Journal of Applied Input-Output Analysis, Vol. 6, 2000

Incorporating Output Projections into a Regional Input-Output Model:
The Case of Forestry in Rural Scotland

By

Kenneth. J. Thomson and Demetrios Psaltopoulos*

Abstract
The paper presents a method of investigating the impact of changes in timber
supply associated with alternative forestry development scenarios, on the rural economy
of Scotland, through a demand-driven input-output model. The projections of a Forestry
Development Model, concerning gross output levels for the forestry planting, harvesting
and wood processing sectors for the year 2050, are set as exogenous to a standard
demand-driven input-output table for Scotland. Changes in the output of these sectors
affect in turn - through the input-output backward linkages - the gross output and final
demand of other sectors in the national economy. The estimation of new gross output
and final demand levels in the national table is followed by the regionalization of thetable to the 'Rural Scotland' level via the GRIT technique. Based on the interindustry
structure of the estimated regional input-output table, the impact of the exogenously-set
forestry output changes on the rural Scottish economy is assessed.

1. Introduction

The recent reform of the CAP and the Uruguay Round Agreement on agriculture are
expected to result in the gradual transition of Western European agriculture towards
world market conditions and therefore significantly influence development in rural
areas. In the remoter areas, forestry is considered to be one of the most likely
alternative uses of agricultural land: 'for the problems which beset the very marginalareas, ... development outlook will be jeopardized unless ... a forestry activity is
gradually built-up' (Commission, 1988).

This paper describes work conducted at and from Aberdeen as part of thetripartite 1991-94 CEC study of Afforestation in Rural Development in Scotland,
Northern Ireland and the Republic of Ireland (Gardiner et a/,,1994)1. Much of the land

Received July 1997, final version received October 1999.

* Department of Agriculture and Forestry, University of Aberdeen, 581 King Street, Aberdeen, AB24
5UA, Scotland, UK, and Department of Economics, University of Patras, Rio, Patras, 26500, Greece.
The authors acknowledge the helpful comments from an anonymous referee. Senior authorship is not
assigned.

1 Commission of the European Communities, CAMAR Project No. 8001-CT90-0008. The other two
research centers were University College Dublin and Queen's University Belfast.

Journal of Applied Input-Output Analysis, Vol. 6, 2000

in these countries shares the characteristics (common also to other parts of the EC) of
depopulation, remoteness from main population centers, and adverse soil and climaticconditions. Additionally, most of new UK forestry planting has concentrated in theseareas.

Preliminary aspects of this work focused upon: (i) the interrelationship between

the forestry sector and other components of the rural economy investigated throughinput-output (I-O) analysis (Psaltopoulos and Thomson, 1993), and (ii) the
implications of alternative national forestry development scenarios for land use, theproduction and processing of timber, agricultural employment displaced and forest
employment created, over the next several decades (Thomson and Psaltopoulos, 1995).
The scenario-specific potential future levels of national timber production would
affect the rural economy not only directly, but also indirectly, via the structure ofinterindustry linkages. Indirect effects can be distinguished into:••'backward linkage' effects, where an increase in forestry output increases demandfor inputs used in the production process, inducing in turn a whole series ofrepercussions for output, income, and employment, as the economy adjusts to the
new level of economic activity. These 'backward linkage' effects are estimated by astandard demand-driven Leontief model, which is based on the assumption of fixed
input expenditures and in the case of a closed model, fixed consumption patterns ofhouseholds; and'forward linkage' effects, where an increase in forestry output increases sales toother sectors (such as timber processing, wood products, paper and board, etc.) andto final demand, triggering a whole series of round effects, as the economy
re-adjusts to equilibrium. These 'forward linkage' effects can be estimated by asupply-driven Leontief model (Ghosh, 1958), which is based on the assumption of
fixed output proportions and in the case of a closed model, fixed earnings pattern ofhouseholds.

So far, forestry-centred national and regional I-O analysis has mostly
concentrated on conventional demand relationships. However, Schallau and Maki
(1983) suggested that in the case of forestry, attention should be given to gross output
rather than final demand constraints ('...exogenous production, rather than exogenous

market constraints...'), and consequently the supply I-O model should be preferred tothe conventional demand-driven one. Similarly, Thomson and Psaltopoulos (1996)
have argued that the standard I-O convention that primary and intermediate inputs canbe made available and used to produce output mainly for sale within twelve months,
can hardly be adopted for forestry with its production cycles of 40 to 100 years.

