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Authors

EDWARD C. WATERS is a private consultant and assistant professor (courtesy appointment),

Department of Agricultural and Resource Economics, Oregon State University, Corvallis, OR

97331-3601; DAVID W. HOLLAND is a professor, Department of Agricultural Economics,

Washington State University, Pullman, WA 99164-6210; and RICHARD W. HAYNES is a

research forester, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station, Forestry Sciences Laboratory, P.O. Box 3890, Portland, OR 97208-3890.
The Economic Impact of Public Resource Supply

Constraints in Northeast Oregon

Edward C. Waters, David W. Holland, and

Richard W. Haynes

Interior Columbia Basin Ecosystem Management

Project: Scientific Assessment

Thomas M. Quigley, Editor

U.S. Department of Agriculture

Forest Service

Pacific Northwest Research Station

Portland, Oregon

General Technical Report PNW-GTR-398

April 1997
Abstract

Waters, Edward C; Holland, David W.; Haynes, Richard W. 1997. The economic impact of

public resource supply constraints in northeast Oregon. Gen. Tech. Rep. PNW-GTR-398.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station. 23 p. (Quigley, Thomas M., ed.; Interior Columbia Basin Ecosystem Management

Project: scientific assessment).

Traditional, fixed-price (input-output) economic models provide a useful framework for conceptualizing links in a regional economy. Apparent shortcomings in these models, however, can

severely restrict our ability to deduce valid prescriptions for public policy and economic development. A more efficient approach using regional computable general equilibrium (CGE) models as

well as a brief survey of relevant literature is presented. Computable general equilibrium results

under several different resource policy scenarios are examined and contrasted with a fixed-price

analysis. In the most severe CGE scenario, elimination of Federal range programs caused the loss

of 1,371 jobs (2.3 percent of regional employment) and $29 million (1.6 percent) of household

income; and an 80-percent reduction in Federal log supplies resulted in the loss of 3,329 jobs (5.5

percent of regional employment), and $76 million (4.2 percent) of household income. These

results do not include positive economic impacts associated with improvement in salmon runs.

Economic counter scenarios indicate that increases in tourism and high-technology manufacturing and growth in the population of retirees can largely offset total employment and income

losses. Evidence suggests that a regional economic transformation, characterized by stable or

declining employment in resource-based industries and growth in tourism and retirement-based

services, is already underway.

Keywords: Regional economics, computable general equilibrium models, input-output models,

economic base theory, public resource policy.
Preface

The Interior Columbia Basin Ecosystem Management Project was initiated by the Forest Service

and the Bureau of Land Management to respond to several critical issues including, but not

limited to, forest and rangeland health, anadromous fish concerns, terrestrial species viability

concerns, and the recent decline in traditional commodity flows. The charter given to the project

was to develop a scientifically sound, ecosystem-based strategy for managing the lands of the

interior Columbia River basin administered by the Forest Service and the Bureau of Land Management. The Science Integration Team was organized to develop a framework for ecosystem

management, an assessment of the socioeconomic and biophysical systems in the basin, and an

evaluation of alternative management strategies. This paper is one in a series of papers developed

as background material for the framework, assessment, or evaluation of alternatives. It provides

more detail than was possible to disclose directly in the primary documents.

The Science Integration Team, although organized functionally, worked hard at integrating the

approaches, analyses, and conclusions. It is the collective effort of team members that provides

depth and understanding to the work of the project. The Science Integration Team leadership

included deputy team leaders Russel Graham and Sylvia Arbelbide; landscape ecology-Wendel

Hann, Paul Hessburg, and Mark Jensen; aquatic—Jim Sedell, Kris Lee, Danny Lee, Jack Williams,

Lynn Decker; economic—Richard Haynes, Amy Home, and Nick Reyna; social science-Jim

Burchfield, Steve McCool, and Jon Bumstead; terrestrial-Bruce Marcot, Kurt Nelson, John

Lehmkuhl, Richard Holthausen, and Randy Hickenbottom; spatial analysis-Becky Gravenmier,

John Steffenson, and Andy Wilson.

Thomas M. Quigley

Editor

United States

Department of

Agriculture

Forest Service

United States

Department of

the Interior

Bureau of Land

Management

Interior Columbia

Basin Ecosystem

Management Project
Introduction

During the 1980s, annual timber harvest from

public lands in Oregon consistently approached

historic high levels. In 1990, timber harvests in

western Oregon began a dramatic decline,

largely reflecting increasing land use restrictions

because of the listing of the northern spotted

owl (Strix occidentalis caurina) as an endangered

species. East of the Cascade Range, however,

the decline has been less precipitous. Although

total cut on west-side National Forests (USDA

FS) decreased by 81 percent from 2,238 million

board feet Scribner rule (MMBF) in 1988 to

416 MMBF in 1993, over the same period,

east-side Forest harvest declined by 45 percent

from 1,250 MMBF to 685 MMBF (table 1).

This trend also is evident on Bureau of Land

Management (BLM) lands, although on the

east side, BLM harvests are of relatively minor

importance (Oregon Department of Forestry

1988-93).

Table 1 also shows an opposite, positive response for private timber. Private harvest

increased by 93 MMBF (3 percent) on the west

side and by 257 MMBF (51 percent) on the

east side. As a result, total harvest from these

three sources decreased by 44 percent on the

west side but by only 18 percent on the east

side, between 1988 and 1993.1

Historically, natural resource industries have

provided a significant portion of Oregon's

employment and income. In 1992, livestock

and timber-related industries together directly

provided an estimated 105,000 jobs, representing about 6.5 percent of total jobs and 7.7

percent of employee compensation paid in the

State (table 2). This total does not include

several thousand resource management jobs in

Federal, State, and local governments.

In the five northeast Oregon counties focused

on for this study (that is, Baker, Grant,

1

 Care should be taken when comparing historical

harvests. As cuts include more private and younger aged

trees, the ratio of total processed output to log input will

change, thereby creating a measurement problem. The

log-scale measurement was established lor large trees and

for times when logs were less fully used. As a result,

private timber harvest may contain 20 to 30 percent

more effective input than the log scale is measuring.

Umatilla, Union, and Wallowa Counties),

employment in livestock and timber-related

sectors is significantly more important. Of

about 60,000 regional jobs in 1992, livestock

directly provided 5,300 jobs. Logging, lumber,

and wood products provided another 4,100

jobs. Together, these industries contributed

about 1 5 percent of regional employment and

employee compensation (table 2).

Recent concern over the viability of several

native anadromous fish runs has jeopardized

traditional public land uses. Ecological disturbance caused by logging and riparian cattle

grazing has been shown to damage salmon

spawning beds. In July 1994, the Ninth Circuit

U.S. Court of Appeals issued an injunction that

would effectively stop grazing activities (and

eventually, perhaps, logging and road building)

in the Umatilla and Wallowa-Whitman National Forests. To help maintain viable spawning

habitat for threatened or endangered salmon,

considerable change in east-side public land

management policy may be necessary. Consequently, how much future access will be available to much of the remaining east-side public

forest land for timber harvest and cattle grazing

is uncertain.

Although it is unclear what changes in logging

and grazing policy will be introduced, the

relative importance of livestock and timberrelated industries in northeast Oregon suggests

that any reduction in access to these natural

resource inputs could have significant impacts

on regional employment and income.

Purpose

The main purpose of this study was to estimate

the regional economic impact of alternative

Forest Service policies regarding access to public

resources in northeast Oregon. As a prelude to

this analysis, we provide a historical overview of

the economy of northeastern Oregon over the

past quarter of a century.

Estimates of total change in regional employment and income are provided under different

assumptions about the nattire and size of the

policy shift and length of time over which adjustment to the new policy occurs. Analysis is

limited to examining the impact of hypothetical

resource supply constraints resulting from

1
Table 1—Annual Oregon timber harvest volume3

Ownership

USDAFS

BLM

Private

Total

1988

West

2,238

1,399

2,754

6,391

East

1993

West

Million board feet

1,250 416

40

505

1,795

339

2,847

3,602 1

East

686

23

762

,471

Change 1988 to 1993

West

MMBF

-1,822

-1,060

+93

-2,789

Percent

-81

-76

+3

-44

East

MMBF

-564

-17

+257

-324

Percent

-45

-43

+51

-18

' Volume is measured by using Scribner rule.

Source: Oregon Department of Forestry, 1988-93.

Table 2—The northeast Oregon regional economy, 1992a

Employment sectorsb

Livestock related

Other agriculture

Food processing

Logging and wood processing

Other agriculture and natural resources

Other employment

Total

State

Number

of jobs

24,461

42,454

25,053

81,074

26,110

1,420,848

1,620,000

Percent

1.5

2.6

1.6

5.0

1.6

87.7

100.0

Number

of jobs

5,353

3,744

2,792

4,101

1,484

42,294

59,768

Region

Percent

8.9

6.3

4.7

6.8

2.5

70.8

100.0

aNortheast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

b

 Full- and part-time employment.

Source: IMPLAN (Alward and others 1989) and Bureau of Economic Analysis, Regional Economic Information System, U.S.

Department of Commerce, 1969-92.

