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Bulletin of Indonesian Economic Studies
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
REGIONAL INCOME INEQUALITY IN INDONESIA
AND THE INITIAL IMPACT OF THE ECONOMIC
CRISIS
Takahiro Akita
To cite this article: Takahiro Akita (2002) REGIONAL INCOME INEQUALITY IN INDONESIA AND
THE INITIAL IMPACT OF THE ECONOMIC CRISIS, Bulletin of Indonesian Economic Studies, 38:2, 201-222, DOI: 10.1080/000749102320145057
To link to this article: http://dx.doi.org/10.1080/000749102320145057
Published online: 17 Jun 2010.
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ISSN0007-4918 print/ISSN1472-7234online/02/020201-22 ©2002IndonesiaProjectANU BulletinofIndonesianEconomicStudies,Vol.38,No.2,2002:201–22
REGIONAL
INCOME
INEQUALITY
IN
INDONESIA
AND
THE
INITIAL
IMPACT
OF
THE
ECONOMIC
CRISIS
Takahiro Akita
InternationalUniversityofJapan,Yamato-machi,Niigata
Armida S. Alisjahbana* Padjadjaran University,Bandung
This paper estimates regional income inequality from 1993 to 1998, using a Theil
index based upon district-level GDP and population data. Between 1993 and 1997,
when Indonesia’s annual average growth rate exceeded 7%, regional income in
-equality rose significantly. A two-stage nested inequality decomposition analysis
indicates this was due mainly to an increase in within-province inequality, espe
-cially in Riau, Jakarta and West and East Java. In 1997, the within-province compo
-nent represented about 50% of regional income inequality. The crisis caused per
capita GDP growth to revert to its 1995 level, but the impact was spread unevenly
across provinces and districts. In 1998 regional income inequality declined to its
1993–94 level. In contrast to 1993–97, three-quarters of the 1998 decline was due to
a change in between-province inequality,with the Java–Bali region playing a promi
-nent role. The crisis appears particularly to have afflicted urban Java and urban
Sumatra.
facturing sector’s share of GDP rose from 12% to 21% between 1985 and 1995, while agriculture and mining’s combined share declined from 46% to 26%. The change was most conspicuous in exports, in which the share of manufacturing rose from 17% to 53%, while that of agricul
-ture and mining combined fell from 73% to 22%. The economic crisis that began in 1997 suddenly brought Indonesia’s dynamic economy to a standstill, and in 1998 it contracted by 13%. The crisis cast a shadow not only on the financial but also on the real sector of the economy. The construction and non-oil manufac
-INTRODUCTION
During the late 1980s and the 1990s, be
-fore the economic crisis, Indonesia achieved an annual average growth rate of more than 7%, comparable to the rapid growth of the 1970s. However, this later growth was achieved without the ben
-efit of large oil revenue windfalls. In the decade before the economic crisis in 1997, Indonesia underwent remarkable struc
-tural changes in production and trade. These included a significant decline in agriculture and mining’s share of value added and trade, and an increase in the share of manufacturing. According to Akita and Hermawan (2000), the manu
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Takahiro Akita and Armida Alisjahbana 202
turing sectors were hardest hit, and con
-tracted in real GDP terms by 33% and 18% respectively.
The rapid economic growth before the crisis was accompaniedby a remarkably stable level of regional income inequal
-ity, as measured in terms of provincial GDP with the oil and gas sectors ex
-cluded (hereafter ‘non-oil and gas GDP’).
According to Akita and Lukman (1995) and this s tudy’s calc ulatio ns , the weighted coefficient of variation in pro
-vincial non-oil and gas GDP was virtu
-ally constant between 1985 and 1997: from 1985 to 1993 it was in the range 0.54–0.55 as measured at 1983 constant
prices; and from 1993 to 1997, as mea
-sured at 1993 constant prices, it was in the range 0.66–0.67.1The weighted coef
-ficient of variation in provincial GDP with the oil and gas sectors included was much larger, owing to these two sectors’ very uneven geographical distribution, but even this has gradually decreased as the contribution of the oil and gas sec
-tors to total GDP has fallen (Akita and Lukman 1995).
Regional income inequality receives a great deal of public attention in Indo
-nesia, mainly because of the persistence of large differences in socio-economic
indicators among regions and prov
-inces . In 1997, Java, r epres enting slightly over 6% of Indonesia’s land area, accounted for 58.6% of total popu
-lation and 64.1% of total non-oil and gas
GDP, while the resource-rich province
of Irian Jaya, representing 20% of total land area, accounted for a mere 1.0% of population and 1.6% of non-oil and gas
GDP. The per capita non-oil and gas
GDP of the richest province (Jakarta) was almost nine times as large as that of the poorest (East Nusa Tenggara, NTT). Even within Java, large disparities exist in per capita GDP between Jakarta and
the other provinces. With respect to other socio-economic indicators: (1) in
Jakarta, the proportion of people below the poverty line in 1996 was 2.4%, while in East Nusa Tenggara and Maluku it was 39% and 45%, respectively; (2) the number of hospital beds per thousand people in 1997 was 1.6 in Jakarta, but less than 0.3 in Lampung and West Nusa Tenggara (NTB); and (3) the num
-ber of students attending senior high school (either general or vocational) per thousand people in 1997 was 45 in Jakarta and Yogyakarta, but only 15 in South Kalimantan and West Nusa Teng
-gara (BPS 2001).
The main purposes of this paper are to estimate regional income inequality in Indonesia between 1993 and 1998 using district-level GDP and population data
(as compiled by BPS, the Central Statis
-tics Agency), and to analyse factors de
-termining regional income inequality, using the two-stage nested inequality
decomposition method developed by Akita (2002). The study period includes 1998, when living standards declined significantly in the midst of the economic crisis; thus we also analyse the initial impact of the crisis on regional income inequality. Most previous studies have employed provincial GDP and popula
-tion data to measure regional income in
-equality in Indonesia, and have been unable to measure inequality within provinces.2Our use of district
-level rather
than provincial data provides a means to analyse not only between-province but
also within-province inequalities.
METHODANDDATA
TheTwo-StageNestedInequality
DecompositionMethod
We estimate regional income inequality using a Theil index based upon district
-level GDP and population data. Theil
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Regional Income Inequality in Indonesia 203 indices are additively decomposable and
possess several characteristics desirable in measures of regional income inequal
-ity: mean independence, population-size
independence, and the Pigou–Dalton
principle of transfers (Bourguignon 1979; Shorrocks 1980).3 We conduct a two
-stage nested inequality decomposition analysis to explore factors determining regional income inequality. This method, as developed by Akita (2002), is analo
-gous to a two-stage nested design in the
analysis of variance (ANOVA). It decom
-poses overall regional inequality, as measured by a Theil index based on dis
-trict-level GDP and population data, into
three components: between-region, be
-tween-province and within-province in
-equality. The between-region component
reflects inequalities between the five ma
-jor islands or island groups: Sumatra, Java–Bali, Kalimantan, Sulawesi and
‘Other’. The between-province compo
-nent is an average of between-province
inequalities(calculated for each of the five regions) weighted by GDP shares. The within-province component is an aver
-age of within-province inequalities
(calculated for each of the 27 provinces, then still including East Timor) weighted by GDP shares. (Appendix 1 provides a detailed account of the method.) This approach can therefore analyse in a co
-herent framework the contribution to overall regional income inequality of within-province as well as between-prov
-ince and between-region inequalities.
