Indonesia- trends in income

6

Economic Inequality inIndonesiaTrends, Causes and Policy Response

SATISH CHANDRA MISHRA

Introduction: Understandingthe Context

The subject of economic inequality has

undergone a renaissance through time. It

once enjoyed centre stage in the classical

economics of Ricardo and Marx, before

being moved to the sidelines with the

emergence of neo-classicism and its

emphasis on the efficiency of resource

allocation. However, the issue re-emerged

in a different form espoused by Keynes and

the politics of the New Deal.1

Economic inequality assumed a

paradoxical flavour with the emergence of

communist states of the USSR and later

China. The economics of the welfare state

recognized the popular appeal of universal

entitlement to basic public goods and

services in democratic regimes. However, its

politics carefully contained the more radical

elements of socialist thinking by resisting

wholesale nationalization of key industries

and banks which had become the opening

song of new socialist revolutions world-

wide. The utopian appeal of Marx and his

exhortation to create a society driven by the

slogan ‘to each according to his needs from

each according to his ability’, was

increasingly replaced by the language of

equality of opportunity, social inclusion and

human rights.

For developing countries, inspired by

the political weight and early successes of

the USSR, income distribution remained

a fascinating topic. Again there were some

Inequality and Social Justice in Asia140

interesting paradoxes. Many, if not most,

post-colonial governments were inherently

attracted to the idea of a ‘fair distribution’

of income, not only among different

segments of the population within their

borders but also across the global economy.

Equal opportunity for citizens was an

appealing concept for developing countries

struggling to build nation-states and create

the technical expertise needed to replace

departing colonial administrations and

businesses. The concept of equality was

equally important on a global level as

developing countries struggled to find a

place in the economic sun which shone

brightly for the rich industrialized countries

and dimly for the majority of less affluent

nations.

Lacking robust business enterprises and

technical expertise, post-colonial govern-

ments soon recognized that the more just

world that they sought could only be

realized through the agency of the state.

Even the much admired Soviet Union

could not escape the ironies of ‘primitive

socialist’ accumulation by which peasants

were starved to feed the cities and build the

economic scaffolding of the new socialism,

which included heavy industry and the new

cities which went with them.

Early models of development empha-

sized the ‘big push’ and capital accumulation

which only a modern industrial sector

could provide. Inequality was just a step in

the scheme of growth. The engine of

growth in the much quoted Lewis model

focussed on the transfer of labour from the

low productivity subsistence sector to the

high productivity modern sector. This

provided an early justification for the

statistical generalizations of economic

inequality during the process of develop-

ment, captured in the much revered

Kuznets U curve hypothesis by which

economic inequality was expected to rise

and then fall dur ing the course of

development.

The Kuznets U curve succeeded in

generating more than its fair share of

academic and policy related controversy.

First, there was the comforting conclusion

that economic inequality was just a passing

phase. Indeed, an acceleration of economic

growth it was argued could even shorten

the length of the shift from wider to

narrower economic inequality. Too much

preoccupation with radical programmes of

asset redistribution and nationalizations

were according to this view, considered

redundant and socially risky.

Second, a socially unacceptable rise in

economic inequality as predicted by the

Kuznets U curve might result in putting an

end to the economic reforms needed in the

early phases of development as political

support for such programmes evaporated.

Another problem envisaged was the

probable emergence of new economic and

political elites which could slow down the

process of income equalization in the

course of development. This second possible

implication of the Kuznets hypothesis raised

the possibility of deliberate government

policy to limit the rise in inequality. This

was achievable through a very diverse policy

mix ranging from progressive taxation on

one hand, to countervailing powers of

public enterprises and labour unions with

respect to business enterprises on the other.

The emergence and the remarkable

economic performance of the Asian

‘Miracle’ countries however, transformed

traditional views on economic inequality.

The presence of these Asian countries as

Economic Inequality in Indonesia 141

serious economic players in the global

market, from the late 1970s onwards

provided living proof (as opposed to

academic calculations from an army of

economic technicians), that growth does

not always have a negative impact on

income distribution. These were economies

which appeared to have achieved record

rates of high growth with low and stable

levels of economic inequality in a relatively

narrow span of just three decades.

The answer as provided by the World

Bank’s much quoted East Asian Miracle

study was an open economy, export

orientation, investment in human capital

and small states.2 These countries provided

a salutary lesson for the rest of the develop-

ing world. Economic protectionism, large

inefficient public enterprises backed by

dirigiste states operating behind high tariff

and non-tariff barriers were viewed as the

prime factors behind faltering growth, high

income inequality and corrupt bureau-

cracies. The conclusion therefore was that

the Kuznets U was not an inevitable feature

of economic growth. It could be avoided

by prudent macroeconomic policies and

appropriate public expenditure allocations

channelled towards raising human capital.

The ‘miracle’ in East Asia was not merely

high economic growth, which had

occurred in many other countries including

the USSR. Rather, it was their ability to

combine high economic growth with

seemingly stable and low inequality in

incomes. Such ‘growth with equity’

outcomes were attractive not only from an

economic standpoint of being able to

choose policies which could raise living

standards and lower poverty in short spans

of time but also were just as attractive in the

realm of politics. They seemed to have

provided evidence, in a world of falling

communist dominos, that small states, free

markets and investment in basic education

and health could provide the fastest and

most effective means of raising the majority

of the population above abject-poverty

levels.

The success of the East Asian economies

from the 1970s to the advent of the Asian

Economic Crisis of 1997-1998 generated

support for the view that economic growth

could be accelerated without having to

worry too much about economic

distr ibution. This conclusion came to

influence the perception of both donor

countries as well as many international

institutions. The political inference of this

view was easy to anticipate. If economic

growth could be income distr ibution

neutral it could also be neutral with respect

to political regimes. This was a comfortable

assessment at the time of the Cold War since

it allowed developed countries of the West

to support Asian dictatorships as long as they

were anti-communist. The logic was simple.

If growth was distribution neutral and

distribution could be managed by a mixture

of macroeconomic and social service

oriented policies, there was little to choose

between dictatorships and authoritarian

regimes in terms of their ability to raise the

absolute poor above the poverty line.

The fact that East Asian economies were

also largely comprized of small states was

the additional icing on the political cake. It

further boosted the intuitive appeal of the

Reagan–Thatcher theory on large

government and protected markets. Rolling

back the state through a mixture of fiscal

conservatism, pr ivatization and the

introduction of market-like budget

allocation mechanisms in public services, all


fitted well with this new brand of

conservatism; one which gave primacy to

economic growth and relegated economic

distribution to the back burner. Issues

related to income distribution and hence

economic inequality were either those

which would be settled during the growth

process itself (as advocated by Kuznets), or

in situations where governments could only

intervene at their own peril.

Gradually, the complexities of an

increasingly new globalized world began to

emerge. Factors such as capital market

liberalizations of the early 1990s and the

globalization of financial markets combined

with the rapid growth of world trade; the

collapse of the USSR and the botched

privatization of Russian public enterprises;

the instability of international capital

markets signalled by the Mexican Financial

Crisis (1994) and the Asian Financial Crisis

only four years later, reflected these

complexities. Further, it has also been

recognized that mechanical modelling of

growth and distribution linkages3 leaves out

a huge spectrum of the cause and effect of

country-based policymaking which affects

who gains control over what and how much

resource at any given moment in history.

This is illustrated in recent times by events

such as the anti-globalization protests in

Seattle and at WTO meetings later; the

collapse of many a third world dictatorship

in favour of multi party democracy; the

emergence of radical Islam, the rise of

China and India, and the current global

financial crisis emanating from sub-prime

mortgage defaults in the US, culminating

with the largest bail out in economic

history. Economic modelling has to a large

extent given way to a philosophical

discourse—from the distribution of income

to fairness and economic justice; from the

percentage of the population below the

poverty line to capabilities, freedoms and

deprivations; from planning and projections

to participation and voice; from technical

certainty to political complexity and finally

from human capital to human development,

social capital and trust.

In a rapidly changing and less ideolo-

gically certain world, economic injustice

and the need to arrive at a ‘fairer’ more

‘equitable’ division of resources has assumed

greater importance in policy formulation.

For example, the ‘hearts and minds’

campaign of an Iraq or an Afghanistan is

centred on a fairer allocation of resources

to local communities. Perceptions of

economic and social injustice also fuel fears

of social instability in India and China as

income disparities noticeably worsen. The

same is true of the politics of climate change

and the protracted negotiations around

agriculture subsidies in the Doha Round.

It is no longer the simple analytics of a

Kuznets U which is driving this new found

concern with an age old political economy

theme.

Instead, it is the competition for political

space, for a larger share of the global

economic pie and for the creation of a

physically safe world fr iendly to open

commerce and labour movements that are

central to this renewed fascination with the

fairness and social acceptability of a given

pattern of income distr ibution. The

frequency and escalation of social conflict

in many countries, combined with political

democracy have also strengthened calls for

‘socially inclusive’ growth, and a more

equitable sharing of environmental and

infrastructure related burdens.

The above discussion provides a


background that addresses some very

cr itical questions relevant to an

understanding of Indonesia’s political

economy and its prospects for the future.

The most obvious of these are summarized

below.

First, is the fact that virtually all accounts

of income distribution in Indonesia during

much of the period after independence,

underscore both low levels of economic

dispar ity, as measured by per capita

consumption expenditure, and their relative

constancy over time.4 This is applicable to

both the aggregate gini coefficient for

Indonesia as a whole as well as the provincial

gini coefficient. The implication is that

high economic growth beginning in the

late 1970s combined with low income

inequality would have, even in the absence

of pro-equalizing policy measures produced

sharply declining poverty rates.

The East Asian Miracle and its

subsequent variants also suggest that the

contribution of low initial levels of income

and in some cases asset inequality,5 such as

through land reform in Taiwan, to the

growth with equity achievements, lay at the

heart of the region’s economic miracle. An

added feature of the Indonesian income

distribution is the fact that the partitioning

of aggregate inequality into inter and

intraregional segments shows a relatively

minor contr ibution of inter reg ional

inequality compared to intraregional.

An obvious paradox in the Indonesian

context lies in explaining how a diverse

archipelago of over thirteen thousand

islands managed to sustain persistently low

levels of economic inequality. A quotation

from a well known work on Indonesian

regional geography serves to highlight the

point:

‘Indonesia is one of the most diverse and

heterogeneous countries in the world.

The international debate of the 1950s and

the 1960s on dualism originated in

Indonesia, simulated by social and econo-

mic conditions in the colonial and early

independence eras; and ‘regionalism’—in

a variety of manifestations—has been a

preoccupation of all governments of

modern Indonesia. Its economy com-

prises both the advanced technology of

modern cities of Java and highly capital-

intensive extractive and processing

industries, as well as tr ibal groups in

isolated regions barely exposed to the

outside world. Its ecology ranges from the

intensive wet rice cultivation of ‘Inner

Indonesia’, supporting some of the most

densely populated areas on earth, to lightly

settled regions in the Outer Islands in

which swidden (slash and burn) agricul-

ture is still predominant. In its culture and

religion the country is equally diverse

containing about 300 ethnic groups and

nearly as many languages. And its

geography is such that some outlying

regions are closer to (and in the past had

stronger economic ties with) neigh-

bouring countries than with the national

capital, Jakarta, and Java more generally’.6

The constancy of economic distribution

against a backdrop of tremendous econo-

mic and social diversity over a five decade

period requires a deep analysis. It cannot be

just explained by analysing the data

in different ways to get time ser ies

distributions of the gini, its regional or

sectoral partitioning or by engaging in a

discussion of whether the Kuznets U is or

is not applicable to the case of Indonesian

development.


Additionally, the impact of the political

and governance system on the distribution

of income also needs to be studied.

Following the economic collapse in 1998

and the transition to democracy, governance

shortcomings in the Indonesian economic

and political system have come under

scrutiny. Criticisms range from the systemic

corruption and cronyism which became the

hallmarks of the New Order system, to

significant differences in the administrative

capacity of regional governments to

formulate and implement development

policy. Add to these the enclave-based

investment in much of Indonesia’s natural

resource sector and one gets a picture of

significant structural inequality in income

distribution. However, the central problem

is that this picture is not supported by much

of the published data on economic

inequality.

There is also the issue of differences in

income distribution brought about by a

decade of intensive reform following the

adoption of democracy. However, the

advent of democracy, in the midst of

Indonesia’s most severe economic crisis,

does not necessarily mean that the burden

of poverty reduction and an improvement

of income distr ibution should be the

responsibility of the new democracy.

Nevertheless, the impact of the new

political system on the distribution of

income remains a focal issue in a country

attempting to endorse the political

leg itimacy of this new system of

government.

The Indonesian case study on economic

inequality continues to draw substantial

interest, not only from the point of view of

data and its statistical variations, but more

so from resolving the gap between what the

data seems to imply against what the logic

of the development process would indicate.

Indonesia has undergone one of the fastest

rates of urban development in the world. It

has a highly diverse geography and large

pockets of natural resource enclave

development. For much of its post-

independence years it has been governed by

authoritarian regimes without much public

scrutiny or criticism. Its industrial sector is

dominated by a very small number of super

r ich ethnically distinct families. By

developed country standards it has a small

state and continues to keep its markets

open.

Important questions arise about how a

country with over three decades or more

of record economic growth behind it

manage to generate and maintain a

relatively low level of economic inequality.

It is also important to understand how

Indionesia ensures that its economic

distribution indices do not show significant

shifts over time despite the country

undergoing a ser ies of financial and

economic shocks, natural disasters and at

least two major changes in its entire system

of government.

These are important questions, answers

to which could provide some indications of

whether future economic growth in

Indonesia will push it in the direction of

rising inequality, increasing interregional

disparities, possible social conflict and severe

strains on its new political system. This

would not be surprising given the recent

record of rising global inequality and the

sharp increases in inequality in the midst of

economic transformations. A number of

Asian economies, the economies of Eastern

Europe and the former USSR, China and

India, point to new challenges towards


producing equitable and inclusive deve-

lopment in the future. The Indonesian

case study which is an example of one

where we would expect high degrees of

inequality, but detect relatively low levels of

it, may make a significant contribution to

the literature on the subject.

Economic Inequality inIndonesia: Patterns and Trends

Measuring Inequality in Indonesia

Consumer expenditure surveys are the most

frequently used tool to assess income

inequality. However, these surveys could

be inaccurate owing to shortcomings

ranging from respondent bias in revealing

actual consumption levels and frequency to

the nature of the consumption basket used

in estimating household consumer expen-

diture. Additionally since surveys focus on

households as opposed to individual

consumption there is a tendency to ignore

the dimensions of intra-household equity,

in particular gender biases in intra-

household income distribution. Other

weaknesses relate to variations in inter

country or interregional prices in the

estimation of cross-sectional gini coeffi-

cients, given the geographical differences in

relevant consumer prices.

