Statistique, Développement et Droits de l‘Homme
Session C-Pa 6a
Monetary and Non-Monetary Measures of
Poverty in Indonesia: A Statistical
Comparison
Ali SAID
Montreux, 4. – 8. 9. 2000
Statistique, Développement et Droits de l‘Homme
Monetary and Non-Monetary Measures of Poverty in
Indonesia: A Statistical Comparison
Ali SAID
BPS Statistics Indonesia
Jl. Dr. Sutomo 6-8
10710 Jakarta, Indonesia
T. + 62 21 381 02 91 F. + 62 21 385 70 46
djoko@mailhost.bps.go.id
ABSTRACT
Monetary and Non-monetary Measures of Poverty in Indonesia: A Statistical Comparison
The paper presents a discussion about poverty measurement in Indonesia. Two major
approaches in measuring poverty including money metric and non-money metric measures have
been intensively carried out. While scholars have paid more attention on the first approach that is
income poverty, measurement of poverty level based on non-monetary approach known as human
poverty index (HPI) was introduced by the UNDP through the publication of 1997 Human
Development Report, whose theme was Human Development to Eradicate Poverty. BPS-Statistics
Indonesia as the government institution producing the official figures of poverty has applied these
two approaches. When income poverty represented by head count index and human poverty index
were applied to measure the provincial poverty level, comparison between the results of the two
approaches indicates that progress in reducing income poverty and progress in reducing human
poverty do not always move together as shown in many provinces. Since the official figures have
been widely used as the basis of policy formulation, results of the two measures should receive
much attention from the policy makers before formulating programs and policies directed to the
poverty alleviation.
RESUME
Mesures monétaires et non-monétaires de la pauvreté en Indonésie: comparaison
statistique
Ce document présente une discussion sur la mesure de la pauvreté en Indonésie. Deux
approches majeures de mesure de la pauvreté, incluant des systèmes de mesures métriques
monétaires et non-monétaires, ont été menées de façon intensive. Tandis que les universitaires se
sont surtout penchés sur la première approche qui est la pauvreté des revenus, la mesure du niveau
de pauvreté basée sur l’approche non-monétaire, connue comme l’indice de pauvreté humaine, a
été introduite dans la publication de 1997 du Programme des Nations Unies pour le
Développement «Rapport sur le Développement Humain», dont le thème était le «Développement
humain pour éradiquer la pauvreté». Le BPS Statistics Indonesia, en tant qu’institution
gouvernementale qui produit les chiffres officiels de la pauvreté, a appliqué ces deux approches.
Lorsque l’indice de comptage et l’indice de pauvreté humaine représentant la pauvreté des revenus
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étaient appliqués pour mesurer le niveau de pauvreté en province, la comparaison entre les
résultats des deux approches indiquait que la progression dans la diminution de la pauvreté des
revenus ainsi que dans la pauvreté humaine n’évoluent pas toujours ensemble, comme on peut le
constater dans plusieurs provinces. Comme les chiffres officiels ont largement servi de base pour
l’élaboration de mesures politiques, les résultats de ces deux mesures devraient être mieux
considérés par les responsables politiques avant de formuler des programmes et des politiques
visant à réduire la pauvreté.
1. Introduction
It is important to note that any poverty study must begin with a definition of poverty. There
are several different criteria that have been used in defining poverty. Many researchers have defined
the poor as those who are unable to meet basic nutritional needs. Other criteria are based on the
levels of expenditure and consumption. Some researchers have defined poverty in very broad terms,
such as being unable to meet the physical (food, health, education, shelter, etc.) and non-physical
(e.g. participation) requirements of a meaningful life. In a broader classification, poverty
measurement can be viewed from two perspectives: monetary and non-monetary approaches.
This paper discusses monetary and non-monetary measurements of poverty in Indonesia and
attempts to compare the results of these two poverty measures. In addition, this study attempts to
examine the relationship between these two measures and to provide some implications for policies
and programs formulation directed to the poverty alleviation.