TheData
In order to estimate regional income in
-equality and conduct a two-stage nested
inequality decomposition analysis, we use district-level GDP data from the BPS
series GrossRegionalDomesticProductof Regencies/Municipalities inIndonesia (BPS 1997b, 1998a, 2000a), where GDP figures
are reported in constant 1993 prices. The district-level statistics provide data on
total GDP and GDP with the oil and gas sectors (including oil and gas extraction, oil refining and LNG) excluded. For Irian Jaya’s Fak-Fak district, the GDP figure
after exclusion of non-oilandgas mining is also reported, owing to that sector’s dominance in the economy.4
Regional GDP shows the amount of income generated within a region, rather than the income received by the region’s inhabitants. Much of the value added generated by a resource-rich region
through extraction activities has not his
-torically accrued to its population, but has gone instead to other regions or abroad (for example, the bulk of income derived from oil and gas has accruedto the central government, with only a small portion going to the governments and people of the producing regions). This is less so since the implementation in 2001 of Law No. 25/1999 on the financial bal
-ance between the centre and regional governments. However, it was the case for the years included in the present study, and for this reason our study, like previous studies of regional income dis
-parities in Indonesia, excludes the oil and gas sectors in the estimation of regional income inequality.5
We also use provincial non-oil and gas
GDP data from BPS’s GrossRegionalDo
-mesticProductofProvincesinIndonesiaby IndustrialOrigin(BPS 2000b) to conduct a shift and share analysis of provincial differences in the growth rate of GDP be
-tween 1997 and 1998 (appendix 2). REGIONALINCOMEINEQUALITY BEFORETHEECONOMICCRISIS Table 1 and figure 1 present the results of the two-stage nested inequality de
-composition analysis. Before the eco
-nomic crisis, overall regional income
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TABLE1 Two-StageNestedInequalityDecomposition,1993–98
(excludingtheoilandgassector)
1993 1994 1995 1996 1997 1998
Regionand TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b
Provincea (%) (%) (%) (%) (%) (%)
Sumatra(73) 0.024 1.7 0.025 1.7 0.028 1.9 0.028 1.8 0.031 2.0 0.032 2.3
DIAceh(10) 0.019 0.1 0.019 0.1 0.019 0.1 0.019 0.1 0.020 0.1 0.018 0.1
NSumatra(17) 0.043 1.0 0.042 1.0 0.038 0.9 0.037 0.8 0.038 0.8 0.034 0.8
WSumatra(14) 0.082 0.7 0.084 0.7 0.090 0.7 0.087 0.6 0.088 0.6 0.111 0.9
Riau(7) 0.225 1.8 0.240 1.9 0.257 2.0 0.274 2.1 0.299 2.3 0.303 2.8
Jambi (6) 0.033 0.1 0.033 0.1 0.036 0.1 0.037 0.1 0.037 0.1 0.036 0.1
SSumatra(10) 0.032 0.4 0.033 0.4 0.034 0.4 0.034 0.4 0.036 0.4 0.031 0.4
Bengkulu(4) 0.016 0.0 0.016 0.0 0.015 0.0 0.014 0.0 0.019 0.0 0.016 0.0
Lampung(5) 0.066 0.5 0.065 0.5 0.074 0.5 0.060 0.4 0.065 0.4 0.048 0.3
Java–Bali(116) 0.172 43.4 0.171 42.4 0.170 41.0 0.169 39.9 0.167 38.6 0.146 35.1
DKIJakarta(5) 0.074 5.0 0.079 5.2 0.084 5.4 0.089 5.6 0.090 5.5 0.118 7.1
WJava(25) 0.083 5.7 0.088 6.0 0.098 6.5 0.101 6.7 0.115 7.7 0.101 6.8
CJava(35) 0.161 6.7 0.172 6.9 0.178 6.8 0.186 7.0 0.187 6.7 0.166 6.6
DIYogyakarta(5) 0.059 0.3 0.059 0.3 0.062 0.3 0.064 0.3 0.069 0.3 0.068 0.3
EJava(37) 0.311 19.3 0.326 19.7 0.343 20.0 0.358 20.6 0.377 20.9 0.365 22.0
Bali(9) 0.097 0.7 0.097 0.7 0.097 0.7 0.097 0.7 0.097 0.7 0.090 0.7
Kalimantan(29) 0.066 1.8 0.065 1.7 0.069 1.8 0.070 1.9 0.069 1.8 0.076 2.3
WKalimantan(7) 0.110 0.8 0.109 0.7 0.107 0.7 0.105 0.7 0.105 0.7 0.103 0.8
CKalimantan(6) 0.033 0.1 0.033 0.1 0.036 0.1 0.038 0.2 0.039 0.2 0.039 0.2
SKalimantan(10) 0.066 0.4 0.064 0.4 0.060 0.4 0.054 0.3 0.058 0.3 0.069 0.4
EKalimantan(6) 0.025 0.3 0.022 0.2 0.021 0.2 0.026 0.3 0.024 0.2 0.027 0.3
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TABLE1(continued) Two-StageNestedInequalityDecomposition,1993–98
(excludingtheoilandgassector)
1993 1994 1995 1996 1997 1998
Regionand TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b TheilT Contrib.b
Provincea (%) (%) (%) (%) (%) (%)
Sulawesi(38) 0.002 0.0 0.003 0.1 0.004 0.1 0.006 0.1 0.006 0.1 0.008 0.2
NSulawesi(7) 0.038 0.1 0.038 0.1 0.037 0.1 0.038 0.1 0.041 0.1 0.046 0.2
CSulawesi(4) 0.002 0.0 0.001 0.0 0.001 0.0 0.001 0.0 0.001 0.0 0.002 0.0
SSulawesi(23) 0.068 0.7 0.071 0.7 0.071 0.7 0.072 0.7 0.077 0.7 0.070 0.7
SESulawesi(4) 0.011 0.0 0.010 0.0 0.015 0.0 0.011 0.0 0.013 0.0 0.017 0.0
Other(47) 0.059 0.8 0.055 0.7 0.052 0.7 0.049 0.6 0.059 0.7 0.056 0.8
NTB(7) 0.022 0.1 0.023 0.1 0.023 0.1 0.023 0.1 0.024 0.1 0.025 0.1
NTT(12) 0.047 0.1 0.050 0.1 0.058 0.2 0.063 0.2 0.060 0.2 0.056 0.2
ETimor(13) 0.079 0.1 0.081 0.1 0.081 0.1 0.077 0.1 0.083 0.1 0.073 0.1
Maluku(5) 0.041 0.1 0.046 0.1 0.051 0.2 0.055 0.2 0.063 0.2 0.062 0.2
IrianJaya(10) 0.112 0.4 0.111 0.4 0.109 0.3 0.106 0.3 0.141 0.5 0.136 0.5
Withinprovince 0.119 45.5 0.125 46.5 0.131 47.4 0.136 48.4 0.143 49.7 0.141 52.8
Betweenprovince 0.125 47.7 0.125 46.6 0.125 45.4 0.124 44.2 0.124 43.1 0.108 40.6
Betweenregion 0.018 6.9 0.019 7.0 0.020 7.2 0.021 7.4 0.021 7.2 0.018 6.6
Total 0.262 100.0 0.269 100.0 0.276 100.0 0.281 100.0 0.287 100.0 0.266 100.0
aFiguresinparenthesesarethenumberofkabupatenandkotamadya. b‘Contrib.’is the% contribution to totalregionalinequality
—Tdinappendix 1, equation (5). Thecontribution figure for a region isthe %
contribution ofthe region’s between-provinceinequality—(Yi/Y)Tpiin equation (5)—while thecontribution figure for a province isthe%
contribution oftheprovince’swithin-provinceinequality—(Yij/Y)Tij inequation(5).
Sources:BPS(1997b,1998aand2000a).
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Takahiro Akita and Armida Alisjahbana 206
inequality increased significantly, from 0.262 in 1993 to 0.287 in 1997. Decom
-position of overall inequality into the within-province, between-province and
between-region components reveals that
this increase was due mainly to the rise in the within-province inequality com
-ponent: its contribution to overall in
-equality rose from 45.5% to 49.7%. The between-region component also contrib
-uted to the increase, but only slightly. On the other hand, the between-prov
-ince component was very stable: its con
-tribution fell from 47.7% to 43.1%. Between-RegionInequality
Among the five regions, Kalimantan had the highest per capita GDP over the 1993–97 period; it was followed by Java–
Bali, Sumatra, Sulawesi and ‘Other’ (table 2). The modest increase in the be
-tween-region inequality component in
the pre-crisisperiod seems to have been
due to an increasing disparity between Sumatra/Java–Bali/Kalimantan and
Sulawesi/’Other’.
Between-ProvinceInequalities
Though the between-province inequality
component remained relatively constant over the 1993–97 period, each region re
-corded a distinct movement in between
-province inequality (figure 2). Largely because of the effect of Jakarta, Java–Bali’s
between-province inequality was the
highest. However, it exhibited a slight decreasing trend, mainly, it seems, be
-cause per capita GDP grew much faster in West Java than in the other Java–Bali
provinces. Accordingly, whereas West Java’s per capita GDP was the second lowest among the Java–Bali provinces in
0.00 0.10 0.20 0.30
93 94 95 96 97 98
Theil T
Within-province inequality component Between-province inequality component Between-region inequality component
FIGURE 1 Two-StageNestedInequalityDecomposition, 1993–98
(excludingtheoilandgassector)
Source: As for table 1.
