Ekonomi dan Keuangan , vol. 37, no. 2, 1989

The Economic and Social Dimensions of Regional Development in Indonesia*^

Hal Hill and Catharina Williams

Ringkasan

Masalah "daerah" selalu merupakan soal penting bagi suatu negara yang tier- corak aneka ragam seperti Indonesia. Maksud tulisan ini memberi gambaran umt rp tentang trend perkembangan ekonomi dan sosial daerah dari tahun 1970-an sampat pertengahan tahun 1980-an, kira-kira dari puncak "boom" minyak pertama sampdi resesi setelah "boom " kedua. Ketimpangan ekonomi dan sosial temyata tidak be. menurut angka-angka indeks yang dipakai dalam analisis ini. Selain itu, meskip secara potensial dampak "boom"minyak dan perkembangan industri modem tidak merata, tidak ada bukti yang menunjukkan bahwa perbedaan antara daejui telah meningkat selama periode ini. Hubungan antara indikator ekonomi dan sosial umumnya lemah, karena itu penting sekali untuk mencari variabel yang cuktp banyak macamnya untuk menilai kemajuan suatu daerah. Terlebih lagi kareic pemerintah semakin mengurangi pengaturan yang amat terpusat, didorong ohh keterbatasan keuangan negara selama masa harga minyak rendah , dm perbaikm infrastruktur dan kemampuan administratif di daerah-daerah.

* This paper is a continuation of work which resulted in a large conference Jh regional economic development in Indonesia, held at the Australian Natio^iaJ University in February 1987, to be published shortly as Hill (ed) (1989). We most grateful to conference participants and paper writers for their insights. Ih^ present paper is based on a data base compiled subsequent to that conference aid book, and it provides essentially a national overview of regional development. I o: detailed provincial surveys see the edited proceedings volume. Note that, owin(; to data limitations, East Timor has been excluded from this paper, and Irian Ja|y

191 HHI and Williams

I. Introduction

The daerah (region) has been a major preoccupation of Indonesian policy makers since Independence. Before 1966 it was manifested in regional insurrection and opposition to rule from . In tbe regime tbe daerah has been tbe focus of central government efforts to accelerate regional development, through vastly increased grants to secondary tiers of government and through its own development expenditures. Successive Repelita underline tbe high priority accorded to tbe goal of regional development. But Indonesia's extraordinary diversity — economic, ecological, demographic, cultural — continues to pose a major challenge to development planners. On tbe one band tbe national motto, , implies a commitment to uniform development, of ensuring that all provinces reach nationally accepted mi• nimum standards of socio-economic development, and that 'exogenous' resource flows from aid and exports are redistributed across the nation. Conversely, this diversity requires a policy environment which encourages tbe evolution of regional comparative advantage, and which facilitates local initiative through decentralisation. For tbe first decade and a half of tbe New Order, tbe government pursued what may be broadly described as a 'centre-oriented, top-down' approach to regional development. Such an approach was understandable in tbe circumstances. Regional administrative and planning machinery was weak. There were massive inflows of resources, first from aid and later from oil, which flowed to and through tbe centre. Physical infra• structure was so run down that only a nationally coordinated strategy could tackle tbe immense backlog. And politically, tbe commitment to a unitary state and to ameliorating regional grievances compelled strong central government intervention. Tbe result was huge increases in develop• ment expenditure and in provincial and kabupaten/kotamadya budgets, in tbe context of centrally-determined priorities and planning. By tbe 1980s Indonesia, perhaps for tbe first time, achieved a genuine measure of internal economic integration, as indicated by vastly increased inter- provincial flows of people and goods, and by reduced inter-provincial price variations. By tbe mid 1980s, however, new challenges in regional policy formulation to this 'centre-driven' strategy bad arisen, for two main reasons. First, tbe government's very success in promoting regional development bad weakened tbe earlier compelling argument for a highly centralised program. Planning and administrative capacity in tbe regions was greatly improved, and national infrastructure was so much better that resources could be moved quickly — whether in tbe form of rice to

192 The Economic and Social Dimensions meet sudden and unexpected local shortfalls, or teachers to alleviate gap;; in the education delivery system. Secondly, the drastic fall in oil pricei in the mid 1980s meant that Jakarta was no longer able to sustain its massive development program and its generous grants to lower-level governments. As is usually tbe case, fiscal austerity bad its greatest impact on 'development' rather than 'routine' items in tbe budget. These two factors, combined with a general strategy of greater liberalisation and deregulation, are leading to a reformulation of regional development policy, with stronger emphasis on decentrabsation. In such a policy environment, planners need to have a good under• standing of tbe economic and social dimensions of regional development. Fortunately, tbe regional data base in Indonesia - practically non-exist• ent before 1970 - has been improved enormously. Thanks to the Biro Pusat Statistik (BPS), Indonesia now has one of tbe most comprehensive range of regional statistics among develo'ping nations. Tbe purpose of this article is to use this data set to analyse tbe record of regional development in Indonesia since tbe 1970s. Tbe oil boom might have been expected to exacerbate regional inequalities, by concentrating development in tbe resource-rich provinces and in tbe capital, Jakarta. On tbe other band, tbe central government's 'fiscal equalisation' measures should have promoted more uniform development. What have been tbe trends in tbe economic indicators - towards more or less inequality? Have social indicators moved in tbe same direction? And what of tbe relationship between economic and social indicators, across provinces and over time?

II. Data Base and Selection of Indicators Tbe first issue is tbe selection of appropriate indicators of regional economic and social development. Tbe best economic welfare indicator would be per capita personal consumption expenditure, adjusted for inter-provincial price variations. Such data are available from periodic household surveys (Susenas), but not on an annual basis. Moreover, in some cases tbe data appear to be implausible, perhaps owing to limited sample sizes in several small provinces. An alternative measure is gross domestic (or regional) product. This suffers from tbe usual limitations associated with using production measures as economic welfare indica• tors; in particular it includes investment, depreciation and stock changes. But, carefully used, tbe GDP figures are a reasonable approximation, especially if two adjustments are made. Tbe first is tbe exclusion of mining from each province's GDP.

