Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014.docx

Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014:
207–25
ISSN 0007-4918 print/ISSN 1472-7234 online/14/000207-19 ©
2014 Indonesia Project ANU
http://dx.doi.org/10.1080/00074918.2014.938404
* Many thanks to the two anonymous referees for their
comments, and to Arief Anshory
Yusuf, Asep Suryahadi, Dharendra Wardhana, Lukas Schlögl,
and seminar participants at
the SMERU Research Institute, Jakarta, on 2 May 2013, and at
the Centre for Economic and
Development Studies, Department of Economics, Padjadjaran
University, Bandung, on 3
May 2013.
ASSESSING POVERTY TRENDS IN INDONESIA BY
INTERNATIONAL POVERTY LINES
Andy Sumner*
King’s College London
Peter Edward*
Newcastle University Business School (United Kingdom)
Indonesia has made well-documented and drastic progress in
raising average in-
comes and reducing poverty. This article adds to the literature
by providing a com-

plementary perspective of poverty between 1984 and 2011. We
discuss the evolution
of poverty in Indonesia using international poverty lines—$1.25
per person per day
(in 2005 purchasing power parity dollars) and $2.00 per day,
and we add $10.00 per
day. We generate estimates of poverty since 1984 and make
projections based on var-
ious trends in growth and inequality. We find that Indonesia has
the potential to be-
come a high-income country by around 2025 and end $1.25-per-
day and $2.00-per-
day poverty by 2030, but this will require strong economic
growth and favourable
changes in distribution. Looking ahead, the end of poverty in
Indonesia may mean
that a large proportion of the population will remain vulnerable
to poverty for some
time to come, suggesting that public policy priorities will need
to balance insurance
and risk-management mechanisms with more ‘traditional’
poverty policy.
Keywords: poverty, inequality
JEL classification: D63, I32
INTRODUCTION
Over the last 30 years Indonesia has made well-documented and
drastic improve-
ments to its average incomes and in the reduction of poverty.
Recently, however,
the context for poverty reduction in Indonesia has increasingly
been a discus-
sion of its slowing rate (see Suryahadi, Hadiwidjaja, and
Sumatro 2012) and how

to reduce poverty sufficiently to meet the National Medium-
Term Development
Plan’s poverty target of 8%–10% (according to the national
poverty line) by 2014.
This article adds to the literature by offering a complementary
perspective. We
analyse international poverty lines—$1.25 per person per day
(in 2005 purchasing
http://dx.doi.org/10.1080/00074918.2014.938404
208 Andy Sumner and Peter Edward
power parity [PPP] dollars) and $2.00 per day, and we add
$10.00 per day—in
our discussion of trends and patterns in poverty reduction. We
use a model of
growth, inequality, and poverty to produce estimates for
previous years and to
project future poverty-reduction patterns by examining various
trends in growth
and inequality.
We are, of course, not the first to consider the evolution of
poverty in Indone-
sia; a number of studies that we review consider the evolution
of poverty by the
national poverty line. Yet, to our knowledge, no study considers
the evolution of
poverty by international poverty lines or makes poverty
projections in various
scenarios. We also discuss trends in inequality and the
distributional pattern of
growth.

INDONESIA’S DEVELOPMENT SINCE 1984
Economic Development
Between 1984 and 2011, gross national income (GNI) per capita
(Atlas method)
in Indonesia increased almost sixfold, from $540 to $2,940,1
and GDP per capita,
in 2005 PPP dollars, almost tripled, from $1,500 to just under
$4,100.2 Average
PPP income stood at about $11 per person per day in 2011. Few
countries have
achieved such a drastic change.3 That said, there was a
noticeable dip after the
1997–98 Asian financial crisis, and the poverty impact of the
crisis beyond the
immediate reverberations has been contentious.
Indicators of structural change in Indonesia’s economic
development have
also shifted substantially since the 1980s (and this
transformation can, of course,
be traced to before the 1980s).4 Indonesia fares reasonably well
when assessed
against countries at a similar level of per capita income—except
in comparisons of
poverty levels by international standards. Indonesia is close to
the upper-middle-
income group weighted mean in indicators of official
development assistance; but
it is close to the lower-middle-income group weighted mean in
the proportional
increase in GDP (PPP) per capita since 1990 and the
contribution of agriculture
1. Measured using the Atlas method of exchange-rate
conversion, used by the World Bank

to categorise countries’ income status as low, middle, or upper
income.
2. Data from the World Bank’s World Development Indicators.
3. The Commission on Growth and Development (2008, 20)
identified just 13–15 coun-
tries—including Indonesia, Thailand, Malaysia, and Vietnam—
that had achieved average
growth rates of 7% a year or more (at which speed the economy
doubles in size every 10
years) for 25 years or longer. Booth (1999) argues that initial
conditions were crucial in dif-
ferentiating the more recent Southeast Asian ‘miracle’ from the
older East Asian ‘miracle’.
4. Large shifts occurred, for example, in the importance of non-
agricultural sectors to GDP
and to the labour force (although with noticeable reverse trends
around the 1997–98 crisis):
the value added in agriculture fell from 22.7% of GDP in 1984
to just 14.7% in 2011, and
employment in agriculture fell from 54.7% of the labour force
to 35.9% in the same period.
In comparison, the value added in industry rose as a share of
GDP from 39.1% to 47.1%,
while services increased drastically as a share of employment
(from 32.0% in 1984 to 43.5%
in 2011) but their share of value added in GDP remained steady
(from 38.2% in 2004 to
38.1% in 2011). Several studies (Fane and Warr 2002, for
example) argue that this economic
growth in the services sector was more beneficial to the poor
than economic growth in the
agriculture sector.
Assessing Poverty Trends in Indonesia by International Poverty

