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Africa in Asia? the developmentchallenges facing Eastern Indonesia andEast TimorAnne BoothPublished online: 23 Jan 2007.

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Oxford Development Studies, Vol. 32, No. 1, March 2004

Africa in Asia? The Development Challenges Facing

Eastern Indonesia and East Timor

ANNE BOOTH*

ABSTRACT In recent years a distinction has been made in the development literature between“Asian” poverty, which is thought to be the result of high rural population densities and highrates of landlessness, and “African” poverty, which is more the result of sparse populationsfarming poor quality land and cut off by inadequate infrastructure from markets for goods,labour and credit. This paper pursues this distinction in the context of Indonesia and points outthat in recent years the highest incidence of poverty has been found not in the densely settledislands of Java and Bali, but in the more remote and less populated provinces in the easternpart of the archipelago. This paper explores the correlates of poverty by province in Indonesiain 1996 and finds support for the view that the poorest provinces are those characterized by lowpopulation densities, undeveloped markets, low road densities and low educational attainment.The policy implications of these findings are examined in the final part of the paper.

1. Asian Versus African Poverty?

Several recent analyses of the economic problems of sub-Saharan Africa have drawn adistinction between “Asian” and “African” poverty. Ellis (1998, p. 10) described thedifference in these terms:

Whereas in Asia, a prevalent feature of rural poverty is near or actuallandlessness so that poor households must rely on off-farm and non-farmincome sources for survival, in Africa the main factors contributing to ruralpoverty are locational and reflect not so much lack of access to land butlocation-specific lack of access to an array of services and opportunities (roads,schools, market services, input supplies, power, non-farm activities), as well asenvironmental constraints.

In making this distinction, Ellis drew on the work of Heyer (1996, p. 284), who arguedthat both rich and poor in many parts of rural Africa “have access to land and engagein own-account farming, in non-agricultural activities and in migration to seek work”.The problem for the poor is that they “do less well in all of these activities”. One reasonwhy they do less well is that they live in scattered communities with little or no accessto roads, credit, irrigation networks or education. Platteau (1996) has stressed theconsequences of inadequate road infrastructure for the development of market net-works in many parts of sub-Saharan Africa, and has suggested that this tends to

*Anne Booth, Department of Economics, School of Oriental and African Studies, Thornhaugh St, RussellSquare, London WCIH OXG, UK.

ISSN 1360-0818 print/ISSN 1469-9966 online/04/010019-17 2004 International Development Centre, OxfordDOI: 10.1080/1360081042000184101

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20 A. Booth

impoverish whole regions. The combination of “sparse populations and deficientcommunication facilities cause rural factor markets to be ill-integrated, highly imper-fect, or altogether missing” in much of Africa (Platteau & Hayami, 1998, p. 373). Thisis in contrast to much of Asia where product and factor markets are better developedand poverty is more often due to lack of access to land or to regular employment.

More ambitiously, Bloom and Sachs have emphasized the importance of locationalor geographic factors in explaining the poor growth performance and the persistence ofmass poverty in much of sub-Saharan Africa, “not only over the past three decades, butfor the entire period of modern economic growth” (Bloom & Sachs, 1998, p. 270).They stress the vital importance of tropical geography, demography and public healthin impeding growth in much of the African continent. Low population densities, theisolation of many communities from roads and markets, technologically underdevel-oped agricultural systems and high rates of natural increase, together with a highincidence of debilitating diseases such as malaria and, more recently, AIDS, have allinteracted with one another to keep a large proportion of the population of sub-SaharanAfrica in poverty. Controversially, Bloom and Sachs argue that it is these essentiallynon-economic factors, rather than policy errors, which have been the main cause ofAfrica’s poor economic performance.

Another recent comparison of agriculture and economic development in Asia andsub-Saharan Africa has emphasized not just the differences in population density andinfrastructural endowments, but also differences in “the prevailing relations of pro-duction, namely the patterns of ownership and control of land and other productiveassets, and organisation of labour” (Karshenas, 2001, p. 323). According to thisanalysis, in many parts of Asia, the rural poor are largely or entirely dependent on wagelabour for their income, and wages rates, both in agriculture and in other sectors of theeconomy, are well below the average product of labour. (This was, of course, the basisof the surplus labour models of economic development associated with Lewis and withFei and Ranis.) Thus, in much of Asia where wages have historically been low,labour-intensive technologies have emerged not just in agriculture but in other sectorsof the economy as well. By contrast, in Africa relative land abundance led to a highreservation wage in agriculture, and encouraged the adoption of more capital-intensivetechniques in other sectors of the economy. Thus, in Africa the ratio of value added perworker in agriculture to value added per worker in the rest of the economy has beenmuch lower than in Asia, although the gap has been reduced since the 1960s(Karshenas, 2001, Table 2).

Broadly speaking, the characteristics of the “African” stereotype, as depicted in thisliterature, can be grouped under eight headings:

(1) High rates of population growth leading to a high proportion (as high as 40%) of thepopulation under the age of 15, and a correspondingly lower proportion in the primeworking age groups.

(2) Rapid growth of the agricultural labour force and a high proportion of the labour forcedependent on agriculture for its primary source of income; agricultural employmentcharacterized by a high degree of seasonality, with little off-farm employment available inthe slack periods.