2. Measurement of Poverty in Indonesia
Measurement of poverty level based on income approach has dominated many literature.
Monetary measurement of poverty concentrates exclusively on deprivation of one variable, i.e.
income. Since lives of human beings can be impoverished in quite different ways, income-based
poverty measures can not be used to measure deprivation in other variable rather than income. A
person having income above poverty line may still be deprived in the sense of being subject to
epidemiological vulnerabilities that can lead to premature mortality, or being illiterate, or being
without crucial health services. Therefore, poverty measurement, which can directly reflect the
characteristics of human live and quality of living is needed as complementary indicator to the
classic poverty measures.
2.1 Monetary Measurement of Poverty
Monetary measurement of poverty often called income poverty focuses on the situation and
progress of the most deprived people in the community in terms of income deprivation.
Measurement of poverty on the basis of income approach is widely employed in developing
countries today. There are at least two main reasons why the monetary measurement is used. First,
there is a need to quantify the magnitude of poverty in order to be able to determine the direction of
effort required to alleviating poverty. Second, to evaluate the success or failure of government
programs and policies, the measurement of changes in the extent and magnitude of absolute poverty
is undoubtedly crucial. Such measurement allows one to judge the relative success or failure of
individual programs and policies.
BPS-Statistics Indonesia as the institution producing the official figures of poverty has long
been working in the area of income poverty measurement since the 1970s. In determining the
magnitude of poverty, what should be done is to define a specified threshold what so called poverty
line to classify the population into two groups; poor and non-poor. The BPS defined poverty line as
lack of command over basic consumption needs, including food and non-food components. Poverty
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Statistique, Développement et Droits de l‘Homme
line is obtained by specifying a consumption bundle considered adequate for basic consumption
needs and then by estimating the costs of these specified basic needs (Sutanto et.al, 1999). Thus, the
poverty line is defined as a minimum standard required by an individual to fulfill his/her basic food
and non-food necessities.
The minimum standard for food adequately required by an individual is set on the basis of the
recommendation of the National Workshop on Food and Nutrition in 1978, as equivalent to the
value of 2,100 calories intake per capita per day. The methodology of determining minimum
standard value for calorie intake is continuously improved. In the 1993 method onward, value of the
2,100 calories - equivalent food sufficiency is calculated from a selected commodity basket, by
taking into account differences among provinces. The selection of reference food commodity basket
is determined on the basis of the frequency of household consuming the commodity and the volume
of calories consumed. In addition, the food bundle is also selected by taking into account the
importance of several essential commodities consisting of 52 items.
The minimum expenditure value for non-food commodities includes expenditure for housing,
clothing, health, education, transportation, durable goods and other essential goods and services.
The selected non-food commodity bundle consists of 27 items for urban areas and 26 items for rural
areas. These non-food items are selected on the basis of the result of “1995 Basic Commodity
Basket Survey”. An item is selected if it constitutes a basic need for the reference population - it is
consumed by the majority of households in the reference population1.
Having determined the minimum value of expenditure for food and non-food commodities,
the poverty line is obtained simply by summing up these minimum expenditure values. The poverty
line has changed overtime following changes in costs of living. Since many criticisms have been
addressed to the official poverty line (e.g. see Bidani and Ravallion, 1993; Magana, 1996), other
estimates of poverty incidence will be used as a comparison. Magana (1996), for example, noted
that the official poverty estimates has undergone methodological changes.
Three kinds of income-based poverty indicator that have been widely used are the incidence
of poverty (head count index), the poverty gap, and the poverty severity index. The head-count
index indicates the proportion of population with a standard of living below the poverty line, while
poverty gap and poverty severity indices measure how acute and severe the living standards are
among the poor. These indices are actually derived from a class of decomposable measures, as
proposed by Foster, Greer and Thorbecke (1984). These three indices have been intensively carried
out in measuring poverty level in Indonesia.