1$3 Hill and Williams

About 96 per cent of mining value added in Indonesia is derived from oil and gas, tbe direct economic spin-offs from wbicb are minimal at tbe local level. Tbat is, almost all tbe oil and gas revenue accrues to entities outside tbe provinces in wbicb production is located, either to tbe central government (in tbe form of taxes), Pertamina, or foreign-owned petro• leum companies. There are, of course, substantial local indirect spread effects (such as in construction, downstream processing, etc.), and these are captured in tbe remaining sectors of tbe regional accounts. Tbe second modification is to adjust these nominal price GDP data for regional price variations. These variations are considerable in an eco• nomy as diverse as Indonesia, in wbicb outlying regions are not yet fully integrated into national commerce. A reasonable proxy for such dif• ferentials might be rice prices, on wbicb comprehensive data are available. However, rice prices are not completely satisfactory since they are sub• ject to government regulation; also in some parts of eastern Indonesia rice is not tbe staple. Fortunately, more sophisticated regional price indices have been constructed. Arndt and Sundrum (1975) prepared such an index up to 1974, and tbe relativities for tbe latter year may be used for 1975, tbe year at wbicb reliable regional GDP data commence. For more recent years tbe cost of living index published by BPS (Kebutuhan Fisik Minimum - Minimum Physical Needs) may be used. Ideally one would want to analyse tbe regional GDP estimates from tbe late 1960s — after economic rehabilitation but before tbe massive oil price increases - through to tbe mid 1980s, when oil prices bad collapsed. However, tbe early estimates of regional GDP are generally regarded as being of rudimentary quality^ and real confidence can be attached to tbe figures only from 1975 onwards. This generates a series from 1975 to 1984, corresponding to tbe peak of tbe first round of oil price increases and tbe onset of slow economic growth, respectively. To provide a more complete picture of regional development, these economic variables need to be supplemented with social indicators. But tbe selection of appropriate social indicators is far more complex: Should they be 'input' (resources devoted to a particular sub-sector) or 'results- based' (identifiable performance indicators) variables?. What specific variables should be selected? And should they be aggregated into a com• bined index of 'social development'?

1 For an evaluation of the early regional GDP estimates, see Arndt (1973), Esmara (1975) and Kerr (1973).

194 The Economic and Social Dimensio u

This is not the place to canvass all the issues/ However, it should be stressed tbat an aggregate social index is not a particularly use ful analytical tool, despite tbe appeal of simpUcity. For one thing, there iire formidable problems involved in its calculation — in assigning weig its to tbe various indicators, in devising maxima and minima scales, and in calbbrating these scales. Secondly, by collapsing various indicators ir to one index, important insights into social development are neglected. F or there is no necessary uniformity id social indicators. Provinces may per• form well in some areas, but poorly in others, and in analysing patte: ns of regional development and in advocating policy prescriptions it is important to draw attention to this mix of outcomes. To keep tbe analysis within manageable bounds, social performaiice is examined with' reference to three key areas - health, poverty a|nd education. In each case, a key indicator of performance is selected a proxy for tbe sector's record, as follows:

Health: By far tbe most widely used measure of health performance is tbe infant mortaUty rate (IMR), tbe number of deaths (before age one year) per 1,000 live births. Life expectancy is tbe most reliable alt native measure, although it is a 'lagged' indicator since it does not fu ly reflect improvements in health at tbe margin. Input measures (such as doctors per 100,000 population) suffer from tbe limitation tbat they tlo not allow for service quality or distributional effects.

Poverty: Tbe data refer to tbe percentage of tbe population in each p: o- vince who fall below tbe Sayogyo poverty line, tbat is, a 'rice equivale: it' minimum annual per capita expenditure of 320 kg in rural areas aid 480 kg in urban areas. Tbe data are derived from Susenas bousebc Id expenditure survey data, with nominal expenditure figures being adjusted for regional price variations. Tbe data indicate tbe incidence of poverty, though not necessarily its severity; tbat is, they show tbe percentage tbe population below tbe poverty line, but not bow far they are bel

2 See Hicks and Streeten (1979), and references cited therein, for an extenc^ed discussion.

1)5 Hill and Williams

Education : Of the three key areas of social performance, education is the most difficult for which to identify a summary social indicator. Recent literacy data are not very reliable, and in anycase they do not incorporate improvements at tbe margin. Tbe most useful alternatives are enrollment ratios. Junior High School enrollments, as a percentage of tbe relevant age group (13-15 years inclusive), was selected as tbe best indicator of tbe depth and spread of education. Primary school enrollments have risen extremely rapidly, and in tbe process it is very difficult to identify from these data reliable inter-provincial variations in educational quality. Senior High School and tertiary enrollments are excluded, as they could hardly be included in a basket of basic social welfare indicators.

For tbe three social indicators data are available for tbe 1970s and 1980s. While not corresponding exactly to tbe reference period of tbe regional accounts data, tbe time periods are close enough for tbe relation• ships between social and economic indicators across provinces and over time to be investigated.

III. Results

Provincial economic performance is shown in Tables 1 and 2. Tbe major adjustment in Table 1 is tbe removal of tbe mining sector, wbicb reduces national per capita GDP by about 40 per cent in both years (compare columns (1) and (2), and (4) and (5)). Tbe price adjustments have a more minor effect. Not surprisingly, tbe exclusion of mining has tbe greatest impact on tbe four 'resource-rich' provinces, Aceb, , Fast , and Irian Jaya. In 1975, tbe sharpest relative decline occurs in Riau — from 7.3 times tbe national level (including mining) to 1.4 times (excluding mining). Irian Jaya falls from 1.5 times tbe national level with mining to being almost identical in tbe non-mining case. Similar trends are evident in 1984, tbe main difference being tbe specta• cular increase in Aceb following tbe LNG boom. In both years Fast Kali• mantan has tbe highest non-mining per capita GDP — followed closely by Jakarta — reflecting tbe peculiar local impact of its 'twin booms', oil and timber.