(3) Technologically backward agriculture, characterized by low yields per unit of land, andlow output per worker in agriculture compared with non-agricultural sectors of theeconomy.

(4) A low incidence of “landlessness” in the sense that most of the rural population can access

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Africa in Asia? 21

land, often under some form of customary tenure, and only a very small proportion of theagricultural labour force is dependent on wage labour for most of its income.

(5) Few off-farm or non-farm sources of income available to agricultural households, with theresult that a high proportion of total farm household income comes from cultivation of thefarm holding.

(6) Poor land and sea transport infrastructure, leading to poorly developed marketing net-works, which makes marketing of farm output impossible or uneconomic.

(7) Poorly developed and highly fragmented markets for labour, land and capital, with theresult that wages, interest rates and land rentals may be much higher in the relatively poorand isolated regions than in more densely settled regions or countries with better integratedmarkets.

(8) A generally low level of human development characterized by low levels of educationalattainment and a high incidence of debilitating diseases, leading in turn to high levels ofmortality especially for infants and children.

This paper suggests that the recent literature on the causes of African poverty hasresonance for Indonesia, and possibly for other parts of the Asia-Pacific region as well.It will be argued that, in spite of several decades of rapid growth at the national level,by the mid-1990s several provinces in Eastern Indonesia still had headcount measuresof poverty that were much higher than the national average. Furthermore, some of thepoorest and most backward regions in Indonesia exhibited a number of economic,geographic and demographic characteristics that had more in common with the“African” stereotype of poverty and underdevelopment than the “Asian” one; but it willalso be argued that the poorest parts of Indonesia are far from uniform, and there areimportant differences, as well as similarities, between them. These differences shouldbe borne in mind in formulating national poverty alleviation strategies.

2. Recent Trends in Poverty in Indonesia and East Timor

Over much of the 20th century, poverty in Indonesia was considered by both colonialand post-colonial governments to be most acute in the densely settled inner islands ofJava, Madura and Bali, although it was acknowledged that poverty was also serious inthe islands to the east of Bali (Lombok, Sumba, Sumbawa and Timor) where theclimate was much drier than in other parts of island Southeast Asia, and agriculturalyields low and erratic. Broadly speaking, poverty in Indonesia was thought to be theresult of “too many people and not enough land”, together with a dearth of bothagricultural and non-agricultural wage labour opportunities for those willing and ableto work (Penny & Singarimbun, 1973, pp. 6–28). Data from the Household Incomeand Expenditure surveys, carried out as part of the National Socioeconomic Survey(SUSENAS) from the mid-1960s onwards, appeared to confirm this view, althoughuntil 1993 the samples were too small to estimate poverty accurately in the smallerprovinces outside Java; but aggregate estimates of poverty for the “outer islands” as awhole did suggest that in rural areas the headcount measure of poverty was lower thanin Java (Sundrum & Booth, 1980, Table 7).

After 1990, the sample size of the SUSENAS was enlarged, and estimates of theheadcount measure of poverty at the provincial level were made by the Central Bureauof Statistics (CBS). According to the estimates published in 1999, the headcountmeasure of poverty was highest in East Timor in both 1993 and 1996, followed by WestKalimantan, Maluku and Irian Jaya (Central Board of Statistics, 1999, Table 12.5).The revised headcount estimates for 1996, published in 2000 (which were based on

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22 A. Booth

Table 1. Percentage and numbers of the population below the official poverty lines,1996 and 1999: poorest six provinces and Java/Bali

1996(1) 1996(2) 1999

% Number ( � 1000) % Number ( � 1000) % Number (1000)

Poorest sixMaluku 19.5 417.0 44.6 934.7 46.1 1013.9Irian Jaya 21.2 427.8 42.3 830.3 54.8 1148.5East Timor 31.2 267.8 41.8 352.5 n.a. n.a.NTT 20.6 749.0 38.9 1395.1 46.7 179.0NTB 17.6 653.0 32.0 1169.3 33.0 1276.8Southeast 8.5 139.4 29.2 466.4 29.5 504.9Sulawesi

Java/BaliEast Java 11.9 4046.5 22.1 7503.3 29.5 10 286.4Central Java 13.9 4157.3 21.6 6417.6 28.5 8755.4Yogyakarta 10.4 303.8 18.4 537.8 26.1 789.1West Java 9.9 3962.1 11.1 4358.8 19.8 8393.4Bali 4.3 125.6 7.8 227.0 8.5 257.8Jakarta 2.5 231.3 2.4 215.8 4.0 379.6

Indonesia 11.3 22 500.0 17.7 34 516.6 23.4 47 974.7

Note: The first set of estimates for 1996 is based on the old poverty lines, which were estimated using amethodology comparable with that used for the 1993 estimates. The second set of estimates for 1996 is basedon the new poverty lines, which were estimated using a rather more generous basket of basic needs (especiallynon-food basic needs), and were thus higher, leading to a higher headcount measure of poverty. n.a., notavailable.Sources: Central Board of Statistics (1999), Table 12.5, Central Board of Statistics (2001), Table 12.5.

revised poverty line estimates), indicated that Irian Jaya and Maluku had the highestheadcount measures of poverty, followed by East Timor, East and West Nusatenggara,and Southeast Sulawesi.1 The CBS poverty estimates made it plain that poverty wasmore acute in Eastern Indonesia than in other parts of the archipelago in the mid-1990s. This was also the case in 1999, although estimates for East Timor were notpublished for that year. In 1999 the headcount measure of poverty increased every-where in the country as a result of the financial crisis and the subsequent contractionof GDP, but in spite of a sharp increase in the headcount measure in Java, the incidenceof poverty was still higher in Irian Jaya, Maluku, and in East and West Nusatenggarathan in any province of Java (Table 1).