Conceptually, the use of household

consumer surveys as a proxy for household

income faces both the problem of

respondent bias, in which higher income

households are reluctant to reveal their

income and savings levels. Added to this is

the fact of consumption smoothening

through either debt or income transfers

within the extended family. The eventual

result that is commonly observed is the

underestimation of total consumption

estimates based on household consumer

surveys compared to consumption estimates

derived from national income accounts.

This underestimation is generally quite

significant (See Table 1 and Figure 1). A

combination of these factors tends to

TABLE 1: Estimate of Private Consumption, 1969–1993,

Rupiah Billion (current)

Year Susenas National Accounts Percentage of Susenas

to National Accounts

(1) (2) (1)/(2) × 100

1969/70 1,949 2,428 80.27

1976 7,223 10,500 68.79

1978 9,488 15,126 62.73

1980 14,814 25,595 57.88

1984 30,674 54,066 56.73

1987 44,617 71,988 61.98

1990 64,721 106,312 60.88

1993 98,015 175,078 55.98

1996 165,810 332,094 49.93

1999 337,778 813,183 41.54

2002 525,636 1,137,762 46.20

Source: BPS, National Accounts; BPS, Pengeluaran Untuk Konsumsi Penduduk Indonesia; and BPS,

Statistical Yearbook of Indonesia, various years.


undermine the estimation of inequality not

only at a point in time or over a long time

period, but across geographical borders as

well.

Apart from the weaknesses in consumer

surveys is the assessment of the broader issue

of inequality in assets. This assumes

significant importance, if initial asset

distribution is expected to influence the rate

and duration of future economic growth,

or help to explain how particular countries

can fall into an ‘inequality trap’. In such a

scenario, an analysis of asset concentration

at the beginning of the growth cycle and

how it changes over time is likely to have

an important bearing on determining

policy choices to reduce such initial

concentration of assets.

The political economy arguments

which usually are the foundation of the

concern with asset inequality are well

grounded in countries where government

and pr ivate business have a powerful

relationship, which undermines future

governance and market reforms. In the

context of East Asia, the success of

economic growth with sustained poverty

reduction in Taiwan, is often attributed to

the success of the radical land reform

programme initiated by the Kuo Mintang

government in the 1950s. Despite

Indonesia’s success in reducing poverty

dur ing the New Order per iod, the

implosion of the Suharto system of

government7 following the Asian Economic

Crisis of 1998 was largely attributed to the

inability of the political system to remove

entrenched corruption and cronyism that

primarily arose from acute wealth and asset

concentration.

Non-income indicators of inequality,

such as access to health, education and legal

FIGURE 1: Estimate of Private Consumption: Susenas andNational Account, 1969–1993

Source: BPS, National Accounts; BPS, Pengeluaran Untuk Konsumsi Penduduk Indonesia; and BPS,

Statistical Yearbook of Indonesia, various years.


redress are equally important dimensions of

inequality with an important bearing on the

degree and pattern of inequality in a given

social and political system. The focus on

income dimensions of inequality could

eventually produce an overstatement of the

degree of equality, or vice versa, in a given

region. In order to present a complete

picture of inequality, not only is the

statistical distr ibution of income and

expenditure needed, but more importantly,

an assessment of the notions of equity or

fairness across individuals, ethnic groups and

gender.

Finally, there is the broader question of

what type of inequality matters most in a

country. If the removal of absolute poverty

is the primary goal, then measures which

show greater sensitivity to the distribution

of income accruing at the lower end of the

distribution spectrum, such as the Atkinson

Index8, are likely to be more appropriate

indicators of inequality. Alternatively, if

inequality within and across provinces is

important, then the Theil index9 is likely to

be the best inequality measure. The gini

coefficient, which focuses on the entire

distribution of income rather than on any

part of it, is a popular measure for analysing

cross country growth-distr ibution

relationships.

Economic Inequality Over Time

Household consumer expenditure surveys

have been available in Indonesia since

1963.10 Despite some changes in sample

size, geographical and consumption basket

coverage, the gini coefficient derived from

the SUSENAS (Survei Sosial Ekonomi

Nasional/National Socio-Economic

Survey) data is widely used for a discussion

of inequality trends in Indonesia.

Figure 2 illustrates two broad features of

the Indonesian inequality picture. The most

FIGURE 2: Gini Coefficient in Indonesia, 1964–2007

Source: BPS, series of Susenas data.


outstanding feature is the relative constancy

of the overall gini, which barely changed in

the 43 years from 1964 to 2007. The gini

coefficient of household expenditure which

stood at 0.35 in 1964 rose fractionally to

0.36 four decades later in 2007. Despite the

Indonesian economy and society

undergoing a major transformation, the

aggregate gini fluctuated only marginally

within the range of 0.32 to 0.36.

The stability of income distribution is

further illustrated in Table 2 which presents

the shares of household consumption

expenditure. The ratio of the top 20 percent

to the bottom 40 percent of consumer

households barely moved from 2.07 in

1963, to 1.87 during the height of the Asian

financial crisis in 1999 and the collapse of

the New Order government, before

reverting to the same level of 2.1 by 2005.

This relatively constant trend is also

reflected in the movements of the shares of

total expenditure of the lowest 40 percent,

middle 40 percent and top 20 percent of

households. The consumption share of the

bottom 40 percent shifts only slightly from

19.4 percent in 1963 to 20.4 percent in

1990 and to 20.2 percent in 2005. The top

20 percent enjoy a share of around 40 to

42 percent in the same period with no

noticeable trend.

Rural economic inequality in Indonesia

tends to be slightly lower than in urban

areas. As indicated in Figure 2 the rural

gini coefficient stood at around the average

aggregate gini in 1963 but fell thereafter to

a low of 0.25 by the end of the 1980s only

to rise again to 0.27 by 2005. Inequality in

urban areas was higher and close to the

national average. The influence of the urban

gini on the national aggregate grew over

time pr imar ily due to the fact that

Indonesia’s urban population increased

rapidly over the four decades or more,

covered by the SUSENAS data.

As anticipated, the inaccuracies and

biases inherent in household consumer

surveys as well as the existence of alternate

theories regarding the relationship of

growth and distribution, has resulted in a

TABLE 2: Share of Expenditure Group

Year Bottom 40% Middle 40% Highest 20% Ratio H20/B40

1963 19.4 40.4 40.2 2.07

1964 18.6 37.9 43.4 2.33

1967 18.4 39.4 42.3 2.30

1970 19.9 39.3 40.8 2.05

1976 19.5 38.0 42.5 2.18

1978 18.1 36.6 45.3 2.50

1980 19.5 38.2 42.3 2.17

1981 20.5 37.4 42.1 2.05

1984 20.4 38.0 41.6 2.04

1987 21.2 37.6 41.2 1.94

1990 20.8 37.0 42.3 2.03

1993 20.4 36.9 42.8 2.10

1999 21.7 37.7 40.6 1.87

2002 20.9 36.9 42.2 2.02

2005 20.2 37.7 42.1 2.08

Source: Akita et al. (1999), and BPS. Statistical Yearbook of Indonesia, various years.


large body of literature on Indonesia’s

consumer expenditure data.11 The debate

over changes in economic inequality in

Indonesia appears to be centred on the

quality of the data and the reliability of the

estimates generated by the movements of

the aggregate and sectoral gini during

particular growth periods and the trends in

inequality across reg ions and across

particular groups. There is thus, a need for

a significant reworking of the commodity

baskets used in the SUSENAS and an

improvement in the conduct of the surveys.

Nevertheless there is a current consensus

that Indonesia does exhibit long-term

stability in the gini coefficient based on

consumer expenditure data.

Interprovincial Inequality inIndonesia

Table 3 presents the gini index between

1976 and 2005 for provinces in Indonesia.

From the data, two salient trends are

noticeable. First, there is a relatively low

dispersion of the provincial gini around the

Indonesian average. Second, the inter-

provincial distribution of the gini coeffi-

cient remains relatively constant over time.

The coefficient of variation of the inter-

provincial gini fell very slightly from around

0.15 in 1976 to 0.12 in 2005. A similar trend

is displayed in the pattern of income

distribution in major urban centres such as

Jakarta and Yogyakarta. In Jakarta the

provincial gini (0.29) rose from below the

national average (0.33) in 1984 to above it

by 1993 (0.42 compared to 0.34) and fell

back to below national average by 2005

(0.27 compared to 0.36). In Yogyakarta, the

gini remained close to the national average

for much of the period rising above it after

1999. Although similar movements can be

discerned for individual provinces, the

overall picture is that the divergence of

provincial gini coefficients from the

Indonesia average is very slight given the

relatively long time period of the survey.

This leads to the conclusion that similar to

changes in the aggregate gini over time, the

pattern of interprovincial inequality in

Indonesia tends to be noticeably constant

and stable over the three decades depicted

in the table.

The same conclusion is reached by

examining the distribution of income

among the top 20 percent, middle 40

percent and the lowest 40 percent of

households. What is remarkable is the fact

that even as late as 2005, the share of the

richest 20 percent of households in Jakarta

stood at 41 percent, in fact lower than the

Indonesia average of 42.2 percent. Given

that Jakarta is Indonesia’s only megacity and

the centre of government as well as much

of its industry and high income services, the

share of its top 20 percent of households in

total consumption would be expected to be

significantly higher than in the rest of

Indonesia.

An examination of data however,

presents a picture of Jakarta being more

egalitarian compared to the rest of the

country. Figure 3 highlights this conclusion

showing that the majority of Indonesian

provinces scored a consumption gini of

between 0.3 and 0.36 while a smaller

number hovered under the 0.3 mark. Given

the diversity of Indonesian provinces in

terms of geography, population density,

natural resource endowments, levels of

urbanization and industrial development

there is very little var iation in inter

provincial distribution of consumption.

Moreover, the extent of the variation also


TABLE 3: Gini Index and Interprovince Trend in Indonesia, 1976–2005

Province 1976 1984 1987 1990 1993 1996 1999 2002 2005

Nangroe Aceh 0.30 0.26 0.26 0.22 0.29 0.26 0.24 – 0.30

Darussalam

North Sumatera 0.28 0.26 0.29 0.25 0.30 0.30 0.25 0.29 0.33

West Sumatera 0.27 0.26 0.26 0.27 0.31 0.28 0.26 0.27 0.30

Riau 0.34 0.26 0.25 0.26 0.27 0.30 0.22 0.29 0.28

Jambi 0.29 0.20 0.23 0.23 0.24 0.25 0.24 0.26 0.31

South Sumatera 0.31 0.27 0.27 0.27 0.30 0.30 0.26 0.29 0.31

Bengkulu 0.31 0.21 0.22 0.26 0.28 0.27 0.25 0.25 0.35

Lampung 0.33 0.29 0.28 0.27 0.26 0.28 0.29 0.25 0.38

Bangka Belitung – – – – – – – 0.25 0.28

Riau Islands – – – – – – – – 0.27

DKI Jakarta – 0.29 0.29 0.31 0.42 0.36 0.32 0.32 0.27

West Java 0.30 0.30 0.30 0.32 0.30 0.36 0.29 0.29 0.34

Central Java 0.31 0.31 0.28 0.29 0.30 0.29 0.26 0.28 0.31

D.I. Yogyakarta 0.37 0.34 0.30 0.35 0.33 0.38 0.34 0.37 0.42

East Java 0.33 0.31 0.33 0.30 0.33 0.31 0.29 0.31 0.36

Banten – – – – – – – 0.33 0.36

Bali 0.23 0.29 0.33 0.30 0.32 0.31 0.27 0.30 0.33

West Nusa Tenggara 0.31 0.30 0.29 0.30 0.27 0.29 0.26 0.27 0.32

East Nusa Tenggara 0.38 0.31 0.28 0.30 0.25 0.30 0.27 0.29 0.35

West Kalimantan 0.32 0.25 0.26 0.28 0.30 0.30 0.27 0.30 0.31

Central Kalimantan 0.27 0.29 0.24 0.25 0.26 0.27 0.24 0.25 0.28

South Kalimantan 0.29 0.26 0.28 0.25 0.27 0.29 0.26 0.29 0.28

East Kalimantan 0.24 0.36 0.31 0.30 0.31 0.32 0.28 0.30 0.32

North Sulawesi 0.41 0.35 0.29 0.28 0.29 0.34 0.27 0.27 0.32

Central Sulawesi 0.38 0.30 0.27 0.25 0.29 0.30 0.29 0.28 0.30

South Sulawesi 0.35 0.35 0.27 0.30 0.27 0.32 0.30 0.30 0.35

Southeast Sulawesi 0.34 0.32 0.29 0.30 0.27 0.31 0.28 0.27 0.36

Gorontalo – – – – – – – 0.24 0.36

Maluku 0.38 0.30 0.30 0.27 0.30 0.27 0.24 – 0.26

North Maluku – – – – – – – – 0.26

Papua – 0.37 0.38 0.33 0.36 0.39 0.36 – 0.39

Indonesia 0.35 0.33 0.32 0.32 0.34 0.36 0.31 0.33 0.36

Standard Deviation 0.05 0.04 0.03 0.03 0.04 0.04 0.03 0.03 0.04

Coefficient of Varia- 0.15 0.14 0.12 0.11 0.13 0.12 0.12 0.10 0.12

tion (Std/Mean)

Source: BPS, Statistical Yearbook of Indonesia, various years; Bappenas (2001), Pembangunan Daerah

dalam Angka (Regional Development in Figures); and Strategic Asia staff calculations.