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Regional Income Inequality in Indonesia 207
TABLE 2 PerCapitaNon-oilandGasGDP
(basedondistrict-leveldata)
Region and Per Capita GDP (Rp ‘000) Growth Rate (%)
Province
1993 1997 1998 1993–97 1997–98
Sumatra 1,342 1,718 1,584 6.4 –7.8
DI Aceh 1,308 1,644 1,522 5.9 –7.5
N Sumatra 1,649 2,187 1,981 7.3 –9.4
W Sumatra 1,449 1,816 1,679 5.8 –7.5
Riau 1,635 2,163 2,119 7.2 –2.0
Jambi 1,078 1,297 1,180 4.7 –9.0
S Sumatra 1,246 1,573 1,442 6.0 -8.3
Bengkulu 1,100 1,226 1,171 2.7 -4.4
Lampung 853 1,060 959 5.6 -9.5
Java–Bali 1,662 2,174 1,853 6.9 –14.8
DKI Jakarta 5,802 7,424 5,979 6.4 –19.5
W Java 1,377 1,882 1,547 8.1 –17.8
C Java 1,070 1,339 1,211 5.8 –9.5
DI Yogyakarta 1,391 1,760 1,563 6.1 –11.2
E Java 1,405 1,828 1,632 6.8 –10.7
Bali 2,010 2,579 2,447 6.4 –5.1
Kalimantan 2,044 2,682 2,585 7.0 –3.6
W Kalimantan 1,506 1,963 1,889 6.8 –3.8
C Kalimantan 1,968 2,539 2,373 6.6 –6.5
S Kalimantan 1,624 2,092 1,965 6.5 –6.1
E Kalimantan 3,516 4,619 4,559 7.1 –1.3
Sulawesi 1,008 1,264 1,201 5.8 –5.0
N Sulawesi 1,091 1,465 1,443 7.6 –1.5
C Sulawesi 949 1,138 1,070 4.7 –6.0
S Sulawesi 1,023 1,284 1,211 5.8 –5.7
SE Sulawesi 861 995 917 3.7 –7.8
Other 873 1,096 1,030 5.9 –6.0
NTB 719 897 859 5.7 –4.3
NTT 610 771 718 6.0 –6.9
E Timor 624 826 813 7.3 –1.5
Maluku 1,220 1,442 1,343 4.3 –6.9
Irian Jaya 1,398 1,829 1,694 6.9 –7.4
Total 1,521 1,974 1,738 6.7 –11.9
Sources: BPS (1997b, 1998a and 2000a). 1993, by 1997 it had become the third highest after Jakarta and Bali.6
Data on provincial GDP from Gross RegionalDomesticProductofProvincesin IndonesiabyIndustrialOrigin (BPS 1996,
1998b, 2000b) show that between 1993 and 1997 West Java’s non-oil and gas
manufacturing grew on average by 12.5% per annum—much more rapidly than the
national rate of 10.4%. In 1997 it ac
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Takahiro Akita and Armida Alisjahbana 208
counted for 37.5% of total non-oil and gas
GDP; the comparable figure for Indonesia as a whole was 24.5%.
East Java had a growth pattern simi
-lar to that of West Java. Again, the non
-oil and gas manufacturing sector was the engine of growth for the provincial economy, recording an annual average growth rate of 12% between 1993 and 1997, and accounting for 30.2% of total GDP in 1997. Unlike West and East Java, Jakarta’s GDP growth during the 1993–
97 period was led by the construction sector, which experienced an annual av
-erage growth rate of 12.6% and accounted for 15.4% of the province’s GDP in 1997. Jakarta’s gross fixed capital formation grew rapidly over this period, at an aver
-age annual rate of 9.1% (BPS, 1997a, 1999), contributing to the construction sector’s high growth rate.
In contrast with Java–Bali, the regions
of Sumatra, Kalimantan and Sulawesi recorded rising levels of between-prov
-ince inequality over the 1993–97 period
(table 1 and figure 2). Kalimantan had the second highest between-province in
-equality after Java–Bali, and experienced
a very slight increase. In Kalimantan, there are very large differences in per capita GDP between the richest province (East Kalimantan) and the other three provinces, and these differencesseem to have increased in relative terms. In 1997, the ratio of the per capita GDP of Kalimantan’s richest province to that of its poorest was 2.4. In contrast, Sumatra’s GDP was more evenly distributed among its provinces and population, but its be
-tween-province inequality increased over
the 1993–97 period . The disparities
between its richest province (North
FIGURE 2 Between-ProvinceInequalitybyRegion,1993–98
Source: As for table 1.
0.00 0.06 0.12 0.18
93 94 95 96 97 98
Theil T
Sumatra Java–Bali Kalimantan Sulawesi Other
Between-province inequality component
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Regional Income Inequality in Indonesia 209 Sumatra) and the other seven provinces
seem to have been increasing. While GDP is more evenly distributedamong prov
-inces and population in Sulawesi than in Sumatra, Sulawesi experienced a growth pattern similar to those of Sumatra and Kalimantan, with per capita GDP growing faster in the richest province (North Sulawesi) than in the other provinces. Thus, Sulawesi’s be
-tween-province inequality rose between
1993 and 1997.
Within-ProvinceInequalities
The within-province inequality compo
-nent increased significantly from 0.119 to 0.143 over the 1993–97 period (table 1
and figure 1). As a result, its contribu
-tion to overall regional inequality rose from 46% to 50%. The increase was due mainly to rises in the within-province
inequalitiesof four provinces in particu
-lar: Riau, Jakarta, West Java and East Java. Whereas their combined contribu
-tion to overall regional inequality was 32% in 1993, it had risen to 37% by 1997. Of the 23 other provinces, 15 experi
-enced an increase in within-province
inequality. However, their contributions to the total increase in the within
-province component of inequality were all negligible.
Of the eight provinces in Sumatra, six recorded an increase in within-province
inequality over the 1993–97 period. How
-ever, only Riau’s increase was significant: its contribution to overall regional in
-equality rose from 1.8% to 2.3%. In 1997, Riau had the highest level of within
-province inequality in Sumatra, followed by West Sumatra and Lampung. Riau’s level of inequality is due largely to the special position of Batam Island, located just 20 km southeast of Singapore, which has received preferential treatment from the central government as an export
-oriented industrial zone. Batam’s per capita non-oil and gas GDP of Rp 12.8
million was much higher than that of Riau’s other districts.
Among the Java–Bali provinces, all
but Bali experienced an increase in within-province inequality; in particu
-lar, Jakarta, West Java and East Java re
-corded significant increases. In 1997, East Java had the highest level of within
-province inequality,accounting for 21% of Indonesia’s overall regional inequal
-ity. This is due to the existence of a few very rich districts: urban Kediri, urban Surabaya, and Gresik. With its limited population, urban Kediri’s per capita GDP was the highest in the entire coun
-try at Rp 22.3 million, well above Cen
-tral Jakarta’s figure of Rp 16.8 million. While falling far short of Kediri, Sura
-baya and Gresik had per capita GDP of Rp 5.7 and 3.8 million, respectively,both significantly higher than that of most other districts in East Java.
Within Java–Bali, Central Java had the
second highest level of within-province
inequality in 1997. This was driven mainly by the districts of Kudus and ur
-ban Semarang, both of which had rela
-tively high levels of per capita GDP (Rp 5.0 and 4.2 million, respectively). West Java had the third highest level of in
-equality in 1997, much lower than the levels recorded for Central and East Java. This is due to the fact that, unlike Central and East Java, which include the primary cities of Semarang and Sura
-baya, respectively, West Java does not have an economicallydominant city and is relatively uniformly developed. In West Java, urban Tangerang had the highest level of per capita GDP (Rp 5.3 million), followed by Bekasi and Serang (each Rp 3.4 million), urban Cirebon (Rp 3.3 million), and urban Bandung (Rp 2.7 million). In other districts, per capita GDP ranged from Rp 1.0 to 2.5 million.
Among the Kalimantan provinces, West Kalimantan registered the highest
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Takahiro Akita and Armida Alisjahbana 210
level of within-province inequality in
1997. This was driven in part by urban Pontianak, which had the highest level of per capita GDP (Rp 4.2 million). In other districts, per capita GDP ranged from Rp 1.0 to Rp 2.4 million. It is inter
-esting to observe that while East Kali
-mantan had very high per capita non-oil
and gas GDP (Rp 4.6 million), its level of within-province inequality is one of the
lowest in Indonesia if the oil and gas sec
-tors are excluded.
Among the Sulawesi provinces, three experienced a slight increase in within
-province inequality. South Sulawesi had the highest level in 1997, due in large part to Ujung Pandang’s per capita GDP of Rp 2.5 million. Sulawesi had a very even distribution of income, however, not only among but also within provinces. Within the ‘Other’ category, Irian Jaya had the highest level of within-province inequal
-ity in 1997.
THEINITIALIMPACTOF THEECONOMICCRISISON REGIONALINCOMEINEQUALITY In this section, we assume that most of the change to be observed in 1998 reflects the initial impact of the economic crisis, and use 1998 district-level and provin
-cial GDP data to analyse this impact on regional income inequality.
The economy contracted significantly in 1998 as a result of the crisis. Accord
-ing to district-level data at 1993 constant
prices, national average per capita non
-oil and gas GDP fell by 11.9% in 1998 (table 2), retreating to its 1995 level.7How
-ever, the impact was very uneven across regions and provinces: while most prov
-inces in Java recorded a fall of 10–20% in
per capita GDP, the effects were much less severe in the Outer Islands.