Table 3—Total and per capita personal income over time for

Category

Total personal income (thousand $)

Population (thousands)

Per capita personal income ($)

Total employment (jobs)

1969 1974 1979 1984

304,105.0 540,576.0 915,643.0 1,251,392.0

92.2 97.9 111.8 116.8

3,298.0 5.522 0 8,190 0 10,714.0

41,093 0 45,749 0 54,569.0 53,336.0

northeast Oregona

1989 1990 1991

1,542,637.0 1,632,475.0 1,717,510.0

112.0 1133 114.7

13,774.0 14,408.0 14,974.0

57,049.0 59,146.0 59,644.0

1992

1,818,414.0

116.1

15,662.0

59,768.0

aNortheast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

Source: Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, 1969-92.

2
implementation of salmon habitat protection

and improvement measures on Federal lands.

No attempt was made to estimate the effects of

other possible policy changes (for example, river

flow augmentation, commercial harvest restriction, and reduction in recreational access).

Besides a traditional analysis using a conventional, demand-driven fixed-price model,2

 this

study also presents results obtained by using

flexible-price, computable general equilibrium

(CGE) models of the regional economy. These

models provide several advantages over more

conventional regional models. The structure of

a CGE model is more consistent with neoclassical economic theory and flexible enough to

incorporate factor and commodity substitution

into the structure of production and demand.

A Profile of the Northeast

Oregon Regional Economy

The following discussion is based largely on

data obtained from the Regional Economic

Information System (REIS) of the Bureau of

Economic Analysis (BEA). The data describe

the regional economy of Baker, Grant, Union,

Umatilla, and Wallowa Counties in northeast

Oregon from 1969 to 1992. The region contains no metropolitan counties and is economically related to larger urban centers in Lewiston,

Idaho, and Walla Walla, Washington.

More than 116 thousand persons presently

reside in the five-county, northeast Oregon

region. From 1969 to 1992, regional population grew from roughly 92,200 to 116,100

persons (table 3). The number of full- and

part-time jobs increased from roughly 41,100

in 1969 to 59,800 jobs in 1992.

According to our estimates for 1992, full- and

part-time employment in agriculture and ag2

 For example, input-output (IO), economic base, and

social accounting matrix (SAM) models. These types of

models produce constant, marginal multipliers (that is,

invariant of the size of the economic shock) by assuming

that factor (labor and capital) supply constraints are

nonbinding; and that factor demand ratios, commodity

supply proportions, and all prices are fixed. Multipliers

derived from fixed-price models generally can be described

as providing an upper bound on the amount of economic

impact resulting from an exogenous demand shock.

ricultural processing was 13,373 jobs (table 2).

The corresponding employment figure for the

logging and woods products industry was 4,101

jobs. Agriculture and agricultural processing

contribute 22.4 percent of total jobs, whereas

lumber and wood products constitute 6.9

percent of total jobs. Combining the two

industries, we find that 29.3 percent of total

jobs in the region are in traditional natural

resource-based industries. By any measure,

resource-based industry is important to the

region. In the cases of cartle production and

logging and wood products industries, much

of the resource base is held as public lands. Behind these aggregate figures, however, stands a

dramatic, ongoing transformation of the regional economy.

We are especially interested in establishing the

current economic baseline for this economy and

reviewing structural changes that have characterized this economy over the last two decades.

As we move into the future, it will be important

to understand the past and the implications of

that past for future patterns of economic

development.

Sources of Personal Income

Personal income as defined by the BEA comes

from five different sources: (1) employee compensation, (mainly wages and salaries); (2)

interest, dividends, and rent (income derived

from property ownership); (3) transfers (mainly

social security and medicare payments); (4) proprietor income (income to self-owned businesses and farms); and finally (5) adjustments

to account for people who receive income in

the area but do not live there (for example,

commuters). The relative contribution of each

of these components to personal income is

summarized in table 4.

The major components of earned income arc

employee compensation and proprietor income.

In 1969, employee compensation made up

56.47 percent of total personal income. By

1992, the share had declined to 49.6 percent. In

1969, proprietor income contributed 21.16

percent of total personal income, 44 percent

from farms and 56 percent from nonfarm

sources. By 1992, the contribution of proprietor income to personal income had declined to

3
Table 4—Components of per capita personal income over time for northeast Oregona

Personal income category

Employee compensation per capita

Dividend interest and rent per capita

Transfers per capita

Proprietors per capita

Residence adjustment per capita

Personal income per capita

Employee compensation

Dividends, interest and rent

Transfers

Proprietors

Residence adjustment

Total percent

1969

1,922

409

365

720

-12

3,403

56.47

12.03

10.71

21.16

-.37

100.00

1974

2,782

688

751

1,439

45

5,705

48.76

12.07

13.17

25.22

.78

100.00

1979

4,636

1,194

1,223

1,150

260

8,462

54.78

14.11

14.45

13.59

3.07

100.00

aNortheast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

1984 1989

Current dollars

5,478

2,009

2,008

1,374

243

11,112

6,913

2,435

2,735

2,040

247

14,369

Percent

49.30

18.08

18.07

12.37

2.18

100.00

48.11

16.95

19.03

14.20

1.72

100.00

1990

7,482

2,466

2,985

1,823

264

15,021

49.81

16.42

19.88

12.14

1.76

100.00

1991

7,742

2,407

3,276

1,933

263

15,622

49.56

15.41

20.97

12.38

1.69

100.00

1992

8,092

2,399

3,548

2,005

286

16,329

49.55

14.69

21.73

12.28

1.75

100.00

Source: Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, 1969-92.

Table 5—Transfer payments over time for northeast Oregona

Transfer payment category

Retirement and disability insurance

benefit

Medical payments

Income maintenance benefits

Unemployment insurance benefit

Veterans benefits

Federal education and training

assistance

Other payments to individual

Total government payments

to individuals

Payments to nonprofit institutions

Business payments to individuals

Total transfers

Population (thousands)

Transfers per capita ($)

1969

20,902.0

3,628.0

1,628.0

1,621.0

3,387.0

72.0

65.0

31,379.0

1,484.0

753.0

33,616.0

92.2

365.0

1974

45,439.0

7,797.0

5,319.0

5,070.0

5,899.0

291.0

379.0

70,284.0

2,037.0

1,249.0

73,570.0

97.9

751.0

1979

84,076.0

19,178.0

9,961.0

6,553.0

7,539.0

1,167.0

716.0

129,275.0

4,555.0

2,878.0

136,708.0

111.8

1,223.0

1984 1989 1990

Current thousand dollars

141,695.0

40,322.0

15,303.0

15,023.0

9,061.0

2,268.0

359.0

224,075.0

5,647.0

4,816.0

234,538.0

116.8

2,008.0

172,305.0

71,190.0

22,071.0

13,687.0

9,558.0

3,702.0

427.0

293,006.0

6,699.0

6,569.0

306,274.0

112.0

2,735.0

186,536.0

82,387.0

24,721.0

16,581.0

9,891.0

3,764.0

553.0

324,519.0

6,973.0

6,761.0

338,253.0

113.3

2,985.0

1991

201,275.0

95,117.0

28,937.0

21,893.0

9,785.0

3,529.0

507.0

361,095.0

8,015.0

6,601.0

375,711.0

114.7

3,276.0

1992

213,747.0

106,395.0

32,766.0

28,100.0

10,519.0

3,897.0

696.0

396,131.0

8,790.0

6,980.0

411,901.0

116.1

3,548.0

•' Northeast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

Source: Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, 1969-92.

4
12.28 percent, 23 percent of which was from

farm and 77 percent from nonfarm sources.

Two major trends emerge from examination of

regional earnings data: (1) growth in wage,

salary, and proprietor income has not kept pace

with growth in transfer and property income;3

and (2) farm income has declined from roughly

one-half of proprietor income in 1969 to

roughly one-fourth of proprietor income in 1992.

Probably the most striking feature of the

structural change in personal income in the

region is the tremendous growth in transfer

income (table 4). Transfers grew from 10.71

percent of personal income in 1969 to 21.73

percent of personal income in 1992. Transfers

were the fastest growing component of personal

income, increasing twelvefold over the period

(in unadjusted terms). Per capita transfers

increased from $365 in 1969 to $3,548 in

1992, a nearly tenfold increase. By comparison,

total per capita personal income increased less

than fivefold over the same period.

The components of transfer income are displayed in table 5. In 1992, most of the transfers

were retirement and disability insurance benefits and medical payments. These two components make up nearly 78 percent of total

transfer income to the region. In 1992, income

maintenance benefit payments (the welfare part

of transfers) were $32.7 million, 7.9 percent of

total transfers. The other major component of

transfer income is unemployment insurance

benefits that constituted 6.8 percent of the total.

Transfers have become the second most important source of income in the region (after

employee compensation), and thus, should be

viewed as a vital part of the new economic base

of the region. The main components of transfer income are those received by retired persons

who settle in the region and bring with them a

significant amount of transfer and other property income.

Although not as dramatic as the trend in transfer income, income from dividends, interest,

and rent also is significant. The portion of

personal income from these sources increased

from 12.03 percent in 1969 to 14.69 percent in

3

 This is true for most rural Oregon counties.