As may be expected, the share of GDP accruing to the poorest six provinces inIndonesia in 1996 was much less than their share of the population. The poorest sixprovinces were also characterized by a low endowment of sealed and gravel roads perunit of area compared with the national average. The labour force was much less welleducated than in most other parts of the country. Especially striking was the very lowpercentage of the labour force working as “employees” in the poorest six provinces,suggesting that labour markets were relatively undeveloped (Table 2). This indicatesthat some of the main features of the “African” stereotype characterized all theseprovinces, which is explored further in the next section of the paper, which examinesthe correlates of poverty by province. But the poorest six provinces were by no meansuniform in some important aspects of their economic structure. In particular, there wasconsiderable variation in the ratio of agricultural value added per worker to non-agricul-

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Africa in Asia? 23

Table 2. Poverty incidence and other indicators 1995/96

Percentage ofthe employedlabour forcewith less thanHeadcount Employees asPercentage Roads (100

km per km2)poverty (%) breakdown of completeda % of labour(1996)a primary (1996)force (1995)GDP (1996)(1996)Region

Poorest sixb 37.5 4.3 5.7 19.8 40.9Sulawesic 17.9 3.8 19.0 26.1 30.2Java/Bali 16.3 61.8 68.0 41.7 28.0Sumatra 15.5 21.2 16.0 27.6 25.6Kalimantan 15.0 8.8 4.1 26.3 34.1

Indonesia 17.7 100.0 13.1 35.6 28.9

aAsphalt and gravel roads only.bSee Table 1 for details of the poorest six provinces.cExcluding Southeast Sulawesi.Source: Poverty data from Central Board of Statistics (2001), Table 12.5; GDP data from Central Board ofStatistics (2000a), Table 1; road data from Central Bureau of Statistics (1997b), Table 8.1.5B; labour forcedata from Central Bureau of Statistics (1996a) and Central Bureau of Statistics (1997a).

tural value added per worker (the “V” ratio), and also in average earnings of wages andsalary earners, relative to the national average. Irian Jaya (now Papua) and East Timorin particular had very low “V” ratios relative to the national average, while the otherfour provinces had higher ratios than the national average (Table 3). Irian Jaya and EastTimor also had much higher average wage and salary earnings than the nationalaverage. I explore the reasons for these disparities in more detail below.

3. Correlates of Poverty by Province

Table 4 reports estimates of correlations of the headcount measure of poverty byprovince (urban and rural areas) in 1996 with a range of demographic and othervariables. The estimates have been made both for Indonesia as a whole and for theouter islands (i.e. excluding the five provinces in Java, and Bali). Looking first at thedemographic variables, there appears to be little correlation between population growthand poverty, either for the country as a whole or for the outer islands. This probablyreflects the high out-migration from some of the poorer provinces of Eastern Indonesiato Java and Sumatra and, increasingly, over the 1980s and 1990s, abroad. But therewere significant positive correlations between poverty and the proportion of the popu-lation under 15, and with infant mortality rates. These suggest a tendency for thepoorer regions to have higher dependency ratios, and also less access to primary healthfacilities.2 There was a negative correlation between poverty and population densities,which lends support to the argument that poverty in Indonesia was, by the mid-1990s,no longer exclusively associated with intense demographic pressures on finite suppliesof land.

There was also a significant negative correlation in 1996 between the percentage ofchildren aged seven to 15 in school and poverty, and a positive correlation betweenpoverty and the proportion of the labour force with less than primary education. Thisis to be expected but it does raise a question of causation: does poverty force families

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Table 3. Comparative labour productivity (“V” ratios) and average monthly earnings,1996

Average monthly earnings 1996b

Headcount measure of poverty “V” Ratioa (Rp.)

Mining fourc

Riau (54.7) 12.6 6.7 257,005Irian Jaya (53.4) 42.3 8.1 378,320East Kalimantan (31.7) 9.7 15.5 355,486Aceh (25.6) 12.7 20.0 263,584

Poorest sixMaluku 44.6 24.5 250,686Irian Jaya 42.3 8.1 378,320Timor Timur 41.8 10.1 336,544East Nusatenggara 38.9 29.8 212,052West Nusatenggara 32.0 56.8 163,460Southeast Sulawesi 29.2 37.1 272,821

Indonesia 17.7 23.1 207,108

aRatio of average value added per worker in agriculture to average value added per worker in the non-agricul-tural sectors of the economy.bAverage monthly earnings per employee (wage and salary workers only) as reported in the 1996 Labour ForceSurvey.cFigures in parentheses show value added in the mining sector as a proportion of total GDP.Sources: Central Bureau of Statistics (1997a) and (1997d), Table 2.1; Central Board of Statistics (2000a) and(2001), Table 12.5.

to take children out of school at an early age or do low levels of educational attainmentlead to greater poverty? I return to this issue below. There was a significant negativecorrelation between the proportion of the labour force working as employees and theheadcount measure of poverty, both for the country as a whole and for the provincesoutside Java/Bali, which indicates that poverty was, by the 1990s, not concentrated inthose regions where a high proportion of the labour force was working as wagelabourers. Although average monthly earnings of wage and salary workers were nega-tively correlated with poverty, the correlation was low and insignificant.

