Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Structural Changes in the Indonesian Economy:
A Network Complication Approach

By

Nuzul Achjar*, Michael Sonis" and Geoffrey J.D. Hewings*

Abstract
Using a time series of social accounting matrices (SAMs) for Indonesia, an exploratory

analysis is conducted to explore some of the more important structural changes in that na
tion's economy and especially to explore the impacts of the 1997 financial crisis on the na
tion's economic structure. By adopting a block structural path analysis, attention was directed to the network complication engendered by gradually exploring links between one

subsystem in the SAMs and the remaining systems. Important changes in the structure of
production were revealed but the dominant changes appeared to lie in the distribution of income between factors, especially the growing importance of labor income and the concomi
tant change in consumption as incomes have risen. The effects of the 1997 financial crisis
was discernible but the long-term implications remain to be explored.

1

Introduction

Earlier work of Sonis et al. (1997a,b) explored structural changes in the Indonesian

economy by analyzing the change of output in each path and the change in the hierar
chy of direct coefficients of production activities. Using a series of Indonesian social
accounting matrices (SAM) for 1975-1985 consisting of five aggregated sectors, theyfound that block structural path analysis (BSPA) proved to be useful in contributing to
the basic understanding of the processes of change within a social accounting frame
work. BSPA methodology was proposed as a complement, not as a replacement to themore familiar forms of structural path analysis (SPA) as suggested by Khan and Thor-

becke (1988), Defourny and Thorbecke (1984) that focused on the micro level analysis
of individual paths.

The present paper extends the analysis to explore the impact of the mid-1997

monetary crisis that resulted in the contraction of the economy from 4.7% growth in
GDP in 1997 to a decline of 13.2% in 1998. Over the same time period, the construc-Received October 2004, final version received October 2006.
*

LPEM, Universitas Indonesia, Jakarta**

Bar Ilan University, Israel and Regional Economics Applications Laboratory, University of Illinois,
Urbana, Illinois, USA***

Regional Economics Applications Laboratory, University of Illinois, Urbana, Illinois, USA

92

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

tion sector declined 40.5%, financial services decreased 26.6%, trade, hotel & restau
rant by 18.0%, and transportation by 15.1%. The manufacturing sector's decline wasmore modest, 11.9%, while agriculture sector maintained positive growth, even gaining
13.0% in the peak of the crisis. In contrast, over the period 1975-95, average eco
nomic growth reached 6 to 7% annually, and income per capita rose by 4-5%, theeconomy experienced a declining share of the agricultural sector, and an increasing
contribution of manufacturing industries to GDP (see figure 1).

Figure 1 The share of primary, manufacturing and services to GDP, 1975-99 (%)

60,0

50,0

40,0

30,0

20,0

10,0

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Primary

Manufacturing

Services

Hence, the goal of this paper is to explore the observed changes in the Indonesian
economy as a precursor to the development of more formal models that could simulatethese changes. In the next section of the paper, some of the major issues are raised to
guide the exploration of changes. Section 3 describes the methodology to be employed;
section 4 presents the empirical applications with their interpretation documented in
section 5.

2 Issues to be Addressed
Using SPA in the SAM framework of Indonesia 1999, Azis (2000, 2001) studied theimpact of the financial crisis on income distribution and extended the methodology into
a computable general equilibrium analysis (CGE). The present paper seeks to uncover

the pattern of the structural changes in the Indonesian economy during the period 1975
-1999, not only on income distribution but also on the changes in the composition of

Structural Changes in the Indonesian Economy: A Network Complication Approach93

production activities. Since no formal behavioral model will be developed, it will not
be possible to provide the type of causal documentation that might be derived from acomputable general equilibrium model; in essence, the search in this paper will attempt
to document what happened and to try to trace potential causal links.

3 Analytical Framework
The hypotheses to be explored will require an evaluation of changes in the network

structure of the Indonesian economy. The analysis will rest on the notion of network
complication - essentially, an uncovering of the way in which interdependence between
components of the economy can be "built up" as more loops of direct and indirect interaction are considered. To accomplish this task, the notion of internal, external multipliers and the notion of augmentation of a multiplier will be presented. The process of
network complication will be evaluated by exploring the influence of changes in a subsystem on other subsystems and the whole system, using block structural path analysis(BSPA) developed by Sonis and Hewings (1997b, 1998). Prior to the elaboration of
BSPA as the main tool of analysis, structural path analysis (SPA) will be summarized
to discuss how this method can be used to explain the structural changes in an econ
omy and how it differs from BSPA.

3.1 Structural Path Analysis (SPA)
The comprehensiveness of the SAM method as a data system that captures the circularinterdependency of economic subsystems has made it an attractive tool to capture theglobal (direct and indirect) effects of injections from exogenous variables on endoge

nous variables can be measured. For example, the analyst might be interested in the
Figure 2 Injection from activities and the paths in SPA and BSPA framework
Block structural path analysis - Sonis and Hewings (1998)

Structural path analysis - Defourny and Thorbecke (1984)

Labor types

Pole oforiginHousehold

Block pole

Block

Block

Block

groupsof origin

Acivities

Factors

Institutions

Agricultural

paid labor

Export ofFood crops

food crops

outputClerical\Urban HH

paid labor

Agricultural

Food crops

Export offood crops-►

output4

paid labor\

Clerical

/

\

\_^

Rural HH
income«={>paid laborNote:<J^ indicates self direct influence■=#* direction of the influence

94

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006
Figure 3 Network of elementary path and network complication
Network ofelementary path and adjacent circuit

Network complication from origin i to destination]

Deforny and Thorbecke (1984)

Sonis andHewings (1998)

OriginDestination

OriginDestination

Bj"p U J,j\ )Bjk~jk 0">JJl> -Jk-0

Direct transfer ofInfluence

Augp(i,y.k)=A

fr,f

pp. u.yi) App—

Ajk_Ijk Bjkjk('.jfj

Global influence

Global economic influences=lmagnitude of the effects that will be driven by food crops export (initial injection) on

the income of urban and rural households respectively (destination, endogenous ac
count), in which the initial injection travels through corresponding production activities
and is then transmitted to various labor types, and then to the destination of interest(figure 2).

While the analysis of the structural changes in the economy using SPA focuses

the attention on individual sector with a highly disaggregated matrix, the BSPA offers amore macro perspective to trace the magnitude of the influence departing from an in

itial injection of an economic subsystem in a way such that the transfer of influence toother corresponding economic subsystems provides feedback loop effects on other cor
responding subsystems - an augmentation process in the whole economic system. Fig
ure 3 provides a conceptual overview of the main distinctions between the two comple
mentary approaches to network analysis within a SAM.