The first effort to take account of supply constraints in forestry I-O analysis wasthat of Darr and Fight (1974), who tried to assess the consequences of local timber
supply constraints on the economy of Douglas County, Oregon. Arguing that
supply-constrained changes in imports cannot be directly formulated within ademand-driven model, Schallau and Maki (1983) formulated a supply model from Darrand Fight's transaction table and estimated the economy-wide impacts resulting froman equivalent change of timber supply in surrounding regions.

Incorporating Output Projection into a Regional Input-Output Model

3

However, Vincent (1986) suggested that, when comparing different types (local
and those outside the study area) of timber supply changes, researchers should make an
ex ante choice between the two models, because '...production increases in the twomodels feed into quite dissimilar sets of linkages...' and '...predicted impacts of supply
increase are significantly influenced by the choice of the model, as well as by the typeof increase... '. To illustrate his argument, Vincent (1986) formulated a supply modelfor Itasca County, Minnesota, and used both types of 1-0 models to estimate impactsof local timber supply changes; results proved that there were different economic
effects, arising solely from the choice of the model.

In contrast to the above-mentioned supply-side forestry-centered 1-0 studies, thispaper investigates the impact of changes in national (i.e. Scottish) timber supply on therural economy of Scotland, by using not a supply 1-0 model (and thus diverging fromthe relevant traditional Leontief assumption), but a conventional demand-driven one
which is adapted to make the gross output of forestry and wood processing industries
exogenous to the 1-0 system (Miller and Blair, 1985). This process is carried out by
combining forestry output estimates associated with alternative Scottish forestry
development scenarios (i.e. not derived in an arbitrary manner) and the regionalizationof an 1-0 table for Scotland.

The next section briefly presents some background material on the economic roleof forestry in rural Scotland. Section 3 reports on preliminary aspects of this work,
namely the construction of a regional 1-0 table for 'Rural Scotland' and the simulation
analysis based on the development of a forestry development model. The methodology
adopted for the estimation of the impacts of alternative national forestry development
scenarios on the economy of Rural Scotland and the corresponding results arepresented in Sections 4 and 5, respectively. The final section discusses the findings ofthis research effort.

2.

Forestry in Rural Scotland

As a relatively rugged and sparsely populated British region, Scotland accounts fornearly half of the total UK forest area, which has expanded rapidly since World War II,
but still accounts for only 10 percent of the land area of Britain compared to theEuropean average of around 30 percent. During the 1980s, almost 75 percent of total

UK planting took place in Scotland, where forestry has become important in land use

and economic terms. With 1.12 million hectares, it now occupies 14 percent of the total
Scottish land area, and in terms of employment share in rural Scotland, it represents 1
percent of the total (in terms of Full Time Equivalents), while wood industries a further
1.5 percent. Also, more than a third of UK timber production takes place in Scotland.

UK forest policy has been pursued via tax and grant incentives operated throughthe Forestry Commission, an executive authority independent of the Agricultural
Departments. The Commission's primary objective was originally to increase timber
production, in order to build a strategic reserve of timber for use in any possible futurewar. Amongst secondary objectives were 'import-saving' and the provision of rural

4

Journal of Applied Input-Output Analysis, Vol. 6, 2000

employment

inremoteareas.

In

1957,

when thestrategic

argument became

overshadowed by the prospect of nuclear war, the promotion of rural employment
became a primary policy objective for the Forestry Commission. Since the 1970s,

conservation and recreation have also become very important issues. Over the last
decade, in particular, there has been much public debate in Scotland concerning
afforestation. Environmentalists suggest negative impacts on conservation of landscapeand wildlife, while economists (NAO, 1987) have indicated that the cost of creating aforestry job in Northern Scotland is twice that of creating a job in agriculture.
Until recently, the determined protection of farming under UK and EC policy led
to the concentration of forestry in upland areas, where land was cheap, and large (over1000 ha) agricultural holdings made easier the transformation of use of substantial

areas of land. Nowadays, as farm support is reduced, forestry may become a more
attractive land use generally, with increased lowland afforestation. According to the
ScottishDevelopment

agricultural

Department(1987),'...

the greatest

alternative useofland is not physical development but the expansion of forestry'.

Nevertheless, the bulk of any further expansion of forestry in Scotland is bound to be
in upland areas, with large-scale coniferous planting on extensive grazings.