Overall regional income inequality, as measured by the Theil index T based upon district-level GDP and population
data, declined from 0.287 in 1997 to 0.266
in 1998, which is essentially the same level as in 1993–94 (table 1 and figure 1).
The two-stage inequality decomposition
analysis reveals that about three-quarters
of the decline was due to the fall in the between-province inequality component;
its contribution to overall regional in
-equality decreased to 40.6% (from 43.1% in 1997).8Consequently,the contribution
of the within-province inequality compo
-nent to overall regional inequality rose sharply to 52.8% in 1998 (from 49.7%), even though the within-province inequal
-ity component itself recorded a slight fall. The between-region inequality compo
-nent declined also, though only slightly. Between-RegionInequality
The economic crisis reduced Java–Bali’s
per capita non-oil and gas GDP by 14.8%
in 1998 (table 2), bringing it to the same level as in 1994–95. Sumatra’s per capita
GDP also declined significantlyin 1998, though less so than that of Java–Bali; it
fell to the same level as in 1995–96. On
the other hand, the crisis seems to have affected Kalimantan and Sulawesi very little. As a result, between-region inequal
-ity fell somewhat from 0.021 in 1996 and 1997 to 0.018 in 1998 (table 1).
Between-ProvinceInequalities
Java–Bali’s between-province inequality
played a major role in the reduction of the between-province component of in
-equality: its contribution to overall re
-gional inequality fell from 38.6% to 35.1% in 1998 (table 1). Upon examining the trend in Java–Bali’s between-province
inequality since 1993, we find that the fall in 1998 is the continuationof a trend that began before 1997 (figure 2), though it is much sharper than in previous years and is due to different factors from those of the pre-crisis period, as explained
below.
The economic crisis affected Jakarta in a significant way. Its economy con
(12)
Regional Income Inequality in Indonesia 211 tracted by 19% in 1998, a reduction of
almost 20% in per capita GDP. The re
-sulting level is equivalent to that re
-corded in 1993 (table 2). The economies of West and East Java also contracted substantially,though by less than that of Jakarta.9The primary reason Java
–Bali
recorded a significant fall in between
-province inequality between 1997 and 1998 appears to have been Jakarta’s large decline in per capita GDP relative to other Java–Bali provinces. This con
-trasts with the 1993–97 period, which
saw a slight decline in Java–Bali’s
between-province inequality, because
per capita GDP grew much faster in West Java than in the other Java–Bali
provinces.
To analyse regional differences in the growth rate of GDP between 1997 and 1998, a shift and share analysis was per
-formed using provincial GDP data (ap
-pendix 2). Shift and share analysis aims to examine the factors determining the growth of a region by comparing the region’s growth with the growth of the nation as a whole. It decomposes the region’s actual total growth into three components: the regional share compo
-nent, the industry-mix shift component
and the competitive shift component. The sector classification used in this analy
-sis was: agriculture; non-oil and gas min
-ing; non-oil and gas manufacturing;gas,
electricity and water; construction; trade; transport and communication; finance; and services. The results are presented in table 3. The provinces of Jakarta, West Java and East Java contracted at much faster rates than the nation as a whole; thus the fall in their GDP exceeded the calculated fall if these provinces had con
-tractedat the same rate as the nation, i.e. total growth minus regional share was negative for these provinces. However, there are differences in the pattern of con
-traction between Jakarta and the prov
-inces of West and East Java: while the
industry-mix shift component played an
important role in the contraction of Jakarta, the competitive-shift component
played a dominant role in the contrac
-tion of West and East Java.10
In Jakarta, the non-oil and gas manu
-facturing, finance, and construction sec
-tors contributed significantly to a large negative industry-mix shift, reflecting the
region’s industrial structure, in which the combined GDP share of these three worst crisis-hit industries was about 60%. The
declines in these three sectors in the coun
-try as a whole were 18.2%, 17.3% and 33.3%, respectively, much larger than the negative growth rate of the total national economy. In Jakarta these three sectors contracted by 18.0%, 9.6% and 38.3%, respectively.
In West Java the non-oil and gas manu
-facturing, finance and construction sec
-tors contributed to a large negative competitive shift, with growth rates of
–21.4%, –40.3% and –46.2%, respectively.
The non-oil and gas manufacturing and
trade sectors contributedsignificantly to East Java’s large negative competitive shift, with growth rates of –24.3% and –17.8%, respectively. In West Java and
East Java the industry-mix shift compo
-nent was also negative, owing to very large negative growth in the non-oil and
gas manufacturingand construction sec
-tors, whose combined GDP shares in West and East Java were 44% and 36%, respectively. Nonetheless, the industry
-mix shift component (which is based upon the growth rates of industries in the nation) was much less significant than the competitive shift component, because of the prominence of the agricul
-tural sector in these provinces and be
-cause the agricultural sector was much less affected than other sectors by the cri
-sis in the nation as a whole.11
In contrast to Java–Bali, Kalimantan
and Sulawesi both recorded an increase in between-province inequality in 1998
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Takahiro Akita and Armida Alisjahbana 212
(table 1 and figure 2). The reason seems to have been that in both regions the richest province—East Kalimantan and North
Sulawesi, respectively—performed better
than the others , though all the provinces experienced negative growth in per capita GDP (table 2). According to the shift and share analysis, East Kalimantan and North Sulawesi had a positive total shift (= total regional growth minus regional
share of national growth), and more than three-quarters of the total shift was ac
-counted for by the competitive shift com
-ponent (table 3). East Kalimantan and North Sulawesi seem to have had a com
-petitive advantage in non-oil and gas
manufacturing and trade. In North Sula
-wesi these two sectors achieved large posi
-tive growth, whereas in East Kalimantan they neither grew nor contracted.
TABLE 3 ShiftandShareAnalysisforProvinces,1997–98,BasedonNon-oilandGasGDP
(Rpbillion)
Total Regional Total Shift Industry Competitive
Growth Share (C) = (A) –(B) Mix Shift Shift
Province (A) (B) = (D) + (E) (D) (E)
DI Aceh –380 –824 444 169 275
N Sumatra –2,733 –3,139 406 368 38
W Sumatra –520 –1,010 490 203 287
Riau –155 –1,080 925 –57 982
Jambi –282 –398 116 56 60
S Sumatra –1,082 –1,551 470 127 342
Bengkulu –109 –220 110 64 46
Lampung –500 –909 409 91 317
DKI Jakarta –12,163 –8,776 –3,387 –2,742 –645
W Java –12,744 –8,583 –4,161 –567 –3,595
C Java –5,750 –5,201 -549 170 –719
DI Yogyakarta –596 –667 71 31 40
E Java –10,424 –8,108 –2,316 –49 –2,267
Bali –306 –954 648 173 475
W Kalimantan –340 –911 571 94 476
C Kalimantan –297 –541 244 161 83
S Kalimantan –404 –781 377 135 242
E Kalimantan –317 –1,440 1,122 256 866
N Sulawesi –89 –475 386 88 299
C Sulawesi –92 –292 201 83 118
S Sulawesi –570 –1,248 678 302 377
SE Sulawesi –95 –207 112 36 77
NTB –125 –424 300 122 178
NTT –77 –358 281 119 162
Maluku –183 –388 205 49 156
Irian Jaya 931 –916 1,847 518 1,329
Total –49,402 –49,402 0 0 0
Source: BPS (2000b).
(14)
Regional Income Inequality in Indonesia 213 Sumatra’s between-province inequal
-ity was stable between 1997 and 1998 (table 1 and figure 2). Among Sumatra’s provinces, Riau performed relatively well. In 1998, it became the richest prov
-ince in Sumatra in terms of per capita GDP (table 2). Like East Kalimantan and North Sulawesi, it appears to have had a strong competitive advantage in non-oil
and gas manufacturing and trade; its competitive shift component explained most of its total shift (table 3).
Within-ProvinceInequalities
In Java–Bali, all provinces except Jakarta
experienced a fall in within-province
ineq uality between 1997 and 1998 (table 1). Jakarta’s within-province
inequality rose in 1998, but this was the continuation of a pre-crisis trend.
Jakarta’s rise in within-province in
-equality over the 1993–98 period seems
to have been due to a rising disparity between Central Jakarta, the second rich
-est district in Indonesia next to urban Kediri, and the other Jakarta districts. In 1998, Central Jakarta experienced an 8% fall in per capita GDP, while the other Jakarta districts recorded falls of 20% or more. Together with the fact that the dis
-tricts in West Java adjacent to Jakarta (Tangerang, Bekasi and Bogor) also re
-corded falls of 20% or more in per capita GDP, this indicates that the economic crisis had very strong adverse effects on the greater Jakarta metropolitan region (Jabotabek). The severe economic down
-turn in Jabotabek would have had enor
-mous direct and indirect effects not only on the other districts of Java–Bali but
also on the Outer Islands, for Jabotabek generated about a quarter of total Indo
-nesian non-oil and gas GDP, and there
are numerous interindustry linkages be
-tween Jabotabek and other regions, es
-pecially provinces in Java.