3.2 Block Structural Path Analysis (BSPA)
To address the research questions, the elaboration of the BSPA will be organized into
three sections that describe and trace the evolution of feedback loop effects from a sim

ple two-region case to a more complex of synergetic effects. The first part focuses theattention on the notion of internal multiplier, external multiplier and augmented multiplier, combined with Schur (1917) and Banachiewics (1937) notion of the inversion ofa 2 x 2 matrix. The decomposition of three economic subsystems will be discussed in
the second part; in the third part, the partial Leontief inverse in a SAM framework will

be discussed to separate the influence of an economic subsystem from other subsys
tems.

Structural Changes in the Indonesian Economy: A Network Complication Approach

95a) Two-Region Extended Leontief Multiplier1
The linkages between Miyazawa (1976), Yamada and Ihara (1969), Ihara (1999), Schur(1917) Banachiewics (1937), and Sonis et al. (1998a) on the idea of self influence,transfer of influence, and augmentation of influence can be explained in a 2 x 2 matrix
that represents intra and interregional flows in a two-region (or two-fold division of asingle economy) system in the following way:
[A,, A,2](1)

LA21 A22J

where, An and A22 are the square matrices of direct inputs within the first and second
regions A.2 and A2, are the rectangular matrices showing the direct inputs purchased by
the second region and vice versa. It is also possible to consider the case where the sec
ond region represents the rest of the economy. The basic idea of interaction between

the two regions can be developed into the interaction between the block sectors within

a single region. The corresponding Leontief inverse matrix, B= (I ~ A)~\ has the fol
lowing block form (the superscripts II on the B 's indicate the number of regions (2) in
B or the cell that has been augmented from the interaction process). The matrix for
two-region case is simplified as:

riff, ift-io//

L iJi\(2)nil

D22 -IThe multiplier matrix (2) can be interpreted further with the help of the Schur-Ba-

nachiewicz formula (Schur, 1917; Banachiewicz, 1937; Miyazawa, 1966; Sonis and
Hewings, 1993):["

Bw= L Bl!A2lB>

BuAiiBi 1 _ [~

Blk

J- L

fin

B1A12B22

where, matrices Bi= (I - An)'1 and B2= (/ - A22)"' represent the Miyazawa internal matrix multipliers for the first and second regions (revealing the interindustry propagation

effects within the region) while the matrices A2iBi,2?iAi2,Ai2Z?2 and BAu show the induced effects on output or input between the two regions (Miyazawa, 1966). The Schur-Banachiewicz procedure provides the notion of an augmented process received by anode in the process of interaction. For the two-region case as represented by previous 2

x 2 matrix, input An is augmented by the transfer of influence through AnBAiu andsimilarly A22 is augmented through A2i2?iAi2 such that:

Si = An + A12B2A21,as

Si = A22 + A2iBiAi2

In equation (4), AuAn are the direct inputs for region 1 and 2 respectively that circu

late within each region, and AiiBAiiAnBAn represents the economic self-influencetransactions as the result of feedback effect of one region to other region and back to
the first region. The Schur (1917) complements, SUS2 may be considered as analogous
to Yamada and Ihara's (1969) notion of augmented inputs. The inverse of Schur's aug
mented input (2.7) is termed as an extended Leontief multiplier in the form:
The methodology in this section is heavily drawn from Sonis (1999) with some change in notation.

96

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Figure 4 The evolution of two-region case of self-influence and transfer of influence
Methods

Types of multiplier

1

Model

Internal matrix multiplier

B,=(I-A „ y'(direct effect)

B2=(I-A 22)'

External matrix multiplier

A2IB,,B ,AI2,(induced effect)

A,2 B2,B 2AV

Miyazawa (1966, 1976)

Yamada and Ihara (1969),

Augmented input

S,=A ,,+A ,2B2A2,

Schurs (1917), Banachiewicz (1937)(augmented Schur complement)

O 2 =A 22 +A 21 B i A 12

Miller and Blair (1985)

X,=A 2i (I-A i, )' A l2 X2(Interregional feedback effects)

X 2 =A l2 (I-A 22 )A 2I X,\

Extended Leontief inverse

B" 2=(I-A "2 -a[ B, A I )'Sonis and Hewing (1998)

B

12 —B

„ A l2 B2 —B iAt2B

72

b" 21=b" 22a2Ib,=b2a2Ib" „Direct transfer ofinfluencefrom
region 1 to region 2

Direct transfer of influence fromregion 2 to region 1

u [m

Br

Bn mmW-

B2:

Augmentation of inputs &B2

into region I

Augmentation of inputs Si
into region 2

»M-

A2l

Structural Changes in the Indonesian Economy: A Network Complication Approach

Bu - (I - An - .-.__.,

Bk = (I - A22 - A21BA12)'1

97()

The evolution of the Leontief extended multiplier provides an important basis for interpreting the notions of economic direct influence, induced self-influence and augmented
influence that were proposed by Miyazawa (1966), Yamada and Ihara (1969), Sonis
and Hewings (1998a). The linkage among those various types of influences is dis
played in figure 4.

At the meso-level of regions, the augmentation of inputs could be further interpreted as the economic self-influence and the transfer of economic influence from region to region (Sonis and Hewings, 1998); the extended Leontief inverse corresponds
to a structural path of economic self-influence. In order to separate the influence of in

ternal and external multipliers that represent direct and induced self-influences, the Le
ontief inverse can be decomposed by using the Miyazawa decomposition:
D7/
£>11

_ T> nllR __ nlILn— £>i£>n — D\\D\

B22 = B2B22 = B22B2
where,

Bft = (I - BAi2BA2iTl ; Bff = (I - A^AnBiT1
B22 = (I — BA B A ?)"' • BIIR =(I — A B A B V1

are the left and right Miyazawa external self-influence multipliers for the first and sec

ond region. A structural path of self-influence corresponding to the analytical structureof the multipliers is shown in (8). The transfer of economic influence from one region
to the other is presented by the block-components of the Leontief block inverse. The
Miyazawa fundamental equations are:nilryll Annanil

D\2 — D\\/\\2D2 — D\A\2L>22

As shown in figure 4, the self-influence and transfer of influence augmentation process
at the meso-level of regions represent the building blocks of the economic interactions
between the economic subsystems. Each regional subsystem generates a decompositionof the Leontief block inverse into the product of partial Leontief inverses corresponding to the chosen regional subsystem. For example, the following formulae represent
explicitly the separation of the direct and indirect self-influence and transfer of influ
ence in the form of a triple decompositions that separates multiplicatively the effects of

intra-regional economic relationships of isolated regional economies,

intra/interregional feedback effects on the level of direct inputs,

L

A21

[nil

0

»

[flfiO|[/-A,i

L 0 #'2 J L

A21

Aa

1 [fi, 0]_/ - A22 J L 0 b2\~r\

11 B22//

L 0

"

'

B2 J

, the

n 1 and/ - A22 J

98

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

= I" JBi 0 1[/-An

Lo b2\

LAii

An

1 [#', 0(9)/-A22J Lo m

Equation (9) provides the block matrix analog of the decompositions (8) of the transfer
of economic influence. The application of the Miyazawa decompositions (6) of the extended Leontief inverses into the product of external/internal multipliers provides fur
ther possibilities for construction of another block matrix analog of (9).

