - Clothing and clothing accessories
Retail Services - Health and personal care
Retail Services - General merchandise

Rental or lease of buildings, job-site trailers, and other structures
Sector
3360

Title
Real estate buying and selling, leasing,
managing, and related services

Proportion

Total

1.0000
1.00

Rental or lease of processing machinery or equipment
Sector
3365

Title
Commercial and industrial machinery and
47

Proportion
1.0000

equipment rental and leasing services
Total

1.00

Repair and maintenance on facility buildings, machinery, and equipment
Sector
3039
3388
3417

Title
Maintained and repaired nonresidential structures
Services to buildings and dwellings
Commercial and industrial machinery and
equipment repairs and maintenance
Total

Proportion
0.363
0.364
0.273
1.00

Sewer and waste
Sector
3390

Title
Waste management and remediation services
Total

Proportion
1.0000
1.00

Shoreside monitors
Sector
3375

Title
Environmental and other technical consulting
services

Proportion

Total

1.0000
1.00

Water expenses
Sector
3033

Title
Water, sewage treatment, and other utility
services

Proportion

Total

1.0000
1.00

Other processors expenditures were allocated according to proportions contained in the
production function of the default processing sector in IMPLAN that were not allocated to any of
the cost categories already used above.
Sector
3319
3014
3381
3380
3377
3369

Title
Wholesale trade distribution services
Animal products, except cattle, poultry and eggs
Management of companies and enterprises
All other miscellaneous professional, scientific, and
technical services
Advertising and related services
Architectural, engineering, and related services

Proportion
0.2569
0.2188
0.1361
0.0636
0.0411
0.0402

3354
3190
3351
3366
3362
3374
3367
3368
3413
3338
3376
3356
3414
3149
3373
3425
3118
3411
3021
3202
3112
3355
3372
3416
3386
3138
3236
3375
3432
3433
3418
3352
3384
3148
3336
3363
3382
3389
3405
3247
3216

Monetary authorities and depository credit intermediation
services
Metal cans, boxes, and other metal containers (light gauge)
Telecommunications
Leasing of nonfinancial intangible assets
Automotive equipment rental and leasing services
Management, scientific, and technical consulting services
Legal services
Accounting, tax preparation, bookkeeping, and payroll
services
Restaurant, bar, and drinking place services
Scenic and sightseeing transportation services and support
activities for transportation
Scientific research and development services
Securities, commodity contracts, investments, and related
services
Automotive repair and maintenance services, except car
washes
Other plastics products
Other computer related services, including facilities
management
Civic, social, and professional services
Petroleum lubricating oils and greases
Hotels and motel services, including casino hotels
Coal
Other fabricated metals
All other converted paper products
Nondepository credit intermediation and related services
Computer systems design services
Electronic and precision equipment repairs and
maintenance
Business support services
Soaps and cleaning compounds
Computer terminals and other computer peripheral
equipment
Environmental and other technical consulting services
Products and services of State & Local Govt enterprises
(except electric utilities)
Used and secondhand goods
Personal and household goods repairs and maintenance
Data processing- hosting- ISP- web search portals
Office administrative services
Plastics bottles
Transit and ground passenger transportation services
General and consumer goods rental services except video
tapes and discs
Employment services
Other support services
Independent artists, writers, and performers
Other electronic components
Air conditioning, refrigeration, and warm air heating
49

0.0294
0.0189
0.0170
0.0135
0.0132
0.0125
0.0119
0.0106
0.0097
0.0084
0.0074
0.0068
0.0061
0.0047
0.0047
0.0043
0.0042
0.0041
0.0041
0.0040
0.0035
0.0034
0.0030
0.0028
0.0026
0.0025
0.0022
0.0021
0.0021
0.0019
0.0019
0.0018
0.0015
0.0014
0.0014
0.0014
0.0010
0.0009
0.0008
0.0008
0.0007

3320
3283
3387
3331
3106
3324
3415
3195
3404
3228
3323
3407
3239
3141
3403
3326
3410
3266
3330
3163
3259
3322
3321
3370
3328
3237
3238
3402
3313

equipment
Retail Services - Motor vehicle and parts
Motor vehicle parts
Investigation and security services
Retail Services - Nonstore, direct and electronic sales
Paperboard from pulp
Retail Services - Food and beverage
Car wash services
Machined products
Promotional services for performing arts and sports and
public figures
Material handling equipment
Retail Services - Building material and garden supply
Fitness and recreational sports center services
Other communications equipment
All other chemical products and preparations
Spectator sports
Retail Services - Gasoline stations
Other amusements and recreation
Power, distribution, and specialty transformers
Retail Services - Miscellaneous
Other concrete products
Electric lamp bulbs and parts
Retail Services - Electronics and appliances
Retail Services - Furniture and home furnishings
Specialized design services
Retail Services - Sporting goods, hobby, book and music
Telephone apparatus
Broadcast and wireless communications equipment
Performing arts
Office supplies (except paper)
Total

0.0006
0.0006
0.0006
0.0005
0.0005
0.0005
0.0004
0.0004
0.0004
0.0003
0.0003
0.0003
0.0003
0.0002
0.0002
0.0002
0.0002
0.0002
0.0002
0.0002
0.0002
0.0002
0.0002
0.0001
0.0001
0.0001
0.0001
0.0000
0.0000
1.000000

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

Title
Employee compensation
Total

Proportion
1.00
1.00

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

Title
Proprietary income
Total

Proportion
1.00
1.00

File Type	application/pdf
File Title	Microsoft Word - IOPAC_SSC_Review_Arpil_NWC
Author	Jerry.Leonard
File Modified	2013-03-20
File Created	2013-03-18