The significant degree of negative correlation shown in Table 4 between per capitaGDP and per capita consumption expenditure and the headcount measure of povertyis to be expected, although not all poor provinces in 1996 had low per capita GDPrelative to the national average. In particular, the province of Irian Jaya (now calledPapua) stands out. In 1996, it had the second highest headcount measure of poverty inthe country, and in 1999 the highest (Table 1). Yet, in both years, per capita GDP inthe province was much higher than the national average; indeed, it was the fourthhighest in the country after the oil-rich provinces of Riau and East Kalimantan and thenational capital, Jakarta (Central Board of Statistics, 2000b, Table 5). Irian Jaya’s highper capita GDP was due to the large mining sector, which contributed over half of totalGDP in the mid-1990s (Table 3). Yet the other provinces with large mining sectors allhad lower than average head count measures of poverty. I explore the reasons for thisanomaly in more detail later in the paper.

The headcount measure of rural poverty in 1996 was positively correlated with thepercentage of the rural labour force working in agriculture and negatively correlatedwith per capita consumption expenditure in rural areas, and with value added in

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Table 4. Correlates of the headcount measure of poverty by province1996

All Indonesia Excluding Java/Bali

Demographic variablesPopulation growth (1990–95) 0.008* � 0.078*Percentage of thepopulation under 15 (1995) 0.591 0.603Infant mortality rates (1996) 0.471 0.287*Population densities (1995) � 0.497 � 0.122*

Education/labour force variablesPercentage of children 7–15 yearsold in school (1995) � 0.539 � 0.538Percentage of the total labour forcenot completed primary school(1996) 0.683 0.463Percentage of labour force workingas employees (1996) � 0.696 � 0.597Average monthly earnings peremployee, 1996 � 0.153* 0.089*

Income/expenditure dataGDP per capita 1996 � 0.671 � 0.56Per capita consumptionexpenditures (1996) � 0.895 � 0.811Gini coefficients of per capitaconsumption expenditures � 0.049* 0.345*

InfrastructureRoad density � 0.483 � 0.049*

*Not significant at 5%.Note: The correlation coefficients (in logs) were estimated for 27 provinces (21 excludingJava and Bali). The minimum value of r which is significant at 5% confidence level for25 degrees of freedom is 0.381; for 20 degrees of freedom it is 0.423.Sources: Demographic data: Central Bureau of Statistics (1998a), Central Board ofStatistics (1999, 2001). Education and labour force data: Central Bureau of Statistics(1996a, 1997a, d). GDP and household expenditure data: Central Bureau of Statistics(1997c), Central Board of Statistics (2000a, b). Road data: Central Bureau of Statistics(1997b).

smallholder agriculture per hectare of arable land (Table 5). These results are again tobe expected; but perhaps more surprising is the lack of any strong correlation betweenrural poverty and the “V” ratio. Neither does there seem to be any strong associationbetween rural poverty and agricultural wages.3 This confirms the point that is alreadyclear from Table 3, that there are considerable differences between the poorest provincesin Indonesia in terms of both relative productivity in the agricultural and non-agricul-tural sectors, and agricultural wage rates.

There was a significant positive correlation between the headcount measure of ruralpoverty and the proportion of the labour force in agriculture, which is to be expected.Less predictable is the significant negative correlation between the proportion of theagricultural labour force working as employees and the headcount measure of ruralpoverty, indicating that rural poverty tends to be higher in those provinces where thereare low levels of landlessness, as proxied by the proportion of the agricultural labour

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Table 5. Correlates of the headcount measure of rural poverty byprovince 1996

All Indonesia(excluding Excluding

Jakarta) Java/Bali

Education/labour force variables

Percentage of the rural labour forcewho have not completed primaryschool (1996) 0.304* 0.337*Percentage of the employed labourforce working in agriculture (1996) 0.556 0.587Percentage of the agricultural labourforce working as employees (1995) � 0.559 � 0.622Growth in agricultural labour force(1990–95) 0.356* 0.439

Income/expenditure dataPer capita consumptionexpenditures (rural) (1996) � 0.825 � 0.786Percentage of total farm householdincome from farm holding (1993) 0.35* 0.23*“V” ratio (1996) � 0.253** � 0.194*

Agricultural dataArea per farm holding (1993) 0.138* � 0.047*Value added per hectare (1993) � 0.408 � 0.331*Percentage of corn producersnot marketing output (1993) 0.335* 0.501Harvesting wages � 0.261*

Ploughing wages � 0.402*

InfrastructureRoad density � 0.339* � 0.232*

*Not significant at 5%.Note: The correlation coefficients (in logs) were estimated for 27 provinces (21 excludingJava and Bali). The minimum value of r which is significant at 5% confidence level for25 degrees of freedom is 0.381; for 20 degrees of freedom it is 0.423. In the case ofharvesting and ploughing, wages data were only available for 14 provinces (four on Javaand 10 outside Java).Source: Central Bureau of Statistics (1995a, b, 1996a, 1997a, b, 1998b).

force working as employees. Thus, the negative correlation suggests that poverty tendsto be worse in those parts of the country where landlessness is lower; but this does notimply that landlessness is not an important determinant of rural poverty within the moredensely settled provinces of Java, Bali and Sumatra. There is much evidence to suggestthat it is (Breman & Wiradi, 2002, pp. 7–11 and passim).