\BLu 0 i r

LO

BL22 J

/

BAn i

/

a12b2i rsf, o i

IBAn

jb. oi r

Lo B2\ La2.5i

r 5i

oi

I

J Lo B2\/

J L 0 ^22 J(10)b) Decomposition of Three Economic Subsystems
Sonis and Hewings (1998a) extended the idea of self-influence and induced selfinfluence for a SAM in similar fashion to the decomposition of three regions into subsystems. A general form of direct coefficient A, exogenous demand d and total output
x for SAM framework is given as:

0
A =

0

0

A13"

An

0

" 0 "
;d =

A32 A33d,' Xi '
; x =

<L

(11)

Xi
Xi

The subscripts refer, respectively, to the usual tripartite division of a social accounting

matrix into submatrices of (1) factors, (2) institutions and (3) activities. The following
decomposition of A may be presented:( 0 0 An
0

0

0

(12)

^ 0 0 A33
where, matrices Ai,A2,A3 represent the direct inputs into factors, institutions and activi
ties separately from which a decomposed inverse can be presented:

B=(I -A)~x =(13)

Decomposition (13) differs from multiplicative decomposition of Pyatt and Round(1979) that is primarily purposed to recognize own direct-effect, indirect self-influenceand synergic cross effect by dividing matrix A into the diagonal and off-diagonal ele
ments and exploiting the properties of permutation matrices.
(14)

where,

M, = (/ - A,)"1
M2= {I -own direct effect-Ai)A2]Tindirect self influenceStructural Changes in the Indonesian Economy: A Network Complication Approach

M3 = /+(/- Ai) A2 +[(/ - Ai) A2f

99

synergetic cross effects

Defourny and Thorbecke (1984) proposed an additive decomposition for tracing the influence of economic subsystem:(/ - A,)"1 = / (M, - /) + (Mi - I) M, + (M3 - /)(15)

Sonis and Hewings (1998a) converted the additive decomposition (10) into a multipli
cative form of a block matrix of direct inputs for three-region or economic subsystems:
An A12 Ai3
A=

(16)

A2\ An A23

A3i A32 A33
The corresponding Leontief inverse is shown as:
nlll
£>H

B=(I -

nlll

Dl\

nlll

Di\

Dill

X>22

nlll

D32

(17)

nlll

£>23

nlll

X533

However matrix (17) does not separate the influence of economic subsystems fromother sub-systems and economic system as the whole. The three-region case or three-block of economic subsystem should again refer to the basic concept of the SchuriBanachiewicz inverse for a pair of sub-systems.
Consider the row and column along A33 in equation (16) represent the domain of eco
nomic subsystem (3). The formation of the partial block matrix, for example, the pairof subsystems (1) and (2) is the domain of subsystem (3). Consider the Schur-Banachiewicz related form defined as (S). The direct inputs for the pair is written as:
A(S)= [An A12]

(18)

LA21 A22J

The corresponding partial Leontief inverse is written as:

B\\(S)r" l B212(S)A2lBl

B'12(S)

BUS)

(19)

Based on the partial Leontief inverse for pair (1, 2), the element of the Schur-Banachiewincz inverse matrix in a three-region subsystem can be written as the follow
ing (for proofs, see Sonis and Hewings, 1998):

B'H
B=

flg

m

(20)

with the Yamada and Ihara (1969) augmented inputs:

Af = Au + AisBA,j

i f j,i f s;i, j,s = 1,2,3

and the extended regional Leontief inverses:

(21)

100

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

fli" = [/ - Au - Atfil (i) AS1 - AisBlL ii) AS1]-1

17* j,i 7^, J 7* s\U 7> = 1,2,3 (22)The corresponding augmented Schur complement presents the trans-subsystem eco
nomic self-influence at the meso-level of subsystems:

5, = Aa + AqB% (i) K + AisBl ii) A1!!

(23)

The augmentation of inputs (21) leads to the detailed structure of augmentation in the
Schur complement (23):Si = Att + A0B$ (i) A, + AuBfL ii) Asi ++ Ai0i (i) AjsBAsi + AisBl (1) AsjBjAjii +h l fs> J fs;ij,s = 1,2,3(24)

Thus, in the three-account system, the economic self-influence may be seen to com
prise the superposition of (i) circulation (direct self-influence); (ii) self-influence gener

ated through bilateral subsystem interdependencies and (iii) self-influence promoted bytri-lateral subsystem interdependencies. The expressions (23) and (24) reflect the exis
tence of a nested hierarchy of different levels of augmentation represented in the recur
sive form in (20); in a sense, the process resembles the Matrioshka idea introduced by

Sonis and Hewings (1991). Furthermore, the generalization of the Miyazawa funda
mental equations (8) for the case of three subsystems also has a recursive form, withthe transfer of influence from each susbsystem defined as:tiS = BfAZB% (0 = B$ (j)ifj,ij= 1,2,3(25)

Moreover, the augmented Schur complement (14) can also be written as:

Si = Au + AuBS (i) A, + AM (i) A*(26)

The expressions (25) and (26) offer the option of presenting the Leontief inverse forthe three-account system in an alternative form:B=
Jll£>33(ZJ /132 £>22

Thus, the following generalization of the Miyazawa external and internal multipliers
holds:

fl?' = BtBT = flTAAj"(28)

where,

Bmr and B'"L are the right and left external self-influence multipliers for subsystem i:

B^R = U - AX (0 A^Bt - AuBfL (i) A2'&r!

(29)

BZL = [I - BAM ii) AH! - BASl (i) Ajf]"1
The generalizations (28) and (29) can be transferred from the meso-level of subsystems
to the higher macro-level of the inner and outer left and right block matrix multipliers.
For example, for the left multipliers:

Structural Changes in the Indonesian Economy: A Network Complication Approach

Bi'l

B=

0

0

0 flg 0
0

101

0

#,"

Bif 0

0

0

B"iL

0

0

0

B3f

?3 B'k{2)
(30)

"B, 0

0 B2 0

. 0

"B, 0

o ■

A»2)

I-An

Agflg<2)00 "0 B2 000 B}c) Partial Leontief Inverse in the SAM framework
The purpose of partial block matrices of direct inputs for the three pairs of blocks (institution, activities), (activities, factors), (factors, institutions) is to separate their influ
ence on other pairs of blocks. Consider the block pair, institutions, activities, as follows:1) The pair institutions and production activities:

The corresponding partial Leontief inverse is formulated as:(32)
where, B2 = (I - An)'1 and ft = (/ - An)'1;
2) The pair, factors, activities:(33)
The corresponding partial Leontief inverse of the pair factors and activities is:3) The pair, factors, institutions:<35>