East Java had a slight decline in within-province inequality, but it still
had the highest level of inequality of all the provinces of Indonesia. Like Jabota
-bek, East Java’s major urban area seems to have been affected very adversely by the crisis; the relatively rich districts of Surabaya, Sidoarjo and Gresik experi
-enced per capita GDP growth rates of
–17%, –18% and –13%, respectively. On
the other hand, Indonesia’s richest dis
-trict, Kediri, recorded only a minor reduc
-tion in per capita GDP (–3%). Central
Java’s within-province inequality de
-clined significantly, almost retreating to its 1993 level. Again, the crisis hit Cen
-tral Java’s major urban areas hardest: Semarang, Kendal, Demak and Kudus recorded significant falls in per capita GDP (19%, 13%, 12% and 13%, respec
-tively). These observations, together with Jabotabek’s very severe economic condi
-tions in 1998, confirm that Indonesia’s economic crisis was a crisis afflicting urban Java (Booth 2000). It also hit most of the other parts of the Java–Bali region,
but to a lesser extent.
Figure 3 depicts the frequency distri
-bution of per capita GDP (using the natu
-ral log scale) of Java–Bali’s districts in
1995, 1997 and 1998. First, the mode of the distribution shifted from the 7.0–7.2
range in 1997 (corresponding to a per capita GDP range of Rp 1.10 to Rp 1.34 million) to the 6.8–7.0 range in 1998 (cor
-responding to a per capita GDP range of Rp 0.90 to Rp 1.10 million). Second, the number of districts whose natural log of per capita GDP is less than or equal to 7.0 (corresponding to per capita GDP of less than or equal to Rp 1.10 million) increased from 40 to 55 (of 116 districts) in 1998, slightly more than in 1995 (53 districts). Third, the number of districts whose natu
-ral log of per capita GDP is greater than or equal to 7.6 (corresponding to per capita GDP of greater than or equal to Rp 2 mil
-lion) fell from 42 to 33 in 1998, a smaller number than in 1995 (36 districts). In sum, the economic crisis seems to have shifted
(15)
Takahiro Akita and Armida Alisjahbana 214
Java–Bali’s distribution to its pre-1995
level.
In Sumatra, all provinces except West Sumatra and Riau experienced a fall in within-province inequality in 1998. Lam
-pung recorded a significant decrease in its within-province inequality, owing
mainly to a substantial reduction in the per capita GDP of Bandar Lampung, the richest district in the province. Among Sumatra’s districts, Banda Aceh, Tebing Tinggi, Medan, Binjai, Sawah Lunto, Palembang and Bandar Lampung regis
-tered relatively large falls in per capita GDP (around 15%). But Batam, the rich
-est district in Sumatra, was not signifi
-cantly affected by the crisis, suffering only a 4% decline in per capita GDP. As in Java–
Bali, the economic crisis in Sumatra seems to have hit major urban areas hardest.
In Kalimantan, the province of South Kalimantan recorded a significant in
-crease in within-province inequality,be
-cause per capita GDP grew (by 3%) in Kota Baru, its richest district, but fell sub
-stantially in its second and thirdrichest districts (Barito Kuala and Banjarmasin) (by 9% and 14%, respectively). Among the municipalities (kotamadya) in Kali
-mantan (Pontianak, Palangka Raya, Banjarmasin, Balikpapan and Sama
-rinda), only Banjarmasin had a large decine in per capita GDP, signifying that the crisis had few adverse effects on ur
-ban Kalimantan.
In Sulawesi, all provinces experienced a slight increase in within-province in
-equality in 1998, with the exception of South Sulawesi, in whose richest district, Ujung Pandang, per capita GDP fell sig
-nificantly (by 9%). In North Sulawesi, four of the seven districts (Minahasa, Sangile Talaud, Gorontalo and Bitung) recorded rises in per capita GDP, though growth rates were much lower than in the pre-crisis period (1–3% vs 6–12%).
FIGURE 3 FrequencyDistributionofthePerCapitaGDPofJava–BaliDistricts
(naturallogscale)
Source: As for table 1.
0 10 20 30 40
6.0 6.4 6.8 7.2 7.6 8.0 8.4 8.8
Per capita GDP (log scale) No. of districts
1995 1997 1998
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Regional Income Inequality in Indonesia 215
The crisis affected other Sulawesi dis
-tricts adversely, but the effects seem to have been uniform across districts.
Figure 4 presents the frequency distri
-bution of per capita GDP (using the natu
-ral log scale) in Outer Island districts in 1995, 1997 and 1998. First, the distribu
-tion shifted to the left in 1998 and back
-tracked to appro ximately the 1995 pattern, but the number of districts in the 6.8–7.2 range (corresponding to per
capita GDP of Rp 0.90–1.34 million) was
much smaller in 1998 than in 1995 (61 vs 69 districts). Second, the number of dis
-tricts falling in the 6.2–6.8 range (corre
-sponding to per capita GDP of Rp 0.49–0.90 million) in 1997 was the same
as in 1995, at 35, but by 1998 it had in
-creased to 39. Third, the number of dis
-tricts whose natural log of per capita GDP is greater than or equal to 7.6 (correspond
-ing to per capita GDP of Rp 2 million or more) fell from 49 to 38 in 1998, only one
more than in 1995. In sum, the economic crisis shifted the Outer Islands’ per capita GDP distribution to the left, but the ef
-fects were not as large as in Java–Bali. It
is interesting to note that, in contrast to Java–Bali, the Outer Islands had more dis
-tricts in the 6.4–6.6 range (correspond
-ing to per capita GDP of Rp 0.60–0.74
million) than in the 6.6–6.8 range (corre
-sponding to per capita GDP of Rp 0.74–
0.90 million). This is because the Outer Islands include the very poor provinces of West and East Nusa Tenggara and (at the time of the study) East Timor.
CONCLUDINGREMARKS
As measured by a Theil index based on district-level GDP and population data,
overall regional income inequality in
-creased significantly over the 1993–97
period (from 0.262 to 0.287), during which time Indonesia achieved an an
-nual average growth rate of more than
FIGURE 4 FrequencyDistributionofthePerCapitaGDPofOuterIslandsDistricts
(naturallogscale)
Source: As for table 1.
0 10 20 30 40
6.0 6.4 6.8 7.2 7.6 8.0 8.4 8.8
Per capita GDP (log scale) No. of districts
1995 1997 1998
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Takahiro Akita and Armida Alisjahbana 216
7%. This finding does not conflict with the fact that GDP and population data from the provincial income statistics (BPS 1996, 1998b and 2000b, which do not include district-level data) suggested
quite stable regional inequality over the same period because, according to the two-stage nested inequality decomposi
-tion analysis, the increase is due mainly to a rise in the within-province inequal
-ity component, especially in the prov
-inces of Riau, Jakarta, West Java and East Java.12The between
-province inequality
component increased also, but only very slightly, whereas the between-region in
-equality component was very stable. Within-province inequality thus played
an increasingly important role in the de
-termination of overall regional income inequality, as measured using district
-level data. In 1997 it accounted for about half of overall regional income inequal
-ity, whereas the between-province and
between-region inequality components
contributed 43.1% and 7.2%, respectively. This result suggests that it would be very misleading to base a judgment about whether regional inequality is increas
-ing or decreasing solely upon provincial data, especially when the economy is growing very rapidly and undergoing significantstructural change.
In terms of per capita GDP, the eco
-nomic crisis caused the Indonesian economy to revert to its 1995 level. The impacts were very uneven across prov
-inces and districts, however. Overall re
-gional income inequality, as measured using district-level data, declined to 0.266
in 1998, which corresponded to the level prevailing in 1993–94. The two-stage
nested inequality decomposition analy
-sis shows that about three-quarters of the
decline was due to the fall in the between
-province inequality component. The Java–Bali region played a prominent role
in the fall in this component. Jakarta was the hardest-hit province in Indonesia,
owing to its heavy reliance on the non
-oil and gas manufacturing, finance, and construction sectors, which were most adversely affected by the crisis; Jakarta’s per capita GDP fell by almost 20%, re
-verting to the level recorded in 1993. The economies of other Java provinces also contracted significantly,but the impacts were less severe than in Jakarta. As a re
-sult, the per capita GDP gap between Jakarta and the other Java–Bali provinces
narrowed. Among the Outer Islands, Sumatra experienced a 7% fall in per capita GDP, but the economic crisis does not seem to have affected Kalimantan and Sulawesi very severely. As a result, the between-region inequality compo
-nent fell in 1998.