TABLE 4: Income Distribution by Classification, World Bank

and Gini Ratio, Indonesia, 2005

No. Provinces 40 Percent of 40 Percent of 20 Percent of Gini

Population Population Population Ratio

with Lowest with Moderate with Highest

Income Income Income

1. Nangroe Aceh Darussalam 21.56 *) 39.06 *) 39.39 *) 0.299 *)

2. Sumatera Utara 20.27 38.18 41.55 0.327

3. Sumatera Barat 21.45 39.31 39.24 0.303

4. Riau 22.88 38.39 38.73 0.283

5. Jambi 20.98 38.89 40.12 0.311

6. Sumatera Selatan 21.6 36.91 41.49 0.311

7. Bengkulu 20.08 34.69 45.23 0.353

8. Lampung 18.82 33.56 47.62 0.375

9. Kep. Bangka Belitung 21.57 41.57 36.85 0.281

10. Kep. Riau 22.32 43.31 34.37 0.274

11. DKI Jakarta 20.64 47.92 31.44 0.269

12. Jawa Barat 19.59 38.3 42.11 0.336

13. Jawa Tengah 22.31 36.52 41.17 0.306

14. DI Yogyakarta 15.41 32.66 51.93 0.415

15. Jawa Timur 19.79 34.67 45.54 0.356

16. Banten 18.79 36.36 44.85 0.356

17. Bali 20.12 34.97 44.9 0.33

18. Nusa Tenggara Barat 21.69 36.79 41.51 0.318

19. Nusa Tenggara Timur 19.91 35.6 44.5 0.351

20. Kalimantan Barat 21.98 36.19 41.83 0.31

21. Kalimantan Tengah 22.32 39.94 37.74 0.283

22. Kalimantan Selatan 22.45 41.04 36.51 0.279

23. Kalimantan Timur 19.78 39.06 41.16 0.318

24. Sulawesi Utara 20.03 39.27 40.7 0.323

25. Sulawesi Tengah 21.85 38.07 40.08 0.301

26. Sulawesi Selatan 19.55 35.51 44.94 0.353

27. Sulawesi Tenggara 18.91 35.43 45.66 0.364

28. Gorontalo 19.87 35.75 44.38 0.355

29. Maluku 24.53 38.07 37.4 0.258

30. Maluku Utara 24.69 37.72 37.59 0.261

31. Papua 17.14 35.69 47.17 0.389

INDONESIA 18.81 36.4 44.78 0.363

Note: *) Susenas in NAD was done lately and the result was not included in national result.

Source: National Socio-Economic Survey, Module Consumption, 2005.

Inequ

ality and S

ocial Justice in

Asia

152

FIGURE 3: Interregional Inequality in Indonesia

Source: Data constructed from Selected Socio-Economic Indicators of Indonesia, 2007.


shows little or no discernible trend over

time.

Variations in regional GDP per capita

across provinces in Indonesia, represented

by Figure 4, however display a different

picture. Clearly per capita regional GDP in

Jakarta is far above both the national average

and several times that of the poorest

province Gorontalo.

Table 5 illustrates some broad geogra-

phical variations in per capita provincial

GDP. It also underscores the influence of

oil and gas as a source of interprovincial

income variation. The ratio of the highest

to the lowest provincial GDP was just over

seventeen in 1978 at the start of Indonesia’s

green revolution, falling to ten by the

outbreak of the Asian economic crisis

in1997 and rising again to its 1978 mark by

the beginnings of the post-crisis recovery

in 2004.

Differences in the distr ibution of

household consumption across income

deciles in rural and urban areas are presented

in Table 6. These estimates cover a twenty

year period from 1984 to 2005 and serve

to highlight yet another instance of the

constancy in the distribution of income, as

approximated by household consumption.

What is remarkable is the relatively equal

distribution of decile household consump-

tion in rural and urban areas across different

FIGURE 4: GDRP Per Capita Across Province in Indonesia, 2005

Note: using 2000 constant prices.

Source: BPS, Gross Regional Domestic Product in Indonesia, various years.


TABLE 5: Regional Output Disparity in Indonesia, 1977–2005

1978 1988 1993 1997 2000 2004

Ratio using GDRP per capita

Highest to Lowest 17.14 16.30 12.49 10.18 18.39 17.57

Java-Bali and Outer Islands 0.60 0.83 0.99 1.09 – –

Western to Eastern 0.79 1.09 1.11 1.12 0.99 1.12

Ratio using GDRP without

Oil-Gas per capita

Highest to Lowest 4.55 7.50 9.61 9.37 13.92 15.83

Java-Bali and Outer Islands 0.93 1.13 1.24 1.30 – –

Western to Eastern 0.95 1.21 1.18 1.21 1.18 1.33

Note: using current market prices.

Source: Strategic Asia calculation based on BPS data, as cited from BPS-Gross Regional Domestic

Product in Indonesia and Indonesian Statistics, various years; Bappenas (2001) Pembangunan Daerah

dalam Angka (Regional Development in Figures).

TABLE 6: Rural-Urban Expenditure Group Share by Deciles, 1984–2005

Country Year Consumption Share by Deciles (%)*

1 2 3 4 5 6 7 8 9 10

Indonesia (Rural) 1984 3.78 5.20 6.16 7.08 8.04 9.09 10.33 11.94 14.38 24.00

Indonesia (Rural) 1987 4.28 5.52 6.37 7.20 8.07 9.03 10.19 11.68 14.02 23.64

Indonesia (Rural) 1990 4.45 5.56 6.50 7.38 8.24 9.17 10.27 11.72 14.08 22.63

Indonesia (Rural) 1993 4.46 5.72 6.58 7.40 8.27 9.21 10.34 11.76 13.95 22.31

Indonesia (Rural) 1996 4.27 5.52 6.38 7.22 8.10 9.07 10.22 11.71 14.03 23.48

Indonesia (Rural) 1999 4.50 5.88 6.76 7.60 8.44 9.38 10.45 11.81 13.84 21.34

Indonesia (Rural) 2002 4.55 5.74 6.57 7.37 8.21 9.14 10.25 11.67 13.87 22.63

Indonesia (Rural) 2005 3.90 5.23 6.14 7.02 7.94 8.97 10.20 11.79 14.26 24.55

Indonesia (Urban) 1984 3.25 4.63 5.61 6.59 7.61 8.78 10.15 11.96 14.78 26.64

Indonesia (Urban) 1987 3.53 4.65 5.64 6.62 7.62 8.73 10.06 11.84 14.82 26.49

Indonesia (Urban) 1990 3.46 4.44 5.38 6.32 7.33 8.46 9.86 11.76 14.99 28.00

Indonesia (Urban) 1993 3.44 4.38 5.31 6.23 7.24 8.36 9.76 11.66 14.92 28.70

Indonesia (Urban) 1996 3.18 4.12 5.04 5.98 7.00 8.16 9.60 11.58 14.97 30.37

Indonesia (Urban) 1999 3.47 4.62 5.47 6.30 7.21 8.26 9.56 11.31 14.22 29.58

Indonesia (Urban) 2002 3.49 4.54 5.41 6.31 7.30 8.43 9.81 11.67 14.66 28.38

Indonesia (Urban) 2005 2.87 3.94 4.81 5.74 6.74 7.92 9.39 11.39 14.75 32.45

Source: World Bank Poverty Monitor (http://iresearch.worldbank.org/PovcalNet/Jsp/index.jsp)

Note: * The income/consumption shares by deciles are based on estimated Lorenz curves. Households

are ranked by income or consumption per person. Distributions are population (household-size and

sampling expansion factor) weighted.


income groups. It is not clear what can be

read into specific estimates of consumption

across rural and urban areas except that they

seem to vary almost randomly. In several

cases urban consumption shares are lower

than rural ones showing lower income

inequality in urban than rural areas, while

in others the opposite was true. For

example, the share of consumption of the

7th decile in urban households was 9.39 in

2005 compared to 10.33 in rural house-

holds in the same decile. In the same year

the consumption share of the 9th decile

stood at 14.26 percent in rural areas com-

pared to 14.75 percent in urban households.

Indonesian data on household

consumption, used widely to estimate

income inequality, therefore, presents a

picture of a remarkable constancy of

income distr ibution over time, across

provinces and across rural and urban

households. However, a different story can

be constructed by examining per capita

provincial GDP, which exhibits a few,

resource rich provinces having per capita

incomes several times higher than those

with fewer resources.

Decomposition of Inequality AcrossProvinces and Sectors

Takahiro Akita et al. (1999) presents a

decomposition of income inequality in

Indonesia between and within urban and

rural areas and across provinces. The

findings are summarized in Table 7 and

clearly indicate an important trend. In both

categories, the contribution of between-

group inequalities to the total was

significantly lower than for within-group

inequality. Hence, in 1993, the percentage

share of between-groups Theil T was

around 18.8 percent compared to a rather

significant 81.8 percent for within group

Theil in Indonesian provinces. The same

picture applies to urban and rural house-

holds, as underscored by the fact that only

24.5 percent of the total income inequality

was accounted for by differences between

urban and rural areas, whereas the remain-

ing 75.4 percent was contributed by in-

equality within urban and rural households.

Decomposition by educational groups

and by gender in Akita et al. (1999) gene-

rates the same conclusion that the largest

share of inequality is generated from within

groups rather than between-groups. For

example, with respect to differences in

household consumption across various

educational groups, variations between

groups accounted for only 32.6 percent

while within-group inequality accounted

for the rest. In the case of decomposition

by gender, the contribution of within-

group inequality was even more pro-

nounced at 97 percent in 1993 compared

to only 3 percent for between-group

inequalities.

Takahiro Akita and Miyata (2007)

provide yet another set of decomposed

inequality estimates, for a wider spectrum

of categories including across educational

groups separately for rural and urban areas

using the SUSENAS data from the 1996,

1999 and 2002 surveys. Although the

numbers are different the overall conclusion

remains unchanged. This basically is that in

Indonesia, within-group inequality

accounts for the overwhelming share of

income inequality variations as opposed to

variations in inequality across groups.

Income Distribution in Indonesia:Contrasts with InternationalExperience

There is a sharp divergence between

changes and pattern of inequality in


TABLE 7: Inequality Decomposition by Province, 1987–1993

Province Theil T Theil L Gini

1987 1990 1993 1987 1990 1993 1987 1990 1993

Aceh 0.182 0.129 0.200 0.178 0.128 0.196 0.333 0.279 0.344

N. Sumatra 0.183 0.142 0.174 0.177 0.142 0.165 0.327 0.293 0.313

W. Sumatra 0.160 0.178 0.222 0.164 0.182 0.214 0.312 0.328 0.355

Riau 0.142 0.147 0.144 0.140 0.145 0.142 0.291 0.296 0.296

Jambi 0.127 0.112 0.135 0.124 0.113 0.130 0.277 0.262 0.285

S. Sumatra 0.182 0.180 0.207 0.172 0.167 0.192 0.322 0.313 0.341

Bengkulu 0.120 0.147 0.149 0.112 0.139 0.138 0.261 0.293 0.290

Lampung 0.184 0.173 0.158 0.175 0.166 0.153 0.329 0.319 0.307

Jakarta 0.188 0.210 0.235 0.181 0.201 0.235 0.333 0.352 0.379

W. Java 0.223 0.246 0.221 0.215 0.223 0.214 0.360 0.358 0.359

C. Java 0.183 0.194 0.198 0.179 0.189 0.189 0.330 0.336 0.340

Yogyakarta 0.226 0.317 0.256 0.220 0.275 0.243 0.363 0.378 0.378

E. Java 0.267 0.227 0.269 0.241 0.207 0.238 0.381 0.351 0.379

Bali 0.222 0.198 0.204 0.209 0.189 0.197 0.356 0.342 0.347

W. Nusa Teng. 0.202 0.234 0.192 0.197 0.208 0.183 0.345 0.354 0.337

E. Nusa Teng. 0.205 0.203 0.170 0.183 0.187 0.158 0.342 0.344 0.314

E. Timor 0.106 0.233 0.300 0.111 0.217 0.264 0.258 0.367 0.404

W. Kalimantan 0.166 0.177 0.200 0.153 0.166 0.184 0.310 0.319 0.337

C. Kalimantan 0.137 0.141 0.146 0.132 0.138 0.137 0.288 0.296 0.290

S. Kalimantan 0.178 0.148 0.168 0.169 0.145 0.166 0.321 0.295 0.318

E. Kalimantan 0.164 0.163 0.214 0.162 0.161 0.211 0.306 0.312 0.354

N. Sulawesi 0.171 0.141 0.165 0.170 0.141 0.160 0.322 0.294 0.311

C. Sulawesi 0.172 0.158 0.183 0.166 0.150 0.175 0.326 0.305 0.331

S. Sulawesi 0.169 0.201 0.172 0.164 0.199 0.173 0.318 0.348 0.321

S.E. Sulawesi 0.205 0.212 0.176 0.197 0.195 0.168 0.349 0.350 0.318

Maluku 0.212 0.123 0.186 0.196 0.119 0.181 0.350 0.277 0.334

Irian Jaya 0.306 0.225 0.246 0.302 0.225 0.249 0.426 371 0.389

All groups 0.247 0.245 0.266 0.232 0.227 0.243 0.372 0.361 0.378

W-group 0.205 0.204 0.216 0.197 0.193 0.201

(% share) (83.0) (83.3) (81.2) (84.9) (85.0) (82.7)

B-group 0.042 0.041 0.05 0.035 0.034 0.042

(% share) (17.0) (16.7) (18.8) (15.1) (15.0) (17.3)

Source: Akita et al. (1999), Inequality in the Distribution of Household Expenditure in Indonesia: A

Theil Decomposition Analysis.

Indonesia and in many other developing

countries in the region. Assuming that data

is reliable, inequality in Indonesia, in almost

all its variants, has remained stable over time

and across regions in the country. In

addition inequality was also low, hovering

between a gini of 0.32 to 0.36 for long

periods of time. The remarkable fact in the

case of Indonesia is that the movements of

the gini coefficient across income groups,


geographical areas and across urban and

rural areas exhibits the same trend of low

and near constant indices.

Figure 5 presents ADB (2007) compa-

risons of changes in inequality in the East

Asian region since 1990. The Indonesian

FIGURE 5: Changes in Gini Coefficient for Expenditure/Income Distributions,1990s–2000s (percentage points)

Note: Years over which changes are computed are as follow: Armenia (1998–2003); Azerbaijan (1995–

2001); Bangladesh (1991–2005); Cambodia (1993–2004); PRC (1993–2004); India (1993–2004);

Indonesia (1993–2002); Kazakhstan (1996–2003); Korea (1993–2004); Lao PDR (1992–2002);

Malaysia (1993–2004); Mongolia (1995–2002); Nepal (1995–2003); Pakistan (1992–2004); Philippines

(1994–2003); Sri Lanka (1995–2002); Taipei, China (1993–2003); Tajikistan (1993–2003); Thailand

(1992–2002); Turkmenistan (1998–2003); and Viet Nam (1993–2004); Income distribution for Korea

and Taipei, China; expenditure distribution for the rest.

Source: Ali (2007).


picture of an almost unchanged gini stands

in sharp contrast to the situation in a range

of other developing countries in Asia.

Figure 6 also from the same source presents

data on changes in per capita expenditures

in 1993 PPP (Purchasing Power Parity)

FIGURE 6: Changes in per Capita Expenditures, Bottom 20 Percent andTop 20 Percent – 1990s–2000s (in 1993 PPP dollars)

Note: Years over which changes are computed are as follow: Bangladesh (1991–2005); Cambodia

(1993–2004); PRC (1993–2004); India (1993–2004); Indonesia (1993–2002); Lao PDR (1992–2002);

Malaysia (1993–2004); Nepal (1995–2003); Pakistan (1992–2004); Philippines (1994–2003); Sri Lanka

(1995–2002); Thailand (1992–2002); and Viet Nam (1993–2004); numbers is parenthesis pertain to

annualized growth rates.