1992 (table 4). On a per capita basis, the

portion accounted for by dividends, interest,

and rental income grew nearly sixfold from

$409 in 1969 to $2,399 in 1992.

We are not able to distinguish property income

originating from within the region from that

originating outside the region. We suspect,

however, tnat the portion coining from outside

has increased with the increasing attraction of

the region as a vacation and retirement destination. Thus, property-type income also must be

viewed as a part of the new economic base. Like

transfer income, it will be an important determinant of the direction of economic change in

the future. In 1992, transfer income and propertytype income combined to make up 36 percent

of total personal income in northeast Oregon.

Sources of Employment

Several features of the change in the structure of

regional employment are worth reviewing. Employment growth by all levels of government

did not keep pace with private sector employment growth. In 1969, government employment made up 24 percent of total nonfarm

employment. By 1992, the share declined to

22 percent (table 6).

The major structural change in private sector

employment was the growth in service-sector

employment to the exclusion of nearly all other

sectors. In 1969, service employment made up

23 percent of private nonfarm employment in

the region. In 1992, service employment made

up 30 percent of private nonfarm employment.

The number of service jobs more than doubled

from 5,996 jobs in 1969 to 12,335 jobs in

1992 (table 6).

In relative terms, job opportunities in manufacturing increased the least of the various employment sectors. Although manufacturing jobs

increased from 6,292 in 1969 to 8,506 in 1992,

these jobs declined as a percentage of total jobs

in the region. In 1969, manufacturing accounted for 24 percent of total private sector

jobs. In 1992, jobs in manufacturing declined

to 20 percent.

Our final observation regarding regional employment trends concerns proprietors, (that is,

self-owned businesses and farms), an economic

5
sectof in which another major change is evident. From 1969 to 1992, the number of farm

proprietors declined slightly from 4,469 to

4,393 (table 7). In the same period, the number

of nonfarm proprietors grew from 5,937 to

10,774. Farm proprietors have been relatively

constant, whereas the number of nonfarm

proprietors has nearly doubled. The result is

that proprietor employment and income is now

dominated by nonfarm business. This was not

the case two decades ago.

Summary of Regional Trends

Firms will remain under pressure to control

labor costs to remain competitive. This will

involve recent labor market trends such as

capital-labor substitution, corporate downsizing, and more competition for good jobs.

Much of future job growth is likely to go to

proprietors (self-owned business) rather than

wage labor jobs. For example, from 1989 to

1992, the number of wage and salary jobs grew

Table 6—Sectoral composition of employment over time for northeast Oregona b

Employment category 1969

Private nonfarm employment:

Agricultural services and

other ANRC

Mining

Construction

Manufacturing

Transportation and public

utilities

Wholesale trade

Retail trade

Finance, insurance and

real estate

Services+

Total private nonfarm

employment

Government employment:

Federal, civilian

Military

State and local

Total government

employment

Total nonfarm employment

Farm employment

Total employment

a

 Full- and part-time employment.

534

109

1,391

6,292

2,376

1,212

6,252

1,938

5,996

26,112

1,970

553

5,702

8,225

34,337

6,756

41,093

1974

708

142

1,643

6,854

2,701

1,419

7,303

2,208

6,963

29,951

1,534

554

6,604

8,692

38,643

7,106

45,749

1979

783

180

2,284

8,716

3,298

2,030

9,058

2,963

8,820

38,140

2,027

494

7,369

9,890

48,030

6,539

54,569

1984 1989

Number of jobs

935

68

1,781

7,915

2,982

1,869

8,746

2,784

9,601

36,904

2,005

569

7,075

9,649

46,553

6,783

53,336

1,205

146

1,600

8,191

3,187

2,087

9,471

2,533

10,818

39,250

2,258

561

8,025

10,844

50,094

6,955

57,049

b

 Northeast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

c

 ANR = Agriculture and natural resources.

1990

1,231

181

1,838

8,681

3,291

2,165

9,446

2,491

11,437

40,764

2,334

554

8,325

11,213

51,977

7,169

59,146

1991

1,336

159

1,878

8,642

3,268

2,068

9,528

2,486

12,005

41,374

2,240

552

8,480

11,272

52,646

6,998

59,644

1992

1,308

153

1,810

8,506

3,285

2,212

9,637

2,494

12,335

41,739

2,402

542

8,592

11,536

53,275

6,493

59,768

Source: Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, 1969-92.
by 1,530 jobs. Over the same period, the

number of proprietors grew by 1,189, almost

exclusively in nonfarm businesses (table 7). It

also seems likely that the growth of relatively

high-paying wage labor jobs will be limited,

especially in sectors producing highly competitive tradable goods.

The reduction in communication cost brought

about by computers and satellites favors relatively remote regions like northeast Oregon.

Some businesses, professionals, and proprietors

that were formerly unable to locate in the

region may now find it profitable to do so.

Examples include firms providing producer

services, a component of the services sector in

table 6. The service sector is usually thought of

as a nonbasic sector with sales mainly to the

local population. Although this is true of many

service businesses, it is also true that selected

service firms do export most of their services

outside the region. Examples are tourist-oriented and producer service businesses. The

communication revolution has opened the

location decision for export-oriented services.

Many of these businesses are choosing to locate

in high-amenity regions. It is likely that such

firms will become an even more important part

of the northeast Oregon economy in the future.

High-amenity value also is attractive to those

seeking recreation and retirement destinations.

The abundant natural amenities of the region

are becoming increasingly well known and

appreciated. As more people take advantage of

these attractions, we expect to continue to see

an increase in the proportion of transfer and

property income in the region.4

The Issue of Regional Economic Base

Although we have previously referred to the

term "economic base," we will here broaden our

discussion of this key concept. Economic base

(or export base) theory conceptually divides a

regional economy into "basic" and "nonbasic"

activities, postulating a causal relation between

the two. A basic activity is one that creates an

inflow of money in return for goods and services sold to buyers outside the region (that is,

"exported"). Regional economic activities that

are traditionally counted as basic include the

extractive industries (agriculture, mining, forestry, and fishing) and all primary and secondary manufacturing.

Export dollars received by basic activities are

used to purchase productive inputs of goods

and services, including labor. The degree to

which these goods and services are supplied by

regional producers and households determines

the amount of nonbasic activity in the region.

It is assumed that nonbasic activity is induced,

and therefore, could not exist without basic

activity. Traditional nonbasic sectors include

most services, retail trade, and state and local

government functions.

Multipliers are calculated as the ratio of total

activity (that is, basic plus nonbasic) to basic

4

 The future growth of transfer income also will depend

on the outcome of the current political debate in Congress.

Table 7—Characteristics of regional employment over

Employment category

Total proprietors:

Farm

Nonfarm

Total wage and salary

employment

Total employment

1969

10,406

4,469

5,937

30,687

41,093

1974

11,129

4,304

6,825

34,620

45,749

1979

12,023

3,851

8,172

42,546

54,569

time for

1984

northeast Oregona b

1989

Number of jobs

13,535

4,353

9,182

39,801

53,336

13,978

4,377

9,601

43,071

57,049

1990

14,186

4,293

9,893

44,960

59,146

1991

14,815

4,336

10,479

44,829

59,644

1992

15,167

4,393

10,774

44,601

59,768

a

 Full- and part-time employment.

b

 Northeast Oregon = Baker, Grant, Umatilla, Union, and Wallowa Counties.

Source: Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, 1969-92.

7
activity. In practice, estimates of industry

employment and payroll generally are used as

indicators of regional economic activity. Thus,

an economic base employment multiplier can

be interpreted as calculating the total number

of jobs generated by an increase in export sales

sufficient to require the addition of one job in a

regional basic industry.

Although useful in understanding how regional

economics work, the concept of economic base

has been subject to some criticism and much

discussion over the years. Critics point out that

the static nature of the hypothesized relation

between basic and nonbasic sectors fails to accommodate structural changes that characterize

a developing economy. Also, the linear relation

between basic and total activity is assumed

invariant relative to the magnitude and direction of the change. Thus an employment

multiplier of 2.0 would be used to predict an

increase of 20 total jobs in response to the

addition of 10 basic jobs, and a loss of 2,000

total jobs in response to the elimination of

1,000 basic industry jobs.

A more fundamental criticism concerns the

definition of basic activity. At the national level,

balance of trade statistics are kept. These include accounts of international flows of goods,

services, and finances. There is no authoritative

accounting of transboundary (that is, exports

and imports) flows, however, from subnational

regions. Consequently, it is necessary to estimate the contribution of the activities of various

industries to the economic base of a region.

Generally, this is done either by the simple

assignment method, in which all manufacturing

and resource-based activity is defined as basic,

or the location quotient method in which a

basic industry provides a greater proportion or

regional employment than is true of that industrv at the national level. Both of these methods

can create serious errors in the estimates of the

export base, especially if the structure of regional production and consumption is different

than the national average. Also, neither method

accounts for the growing prevalence of selfemployed activity, the emergence of nonmanufacturing exports (for example, producer

services), or the increasing importance of

transfer and property-type income.