L A21 A22 J
with the corresponding partial Leontief inverse:

(36)

A21&2

Define the augmented inputs proposed by Yamada and Ihara (1969):

AS = A, + AisBAsj

i t h i ? s, J. j, * = 1 A3

(37)

102

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

and the extended regional Leontief inverses:

m = [/ - a. - AtfiKDAH! - AfrBLaxr1/

s,t, j, s= 1,2,3

Augmented input of the blocks in the SAM are:Ag = AnBAn, AS = A,,;AS? = A2>
; AS = AuAn,
A3'( = An&A*; A|2 = AM

(39)

The extended self-influence Leontief inverses at the meso level of the major divisions
are:

(40)
B22 = [I - A22 -B'i = [I - A33 The corresponding augmented complements:
5i = A13B3A32B2A21(41)

S3 = An + Ai\A 13B3A32

S3 = A33 + A32B2A21A13
have the economic network structure associated with the blocks A22, A33 and with thecomponents of the quasi-permutation matrix of direct inputs:

P=

0

0

A,3

Aj,

0

0

0

A32

0

(42)

This matrix represents the macro level feedback loop of the transfer of economic influ
ence between factors, institutions and activities. Drawing on (39), the Leontief inverse
for this SAM has a form:

A13B3A32B22

A13B33

B2A21B11

B22

B2A21A13B33

B3A32B2A21B11

BAnBn

B33

B=

A13B3A32

53A32

A13

(43)

K

0

0

0

flg

0

0

0

B\3

Here, the diagonal matrix:

B'il

0

0

0

#22

0

0

0

flg

(44)

represents the macro level of economic self-influence within the factors, institutions

Structural Changes in the Indonesian Economy: A Network Complication Approach103

and activities, and the block multiplier:I

A13B3A32

A13

BA21

I

BAiAn

B3A32BA21

BA32

I

M=

(45)

represents the macro level transfer of influence. It is important to stress that the quasipermutation matrix P represents the building block of this macro level transfer of influence:

M=

I

A13BA32

Ab

/

0

o"

B2A21

/

B2A21A13

0

/

0

LO 0

/

B3A32BA21

B3A3

+

"/

0

o"

0

0 An

0

&

0

A21

0

.0

0

0 A32

0
0.
(46)

0

0

An

7

0

0

0

0

A13

A21

0

0

OB2

0

Au

0

0

0

A32

0

0

ft

0

A32

0

7

0

0

O82

0

0

B,

0

= I+DJ>+PDJ>

where,

D2=

0

(47)

is the diagonal block matrix of the direct self-influence of factors, institutions and ac

tivities. Thus, the SAM inverse has the following form, including the macro level direct
and extended self-influence associated with the block diagonal matrices, D2 and D3 themacro transfer of influence, P:

B= MDi = [I + D2P+ PD2P] D3(48)

At the meso level for the major divisions of the economy, the compact form of endo
genous block matrix B and final demand d can be shown as:

Bd=

Dm

nlll

A nBitI32BS

An B%

0

D A jylll
DiAl\ti\\

I?"'
tfzi

HA A J?'"
DV\l\l\nD-Sl

d,

B3A32B2A21BH

B3A32B22

B33

.dA_

An

A13B3A32

B2U +

/

B3A32

(49)

_

B2A21AI3

B3U/

The expression (49) reveals the major paths of influence in the transmission of eco

nomic impulses at the meso level of the SAM, rather than drawing attention to the individual path. Within the blocks, the individual paths are still preserved. In other104

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

words, the portraits of individual trees are still preserved in the forest picture of BSPA.
Using equation (49), the injection of institution di will transform the composition ofchanges in institution in the form of B"idi. The change in institutional income distribu
tion will further influence factorial incomes, AnBA^iBiid^ and output of production ac

tivities, BAiiBiidi. This series of processes follows a complication chain in the form:

A — BSdi — BAnBSdi -> A13BA32B&I1(50)

A similar complication chain can be observed from the injection of activities dA to thetransformation activities B"idA, factorial incomes, A^B"idA, and the institutional income,B2A21A13B33A such that:

BldA -* AnB&dA -* BAiA^id,(51)

3.3 Macro Decomposition
Finally, the pattern of structural changes in the Indonesian economy will be analyzed
by decomposing changes of income and output into three components: first, change of
output generated by the influence of final demand; second, change in technology (in-tersectoral linkages); and third, synergetic effects between change in final demand andtechnology. Using this decomposition, the indication of hollowing out process can beevaluated. Following Sonis et al., (1997b), the decomposition of changes of output
generated by institutions and activities are drawn as the following:

AX = X - Xo
AB = B(- Bo(52)

Ad = dt- do

where, AX A B,Ad are changes of total output, change of Leontief multiplier, andchange of final demand between two different times respectively. Analogous to thestandard input-output model to derive output as the multiplication between Leontief inverse and final demand, change in income or output can be written as:

AX = Xt-Xo = Bd - Bodo

(53)

The above change of output (53) can be decomposed into three components that cap
ture the value of changes:

AX = (Bo + AB) + (do + Ad) + Bodo
ABAd

(54)

where, BoAd is a change in the value of final demand, Ado is a change in technology,

and ABAd is a change as a result of synergetic interaction between changes in valueof final demand and changes in technology. Percentage changes in the income and out
put of institutions and activities in two time periods from to to U derived by changes infinal demand, technology, and both final demand and technology are gives as:(a) Percentage change in final demand of economic subsystem 1: Afd(difl~iQ(b) Percentage change in technology of economic subsystem i: S(Ai)ll-t0dit0

Structural Changes in the Indonesian Economy: A Network Complication Approach

(c)

105

Percentage change in final demand and technology of economic subsystem /as a result of synergetic interaction:5(A/)tl"t0 8(di)tl~t0.

4 Empirical Applications
The analysis of the pattern of the structural changes uses a set of six aggregated Indonesian SAMs for 1975, 1980, 1985, 1990, 1995 and 1999. The elements of the SAM
are aggregated into two types of factors (labor and capital), three groups of institutions(household, company and government), and five sectors of production activities (see ta
ble 1). With this SAM data set, any indication of hollowing-out in the Indonesian
economy can be analyzed based on changes in the input linkages over time.

Table 1 Classification of main sectors in the Indonesian SAM, 1975-1999
Main Sector
1.

2.

3.

Factors

Institutions

Activities

Elements of Main Sectors
1.1.

Labor

1.2.

Capital2.1.

Households

2.2.

Companies

2.3.

Government

3.1.

Farm Food Crops, Livestock, Food Manufacturing.

3.2.

Estate crops, forestry, hunting.

3.3.

Mining, Non-food Manufacturing, Utilities, and Construction.

3.4.

Trade, Restaurants, Hotels, Transport, and Communication.

3.5.

Financial Services, Real Estate, Government.