3. Input-Output and Forestry Development Scenario Analysis
3.1 Input-Output Analysis

The earlier stages of this work involved the further advancement of knowledge andunderstanding of the economic role of forestry in Rural Scotland via the developmentof a regional 1-0 model. The first task was the definition of the study area as 'Rural
Scotland' (i.e. Local Authority Districts with population density of less than one person
per hectare). The 1989 1-0 table for Scotland was 'regionalized' to this area (which
comprises most of Northern and Southern Scotland outside the Central Belt), using a'variable-interference' non-survey technique (GRIT, see Jensen et al.9 1979).

The initial mechanically-derived coefficients of the forestry planting, harvesting
and timber processing sectors were adjusted via the utilization of 'superior' dataobtained from national forest authorities and timber-processor surveys, while forestry
contractor

surveysprovidedestimatesof relevanttransboundary

incomeandexpenditure flows (the regionalization process is reported in detail in Gardiner et al,1994). As a result, a 17-sector 1989 1-0 table was constructed for Rural Scotland (forclassification of economic sectors see Appendix A).

Table 1 presents output, income and employment multipliers and coefficients,
calculated from the constructed regional 1-0 table for rural Scotland. Type 1 output
multipliers express the regional significance of the backward linkages of each industry.
Results show that the highest direct and indirect increase of gross output generated byan increase of £1 in sectoral final demand is observed in the Timber Processing sector(1.52), mostly due to the high degree of linkages with the region's Forestry Harvesting

sector. Also, there are high Type 1 output multipliers for Wooden Furniture (1.31),

Incorporating Output Projection into a Regional Input-Output Model

5

Pulp, Paper and Board (1.24) and Wood Products (1.23). Type 1 multipliers are low inAgriculture (1.17), Forestry Planting (1.16) and Forestry Harvesting (1.12), indicating

weak linkages with other sectors. This is due to the high share of imports and income
from employment in total inputs. In general, with the exception of Timber Processing,
the level of Type 1 multipliers is rather low, and it is probably worth mentioning that,
although Type 1 multipliers in Wood Products and Pulp, Paper and Board arecomparatively high, these sectors are characterized by significant import leakages.
Table 1 also shows Type 2 output multipliers, which express the direct, indirect(i.e. from sales of input to other sectors) and induced (from household spending)increase of regional gross output generated by an increase of £1 in final demand for the
relevant sector's output. As a consequence of high induced effects, and in contrast to
the low Type 1 multiplier, the Type 2 multiplier for Forestry Planting (4.38) is thehighest available, while the value of the Forestry Harvesting multiplier is of averagemagnitude (2.04). Similarly, Type 2 multipliers for Timber Processing (2.31) and
Wooden Furniture (2.36) are amongst the highest. On the other hand, capital-intensive
industries such as Pulp, Paper and Board (1.77) and Wood Products (1.81) haverelatively low Type 2 multipliers. The multiplier for Agriculture is the lowest (1.63).
Also, the same Table presents sectoral income coefficients (which indicate thetotal increase in incomes generated by a unit increase in the output of a particularsector) and multipliers for the economy of Rural Scotland. Direct and indirect income

coefficients (DIICs) are high for industries such as Forestry Planting (1.549), Wooden
Furniture (0.509), and Forestry Harvesting (0.446). However, as the low Type 1

income multipliers for these industries prove, this is due to the high direct income
linkages, rather than to indirect income effects. On the other hand, low DIICs in Pulp,
Paper and Board (0.253), and Wood Products (0.275) are mostly due to low direct

income linkages, as indirect income effects (and Type 1 income multipliers) are high inthese sectors. The DIIC for Timber Processing is average (0.381), but the Type 1

income multiplier (2.25) is the highest available, due to a very low DIC in the sector.
Agriculture has a low DIIC but a high Type I income multiplier, due again to very low

direct income effects. Direct, indirect and induced income coefficients (DIIICs) follow

the same pattern as the DIICs. Similarly, Type 2 multipliers follow the same pattern as
the Type 1 multipliers.
Finally, employment coefficients and multipliers are also shown in Table 1. Direct
employment coefficients (DECs) show that an additional £1 million of output from thelabor-intensive Forestry Planting and Forestry Harvesting sectors creates 84 and 47

jobs, respectively in these industries. Increased output has also a relatively high direct
job impact in Wooden Furniture (39 jobs), Agriculture (33 jobs), and Wood Products(28 jobs). Almost all the above industries are labor-intensive. On the other hand,increased output in the capital-intensive Pulp, Paper and Board (12 jobs) and Timber
Processing (19 jobs) sectors seems to create a lower number of direct new jobs. Direct

and indirect employment coefficients (DIECs) are high for industries such as Forestry
Planting (89 jobs), Forestry Harvesting (52 jobs), and Wooden Furniture (48 jobs).
However, as the low Type 1 employment multipliers for these industries prove - withthe exception of Wooden Furniture for which both the DEC and indirect employment
effects are high - this is due to the high direct employment linkages of these industries,