It is also noteworthy that outside Java there is a significant positive correlationbetween the headcount measure of rural poverty and the proportion of agriculturalhouseholds growing corn, but not marketing it (Table 5). Corn is an important foodcrop in much of Eastern Indonesia where it is grown largely for home consumption,while in other parts of the outer islands, with better infrastructure and higher household

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Table 6. Agricultural and labour force indicators, and per capita GDP, 1996: poorestsix provinces and Indonesian averagea

Province Agriculturaloutput per

Land area peragriculturalagricultural Services LF/ Labourers/workerb

TNALF(%) ALF(%)ALF/TLF (%)worker (ha)(Rp. million)

Maluku 1.923 0.88 59.0 76.8 4.3Irian Jaya 2.288 7.28c 73.1 81.7 1.6East Timor 0.951 1.01 75.9 74.7 0.6NTT 1.113 1.24 67.4 51.9 1.1NTB 1.715 0.62 50.1 67.5 15.1SoutheastSulawesi 1.899 2.75 54.9 76.2 3.8

Indonesia 2.206 1.27 44.0 66.2 14.0

aALF: Agricultural labour force; TLF: Total labour force; TNALF; Total non-agricultural labour force.Services labour force excludes financial services.bValue added from the agricultural sector including large estates, forestry and fishery.cThis is probably an overestimate.Sources: Agricultural land: Central Bureau of Statistics (1997b), Table 5.1.1, with additional data fromKORPRI (1996), Maluku (1998) and Irian Jaya (1998). Labour force data from Central Bureau of Statistics(1996a 1997a). Agricultural output data from Central Board of Statistics (2000a).

incomes, many corn-growing households market at least part of their crop. Yields perhectare were also much higher in these more affluent provinces, the result of morewidespread use of new varieties and fertilizer. In the two main corn-growing provincesof Sumatra at the end of the 20th century, North Sumatra and Lampung, yields werehigher than in Java, while in East Nusatenggara, the main corn-growing province inEastern Indonesia, yields were only about 75% of those in Java.4

4. The Relationship Between Average Holding Size, Land Productivity, Off-

farm Income and Rural Poverty

While there is a significant degree of positive correlation between value added perhectare in smallholder agriculture and rural poverty, the estimates in Table 5 suggestthat there is little correlation between land area per agricultural household by provinceand poverty. Indeed, as can be seen from Table 6, land area per agricultural workervaried considerably within the six poorest provinces in 1996. In Irian Jaya it was muchhigher than the average for Indonesia as a whole, although the land data for thisprovince, and for some other parts of Eastern Indonesia, are far from reliable.5 Butclearly the evidence does not support the view that the provinces in Indonesia with thehighest headcount incidence of poverty are all “land-poor”. Of the six poorestprovinces, only West Nusatenggara (NTB) conforms to the land-poor stereotype.

The problem in most of the other poor provinces in Eastern Indonesia is lowagricultural productivity which, combined with poor infrastructure and inadequatemarketing facilities, has led to low farm household incomes compared with the nationalaverage (Table 7). Particularly striking are the low earnings per agricultural householdfrom non-agricultural wage earnings and other non-agricultural activities. This indi-cates that the poorest provinces in rural Indonesia are those where a high proportion ofthe labour force are dependent on agriculture as the primary source of household

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Table 7. Sources of farm household income, 1993 (Rp. � 1000)

Non-agriculturala

Agriculture holdingb Off-holding agriculturea Wages, etc. Other Total

Maluku 888 (52.6) 89 325 385 1687Irian Jaya 1042 (63.0) 82 271 258 1653East Timor 910 (63.3) 55 263 210 1438NTT 963 (61.2) 56 273 281 1573NTB 821 (52.0) 134 346 277 1578Southeast Sulawesi 1167 (59.1) 86 421 301 1975Indonesia 880 (50.0) 189 458 233 1760

aOff-holding agriculture refers to sources including agricultural labour, and other activities in the agriculturalsector. Non-agricultural income is broken down into wage income and income from self-employment inmanufacturing, trade, transport, etc. “Other” non-agricultural income includes pensions and other transfers(net) minus consumption taxes. For further details see the source document.bFigures in parentheses refer to income from the agricultural holding as a percentage of total farm householdincomes.Source: Central Bureau of Statistics (1995b), Tables 1–5.

income, but where agricultural productivity is low, and not compensated for either bylarger holding sizes or substantial off-farm sources of income.6