2.2 Non-monetary Measurement of Poverty
Non money metric measurement of poverty in Indonesia was first introduced by the
Indonesian Family Planning Coordinating Board (or the BKKBN), which developed some
indicators to measure poverty with family as the unit of measurement. While BPS-Statistics
Indonesia has been working on poverty at the macro level, the BKKBN has tried to provide poverty
data at the micro level to fulfill the need of targeting programs for the poor2. However, many
scholars questioned about the validity of measurement and the reliability of data collection. Raharto
and Romdiati (2000), for example, noted that the BKKBN’s concept of poverty are facing some
problems relating to the methodology of data collection, operational definition of psychological and
social variables, and the accuracy of answering question provided by the respondents. In addition,
they also suggest that the significance of some indicators in the BKKBN’s concept need to be tested
1
A reference population is a group of people living just above poverty line and their pattern of consumption is used as
the basis of determination of minimum consumption standard.
2
Due to unavailability of the data on the number of poor families based on the BKKBN’s criteria, the incidence of
poverty on the basis of BKKBN’s concept will not be use for comparison.
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Statistique, Développement et Droits de l‘Homme
statistically against the incidence of poverty at the macro level produced by BPS-Statistics
Indonesia.
Non-monetary measurement of poverty, which is expected to capture other dimensions of
poverty rather than income was introduced by the UNDP in its publication of the 1997 Human
Development Report, whose theme was Human Development to Eradicate Poverty. It is important
to note that “poverty has many faces. It is much more than low income. It also reflects poor health
and education, deprivation in knowledge and communication, inability to exercise human and
political rights and the absence of dignity, confidence and self-respect” (UNDP, 1997). Since
poverty has many dimensions, the UNDP develops a composite index what so called Human
Poverty Index (HPI) for comparing level of poverty between the regions. HPI concentrates on
measuring deprivation in three essential areas - survival (% of people expected to die before age
40), knowledge ( % of adult population who are illiterate), and a decent standard of living (% of
people without access to health services and safe water, and the % of malnourished children under
five). Significantly missing in the HPI is any indicator of income or expenditure.
Measurement of poverty on the basis of non-monetary approach seems to be more appropriate
in the developing countries like Indonesia, where the main issues of poverty involve hunger,
illiteracy, and the lack of health services or clean water, compared to the developed countries where
hunger is rare, literacy is almost universal, most epidemic are well controlled, and almost all people
can access to health services and safe water. In this respect, human poverty index is expected to
enable to judge the extent of human poverty and to monitor progress of the most deprived people in
the community, while in the same way incidence of income poverty is needed to monitor progress
in eliminating poverty.
3. Trends in Incidence of Income Poverty and Human Poverty in Indonesia
Trends in poverty incidence in terms of both income poverty and human poverty will be
highlighted both in the period prior to the crisis and the period of on-going crisis. Poverty incidence
during the two different periods is in a great concern due to a very contrast situation between the
two periods. As has been discussed by many scholars (e.g. Irawan and Suhaimi, 1999), economic
crisis that hit Indonesia in the mid-1997 following the long drought during the year, is believed to
have brought about setback of improvement in human development achieved by Indonesian
population.
3.1 Trends in Income Poverty
Improvement in major social and economic condition (e.g. health and education) during the
period prior to the crisis was a significant issue of the success of Indonesian development.
Development of infrastructure mainly in education and health sectors in most villages is a
significant program to provide a better access for the population living in rural and remote areas to a
very basic economic and social needs, besides to enlarge the people choices. In 1960, Indonesia’s
life expectancy at birth was 41.2 years; in 1996 it had reached 66.0 years. Adult literacy increased
remarkably from 54% in 1970 to 85.3% in 1996, while the percentage of malnourished children
under five declined from 51% in 1975 to 36.1% in 1995.