In columns (3) and (6) tbe nominal price GDP data have been recalculated at Jakarta prices. Tbe effect on provincial GDP figures and ranking is small in most cases. There appears to be a sUgbt compression in inter-provincial variations, since tbe figures of tbe four low GDP provinces are raised by tbe adjustment, while those of some of tbe very high GDP provinces — notably Fast Kaliniantan - fall. However, tbe association between regional price levels arid GDP is not very strong.

196 The Economic and Social Dimensioris

Table 1: Per Capita GDP of Provinces, 1975 and 1984 (Rp '000, current prices)

19 7 5 1 9 84 GDP, exd. GDP, exd. mining, GDP.excl. GDP, exd. mining, GDP mining price adjusted GDP mining pri( adjusted (1) (2) (3) (4) (5) (6) 97.0 66.1 723 1,6943 4692 14.7 94.6 833 913 465.5 4263 459.0 West SumaUa 59 i 593 59.9 437.1 4313 478.1 Riau 984D 113.7 114.0 3P92.7 543.4 510.9 76.4 70.1 643 3273 2973 316.9 137.1 98.9 883 6973 5333 623 S\& 513 493 3173 3153 i 333 71.9 713 68.0 2133 212.9 17.9 Java Jakarta 1955 195.9 1955 1,1915 1,1915 ,191.9 71.1 63 i 685 3843 3233 339.4 56X) 55.7 663 3093 307.7 369 3 56J 563 70 J) 307.0 3053 363.7 65.6 653 782 3993 397.7 509.4 Kalimantan 76.1 76.0 72.1 3393 3382 3153 ^y _ • A. • . a a r * 80.9 OA X 67XT 3e 514.0 511.4 459.0 Centra] Kalimantan 803 70.4 702 493 4283 4253 395.9 514.9 2272 215.0 3,869.7 1,316.1 ,148.7 80.1 793 64.4 3463 343.6 3 753 563 56.1 552 286.1 2783 284.9 663 663 73 7 308 1 305.4 318.9 633 53.9 505 3333 299.0 3092 Eastern Indonesia 68.0 673 71.0 4173 414.7 432.6 41.7 41.2 50.9 2133 210.4 2563 38.7 38.6 322 1982 1973 184.4 863 84.9 693 402.0 388.7 319.0 Irian Jaya 205.7 79.9 n.a. 6803 3113 232.1

INDONESIA 1334 793 75.4 699.1 426.9 430.7

Sources: BPS, Pendapatan Regional Provinsi - Provinsi di Indonesia, Jakarta, various issues, for GDP estit rates. BPS, Kebutuhan Fisik Minimum, Jakarta, various issues, and Amdt and Sundrum (1975), for regional price data. BPS, Sensus Penduduk 1971 and 1980, andSUPAS 1985, Jakarta, for population estimates an|i inter• polations.

19 Hill and Williams

Table 2: Real Economic Growth by Province. 1975-84 (annual average growth, per capita)

GDP excl. GDP mining (1) (2) Sumatra. Aceh 15.9 O C 83 North Sumatra 5.0 5.9 9.0 8.9 £. Q 1 Q Riau —0.0 TorvftKl J al 11 Ul 2 4 2.7 South Sumatra 4.5 6A Bengkulu 9.4 9.4 Lampung 0.5 03

Java Jakarta 73 7.8 West Java 6.1 6.6 Central Java 6.4 63 Yogyakarta 4.1 4.1 East Java 6.9 63 Kalimantan West Kalimantan 5.4 5.3 7i 73 South Kalimantan 5.0 5.0 East Kalinantan 9JS 3.8

ouiawcM North Sulawesi S3 53 Central Sulawesi 4.7 4.5 South Sulawesi 5.2 5.1 Southeast Sulawesi 53 5.4 Eastern Indonesia Bah 103 10.1 West Nusa Tenggara 5.4 53 Fast Nusa Tenggara 5.9 53 Maluku 4.7 4.4 Irian Jaya -0.7 5.6 INDONESIA 43 5.8

Sources: Calculated from sources to Table 1.

198 The Economic and Sociai Dimensions

High income Aceh, for example, has below average prices, presumabl;' because its traditional rice surplus is 'trapped' in the province by poor regional transport infrastructure (Hasan, 1976); conversely, prices in th 5 desperately poor province of East Nusa Tenggara appear to be abov average. It is likely that the quality of physical infrastructure is at least as important a determinant of these price variations. This is illustrate 1 by the substantial differences in the price-adjusted 1984 GDP figures for such remote provinces as Maluku and Irian Jaya. ,(The fact that no siici large difference is found for, say, North Sulawesi is at least suggestive cf unofficial trade.) The exclusion of mining has little effect on inter-provincial growth rates outside the four resource-rich provinces (Table 2). The econom c contraction in both Riau and Irian Jaya is due entirely to the minir g sector. In fact, the non-mining sector of Irian Jaya gtew quite rapidl; although such figures need to be interpreted with caution in an unusual subsistence-oriented economy. Among the four provinces, Aceh had b(y far the most impressive non-mining performance. What of the relationship between levels of GDP and economlic growth? Have the fastest growing provinces been predominantly the riqh or poor ones? The outcomes can be divided into four quadrants: I: low growth, high income II: high growth, high income 111: high growth, low income IV: low growth, low income where 'low' and 'high' mean effectively below and above the national averages respectively. The results are shown in Figure 1, for the noi- mining, price adjusted GDP case. Since the average is skewed by the few very high GDP provinces, most fall within quadrants 111 and IV. While only four provinces were within the high growth —high income categoi/. North and South Sumatra, Fast Java and Jakarta - all for differei) reasons somewhat special - a heartening number of fairly poor provinces grew very rapidly. Especially notable were the smaller provinces ofj Aceh, Bali, West Sumatra and Bengkulu. But not far behind them we -e the two big Java provinces. Moreover, even among the low income-low growth provinces, there was a cluster of some seven which were no( substantially below either average. The 'problem' cares of very low^ income or growth — or both — are clearly Lampung, Jambi and Fajs and West Nusa Tenggara. 1