Lately, the question of what activities constitute

Oregon's economic base has received much

attention. Until recently, the answer seemed

obvious: lumber and wood products industries

claimed a major share of employment, income,

and export sales of most counties. Links with

forestry, logging, transportation, and secondary

wood products industries, as well as substantial

industry payrolls, ensured that growth in wood

products had significant multiplier impacts on

regional economies. The almost pervasive

nature of employment in wood products is also

key. Mills have traditionally located near major

timber sources, often providing the main

employment in small towns and rural areas.

In a recent paper, Beuter (1995) reported that

in 1990, wood products industries provided

more than one-third of Oregon's economic

base, with forestry, fisheries, agriculture, and

food processing contributing another one-third.

According to Beuter, in eastern Oregon the

contribution of wood products was less, about

one-quarter, with forestry, agriculture, and food

processing contributing more than 50 percent

of the economic base of the region. Hightechnology manufacturing, much touted as the

foundation of Oregon's economic future,

comprised about 11 percent of the economic

base of the Portland metropolitan region but

less than 1 percent of the economic base statewide. Beuter's analysis stresses the importance

to the State economy of maintaining a viable

wood products industry. He also doubts

whether high-technology manufacturing will

ever become significant outside the Interstate 5

corridor because of its locational requirements,

which differ from those of the timber industry.

Beuter used 1990 location quotients to estimate

export base indices and defined basic activities

in a limited way, which tends to exaggerate the

importance of resource-based industries. His

analysis thus overestimates the current importance of wood products relative to other components of the regional economy. As evidence,

consider that since 1990, Oregon wood products employment lost more than 10,000 jobs,

whereas total employment in the State increased

by more than 50,000 jobs. Also between 1990

and 1994, Oregon's exports to foreign countries

increased 40 percent. This was largely due to

dramatic increases in high technology and agri8
culture sales, whereas foreign exports of lumber

and wood products remained about constant.

Although these aggregate numbers ignore the

important geographical aspects of the employment shift, they do indicate a trend that is not

predicted by a simple economic-base approach.

A major problem with standard economic base

analysis is that it excludes "nontraditional"

components of regional economic base. For

example, in 1992, combined transfer and

property-type income contributed 36 percent

of total personal income in northeast Oregon.

Most of this is derived from sources outside the

region. Federal Government spending is another important source of outside income often

overlooked by standard economic-base analysis.

Dollars from these outside sources directly

finance a large portion of industry purchases,

household consumption, and local government

activity, and thus, should properly be included

in the regional economic base.

Economic-base models provide a useful framework for conceptualizing economic links in a

regional economy. Apparent shortcomings,

however, can severely restrict our ability to formulate relevant prescriptions for public policy

and economic development. One alternative is

to use IO or SAM-based models. These fixedprice models provide internally consistent

representations of regional economic structure

but under restrictive assumptions (for example,

fixed-proportion production functions, unconstrained factor and commodity supplies, and

fixed or price-inelastic demand for goods and

services). Ideally suited to estimating the impact

of changes in final demand, fixed-price models

are severely limited in their applicability to

supply-side issues. A more efficient approach,

using regional CGE models is described below.

Natural Resource Constraints

and Regional Economic Analysis

For examples of innovative uses of fixed-price

models to analyze the impacts of natural resource constraints, the reader is referred to

Petkovich and Ching (1978) (mining), and

Waters and others (1994) (timber). Examples of

CGE applications to resource policy issues can

be found in Despotakis and Fisher (1988)

(petroleum) and Berck and others (1991) (water).

In the Pacific Northwest, several recent studies

have used fixed-price (constant multiplier)

methods to estimate impacts resulting from

implementation of hypothetical salmon recovery plans. To our knowledge, there has been no

comparable flexible-price analysis of this issue.

Aillery and others (1994) examine direct and

total impacts resulting from flow modifications

on the Snake River to facilitate downstream

migration of salmon. They estimate that reduced irrigation capacity could reduce agricultural employment in the Upper Snake River

basin by 2,500 jobs and total employment by

4,100 jobs.

Haynes and others (1992) compare the costs

associated with implementing salmon recovery

measures on National Forest land in the Columbia and Snake River basins with impacts of

eliminating timber, range, and recreation

programs in sensitive anadramous habitat areas.

The authors conclude that even under their

worst case scenario, any resulting job losses

would seem minor spread over tne entire region,

but would be significant in certain localities. Job

loss resulting from reduced timber availability in

the Umatilla and Wallowa-Whitman National

Forests is estimated at between 94 and 925 jobs,

depending on availability of private log supplies.

In a later study, by using similar methods, Bolon

and others (1994) compare incremental costs of

adopting the proposed interim PACFISPP

strategy on affected anadramous fish habitat

with estimates of foregone sales if timber, range,

and recreation programs on Western public

lands were eliminated. Their baseline scenario

includes any de facto restrictions on logging,

grazing, and recreation activities resulting from

recent legal and administrative actions. Consequently, the additional costs of implementing

PACFISH seem minor compared with the value

of timber and recreation programs on Federal

lands. It seems, however, that the costs incurred

in implementing the guidelines on public range

may exceed the value of the Federal grazing

program, particularly on BLM land. No esti5

 Comprehensive strategy for improved Pacific salmon

and steclhead habitat management developed by the

USDA Forest Service in 1992-93. PACFISH specifies

riparian management objectives to assure maintenance

or restoration offish habitat.

9
mate of regional employment or income impacts was provided.

A detailed study by Robison and Freitag (1994)

presents estimates of job and earnings impacts

resulting from timber supply reductions in the

three Oregon counties associated with the

Wallowa- Whitman National Forest. The authors used nine community-level, economicbase models to derive employment and earnings

response assuming a 56-percent (-167 MMBF)

reduction in available log supplies and a particular geographical distribution of mill cutbacks and closures. In aggregate, they estimate

that the three-county region would lose 1,943

jobs accounting for $56 million in earnings.

The authors estimate it would take a fourteenfold increase in recreation activity to replace

these lost jobs, or a twenty-eightfold increase to

replace lost earnings,6 Finally, Robison and

Freitag emphasize the uneven distribution of

local economic impacts. They estimate that

Union County would lose 15 percent of earnings and 13 percent of jobs, with the community of North Powder losing 70 percent of its

employment. Wallowa County would lose 11

percent of earnings and 13 percent of jobs, with

the communities of Wallowa and Joseph each

losing more than 40 percent ot their job base.

Obermiller examined impacts of the range

restrictions by using an updated, survey-based,

IO-type model of the Wallowa County

economy (Obermiller and West 1983). He

assumes that the direct effect of closing the

Wallowa-Whitman National Forest to livestock

grazing would reduce the cattle herd by 38

percent. Total impacts resulting from the

closure include a $2.5 million (42 percent of

1981 baseline) reduction in cattle sales, $6.3

million (2.8 percent of 1981 baseline) reduction

in total regional sales, and $1.25 million (2

4

 Th e basis fo r this calculation , however, seems curiou s

given their description ot" the regional export base in

which tourism was estimated to generate 4 percent of

earning s i n th e three-counr y region .

Obrmiller, E 1994. The local monetary costs of

closure of the Wallowa-Whitman National Forest in

Wallowa County, Oregon, to domestic livestock grazing;

report to the Wallowa County Court. On file with: Fred

Obermiller, Oregon State University, Department of

Agricultural and Resource Economics, Corvallis, OR

97331-3601 .

percent of 1981 baseline) reduction in local

household income.

Niemi and others8 estimated economic impacts

of legal restrictions on public grazing. They

juxtapose the relatively small localized impacts

of the grazing restrictions against the backdrop

of a diverse, 13-county economy spread across

parrs of three states (Oregon, Washington, and

Idaho). The authors offer severe criticism of

Obermiller's results but do not provide quantitative counter estimates. They predict that "for

the region as a whole, the positive impacts of

the injunction should outweigh the negative

ones, especially in the long run." Niemi and

others (1994) emphasize the inherent dynamism of this regional economy, stating that

economic growth is being driven by population

growth, which is strongly linked to quality of

life and natural environmental amenities.

Traditional resource-based industries, which

tend to consume or alter these natural amenities, are shrinking and have become relatively

unimportant as a source of regional growth.

These themes are supported by both Power9

(1995) and Rasker (1995).

Also, the cost estimates associated with salmon

recovery efforts reported above should be placed

in proper perspective against the potential

gains. Radtke and Davis10 (1995) estimated the

annual state-level economic contribution of a fully

restored salmon run (10-16 million fish) at $136

million to $273 million in exvessel sales, providing

13,000 to 25,000 total jobs and $254 million

to $507 million personal income state-wide.

8

 Niemi, E.; MacMullan, E.; Whitelaw, E. 1994.

Economic consequences of an injunction to protect

salmon habitat on the Wallowa-Whitman and Umatilla

National Foresrs; report prepared for Pacific Rivers

Council. On file with: ECO Northwest, 99 W. Tenth

St., Suite 400, Eugene, OR 97401. (Note: The Pacific

Rivers Council is the lead plaintiff in the lawsuit that

brought the Ninth Circuit US Court injunction

restricting grazing in the Umatilla and WallowaWhitman National Forests).