To a larger extent, such substantial progress in human development had an impact on a
massive reduction in the incidence of income poverty prior to the crisis period. Based on the
National Social and Economic Survey (or the SUSENAS), during the period 1976-1996 the number
of population living below the official poverty line dropped dramatically from around 54 millions
(40.1%) to 22.5 millions (11.3%). Estimates by the World Bank also confirm the same trends in
which the incidence of poverty declined from around 57% in 1971 to 19% in 1990 (World Bank,
1994). Based on the estimate by Ikhsan (1999, forthcoming), the incidence of poverty in 1996 was
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around 18%. Magana (1996) argues that such a dramatic reduction in income poverty relies much
on the three principle factor: rapid economic growth generating rapid growth in demand for workers
and income, initially in rural areas; relatively free and unhindered labour markets allowing workers
to migrate to the jobs from rural to urban areas; and expansion and accessibility of health,
education, basic infrastructure and other human development services to the majority of the
population leading the improvement of quality of life and the increase of productivity.
The continuity of progress in reducing the incidence of income poverty (or head-count index)
is followed by an improvement in the poverty gap index and poverty severity index (Sutanto and
Avenzora, 1999). Based on the data available in the country, during the period 1987-1996 poverty
gap index declined from 3.15% to 1.59% for urban areas and from 2.83% to 1.8% for rural areas. At
the same period, poverty severity index decreased from 0.95% to 0.41% for urban and from 0.76%
to 0.43% for rural.
60.0
54.2
49.5
50.0
40.1
48.0
42.3
40.0
35.0
30.0
28.6
30.0
21.6
20.0
17.4
27.2
25.9
15.1
22.5
13.7
24.23
23.2
11.3
10.0
0.0
1976
1980
1984
1987
1990
1993
No. of poor people (million)
1996
1998
1999
% poor people
Figure 1. Trends in the Incidence of Poverty, Indonesia, 1976-1999
However, such continuous reduction in the incidence of income poverty was altered by the
economic crisis. The crisis affected in a substantial increase in the incidence of income poverty by
more than doubled. Based on the official figure resulted from the mini-SUSENAS3 conducted in
December 1998, the number of the poor increased to 49.5 million (24.23%), or an absolute increase
of around 27 million as compared with the figure of 1996 (see Figure 1). A comparable figures were
exhibited from the 100 Villages Survey, which found that the incidence of income poverty
increased from 13.5% in August 1997 to 27% in December 1998 (BPS and UNICEF, 1999). The
extent of the increase in the incidence of income poverty especially during the period 1996-1998
was mostly due to the skyrocketing prices of most commodities especially food commodities
resulting in a substantial increase in the poverty line. A sudden increase of prices brought about the
phenomenon of transient (transitory) poverty4 (BPS and UNICEF, 1999). The preliminary figure of
poverty incidence in 1999 resulted from the February 1999 SUSENAS was around 48 million
(23.2%). The decline during the period December 1998-February 1999 was in line with a starting
reduction in prices of most commodities. The crisis also affected in the increase of poverty gap and
3
The mini-SUSENAS is household social and economic survey conducted in December 1998 covering a smaller sample
size (10,000 households) than regular SUSENAS covering 65,000 households.
4
Phenomenon of transient poverty is different from chronic poverty, which is more related to structural problem rather
than a sudden temporary shock (Irawan and Suhaimi, 1999).
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poverty severity indices indicating that the degree of poverty has worsened and the poor have
become poorer.
3.2 Trends in Human Poverty
When the UNDP introduced HPI in 1997, BPS-Statistics Indonesia directly adopted the index
to capture the poverty levels and trends. Comparison between 78 developing countries shows that
ranking of human poverty index for Indonesia is 23 (UNDP, 1997). Based on data available in the
country, during the period of 1990-1996, human poverty index5 of Indonesia declined from 27.6%
to 24%, with all three essential indicators contributing to the decline (see Table 1). This means that
in 1996 an “average” of some a quarter of Indonesian population is affected by the various forms of
human poverty included in the measure.
In line with the increase of the incidence of income poverty due to the crisis, the incidence of
human poverty also increased. While the incidence of income poverty substantially increased (or
increased by 104%) during the period 1996-1999, the incidence of human poverty did not show
much changes during the same period - HPI just increased slightly to 25%.