Source: Ali (2007).


dollars in selected Asian countr ies.

Indonesia once again illustrates the relative

similar ity of growth in per capita

consumption in the bottom 20 percent and

the top 20 percent of the households. The

growth of per capita expenditure was 2.09

percent per annum in the bottom 20

percent compared to 1.95 in the top 20

percent households.

Table 8 presents movements of the gini

index in a range of countries across Asia,

Latin America and Africa between 1981 and

2004. As indicated by other comparative

indicators, Indonesia exhibits both low and

relatively unchanging gini coefficients over

time. A comparison of economic inequality

between Indonesia and countries such as

India, China, Bangladesh and Thailand

(Figure 7) for the two and half decades

spanning 1981 and 2004, again demons-

trates that Indonesia experienced the lowest

change in income distribution amongst all

these countries.

The contrast with two neighbouring

TABLE 8: Gini Index* in Selected Cross-Region Countries, 1981–2004

Country 1981 1984 1987 1990 1993 1996 1999 2002 2004

Bangladesh 25.88 26.14 28.85 28.56 28.27 33.00 33.42 33.42 33.42

China-Rural 24.99 26.69 29.45 30.57 32.13 33.62 35.39 38.02 38.09

China-Urban 18.46 17.08 20.20 24.78 28.47 29.09 31.55 33.46 33.98

India-Rural 31.57 30.06 30.13 29.49 28.59 29.02 29.52 30.04 30.46

India-Urban 34.21 33.33 35.57 35.06 34.34 35.08 35.96 36.85 37.59

Pakistan 33.35 33.35 33.35 33.23 30.31 28.65 33.02 30.39 31.18

Indonesia 33.29 33.29 33.12 34.65 34.36 36.55 31.73 34.30 34.30

Lao PDR 30.40 30.40 30.40 30.40 30.40 37.00 37.00 34.67 34.67

Malaysia 48.63 48.63 47.04 46.17 47.65 48.84 49.15 49.15 49.15

Philippines 41.04 41.04 40.63 43.82 42.89 46.16 46.09 44.48 44.48

Sri Lanka 32.47 32.47 32.47 30.10 32.30 34.36 33.24 40.18 40.18

Thailand 45.22 44.63 43.84 45.03 46.22 43.39 43.53 41.96 41.96

Viet Nam 35.68 35.68 35.68 35.68 35.68 35.58 35.52 37.55 34.41

Argentina-Urban 44.51 44.51 44.51 45.35 45.35 48.58 49.84 52.52 51.28

Brazil 57.57 57.88 59.31 60.68 59.82 59.98 59.19 58.75 56.99

Chile 56.43 56.43 56.43 55.52 55.47 55.06 55.55 54.92 54.92

Colombia 59.13 56.12 53.11 52.46 54.27 56.96 57.92 58.83 58.83

Peru 45.72 45.72 45.10 43.87 44.87 46.24 49.82 54.65 52.03

Mozambique 44.49 44.49 44.49 44.49 44.49 44.49 45.58 47.11 47.11

Namibia 74.33 74.33 74.33 74.33 74.33 74.33 74.33 74.33 74.33

Nigeria 38.68 38.68 38.68 42.71 44.95 46.50 45.33 43.60 43.60

Zambia 60.05 60.05 60.05 60.05 52.61 49.79 53.44 50.74 50.74

Zimbabwe 56.17 56.17 56.17 56.17 52.81 50.12 50.12 50.12 50.12

Note: * Gini index: A measure of inequality between 0 (everyone has the same income) and 100 (richest

person has all the income).

Source: World Bank Poverty Monitor (http://iresearch.worldbank.org/PovcalNet/Jsp/index.jsp).


large economies is illustrated in Figures

8 and 9, which present a picture of

unambiguously rising inequality in both

urban and rural households. Interestingly

the sharpest increase in urban rural

inequality is shown, as one might expect

from theory, in China, the fastest growing

economy in the region. Indonesia on the

other hand, despite a 7 percent average

growth in the 1990s; a record fall in output

FIGURE 7: Economic Inequality in Selected Asian Countries, 1981–2004

Source: World Bank Poverty Monitor (http://iresearch.worldbank.org/PovcalNet/Jsp/index.jsp).

Years

FIGURE 8: Rural Gini Index in China and India, 1981–2004


Year

FIGURE 9: Urban Gini Index in China and India, 1981–2004

Source: World Bank Poverty Monitor (http://iresearch.worldbank.org/PovcalNet/Jsp/index.jsp)

following the Asian Economic Crisis which

was then followed by five years of

reasonably fast recovery (2007) with GDP

growth averaging around 6.4 percent,

showed very little movement in the

aggregate or provincial gini coefficients.

Movements in GDP growth, gini

indices and the incidence of poverty in

Indonesia are illustrated in Table 9 and

Figure 10. Although there might be

superior ways of presenting the data (for

example, by estimating trends in each

variable for the period between 1964 and

2007), the general conclusion is quite

straight forward. Low levels of economic

inequality during periods of high economic

growth allowed Indonesia to reduce

absolute poverty substantially (Figure 11)

from the 1970s onwards. The clustering of

the near-poor close to the poverty line, is

consistent with the fact that the share of

household consumption changed relatively

little between the bottom 20 percent and

the bottom 40 percent. Not only was

inequality low according to Indonesian

TABLE 9: Indonesia Economic

Indicators, 1964–2007

Year GDP Growth Poverty Gini Index

1964 3.5 – 0.35

1969 7.1 60.00* 0.35

1976 6.9 40.08 0.34

1978 7.7 33.31 0.38

1980 7.9 28.56 0.34

1981 7.4 26.85 0.33

1984 6.0 21.64 0.33

1987 3.9 17.42 0.32

1990 7.2 15.08 0.32

1993 6.5 13.67 0.34

1996 8.0 17.65 0.36

1999 0.8 23.43 0.33

2002 4.5 18.20 0.34

2005 5.7 15.97 0.33

2006 5.5 17.75 0.36

2007 6.3 16.58 0.36

Source: BPS (1997) Statistics during 50 years

Indonesian Independence; and BPS Statistical

Yearbook of Indonesia, various years.

Note: * Poverty data 1969 was estimated.

data, but it was relatively evenly distributed

amongst the poor segments of the

population. The result was the economic


FIGURE 10: Economic Growth, Poverty and Inequality in Indonesia, 1964–2007

Source: BPS National Income Statistics and Susenas Consumption data.

Note: Gini Index and poverty rate are using 1993 data = 100.

FIGURE 11: Poverty in Indonesia, 1976–2007

Source: Constructed from BPS data, various edition.


miracle for which Indonesia and several

other countries in the region eventually

came to well known.

Finally Figure 12 illustrates another

distinction between Indonesia and the

behaviour of economic inequality in the

world as a whole. Francois Bourguignon

and Morrison (2002) decompose long-

term global inequality trends. Their

estimates show that a large part of the

differences in cross-country inequality is

explained by cross-country variations

(around 60 percent of the total) with the

rest being attributed to within-country

shifts in inequality. Economic inequality in

Indonesia shows a completely different

pattern with the largest part of inequality

variations being generated by within-group

(province, sector, educational groups,

gender, etc.) as opposed to across groups,

which account for only a small proportion

of inequality. To understand the dynamics

of g rowth and distr ibution and the

direction of causation one needs to

construct specific case studies within

provinces or sectors.

Non-Income Inequality

This paper has focused pr imar ily on

variations in measures of inequality based

on household consumption which serves as

a proxy for household income. However,

indicators produced in Indonesia’s human

development reports of 2001 and 2004

describe variations in a range of non-

income variables across the provinces.

As reflected in Table 10, there is a

significant difference in provincial rankings

based on regional GDP per capita and those

based on ranking in Human Development

Index (HDI) terms. The difference between

the gross regional domestic product

(GRDP) and the HDI ranks ranged from

+17 to –26 among 30 Indonesian provinces

in 2002. The case of Papua illustrates the

point. Although Papua was the third

richest province in terms of regional per

capita income, it was among the most

FIGURE 12: Global Inequality and its Components, 1820–1992

Source: Bourguignon and Morrisson (2002) and World Bank (2005).


TABLE 10: Comparison of per Capita GRDP and HDI, 2002

GRDP GDRP Rank HDI HDI GRDP Rank

US$ PPP Rank – HDI Rank

D.I. Yogyakarta 1,581 20 70.8 3 17

Maluku 950 28 66.5 12 16

North Sulawesi 1,695 17 71.3 2 15

Jambi 1,270 23 67.1 10 13

Bengkulu 1,188 24 66.2 14 10

Central Java 1,340 22 66.3 13 9

Lampung 1,085 27 65.8 18 9

Riau 2,050 13 69.1 5 8

West Sumatera 1,714 16 67.5 8 8

North Maluku 1,094 26 65.8 19 7

South East Sulawesi 948 29 64.1 26 3

Central Kalimantan 2,321 8 69.1 6 2

East Nusa Tenggara 756 30 60.3 28 2

DKI Jakarta 7,705 2 75.6 1 1

West Java 1,680 18 65.8 17 1

Gorontalo 1,117 25 64.1 24 1

North Sumatera 2,357 7 68.8 7 0

South Sulawesi 1,340 21 65.3 21 0

South Sumatera 1,769 15 66.0 16 –1

East Kalimantan 9,242 1 70.0 4 –3

Bali 2,497 6 67.5 9 –3

Banten 2,727 5 66.6 11 –6

East Java 1,641 19 64.1 25 –6

Bangka Belitung 2,083 11 65.4 20 –9

Central Sulawesi 2,053 12 64.4 22 –10

Nangroe Aceh Darussalam 3,051 4 66.0 15 –11

South Kalimantan 2,092 10 64.3 23 –13

West Kalimantan 1,975 14 62.9 27 –13

West Nusa Tenggara 2,290 9 57.8 30 –21

Papua 4,180 3 60.1 29 –26

Source: BPS, Bappenas and UNDP, Human Development Report (2004), p.12.

disadvantaged Indonesian provinces, ranked

29 out of 30 on the human development

scale.

Significant differences in HDI scores

existed across districts within each province

and are reflected in Figure 13. Interdistrict

variations in HDI performance were more

pronounced within provinces than across

provinces. According to Indonesia’s Second

Human Development Report in 2004,

within the Province of Papua, HDI indices

ranged from 47 in Jayawijaya, to 73 in the

port city of Sorong. A range of variation

higher than that shown in interprovincial


comparisons. The implication that can be

drawn is that HDI indices, affected

considerably by the access and quality of

public services, might be more diverse

within provinces than across them. Another

equally apparent trend is that HDI

underwent a marked decline in a number

of districts in sharp contrast to improve-

ments of HDI in most districts. This leads

to the theory that clearly the impact of

economic growth and more critically of

public service provision was not shared as

equally as suggested by household

consumption data. In the Indonesian

context, however, broad judgements on the

behaviour of inequality are not possible

based on aggregate data. What needs to be

conducted are case studies at the local level

to highlight barr iers and bottlenecks

towards more equally shared quantity and

quality of economic growth.

The good news from non-income data

is that key non-income indicators such as

life expectancy, adult literacy and infant

FIGURE 13: Range of HDI Values within Provinces, 2002

Note: The diamond represents the weighted average for the province, and the line links the lowest

and highest values.

Source: BPS, Bappenas and UNDP, Human Development Report, 2004.


mortality improved sharply during the last

three decades of the 20th Century (Figure

14). However, the disturbing fact is that

interdistrict variations in these indicators

still remains very high and in some

provinces and districts there is a noticeable

gap between rankings based on per capita

income and per capita HDI. Clearly the

dynamics of economic inequality, poverty

reduction and non-income indicators of

well-being are much more complicated and

require careful local level scrutiny.

Economic Inequality in Indonesia:Making Sense of it All

The vast body of statistical evidence

reproduced in the previous sections clearly

illustrates the rather distinct nature of

income inequality in Indonesia both over

time and across sectors and regions. Taking

the data at face value, would suggest that

Indonesia has managed to maintain a

relatively unchanged distribution of income

at all income levels of households over a

relatively long period of time. Achieving

this would be difficult in a country with low

levels of economic growth and/or structural

change. It would also be surprising in an

economy where relative constancy in

income distribution has been accompanied

by significant GDP growth, structural shifts

in the composition of output, rapid

migration from rural to urban areas, and a

situation where the economy has enjoyed

early capital account mobilization and a

relatively small state.

How much confidence can be placed on

the results of consumer household surveys

in the context of such a rapid historical

transformation needs to be examined. Of

equal importance is the analysis of

movements in the gini, particularly in times

of economic boom and in the midst of

economic crises.

FIGURE 14: Infant Mortality and Life Expectancy, 1960–2000

Source: BPS, Bappenas and UNDP (2001).


Indonesia’s EconomicTransformation andUnderestimation of Inequality

Economic Diversification ofIndonesia

The Indonesian development story is just

four decades old. In that time it moved from

being an overwhelmingly rural, low-

income economy to a diversified middle-

income country. Some of the main

contours of this development are spelt out

in Figures 15 and 16 and Tables 11 and 12.

Figure 15 presents the main features of

Indonesian economic development

between the mid-1960s and 2005. Within

this time-period, the sectoral contribution

to GDP from agriculture declined from just

over a half to an eighth of the total. Mining

and quarrying, which expanded rapidly in

the 1970s, but declined sharply in the 1980s

and beyond, was over shadowed by the

contribution of manufacturing. The weight

of the manufacturing sector continued to

grow till the onset of the Asian economic

FIGURE 15: Gross Domestic Product at Current Market Prices, by Industrial Origin,1968–2005 (billion rupiahs)

Source: BPS (1997) Statistics During 50 Years Indonesian Independence; BPS, Statistical Year Book

of Indonesia 2005/2006.

TABLE 11: Agriculture and

Manufacturing Sector Contribution,

1971–2007

Agricultural Manufacturing

Year GDP Employ- GDP Employ-

Share ment Share ment

Share Share

1971 44.0 64.2 8.8 6.5

1980 24.0 54.8 13.0 8.5

1990 17.9 56.0 19.4 10.2

1997 16.1 41.2 26.8 12.9

1998 18.1 45.0 25.0 11.3

2002 15.7 44.3 30.7 13.2

2007 13.8 41.2 27.4 12.4

Source: BPS & Bank Indonesia, var ious

publications and years.

Inequ

ality and S

ocial Justice in

Asia

168

FIGURE 16: Economic structure in Indonesia, 1951–2000

Source: Daan Marks, The Service Sector in Indonesia’s National Accounts, 1951–2000 (2005).