The regional accounts data also assist in identifying the major Ic ci of economic prosperity in-Indonesia, and the lagging regions (Table Hill and Williams

Figure 1: Provincial GDP and Economic Growth, 1975—84

120 17 (215.0) 9 (195.9) 1 Aceh 110- I II 2 North Sumatra 3 West Sumatra low growth, 00 high growth, high income 4 Riau II high income 5 Jambi 100- 6 South Sumatra I 7 Bengkulu 8 Lampung 90- T3 9 Jakarta I 10 West Java 11 Central Java 80- 12 Yogyakarta 8 National average = 75.4 >13 •c 13 East Java • 20 14 West Kalimantan 12 •14 • 1 S; 70- • 25 •22 15 Central Kalimantan 8(0.5) •10 •11 (15 16 South Kalimantan • 5 •18 17 East Kalimantan t 60- • 3 18 North Sulawesi 8. 19 Central Sulawesi •19 h 23 20 South Sulawesi o •21 21 Southeast Sulawesi 00 50- •16 • 7 22 Bali c IV III 23 West Nusatenggara low growth, high growth, 24 East Nusatenggara § 40 low income low income Z 25 Maluku 26 Irian Jaya 24 30 1.8 2.8 3.8 4.8 5.8 6.8 7.8 8.8 9.8

Real annual growth in per capita non-mining GDP, 1975-84

200 The Economic and Social Dimension! i column 6; Table 2, column 2). 'Western' Indonesia encompasses many of Indonesia's better off regions: four of the top five provinces (Jakarti ., South Sumatra, Aceh, Riau) and six of the top 10. And although tie Java-Bali provinces (excluding Jakarta) are not among the most prospe •- ous provinces, neither are they the poorest. None is among the poore it 10, for .example, their rankings ranging from a surprisingly high 6 fc r East Java to 10 for West Java. The really poor regions are a mixed assort• ment of cases: traditionally deprived provinces of East and West Nuia Tenggara; the two smaller provinces of Sulawesi (Central and Southeast), the special case of Irian Jaya; and the transmigration province of Lan- pung. If 'equitable' regional development is to have any meaning, thcie provinces require a particular development focus. The social indicators discussed above assist in providing a more complete picture of regional development. But the record is a good deal more complex. There is no consistent pattern for many provinces amo ig indicators and over time; nor is there a strong association between eco• nomic and social indicators. Such a complex pattern arises because in enormous array of economic, historical, social and cultural factors impinges on social development, and their effects differ among the three variables analysed. Social indicators are presented in Table 3, together with a summiry picture in Table 4, and the rate of change in Table 5. It will be useful to classify the provinces into four main categories of social performan ;e, using as yardsticks national average figures.

(0 Excellent social record (those in Table 4 which have 6 'Gs'): T lis includes Aceh, North Sumatra, Jakarta and North Sulawesi. Three of 1 h^ four are considered high income provinces, although Aceh was not in l he 1970s. In all four provinces the social accomplishments compare favour• ably with much higher income countries. A distinctive set of cultma)- historical factors explains the outstanding performance in North Sulawe^ (See Sondakh and Jones, chapter 15 in Hill (ed) (1989)). Befitting its capital city status, Jakarta had both the lowest infant mortahty rate •< nd the high education enrollment ratio in 1985. («) Generally good social record: In another five provinces the rec iifd was good in most but not all cases (at least 4 'Gs'). The most interest ing of these is Yogyakarta, traditionally considered to be one of the pooi e^t regions of Indonesia. Apart from its high poverty ranking in the 19' Os, it scores remarkably well, in 1985 being second only to Jakarta in its opv infant mortality rate and sixth in education. Here also a range of non- economic factors has contributed to this excellent record for a l)w- income province (see Booth and Damanik, chapter 11 in Hill (ed) (198|9)).

101 Hill and Williams

Table 3: Social Indicators by Province. 1970s and 1980s

Health Poverty Education Infant Mortality (/I POO) % below poverty line Junior High School Enrdlment 1977/78 1985 1976 1984 1971 1985 0) (2) (3) (4) (5) (6)

Sumatra Aceh 91 45 185 1.7 596 866 North Sumatra 91 58 413 173 51.0 853 West Sumatra 121 77 323 7.1 49.4 853 Riau 113 59 356 223 403 80.5 Jambi 118 62 29.7 7.0 42.0 78.1 South Sumatra 118 71 37P 116 46.7 766 Bengkulu 106 62 286 103 543 826 Lampung 97 CA 48.7 414 59 403 755 Java Jakarta 80 32 27i4 136 566 876 West Java 129 84 45.4 24.6 363 60.6 Central Java 96 70 763 463 393 68.4 Yogyakarta 62 37 653 17.4 575 84.1 East Java 99 71 696 36.9 433 713 Kalimantan West Kalimantan 116 54 266 136 40.9 79.0 Central Kalimantan 100 73 25.1 213 57.0 76.4 South Kalimantan 111 88 163 19.7 475 71.0 East Kalimantan 99 AA 166 21.4 473 846 42 Sulawesi North Sulawesi 94 55 38.4 6.9 58.7 816 Central Sulawesi 128 78 405 25.0 64.4 783 South Sulawesi 108 65 32.1 293 453 743 Southeast Sulaw isi 114 78 574 35.7 633 803 Eastern Indonesia Bali 88 64 424 29.1 35.1 80.7 West Nusa Tenggara 187 146 536 51.4 32.0 66.1 East Nusa Tenggara 124 88 556 49.4 61.7 77.6 Maluku 124 80 48.7 37.1 69.1 80.7 Irian Jaya 106 n.a. n.a. 16.7 n.a. 78.0

INDONESIA 107 72 523 303 443 73.0

Sources: Hugo et al. (1987, p. 125), and Streatfield Larson (1987) for Infant Mortality estimates for 1977/78 and 1985 respectively. Poverty Rates: Computed from BPS,3t«enas 1976 and 1984, Jakarta. We are indebted to Dr Abuzar Asra for providing the raw data from which these data have been estimated. BPS, Sensus Penduduk 1971, andSUPAS 1985, JakarU, for Junior High School enrollment ratios.