9

 Power, T. 1995. Economic well-being and environmental protection in the Pacific Northwest. Unpublished

report. On file with: University of Montana, Economics

Department, Missoula, MT 59812.

10

 Radtke, H.; Davis, S. 1995. An estimate of the asset

value for historic Columbia River salmon runs; report

prepared for the Institute for Fisheries Resources. On file

with: Hans Radtke, P.O. Box 244, Yachats, OR 97498.

10
The Northeast Oregon CGE

Model

A regional CGE model consists of a system of

equations representing the equilibrium behavior

or factor and commodity markets and other

relevant economic institutions. The system can

simulate economic response to changes in

various policy, management, and behavioral

variables. A kev feature is the inclusion of

relative prices that reflect the economic scarcity

of all commodities and productive factors in the

model. Endogenous prices adjust until factor

and commodity market equilibrium conditions

are satisfied. Compared with fixed-price models, the CGE method is more consistent with

modern economic theory, allows greater flexibility in the specification of economic behavioral relations, and generally produces more

moderate estimates of economic impact.

Implementing a regional CGE model does not

require a priori designation of an economic

base. Basic activity is not necessarily limited to

a few traditional manufacturing sectors. In a

CGE model, economic change is governed by

supply-side (for example, available quantities of

productive goods and services) and traderelated constraints, rather than by backward

links transmitted via changes in final demand.

Also, because the opportunity to substitute

among resource inputs is subject to diminishing

returns in a CGE model, measures such as

employment multipliers are variable depending

on the level of resource inputs.

Figure 1 traces the basic steps of a regional

CGE modeling effort. First, data are collected,

organized, and reconciled into a benchmark

equilibrium data sci (the social accounting

matrix).11 Next, behavioral and accounting

relations are specified, and the model parameters are calibrated given the benchmark data.

Finally, the policy-change scenarios are introduced, and counterfactual equilibria represent11

 The data set for the northeast Oregon CGE was

assembled mainly from IMPLAN-generated regional

product accounts, state of Oregon tax and expenditure

data, and RE1S county income and employment

estimates. Timber harvest estimates (Oregon Department

of Forestry) and livestock grazing statistics (Bedell 1984,

Bedell and Stringham 1984, Hewlett and others 1987)

also were used to estimate benchmark resource flow levels.

ing the situation under the new policy regimes is

calculated. Impacts are estimated by comparing

the counterfactual equilibria against the benchmark scenario.

Structure of the Northeast Oregon

CGE Model

Allocation of all resources and commodities m

the northeast Oregon CGE model is a function

of economic scarcity as reflected by the relative

prices of all goods, services, and productive

factors. Thus, price variables assume a preeminent role in the model. Key determinants of

relative prices include (1) factor supply and

production constraints; (2) ability of regional

consumers to substitute among alternative

sources of commodity supply (that is, regional

industrial supply, regional nonindustrial supply,

and imported supply); (3) ability of regional

producers to supply alternative markets (that is,

regional versus outside the region, or "export");

and (4) demand conditions affecting regional

and export markets.

Figure 2 traces the links among components of

the regional CGE model.12 First, value is added

to inputs of labor, services of proprietors, and

capital via linearly homogeneous Cobb-Douglas

production functions, and combined with intermediate inputs to produce output for each sector

(X). Behavioral assumptions ensure that producers maximize economic returns by equating the

marginal factor cost with the value of the

contribution of each factor to marginal product.

Each unit of X is either sold to local buyers

(XXD) or exported outside the region (E). A

constant elasticity transformation function

(CET) governs the ease with which regional

producers can switch between regional and

export market destinations. Revenue maximizing behavior by producers determines the

proportion of output supplied to satisfy regional

demand versus export markets. Export demand

is assumed to be perfectly elastic (that is, world

commodity prices are fixed), whereas regional

demand is influenced by endogenous price and

income effects.

12

 A list of variables, parameters and equations, and

detailed descriptions of the CGE and fixed-price models

are available on request.

11
Figure 1—Flowchart of CGE modeling procedures.

Commodities produced for regional use (XXD)

are combined with available nonindustrial

supplies (GS, "government sales") to form total

aggregate supply from regional sources (XD).

This aggregation occurs via a constant elasticity

substitution (CES) function. The treatment of

government supplies as imperfect substitutes for

private supplies in generating total regional

commodity supply illustrates the flexibility of

the regional CGE framework. In constructing

the analysis for this paper, we imposed quantity

restrictions on government supplies of logs and

grazing.13 Regional supply (XD) is, in turn,

combined with competitive imports (M) via a

CES aggregation to form a composite absorption good (or service) for each class of commodity (Q). The role of the nested CES functions is

to allow partial substitution of public for private

13

 By using this framework, we also could have examined

the potential impact of public grazing or logging fee

(price) changes as an alternative policy.

12
Figure 2—Schematic of the northeast Oregon CGE model.

ment sales are assumed to be offset by transfers00

from other sources (that is, State and Federal

Government).15 Consumption by each of three

household income classes is driven by changes

in endogenous factor incomes and relative

commodity prices. Finally, business investment

spending can be treated as either exogenous or

endogenous, depending on the model specification and implied length of run.

Resource Shock Scenarios

The baseline for this study is the aggregate

estimated economic structure of the fivecounty, northeast Oregon region in 1992. All

direct-impact scenarios are measured as reduc15

 Although this assumption may tend to underestimate

the extent of regional economic adjustment, it is not

unreasonable given the currently changing relation

between state and local Fiscal responsibilities.

13

(and imported) sources of logs and forage.14

Expenditure minimization at both stages of

aggregation determines substitution between

XXD and GS, and between XD and M, respectively. The use of CET and CES functions in

the model accommodates the observed phenomenon of "crosshauling" in which simultaneous imports and exports appear in highly

aggregated commodity classifications.

Total supply of Q supports intermediate demand (ND) and final demand for consumer

goods (C), investment needs (IT), and government purchases (G). In this model, all spending

by local agencies of Federal, State, and local

government is fixed at baseline levels. Any

reduction in revenues from taxation or govern14

 This treatment contrasts with a fixed-price analytical

approach in which the relative proportions of inputs from

public, private, and imported sources is assumed to be fixed.
tions in resource supply relative to the 1992

baseline. It can be argued that in anticipation of

de facto or perceived changes in resource

management policy, considerable adjustment

already has occurred. Thus, using 1992 as the

base year will tend to overestimate the actual

impact of a future policy shift. It is also useful,

however, to view the effects of a major shift in

public policy and attitude against the backdrop

of a real level of resource use in the recent past.

Whether this level of resource use was sustainable in the longer term or would have been

reduced for other reasons (for example, forest

health, fire) is an important question but one

that is not directly addressed here. Positive

impacts associated with the expected improvement in salmon spawning and migration success

(for example, commercial and recreational

fishing) are not directly considered here.16

The main scenarios examined are as follows:

1. Moderate resource shocks:

A. A 25-percent reduction in Federal

grazing animal unit months (AUMs)

B. A 50-percent reduction in logging on

Federal lands

2. Severe resource shocks:

A. A 99-percent reduction in Federal

grazing AUMs

B. An 80-percent reduction in logging on

Federal lands

Each scenario is examined by using fixed-price

IO and flexible-price CGE methods. The CGE

model results also are examined under different

assumptions regarding the length of time over

which economic adjustment occurs. This is

done by assuming differing mobility of primary

factors (labor, proprietors, and capital) as

follows:

• Short run (1-2 years):

• Only labor is able to adjust. Workers who

have been laid off remain in the region and

receive an average unemployment benefit.

• Intermediate run (2-5 years):

• Unemployed labor leaves the region. Proprietors can move into other businesses but do

not leave the region.

• Long run (5-10 years):

• Unemployed labor and unprofitable proprietors are able to leave the region.

In all three CGE formulations, sectoral (that is,

"corporate") capital is assumed to remain fixed

at baseline levels. In the CGE models, the resource shocks are implemented as proportional

reductions in the baseline availability of GS

commodities. Thus, the direct impacts of

resource supply shocks are treated as supplyside phenomena. This treatment has logical

appeal and also is consistent with neoclassical

economic theory.

A key feature of the CGE models is the ability

to substititute among public, private, and

imported sources of logs and livestock forage

via CES aggregation functions as described in

the previous section. The ease of substitution is

determined by exogenously specified elasticities

and endogenous variation in the relative cost of

inputs obtainable from the three alternative

sources of supply. An implication of the constant elasticity specification used here is that,

because of the law of diminishing returns,

relatively small shifts in the availability of

alternative supplies are much more easily

accommodated than are major shifts. In practice, we have assumed that the substitution of

private or imported logs and forage to replace

reduced public supplies is difficult because of

high transportation costs, seasonal grazing

constraints, and the length of time necessary to

alter timber growth and harvest rotations.17

In contrast to the CGE models, fixed-price

models regard all factor supplies as interregionally and intersectorally elastic by holding all

commodity and factor prices fixed. Constant

multipliers result from the assumption of fixed

proportion, column-normalized expenditure

coefficients.18 The magnitude of these multipliers reflects the strength of backward links in the

regional economy.