Econ

omic In

equality in

Indon

esia169

TABLE 12: Structure of Provincial GDP Sector-wise (in percent)

1975 1990 2004 StructuralChange

A I S M A I S M A I S M 3- 9-sector sector

Aceh 47.3 22.8 29.9 3.5 17.9 66.4 15.7 28.7 23.9 50.2 26.0 18.3 54.8 58.7North Sumatra 41.0 18.8 40.3 6.3 34.5 25.8 39.7 18.2 24.5 33.5 42.0 25.4 33.0 50.9West Sumatra 43.7 16.5 39.8 9.5 31.9 18.8 49.3 12.1 24.4 22.6 53.0 12.2 38.7 41.9Riau 2.8 91.2 6.0 2.2 5.4 81.4 13.2 6.5 16.9 67.7 15.4 30.9 46.8 109.5Jambi 50.0 17.8 32.2 9.2 34.3 20.8 44.8 14.4 29.2 33.0 37.9 11.8 41.5 43.8South Sumatra 20.9 47.3 31.8 19.1 18.1 44.8 37.1 19.7 19.8 54.8 25.4 22.6 15.0 24.8Bengkulu 53.5 6.6 39.9 1.9 34.1 17.9 48.0 3.0 40.1 10.5 49.5 4.0 26.8 34.1Lampung 56.4 9.1 34.5 7.3 41.9 14.9 43.1 10.9 37.4 22.7 39.9 11.8 38.0 43.6Sumatra 21.8 56.4 21.8 6.4 21.9 48.2 29.9 15.7 22.8 46.8 30.4 23.1 19.2 (n.a.)

Jakarta 1.7 23.0 75.3 15.5 1.1 37.9 61.0 26.4 0.1 27.5 72.4 15.9 8.9 39.7West Java 34.6 22.4 43.0 8.0 21.6 39.5 38.9 20.4 12.3 53.8 33.9 42.6 62.7 77.1Central Java 43.6 13.2 43.2 9.5 30.5 30.2 39.3 24.9 19.9 40.5 39.6 32.6 54.5 58.9Yogyakarta 41.6 14.2 44.2 8.9 28.8 16.9 54.3 10.3 16.6 24.8 58.6 14.7 49.9 49.9East Java 42.9 13.1 44.0 11.7 25.5 27.9 46.6 21.0 17.5 37.4 45.1 29.6 50.7 62.1Bali 47.8 11.9 40.5 3.0 34.7 11.7 53.6 5.3 20.7 15.4 63.9 9.0 54.1 66.4Java-Bali 33.8 17.4 48.8 10.6 20.6 33.1 46.3 22.1 11.6 39.0 49.5 29.2 44.5 (n.a.)

West Kalimantan 51.3 13.7 35.1 10.5 27.6 23.5 48.9 18.7 27.3 29.9 42.8 19.8 47.9 54.0Central Kalimantan 53.9 10.0 36.0 3.9 36.4 20.4 43.2 9.8 41.7 14.5 43.7 9.0 24.5 29.3South Lalimantan 40.9 7.0 52.2 4.7 26.1 23.9 50.0 16.9 25.3 38.5 36.2 15.5 63.0 63.0East Kalimantan 13.4 62.1 24.5 5.0 9.3 71.2 19.5 31.3 6.4 79.5 14.1 37.5 34.7 67.2Kalimantan 28.1 40.3 31.6 6.0 16.7 53.0 30.3 25.6 14.9 61.5 23.6 29.7 42.3 (n.a.)

North Sulawesi 45.1 8.5 46.4 4.4 35.4 12.0 52.6 5.7 21.0 32.6 46.4 9.2 48.3 59.3Central Sulawesi 63.8 6.8 29.4 1.2 42.3 16.3 41.4 5.9 45.3 38.4 7.7 38.9 36.9South Sulawesi 53.0 5.1 41.9 3.6 42.3 16.7 41.0 7.8 33.5 27.3 39.1 13.5 44.4 50.2Southeast Sulawesi 43.8 23.2 33.0 1.3 40.2 14.8 45.0 2.3 41.1 19.3 39.6 6.2 13.0 36.1Sulawesi 51.4 7.3 41.3 3.5 40.8 15.5 43.7 6.6 33.7 25.7 40.5 10.9 36.9 (n.a.)

West Nusa Tenggara 60.8 7.0 32.2 2.4 48.0 10.5 41.6 2.8 24.7 44.8 30.5 3.4 75.5 82.6East Nusa Tenggara 69.1 4.9 26.1 2.3 50.0 6.9 43.1 1.9 42.5 11.2 46.3 1.6 53.2 55.9Maluku 63.3 5.3 31.4 1.1 32.8 24.7 42.4 14.4 36.5 12.6 51.0 8.1 53.7 54.4Papua 20.3 63.9 15.9 0.5 18.1 57.3 24.6 2.4 10.0 60.1 20.9 5.6 10.1 27.4Eastern Indonesia 45.9 30.0 24.1 1.3 34.2 29.7 36.1 5.3 26.4 42.6 30.9 4.5 39.0 (n.a.)

Indonesia 30.9 31.6 37.5 8.2 21.9 37.9 40.3 19.6 15.8 42.4 41.8 26.3 30.3 56.0

Note: Based on current prices: A = Agriculture; I = Industry; S = Service; M = Manufacture, which is a subset of I.

Source: Hal Hill, Indonesia’s Changing Economic Geography, ANU, 2008.


crisis in the late 1990s before stabilising at

approximately 27-28 percent of GDP. The

broad shift is captured in Table 11 which

illustrates the sharp and the sustained

decline in the importance of agriculture in

GDP and the rise of manufacturing and

services over the half a century following

independence.

As in many other developing countries,

the structural shift in GDP is only partially

mirrored in the composition of employ-

ment. Agr icultural employment fell

continuously from around 64 percent of

total to around 41 percent today while the

share of manufacturing employment rose

steadily in the same period from a mere 6.5

percent at the start of the growth period to

around 12.4 percent in 2007. Figure 16

from Marks (2005) illustrates the scale of

Indonesian economic diversification with

the decline in agriculture and the rise of

industry and services. The interprovincial

picture presented in Table 12, clearly shows

that while the scale of the structural shift

varied across provinces, the move away from

agriculture to non-agriculture was evident

in most of the country.

As in many other countries of the

region, the continued diversification of

production was mirrored in the growth of

the urban population. Figure 17 illustrates

the extent of the population shift between

1950 and 2007. The share of the urban

population rose steadily from just over 12

percent at the start of the period to nearly

50 percent of the total by 2007.

Although the rate of urbanization may

to some extent reflect the impact of change

in Java where much of industry and

population was concentrated and where

population densities in the rural sector were

already among the highest in the world.

However, the magnitude of the structural

shift in both production and population

tends to indicate a pattern of development

discussed at length by Lewis and later

FIGURE 17: Urban Population in Indonesia, 1950–2007

Source: UN Department of Economic and Social Affairs, World Population Prospects, the 2006 Revision

Population Database, UNFPA and UNESCAP (2008); and BPS (Population Census and SUPAS).


Kuznets, which was the source of much of

the early literature on the growth-

inequality relationships.

Further evidence of the Lewis dual

economy type development in Indonesia is

provided by real wage data presented in

Figures 18 and 19. Although some

controversy exists over the scale of the real

wage increase during the New Order

period, Indonesian real wages on average

FIGURE 18: Real and Nominal Wages in Indonesia, 1986–1999

Source: Irawan, Ahmed and Islam (2000) Labour Market Dynamics in Indonesia, Analysis of 18 Key

Indicators of the Labour Market (KILM) 1985–1999. Jakarta: International Labour Office.

FIGURE 19: Real and Nominal Wages in Indonesia, 2000–2007 (1995 constant prices)

Source: ILO, Labour and Social Trends in Indonesia, 2008.


tended to be relatively constant during the

per iod of the economy’s structural

transformation. This is in alignment with

the observation of a large number of near

poor bunched around the subsistence based

poverty line, the absence of independent

wage bargaining structures and the fact that

the first phase of Indonesian economic

growth in the 1970s and early 1980s was

basically relatively unskilled and labour

intensive.

With regard to inequality, two broad

conclusions are possible. The first is that

Indonesian economic development

mirrored the classic pattern of labour

movement at a relatively constant real wage

between the subsistence and modern

sectors. Secondly, despite the geographical

diversity of the country and the importance

of oil and gas in some provinces, this overall

pattern of dual economy growth present.

Government Policy and the Evolutionof Inequality in the New Order

In the absence of any major redistribution

of income at the beginning of the deve-

lopment process, a structural transformation

of the economy should have resulted in a

shift of income distribution in favour of

profits and capital accumulation and away

from labour at the early stages of the growth

process. Other things being equal, this

should have led to growing inequality in

household incomes during the New Order

era with its record economic growth and

tight control over trade unions and labour

oriented political groups.

The expected rise in inequality could

have been mitigated by government policy

such as raising the incomes of households

in the lower incomes deciles. This could

have been implemented in diverse ways

ranging from progressive taxation to public

expenditure allocations to pro-poor

programmes and to low growth regions.

The degree to which this actually happened

during the New Order remains highly

controversial but there are particular

features of Indonesia’s growth process that

might have limited the expected rise in

inequality.

Controlling inflationary pressures

through conservative monetary and fiscal

policies on the one hand and raising the

supply and the access to food grains on the

other undoubtedly helped to prevent

erosion in the economic welfare of low

income households. Indonesia’s success (in

contrast to many other oil exporting coun-

tries, such as Nigeria) in saving windfalls

from the oil price boom in the mid-1970s

and redirecting these towards infrastructure

and public services such as education and

health, is well known. The impact of these

policies is likely to have been propor-

tionately greater on lower income house-

holds. This combined with the fact that the

first phase of growth in the 1970s and early

1980s was labour intensive and export

oriented, only adds to the argument that

Indonesia’s economic growth was widely

shared. Sharp declines in absolute poverty

followed and further provided evidence of

Indonesia’s economic miracle in those

years.

Indonesia also scored some early

successes in the field of education and

health. Its remarkable success in raising

primary education enrolment compared to

even the miracle economies of south-east

Asia is presented in its first National Human

Development Report for 2001 (Figure 20).

In 1965 Indonesia’s gross primary enrol-

ment ratio stood at around 68 percent


FIGURE 20: Primary Enrolment in Southeast Asia, 1965–1990

Source: BPS, Bappenas, and UNDP (2001).

compared to around 80 percent for

Thailand and over 90 percent for Malaysia.

By the end of the 1980s, Indonesia enjoyed

the highest pr imary enrolment ratios

amongst neighbouring countries. This was

reflected in a sustained rise in Indonesia’s

public expenditure devoted to education

from 1970 to 1990 (Figures 21 and 22).

Although achievements in the health

sector were more modest, they were

nevertheless significant. For example, the

country succeeded in effecting a sharp

reduction in infant mortality rates, from an

unacceptably high 130 per thousand live

births at the beginning of the 1960s to

around 50 by the mid-1990s. The result was

a marked improvement in life expectancy

which moved up from 40 years in 1960 to

60 years by 2000.

Sustained economic growth, relatively

low initial rates of income inequality, rising

public expenditure on primary health and

education and a fiscal policy which was able

to keep inflation in check all contributed

to sustaining a rise and preventing a fall in

the share of consumption in lower-income

households. A substantial increase in job

opportunities in the urban sector, were

availed of by thousands of young female

workers who entered the workforce in

textile and garment factories en masse. The

reduction in absolute poverty noted in the

economic literature on Indonesia is a

testimony to its several successes in its first


FIGURE 21: Education and Health Expenditure, 1969–1998(as percent of development expenditure)

Source: BPS, Bappenas and UNDP (2001).

FIGURE 22: Primary School INPRES Budget, 1974–1998

Source: MoF, Financial Notes, various years.


phase of labour intensive and public service

oriented growth. Although such trends in

poverty reduction were not reflected in an

improvement of the overall income

distribution, they nevertheless played a

pivotal role in preventing a rise in ‘relative

inequality’ by raising the incomes of the

poor at a faster rate than the rich in the early

phase of development. This further

underscores the fact that economic growth

in Indonesia seemed to be widespread and

shared by some of its poorest households.

Asset Concentration andImplications for Income Inequality

With respect to income distribution in the

upper ranges, the picture is considerably less

clear for a wide variety of economic and

political reasons. However, there are several

factors that contributed to asset concen-

tration and income inequality. These are

summarized below.

First, asset ownership and distribution

in the country’s most dynamic sector of,

manufacturing and mining industries, still

remains ambiguous. Claessens et al. (1999),

in a much quoted paper, estimated the

extent of market capitalization by top ten

families in a number of Asian countries.

Their data summarized in Figure 23

illustrates the acute concentration of assets

in Indonesia which tops the list relative to

other East Asian countr ies. Market

capitalization in the hands of the top ten

families accounted for as much as 57.7

percent of the total in Indonesia compared

to 46 percent in Thailand, 24.8 percent in

Malaysia, 18.4 percent in Taiwan and around

2.4 percent in Japan.

Information on the ownership and

control structure of Indonesian corpora-

tions remains blurred even in the present

day. Indonesian conglomerates were held

together since their inception in a web of

cross-holdings and inter-linked director-

ships. Market capitalization data taken from

capital market directories is frequently

misleading and provides only a very

FIGURE 23: Market Capitalization Controlled by Top Ten Families, 1996

Source: Claessens, Djankov and Lang (1999).


approximate mapping of the structure of

ownership and the concentration of assets.

In addition, the well-known interlocking of

commercial, military and political interests

in public and government favoured

enterprises makes even a near accurate

estimation of asset concentration during the

New Order exceptionally difficult.

Open capital markets complicate the

problem of estimating asset concentration,

since rich households and large businesses

often invest in both financial and physical

assets overseas. While quantitative data on

the concentration of non-agricultural

ownership and control is rare, qualitative

sources confirm Claessens hunch of marked

asset concentration in Indonesia during the

New Order. There is little to suggest that

the structure of ownership has changed

significantly in the brief period since the

advent of democracy following the 1999

elections.

Land is another key asset. It is however,

yet another area where accurate estimates

of concentration are difficult to access. This

is not only because a considerable part of

total land holdings remain uncertified but

also because the practice of share cropping

blurs the distinction between income

generated from ownership and from

renting. Whatever data is available tends to

suggest a r ising inequality in land

ownership. Tables 13 and 14 record a

steadily rising gini coefficient in both Java

(where it rose from 0.45 in 1973 to around

0.72 in 2003) and non-Java provinces where

TABLE 13: Inequality on Land Holdings, 1963–2003

Java Outside Java National

Average Land Land Average Land Land Average Land Land Land Theil

Holdings (ha) Gini Holdings (ha) Gini Holdings (ha) Gini Index

1963 0.70 – 1.90 – 1.10 – 0.29

1973 0.60 0.45 1.50 – 1.00 0.55 0.28

1983 0.58 0.49 1.38 0.48 0.98 0.50 0.23

1993 0.47 0.56 1.19 0.48 0.83 0.64 0.23

2003 0.30 0.72 0.80 0.64 0.70 0.72 0.26

Source: Land Theil Index from Frankema and Marks (2007); Average land holdings from data from

1963 to 1983 taken from Statistics during 50 years Indonesian Independence, 1993 and 2003 taken

from UNSFIR (2004); data for Land Gini from Ministry of Agriculture paperwork, based on Agriculture

Census, various years.