202 The Economic and Social Dimensions

Table 4: Summary Indicators of Social Performance, 1970s and 1980s

1970s 1980s Health Poverty Education Health Poverty Education Sumatra Aceh G G G G G G North Sumatra G G G G G G West Sumatra P G G A G G Riau A G A G G G Jambi P G A G G A South Sumatra P G A A G A Bengkulu A G G G G G Lampung A A A P P A Java Jakarta G G G G G G West Java P A P P A P Central Java G P P A P G Yogyakarta G P G G G G East Java A P A A P A Kalimantan West Kalimantan p G A G G A Central Kalimantan A G G A G A South Kalimantan P G A P G A East Kalimantan A G A G G G Sulawesi North Sulawesi G G G G G G Central Sulawesi p G P A A A South Sulawesi A G A A A A Southeast Sulawesi A A G A A G Eastern Indonesia Bali G A P G A G West Nusa Tenggara P A P P P A East Nusa Tenggara P A G P P A Maluku P A G P P G Irian Jaya A na. n.a. n.a. G A

Sources and Notes: Based on data in Table 3. G indicates provincial record at leas 10% (20% in case of poverty) superior to national average; P indicates 109 > (20%) inferior; A indicates within 10% (20%) of national average.

20 Hill arid Williams

Table 5: Changes in Social Indicators by Province, 1970s-80s (% change, increase for education, decrease for health and poverty; figures in parentheses indicate contrary trend)

Health Poverty Education (1) (2) (3)

Sumatra Aceh 50.6 91.0 45.6 ivoim oumaxra JC 673 DO Jo West Sumatra 36 A 78.0 723 Riau 47.8 36.8 1003 Jambi 473 76.4 86.0 South Sumatra 39.8 68.1 64.0 Bengkulu 41.5 633 523 I.ampung 39.2 15.0 883

Java Jakarta 60.0 50.4 56.4 West Java 34.9 45.8 66.0 Central Java 27.1 39.6 74.1 Yogyakarta 40.3 733 453 East Java 28.3 47.0 81.6 Kalimantan West Kalimantan 53.5 483 733 Central Kalimantan 27.0 15.1 24.6 South Kalimantan 27.3 (20.9) 593 East Kalimantan 57.6 (27.4) 793 Sulawe ii North Sulawesi 413 82.0 39.0 Central Sulawesi 39.1 38.9 21.4 South Sulawesi 39.8 9.0 633 Southeast Sulawesi 31.6 37.8 26.8 Eastern Indonesia Bali 27.3 31.4 129.9 West Nusa Tenggara 21.9 3.0 106.6 East Nusa Tenggara 29.0 10.2 25.8 Maluku 353 23.8 16.8 Irian Jaya n.a. n.a. n.a.

INDONESIA 32.7 42.5 643

Sources : Calculated from data in Table 3.

204 The Economic and Social Dimensions

The two resource-rich provinces, Riau and East Kalimantan, also have s good record, especially in the 1980s. This is especially so in view o the frequent characterisation of their performance as one of 'enclave development. In the smaller Sumatran provinces of West Sumatra and Bengkulu the record is also generally good.^ As with economic indicators, the provinces with the best social indi • cators are located disproportionately in 'western' Indonesia: of these tO]i nine provinces, six (Jakarta plus the Sumatra five) are in this region. (Hi) Fair social record: Six provinces were clustered fairly consistentl r around the average (at least 2 'Gs', no more than 1 'P'). These comprise i wide mix of provinces: rapidly growing Bali, with perhaps the best recor 1 of the six; high income South Sumatra; the two 'frontier' provinces cf Kalimantan, West and Central; and two low-income cases, Jambi and Southeast Sulawesi. The diversity of these six underlines the weak assoc i- ation between economic and social performance in many provinces. (zv) Uneven social record: Another four provinces were clustered around the national average, but without the stronger performers include d in group (zzz) (up to 2 'Gs' up to 2 'Ps'). These also comprise a mixed group, with East Java a rapidly growing relatively high-income' province, in addition to three provinces possessing both below average growth ai ci income. South Kalimantan, and South and Central Sulawesi. | (v) Poor social record. Finally, there are six provinces in which 1 social record is poor, in some desperately so (either having no 'Gs' or at least 3 'Ps'). There is great variety among indicators within this groip, in that some provinces perform quite well in one or two social areas, bu); poorly in others. Maluku and Central Java stand out in this respe ;t. Partly on account of its history, Maluku's education standards are go >d (see Meyer and Martono, chapter 24 in Hill (ed) (1989)), while its pov;r- ty and health record are poor. In Central Java, the record is even mc re mixed, with no consistent pattern even within social indicators. The f< ur worst performers are all very poor provinces. Lampung, as noted, iias experienced very rapid population growth, without the necessary so( ial and physical infrastructure to promote social development. West Jaia*s record in social development has been uniformly poor in the New Or ier period, matching neither its own economic record, nor the social progiess of the other Java provinces. While containing large pockets of relal iye