The increase in the incidence of human poverty during the crisis can be examined through
changes in the components of HPI. As previously mentioned, the crisis has brought about some
thorough-going changes in people’s life, especially in health sector. Irawan and Suhaimi (1999)
noted that the crisis had an impact on the changes in the food consumption patterns and on the
decrease in the quality of food consumed by the population. In addition, utilization of health
facilities has also declined due to the decline in the real income and the increase in the cost of
medical health services. Such changes, to some extent, have caused the decline in health status of
the population. The decrease of health status, in turn, affected mortality level. As one component of
HPI, the proportion of people expected to die before becoming age 40 increased from 12.3% in
1996 to 16% in 1999. Another component contributing changes in HPI is the percentage of
population without access to health services, which may be due to the inactivity and damage of
health facilities as affected by the crisis. This component increased from around 11% in 1996 to
21% in 19996.
Table 1. Human Poverty, Indonesia, 1990-1999
Year
People not
Expected
To survive
To age 40
(%)
1990
15.2
1996
12.3
1999 *)
16.0
Source: BPS and UNDP, 1997
Note: *) Preliminary figure
Adult
Illiteracy
Rate
(%)
Population
Without
Access
to safe
water (%)
18.5
14.5
11.6
54.7
52.8
51.5
Population Underweight
Human
Without
children
Poverty
Access
under age index (HPI)
to health
five (%)
Value
Services (%)
5
14.0
10.6
21.4
44.5
36.1
30.3
27.70
23.98
24.91
The values of human poverty index presented in this paper are slightly different from the estimates made by the
UNDP. The differences may occur because of different concept and measurement.
6
This dramatic increase is actually questionable. A little change in the concept and definition used in the survey may
also significantly influence the results.
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3.3 The Disaggregated Income Poverty and Human Poverty
Estimating separate human poverty index (HPI) and head-count index (HCI) for provinces
and major group of region reveals disparities and contrasts within country. Several important points
can be drawn as follows (see Tables 2 and 3 and Figure 2):
• During the period prior to the crisis all provinces have done better in reducing income
poverty than human poverty. In 1996, many provinces have reduced income poverty to
less than 10%, but 25% or more are affected by human poverty. These provinces include
Riau, South Sulawesi, Central Sulawesi, Jambi and West Java. However, as an impact of
the crisis some provinces such as Lampung, Central Java, East Java, Irian Jaya, East Nusa
Tenggara, and Maluku recorded a higher incidence of income poverty than human poverty
in 1999. In addition, while incidence of income poverty during the crisis increased in all
provinces, in the same time some provinces recorded a reduction in the incidence of
human poverty (Table 2).
• West Nusa Tenggara, East Nusa Tenggara, East Timor, West Kalimantan, Maluku and
Irian Jaya are the most affected provinces by both income and human poverty, while
provinces with relatively low incidence of income and human poverty are Jakarta, Bali,
East Kalimantan and Yogyakarta.
• Looking at the HCI and HPI rankings of each province relative to other provinces shows
that some provinces have done much better in reducing income poverty than human
poverty in the one hand, while some others have experienced more progress in human
poverty than income poverty on the other hand (Figure 2).