5. The Relationship Between Relative Labour Productivity, Wage Earnings,

Education and Poverty

It is clear from Table 3 that ratios of agricultural labour productivity to non-agriculturallabour productivity vary widely among the poorest six provinces in Indonesia, as doaverage earnings accruing to wage and salary workers. Two provinces (Irian Jaya andEast Timor) had relative productivity ratios that were well below the average for thewhole country, and indeed below the average for Africa after the 1970s (Karshenas,2001, Table 2). The most obvious reason for these variations in the two provinces is thepresence of the large mining sector in Irian Jaya and an unusually large establishmentof both military and civilian government officials in both provinces.7 This was also thereason for the very high average wage and salary earnings in both provinces, and for thehigh degree of inequality in consumption expenditures, compared with the nationalaverage (Tables 3 and 8). But the great majority of the population in both provinces inthe mid-1990s remained poorly educated and could not access the highly paid jobs inmining and in public administration. With little demand for unskilled wage workers,either in agriculture or elsewhere in the economy, they were trapped in unproductiveself-employment in subsistence agriculture. Thus, the low levels of education prevailingin these two provinces can be seen as one reason for the continuing high levels ofpoverty. In addition, there is considerable evidence from many parts of Indonesia thatlow household income is an important reason for children dropping out of theeducation system after, or even before, the completion of the 6-year primary cycle(Booth, 2000, pp. 93–96). Even where household income might permit a child to stayin school, parents in remote rural areas probably see little point in spending money onfurther education when wage employment opportunities are so restricted. Thus, avicious circle of poverty and low levels of education is established that is very hard tobreak.

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Table 8. Per capita GDP and per capita consumption expenditures byprovince and Gini coefficients of consumption expenditures, 1996

Per capita Per capita consumption GiniGDP expenditure (PCCE) coefficient

(Rp. � 1000) (PCCE)(Rp. � 1000)

Poorest provincesMaluku 1721 644 0.269Irian Jaya 4174 731 0.386East Timor 1011 597 0.363East Nusatenggara 920 497 0.296West Nusatenggara 1081 567 0.286Southeast Sulawesi 1302 627 0.311

Java/BaliEast Java 2249 690 0.311Central Java 1758 661 0.291Yogyakarta 2179 907 0.353West Java 2251 1005 0.356Bali 2954 996 0.309Jakarta 8976 1983 0.363

Indonesia 2606 840 0.355

Source: Central Board of Statistics (2000a), Table 5, 2000b, pp. 24–27.

In the other four poor provinces, relative productivity disparities (“V” ratios) werehigher than the national average, and disparities in household expenditures were not aspronounced (Table 3). In West Nusatenggara, where land availability per agriculturalworker is low and wage and salary earnings are also well below the national average,there can be little doubt that poverty is due to the classic “Asian” causes: too manypeople and not enough land or employment for them. Unsurprisingly, West Nusateng-gara has been characterized by high rates of out-migration in recent decades, to otherparts of Indonesia and abroad (Central Bureau of Statistics, 1994, Table 3.10).

6. The Relationship Between GDP, Consumption Expenditures, Inequality and

Poverty

There are other aspects to the poverty problem in Eastern Indonesia that are not fullycaptured by the indicators already discussed. Although most of the poor provinceslisted in Table 1 are also characterized by lower than average per capita GDP, there isone startling exception (Table 8). As has already been noted, in 1996 per capita GDPin the province of Irian Jaya was well above the national average, as it was in the otherthree provinces where mining accounted for over 25% of provincial GDP. What thenexplains the very high headcount measure of poverty in that province, not justcompared with the other mining provinces but also with the national average? In thepast analysts have pointed to the very large export surplus in the province, indicatinga substantial “drain” of natural resource wealth to the centre (see, e.g. Booth, 1996,p. 118); but between 1993 and 1997, the export surplus was much reduced, and insome years negative (Booth, 2003, p. 192).

The high incidence of poverty in 1996 was due to the fact that most of thepopulation of the province was engaged in unproductive agricultural work, with littleaccess to employment in other parts of the economy. The highly segmented nature of

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30 A. Booth

the regional economy is reflected in the aggregate expenditure data from the regionalincome accounts. In the 1990s, a high proportion of regional GDP was devoted toinvestment expenditures and a correspondingly low share to private consumptionexpenditures; but the investment mainly went into the mining sector and associatedinfrastructure, which generated little employment and had little impact on the rest ofthe provincial economy. This, in turn, has led to low average per capita consumptionexpenditures in comparison with most other provinces and with the national average,and high inequalities in per capita consumption expenditures, resulting in poverty forthe many and relative affluence for the few (Table 8).

7. Policy Responses

Indonesia, like most other developing countries, has in recent years been underenormous pressure from aid donors to prepare a national poverty alleviation strategy.The evidence reviewed in this paper makes it clear that there can be no one-size-fits-all“national” strategy in Indonesia because the nature of poverty in Indonesia varies somuch by region. The evidence in Table 1 makes it clear that even before the crisis of1997/98, there were still many millions of people below the official poverty line in Java.In most cases their poverty would have been the result of lack of access to land,combined with low levels of education and skills which would have made it difficultfor them to gain access to regular non-agricultural employment (Breman &Wiradi, 2002, pp. 7–12). In addition, Java and Bali have experienced the most rapidfertility declines in recent years, and so their populations will age most rapidly incoming decades. Poverty among the elderly and infirm already appears to be a seriousproblem in Java and is likely to worsen in coming years. But in other parts of thearchipelago, the continuing high levels of poverty have different causes. What thenneeds to be done?