16

 Enhancement of environmental amenities under

stricter land use policies, however, may be responsible

for some of the positive impacts illustrated in the next

section (economic counter scenarios).

17

 This assumption also would result in larger estimates

of economic impact in response to a reduction in resource

supplies than would a less restrictive assumption.

18

 In the fixed-price model used for this study, factor

incomes and household expenditures also are assumed

endogenous.

14
The fixed-price specification embodies traditional behavioral assumptions and procedures

regarding regional economic systems. Consequently, the resource supply shocks are modeled

as "equivalent" reductions in exogenous demand for the output of the directly impacted

industrial sectors. Although this approach is

logically less appealing and less consistent with

modern notions of microeconomic behavior,

arguably reasonable results can be generated

given careful construction of the direct-shock

scenario. There are also several supply-side

fixed-priced modeling techniques described in

the literature that allow a more consistent

treatment of the direct-shock scenario but

usually at the cost of adopting even more

questionable assumptions regarding the behavior of regional economic systems.

Results

Results obtained under each scenario by using

CGE and IO methods are presented below. For

each shock scenario, CGE model results under

the three length-of-run assumptions (short run,

intermediate run, and long run) are presented

first, followed by results obtained by using the

IO model. Aggregate employment results also

are displayed in table 8. Income and revenue

results are summarized in table 9.19

19

 More detailed sectoral results for other variables in the

model are available on request.

15

Table 8—Results: comparative aggregate employment impacts

Shocks

Range shocks:

Moderate (-25 percent)—

Range and livestock

Other

Total

Employment multipilier

Severe (-100%)—

Range and livestock

Other

Total employment change

Employment multiplier

Logging shocks:

Moderate (-50 percent)—

Logging and wood products

Other

Total

Employment multiplier

Severe (-80 percent)—

Logging and wood products

Other

Total employment change

Employment multplier

Short run

-9

-3

-12

1.33

-516

-78

-594

1.15

-928

-300

-1,228

1.32

-1,786

-580

-2,366

1.32

Model configuration

Medium run Long run

Change in number of jobs

-32

37

5

-.16

-1,313

1,366

53

-.04

-1,141

-359

-1,500

1.31

-2,118

-681

-2,799

1.32

-29

-12

-41

1.41

-1,036

-335

-1,371

1.32

-1,138

-628

-1,766

1.55

-2,115

-1,214

-3,329

1.57

Fixed price

-236

-72

-308

1.31

-947

-290

-1,237

1.31

-1,246

-914

-2,160

1.73

-1,993

-1,460

-3,453

1.73
16

Table 9—Results: comparative aggregate income and revenue impacts

Shocks

Range shocks:

Moderate (-25 percent)—

Household income

Low income households

Medium income househoulds

High income households

Total change in household income

State local government revenues:

Range fees

Other revenues

Total change in government revenue

Severe (-100 percent)—

Household income

Low income households

Medium income households

High income households

Total change in household income

State and local government revenues:

Range fees

Other revenues

Total change in government revenue

Logging shocks:

Moderate (-50 percent)—

Household income

Low income households

Medium income households

High income households

Total change in household income

State and local government revenues:

Timber fees

Other revenues

Total change in government revenue

Severe (-80 percent)—

Household income

Low income households

Medium income households

High income households

Total change in household income

State and local government revenues:

Timber fees

Other revenues

Total change in government revenue

Short run

-0.006

-.130

-.143

-.279

-.093

-.035

-.128

-.217

-4.891

-5.450

-10.558

-.371

-1.100

-1.471

-.932

-8.025

-5.032

-13.989

-9.105

-2.051

-11.156

-1.837

-15.556

-9.796

-27.189

-14.568

-4.059

-18.627

Model configuration

Medium run Long run

+0.019

-.052

-.186

-.220

-.093

-.009

-.102

+.688

-1.083

-5.897

-6.292

-.371

-.478

-.849

-2.618

-21.300

-11.084

-35.002

-9.105

-3.080

-12.185

-4.901

-39.614

-20.663

-65.178

-14.568

-6.839

-21.407

Million dollars

-0.030

-.489

-.470

-.989

-.093

-.094

-.187

-.914

-14.541

-13.993

-29.448

-.371

-3.23

-3.601

-2.814

-24.060

-13.579

-40.452

-9.105

-4.222

-13.327

-5.289

-45.080

-25.603

-75.971

-14.568

-8.031

-22.599

Fixed price

-0.240

-3.390

-3.220

-6.850

-.960

-13.610

-12.940

-27.510

-3.920

-30.390

-17.920

-52.230

-6.260

-48.590

-28.650

-83.500
Moderate Resource Shocks

Shortrun range shock—In the short run, with

only labor adjusting, the 25-percent reduction

in public range supply has only a slight impact

on the regional economy. Regional private

output of hay and pasture decreases by 1.74

percent, but imports rise by 13.9 percent.

Consequently, total supplies of range, hay, and

pasture remain about constant. Total employment decreases by only 12 jobs, including a loss

of 9 livestock-related jobs. Changes in household incomes are slight with low, medium, and

high income households experiencing declines

of less than one-tenth of 1 percent (0.1 percent). Total state and local government revenues

decline by $128,000.

Intermediate-run range shock-—In the intermediate run, proprietors are free to pursue

other business opportunities in the region. The

25-percent reduction in public range induces a

reallocation of economic activity. Imports of

hay and pasture slow somewhat compared with

the shortrun scenario to a rate 8 percent above

baseline levels. Overall, there is a 0.82-percent

decrease in total supply of range, hay, and pasture. A loss of 32 livestock-related jobs is offset

by small gains in some other sectors, and so

total employment remains virtually unchanged.

Total household income declines by $220,000.

Longrun range shock—In the long run, unemployed labor and unprofitable proprietors leave

the region. Production of private hay and pasture recovers and increases 5.7 percent above

baseline, adding 17 new jobs. Hay imports

settle at a rate less than 1 percent above baseline

levels. Total availability or range, hay, and pasture declines by only 0.87 percent. Employment declines for almost all other sectors for a

net reduction of 41 jobs. Total household

income falls by just less than $1 million (0.05

percent). Total state and local government

revenues are down $187,000.

Fixed-price range shock—Under fixed-price

analysis, output and employment changes are

directly proportional. Hence, no sector exhibits

employment increases. Livestock-related industries lose 236 jobs, and another 72 jobs are lost

in the rest of the economy. Total household

income falls by $6.85 million, with low, medium, and high income households each losing

less than 1 percent of baseline income. Estimated fixed-price employment impacts are

roughly seven to eight times greater than

estimates using the regional CGE model.

Shortrun log shock—The shortrun impact of a

50-percent reduction in logging of public

timber is more significant. Total employment

decreases by 1,228 jobs. Output of private logs

remains about constant but is allocated away

from export markets to supply regional mills.

Log imports increase 34.7 percent, but total

supply of logs in the region falls by 13.9 percent. Logging and wood-processing sheds

almost one-fourth of baseline employment (928

jobs) largely because of the increased cost of

purchasing higher priced logs. Incomes of low,

medium, and high income households decline

by 0.2 percent, 0.91 percent, and 1.02 percent,

respectively. Revenues of local governments

decline by at least $11 million, mostly because

of reduced Federal timber sales.20

Intermediate-run log shock—The reallocation

of activity induced by the 50-percent reduction

in public logging fails to insulate the economy

from negative impacts. Compared with the

shortrun scenario, log imports slow considerably. In the intermediate run, logs are imported

at a rate of 17.7 percent above the baseline level,

but total log supply falls 17.9 percent below

baseline levels. Despite an increase in livestock,

agriculture, and food-processing employment of

218 jobs, large decreases in logging and wood

processing (-1,141 jobs) induce a net loss of

1,500 total jobs. Household income declines by

$35 million, and incomes for low, medium, and

high income households decrease by 0.58

percent, 2.42 percent, and 2.25 percent, respectively. State and local government revenues are

down more than $12 million.

Longrun log shock—Regional log supplies

remain about the same as in the intermediate

run (that is, 17.98 percent below baseline).

Employment shows the same trend as in the

intermediate run, although more negative (less

positive). Slight increases in livestock, agriculture, and food-processing employment are

20

 Note that reductions in local government revenues

resulting from reduced Federal timber sales may actually

be mitigated through revenue guarantees under The

Northwest Forest Plan.

17
canceled by large reductions in logging and

wood products (-1,138 jobs), services, and

trade. Total employment decreases by 1,766

jobs. Total household income declines by

$40.45 million, with reductions of 0.62 percent, 2.73 percent, and 2.76 percent in incomes

of low, medium, and high income households,

respectively.

Fixed-price log shock—Logging and wood

products shed 1,246 of the total 2,160 jobs lost

in the economy. A total of $52.23 million

household income is lost. Low, medium, and

high income households lose 0.86 percent, 3.45

percent, and 3.64 percent of baseline income,

respectively. Here the fixed-price employment

impacts range from 75 percent greater in the

short run to 22 percent greater in the long run

than estimates from the regional CGE model.

Severe Resource Shocks

Shortrun range shock—Even in the short run,

the impact of the virtual elimination of public

range in the region is unambiguously negative.