3 It is possible that our education indicator may be somewhat misleading in 'hte- starter' cases, where the very recent spread of education has resulted in sd ool attendance among age groups older than the nationally assumed norm. Benglulu and East Kalimantan, both 'frontier' provinces, could fall in this category. Hill and Williams

prosperity, especially around Jakarta and Bandung, in 1985 it had the lowest education enrollment ratio and one of the highest infant mortality rates. West Nusa Tenggara undoubtedly has the worst social record of all in the 1980s: an infant mortality rate over double the national average, the highest poverty rate, and the second lowest education enrollment ratio. Despite its marginally higher per capita GDP, its social record is much inferior to that of neighbouring East Nusa Tenggara. While having by far the lowest per capita GDP, the latter's education record is com• paratively good, again mainly owing to historical factors (see Corner, chapter 7 in Hill (ed) (1989)). The social record thus has some similarities to the economic record, but equally some significant divergences. The similarities are, principally, the preponderence of good performers in the western region, and the very poor social and economic record in the east, especially the Nusa Tenggara two. Lampung, also, rates very poorly according to all criteria. Yet there are, equally, cases of good economic performance and an indif• ferent social record, and vice-versa. We return to this point shortly. As with the economic indicators, there is not a strong association between initial levels of social indicators and changes over the decade. Using the 'four-quadrant' approach discussed above,'* there is a wide range of outcomes in health performance. Eight provinces are located in quadrant II, indicating superior levels and rates of improvements; the best in both respects are clearly Jakarta, Yogyakarta and Aceh. Three more are in Sumatra, in addition to North Sulawesi and East Kalimantan. The quadrant I cases, generally close to the average, comprise East and Central Java, Bali, and Central Kalimantan. The serious quadrant IV regions comprise just four provinces: West and East Nusa Tenggara, Southeast Sulawesi, and South Kalimantan. The remaining nine provinces are in quadrant III, though in most the rate of improvement is close to the national average. The national poverty averagp is pulled up by the record in Java, so that most provinces are located in quadrants I and II. Only six provinces had above average poverty in 1976: four were in quadrant IV - East and West Nusa Tenggara, Southeast Sulawesi, and Central Java, while the more rapid improvement in East Java and Yogyakarta placed them in

4 The figures are not presented here, but the quadrants have the same meaning. That is, quadrant I denotes a better than average record in the initial year (lower infant mortality, lower poverty, higher enrollment) but below average improve• ment, quadrant II indicates a better than average record in the initial year and in the improvement, and so on.

706 The Economic and Social Dimensfoni quadrant III. The 10 quadrant 11 provinces are dominated by Sumatia (six: Aceh, Bengkulu, Jambi, and West, South and North Sumatra), in ad• dition to Jakarta, West Java (very close to the average level and improv ment). West Kalimantan, and North Sulawesi. The nine quadrat 1 oasis comprise a mixed assortment, including Lampung (almost in quadrar t IV), the three Kalimantan provinces (for two of which the data suggesit an improbable increase in poverty) and five other provinces. The education indicator displays the most even performance of all, reflecting concerted government action in this area. There are r o quadrant IV cases, of low enrollment ratios and low increases. And there are just three quadrant II provinces — North and West Sumatra, and BE st Kalimantan — .all of which are close to the- national average in one vl both respect. The biggest grouping of provinces is in quadrant 1, which in the main comprises smaller provinces outside Java (expect for Jakarta and Yogyakarta). Quadrant 111 includes the three big provinces of Ja\ ai together with Bali, West Nusa Tenggara and four other provinces. Combining the social performance data of the 1970s and the rates of improvement in the subsequent decade thus underlines again the gener il• ly good performance in most of Sumatra, parts of Java (most notat ly Jakarta and Yogyakarta), and a few other pockets, especially North Sula• wesi and, surprisingly, East Kalimantan (if the 1984 poverty data irp discounted). Conversely, the serious cases also appear in sharp foe is, particularly the two in Nusa Tenggara, Lampung and Southeast Sulawesi In analysing the regional economic and social performance, t v^ other questions are important. First, what are the broad trends in regioil-' al equality, both for economic and social variables? And is there a strc ng association between these variables, across provinces and over time? There are no obvious a priori expectations regarding trends in regional economic and social equality. On the one hand there hive been many powerful forces likely to lead to increased inequality: the oil and gas boom and its region-specific effects; the emergence of mod ;rh sector enclaves in various parts of the country; the concentration df much of the manufacturing investments in a few key locations; and the inevitably 'lumpy' nature of very large infrastructure and aid proje ;ts. Conversely, there have been very strong 'equalising' forces, including the fiscal arrangements in the oil and gas sector, which ensure that most qf the revenue from these investments accrues to the central govemmei(t. Also important have been several major government programs wit i a consistent nation-wide focus, such as in rice and education, and the vastly improved physical infrastructure, which has facihtated grentbr mobility of resources. Hill and Williams

The most widely used measure of regional distribution is the 'Wil• liamson dispersion index', devised and applied in his seminal 1965 article. Essentially it is a weighted coefficient of variation which measures the regional dispersion of an attribute, weighted by each province's share in national population.^ The indices for the major economic and social variables discussed above are presented in Table 6. A simple analysis of the GDP data suggests an extremely high index in both years, but these are obviously distorted by oil and gas. Excluding mining, the index falls very sharply, by over half in 1975 and almost 40 per cent in 1984. Adjusting the data for inter-regional price variations results in a further small reduction in both years, indicating that generally higher prices in high-income provinces (and the converse) do overstate regional GDP differences, albeit slightly. The results indicate a narrowing of regional differentials if the mining sector is included. But in the more relevant case, excluding mining, the index has risen from a fairly low figure in 1975 by about 20 per cent. However, even the non-mining figures are affected by the 'outlier' problem, particularly the very high estimates for Jakarta, Riau and East Kalimantan. The exclusion of these three provinces reduces the dispersion indices significantly, to approximately one-half in the price adjusted, non-mining series. Since all three cases represent to some extent 'enclaves', peripheral to the national pattern, it is reasonable to conclude that the regional differentials were both low and rising only very slowly over the period 1975-84. This conclusion is broadly consistent with earlier estimates of regional inequality in Indonesia. Esmara (1975, p. 46), using 1972 data, calculated the index to be 0.945, falling to 0.262 if oil income and three high-income provinces (Riau, East and Central Kalimantan) are excluded. Citing the earlier study of Williamson (1965), and comparing Indonesia with other developing countries possessing an approximately similar

5 Statistically, Williamson defmes the index as follows:

where fi = population of the i"* province n = national population yj = attribute (GDP per capita, infant mortabty, poverty, education) of tbe i*^ province, y = national average of tbe attribute.