The structural changes in the Indonesian economy are analyzed from two different ap
proaches. Considered first is the influence of an initial injection from final demand ofboth institutions and production activities. Feedback loop effects that work in an eco
nomic system through economic subsystems, such as from institutions and activities
are identified to separate the influence of other subsystems in transforming the eco

nomic system. The impact of an initial injection from institutions to the transformationof institutional income, output of activities, and factorial income are presented in table
2a and 2b. Table 3a and 3b show the injection of activities and its influence on thetransformation of activities, factorial, and institutional income2.

2 It should be noted that the series of 1975-1999 SAM data use current market prices. Thus, theanalysis emphasizes changes in the composition of elements within each three economic subsystem
as a proxy to analyze structural changes in the Indonesian economy. In addition, the analysis uses direct coefficient multiplier (/ - An)~' instead of a constrained multiplier (/ - C)~' to capture the mar
ginal propensity to consume, where A23 ih C23.

106

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Table 2a Injection of institutions and the transformation of institutions,activities and factors, 1975-1999(Rp. billion)
EXOGENOUS
ACCOUNTHouseholds

1975

TOTAL

1985

1990

1995

1999

167

401

3,613

6,022

18

75

313

5,343

11,467

363

425

2,820

12,73432,22982,081

381

666

3,534

21,69049,71792,008

1990

1995

1999
66,152-

Firms

Government

1980

9,928
—

f

INSTITUTIONS

1975

1980

1985

Households

448

748

5,348

22,76950,086

Firms

167

324

1,912

9,587

22,157

13,286

Government

373

524

3,434

18,964

43,86096,967987

1,596

10,694

51,320116,103

176,405

TOTAL

f

ACTIVITIES

1975

1980

1990

1995

1999

Food crops

384

492

3,650

36,15978,411

94,696

Estate Crops

36

81

496

12,54532,56628,821

Manufacturing

149

220

2,009

39,81095,064

137,236
67,731

Trade

Other Service
TOTAL

1985

97

153

1,332

28,49567,382

223

284

2,445

3,136

13,137

6,651

889

1,230

9,932

120,145286,560

335,135

1990

1995

1999

14,41035,12844,108I
FACTORS

1975

1980

1985

Labor

272

392

3,230

Capital

317

423

2,980

14,25930,62941,861

589

815

6,210

28,66965,75785,969TOTALStructural Changes in the Indonesian Economy: A Network Complication Approach

107

Table 2b Injection of institutions and the transformation of institutions,activities and factors 1975-1999 (%)
EXOGENOUS
ACCOUNT

1980

1975

Households

0

1985

25.0

1999

1995

1990

11.3

16.7

12.1

10.8

Firms

4.7

11.3

8.9

24.6

23.1

0.0

Government

95.3

63.7

79.8

58.7

64.8

89.2

100

100

100

100

100

100

TOTAL

r

INSTITUTIONSHouseholds

45.3

48.9

TOTAL

50

1999

1995

44.4

43.1

37.5

17

20.3

17.9

18.7

19.1

7.5

37.7

32.8

32.1

37.0

37.8

55.0

100

100

100

100

100

100

Firms
Government

1990

1985

1980

1975

r

ACTIVITIESFood crops

1975

1985

1980
40

43.2

1995

1990

36.8

30.1

27.4

1999
28.3

Estate Crops

4.1

6.6

5

10.4

11.4

8.6

Manufacturing

16.8

17.9

20.2

33.1

33.2

40.9

Trade

10.9

12.4

13.4

23.7

23.5

20.2

24.1

23.1

24.6

2.6

4.6

2.0

100

100

100

100

100

100

Other Service
TOTAL

1
FACTORS

1975

1980

1985

1990

1995

1999

Labor

46.3

48.1

52.0

50.3

53.4

51.3

Capital

53.7

51.9

48.0

49.7

46.6

48.7

100

100

100

100

100

100

TOTAL

108

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Table 3a Injection of activities and the transformation of activities, factors,
and institutions, 1975-1999 (Rp. billion)
EXOGENOUS
ACCOUNT

1975

1980

1985

1990

1995

1999

Food crops(948)(2,456)(6,469)4,879

13,702

114,721Estate crops

173

968

(129)

1,374

2,302

27,848Manufacturing

3,842

19,54530,778106,321237,710

329,987

Trade

2,619

8,661

17,772

3,377

13,33875,823

1

(59)

314

2,127

6,915

10,306

5,687

26,65942,266

118,078

273,967

558,685

Other Service
TOTAL

ACTIVITIES

1975

1980

1985

1990

1995

1999

Food crops

6,143

16,272

33,665148,296

401,117982,860

Estate Crops

1,019

4,954

6,399

21,28960,664160,403

Manufacturing

6,913

32,58465,981

363,934

905,724

1,232,651

Trade

4,315

14,41532,379177,588473,962

937,548

Other Service

1,864

7,030

16,036

65,210241,751

348,093

20,25475,255

154,160

776,317

2,083,218

3,661,555

1975

TOTAL

FACTORS
Labor

Capital
TOTAL

1980

1985

1990

1995

1999

4,953

18,14339,211

82,292233,203499,945

7,780

29,55450,196

94,284

223,004

445,592

12,73347,696

89,407

176,576456,207945,537

ir

INSTITUTIONS

1975

1980

1985

1990

1995

1999

Households

9,278

30,38752,612

134,305

348,843704,781

Firms

3,690

17,563

21,59339,56096,650185,531

Government

1,554

9,577

11,482

22,171

39,177

108,587

14,52257,52785,687

196,036484,670

998,899

TOTAL

Structural Changes in the Indonesian Economy: A Network Complication Approach

109

Table 3b Injection of activities and the transformation of activities, factors,
and institutions 1975-1999 (%)
ACTIVITIESFood crops

1980

1975
-16.7

1985

1990

-9.2

-15.3

1999

1995

4.1

5.0

20.5

Estate Crops

3.0

3.6

-0.3

1.2

0.8

5.0

Manufacturing

67.6

73.3

72.8

90.0

86.8

59.1

Trade

46.1

32.5

42.1

2.9

4.9

13.6

0

-0.2

0.7

1.8

2.5

1.8

100

100

100

100

100

100

Other Service
TOTAL

r

ACTIVITIES

1975

1990

1985

1980

1995

1999

Food crops

30.3

21.6

21.8

19.1

19.3

26.8

Estate Crops

5.0

6.6

4.1

2.7

2.9

4.4

Manufacturing

34.1

43.3

42.7

46.9

43.5

33.7

Trade

21.3

19.2

21

22.9

22.8

25.6

9.2

9.3

10.4

8.4

11.6

9.5

100

100

100

100

100

100

Other Service
TOTAL

r

FACTORS

1975

1980

1985

1990

1995

1999

Labor

38.9

38.0

43.9

46.6

51.1

52.9

Capital

61.1

62.0

56.1

53.4

48.9

47.1

100.0

100

100

100

100

100

TOTAL

r

INSTITUTIONS

1975

1980

1985

1990

1995

1999

Households

63.9

52.8

61.4

68.5

72.0

70.6

Firms

25.4

30.5

25.2

20.2

19.9

18.6

Government

10.7

16.7

13.4

11.3

8.1

10.9

100

100

100

100

100

100

TOTAL

Note: numbers in parentheses are negative

110

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

4.1 The Injection of Institutions
Table 3a shows the value of institutional income, the demand for production activities,

and factorial income generated by the injection of institutions during 1975-1999; table
3b displays the percentage of the composition of the elements of such economic sub
systems. The final demand of institutions in the SAM framework might partially orcompletely be derived from the transfer of income from abroad to Indonesian households. In 1975, income from abroad received by households was virtually non~existen,

and was too small to be included in the table. Significant income transfers received byIndonesian households from abroad were recorded in the 1980 SAM table. They increased consistently from Rp. 67.0 million to Rp. 9,930 million between 1980 and