Private hay and pasture decreases by 18.3

percent, but total supply of range, hay, and

pasture in the region decreases by only 2.65

percent because of a sevenfold increase in hay

imports. The livestock sector decreases output

by 2.36 percent, and sheds 516 jobs. Altogether, 594 regional jobs are lost, along with

$10,558 million in household income. This

translates into a reduction in the incomes of

low, medium, and high income households of

0.05 percent, 0.56 percent, and 1.11 percent,

respectively. Local government revenues from

sales of Federal grazing permits decline by

$371,000, and total state and local government

revenues are down $1,471 million.

Intermediate-run range shock—In the intermediate run, hay imports remain high, about

six times baseline levels. Large cuts in livestockrelated employment (-1,313 jobs) are countered

by an increase of 1,366 jobs in other sectors

(mainly trade, services, and other agriculture) so

that net regional employment increases by 53

jobs. Total household income declines by $6.29

million, decreasing by 1.12 percent for medium

income households and 1.2 percent for high

income households, but increasing by 0.15

percent for the low income group. Total state

and local government revenues decline by

$849,000.

Longrun range shock—In the longer term,

private production of hay and pasture returns

to about baseline levels. Hay imports settle at a

level 21 percent above baseline. Total supply of

range, pasture, and hay is 19.8 percent below

the original level. A large cut in livestockrelated employment (-1,036 jobs) is accompanied by decreases in most other sectors, so that

total regional employment decreases by 1,371

jobs. Total household income declines by

$29.45 million, falling by 0.2 percent for low

income households, 1.65 percent for medium

income households, and 2.84 percent for the

high income group. Total state and local government revenues are down by $3.6 million.

Fixed-price range shock—Livestock-related

industries lose 947 jobs, and another 290 jobs

are lost in the rest of the economy. In household income, $27.51 million is lost, with low,

medium, and high income households losing

0.21 percent, 1.55 percent, and 2.63 percent of

baseline household income, respectively. Under

the severe range shock, the fixed-price model

now underestimates economic impact relative

to the regional CGE model.

Shortrun log shock—The response to an 80-

percent reduction in baseline Federal log

supplies is decidedly negative. A 68.5-percent

increase in log imports partially counters the

80-percent decline in public log supply. But an

8.85-percent reduction in private log output

combines to reduce total regional log supply by

28.36 percent from baseline levels. This contributes to a 48.38-percent reduction in wood

products activity, and the loss of 1,786 logging

and wood-processing jobs. Total employment

falls by 2,366 jobs, with the loss of $27.19

million in household income. Incomes decline

by 0.4 percent, 1.77 percent, and 1.99 percent

for low, medium, and high income households,

respectively. State and local government revenues decline by $18,627 million, $14,568

million of which is due to reduced Federal

timber sales.

Intermediate-run log shock—Despite a 30.3-

percent increase in log imports, total log

supplies fall by 35.1 percent, including a 10-

percent reduction in private logs. Logging and

18
wood products employment declines by onehalf (-2,118 jobs). Total regional employment

declines by 2,799 jobs, despite an increase of

411 jobs in livestock, other agriculture, and

food processing. Household income declines by

$65-18 million, therby resulting in decreases for

low, medium, and high income households of

1.08 percent, 4.5 percent, and 4.2 percent,

respectively. State and local government revenues are down more than $21 million.

Longrun log shock—Total log supplies remain

about 35 percent below baseline levels as in the

intermediate scenario. Logging and wood

products employment remains weak (-2,115

jobs). Employment in services, trade, and most

other sectors also weakens, so that total regional

employment is 3,329 jobs below the baseline

level. Household income declines by almost

$76 million, thereby resulting in decreases for

low, medium, and high income households of

1.17 percent, 5.12 percent, and 5.2 percent,

respectively. There is also a loss of $22.6 million

in state and local government revenues.

Fixed-price log shock—Logging and wood

products shed 1,993 of the total3,453 jobs lost

in the economy. In household income, $83.5

million is lost, with low, medium, and high

income households losing 1.38 percent, 5.52

percent, and 5.82 percent of baseline household

income, respectively.

Combined intermediate-run range and log

shocks—It is interesting to note that if both

range and log shocks occur simultaneously, the

intermediate-term impact seems significantly

worse than the sum of the two individual

shocks. Under the combined shock scenario,

2,847 jobs are lost compared with 2,746 jobs if

the separate intermediate-run impacts of the log

and range scenarios are summed. For reference,

the fixed-price model indicates a loss of 4,690

jobs. There is also an additional $2.52 million

loss in household income under the combined

scenario. The difference can be attributed to

increased pressure on relative prices (particularly

the rate or return to proprietors), which exacerbates output and employment impacts under

the combined shock scenario.

Economic Counter Scenarios

In addition to the range and logging supply

shocks, several expansionary "economic counter

scenarios" also were examined. Results of these

scenarios are presented below and in table 10.21

The basic counter scenarios examined include

the following:

"High-technology" assumes the location or

expansion of a regional facility for manufacturing high-technology products, and the resulting

hiring of 330 new workers at the facility.

"Inmigration" assumes 1,000 households settle

in the region, bringing with them an average of

$91,000 in transfer and property income (total

$91 million). The inmigrants also build new

houses at the rate of 200 per year, spending

$100,000 per home in construction costs (total

$20 million).

"Tourism" assumes there is roughly a doubling

in nonresident tourist and recreation activity in

the region (that is, enough to generate 2,200

service-sector jobs, or about 4 percent of the

1992 nonfarm employment base).

"Combined" refers to simultaneous impact of

all three counter scenarios (that is, high-technology, inmigration, and tourism).

All counter scenarios include the "new baseline,"

which assumes the simultaneous, longrun

impact of the severe public logging (-80 percent) and severe public range-reduction (-100-

percent) scenarios. Thus, relative to the original

1992 situation, there are now 4,679 fewer jobs

available in the new baseline, including 3,199

jobs lost from resource-based industries and

1,480 jobs lost from other sectors.22 Total

household income is $105 million less than it

was in 1992.

The counter scenarios should be regarded as

illustrative only, and not viewed as prescriptions

21

 In cable 10, counter scenario impacts are expressed as

changes relative to the original, 1992 baseline levels.

22

 This is slightly less severe than the straight sum of

individual impacts under the severe logging and severe

range scenarios (-4,700). The difference (21 jobs) is due

to the need to slightly modify the standard CGE model

to simultaneously accommodate the combined resource

shocks and economic counter scenarios.

19
or predictions of future circumstances. Although the scenarios were selected assuming,

arguably, reasonable growth prospects for the

northeast Oregon regional economy over the

next 5 to 10 years, they are not based on any

knowledge of pending industrial locations or

extrapolated from any current demographic or

economic trends.

Expansion of high-technology manufacturing in

the region adds 332 manufacturing jobs (236

plus 96 jobs previously lost in the baseline

scenario) and 109 jobs in services industries.

Altogether there are 433 more jobs than in the

new baseline, and an additional $9 million in

household income.

Inmigration results in the addition of 243

construction jobs and 860 service jobs. Total

employment increases by 1,082 jobs but is still

3,597 jobs lower than in 1992. Largely because

of the influx of exogenous, unearned transfer

and property income, household income is

$109 million greater than in the new baseline,

and $4 million higher than it was in 1992.

Tourism expansion adds 2,179 service-sector

jobs (eating, drinking, and lodging; trade and

other services). Total employment increases by

2,229 jobs compared with the baseline in table

10. Household income increases by $26 million

but remains $79 million lower than in 1992.

If all three expansion scenarios occur simultaneously, 3,707 total jobs are added, including

250 construction jobs, 330 manufacturing jobs,

and 3,117 service-sector jobs. Total employment, however, is still 972 jobs lower than it

was before the impact of the severe resource

shocks. Household income is $38 million

greater than it was in 1992, with medium and

nigh income households adding $30 million

and $11 million, respectively; low income

households are still about $3 million worse off

than they were in 1992.

Conclusions

The results presented here emphasize the

complexity of the answer to the question How

dependent is Northeast Oregon on resourcebased industries? Data show that in 1992, 29

percent of regional employment was natural

resource based. Consequently, by most measures, a sustained, severe reduction in the avail20

Table 10—Results: employment and income impacts under possible scenarios, change relative

to original 1992 economy

Employment

Resource-based:b

Construction

Other manufacturingc

Servicesd

Total jobs

Household income:

Low income households

Medium income households

High income households

Total household income

New

baseline3

-3,199

-50

-96

-1,334

-4,679

-6

-59

-40

-105

Hightechnology Inmigration Tourism

Change in number of jobs

-3,208

-49

236

-1,225

-4,246

-5

-54

-37

-96

-3,218

193

-98

-474

-3,597

Million dollars

-5

10

-1

4

-3,154

-45

-96

845

-2,450

-5

-44

-30

-79

Combined

-3,189

200

234

1,783

-972

-3

30

11

38

a

 New baseline—includes the simultaneous longrun impact of the severe logging (-80 percent) and severe range reduction (-100

percent) scenarios.

b

 Resource based—includes livestock-related, logging and wood products, other agriculture, other natural resources, and

agriculture processing.

c

 Other manufacturing—includes all manufacturing industry other than agricultural processing and wood products

d

 Services—includes transportation, communications, and utilities; wholesale and retail trade; eating, drinking, and lodging;

finance, insurance, and real estate; other services; and government industry and government enterprise.
ability of once abundant public range and

timber resources will have dramatic impacts on

the existing regional economic structure. In the

most severe cases examined (1) elimination of

Federal range programs caused the loss of 1,371

jobs (2.3 percent of regional employment) and

$29 million (1.6 percent) of household income;

and (2) an 80-percent reduction in Federal log

supplies resulted in the loss of 3,329 jobs (5.5

percent of regional employment) and $76

million (4.2 percent) of household income.