208 Table 6: Dispersion Indices

1970s 1980s (1) Economic (current prices unless otherwise indicated)

23 all 23 aU provinces provinces provinces provinces GDP per capita, 1975 .836 .935 GDP per capita, 1984 .501 .801 (1975 prices) (.422) (.705) Excluding mining, 1975 .267 .403 Excluding mining, 1984 .237 .499 (1975 prices) (.215) (.487) (2) Social Infant mortality, 1977/78 .178 Infant mortality, 1985 .272 Poverty, 1976 .587 Poverty, 1984 .598 R Education, 1971^ .179 Education, 1985 .116

8o Sources and Notes: see text, '23 provinces' refers to exclusion of Jakarta, Riau and East Kalimantan. ~cr- Hill and Williams number of administrative boundaries (an important determinant of the value of the dispersion index), Esmara found Indonesia's regional dif• ferentials to be comparatively modest. Azis (1985, p.229) prepared estimates of the Williamson index and found much higher values for the years 1971, 1975 and 1980, of 1.383, 1.288 and 0.957 respectively. While no explanation for these higher figures is provided, his non-oil estimates (0.442 and 0.484 for 1975 and 1980 respectively) are similar to ours, as is his conclusion that there has been no appreciable rise in inequality. Uppal and Budiono (1986) calculated indices on an annual basis for the years 1976—80, using non-mining GDP data. They con• cluded, perhaps controversially, that regional inequality in Indonesia appeared to be declining. Their results were, however, challenged by Kameo and Rietveld (1987), on the grounds that the original data base could equally be interpreted as suggesting an increase in inequality, and also because the index is much lower if personal expenditure (from Suse• nas) rather than non-mining GDP data are used. Their index for personal expenditure, of 0.224 in 1976, falls within the range of our estimates for the adjusted data in 1975. Unfortunately, there have been no recent cross-country updates of Williamson's pioneering estimates. The two recent studies for the Asia- Pacific region of which we are aware are Treadgold (1987) on New Guinea and Sundrum (1987) on India. Treadgold estimated that the dispersion index for Papua New Guinea rose sharply from 0.463 in 1966/ 67 to 0.997 in 1980, before falling slightly to a still very high 0.828 in 1983. These results may be compared directly with those for Indonesia since the number of administrative units (17) is not substantially less; however no allowance is made for the effects of enclave mining develop• ments in the PNG study. Sundrum (1987, 47—51) found much lower indices for the 16 Indian states: an index of 0.213 in 1960/61, rising to 0.348 by 1977/78; and using household expenditure survey data the index for the latter year was just 0.176. These results are not greatly dif• ferent from Indonesia's if suitable adjustments are made, thus confirming the latter's status as a 'low regional inequality' country, especially so for such a diverse archipelagic nation.

The social indicators suggest a much more uniform pattern of development, except for poverty. The dispersion in infant mortality rates is very low, although there has been some increase over the period. That for education is equally low, and remarkably, it had fallen even further by 1985. Only in poverty rates is there a much greater variation, a pattern which showed little change from 1976 to 1984. The significant• ly higher index for poverty reflects the continued presence of serious

210 The Economic and Social Dimensions poverty pockets in much of eastern Indonesia, parts of Java, and Lam • pung. Unlike health and education, this variable is not as immediately amenable to pubhc poUcy programs designed to produce quick results But, with this exception, the social record of the New Order has beei impressive. In an era of high growth, a strong uniformity in social pei- formance has been achieved and maintained. On the basis of earlier discussion, a strong association betwee i economic and social performance would not be expected. There are to^) many cases of good social indicators in low-average income provincej, and an indifferent record in more prosperous regions, for such an assoc - ation to be present. The data in Tables 7 and 8, and the graphical sunj- maries of the 1980s data in Figures 2-4 confirm this hypothesis.

Table 7: Correlation Coefficients — Linear (Unear relationships, rank correlations in parentheses)

Health Poverty Educatioi

(1) 1970s GDP per capita -.060 -.245 .173 (-.300) (-.521) (.015) GDP excl. mining, per capita -.304 -.488 .012 (-.302) (-.495) (.034)

GDP exd. mining, price adjusted, -.344 -.344 .065 per capita (-.497) (-.189) (.224)

(2) 1980s GDP per capita -.382 -.219 .350 (-325) (-.488) (.465) GDP excl. mining, per capita -.486 -.307 .429 (-392) -.486) (.471)

GDP excl. mining, price adjusted, -.512 -341 .419 per capita -.443) (-.508) (.484)

(3) Change, 1970s-80s

Growth in GDP per capita, 1975-84 -.156 .358 .005 including mining (-.155) (•112) (.073) excluding mining -.070 .232 .160 (-.124) (.243) (.094)

1 Hill and Williams

Table 8: Correlation Coefficients - Best Fits

Health Poverty Education

(1) 1970s GDP per capita .208 .405 (DL) ,173 (L) GDP excl. mining, per capita .372 .505 (DL) .045 GDP excl. mining, price adjusted, per capita .406 383 .144

(2) 1980s GDP oer ranita 514 1T)1) 406 498 GDP excl mininff ner caoita 581 tDL) 451 416 GDP excl. mining, price adjusted. .-J o 1 yL£t-i J per capita O O C /TVT X .243 (L) .985 (DL) .885 (DL) (3) Changes, 1970s -1980s Growth in GDP per capita, 1975-84 including mining .512 (DL) .358 (L) .389 (DL) excluding mining .121 (L) .307 (L) .160 (L)

Note: The best fit is a semi-log relationship, unless otherwise indicated, by double- log (DL in parentheses) or linear (L in parentheses).