1999, as more Indonesian workers were employed abroad, many of them as unskilled
as well as illegal laborers. The share of government receipts from abroad in institu

tional income was still dominant from 1975 to 1999, although it tended to decrease.
While firms' receipts from abroad ranked second in institutional income in 1990 and
1995, no firm receipts were available in the 1999 SAM data.

The injection of institutions has transformed the pattern of institutional income

distribution. In 1975 for example, an institutional injection generated 45.3%, 17% and37.7% of the income of households, firms and government respectively. This distribu

tion pattern was almost the same until 1995, but changed significantly in 1999. Furthertransformation from institutional income to production activities revealed that the larg
est part of institutional demand went to food crops during the whole period from 1975
to 1985, between 36-43% of the output of production activities. The demand for foodcrops dropped from 36.8% to 28% in 1990 and 1999 respectively. Compared to otherproduction sectors, institutional demand for estate crops from 1975 to 1985 was notstrongly related.

The transformation of production activities from the injection of institutional income showed the declining share of food crops from 1975 to 1999; they were substi
tuted by manufacturing. This pattern indicated the increasing impact of institutional
consumption and spending toward manufacturing products. In the period of financial
crisis, the share of food crops rose slightly from 27.4% in 1995 to 28.3% in 1999. The

share of financial (including the government sector) outputs declined significantly after
1985 from 23-24% during 1975-85 to 2.6% and 4.6% respectively in 1995. In 1999,
the share was down to only 2%. This result is interpreted as the declining influence ofhousehold consumption, firm investment and government expenditure in the financial

and government sector. The financial sector was badly hit by the crisis in which many
commercial banks collapsed. Figures 5a, b and c provide the pattern of the changes inthe structure of economic subsystems from 1975-1999 as the result of the injection of
institutions.

The changing pattern of production activities on factorial income indicates the increasing share of labor compared to capital. During 1975-1980, the share of capital income was larger than labor income. In the next periods, the share of labor income increased to dominate capital income. The transformations of the influence from institu
tions to production activities and to factors provided positive effects on labor income
distribution during the whole period. Given the aggregate nature of the system (withonly a broad distinction between labor and capital), nothing can be concluded about

Structural Changes in the Indonesian Economy: A Network Complication Approach

111

Figure 5a Injection of institutions and the transformation of institutional income.
60-i
50-

&.

40-

*

I

^Q.