Table 2. Human Poverty Index (HPI) and Head-Count Index (HCI) by Province, 1996-1999
Province
Jakarta
Bali
Yogyakarta
East Kalimantan
North Sulawesi
Bengkulu
East Java
North Sumatra
Central Java
South-east Sulawesi
West Sumatra
Lampung
South Kalimantan
West Java
Central Sulawesi
South Sumatra
Jambi
Maluku
South Sulawesi
Aceh
East Nusa Tenggara
Riau
West Nusa Tenggara
Irian Jaya
Central Kalimantan
1996
HPI
HCI
17.70
2.48
18.50
4.29
19.70
10.42
19.70
9.24
20.50
10.60
21.60
9.37
22.80
11.86
22.90
10.92
23.00
13.91
23.20
8.48
23.60
8.76
23.90
10.65
24.20
14.33
25.20
9.88
25.90
8.18
26.00
10.72
26.10
9.06
26.10
19.47
27.70
8.02
28.60
10.79
28.90
20.57
30.90
7.94
31.40
17.61
32.00
21.17
33.00
11.24
1999 *)
HPI
HCI
9.82
6.59
17.87
9.85
19.27
22.62
22.96
17.65
22.98
21.61
23.60
23.23
25.59
26.24
24.35
17.03
25.13
27.01
26.92
25.50
26.29
16.75
27.29
30.77
24.57
22.33
23.51
20.79
29.28
24.78
25.81
24.42
25.86
24.24
25.31
37.88
27.88
21.68
30.22
16.47
35.11
44.95
30.52
13.65
33.14
23.93
34.09
46.76
29.09
16.83
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1996 Rank
1999 Rank
HPI
HCI
HPI HCI
1
1
1
1
2
2
2
2
3
12
3
13
4
9
4
8
5
13
5
10
6
10
7
14
7
19
12
21
8
17
8
7
9
20
10
22
10
6
16
20
11
7
15
5
12
14
18
24
13
21
9
12
14
11
6
9
15
5
21
19
16
15
13
18
17
8
14
16
18
23
11
25
19
4
19
11
20
16
22
4
21
24
26
26
22
3
23
3
23
22
24
15
24
25
25
27
25
18
20
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Statistique, Développement et Droits de l‘Homme
West Kalimantan
35.40
21.98
East Timor
43.00
31.15 -Note: Ranked on the basis of HPI values in 1996
*) Preliminary official figures
39.71
29.72
--
26
27
26
27 --
27
23
--
• Disaggregated incidence of poverty by major region shows that regional variation in
income poverty is significant in Indonesia. In 1996, income poverty in the western part of
Indonesia was around 10%, but it was around 15% in the eastern region (see Table 3).
Comparison between regions show that Sulawesi led as region with the lowest incidence
of income poverty. Such disparities are also observed in the human poverty. Human
poverty is more pervasive in the eastern region than in the western region. Said (1998)
noted that regional imbalance in the incidence of poverty is closely related to the
inequalities in regional development in the country with the western part of Indonesia
being more developed than the eastern part region.
• Looking at the changes in HPI and HCI values shows that during 1990-1996 Kalimantan
experienced the most rapid decline in the incidence of poverty. The economic crisis that
hit the country has affected the poorest region become poorer. In terms of changes in HCI
by major islands, the most affected region by the crisis is Sulawesi followed by Java-Bali
and Sumatra. In a broader classification of the regions, in the period prior to the crisis
western part of Indonesia experienced more rapid decline in the incidence of both income
and human poverty than the eastern region. The table also shows that during the period
1996-1999 the incidence of income poverty increased more dramatically in the western
part of Indonesia than in the western regions, while in the same period the western regions
experienced a lower increase in the incidence of human poverty than the eastern regions.
Provinces w ith relatively m ore
progress in hum an poverty than
incom e poverty
HPI rank
0
2
4
6
8
10
12
14
16
18
20
Provinces w ith relatively m ore
progress in incom e poverty than
hum an poverty
Income
poverty
rank
HPI rank
North Sumatra
Central Java
Yogyakarta
East Java
North
Sulaw esi
0
2
4
6
8
10
12
14
16
18
20
22
Income
poverty
rank
Riau
Jambi
Central
Sulaw esi
South
Sulaw esi
Figure 2. HPI Rank and Income Poverty Rank of Some Selected Provinces, Indonesia, 1996
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Table 3. Trends in HPI and HCI and their Changes by Major Region, Indonesia, 1990-1999