The impact of the economic crisis was borne disproportionately by Java–Bali’s
major urban areas. In Jakarta and West Java, the Jabotabek districts were severely affected; with the exception of Central Jakarta, all of them recorded a decline of 20% or more in per capita GDP. As a re
-sult, within-province inequality fell in
West Java. It also fell in Central and East Java, again because of a very large de
-cline in per capita GDP in their major urban districts. These observations con
-firm that Indonesia’s economic crisis was a crisis afflicting urban Java. However, with the exception of Batam, Sumatra’s major urban districts also experienced a relatively large decline in per capita GDP. Thus the crisis seems to have adversely affected Sumatra’s urban areas, as did those of Java–Bali.
(18)
Regional Income Inequality in Indonesia 217 NOTES
* Takahiro Akita, International Develop
-ment Program, International University
of Ja pa n, Yam a to-ma ch i, M in am i
Uonuma-gun, Niigata 949-7277, Japan;
e-mail address: akita@iuj.ac.jp; Armida
S. Alisjahbana, Department of Econom
-ics and Development Studies, Faculty of
Economics, Padjadjaran University,
Bandung, Indonesia. The authors are
grateful to the International University
of Japan and the Japan Society for the
Promotion of Science (Grant-in-Aid for
Scientific Research No. 12630073) for
their financial support, and to anony
-mous referees for their helpful com
-ments.
1 William son (1 96 5) intr od uced the
weighted coefficient of variation (the
coefficient of variation weighted by
population) as a measure of regional
income inequality. The large increase in
the coefficient between the 1985–93 and
the 1993–97 periods is due solely to the
change in base year for constant price
estimates between these periods.
2 These include Akita and Lukman (1995);
Es ma ra (1 97 5); Ga rcia Garcia a nd
Soelistianingsih (1998); and Uppal and
Budiono Sri Handoko (1986).
3 An inequality index is said to be addi
-tively decomposable if total inequality
can be written as the sum of between
-group and within-group inequalities.
‘Mean independence’ implies that the
in dex re ma ins un cha ng ed if eve ry
region’s income is changed by the same
proportion, while ‘population-size in
-dependence’ indicates that the index re
-mains un chan ged if the n umbe r of
people in each region is changed by the
same proportion, i.e. the index depends
only on the relative population frequen
-cies in each region and not on the abso
-lute population frequencies. Finally, the
Pigou–Dalton principle of transfers im
-plies that any income transfer from a
richer to a poorer region that does not
reverse their relative ranks in income
reduces the value of the index.
4 In Fak-Fak, non-oil and gas mining ac
-counts for more than 90% of total GDP.
5 For Irian Jaya’s Fak-Fak district, non-oil
and gas mining is also excluded, for the
same reason as the oil and gas sectors.
6 For an unknown reason, West Java’s
GDP is shown as much larger in Gross
Regional Domestic Product ofRegencies/ Municipalities inIndonesiathan in Gross RegionalDomesticProductofProvincesin Indonesia. For example, West Java’s non
-oil and gas GDP in 1997 was Rp 76,150
billion in the district (regency/muni
-cipality ) stati sti cs (BPS 20 00a ), but
Rp 68,010 billion in the provincial sta
-tistics (BPS 2000b). In other provinces,
the discrepancy is significantly smaller
over the 1993–97 period (all are within
3% of each other).
7 If provincial GDP data are used, the de
-cline is 13.9% (BPS 2000b).
8 Since we use only 1998 data, care should
be taken in interpreting the results.
District-level GDP data for 1999 were not
available at the time of writing, so we
do not know whether the within-prov
-ince inequality component fell or rose
in that year. But regional income in
-equality as measured on the basis of pro
-vincial GDP data (BPS 2000b) declined
further in 1999, mainly because of the
fall in the between-province inequality
component.
9 The 1997 figure for East Java’s GDP in
GrossRegionalDomesticProductofRegen
-cies/MunicipalitiesinIndonesiawas smaller
than that in GrossRegionalDomesticProd
-uctofProvincesinIndonesia(Rp 62,815 vs
Rp 64,259 billion); in 1998 the former
became larger (Rp 56,606 vs Rp 53,825
billion) (BPS 2000a, 2000b). Therefore,
the rate of decline in GDP appears much
smaller when the statistics of regencies/
municipalities are used than when pro
-vincial statistics are used (–10% vs –16%).
10 The industry-mix shift component ex
-plains that part of the growth differ
-ence that is due to the difference in the
composition of industries between the
r e gion an d the n a tion , wh e r e th e
gr ow th diffe re nce is tota l re gion al
growth minus regional share of na
-tional growth. The competitive shift
component explains that part of the
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Takahiro Akita and Armida Alisjahbana 218
growth difference that is due to the
difference in the growth rates of in
-dustries between the region and the
nation.
11 This is true even though the agricultural
sectors in West and East Java contracted
by 7.6% and 5.0%, respectively, both of
which rates exceeded the 2.6% negative
growth rate in the agricultural sector of
the country as a whole.
12 Household expenditure data from the
National Socio-Economic Surveys (Su
-senas) also indicate an increase in in
-equality, as measured by Theil indices
and the Gini coefficient, between 1993
and 1996 (Akita and Szeto 2000).
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-tively Decomposable Inequality Mea
-sures’, Econometrica 48 (3): 613–25.
Tsakloglou, P. (1993), ‘Aspects of Inequal
-ity in Greece: Measurement, Decompo
-sition and Intertemporal Change, 1974,
1982’, JournalofDevelopment Economics40
(1): 53–74.
Tsui, K.Y. (1993), ‘Decomposition of China’s
Regional Inequalities’, JournalofCompara
-tiveEconomics17 (3): 600–27.
Uppal, J.S., and Budiono Sri Handoko (1986),
‘Regional Income Disparities in Indo
-nesia’, EkonomidanKeuanganIndonesia34
(3): 286–304.
Williamson, J.G. (1965), ‘Regional Inequal
-ity and the Process of National Devel
-opment: A Description of the Patterns’,
EconomicDevelopmentandCulturalChange
13 (4): 3–45.
(21)
Takahiro Akita and Armida Alisjahbana 220
APPENDIX1:
TWO-STAGENESTEDINEQUALITY
DECOMPOSITION METHOD
This appendix presents the two-stage
nested inequality decomposition method, an extension of the one-stage method of
inequality decomposition(Anand 1983). Numerous studies have used the latter to analyse factors determining income in
-equality, but most have applied it to analysis of interpersonal or interhouse
-hold income inequality (see, for example, Akita and Lukman 1999; Akita, Lukman and Yamada 1999; Akita and Szeto 2000; Anand 1983; Ching 1991; Estudillo 1997; Glewwe 1986; Ikemoto 1985; Jenkins 1995; Mookherjee and Shorrocks 1982; Tsakloglou 1993; and Tsui 1993).
We consider the following hierarchi
-cal structure of a country: region–
province–district. With a district as the
underlying regional unit, overall re
-gional income inequality can be mea
-sured by the following Theil index (Theil index T).
÷ ÷ ÷ ø ö ç ç ç è æ ÷÷ ø ö çç è æ
ååå
N n Y y Y y T ijk ijki j k
ijk
d= log , (1)
where
yijk is the income of district k in prov
-ince j in region i;
Y is the total income of all districts = yijk
k
å
jå
iå
æ è ç ç ö ø ÷ ÷ ;nijk is the total population of district k
in province j in region i; and
N is the total population of all dis
-tricts = nijk k
å
jå
iå
æ è ç ç ö ø ÷ ÷ .If we define Tdi as follows to measure
between-district income inequality for re
-gion i,
÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷÷ ø ö çç è æ
åå
i ijk i ijkj k i
ijk di N n Y y Y y T = log
, (2)
then Td in equation (1) will be decom
-posed into
BR di i i i i i i di i i d T T Y Y N NY Y Y Y T Y Y T + ÷ ø ö ç è æ = ÷ ÷ ÷ ø ö ç ç ç è æ ÷ ø ö ç è æ + ÷ ø ö ç è æ =
å
å
å
log (3) whereYi is the total income of region i
= yijk
k
å
jå
æ è ç ç ö ø ÷ ÷ ;Ni is the total population of region i
= nijk
k
å
jå
æ è ç ç ö ø ÷÷ ; and
÷ ÷ ÷ ø ö ç ç ç è æ ÷ ø ö ç è æ =
å
N N Y Y Y Y T i i i i BR logmeasures income inequality between re
-gions.
Therefore, the overall regional income inequality Td is the sum of the within
-region component and the between
-region component. Equation (3) is the ordinary one-stage inequality decompo
-sition equation.