B

20-

"^^A
A

~~~~ B

""

^-^

^

~

^"

H

-H"\

1985

1990

1995

10

^

01980

1975

- Households■ Firms

1999- Government

Figure 5b Injection of institutions and the transformation of activities
60
50

1975

♦

Food crops—*— Trade

1980

1985
■ Estate crops

1990

1995

1999
■ Manufacturing■ Financial

Figure 5c Injection of institutions and the transformation of factorial income

112

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Figure 6a Injection of activities and the transformation of activities

1975

1980

1985

- Food crops• Estate crops- Trade• Financial

1990

1995

1999

■ Manufacturing

Figure 6b Injection of activities and the transformation of factorial income

Figure 6c Injection of activities and the transformation of institutional income

70
60
50

1

40

eu

30
20
10
0
1975

1980

• Households

1985

1990

-Firms- Government

1995

1999

Structural Changes in the Indonesian Economy: A Network Complication Approach113

the impact on the distribution of income across income groups.

4.2 The Injection of Production Activities
In the final demand of production activities, the share of manufacturing remained thehighest over the years from 1975 to 1999. It increased from 68% in 1975 to 73.3% in

1980; by 1990, it was 90% of total final demand of production activities. Although theshare of manufacturing sector in final demand in 1999 decreased to 59.1%, this sector
still plays a dominant role in the formation of final demand, particularly exports.
Table 3a and 3b exhibit the influence of initial injection from production activities
and its subsequent transformation of the output of production activities, factorial, andinstitutional income distribution. Here, the output of manufacturing sector played adominant role over the years, from 34.1% of total activities' output in 1975 to 46.9%

in 1990 - the largest share over 1975-1999. The decreasing share of manufacturingfrom 46.9%, 43.5%, and 33.7% in 1990, 1995, and 1999, respectively, followed the increasing share of demand for food crops. The injection of production activities gener
ally increased the share of factorial and labor income between 1975 and 1999. The dis
tribution of labor income in factors of production changed from 38.9% in 1975 to become 51.7% in 1990. Over the period from 1990 to 1999, labor has received the lion's

share in the factor incomes, figuits 6a, b, c pronde the pattein of changio ao a result of
the injechtor of aetirities.

4.3 The Hierarchy of Direct Coefficients
Analysis in the change in the hierarchy of direct coefficients of production activities in

the SAM framework was analyzed. The use of food crops as an input to food crops(1,1) ranked highest in the hierarchy from 1975 to 1985, then it fell to second rank

during 1990-95, and returned to the highest rank in 1999. During 1975-1980 and
1990, the use of food crops as an input by financial, real estate and government sector(1,5) was ranked second and third respectively; but then fell down to rank 21st during

1990-95 and rank 16th in 1999. The group of the inputs that had the highest rank be
tween 1975-1990 was dominated by food-crops as an input into other sectors (figure8). The use of food crops as the inputs for financial, real estate, and government (1,5)

in the SAM table was dominated by the government sector. Food-crops were distrib
uted as part of the compensation paid to civil servants. It should be noted that between
1975 and 1980, the government still played an important role in controlling economic
activities. It is not difficult to understand the importance of (1,3), the use of food crops
by manufacturing sectors, and by restaurants (1,4) (see figure 7).

Over the period from 1990 to 1999, the pattern of inter-industry relationships

changed significantly in comparison to previous periods. The pair of sectors in the fivehighest ranks was dominated by intra-industry replacing inter-industry. During 1990-95
for example, the first rank was achieved by (3,3) indicating the use of more of thesame manufacturing sector as the input. This finding is obviously sensitive to the levelof aggregation but does indicate a strengthening and deepening of the level of interactions between firms within a broad sector. The pattern of the hierarchy for the top fivewas stable over the period 1990-1995 that placed mining, non-food manufacturing,

114

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Figure 7 The hierarchy of direct coefficients in the Indonesian SAM 1975-1999
Cell

Cell

CeU

Cell

Cell

Cell

Rank

1975

1980

1985

1990

1995

1999

1

1,1

1,1

w

14 k

2

1,5

1,5

3,3

3

1,4

1,4

1,5

4

1,2

3,3

1,4

5

3,3

1,2

1,2

6

1,3

2,2

3,4

7

2,2

8

3,5

9

3,4

K **
\ /.

A P

\/ V

3,5
4,4
3,4

10

5,4

11

4,4

12

5,5

13

3,2

5,2

14

5,2

3,2

/

^

5,5

1,3
5,4

15

4,5

4,5

16

5,3

5,3

17

4,2

4,2

18

3,1

2,1

19

5,1

3,1

\A
A f
Or*

4,4
5,5

3,5
3,2

4,5

4,4

1,1

3,3

3,3

4,4

1,1

/ ^*

3,3

/ *

1,1
5,5

5,5

\ ^*

2,2

1 /*

tli
Vm

w
vAl
\ l/y /\

2,2

2,2

5,5

4,2

4,2

4,3

4,3

4,1

4,1

4,3

3,5

3,4

3,5

3,1

3,2

3,4

3,5

2,1

4,2

1,4

5,4

3,2

3,2

5,4

3,1

1/ >

5,2

2,1

\

4,2

1

V

s*

^\x

\/^

2,2

3,1
5,3

5,1

20

4,3

5,1

2,1

4,1

4,1

4,1

22

2,1

4,3

4,3

23

2,3

2,3

2,3

24

2,4

2,5

2,4

25

2,5

2,4

2,5

\

4,4

1,3

21

/

+

P\>

'/In'*//A ML// \ A

//\r
/ f
Vf

5,4
4,5
2,3

\

^

\ / ^
V w

1,4

'A*

3,4

\

5,3

/

\

^

X
/ ^

3,1
2,3

\ /b

4,1

^&, f

4,5

; k

5,4

\\ // fc
\ /

"

1,4

2,1
2,3

5,3

5,1

5,2

5,2

5,2

1,5

M

4,5

5,1

^

1,2

5,1
1,5

/

\

5,3

/ ^4

1,2

2,4

1,5

1,2

2,4

1,3

1,3

1,3

2,4

2,5

2,5

2,5

Sector codes:
1.

Farm food crops, livestock, and food manufacturing

2.

Estate crops, forestry, hunting

3.

Mining, non-food manufacture, utilities and construction

4.

Trade, restaurants, hotels, transport, and communication

5.

Financial, real estate, and government

utilities and communication as the highest rank (3,3), followed by food crops (1,1),
then financial, real estates, and government (5,5), trade, hotel & restaurant, transport,

communication (4,4), and the pair of estate crops, forestry and hunting (2,2). In 1999,
the pattern of the hierarchy has changed. The pair of food sector (1,1) returned to its

position in the first rank, followed by estate crops (2,2), mining, manufacturing, utili
ties and construction in the third rank; pair of trades (5,5) and financial, real estate, andgovernment (4,4) was in the fourth and fifth rank respectively.
On one hand, the pair of intra-industries of (1,1), (2,2), (3,3), (4,4) and (5,5) con

verge to form the top hierarchy from 1990 to 1999, while, on the other hand the use offood crops dropped significantly to a lower hierarchy such as (1,3) drop from rank 6th

Structural Changes in the Indonesian Economy: A Network Complication Approach

115

Table 4a Decomposition of changes in institutional income 1975-1985 and1990-1999 (%)

Period1975-1980

1980-1985

1990-1995

1995-1999

SectorChange inChange inChange in final

final demand

technology

demand & technology

Al^Cd,)11-10ecA,)11-10^08(A,)el-8(d,)IMi

TotalchangeHouseholds

95.1

-1.6

-3.3

100

Firms

99.1

0.2

0.7

100

Government

56.1

32.6

11.4

100

Households

64.6

5.9

29.5

100

Firms

99.6

-0.1

-0.3

100

Government

97.6

0.3

2.1

100

Households

86.2

6.0

7.8

100

Firms

91.9

3.4

4.7

100

Government

79.1

-9.1

-11.8

100

Households

80.8

-7.6

-11.6

100

Firms

78.5

-6.1

-15.3

100

Government

82.8

12.1

5.2

100

Note: negative changes were calculated as the absolute number of changes.

to 11th, 23rd and 24th in 1975, 1980, 1990 and 1999 respectively. As noted previously,
the use of food crops as the inputs by financial, real estate and government declined
sharply (1,5), replaced by its own sector (5,5), and by mining, non-food manufacturing,utilities and construction (3,5). The lowest hierarchy was the pair of (2,4) and (2,5)
during the whole period; while (2,3) increased significantly since 1990 to become rank

14th, 5th, and 13th in 1990, 1995 and 1999 respectively.
4.4 The Influence of Final Demand and Technology
The analysis on decomposition of income and output change is focused on two periodsof time: 1975-1985 (see previous work of Sonis et al.9 1997) and 1990-1999 that may
be considered to represent the state-led development stage of Indonesia and the periodof market-led economy respectively. Four sub-periods: 1975-1980, 1980-1985 (repre
sent 1975-1990 period), 1990-1995 and 1995-1990 (represent 1990-1990 period) arecompared to reveal the pattern of the effect of changes in final demand, technology,
and the combined (synergetic) effects. The patterns of the percentage change in institu

tional income during those sub-periods are varied. Table 4a shows the dominant role offinal demand in changing households and firm incomes (more than 95%), compared togovernment income (56.1%) during the period from 1975 to 1980. From 1980-1985,
the pattern was reversed for households and government income; change in final demand was dominant (97.7%) in changing government income, while the greater change

in technology affected household income (29.5%). Closer observations for the 19901995 and 1995-1999 time periods show that final demand still played a dominant role,116

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