6

Journal of Applied Input-Output Analysis, Vol. 6, 2000

rather than to the indirect employment effects which are rather low. On the other hand,

the low DIEC in Pulp, Paper and Board (18 jobs) is mostly due to low direct
employment effects, as indirect effects are high in this sector. The DIEC for Timber
Processing is average (42 jobs), while both DIEC and Type 1 employment multiplier
are low for Agriculture.

Table 1. Output, Income and Employment Multipliers, Rural Scotland, 1989
OutputTYPE 2

TYPE1

Industries(1) Agriculture

]1.17

1.63

(2) Forestry Planting

11.16

4.38

(3) Forestry Harvesting

11.12

2.04

(4) Timber Processing

11.52

2.31

(5) Wood Products

11.23

1.81

(6) Wooden Furniture

L.31

2.36

(7) Pulp, Paper and Board

1.24

1.77

IncomeIndustries(1) Agriculture

Dmc

TYPE 2

1i.36

0.304

1.83

2.093

1.40
1.57

DIC

DEC

TYPE1

0.166

0.225

(2) Forestry Planting

1.494

1.549

11.04

(3) Forestry Harvesting

0.383

0.446

]1.16

0.603

(4) Timber Processing

0.169

0.381

:>.25

0.514

3.04

(5) Wood Products

0.186

0.275

11.48

0.372

2.01

(6) Wooden Furniture

0.415

0.509

11.23

0.688

1.67

(7) Pulp, Paper and Board

0.173

0.253

1.46

0.342

1.98

Employment
DEC

DIEC

TYPE1

DIIEC

TYPE 2(1) Agriculture

33

38

]1.15

44

1.33

(2) Forestry Planting

84

89

11.06

132

1.57

(3) Forestry Harvesting

47

52

]1.10

64

1.36

(4) Timber Processing

19

42

;>.26

53

2.84

(5) Wood Products

28

37

1.32

44

1.59

(6) Wooden Furniture

39

48

1.24

62

1.63

(7) Pulp, Paper and Board

12

18

1.54

25

2.14

Industries

Source: Authors' Calculations

Note: DIC: Direct Income Coefficients; DIIC: Direct and Indirect Income Coefficients; DIIIC: Direct, Indirect andInduced Income Coefficients, DEC: Direct Employment Coefficients; DIEC: Direct and Indirect Employment
Coefficients; DIIEC: Direct, Indirect and Induced Employment Coefficients, Type I Multipliers: Direct and Indirect

Effects/Direct Effects; Type II Multipliers: Direct, Indirect and Induced Effects / Direct Effects

Direct, indirect and induced employment coefficients (DIIECs) indicate the total
employment effect of increased sectoral output. The total number ofjobs created by anincrease in output in Forestry Planting (132) and Forestry Harvesting (64) is high.

Other sectors with significant impact are Wooden Furniture (62) and Timber

Incorporating Output Projection into a Regional Input-Output Model

7

Processing (53). Agriculture (44) and Wood Products (44) create a moderate amountof total jobs. Type 2 multipliers follow almost the same pattern as the Type 1
multipliers.

In overall, the above analysis has suggested that the labor-intensive forestry
planting and harvesting sectors seem to offer a relatively high potential for improving
economic activity in Rural Scotland, and therefore promoting rural development. Thisis due to the high direct impact of forestry in the economy rather than to its backward

linkages (indirect and induced effects) with other industries. Timber processing andwood products seem to be capital-intensive industries, characterized by generally low
direct economic effects, but unlike forestry planting and harvesting, they have strong

backward linkages, which would be even stronger if the proportion of wood imports intotal inputs was lower. It is worth mentioning here, that in the case of the timber

processing sector, all timber purchases originated from Scotland, while a verysignificant proportion of timber purchased by the wood products and paper and board
sectors originated from either Continental Europe or the American Continent.
From the above, it was concluded that the economic impact of the development of
the forestry sector in Rural Scotland would be significant. Based on the quite

reasonableassumptionof almostperfect

substitutability between

increases

domestically produced and imported timber (McGregor and McNicoll,in1989), asubstantial increase in the output of forestry could lead to a decrease in theimport-dependence of thedownstream

industries.