Next, if we define Tijas follows to mea
-sure within-province income inequality
for province j in region i,
÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷ ÷ ø ö ç ç è æ
å
ij ijk ij ijk k ij ijk ij N n Y y Y y T = log,
(1)
NOTES
* TakahiroAkita,International Develop-mentProgram,International University of Ja pa n, Yam a to-ma ch i, M in am i Uonuma-gun,Niigata949-7277,Japan; e-mailaddress:akita@iuj.ac.jp; Armida S.Alisjahbana,Departmentof Econom-icsandDevelopment Studies,Facultyof Economics, Padjadjaran University, Bandung,Indonesia.The authors are gratefultothe International University of Japanand the JapanSociety for the PromotionofScience(Grant-in-Aid for ScientificResearch No. 12630073) for theirfinancial support,and to anony -mous referees for their helpful com -ments.
1 William son (1 96 5) intr od uced the weighted coefficient ofvariation (the coefficientof variation weighted by population) asa measure ofregional incomeinequality. Thelargeincreasein thecoefficient betweenthe1985–93and the1993–97periodsisduesolelytothe changeinbase year forconstant price estimatesbetweentheseperiods. 2 TheseincludeAkitaandLukman(1995);
Es ma ra (1 97 5); Ga rcia Garcia a nd Soelistianingsih(1998);andUppal and BudionoSriHandoko(1986).
3 Aninequalityindexissaidtobe addi -tivelydecomposable iftotalinequality can bewrittenasthe sum of between-group and within-group inequalities. ‘Meanindependence’ impliesthat the in dex re ma ins un cha ng ed if eve ry region’sincomeischangedbythesame proportion, while‘population-size in-dependence’ indicatesthattheindex re-mains un chan ged if the n umbe r of peopleineachregionischangedbythe sameproportion, i.e.theindexdepends onlyontherelativepopulation frequen-ciesineachregionandnotonthe abso-lutepopulationfrequencies. Finally,the Pigou–Daltonprincipleoftransfersim -pliesthat anyincome transfer from a richertoa poorer region thatdoes not reversetheirrelativeranks inincome reducesthevalueoftheindex.
4 InFak-Fak,non-oilandgasminingac -countsformorethan90%oftotalGDP.
5 ForIrianJaya’sFak-Fakdistrict,non-oil andgasminingisalsoexcluded,forthe samereasonastheoilandgassectors. 6 For an unknown reason, WestJava’s
GDP isshownas muchlargerinGross
Regional Domestic Product ofRegencies/
Municipalities inIndonesia thaninGross
RegionalDomesticProductofProvincesin
Indonesia. Forexample,WestJava’snon
-oilandgasGDPin1997wasRp76,150 billionin the district (regency/muni-cipality ) stati sti cs (BPS 20 00a ), but Rp68,010 billionin theprovincial sta-tistics(BPS2000b).In other provinces, the discrepancy issignificantly smaller overthe1993–97period (allarewithin 3%ofeachother).
7 IfprovincialGDPdataareused,the de-clineis13.9%(BPS2000b).
8 Sinceweuseonly1998data,careshould be taken in interpreting the results. District-levelGDPdatafor1999werenot availableatthe time of writing,sowe donotknowwhether thewithin-prov -ince inequalitycomponent fell or rose in that year. But regional income in-equalityasmeasuredonthebasisof pro-vincialGDPdata(BPS 2000b)declined further in1999, mainlybecauseofthe fallinthebetween-provinceinequality component.
9 The 1997figureforEastJava’sGDPin
GrossRegionalDomesticProductofRegen
-cies/MunicipalitiesinIndonesia wassmaller
thanthatinGrossRegionalDomesticProd
-uctofProvincesinIndonesia (Rp62,815vs
Rp 64,259billion);in 1998 theformer becamelarger(Rp 56,606vs Rp53,825 billion)(BPS2000a,2000b). Therefore, therateofdeclineinGDPappearsmuch smallerwhenthestatisticsofregencies/ municipalities areusedthanwhen pro-vincialstatisticsareused(–10%vs–16%). 10 The industry-mixshift componentex -plains that part of the growth differ -encethatisduetothedifferenceinthe composition of industriesbetweenthe r e gion an d the n a tion , wh e r e th e gr ow th diffe re nce is tota l re gion al growth minus regional share of na -tional growth. The competitive shift component explains that part of the
(2)
growth difference that is due to the difference in the growth rates of in-dustries between the regionand the nation.
11 Thisistrueeventhoughtheagricultural sectorsinWestandEastJavacontracted by7.6%and5.0%,respectively,bothof whichratesexceededthe2.6%negative
growthrateintheagricultural sectorof thecountryasawhole.
12 Household expenditure data fromthe National Socio-EconomicSurveys(Su -senas)alsoindicatean increasein in -equality,asmeasuredby Theilindices andtheGini coefficient, between1993 and1996(AkitaandSzeto2000).
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Science,forthcoming.
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Akita,T.,andR.A.Lukman(1995), ‘Interre-gion al In equalities in Ind on esia: A Sectoral Decomposition Analysis for
1975–92’,Bulletin of IndonesianEconomic
Studies 31(2):61–81.
Akita,T.,andR.A.Lukman(1999),‘Spatial PatternsofExpenditureInequalities in Indonesia,1987,1990and1993’,Bulletin
of Indonesian Economic Studies 35 (2):
65-88.
Akita,T., R.A. Lukmanand Y. Yamada (1999),‘InequalityintheDistribution of HouseholdExpenditures inIndonesia:A TheilDecomposition Analysis’, TheDe
-velopingEconomies37(2):197–221.
Akita,T.,andJesseJ.K.Szeto(2000),‘Inpres DesaTertinggal(IDT)Program and In-donesianRegionalInequality’,AsianEco
-nomicJournal 14(2):167–86.
Anand, S.(1983),Inequality and Povertyin
Malaysia:Measurement andDecomposition,
AWorldBankResearchPublication, Ox-fordUniversityPress,NewYork. Armstrong,H.W.,andJ.Taylor(1985),Re
-gionalEconomics andPolicy, Blackwell,
London.
Booth,A.(2000),‘TheImpactofthe Indone-sian Crisis on Welfare: What Do We KnowTwo YearsOn?’, inC.Manning and P.vanDiermen (eds),Indonesiain
Transition: SocialAspectsofReformasiand
Crisis,InstituteofSoutheastAsianStud
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Bourguignon, F.(1979),‘Decomposable In-comeInequalityMeasures’,Econometrica 47(4):901–20.
BPS(1996),GrossRegionalDomesticProductof
ProvincesinIndonesiabyIndustrialOrigin,
1993–1995,Jakarta.
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ofProvinces in Indonesiaby Expenditure,
1993–1996,Jakarta.
BPS(1997b),GrossRegionalDomesticProduct
of Regencies/Municipalities in Indonesia,
1993–1995,Jakarta.
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of Regencies/Municipalities in Indonesia,
1994–1997,Jakarta.
BPS(1998b),GrossRegionalDomesticProduct
ofProvincesinIndonesiabyIndustrialOri
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ProvincesinIndonesiabyExpenditure,1995–
1998,Jakarta.
BPS(2000a),GrossRegionalDomesticProduct
of Regencies/Municipalities in Indonesia,
1995–1998,Jakarta.
BPS(2000b),GrossRegionalDomesticProduct
ofProvincesinIndonesiabyIndustrialOri
-gin,1996–1999,Jakarta.
BPS(2001), Statistical Yearbook ofIndonesia 2000,Jakarta.
Ching, P. (1991),‘SizeDistribution of In -comeinthePhilippines’,inT.Mizoguchi (ed.),MakingEconomiesMoreEfficientand
MoreEquitable:FactorsDeterminingIncome
Distribution,Kinokuniya Company Ltd,
Tokyo:157–78.
Esmara,H.(1975),‘RegionalIncome Dispari-ties’,BulletinofIndonesianEconomicStud
-ies 11(1):41–57.
(3)
Estudillo,J.(1997),‘IncomeInequalityinthe Philippines, 1961–91’, The Developing
Economies 35(1):68–95.
García García,J.,and L.Soelistianingsih (1998),‘WhyDoDifferencesinProvincial Income PersistinIndonesia?’,Bulletinof
IndonesianEconomicStudies 34(1):95–120.
Glewwe,P.(1986),‘TheDistribution of In-comeinSriLankain1969–70and1980– 81:ADecomposition Analysis’,Journalof
Development Economies 24(2):255–74.
Ikemoto, Y.(1985),‘IncomeDistribution in Malaysia:1957–80’,TheDevelopingEcono
-mies 23(4):347–67.
Jenkins, S.P. (1995),‘Accounting for In -equalityTrends:Decomposition Analy-sis for the UK, 1971–86’, Economica 62 (246):29–63.
Mookherjee, D.,andA.Shorrocks(1982),‘A Decomposition AnalysisoftheTrendin UKIncomeInequality’,TheEconomicJour
-nal 92(367):886–902.