The continued high levels of poverty that still prevailed in Eastern Indonesia in the1990s, after three decades of rapid growth at the national level, would seem to lendsupport to those economists who see adverse geography as a key reason for continuingpoverty and underdevelopment in many parts of the developing world. Unlike WesternChina, or many countries in Africa, Eastern Indonesia is not landlocked, but cut offfrom the more densely settled islands of Java, Bali and Sumatra by sea. Over much ofthe 20th century, most exports have originated from Western Indonesia, especially fromJava and Sumatra, and infrastructure development, including the development ofmodern port facilities, has been concentrated on these two islands. Thus, it was notsurprising that Western Indonesia benefited more from the growth in agriculture,manufacturing and the modern service sector that occurred in the three decades fromthe late 1960s to the late 1990s. The important policy reforms of the Soeharto era werenational reforms, but geographical remoteness prevented much of Eastern Indonesiafrom benefiting from them.

Sachs (2003, p. 40) has recently argued that “in the short term, only three alterna-tives may exist for an isolated region”. The first is continued impoverishment, thesecond is migration of the population to more dynamic regions and the third is“sufficient foreign assistance to build the infrastructure needed to link the regionprofitably with world markets”. In fact, the assistance does not have to be foreign, if thenational government has the resources and the will to invest in infrastructure andhuman resource development in the lagging regions. Of course it could be argued thatif the lagging regions have little or no economic potential, then encouraging populations

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to move out is the most efficient solution, although there is much international evidencethat the relocation of large populations is costly and can lead to ethnic and religioustensions.8

In the final years of the Soeharto era there was much discussion in policy circles inIndonesia about poverty in Eastern Indonesia and the region’s apparent failure tobenefit from the rapid economic growth and structural change that was transformingJava, Bali and Sumatra. This discussion was triggered by the presidential budget speechof January 1990, which stressed the importance of developing the eastern part of thearchipelago, and marked an important turning point in post-independence thinkingabout the nature of the Indonesian economy and polity. As Chauvel (1996, p. 61)argued, the great achievements of Soeharto’s “New Order” were to impose strongcentral control over all of Indonesia’s vast territory and to use that central control toimplement ambitious programmes of economic and social development. But after morethan two decades of such development, in 1990 Soeharto appeared to be concedingthat regional development disparities were emerging that could indeed threaten theunity of the nation.

The preoccupation with Eastern Indonesia over the 1990s has been criticizedbecause it shifted the focus of the debate over poverty policies away from Java and Bali,although the official data (not to mention many studies carried out by academics andnon-governmental organizations (NGOs)) made it clear that there were still manymillions of poor people in Java, Bali and Sumatra who had not benefited much, if at all,from three decades of rapid growth. Perhaps the official emphasis on Eastern Indonesiawas deliberately intended to distract attention from the problems in Java, but it did leadto a significant shift in the distribution of regional development grants from the centralgovernment towards the poorest provinces in Eastern Indonesia (Azis, 1996; Booth,1996, 2003). How this money was spent remains a contentious issue, but it seems thattransport infrastructure, education and health facilities did improve in the six provinceswhich had the highest headcount measure of poverty in 1996.9 Even so, as this paperhas argued, there was still a significant development gap between these provinces andmuch of the rest of the country in the mid-1990s (Table 2).

Since the severe economic crisis of 1997–99 and the demise of Soeharto, Indonesianpolicy-makers have faced a new and even more complex set of problems in formulatingpoverty policies. As a result of the crisis, the headcount measure of poverty and thenumbers below the official poverty line have grown considerably (Table 1). Theincrease in numbers of poor has been greatest in Java, especially in the province of WestJava.10 This increase has in turn triggered a new debate over appropriate “social safetynets” to prevent vulnerable families from falling into poverty as a result of sudden,sharp reductions in household earnings. This new attention to problems of vulnerabilityin the more industrialized parts of the country is no doubt desirable and a corrective tothe prevailing attitude in the latter part of the Soeharto era, when official povertydiscussions were very much preoccupied with Eastern Indonesia and official rhetorictended to suggest that the poverty problem in other parts of the country was beingsuccessfully tackled by government development programmes. But the problems of thepoor and remote regions of Eastern Indonesia remain serious, as the headcountestimates of poverty in 1999 make clear. In the much more open and liberal atmos-phere that has prevailed since May 1998, politicians, journalists, academics, studentsand an array of NGO activists all feel more empowered to criticize what is perceived ascentral government exploitation of the regions. In the oil- and gas-rich provinces inparticular, the sense of grievance increased to the point where there is considerablesupport for secession. This is certainly the case in Papua. Elsewhere in the country,

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demands have grown for greater government transparency and accountability at alllevels.

During his brief period as president, B. J. Habibie reacted to these demands byembarking on an ambitious programme of decentralization which was intended todevolve responsibilities for many economic and social development programmes to theprovinces and to sub-provincial levels of government. The legislation ushering in thisnew era of decentralization in Indonesia (Laws 22 and 25, May 1999) and thesubsequent spate of government regulations have already given rise to a considerableliterature which is set to increase as the ambitious decentralization programme gathersmomentum. While most observers have welcomed the attempt to move away from thehighly centralized system that characterized the Soeharto era, the poorer and moreremote provinces have expressed concerns that the decentralization process, whiledevolving many additional development responsibilities to provinces and districts, willdeprive them of the central government grants that they need to carry out their newresponsibilities.