Region
Java-Bali
Sumatra
Kalimantan
Sulawesi
Other Islands1
HPI value
Head Count Index (HCI)
Change in
(%)
(%)
HPI value (%)
1990
1996
1999 1993 1996
1999 1990-96 1996-99
26.36
28.35
34.38
27.69
33.40
22.46
25.08
28.31
25.29
29.78
22.98
26.46
29.76
26.84
31.67
12.84
12.88
20.17
9.94
22.85
10.75
10.15
15.35
8.59
20.33
22.56
20.78
22.97
22.56
37.20
-14.8
-11.5
-17.7
-8.7
-10.8
Change in
HCI (%)
1993-96 1996-99
+2.32
+5.50
+5.12
+6.13
+6.35
-16.28
-21.20
-23.90
-13.58
-11.03
+109.86
+104.73
+49.64
+162.63
+82.98
Western Part of Indonesia2 26.69 23.02 23.79 12.85 10.59 22.10 -13.75
+3.34
Eastern Part of Indonesia3 31.21 27.43 29.11 17.17 14.46 27.32 -12.11
+6.12
Indonesia
27.70 23.98 24.91 13.67 11.34 23.15
-13.3
+3.88
Note: 1 Include West Nusa Tenggara, East Nusa Tenggara, East Timor, Maluku and Irian Jaya
2
Includes Java-Bali and Sumatra
3
Includes Kalimantan, Sulawesi and Other Islands
-17.59
-15.78
-17.04
+108.69
+88.93
+104.14
4. Statistical Test of the Relationship between Head Count Index and Human Poverty Index
The following statistical exercise attempts to examine the relationship between monetary and
non-monetary measures of poverty in Indonesia on the basis of 1996 data. The regression and
correlation analysis will be utilized to test such relationship. As the official figures of income
poverty produced by BPS-Statistics Indonesia being criticized by many scholars, the data produced
by Ikhsan (1999, forthcoming) on the basis of another method7 will be used for a comparison.
Results of the correlation analysis show that relationship between incidence of income
poverty and human poverty is not quite strong. Comparison between the Official (BPS) Method and
CBN Method confirms that the Official Method seems to be more sensitive than CBN Method in
measuring such relationship as indicated by a higher coefficient of correlation of Official Method
(r=0.77) compared to that of the CBN Method (r=0.58) (see Table 4). This result indicates that the
higher is the incidence of human poverty in a province, the higher is the incidence of income
poverty in that province. Compared with the coefficient of product moment correlation, rank
correlation between HPI and HCI shows a weaker relationship with official method also showing a
higher coefficient of correlation than CBN method.
Table 4. Correlation Coefficient between HPI and HCI, Indonesia, 1996
Income Poverty
Official Method
CBN Method
HCI (%)
HCI Rank
HCI (%)
HCI Rank
HPI (%)
0.7682
-0.5850
-HPI Rank
-0.5391
-0.4121
Note: n=27 observations (provinces)
Human Poverty
A deeper examination of the relationship between income poverty and human poverty can be
seen in the regression analysis. Results of the regression analysis show that not all indicators in the
component of HPI as the independent variables are significant in explaining the incidence of
7
Mohamad Ikhsan has applied the cost of basic need as used by Bidani and Ravallion (1993) to calculate the incidence
of poverty in Indonesia in 1996 and onward.
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Statistique, Développement et Droits de l‘Homme
income poverty. Using head-count index on the basis of Official Method as dependent variable, the
result shows that three indicators of HPI including education variable, survival variable and health
service variable are statistically significant in explaining income poverty, while based on the CBN
Method the only significant variable is illiteracy rate (see Table 5). On the basis of BPS Method,
education variables explains around 51% of the variation in poverty incidence, while health services
and survival indicators explain around 18% and 7% of the variation respectively. This result also
suggests that income poverty produced on the basis of Official Method is more sensitive than CBN
Method in explaining the relationship between HPI and HCI.