Table 4b Decomposition of changes in output of production activities
1975-1985 and 1990-1999 (%)

Period1975-1980

1980-1985

1990-1995

1995-1999

SectorChange inChange inChange in final

final demand

technology

demand & technology

A?S(di)a4a8(A,)IW0d,"8(A,)IW08(di)tW0

TotalchangeFood crops

63.9

-8.0

-28.1

100

Estate crops

99.2

-0.1

-0.8

100

Manufacturing

96.7

-0.8

-2.5

100

Trade

94.1

-1.2

-4.8

100

Financial

85.2

-3.4

-11.4

100

Food crops

36.9

40.4

22.7

100

Estate crops

51.6

26.7

21.7

100

Manufacturing

57.0

26.9

16.1

100

Trade

71.1

18.2

10.7

100

Financial

51.3

30.7

18.1

100
100

Food crops

82.7

7.5

9.8

Estate crops

67.9

13.9

18.3

100

Manufacturing

84.5

6.7

8.8

100

Trade

84.6

6.6

8.7

100

Financial

53.2

20.0

26.8

100

Food crops

81.8

-7.1

-11.1

100

Estate crops

84.3

-6.3

-9.5

100

Manufacturing

65.8

-18.5

-15.7

100

Trade

74.7

-10.2

-15.1

100

Financial

62.1

-17.0

-20.9

100

Note: negative changes were calculated as the absolute number of changes.

however, there has been an increasing role for changes in technology and synergetic ef
fects accounted for changing institutional income.

Comparing to the 1980-1985 period, the pattern of change in the output of activi

ties during 1995-1999 is quite different. The value of final demand increased during

1990-1995 while technological and synergetic effects declined compared to the 19801985 period (table 4b). During 1990-1995, there has been a clear decline in the role oftechnology and synergetic effects (negative sign) that indicate the decline in intermedi
ate input.

5 Interpretation of the Results
Using a set of 1975-1999 aggregated SAM data, at the macro scale, the results from
two initial injections of institutions and production activities provide some general fea-

Structural Changes in the Indonesian Economy: A Network Complication Approach117

tures of the structural change in the Indonesia economy over the years from 1975 to

1999. The most important feature of the impact from injection of both institutions andactivities is the increasing consumption of food crops during the financial crisis in1999 with the decline in the share of trade, estate crops and financial & government
services, compared to 1995. However, whether this represents a cyclical rather than amore permanent, longer-run structural change in Indonesian economy should be con

firmed through the analysis of the hierarchy of direct coefficient of production activity
in the SAM framework with a more detailed level of aggregation and with further ex
plorations of future SAMs.

An important interpretation from the impact of institutional income to the transfor
mation of production activities is the declining share of food crops consumption, sub
stituted by the increasing share of manufacturing consumption over the period 19751995. The impact of the initial injection of production activities to factorial income andits subsequent influence on institutional income was varied. The share of household income was still the largest compared to capital during 1975-1999, and the share ofcompanies dropped significantly from 30.5% in 1980 to 18.6% in 1999 - the lowest
level during the whole period. This consumption pattern follows an Engel's curve thatshows a declining portion of income spent on food consumption when income per cap
ita rises. In the midst of the crisis in 1999, the share of consumption of food crops

rose again due to the decline in real income. In this situation, the influence of the declining institutional income from households, companies and government to production

activities provided a significant impact on the financial sector. In 1999, the demand forfinancial services declined dramatically.

The results from the hierarchy of direct coefficients might have been influenced
by the changes in real income, trade linkages, the adoption of technology, and govern

ment policies, both directly and indirectly. Until 1975, the role of private sector partici
pation in the implementation of long-term development strategy was still limited. Gov
ernment played major roles in initiating development, particularly in the agricultural
sector to achieve rice self-sufficiency. In the same period, the output of commercial
estate-crops was not as extensive as food crops as a result of significant government intervention. The hierarchy of the intra-sectoral use of estate crops is in rank 7th and 6th
respectively in 1975 and 1980, and moves down to rank (15th) in 1985. In the next pe

riods, the increasing role of estate crops as the input for sector 3 indicates the emer
gence of the output of non-foods manufacturing industries that require estate crops as

the raw materials, such as palm oil, and other related industries after 1985. The hierar
chy of intra-industry transactions for estate crops increases after 1985 from rank 15th
to become rank 5th in 1990 and 1995, and then at the second rank in 1999. The requirement of estate crops by restaurants (2,4) and by service sector (2,5) is low, hence,placing these pairs at lower level.

As for changes in the structure of production activities, labor and capital efficien
cies in many ways might have been driven by external factors as well as government

intervention. The changes in the structure of the Indonesian economy that place foodcrops as the highest rank in the hierarchy of intermediate input was partly influenced
by government policy at the earlier stage of the new order regime under President Soeharto to achieve rice self-sufficiency The declining role of food crops, replaced bymanufacturing activities since 1980, were not only influenced by the changes of in-

118

Journal of Applied Input-Output Analysis, Vol. 11 & 12, 2006

come that generated more manufacturing demand, but also induced by government

policies such as import substitution, market-driven, export oriented, and outward looking strategy .

In Achjar et al. (2005), the decomposition of production activities into goods andservices into disaggregated SAM documents evidence of the dominant role of thegoods sector in shaping the Indonesian economy. Obviously, at more disaggregated lev
els, it will be possible to explore the changing role of specific sectors in a variety ofways - in terms of industrial interdependence, and in income formation for example.

6 Summary and Conclusions
Using block structural path analysis, the mechanism of direct, direct transfer and aug
mentation of the influences that work in each economic subsystem has been explored.

The influence of economic subsystems in the SAM framework cannot be detected byconventional structural path analysis that emphasizes individual sectors and paths. It

has been shown in the empirical application that the injection from both block matrices

of institutions and activities has created an increasing share of labor income comparedto capital over the period 1975-1999. This indicates that the changes in economic
structure have contributed to the improvement of labor income through government

policies such as subsidies for the poor and a labor-intensive industrialization strategy as
well as to market forces propelled by foreign direct investment and the general liberali
zation of the economy. However, the conclusion should be tempered carefully by con
sidering that recently, more high-tech manufacturing industries that absorb highly edu
cated labor have been developed. Without a more detailed break down of income bylevel across households, it is difficult to assess the impact of these changes in income
distribution within the household sector. Further, the one advantage of the SAM frame
work is the ability to estimate institutional (household) income and not just income de
rived by labor as a factor.

The hierarchy of direct coefficients in the SAM framework shows a tendency of
intra-industry linkages to replace inter-industry. This pattern reveals preliminary evi
dence from the hypothesis that the maturity of an economy may be characterized by

the deepening of the intra-industry transactions due to the changes in technology, thereduction of transport cost, innovation processes, and other external factors. However,the decomposition of the change of output into three elements: internal, direct, andsynergetic influences cannot confirm any indication of hollowing out processes. Thechange in the output of activities and change in income were more influenced bychanges in final demand. The role of technology was almost negligible.
The analysis conducted in this paper may be considered as an exploratory analysisof the Indonesian economy viewed through the lens of a series of social accounting
matrices. While there is evidence of some important structural changes, the analysis
could not formally link the changes to policy initiatives, changes in Indonesia's termsof trade or other macro policy instruments. The next challenge would be to craft atransparent computable general equilibrium model that would enable analysis of thesechanges to be linked to more formal policy instruments. Further, it will be important toStructural Changes in the Indonesian Economy: A Network Complication Approach119

see whether post 2000, the Indonesian economy returned to its "long-run" development
path or, as a result of the 1997 crisis, moved off in a different direction.

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