The

expansion of the woodprocessing industries could create an important number of direct and indirect new jobs.
Backward linkages would then further increase income and employment in the rural
economy.

3.2 Forestry Development Scenario Analysis

The findings and conclusions of 1-0 analysis clarified the current situation in the study
region, but their fuller usefulness only emerges when they are applied to theconsideration of future development possibilities for forestry in Rural Scotland. For

this purpose, a limited number of possible future national (i.e. Scottish) forestry
development scenarios were selected, and their implications into the next century forland use, the production and processing of timber, agriculture, rural employment, andother policy-relevant areas were analyzed through a forestry development model(Thomson and Psaltopoulos, 1995).

The model was built on a spreadsheet, and consisted of two main parts, namely

base-data for the 1980s, followed by successive projected decade blocks. Six
alternative afforestation scenarios ranging from 'no further planting' to 'accelerated
expansion' were defined, including 'lowland' and 'green forestry', and a 'most likely1

scenario (see Appendix B). Based on a number of common background assumptions,

including fiiture labor productivity trends in both forestry and agriculture, calculations
produced future values of national (i.e. Scottish) forest area, wood output, transfer offarmland, displaced agricultural employment, and forest employment created. In order
to include at least part of the longer rotations involving broadleaved trees, and to bringin future cycles of conifers, the year 2080 was chosen as the ultimate time horizon. A

8

Journal of Applied Input-Output Analysis, Vol. 6, 2000

distinction was drawn between current (decade-specific) and accumulated(rotation-specific) forest jobs created on transferred agricultural land and existing
forest areas. In this way, the future implications of different assumptions as to future
forestry policy and practice in Scotland were produced.

The 'Accelerated Expansion' Scenario 2 generates the highest figures of forest
area, timber production, and forestry jobs in Scotland, while the 'Maintained
Expansion' and 'Lowland Forestry' Scenarios 1 and 4 create wood output andemployment levels higher than present. The 'Most Likely' Scenario 6 creates a numberof forestry jobs above present levels until the 2040s. Finally, the 'Green Forestry'
Scenario 5 creates relatively low levels of forest area, timber production and forestry
jobs. All Scenarios (except the 'No Further Expansion' Scenario 3) generate positive

net employment effects associated with coniferous afforestation. On the other hand, net
employment effects associated with broadleaved afforestation are negative.

4. Sector Inputs to I-O Model
As a first step in applying the scenario model results to the 1-0 method, average 1989
unit values regarding timber prices (£ per cubic metre) and establishment cost (£ per

hectare established) were applied to the Scenario-specific (conifer and broadleaved)
national timber output and new planting (including restocking) area projections of theforestry development model for the chosen year 2050 (using the Scenario backgroundassumption of constant real timber prices and real establishment costs).

In this way, new planting (including restocking) area and total wood production
were converted into gross output value estimates for the forestry planting andharvesting sectors, respectively. The input-output 'homogeneity' assumption means thatthe conversion of new planting area and wood production into gross output values forthe forestry planting and harvesting sectors was carried out by applying a uniform

average unit value for total (coniferous and broadleaved) projections. Undoubtedly,
this gives rise to an inconsistency problem, as Scenario-specific projections do not
retain the specific product mix observed in the 1989 1-0 table. However, the very low

Scenario-specific share of broadleaves, both in area and timber output terms, probably
excuses a small error in the estimated values. In the case of agriculture, despite theexistence of Scenario-specific transfers of farmland to forestry, it was assumed that
there is no change in the value of farm output.
With regard to wood usage, three alternative assumptions were then considered:
Assumption A: Additional Timber Exported as Raw Material

Higher domestic wood production associated with each of the six forestry development
scenarios is exported in the form of sawlogs and pulpwood; there is no change in the
consumption level of home-grown timber by the domestic wood processing industry.

Incorporating Output Projection into a Regional Input-Output Model

9

Assumption B: Additional Timber Processed by Wood Processors

Domestic wood production associated with each of the six forestry development
scenarios is processed by the domestic wood processing industry, while the value ofwood imports is adjusted accordingly (i.e. there is no change in the imports
coefficients). The distribution of timber volume sales by the Scottish forestry
harvesting sector to wood processing industries remains similar to that observed in
1989.