Although the first round of funding allocations announced in late 2000 appeared toallay these fears, there can be little doubt that the decentralization process has increaseduncertainty about central government development subsidies in those poor and smallprovinces that have little scope for increasing own-revenue collections in the short ormedium term.11 In Eastern Indonesia, only Papua will benefit from the new revenue-sharing rules applying to the exploitation of natural resources. While decentralizationwill give the other provinces and sub-provincial governments more autonomy to planand implement development programmes, such autonomy will be of little value if theyhave less money to spend.

One former province in Eastern Indonesia will not have to worry about theimplications of the decentralization process as it successfully broke away from Indone-sia and, after a period of rule by the United Nations, achieved independence as asovereign state in 2002; but East Timor’s problems of poverty and geographic isolationhave hardly been solved by political independence. Its leaders hope that a combinationof international aid and the revenues from the exploitation of the country’s offshore oiland gas reserves will fund its development needs in the immediate future and over thelonger term (Gusmao, 2001). These needs will be substantial, given the levels ofpoverty that prevailed prior to 1999 and the destruction that occurred in the latter partof that year. If the new nation of Timor Lorosae is successful in using both internationalaid and its own natural resource revenue to promote rapid and equitable developmentin coming decades, its example will certainly serve to increase the already strongpressures for political independence in Papua and perhaps elsewhere in EasternIndonesia as well. If it fails, the failure may persuade neighbouring provinces inIndonesia that they are, after all, better off as part of a larger nation.

Notes

Much of this paper was written while I was a visiting fellow at the Institute of Southeast AsianStudies, Singapore, from January to May 2001. I am grateful to ISEAS for providing a verysupportive research environment, and to the Leverhulme Foundation for their financial assist-ance.1. For discussions of the problems with the official poverty line used by the Central Bureau of

Statistics, see Booth (1993) and Bidani & Ravallion (1993). It is not possible here to give afull account of the debate surrounding the official poverty estimates in Indonesia, or to givea comprehensive explanation of the changes in the estimation of the poverty line that wereintroduced in 1999. Suffice it to say that the changes were made in order to incorporate a

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larger number of goods and services in the poverty line basket of basic needs. This had theeffect of increasing the poverty line, although the magnitude of the increase varied byprovince, thus affecting the relative poverty rankings. Some critics argue that even the revisedestimates still underestimate the extent of poverty in Indonesia, both before and after thecrisis; see Dhanani & Islam (2002).

2. Malaria is much more widespread in Eastern Indonesia than in other parts of thearchipelago, and is a major cause of high infant and child mortality.

3. The correlations reported in Table 5 use data on agricultural wages which are available foronly 14 provinces, but other wage series for 26 provinces (daily wages for production workersbelow the level of foreman) for 1991 show only a weak negative correlation with theheadcount measure of poverty in 1993.

4. See Buletin Ringkas BPS, January 2001, Table 27.5. The CBS does not give data on area of land for Maluku, East Timor and Irian Jaya, although

the 1993 Agricultural Census did give estimates of land under smallholder cultivation forthese provinces. Land data for these three provinces are taken from provincial statisticalyearbooks, and are subject to a large margin of error.

6. The role of average holding size, agricultural productivity per hectare and access to off-farmincome can be seen from the results of an ordinary least squares regression of these variableson the headcount measure of rural poverty. Both value added per hectare in smallholderagriculture and average holding size show the expected negative signs and are highlysignificant. If a third variable, the proportion of total farm income obtained from the farmholding, is added, over 50% of the observed variation in headcount poverty betweenprovinces is explained. For further discussion of the relationship between agriculturalhousehold dependency on income from the farm holding, rural poverty and other demo-graphic and agricultural variables, see Booth (2002), pp. 188–191.

7. In 1995, there were 20.8 civil servants per thousand people in Indonesia as a whole. In EastTimor and Irian Jaya the figures were 32.7 and 36.4, respectively (civilian employees only).Data from Central Bureau of Statistics (1996a, b).

8. Parts of Eastern Indonesia have been plagued by ethnic and religious conflict in the last 5years; in the province of Maluku, which is the worst affected region, in-migration of Moslemsfrom other parts of the country has led to violent clashes with local Christian populations.The problems have been aggravated by the activities of Islamic militias recruited from Java.

9. For a discussion of the improvements in educational and other indicators in East Timor inthe years from 1980 to 1998, see the chapters by Booth and Jones in Hill & Saldanha (2001).

10. The official data show that numbers of poor in West Java increased by over four millionbetween 1996 and 1999. The percentage increase in the numbers of poor between 1996 and1999 (by province, excluding East Timor) was negatively correlated with the headcountmeasure of poverty in 1996 (r � –0.455). See Central Board of Statistics (2001), Table 12.5.

11. See Alm et al. (2001) for a discussion of the prospects for the decentralization process. Lewis(2002) and Booth (2003) look at the impact of the first round of funding allocations,announced in December 2000, on regional equity.

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