TABLE 14: Numbers of Agricultural Households by

Land Area Ownership, 1983–2003

1983 1993 2003

Household Share (%) Household Share (%) Household Share (%)

< 0.5 Ha 6,412,246 42.26 10,631,887 53.93 14,028,589 56.41

0.5–0.99 Ha 3,671,243 24.19 4,348,303 22.06 4,578,053 18.41

1.0–1.99 Ha 2,922,294 19.26 3,132,145 15.89 3,460,406 13.91> 2.0 Ha 2,168,315 14.29 1,601,409 8.12 2,801,627 11.27

Source: BPS, Agriculture Census, various years.


the gini rose from 0.48 in 1983 to 0.64

in 2003.

While asset concentration may not

necessarily translate into income inequality

in the absence of reinvestment of profits

into the business or redistributive taxes and

subsidies by the state, asset concentration is

likely to trigger, with a time lag, a rise in

income inequality. Brasukra Sudjana and

Satish Mishra (2004) argue that the extent

of asset and income redistr ibution in

Indonesia was historically very small. It

follows that asset concentration is likely to

be reflected over time in rising income

inequality. The absence of such trends in

household consumer surveys, therefore,

reveal a significant underestimation of

consumer expenditure and incomes of

households in the upper income bracket.

Underestimation of RicherHousehold Consumption

The underestimation of consumption of

upper-income households remains a major

drawback afflicting household consumer

expenditure surveys. In Indonesia this

underestimation tends to be more pro-

nounced relative to other countries for two

reasons. First, the income stream generated

from high asset and land concentration is

largely unknown given the fact that assets

can be held under multiple identities and

legal forms and because the commodity

basket used in the consumer surveys very

inadequately reflects the actual consump-

tion patterns of the rich, especially in urban

areas (refer to Appendix 1). Second, the

consumption basket used in SUSENAS is

designed to capture the consumption

pattern of the median consumer, and thus

excludes a wide range of consumer durables

including automobiles, holidays abroad,

health insurance in addition to transfers

overseas for children’s education or medical

expenses incurred abroad.

The net implication is the consumption

pattern of the richer households is not

approximated by the commodity baskets

used in the SUSENAS consumption

modules. Further, this underestimation is

likely to become more pronounced over

time as the economy becomes more diverse;

the size of the higher productivity non-

agr icultural sectors increases and the

number of households in the upper-income

bracket also rises. Based on this logic, the

larger the proportion of wealthier house-

holds in the economy the greater the

underestimation of household consump-

tion as a proxy for household income.

In fact, this is likely to be the most

plausible explanation for the constancy in

Indonesia’s income distribution indices

despite the country’s rapid economic

transformation. Some evidence for such a

possibility is presented by UNSFIR (2004).

A reworking of the gini coefficients

assuming a different composition of the

consumer basket which includes high-value

items, leads to a dramatic r ise in the

aggregate gini (Figure 24).12

Clearly, the underestimation of higher-

income household consumption is a serious

flaw in the Indonesian income distribution

statistics, and merits greater attention than

it has received over the years. One reason

for overlooking the flaws in the data is the

fact that government policy has tended to

focus on absolute poverty reduction

through a mixture of social welfare

expenditure and export oriented growth.

Redistribution of income away from the

rich towards the poor has by and large been

absent in the policy agenda. During the first


two decades of economic growth in the

1970s and 1980s, the availability of surplus

labour and labour intensive agricultural and

industrial production, combined with the

windfall gains from the first oil boom, eased

the political pressure to conduct an asset

redistribution programmes of the kind that

was experienced in Taiwan. In later years,

the involvement of the military in business,

not only in timber and illegal logging, but

also natural commodity exports combined

with its dominance in politics made any

serious redistribution agenda politically

unpalatable.

Interpreting Income Inequality Shiftsduring the Growth Process

Given the rather average and aggregate

estimates of economic inequality in

Indonesia following independence,

especially in the New Order period and

later, many observers have shifted the focus

to more localized swings in income

distribution. Thus, Anne Booth (1992)

argued that urban-rural disparities increased

between 1969 and 1978, but declined

thereafter. Similarly, real consumer

expenditure growth was faster in urban Java

than elsewhere between 1970 and 1976,

while regional income disparities increased

in the 1970s due to the impact of oil on the

regional GDP. Finally, regional disparities in

per capita consumption expenditure,

corrected for regional price differences

actually widened between 1980 and 1987.

Martin Ravallion and Monika Huppi

(1991) in a similar vein argued that poverty

alleviation and under-nutr ition in

Indonesia continued to decline during the

structural adjustment phase of the 1980s

due to gains enjoyed by the rural sector in

the growth process. Peter Timmer (2004)

argues that Indonesia enjoyed considerable

pro-poor growth for much of the New

FIGURE 24: Official (SUSENAS) and Corrected Gini Index, 1976–2002

Source: BPS data, calculation by UNSFIR.


Order period from 1967 to 1996. The

advent of the Green Revolution and the

establishment of the food logistics agency—

BULOG—contributed towards stabilizing

food prices which combined with invest-

ment in irrigation, and the introduction of

high-yielding seed varieties raised labour

productivity and incomes in rural areas. This

is likely to have been an important factor

behind the observed fall in rural gini

coefficients in the 1970s.

Although such interpretations of

income inequality and the incidence of

poverty in particular episodes of economic

growth or in specific regions or a given

sector all shed valuable light on the

complexity of Indonesian economic

development, they fail to deliver any

significant policy message for the future. In

particular, such disaggregated and disparate

case studies, decompositions and reworking

of official data only contribute to the lack

of clarity which surrounds the question of

economic inequality in Indonesia. Clearly,

the first step towards a programme for

equitable development in Indonesia is the

production of reliable and sufficiently

detailed data on income distribution and its

components at both national and district

levels, which remain the twin hubs of policy

making in today’s Indonesia.

Economic Inequality and FutureIndonesian Development

The outbreak of the Asian Economic Crisis

in 1998 resulted in a dramatic transfor-

mation in fortunes. Not only did the

country endure its worst economic crisis in

half a century, but the country also

underwent a significant change in the

structure of its economic and political

institutions. The crisis coincided with a

time when the global economy was

undergoing a fundamental shift, where

foreign exchange and financial flows grew

substantially faster than international trade.

Indonesia enjoyed both good policy and

good luck in the first one and a half decade

of its development during the 1970s and the

1980s. Growth was primarily generated by

the Green Revolution and labour intensive

textiles and footwear industr ies. This

contributed towards raising the income of

rural households and progressively lowering

the incidence of absolute poverty. With

relatively low levels of asset inequality, a tiny

industrial sector and the absence of a

landlord class that predominated in India or

Philippines, the acceleration of economic

growth actually resulted in a secular decline

in poverty.

This picture began to change with the

diversification of the economy first with oil

revenues followed by the growth of the

manufacturing sector. The Asian economic

crisis reversed the growth engine and led

to a major restructur ing of most of

Indonesia’s banks, as well as many of its

corporations. The advent of multi-party

democracy and the retreat of the military

from politics, set the stage for fracturing the

symbiotic relationship between business

and politics that had characterized the

Suharto government. It led to an increased

political awareness of the major ity

population and enhanced the political

attractiveness of pro-poor and pro-equity

policies. The question is whether

Indonesia’s impressive record on growth,

equality and poverty reduction is likely to

be sustained under the changing conditions

of the domestic democracy and inter-

national globalization. If not it is ques-

tionable whether income inequality will


FIGURE 26: Unemployment Rate in Selected Asian Countries, 1990–2007

Source: ADB Key Indicators 2008.

FIGURE 25: Poverty and Unemployment Rate Post-Crisis

Source: BPS, Labour Force Situation Report and Indonesian Statistics, various years.


follow the rising trend so familiar in other

Asian countries.

Although a detailed discussion of

Indonesia’s changing economic structure

and its impact on future inequality is outside

the scope of this paper, a number of

observations are warranted.

Firstly, the relatively easy development

phase where labour intensive industries and

new agricultural technology could deliver

major employment and productivity gains

ended by the late 1980s. The Asian Crisis

combined with the sharp fall in output that

followed, resulted in changing foreign trade

and production patterns. This in turn led to

a continued evolution in the structure of

output, especially in manufactur ing.

Textiles, garments and footwear have all

come under competitive pressure from low

wage economies of Asia, such as China,

Bangladesh and Viet Nam in particular.

Indonesia’s manufacturing base remains

narrow, focussed on assembly rather than

manufacturing. Trade patterns have also

tended to dr ift away from the high

technology markets of the US and Europe,

to trade in commodities and palm oil with

China and ASEAN countries.

Some evidence of this structural change

is provided by the behaviour of employ-

ment and poverty indicators with respect

to fluctuations in GDP. Figures 25 and 26

present data on open unemployment and

poverty incidence in Indonesia after the

Asian Economic Crisis. While there are no

detailed estimates of the response of

employment and poverty elasticities to

changes in economic growth, it is clear

that the resumption of economic

growth has had little impact on both

FIGURE 27: GDP Growth and Unemployment in China (percentage)

Note: GDP is using constant price 2000.

Source: Labour and Social Trends in ASEAN 2007; ADB Key Indicators 2006, and IMF-International

Financial Statistic (http://www.imfstatistics.org/imf/ ).


employment as well as absolute poverty

percentages.

The phenomenon of jobless growth

(Figure 27) much in evidence in China

points to a new phase in economic develop-

ment against the backdrop of a global

marketplace. There is little reason to assume

that Indonesia will not face the same

structural pressures as it moves on to a

higher growth path. In both China and

India one of the consequences of this

unbalanced growth has been a secular rise

in inequality.

Secondly, without a diversified manu-

facturing base and with a less developed

higher educational infrastructure, the major

source of future economic growth in

Indonesia is likely to focus on the exploi-

tation and export of natural commodities.

Such economic activity is not only likely

to be confined to a few favoured districts,

but is additionally likely to be both capital

intensive and conflict prone. Thus, future

economic growth is likely to be enclave

focussed, inequality prone and would

require local government protection. Such

growth is set to be very different from the

broad based agricultural growth of the

1970s and early 1980s.

Thirdly, the globalization of financial

markets, in effect, acts as a brake on

government fiscal and monetary policy.

Major departures from neighbour ing

country macroeconomic policies could

trigger capital flight and lower investor

confidence. There are limits to the

government’s ability to tax and spend on

social welfare and other inequality

dampening programmes. Without an oil

bonanza or its equivalent raising the

revenue/GDP ratio will be difficult. Equally

difficult is getting consensus from district

governments to direct revenues at poor

districts and away from the richer ones.

While Indonesia continues to have an

impressive anti-poverty PNPM programme

in place, its volume and reach may be

inadequate in the context of internationally

transmitted financial or export market

shocks. In particular, if inequality rises in

tandem with the experience of other Asian

countries the same pace of future economic

growth might deliver a lower rate of poverty

reduction.

Fourthly, while this leaves room for

‘smart’ interventions in health and educa-

tion, an area in which Indonesia has lagged

behind many of its neighbours, these are

typically long gestation public expenditure

interventions. These interventions also

require a fairly comprehensive reform of the

civil service in these sectors and the forging

of unfamiliar partnerships with civil society

and private sector service providing organi-

zations. While Indonesian officials are now

required to allocate at least 20 percent of

the total government budget on education

by Constitutional law, regional govern-

ments have yet to spend this budget fully

or in ways which improve the quality of

education.

The above reasons suggest that while

Indonesian economic development may

follow the pattern already set by many of

its neighbours and experience higher

growth with rising inequality its policy

choices remain limited. Additionally,

because the country continues to lack a

reliable set of data, to project future trends

in inequality, public policy tends to place

less importance on dampening inequality as

compared to reducing absolute poverty.

As Indonesia’s inequality predicament

becomes more apparent and as the potential


for regional conflict around competing

claims to Indonesia’s natural commodities

begins to surface, inequality is likely to

emerge as a central issue on the policy

horizon.

Conclusions and PolicyRecommendations

Economic Inequality in Indonesia

Renewed global and regional interest in the

scale and the dynamics of economic

inequality has yet to create a resonance in

Indonesia. This is partly attributable to the

reliability of data on income distribution.

Indonesian consumer surveys tend to

overstate the consumption of poorer

households and severely underestimate the

consumption of the rich. The net result is

an unusual uniformity in gini coefficients

generated from such data both over time

and across regions and sectors.

An important argument is that the

observed statistical uniformity of the

income gini in Indonesia contradicts both

development experience, as well as statistical

common sense. Given the enormous

structural changes that occur red in

Indonesia over the forty year period of 1968

to 2008, it would be reasonable to expect

significant shifts in the measured gini. The

fact that official statistical sources failed to

reveal such variations in expected inequality

provides the basis for taking a closer and

more analytical look at the way the use of

household expenditure data to approximate

the calculation of income inequalities in

Indonesia has tended to lend a bias to such

estimates. The time is opportune to initiate

a policy dialogue on inequality by ques-

tioning what the official figures tell us. This

study plans to focus on the factors which

are likely to lead to an a priori expectation

that income inequality may have risen over

time. Additionally, this study will also

attempt to make adjustments in the

estimation of income inequality which take

into account the underlying structural

changes over time.

Industrial diversification, rapid urbani-

zation, geographical concentration of

natural resource investment, the acute

concentration of industrial assets in the

hands of an ethnic minority, the close and

symbiotic relationship between military,

civil service and private business and the

political dictatorship which stifled any civil

society protest over the inequality issue, and

the physical liquidation of the left in the

1960s, has kept inequality off the policy

agenda. The first task is to ensure that it is

back on the front burner of development

policy. Therefore, re-assessing the measure-

ment of inequality is an important step in

that direction. An even more critical step is

an analysis of how rapid growth and

associated structural shifts in output,

employment, skill and technology base and

a wholesale change in governance systems

is likely to impact on levels and evolution

of inequality.

That theory must be synchronized with

measurement, is a key factor that has been

absent in Indonesian development debates.