Assumption C: Home-Grown Timber Processing

Domestic wood processors process only home-grown timber associated with each of
the six forestry development scenarios (i.e. there are no imports of raw timber forprocessing). The distribution of timber volume sales by the Scottish forestry harvesting
sector to wood processing industries remains similar to that observed in 1989.

These three Assumptions represent extremes of correspondence between thedomestic forestry and wood processing sectors and yield new levels of national outputs
for the forestry planting, harvesting and wood processing industries.
In an 1-0 context, exogenous changes in sectoral gross output - as a result offorces outside the 1-0 model, such as production targets or natural disasters - have an
impact on the gross output and final demand of other sectors in the economy (throughthe 1-0 backward linkages). To estimate these sectoral changes, consider a three-sector
model, with Yu Y2, andX3 determined exogenously (where 7, and Xf represent the final

demand and gross output of sector i, respectively, and X3 denotes - in this example - theexogenously determined national output of the forestry and wood processing sectors

consistent with each of the three assumptions of timber distribution).

The basic balance equation of this system can be written as (Miller and Blair,
1985):(l-au)Xl-anX2-al3X3=Yx- alxXx + (1 - a22)X2- a23X3 =Y2(1)

where a., are input-output coefficients (inputs required from sector / per unit of output
of sector j).
Rearranging the above, gives:(l-au)X,-anX2+0Y3 =Yx+0Y2(l-a22)X2+0r3=0^+
Y2
22 /
2
3 —
12

+a23X323
3+ 072-(l-<or, in matrix form:

(2)

10

Journal of Applied Input-Output Analysis, Vol. 6, 2000

~an

0

1

0

(l-a22)

0

0

1

-1

0

0

~<h \

(3)

Denoting the matrix of coefficients on the left-hand side as M and using theresults from the inverse of a partitioned matrix, the inverse of M is:
r

r

12

o

r2X

r22

0

fix

A

-1

(4)

where y are the elements of the Leontief inverse matrix for the model containing only
sectors 1 and 2,(l-au)

-a

12

(5)

Thus, the estimation of the endogenously determined X\, X2and 73 will be in the
form:

xl

=

rn
r2X

rn

P\

A

0
0
-1

•

'1

0

CL13

0

1

a23

0

0

(6)

Thus, the economic impact (i.e. in the form of change in the level of gross output
and/or final demand) of an exogenously-set change in the national output of theforestry planting, harvesting, and wood processing sectors, is estimated.

The adjustment of the national (Scottish) 1-0 tables was followed by theirregionalization to the 'Rural Scotland' level (applying GRIT and assuming that forevery sector, the regional/national employment ratio remained constant for the different
scenarios / wood-usage Assumptions) and the estimation of 'scenario / wood-usage
Assumption'-specific regional output levels. In this way, the regional output, income
and employment effects of exogenous changes in timber supply were estimated.

5. Results

Following the procedure outlined in the previous section, Table 2 presents the impact

Incorporating Output Projection into a Regional Input-Output Model11

in the year 2050 of the six Forestry Development Scenarios on the economy-wide('total') output, income and employment in Rural Scotland, associated with
Assumptions A, B and C.
Table 2. Impact of Forestry Development Scenarios on Output, Income and Employment,
Rural Scotland, 2050 (£ MILLION, FTE JOBS, at 1989 values)
Assumption A: Additional Timber Exported as Raw Material
Output% Change