Table 5. Regression of Income Poverty on the Components of HPI for Indonesian 1996 Data:
Ordinary Least Square (OLS) and Stepwise Methods
Independent
Variables
SURVIVAL
ILLITERATE
WATER
HEALTH_S
MALNUTRION
R2
Notes: * = Significant at 10%
Official Method (BPS)
CBN Method
OLS
Stepwise
OLS
Stepwise
0.4293 *
0.4773 **
0.1684
0.2299 ***
0.2174 ***
0.7170 ***
0.9095 ***
0.0208
-0.1377
0.2728 ***
0.2903 ***
0.3242
0.0346
0.2566
76%
76%
72%
63%
** = Significant at 5% *** = Significant at 1% n = 27 observations
It is interesting to investigate the insignificance of malnutrition variable as shown in the regression
result both based on the Official and CBN Methods8. As Reutlinger and Selowsky (1978) pointed
out, malnutrition is one of several manifestations of poverty. The nutritional status of children under
five especially infants is perhaps the most important determinant of the individual’s initial physical
condition, which in turn determines the effectiveness of further investment in human capital. Lack
of the relationship between malnutrition variable and income poverty may be due to the weaknesses
of the measurement of malnourished children under five. Indication of insensitivity of malnutrition
variable can be seen in the continuous decline of the percentage of malnourished children under five
during the period pre- and post crisis. This actually contradicts to other findings (e.g. see Irawan
and Suhaimi, 1999; Jahari et. al, 1999). Study conducted by Jahari et. al (1999) shows that if
malnutrition status is classified into two categories -- moderate and severe, the impact of the crisis
can clearly be seen in the increase in the percentage of severely malnourished children under five.
Therefore, the incidence of income poverty seems to be more closely associated with the incidence
of severe malnourished children under five than combination of moderate and severe level of
malnutrition.
5. Conclusion and Implication
Attempt has been made to asses the extent of poverty on the basis of monetary and nonmonetary approach and to examine the relationship between monetary-based measure (income
poverty) and non-monetary-based measure (human poverty). The main findings can be summarized
as follows:
• Changes in the incidence of income poverty goes hand in hand with the changes in the
incidence of human poverty. Results of the regression and correlation analysis support this
finding. However, disaggregated incidence of poverty by province and major region
shows that many provinces relative to other provinces have done much better in income
poverty than in human poverty and vice versa.
8
This finding is also in line with the UNDP’s findings.
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Statistique, Développement et Droits de l‘Homme
• Some provinces have reduced income poverty to less than 10%, but the incidence of
human poverty was still above 20%. In a broader classification of the region, the
incidence of income and human poverty in the eastern part of Indonesia was more
pervasive than in the western region.
• With regards to the economic crisis, its impact on poverty incidence was better recorded
by the incidence of income poverty than the incidence of human poverty. Non-monetary
measure of poverty (human poverty index) in the case of measuring such a sudden shock
seems to be insensitive.
• Result of the regression analysis shows that components of HPI showing significantly in
explaining income poverty include the percentage of people not expected to survive to age
40, adult illiteracy rate, and percentage of population without access to health services.
The findings of the study lead to some speculation for programs and policies formulation as
follows:
• With respect to the fact that progress in reducing income poverty and human poverty does
not always move together as shown in many provinces, formulation of programs and
policies directed to the poverty alleviation should take into account the magnitude of both
income and human poverty. In other words, poverty alleviation programs should be
directed not only to eliminate income deprivation but also to eradicate poverty in the
forms of other deprivation as included in the components of human poverty index.
Development in health sector seems to be the main priority due to the highest deprivation
in the components of human poverty being in this sector. It is believed that much progress
in human poverty and human development is the key for the reduction in income poverty
in the long term.
• With respect to the imbalance in incidence of poverty between the western part and the
eastern part of Indonesia with the eastern region being more affected especially by human
poverty and facing geographical barrier, which make it very hard for the government to
provide a better access to health and educational services for the poor, a huge investment
in infrastructure and social development in the eastern region should become the main
priority. In addition, identification of geographical location of the people affected by
poverty before implementing program and policies directed to poverty alleviation should
receive much attention from the policy maker.
• It would be very useful to consider what indicators are used to monitor poverty levels. A
set of indicators that can monitor the progress in both income and human poverty should
be formulated and be integrated in the regular survey like Social and Economic Survey (or
the SUSENAS). One suggestion made in conducting the SUSENAS is that the SUSENAS
is conducted in the form of longitudinal survey rather than cross section survey as
currently carried out. Such longitudinal survey enables to monitor progress of social and
economic condition from time to time consistently.
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Statistique, Développement et Droits de l‘Homme
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