What is remarkable is how iow the coefficients are in many cases. In the simplest example, using unadjusted GDP and assuming a linear relatio iship, the highest coefficient in either year for any variable is 0.382 (health, in the 1980s). The relationship between health and GDP per capita in the 1970s is very weak, while all others show little relation• ship. The results are improved by making several adjustments. First, the figures are substantially higher if mining is excluded since, as noted, these enclave activities have little direct impact on local welfare; this effect is especially pronounced in the 1980s. Secondly, adjusting for relative prices strengthens most of the relationships, although the effect is not great. Thirdly, rank correlations generally produce higher figures (shown in parentheses in Table 7), an expected result since this calcula• tion is not distorted by the magnitude of outlier cases. Fourthly, the associations were tested using other functional forms - semi-log, double- log, quadratic — on the plausible assumption that the underlying relation• ships are likely to be non-hnear. This produced some higher figures (see Table 8), but still fairly weak results. Finally, the data were inspected

212 The Economic and Social Dimensions

Figure 2: Provincial GDP and Infant Mortality, 1984-85

9(1 191. 17(1148.7)

620- I II high mortality, <= low mortality, high income high income 570-

520- •13 •4 • 1

3» 470- Rt 15 %2 Nationalavmge = 430.7 22 •c 420-

0\ • 16

• 18 370-1 • 11 cd •12 o • 10 7

320- 25 • 20^ • ,14 a • 21

I • 19 Ill low mortality, c 270- o . •23 (146.0) low income Z IV 220- high mortality, 26 low income

• 24 170 120 110 100 90 80 TO 60 5o" 40 30 Infant Mortality Rate, 1985

513 Hill and WHIiams

Figure 3: Provincial GDP and Poverty Incidence, 1984-85

9(1191.9) T • • , 17 (1148.7)

I n high poverty, low poverty, high income g high income 11 • 6

> g • 4 1 (1.7) a, •13 1 (A

—

•15 #2 •a National average = 430.7 22 cd • I 4204 CL 00 ON • 16 18 A 370-1 • 11 • 'S, • 12 cd o • 10 25 3204 • •20 5s o • 21 • 14 • 00 19 IV • m 2704 ^ high poverty. low poverty, low income low income • 2204 • 26 8

• 24 170- 1 1 r 55 49 43 37 31 25 l'9 13 Poverty Rate, 1984

214 The Economic and Sociai Dimensiors

Figure 4: Provincial GDP and Education Enrollments. 1984

9(11 U.9) 17(1148.7)

620- I U low enrollments, high enrollments, high income high income 570- • 6

520- • • 113 4 «3 S 470- •a" 15* •2 CO National average = 430.7 22 «+420- 00 ON • 16 ea" •a 370 • •18 a • 11 • 12 o 8, • 10 • 7 Q 320- •14 • 20 •s ^25 O • 21 00 c • 19 I 270- o • 23 111 Z high enrollments, IV 26 • low income 220- low enrollments, • 8 low income • 24 170 -I—I—r—T 1 1—I 1 1 1 1 1 1—r 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 Education attainment (Junior High School Enrollments as a percentage of relevant age group)

21) Hill and Williams visually and outlier cases removed (data not presented here). In most cases, however, there was Uttle improvement in the results after removal of such outUers. Similarly weak associations were found in the case of changes in these variables over the decade, suggesting that despite these integrating economic and social forces at a national level, the experiences at provincial levels were quite diverse. This is not the place to explore the weak association between eco• nomic and social indicators in any detail. Several provincial examples of such a phenomenon were provided in the discussion above. For a country as diverse as Indonesia, in which economic and social integration have become a reality only in the last quarter century, the conclusion is perhaps not a surprising one. Studies in other developing countries have also found similar results (see Hicks and Streeton (1979) and references cited therein). But the findings do point to important policy implications. In particular, economic growth alone cannot be expected to lead to improved social performance. Specific targetting may also be necessary in the formulation of social programs. Nor can it be assumed that high- income provinces will necessarily have a better social record and there• fore warrant less government attention.

IV. Conclusion

The purpose of this article has been to analyse the economic and social dimensions of regional development in Indonesia since the 1970s. On the basis of the vastly improved data base generated by BPS, it is now possible to provide a comprehensive picture of such development. Two main conclusions emerge from our study. First, there is extraordinary diversity in modern Indonesia, with respect to economic indicators, social indicators, and changes in these variables over time. And there is no necessary correlation between the two sets of data. This diversity is obviously a key factor for government planners attempting to implement national plans which have consistently emphasised the goal of regional development. The second conclusion is that the record of regional development - as indicated by the indices of dispersion - is a good one. In an era of generally rapid growth and massive exogenous shocks, the regional fabric has held together well. There is certainly no evidence of increasing regional inequality, whether in economic or social conditions. There is much scope for further detailed research on regional aspects of Indonesian economic development. Other social variables could be introduced into the analysis, although we are confident that those used in this paper are suitably representative. Most important, the period of

216 I The Economic and Social Dimensiors analysis here is too short to detect major long-run trends of the type investigated by Williamson (1965) in devising his famous 'inverted-U' relationship. It also needs to be emphasised that we have been concenn d mainly to identify trends and patterns, rather than to explain them. >^ e have not attempted to model Indonesia's regional development, a veiy difficult exercise in view of the methodological and empirical constraints. Nor have we explored other components of the regional dimensio:i, including resource (labour and capital) mobihty and the local impact of national poUcies in the area of public finance and trade pohcy. Final! ^ we have interpreted 'regional' in the context of current administrate e boundaries, as dictated by data availability. In reality, however, region il issues are much more complex than this. In some respects the provinci s are too aggregated as units of regional analysis, especially in the presenc e of enclaves and marked intra-provincial variations. In other cases theie may be an argument for aggregating the units of analysis where several provinces face broadly similar development constraints and issues.

2\'i Hill and Williams

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218