Income% Change

Employment% Change

Effects

from 1989

Effects

from 1989

Effects

from 1989

SCENARIO 1

232.95

1.56

164.42

2.73

15670

3.13

SCENARIO 2

353.682.38

266.47

4.43

24544

4.91

SCENARIO 3

-4.84

-0.03

-32.63

-0.54

-1630

-0.33

SCENARIO 4

206.141.38

141.75

2.36

13700

2.74

SCENARIO 5

74.15

0.50

38.98

0.65

4393

0.88

SCENARIO 6

180.681.21

125.15

2.08

12048

2.41

Assumption B: Additional Timber Processed by Wood Processors
Output% Change

Income% Change

Employment% Change

Effects

from 1989

Effects

from 1989

Effects

from 1989

SCENARIO 1

1634.2110.98

773.75

12.87

73684

14.73

SCENARIO 2

2396.6516.10

1154.8519.21

109125

21.81

SCENARIO 3

112.71

0.76

18.48

0.31

3236

0.65

SCENARIO 4

1464.989.84

689.16

11.46

65817

13.15

SCENARIO 5

587.233.95

262.09

4.36

25634

5.12

SCENARIO 6

1278.918.59

602.72

10.02

57517

11.50

Assumption C: Wood Processors Process only Home - Grown Timber
Output% Change

Income% Change

Employment% Change

Effects

from 1989

Effects

from 1989

Effects

from 1989

SCENARIO 1

1639.18

11.01

775.81

12.90

73906

14.77

SCENARIO 2

2403.4116.15

1157.64

19.25

109427

21.87

SCENARIO 3

114.11

0.77

19.06

0.32

3299

0.66

SCENARIO 4

1469.569.87

691.05

11.49

66022

13.20

SCENARIO 5

589.733.96

263.13

4.38

25747

5.15

SCENARIO 6

1282.968.62

604.37

10.05

57696

11.53

Source: Authors' Calculations

Referring to Assumption A, Scenario 2 gives the highest positive changes in total
output, income and employment; compared to 1989 levels, regional output increases by
2.4 percent, income by 4.4 percent, and employment by nearly 5 percent. Scenarios 1,
4 and 6 increase regional employment by 3.1, 2.7 and 2.4 percent respectively. Output,

income, and employment increase marginally under Scenario 5, but marginallydecrease under Scenario 3. With regard to Assumption B, again Scenario 2 generates
the highest economic effects, as regional output increases by 16.1 percent, income by
19.2 percent, and employment by almost 22 percent. The economic impact of
Scenarios 1, 4 and 6 is somewhat lower, but nevertheless quite significant (regional
employment expands by 14.7, 13.1, and 11.5 percent respectively). Regional output

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Journal of Applied Input-Output Analysis, Vol. 6, 2000

expands by nearly 4 percent if Scenario 5 is applied, while there is a marginal (under 1

percent) increase under Scenario 3. Finally, results associated with Assumption C are

marginally higher (leakages are lower, but processors process a lower volume oftimber) but generally similar in pattern compared to those of Assumption B. Due to thelabor intensity which characterizes the forestry and wood processing industries, relativechanges of regional income and employment are higher than those of output.
In general, Assumptions B and C generate a much higher level of economic
activity, compared to Assumption A.

6. Discussion

The paper has presented a method of investigating the impact of exogenous forestry
output changes associated with alternative Forestry Development Scenarios on therural economy of Scotland, via the regionalization of a standard demand-driven
national 1-0 model.

The main advantage of this method is that, while based on conventional demand
relationships, it also takes account of local (within Rural Scotland) and adjacent (restof Scotland) timber supply constraints, enabling therefore the formulation of
supply-constrained changes in timber imports. The fact that the method cannot
consider constraints in timber imports originating from areas other than those specificto the forestry development model (i.e. Scotland) is undoubtedly a shortcoming.
However, this problem is irrelevant in the case of downstream industries which obtain
raw material only from areas covered by the model (as in the case of the timber
processing sector in Rural Scotland).

In general, the findings of this study indicate that alternative forestry development
strategies in Scotland can bring about quite different long-run consequences, especiallyas regards output and employment generation in rural areas. The economic impact ofmost afforestation scenarios by the year 2050 seems to be significant, especially if all
additional timber is processed by regional wood processors. The increase in the level of
employment associated with 'production-oriented' scenarios ranges from 11 percent to22 percent.

On the other hand, there is a low, but still positive, economic impact associatedwith the 'no further expansion' and the 'green forestry' scenarios. Not unexpectedly, thelevel of additional economic activity becomes much lower if all additional timber isexported (around 20 percent of the level generated if all additional timber is processedby domestic wood processors).

Incorporating Output Projection into a Regional Input-Output Model

13

Appendix A. Industrial Classification for Input-Output Table for Rural Scotland, 1989
Industry Group

1. Agriculture

SIC Code
0100

2. Forestry Planting

0200 part

3. Forestry Harvesting

0200 part

4. Timber Processing

4610

5. Wood Products

4620, 4630, 4640, 4650,4663, 4664

6. Wooden Furniture4671,4672

7. Pulp, Paper & Board

4710

8. Paper & Board Products

4721,4722, 4723, 4724, 4725, 4728

9. Printing & Publishing

4751,4752, 4753, 4754

10. Construction

5000, 5010, 5020, 5030, 5040

11. Distribution

6110,6120, 6130, 6149, 6150, 6160, 6170, 6180,
6190,6210, 6220, 6300, 6410, 6420, 6430, 6450,