The global fascination with the Asian

miracle and the belief by governments and

international agencies in the uniqueness of

the Asian model undermined any serious

cr itical thinking of the issue in the

Indonesian context. As both India and

China are now discover ing, sustained

economic growth in the context of a

globalized free markets can create major

imbalances. The very fact that income


inequality levels in China (once the envy

of countr ies attempting to promoted

balanced growth and poverty reduction) are

now approaching levels similar to those in

Brazil, long derided as representing one of

the worst cases of income inequality, over

a short span of 20 years, illustrates the need

to anticipate the direction and speed of such

future movements in inequality rather than

celebrating the spurious observed constancy

of inequality measures.

The Indonesian case, much like the

Chinese one, is interesting in that the early

phase of development did distribute the

benefits of economic growth relatively

widely. A combination of labour intensive

industrial technology, principally in textiles,

labour augmenting green revolution in rice,

and the dramatic transfer of agricultural

labour at a relatively low and controlled

wage to urban industry in a textbook

Lewisian process did for a while keep

inequality relatively constant. Indonesian

data tends to support this conclusion, but

only for a decade or so after the Green

Revolution from the mid-1970s onwards.

By the time the Asian Economic Crisis of

the 1998 arrived, Indonesia had all the signs

of an economy where future directions of

inequality would be very different from

what it had enjoyed in the very early years

of its development.

Government policy of the early New

Order period did help in alleviating poverty

and keeping inequality levels relatively

constant, partly by conserving and

redirecting the oil price windfalls of the

mid-1970s.13 Additionally, Indonesia’s

achievements in basic health, primary

education and literacy as well as in

infrastructural development which eased

the outward migration of labour from rural

areas should not be discounted. However,

the latter half of the New Order period

from the mid-1980s, was characterized by

a pervasively corrupt bureaucracy, the

establishment of pocket banks by leading

conglomerates and by a concentration of

power in Suharto’s inner family circle

immune from any countervailing power in

the military. The destruction of the

communists and the fusion of all political

tendencies into a single overarching

machine (the GOLKAR) reaching down to

the smallest village as well as the practice

of military and police personnel running

their own businesses, most pronounced in

the forestry sector, all point to structural

conditions for a rise in income inequality

over time. The fact that land reform, a

major contributor to the decline of rural

landlordism in China and later Taiwan, was

never taken seriously in Indonesia and that

property taxation remains one of the lowest

in the world till today illustrates the refusal

of the state to initiate a direct approach to

income redistribution. A few approaches

which were tried, such as transmigration,

simply fuelled local resentment and conflict

and eventually resulted in actually widening

the gap between the rich and the poor in

concerned provinces such as Papua,

Kalimantan and the Maluku regions.

Looking ahead, it can be argued that

future economic development in Indonesia,

in the absence of a countervailing policy to

promote equity, is likely to be inequality

enhancing rather than inequality

dampening, for the following reasons.

First, the momentum of urbanization

has run its course although the urban

population is still expected to continue

rising over the coming decade and a half.

This, combined with a liberalized wage


bargaining mechanism will tend to generate

an upward pressure on real wages owing to

the emergence of labour shortages in key

sectors.

Second, regional inequality is also set to

rise both due to the widely differing

resource and human capital endowments of

specific regions as well as the fact that future

foreign investment is likely to be channelled

towards those states rich in natural resources

such as energy, plantations and minerals.

State capture of local governments by large

domestic and foreign corporations also

cannot be ruled out within such a scenario.

Third, Indonesia has now entered its

second major economic shock in less than

ten years. The ILO and other agencies have

indicated that such crises have traditionally

been accompanied by both a rise in formal

unemployment as well as an increase in the

size of the informal economy. Although

the extent to which such informalization

of the economy generates new patterns of

intersectoral inequality remains to be

studied, it nevertheless signals the emer-

gence of new economic forces which

militate against the thesis of a relatively

constant degree of economic inequality in

Indonesia in the early 21st Century.

Additionally, globalization has been

accompanied in many countries by rising

wage inequality between skilled and

unskilled labour and inequalities between

exporting and domestic market oriented

regions. Also, the fact that changes in

income inequality can occur much faster in

open capital and commodity markets

suggests that the vision of a future Indonesia

much less equal than what both the data

suggest, and what economic logic would

dictate, becomes more plausible.

As a consequence future economic

development of Indonesia is unlikely to

follow the relatively easy path of the past.

Both employment and poverty elasticities

with respect to growth seem to be falling

and new investments probably in the natural

resource sector are likely to be more capital

intensive and region focussed. Inequality

may well follow the path already familiar in

many other Asian countries as documented

in the ADB report from 2007.

From a public policy perspective how-

ever, the critical question is regarding what

democratic governments can do in practice

about containing the expected rise in

inequality on the one hand, and actually

promoting equitable development on the

other.

Economic Inequality in Indonesia:Arriving at Public PolicyRecommendations

One key issue in arriving at policy recom-

mendations to contain a rise in or to reduce

existing levels of income inequality is that

in the era of globalized financial markets, the

policy space open to the government to

effect inequality reducing measures is likely

to be severely limited. For example, the

government’s ability to tax and spend for

social welfare programmes will be

constrained by fears of capital flight and

lower investment flows. Its ability to enforce

national priorities and standards on regional

governments will be limited by local

political support for directly elected

regional executive heads. The lack of a

social consensus on the limits to inequality

naturally hinders agreement on when

government needs to act to contain the

trend towards higher inequality.

Box 1 presents a summary of steps taken

by successive Indonesian governments

towards promoting equality and reducing

poverty during the post-independence


BOX 1: Policy Responses Impacting Inequality

Year Policy/Program Information Evaluation

Soekarno era

1950 Benteng (Fortress) To promote the deve- Indigenous importers with

Programme lopment of indigenous inadequate financial

entrepreneurs faster, resources continued to

Djuanda, the Minister serve as agents for ethnic

of Welfare, in April Chinese businessmen (Ali-

1950 issued a regula- Baba business).

tion which gave priority Indonesia’s experience

to indigenous busi- with its first affirmative

nessmen to import programme to promote a

goods from abroad. To strong and self-reliant

facilitate this import indigenous business class

trade, indigenous busi- proved to be a failure and

nessmen were given in the second half of the

easy access to cheap 1950s came to an

credit inglorious end

1960 Land reform The Basic Agrarian It is very difficult to

Law 1960 was a key estimate how much land

part of Soekarno’s has been redistributed

concept on Indonesian under this law, because

socialism and indeed after 1965 there is

one of the few pieces evidence that landlords

of socialistic legislation took back land that had

that was ever enacted been confiscated or

in the Guided Economy squatted on by labourers.

Period. Soekarno’s Implementation of this

landredistribution policy remain blurred (no

programme record data). But, at that

time land distribution was

usually used as an agenda

of the Indonesia

Communist Party (PKI)

and as a result triggered

rural horizontal conflict

between landlords and

PKI’s members

1964 BIMAS programme Agriculture intensifica- Not yet implemented due

and slogan ‘Panca tion programme by to political-economy

Usaha” using better ways on instability

farming (use of fertili-

zer, improved water

control, selected

seeds, etc.)

New Order era (Soeharto)

1966–1968 BIMAS programme Involved students from After 1974, production

with credit support agricultural studies growth tended to decline

from BRI to farmers fields as the BIMAS intensi-

fication programme ran

Contd...


into problems. Credit

default increased

moderately

1967 BULOG establish- To control rice price, In 1969, BULOG was also

ment distribution, and made responsible to

import authorities manage rice buffer stock

(Presidential Decree No

11/1969)

Repelita I Emphasized food

(1969-1970 to production, infra-

1973-1974) structure rehabilita-

tion and government

capacity building

(civil service admini-

stration)

1969 Inmas programme Rice intensification

programme carried

out by former BIMAS

participants, but with-

out government credit

1969-70 Kabupaten Public To encourage

Works Programme Kabupaten authorities

to carry out labour-

intensive public works

with financial assistance

from the central govern-

ment through per

capita subsidies

1969 and after Irrigation Develop- Government preferred On Pelita I, government

ment scheme to increase land pro- completed the building of

ductivity to improve irrigation infrastructures

farmer income (rural on almost 1.5 million Ha

income) rather than paddy land. Inflation was

distribution of assets/ well-controlled (moderate

land level) as a result of rice

price stability (food

availability). Agriculture

sector (include irrigation)

budget accounted for

almost one-third overall

government budget

1970 INPRES funding Government system, To reduce disparity/

system which allows direct inequality on human

grants from the center development, per capita

to the regions GDRP and income

(allocated at different distribution interprovince

levels, i.e. Provincial,

District and Village

Contd...


Contd...


Repelita II Emphasized

(1974-1975 to employment and

1978-1979) distributional

equity as well as

economic growth

1970s Puskesmas deve- Government policy to

lopment improve public

services on health

1974 INPRES primary Government policy to

school increase primary school

enrolment rate and

decrease illiteracy rate,

in order to improve

human capital

1978 Establishment of To increase womens

State Ministry of participation on

Women’s Role national development

agenda

Repelita Government 8 roads to equality: Most of scholars believe,

(1979-1980 to launched jargon regional development, this jargon was the

1983-1984) “Trilogy of Develop- access to health and government’s answer to

ment”: growth, stabi- education services, political instability,

lity and equality; employment opportunity regional dissatisfaction

and also 8 roads to equality on minimum and social unrest which

equality needs (food, clothes steadily increased during

and housing), law Pelita II (1973–1978)

access, etc.

Repelita III was to

focus on agriculture

sector to achieve

food self sufficiency,

and to boost manu-

facturing industry

1979 Income-Generating Joint project of Ministry First phase evaluation

Project for the of Agriculture and BRI showed that the average

Marginal/Landless to increase income of real income of the

Farmers (P4K) small farmer self-help participating small-farmers

groups and organizing had increased by approxi-

them to gain access to mately 40 percent

formal credit for funding

their business

Repelita IV Focus to maintain food

(1984-1985 to self-sufficiency and to

1988-1989) encourage machinery

industry

Contd...


Contd...


1980s Government policies Peningkatan Peranan Training and socialization

to increase female Wanita Tani (P2WT) about new agricultural

income technology

Peningkatan Peranan Support rural women in

Wanita dalam Industri small medium industry

Kecil (P2WIK) (household industries)

Peningkatan Peranan To improve skill and

Wanita menuju literacy rate of women, to

Keluarga Sehat dan socialize the significance

Sejahtera (P2W-KSS) of family reproductive and

health system for women

from poor family

Repelita V Focus on agricultural

(1989-1990 to sector, maintain food

1993-1994) self-sufficiency,

export promotion,

employment opportu-

nities, agro-industry

and machinery

1993 The Inpres Desa Established via Presi- The actual amount of the

Tertinggal (IDT) dential Decree to IDT grant per capita basis

programme accelerate poverty might be too small; The

reduction in left behind allocation of IDT grants

villages. IDT consisted with equal amount per

of fund—Rp 20 million/ village was problematic,

village—given to the due to the disparity on

communities to manage population density on each

and execute income- village

generating activities.

1993 Increasing access Promoting income BKK scheme serves 41

to credit via Badan earnings opportunities percent of the villages in

Kredit Kecamatan for the poor Central Java

(BKK) Scheme

1995 Takesra/Kukesra Appeal to companies

with post-tax income

of Rp 100 million or

more to contribute up to

2 percent of their after-

tax income to help

launch a new savings

and loan programme

aimed to assist families

who were still below

the poverty line

1996 School-feeding Programme to provide Expected to serve 29.28

Programme in supplementary food to million school students

IDT village primary school students

in IDT villages

Contd...


Contd...


Post Soeharto (Reformation Era)

1998 Special Market OPK commenced by In December 1998, nearly

Operations (OPK) as distributing 10 kg of 9.3 million households

part of social safety rice each month to were beneficiaries. Budget

net programme eligible households at for Social Safety Net

subsidized price of reached Rp 9 trillion

Rp 1000/kg.

1998 Employment Gene- Programme to provide Padat Karya has grown

ration (Padat Karya income support to the to include 13 sub-

Programme) unemployed and the programmes involving

poor; obtain production 8 executing agencies and

of benefits in the form reaching more than 300

of lasting social capital, districts

including people’s skills

and enterprise

1998 SME schemes Government allocated Budget on 1998-99 was

Rp 20 trillion to provide Rp147.2 billion or 0.9

SMEs with technical percent to GDP

assistance and access

to credit

Propenas era Economic develop- Sustainable develop- Inconsistency of national

(2000–2004) ment with ‘Ekonomi ment, poverty reduction, programmes, due to

Kerakyatan’ principle employment creation, political instability and

social justice, public systemic transition

participation, equal,

regional autonomy

principle, etc.

1999, 2001 Regional Autonomy According to this law, Regional disparities were

and after Law established natural-resource-rich likely to increase. Balanc-

provinces will have ing funds mechanism was

largest share for natural started via DAU, DAK and

resources revenue Dana Bagi Hasil

2003 State Finance Law Policymaking process

No 17/2003 was changed

Bappenas no longer

has budgetary rights

2004 Law on National It regulates planning Planning, budgeting,

Development and budgeting process monitoring, and policy-

Planning System in short and medium making on national

established term development became

more complex

Middle Term To achieve economic • Government target on

Development stability which will economic develop-

Plan (2004– provide employment ment: poverty

2009) opportunities and reduction, agriculture

Contd...


Contd...


minimum needs revitalization, manu-

availability, and also facturing competitive-

to built strong foun- ness, improved non

dation for sustain- oil-gas export, improved

able development investment climate,

(vision) support to SMEs,

labour market, macro-

economic stability

• Government target on

reducing regional

inequality: village

development and

regional disparities

reduction focused on

less developed region

• Government target to

improve HDI: provide

basic access to

health, education, and

social protection;

increasing population

control; and religious

aspect on develop-

ment

Long-Term Indonesia yang There are 2 missions Reduction on inequality

Development Maju, Mandiri dan which strongly related and regional income

Plan (2005– Adil (vision). with equity: (a) Develop- disparity; food availability

2025) ment is equal for all and for all; and to serve and

social justice; and improve public housing

(b) social welfare to and infrastructure.

achieve national Improved human capital;

competitiveness and infrastructures

development agenda;

employment opportunities;

non discriminative

development agenda,

reduce poverty rate;

spatial development

Government Social Protection Programmes under this Programmes target to 19.1

Work Plan and Support Cluster cluster: Raskin (Rice for million households

2009 the Poor), Jaskesmas,

BLT (Bantuan Langsung

Tunai), Programme to

Increase Farmer Wel-

fare and Programme

Keluarga Harapan

(Family Hope Plan)

Contd...


Contd...


Social Empower- PNPM Mandiri (National Each kecamatan which

ment Cluster Programme on Social included in this programme

Empowerment) was the will have Rp 3 billion/year

focus of this cluster as government support.