Analysis of economic counterscenarios suggests

that plausible, simultaneous increases in tourism, high-technology manufacturing, and the

population of independently employed or

retired persons can partially offset employment

and income losses resulting from resource

policy changes. The industry mix of the new

jobs and the distribution of household income

will both be different than they were originally.

Evidence suggests that the regional economy

has already begun a transformation, characterized by stable or declining employment in

resource-based industries and employment

growth in tourism and retirement-based services.

These trends are likely to continue with or

without major changes in natural resource policy.

Proprietors currently provide the major input in

the regional livestock industry. It was noted

under "Sources of Employment" chat nonfarm

proprietors have become a fast-growing component of the northeast Oregon regional economy.

If access to public range becomes restricted, we

would expect to see an acceleration of this trend

as small- and medium-sized livestock operations

transfer soine or all of their resources into other

kinds of businesses.

In this analysis, commodity prices outside the

region for logs, lumber, hay, and livestock were

assumed to remain fixed. This assumption

seems reasonable given that changes in the

regional output of these commodities would

not significantly affect world supplies. World

commodity prices, however, have fluctuated

during the period under consideration. If the

effect of recently higher lumber prices had been

included, the response of regional and imported

log supplies would have been greater, thereby

resulting in a smaller estimated decline in

regional employment and income. On the

other hand, incorporating the effect of falling

prices, such as was recently observed for beef

products, would have resulted in larger estimated reductions in the output and employment of livestock and related industries.

Our treatment of all government activity as

fixed allows comparison of preshock and

postshock scenarios in "revenue-neutral" terms

(that is, assuming no change in government

expenditures in the region). Although this

assumption may tend to underestimate the

amount of regional impact resulting from an

economic shock, it is not unreasonable given

the currently unstable relation between state

and local fiscal responsibilities in Oregon. If

reductions in government revenues had been

translated directly into reduced expenditure

levels, then the impact of the resource shocks

would have appeared more severe.

Moderate shock results under the fixed-price

model are more pessimistic than under CGE

assumptions. In the case of the severe range or

log shock, however, certain impacts appear less

severe under the fixed-price treatment than in

the corresponding longrun CGE model scenario.23

 This is because adjustment to severe

restrictions on Federal land use is considerably

more difficult when modeled as a CGE supplyside constraint than when modeled as a fixedprice reduction in demand. In the flexible-price

model, increase in the regional cost of feed

makes the livestock sector less profitable. For

the severe log shock, increase in regional log

prices hampers adjustment in the wood-processing sector. Clearly the ehminarion of public

resource supply has differed, and severe consequences occur that are difficult to capture by

using conventional, fixed-price models. It is

interesting, however, that both the fixed-price

and flexible-price models tell much the same

story regarding total employment impacts

under severe resource shocks in the long run.

The difference between models is in estimated

impact on the directly affected sectors (that is,

range and livestock, or logging and wood

products).

23

 For example, under the severe range shock scenario,

the longrun CGE model estimates loss of an additional

89 livestock-related jobs and 45 other jobs compared

with the fixed-price model.

21
Literature Cited

Aillery, M.; Betels, P.; Cooper, J. [and others]. 1994. Salmon recovery in the Pacific Northwest: a

summary of agricultural and other effects. AIB-699. Washington, DC: U.S. Department of

Agriculture, Economic Research Service. 10 p.

Alward, G. [and others]. 1989. Micro IMPLAN software manual. Fort Collins, CO: Colorado

State University. [Irregular pagination].

Bedell, T. 1984. Dependency on Federal grazing in eastern Oregon. Rangelands. 6(4): 152-155.

Bedell, X; Sringham, T. 1984. Forage sources for eastern Oregon cattle ranches with Federal

grazing permits. In: Research in rangeland management. Spec. Rep. 715. Corvallis, OR: Oregon

State University, Agricultural Experiment Station: 7-14. In cooperation with: U.S. Department

of Agriculture, Agricultural Research Service.

Berck, P.; Robinson, S.; Goldman, G. 1991. The use of computable general equilibrium models to

assess water policies. In: Dinar, A.; Zilberman, D., eds. The economics and management of water

and drainage in agriculture. Amsterdam, NY: Kluwer Publishing Co: 489-509.

Beuter, J. 1995. Legacy and promise: Oregon's forests and wood products industry report for the

Oregon Business Council and the Oregon Forest Resources Institute. Portland, OR: Oregon

Business Council. 56 p.

Bolon, N.; Hansen-Murray, C; Haynes, R. 1994. Estimated economic impacts on the timber,

range, and recreation programs on NFS and BLM public lands from adopting the proposed

interim PACFISH strategy. Gen. Tech. Rep. PNW-GTR-344. Portland, OR: U.S. Department

of Agriculture, Forest Service, Pacific Northwest Research Station. 80 p.

Despotakis, K.; Fisher, A. 1988. Energy in a regional economy: a computable general equilibrium

model for California. Journal of Environmental Economics and Management. 15: 313-330.

Haynes, R.; Bolon, N.; Hormaechea, D. 1992. The economic impact on the forest sector of critical

habitat delineation for salmon in the Columbia and Snake River basins. Gen. Tech. Rep. PNWGTR-307. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 33 p.

Hewlett, J.; Cross, T.; Hart, R. 1987. Enterprise budget: cow-calf, La Grande area. EM 8337.

Corvallis, OR: Oregon State University Extension Service. 4 p.

Niemi, E.; MacMullan, E.; Whitelaw, E. 1994. Economic consequences of an injunction to protect

salmon habitat on the Wallowa-Whitman and Umatilla National Forests. Eugene, OR: ECO

Northwest; preliminary report. 20 p.

Obermiller, E; West, P. 1983. The structure of a resource dependent economy: Wallowa County,

Oregon. Corvallis, OR: Department of Agricultural and Resource Economics, Oregon State

University. 105 p.

Petkovich, M.; Ching, C. 1978. Modifying a one region Leontief input-output model to show

sector capacity constraints. Western Journal of Agricultural Economics. 3: 173-179.

Rasker, R. 1995. A new home on the range: economic realities in the Columbia River basin. Washington, DC: The Wilderness Society. 59 p.

Robison, M.; Freitag, J. 1994. The economic impact to local communities of eliminating the

Wallowa-Whitman National Forest timber program. Moscow, ID: Robison and Associates. 57 p.

State of Oregon, Department of Forestry. 1993. Oregon timber harvest reports for 1988-1993.

Bourhill, R., comp. Salem, OR: Oregon Department of Forestry.

22
U.S. Department of Commerce, Bureau of Economic Analysis. 1992. Employment and income

data tor Oregon counties: 1969-1992. Washington, DC: U.S. Government Printing Office.

Regional Economic Information System: on CD-ROM.

U.S. 9th Circuit Court. 1994. Pacific Rivers Council, Plaintiff, vs. Jack Ward Thomas, Chief,

United States Forest Service, Defendants. Order dated July 7, 1994. No. 30F-3d 1050: 7425-

7442.

Waters, E.; Holland, D.; Weber, B. 1994. Interregional effects of reduced timber harvests: the

impact of the northern spotted owl listing in rural and urban Oregon. Journal of Agricultural

and Resource Economics. 19(1): 141-160.

23
Waters, Edward C; Holland, David W.; Haynes, Richard W. 1997. The economic impact of public resource supply constraints in northeast Oregon. Gen.

Tech. Rep. PNW-GTR-398. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station. 23 p. (Quigley, Thomas M..

ed.; Inferior Columbia Basin Ecosystem Management: scientific assessment).

Traditional, fixed-price (input-output) economic models provide a useful framework for conceptualizing links in a regional economy. Apparent shortcomings in

these models, however, can severely restrict our ability to deduce valid prescriptions for public policy and economic development. A more efficient approach

using regional computable general equilibrium (CGE) models as well as a brief

survey of relevant literature is presented. Evidence suggests that a regional

economic transformation, characterized by stable or declining employment in

resource-based industries and growth in tourism and retirement-based services, is

already underway.

Keywords: Regional economics, computable general equilibrium models, inputoutput models, economic base theory, public resource policy.

The Forest Service of the U.S. Department of

Agriculture is dedicated to the principle of multiple

use management of the Nation's forest resources

for sustained yields of wood, water, forage, wildlife,

and recreation. Through forestry research,

cooperation with the States and private forest

owners, and management of the National Forests

and National Grasslands, it strives-as directed by

Congress—to provide increasingly greater service

to a growing Nation.

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