6460, 6470, 6480, 6530, 6540, 6560, 6720,6730

12. Road Transport

7210, 7220, 7230,7260

13. Banking & Insurance

8140,8150, 8200

14. Other Business Services

8310,8320, 8340, 8350, 8360, 8370, 8380, 8394,
8395, 8396

15. Energy

1113, 1114, 1115, 1200, 1300, 1401, 1402, 1520,
1610, 1620, 1630, 1700

16. Other Manufacturing

2100,2330,2396, 2210,2220, 2234, 2235, 2245,
2246,2247,2310, 2410,2420, 2436, 2437, 2440,

2450, 2460, 2471, 2478, 2479, 2481, 2489, 2511,
2512,2513,2514, 2515,2516, 2551,2552, 2562,
2563, 2564, 2565, 2567, 2568, 2569, 2570, 2581,
2582,2591,2599, 2600,3111, 3112,3120, 3137,

3138,3142,3161, 3162,3163, 3164,3165, 3166,

3167,3169,3204, 3205,3211, 3212,3221, 3222,
3230, 3275, 3276, 3244, 3245, 3246,3251, 3254,

3255,3261,3262, 3281,3283, 3284, 3285, 3286,
3287, 3288, 3289, 3290, 3301, 3302, 3410, 3420,
3432, 3433, 3434, 3435, 3441, 3442, 3443, 3444,
3453,3456, 3459, 3460, 3470, 3480,3510, 3521,

3522,3523, 3530, 3610,3620, 3633, 3634, 3640,
3650,3710,3720, 3731,3732, 3733, 3740, 4115,

4116,4121,4122, 4123,4126, 4130,4147, 4150,
4160,4180,4196, 4197,4200, 4213,4214, 4221,
4222,4239, 4240, 4261, 4270, 4283,4290, 4310,
4321,4322,4336, 4340, 4363, 4364, 4370, 4384,
4385, 4350, 4395, 4396, 4398, 4399,4410, 4420,
4510,4531,4532, 4533, 4534, 4535,4536, 4537,
4538, 4539, 4560, 4555, 4556, 4557,4811, 4812,

4820,4831,4832, 4833, 4834, 4835,4836, 4910,
4941, 4942, 4920, 4930, 4954, 4959

17. Other Services

6148,6510, 6520,6710, 6611,6612,6620,6630,
6640, 6650, 6670,7100, 7400,7500,7610,7630,
7640, 7700. 7901,7902, 8410, 8420, 8430, 8460,
8480, 8490, 8500,9111, 9112,9120,9130,9140,

9150,9190, 9211,9212, 9230,9310,9320,9330,
9360, 9400, 9510,9520, 9530, 9540, 9550, 9560,
9611,9631, 9660, 9690, 9711,9741,9760,9791,
9811,9812, 9820, 9890, 9900

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Journal of Applied Input-Output Analysis, Vol. 6, 2000

Appendix B. Scottish Forestry Development Scenarios

The following six alternative forestry development scenarios are considered, separately for
conifer and broadleaved plantations in Scotland:
1. Maintained Expansion at the average rate and characteristics of new planting during the

1980s, i.e. mainly commercial planting of Sitka Spruce in upland and some poorer lowland
areas, and clear-felling for bulk processing.

2. Accelerated Expansion with the rate of new plantings increased by 50 percent, but noother major changes in assumptions.

3. No Further Expansion, i.e. only replanting of felled areas with similar types of tree as in
Scenario 1.

4. Lowland Afforestation with new planting confined to marginal arable land currently incrops, temporary grass or set-aside. These new plantings are assumed to be primarily

commercial in nature (but with 20-30 percent broadleaves, compared to about 3 percent in

Scenarios 1 to 3), and to have a (net) yield 20 percent higher than existing plantations.
5. 'Green' Forestry, with afforestation at 50 percent of the 1980s rate, but with all forest
management, i.e. planting, maintenance and harvesting, carried out to maximise
non-market benefits such as visitor use and environmental enhancement. Thus, newplanting and replanting are of native species, and there is less clear-felling and greater
maturation allowed. Consequently, felling and yield rates are taken as 50 percent below
base levels.

6. "Most Likely" Scenario comprises specific informed judgments as to the most probabledevelopments during the foreseeable future, made partly on the basis of the information
gathered in the field surveys, and partly on the basis of discussions with agricultural andforestry experts and officials. New planting continues at 1988-92 rates (i.e. some 20
percent less than the 1980s average), while smaller blocks lead (eventually) to lower yields.

Incorporating Output Projection into a Regional Input-Output Model

15

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