The target is to cover

5720 kecamatan

SMEs Empower- Focus to improve busi-

ment Cluster ness climate such as

ease to do business,

special tax for SMEs,

and Kredit Usaha

Rakyat (People Busi-

ness Credit)

Sources: Booth, Anne (ed),1992. The Oil Boom and After: Indonesian Economic Policy and

Performance in the Soeharto Era. Oxford University Press. Booth, Anne and Peter McCawley (ed),

1981. World Bank, 1994. Thee Kian Wee, 2004. ‘Indonesia’s First Affirmative Policy: The Benteng

Programme in the 1950s’. Paper presented at the Workshop on the Economic Side of Decolonization,

Yogyakarta, 18-19 August 2004. National Law on RPJP, RPJM and Propenas. Financial Statement,

Ministry of Finance, various years. Pidato Repelita, various periods. Sjahrir, 1986, Ekonomi Politik

Kebutuhan Pokok: Tinjauan.

Contd...


period. These measures reflect the chang-

ing philosophy and mood of the times from

direct support for indigenous entrepreneurs

in the Benteng Programme of the 1950s to

the basic health and education programmes

of the 1970s, to conditional cash transfers

of the current administration.

These programmes reflect a rather

meander ing and haphazard approach

towards inequality moving from directly

focusing on redistribution of assets to

attempts to reduce the proportion of the

population below the poverty line. On the

whole, programmes such as INPRES and

rural credit programmes of the New Order

were attempts to pull people out of abject

poverty, rather than change the distri-

bution of income for the economy as a

whole. In fact, the asset data, especially in

manufacturing, the fastest growing sector in

the 1980s and 1990s was characterized by

the sharpest concentration of assets.

Overall, with the exception of the early

Sukarno years, the primary policy concern

of the New Order governments was the

containment of absolute poverty. This

policy worked well in the first easy phase

of growth, resulting in a relatively broad

sharing of economic growth. However, by

the time of the launch of major structural

changes in the economy, the political mood

had shifted away from income redistri-

bution or concern for equality to the

prior ity of achieving rapid economic

growth as the core legitimizing principle of

a consolidated authoritarian regime.

Given the high probability of rising

inequality within an open economy

operating under a globalized market place,

the principal question facing the govern-

ment is the formulation of an appropriate

policy agenda to tackle inequality. Given the

neglect of inequality as a policy concern in

the past and the serious data problems


which bedevil measurement of inequality

in Indonesia at present, it may be premature

to arrive at a well formulated policy package

to contain inequality. Nevertheless, a

number of preliminary recommendations

can be made as key steps towards the

formulation of a more comprehensive

policy towards income inequality. The

central elements of such a policy are

summarized below:

• A social consensus on the degree of

income inequality tolerable in the

country and its key components.

Such a consensus will help successive

governments to define indicators

and activities which maintain

inequality within a targeted range.

One immediate option is to ensure

that such equality targets are

enshr ined in the design of the

2009–2014 medium term develop-

ment plans. Clearly, much public

consultation needs to go into such

target setting but such a process helps

to highlight the fact that concepts of

inequality are as much a matter of

political and ethical preference as

technical economic targets.

• A determined effort to reduce asset

concentration in industry and

services by a tighter application of

anti-trust law as well as by pre-

venting the creation of new

monopolies through de facto state

guarantees. This in effect would

entail the unravelling of the structure

of ownership and control in business

in Indonesia, an area in which no

reliable information is available. It

would also require the promotion of

more competition in indusry. This

can be facilitated by promoting and

encouraging new start up firms and

joint ventures with foreign firms.

• A sharp upward revision in taxes

related to property to bring these to

levels on par with similar economies

in other parts of the world.As a first

step it would be necessary to make

land and property registration

mandatory. A second step would be

to commission a special study on the

appropriate bench mark and how

such taxes can be collected in the

future.

• A renewed concern for raising

human development achieve-

ments of the past by improving the

quality of essential public services

and inclusive access to them by all

segments of the community. This

will not only assist in ensuring the

upward social mobility of poor

households but also provide them

with a minimum base of skills which

can be upgraded in the work place.

• Careful monitor ing of inter-

regional economic inequality with

the DAK, and special financial grants

have to be made to assist the

backward and the most disadvan-

taged regions. One model would be

to use the Fiscal Commission

approach common in India where

special quasi-judicial grants are made

to provincial governments in case

particular emergencies and special

needs arise. Another measure is to

augment the capacity of regional

governments to budget and plan

public expenditure and thus improve

project delivery, a matter of some

concern at present when many

regional governments are unable to

spend budgets allocated to them.


The above menu of policy measures has

the merit of shifting attention back to

inequality and away from an exclusive

concern with absolute poverty issues. The

two are clearly intertwined. Policy

approaches of the past have tended to focus

on only one aspect of the problem, that of

absolute poverty. The arguments put forth

provide a basis for a rebalancing of the

agenda towards a joint concern for poverty

and inequality, something that lies at the

heart of the human development and

capability approaches to development.

APPENDIX 1Measurement of ConsumerExpenditure in Indonesia:Comments on the SUSENASData

The National Socio-Economic Surveys

(SUSENAS) was conducted for the first

time in 1963 in order to collect data on the

demographic and socio-economic

characteristics of household members,

which include education, age, employment

status, consumption expenditure and living

condition. Since then, these surveys have

been undertaken regularly. The SUSENAS

was intended to cover all of Indonesia, but

the early surveys did not include all

provinces. It was not until 1982 that all

provinces including East Timor were

covered. The first SUSENAS in 1963

covered only five Java provinces and selected

16,000 households as a sample.

Since 1986, SUSENAS have used a

combined stratified/two-stage random

sampling technique with the main sampling

frame consisting of a list of enumeration

areas which are formed by breaking down

every village into smaller geographical units

with about 200 to 300 homogeneous

households. The selection of a sample of

households is made by classifying

enumeration areas into strata, choosing

several enumeration areas from each

stratum, and then selecting households from

each of the selected enumeration areas. In

the SUSENAS, province, urban/rural, and

expenditure categories are regarded as strata.

Since 1993 the SUSENAS have been

fielded yearly and is representative at the

level of the district (Kabupatan/Kota). Each

survey has a sample size of about 200,000

households (close to 900,000 individuals).

However, prior to 1993 only samples of

about one-quarter the size are available and

the survey is not representative at the

district level. The survey instrument con-

tains a core questionnaire, which collects

information about demographic characte-

ristics of all household members, their edu-

cation, labour market activities, and health.

Since its inception, SUSENAS have

placed an emphasis on collecting household

consumption data in order to estimate the

incidence of poverty and the degree of

inequality. There are two kinds of

consumption items in the questionnaire:

food and non-food items. There are

altogether 203 items in the food category

and a total of 103 items in the non-food

category. The Central Bureau of Statistics

has also been trying to collect household

income data in the SUSENAS, but due to

the relative inaccuracy of the data, it has not

published the results regularly.

In the context of decentralization, the

importance of poverty measurement at the

distr ict level is gaining importance in

Indonesia. Local level planners need local

level information that is timely and accurate.

BPS has started to calculate and make

available district level poverty estimates

based on the core, but these estimates are


subject to large variance as sample sizes at

the district level very small. As a result, some

districts have funded enriched sampling of

the SUSENAS to improve their poverty

estimates.

The SUSENAS provides reliable

information on changes in welfare on a

consistent basis. But it must be noted that

the picture presented is static, based on a

measurement of one point in time. Poverty

is dynamic and vulnerable households can

move in and out of poverty as a result of

local or widespread shocks such as personal

illness, natural disasters, or major changes in

prices of basic commodities. These inter-

temporal changes are not captured by the

SUSENAS. BPS has attempted to develop

current indicators of poverty using existing

and frequently reported data collected for

other purposes. Real wage data has been

found to be well correlated with changes

in monetary poverty. Real wage data is

reported for the national level and provides

policymakers with useful early information

about potential changes in welfare. Leading

indicators of poverty are also needed at the

district level where local governments are

responsible for providing social safety net

support. In 2005, a pilot effort was under-

taken with BPS assistance to devolve the

collection and analysis of nominal and real

wages to five trial districts. Given the decen-

tralization context coupled with the size

and heterogeneity of Indonesia in terms of

geography, markets, and access, local infor-

mation for local level decision-makers is

imperative.

While sample statistics descr ibing

changes of welfare for populations are

readily available, there is also a need for tools

to identify poor individuals. Traditional

means-testing based on employment status

and reported incomes are not viable where

the formal sector accounts for only 30

percent of the labour force and do not take

into account the dynamic nature of poverty.

BPS plans to pilot a household listing in

2005 which considers both individual and

household characteristics and the target

number of poor to be identified based on

national and regional poverty estimates.

The challenge will be to create flexible rolls

that are based on generally accepted criteria

that can be developed and maintained at a

reasonable cost.

In the surveys, however, it is widely

believed that, non-food expenditures are

progressively understated by larger-income

households, especially in urban areas, and

thus expenditure inequalities are

underestimated if they are measured based

on the SUSENAS data. Secondly, it is

reported that there is a wide discrepancy

between the total household expenditure

estimated based on the SUSENAS data and

the total private consumption expenditure

from the national accounts. Thirdly, it is

said that the survey months covered in the

SUSENAS are different from one survey to

another, and thus care should be taken

when interpreting the SUSENAS time-

series data of consumption expenditure.

Data Basket

• Food (cereals, tubers, fish, meat, eggs

and milk, vegetables, legumes, fruits,

oil and fats, beverage stuffs, spices,

miscellaneous food items, prepared

food and beverages, alcoholic

beverages, tobacco and betel)

• Non-food (Housing and household

facility, goods and service, education

cost, health cost, (clothing, footwear,

and headgear), durable goods, taxes

and insurances, parties and

ceremonies)


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End Notes

1. Also see Kaldor (1956).

2. World Bank’s main report on The East Asian Miracle: Economic Growth and Public Policy (1993) provided a

glowing account of the achievement of the East Asian region arguing that a combination of conservative

macroeconomic policy, export-led growth and investment in human capital had succeeded in triggering nothing

short of an economic miracle in these countries.

3. As Bruno, Ravallion and Squire (1998) point out, the relationship between distribution and growth is anything

but simple, questioning a frequent assumption that countries might face a trade-off between growth and equity.

They write ‘there does not appear to be any intrinsic overall trade off between long-run efficiency and equity. In

particular, policies aimed at facilitating accumulation of productive assets by the poor, when adopted in a relatively

non-distorted framework, are also important instruments for achieving higher growth. The problem should not

be posed as one of choosing between growth and redistribution’ (p. 138).

4. Stability in patterns of economic inequality is not unusual however. As Bruno, Ravallion and Squire (1998) in a

study of inequality in 45 countries point out, inequality rankings across countries remain highly stable over

time. The rank correlation coefficient for gini indices in these countries between the 1960s and 1980s was 0.85.

At the same time around 87 percent of total inequality in these countries was explained by inter-country variations

in inequality and only 6 percent accounted for by in-country differences. Just as significant is the fact that in-


country gini indices showed little variation over time. Only 17 out of 45 countries had a significant trend in gini

indices, either positive or negative, and out of these 12 countries exhibited very small time trends less than

plus/minus 0.4 percent.

Ravaillon (2001) and (2007) argues against taking such averages of the gini coefficients for granted and the

need to examine periods of changes in the gini and the in-country determinants of such shifts in inequality. The

idea that growth is distributional neutral as implied by the constancy of gini across countries with very different

growth patterns does not preclude the need for detailed country level accounts of factors which might account

for a given distribution of income, a sentiment echoed by Kanbur (2004).

5. There is by now a large volume of literature on the impact of initial patterns and extent of inequality on subsequent

growth and poverty reduction. One strand using a political economy approach (Alesina and Perotti, 1993, and

Alesina and Rodrik, 1994, and Alesina, 1998, tends to focus on the link between initial inequality and the political

pressures for redistribution generated by the median voter. This results in increases in capital tax rates which

discourage investment and future growth. The other strand relies on the power of a wealthy elite to obtain

differential treatment through lobbying and, therefore, over investment in assets, e.g. land owned by the elite

(Persson and Tabellini, 1994). The same logic applies in models which focus on the power of lobbies to thwart

the implementation of stabilization reforms which might change the distribution of income. The implication of

such models is, however, that the economic system is caught in an inequality trap in which initial inequalities

in income distribution are perpetuated into the future. This partially explains the stability in gini coefficients in

some economies over time.

The other strand is the impact of asymmetric information on the supply of credit to the poor who are, therefore,

prevented from making productive investments into schooling and health such as to escape from the ranks of

the poor (Bannerji and Newman, 1993).

6. Hill (1991), p. 3.

7. See Mishra (2000) for a comparison between Indonesia’s systemic collapse in the late 1990s and the situation

in former USSR following the fall of the Berlin Wall in 1990.

8. The Atkinson Index is one of the few inequality measures that explicitly incorporate normative judgements about

social welfare (Atkinson 1970). The index is derived by calculating the so-called equity-sensitive average income

(ye), which is defined as that level of per capita income which if enjoyed by everybody would make total welfare

exactly equal to the total welfare generated by the actual income distribution.

9. While less commonly used than the Gini coefficient, the Theil index of inequality has the advantage of being

additive across different subgroups or regions in the country. The Theil index, however, does not have a

straightforward representation and lacks the appealing interpretation of the Gini coefficient. The Theil index is

part of a larger family of measures referred to as the General Entropy class.

10. Changes in sample size and coverage are described in Appendix 1.

11. Akita and Lukman (1995), Akita, Lukman and Yamada (1999), Asra (1989,1999, 2000), Booth (1992, 2000),

Booth and Sundrum (1981), Boediono (1990), Alatas and Bourguignon (2005), Sujdana and Mishra (2004),

Alisjahbana (2001), Dhanani and Islam (2000), Hughes and Islam (1981), Kadarmanto and Kamiya (20040,

Ravaillon and Huppi (1991), Resososudarmo and Vidyatama (2006), Skoufias, Suryahadi and Sumarto (2000),

Suryahadi and Sumarto (2003), Suryahadi, Sumarto and Pritchett (2003), Suryadarma et al. (2005, 2006),

Tjiptoherijanto and Remi (2001), Uppal and Handoko (1986), Yoneda (1985) and Yusuf (2007), Frankema and

Marks (2007).

12. Anne Booth (1992) writes, ‘A serious criticism of the consumer expenditure survey data is that they consistently

show a lower rate of growth in the 1970s for Indonesia as a whole than the household consumption component

of the national income accounts. This is widely considered to be due to progressively greater understatement

of non-food expenditures by wealthier households, especially in urban areas (p. 330).

13. For a much quoted comparison between Indonesia and Nigeria see Bevan et al. (1999).

Documents

Indonesia- trends in income