Shorrocks,A.F.(1980),‘TheClassof Addi-tively Decomposable Inequality Mea -sures’,Econometrica 48(3):613–25. Tsakloglou,P.(1993),‘Aspectsof
Inequal-ityinGreece:Measurement, Decompo-sitionandIntertemporalChange,1974, 1982’,JournalofDevelopment Economics 40 (1):53–74.
Tsui,K.Y.(1993),‘DecompositionofChina’s RegionalInequalities’,JournalofCompara
-tiveEconomics 17(3):600–27.
Uppal,J.S.,andBudionoSriHandoko(1986), ‘Regional Income Disparities in Indo -nesia’,EkonomidanKeuanganIndonesia 34 (3):286–304.
Williamson,J.G.(1965),‘Regional Inequal-ity andthe Processof National Devel -opment:ADescriptionofthePatterns’,
EconomicDevelopmentandCulturalChange
13(4):3–45.
(4)
APPENDIX
1:
TWO
-
STAGE
NESTED
INEQUALITY
DECOMPOSITION
METHOD
This
appendix
presents
the
two
-
stage
nested
inequality
decomposition
method,
an
extension
of
the
one
-
stage
method
of
inequality
decomposition
(Anand
1983).
Numerous
studies
have
used
the
latter
to
analyse
factors
determining
income
in
-equality,
but
most
have
applied
it
to
analysis
of
interpersonal
or
interhouse
-hold
income
inequality
(see,
for
example,
Akita
and
Lukman
1999;
Akita,
Lukman
and
Yamada
1999;
Akita
and
Szeto
2000;
Anand
1983;
Ching
1991;
Estudillo
1997;
Glewwe
1986;
Ikemoto
1985;
Jenkins
1995;
Mookherjee
and
Shorrocks
1982;
Tsakloglou
1993;
and
Tsui
1993).
We
consider
the
following
hierarchi
-cal
structure
of
a
country:
region
–
province
–
district.
With
a
district
as
the
underlying
regional
unit,
overall
re
-gional
income
inequality
can
be
mea
-sured
by
the
following
Theil
index
(Theil
index
T
).
÷ ÷ ÷ ø ö ç ç ç è æ ÷÷ ø ö çç è æ
ååå
N n Y y Y y T ijk ijki j k ijk
d= log
,
(1)
where
yijk
is
the
income
of
district
k
in
prov
-ince
j
in
region
i
;
Y
is
the
total
income
of
all
districts
= yijk
k
å
jå
iå
æ è ç ç ö ø ÷ ÷;
nijk
is
the
total
population
of
district
k
in
province
j
in
region
i
;
and
N
is
the
total
population
of
all
dis
-tricts
= nijkk
å
jå
iå
æ è ç ç ö ø ÷ ÷.
If
we
define
Tdias
follows
to
measure
between
-
district
income
inequality
for
re
-gion
i
,
÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷÷ ø ö çç è æ
åå
i ijk i ijkj k i
ijk di N n Y y Y y
T = log
,
(2)
then
Tdin
equation
(1)
will
be
decom
-posed
into
BR di i i i i i i di i i d T T Y Y N NY Y Y Y T Y Y T + ÷ ø ö ç è æ = ÷ ÷ ÷ ø ö ç ç ç è æ ÷ ø ö ç è æ + ÷ ø ö ç è æ =å
å
å
log(3)
where
Yi
is
the
total
income
of
region
i
= yijk
k
å
jå
æ è ç ç ö ø ÷ ÷;
Ni
is
the
total
population
of
region
i
= nijk
k
å
jå
æ è ç ç ö ø ÷÷
;
and
÷ ÷ ÷ ø ö ç ç ç è æ ÷ ø ö ç è æ =
å
N N Y Y Y Y T i i i i BR logmeasures
income
inequality
between
re
-gions.
Therefore,
the
overall
regional
income
inequality
T
dis
the
sum
of
the
within
-region
component
and
the
between
-region
component.
Equation
(3)
is
the
ordinary
one
-
stage
inequality
decompo
-sition
equation.
Next,
if
we
define
T
ijas
follows
to
mea
-sure
within
-
province
income
inequality
for
province
j
in
region
i
,
÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷ ÷ ø ö ç ç è æ
å
ij ijk ij ijk k ij ijk ij N n Y y Y yT = log
,
(5)
then
Tdiin
equation
(2)
can
be
further
decomposed
into
pi ij j i ij i ij i ij j i ij ij j i ij di T T Y Y N N Y Y Y Y T Y Y T + ÷÷ ø ö çç è æ = ÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷ ÷ ø ö ç ç è æ + ÷ ÷ ø ö ç ç è æ =å
å
å
log(4)
where
Yij
is
the
total
income
of
province
j
in
region
i
= yijkk
å
æ è ç ç ö ø ÷ ÷;
Nij
is
the
total
population
of
province
j
in
region
i
= nijk kå
æ è ç ç ö ø ÷÷
;
and
÷ ÷ ÷ ÷ ø ö ç ç ç ç è æ ÷÷ ø ö çç è æ =
å
i ij i ij j i ij pi N N Y Y Y Y T logmeasures
income
inequality
between
provinces
in
region
i
.
By
substituting
Tdiin
equation
(4)
into
equation
(3),
we
obtain:
BR BP WP BR pi i i ij i j ij BR j pi ij i ij i i d T T T T T Y Y T Y Y T T T Y Y Y Y T + + = + ÷ ø ö ç è æ + ÷ ÷ ø ö ç ç è æ = + ú ú û ù ê ê ë é + ÷÷ ø ö çç è æ ÷ ø ö ç è æ =
å
åå
å
å
(5)
Equation
(5)
is
the
two
-
stage
nested
in
-equality
decomposition
equation,
in
which
overall
regional
income
inequality
is
decomposed
into
the
within
-province
component
(
T
WP),
the
between
-province
component
(
T
BP),
and
the
between
-
region
component
(
T
BR).
The
within
-
province
component
is
a
weighted
average
of
within
-
province
income
in
-equalities
(
T
ij),
while
the
between
-
province
component
is
a
weighted
average
of
be
-tween
-
province
income
inequalities
(
T
pi).
APPENDIX
2:
SHIFT
AND
SHARE
ANALYSIS
Shift
and
share
analysis
is
a
technique
that
has
been
widely
used
to
examine
the
factors
determining
regional
growth
(see,
for
example,
Armstrong
and
Tay
-lor
1985).
It
divides
a
region’s
growth
into
three
components.
The
first
is
the
region’s
share
of
national
growth
(RS).
If
a
region
grows
at
the
national
average
rate,
it
will
maintain
its
share
of
national
output.
The
formula
for
calculating
RS
for
a
particular
sector
can
be
expressed
in
the
following
way:
÷÷ ø ö çç è æ D = N N i i E E e RS
,
where
ei
=
regional
output
in
sector
i
at
the
beginning
of
the
period;
EN
=
total
national
output
at
the
begin
-ning
of
the
period;
and
DEN
=
the
change
in
total
national
output.
The
second
component,
the
industry
-mix
shift
component
(IMS),
is
based
on
the
premise
that
a
region
that
has
a
rela
-tively
larger
share
of
output
in
fast
-
grow
-ing
industries
should
grow
faster
than
the
nation
as
a
whole.
IMS
for
a
single
sector
can
be
defined
as:
÷÷ ø ö çç è æ D -D = N N i i i i E E E E e IMS
(6)
where
Ei
=
national
output
in
sector
i
at
the
beginning
of
the
period;
and
DEi
=
the
change
in
national
output
in
sector
i
.
The
third
component
is
called
the
competitive
shift
component
(CS).
A
re
-gion
may
have
a
competitive
advantage
in
some
industries
relative
to
other
re
-gions
because
its
environment
is
condu
-cive
to
the
growth
of
these
industries.
CS
for
a
single
sector
can
be
defined
as:
÷÷ ø ö çç
è
æD -D
=
i i i
i i i
E E e
e e
CS
,
where
Dei=
the
change
in
regional
output
in
sector
i
.
The
output
growth
of
a
particular
sec
-tor
(sector
i
)
of
a
region,
Dei,
is
now
given
as
the
sum
of
these
three
components:
÷÷ ø ö çç
è
æ D
-D + ÷÷ ø ö çç
è
æ D
-D +
÷÷ ø ö çç è æ D = + + = D
i i i
i i N
N i
i i
N N i i i i i
E E e
e e E
E E
E e
E E e CS IMS RS e
while
the
total
output
growth
of
a
region
is
given
by
÷÷ ø ö çç
è
æ D
-D +
÷÷ ø ö çç
è
æD -D
+ ÷÷ ø ö çç è æ D =
+ + =
D
å
å
å
å
å
=
= =
= =
i i i
i n i
i
N N i
i n i
i N
N n i
i n i
i i i n
i i
E E e
e e
E E E
E e E
E e
CS IMS RS e
1
1 1
1 1
) (