Lines 209
to GDP, and close to the low-income-group weighted mean in
primary export
dependency (Sumner, Suryahadi, and Thang 2012).
Indonesia’s $2.00-per-day poverty rate is, surprisingly,
comparable with or
higher than those of its poorer neighbours, such as Cambodia
and Vietnam (figure
1). It is startling that Vietnam, which in 2010 had less than
three-quarters of the
GDP per capita income of Indonesia, has a much lower $2.00-
per-day poverty rate
(34% in 2010 compared with Indonesia’s 45%) and that
Indonesia’s poverty rate
is close to Cambodia’s poverty rate, which is 48%.5 Although
the data for GDP
per capita (PPP) differ, the survey means are similar, and are
higher in Vietnam in
2010 than in Indonesia or Cambodia—which explains why
Vietnam has the low-
est poverty rate of the three.
The Evolution of Income Poverty and Distribution in Indonesia
Many studies published since the 1997–98 Asian financial crisis
consider the
evolution of poverty in Indonesia. We identified about 60 such
studies, most of
which are based on time-series analysis of data from the
National Socio-economic
Survey (Susenas), conducted by Badan Pusat Statistik (BPS),
the central statistics
5. Income shares of the bottom 40% were as follows: Indonesia,
19% in 2010; Cambodia,

19% in 2008; and Vietnam, 19% in 2008. Gini coefficients were
as follows: Indonesia, 35 in
2010; Cambodia, 38 in 2008; and Vietnam, 36 in 2008.
FIGURE 1 Poverty, GDP per Person, and National Account and
Survey Means in
Indonesia, Cambodia, and Vietnam, 1995–2010
1995 2000 2005 2010
0
1,000
2,000
3,000
4,000
5,000
1995 2000 2005 2010 1995 2000 2005 2010
0
10
20
30
40
50
60

70
80
90
100
Indonesia Cambodia Vietnam
PPP $ %
GDP per person (lhs)
Survey mean (lhs)
NA mean (lhs)
Poverty rate (rhs)
Source: Authors’ estimates based on data from the World Bank
(2013a, 2013b).
Note: PPP = purchasing power parity (in 2005 dollars). NA =
national account (household final con-
sumption). Poverty measured against the international poverty
rate of $2.00 per person per day. NA
and survey means taken, respectively, from the World Bank’s
World Development Indicators and
PovcalNet database.
agency. Susenas data are available every three years from 1984
to 2002, and every
year from 2002 onwards. A few studies draw on data from
Sakernas, the national

labour-force survey (conducted annually from 1986 onwards),
and from the
RAND Corporation’s regular Indonesia Family Life Survey to
estimate expendi-
ture poverty and, in particular, to examine chronic and transient
poverty.
We can group these identified studies into three relevant
themes: trends over
time in expenditure poverty, the relation between expenditure
poverty and eco-
nomic growth over time, and trends in inequality. The studies
that focus on trends
in expenditure poverty typically use Susenas data over a period
of time, and use
either the national monetary poverty lines of BPS or a variation
of the poverty
lines calculated by Pradhan et al. (2001). They tend to agree
that absolute poverty
declined in Indonesia during the Soeharto years (Asra 2000;
Booth 2000; Fried-
man 2005); yet poverty was still a problem in the lead-up to
1997–98 Asian finan-
cial crisis, and its rate may have been underestimated owing to
national poverty
lines being set low (Asra 2000). Moreover, welfare
improvements have slowed
since the crisis (Friedman and Levinsohn 2002; Lanjouw et al.
2001; Skoufias,
Suryahadi, and Sumarto 2000; Suryahadi, Hadiwidjaja, and
Sumatro 2012).
Some studies disagree about how quickly Indonesia’s poverty
level, as an indi-
cator of Indonesia’s recovery, returned to pre-crisis levels after
the 1997–98 Asian

financial crisis. Those arguing that poverty fell quickly after the
crisis, or that
the social consequences were less severe than expected, include
Suryahadi and
Sumarto (2003a, 2003b), while those arguing that the crisis had
more significant or
lasting consequences for poverty in Indonesia include Dhanani
and Islam (2002)
and Ravallion and Lokshin (2007). To a certain extent, the use
of different poverty
indicators plays a part in the different findings.
McCulloch and Grover (2010) suggest that the 2008 global
financial crisis had
only a moderate impact on Indonesia’s poverty rate. Suryahadi,
Hadiwidjaja, and
Sumarto (2012) note that this rate has risen only twice since the
1990s: during the
1997–98 crisis, owing to job losses and hyperinflation, and in
2005–6, owing to
inflation caused by rises in the domestic fuel price and in the
cost of rice (the latter
because of the 2004 ban on rice imports—see McCulloch 2008).
Studies focused on the relation between expenditure poverty and
economic
growth typically use Susenas data, and use either the national
monetary poverty
lines of BPS or a variation of the poverty lines calculated by
Pradhan et al. (2001).
They tend to agree that economic growth in Indonesia has,
overall, benefited the
poor, and that Indonesia has had a high and stable growth
elasticity of poverty,
even after the 1997–98 crisis (Baliscan, Pernia, and Asra 2010;
Friedman 2005;

Suryahadi, Hadiwidjaja, and Sumatro 2012; Timmer 2004). Yet
economic growth
in different sectors has different impacts on poverty—economic
growth in the ser-
vices sector, for example, has been found to do more to increase
the incomes of the
poor than has growth in agriculture (Fane and Warr 2002;
Suryahadi, Suryadarma,
and Sumarto 2006; Suryahadi, Hadiwidjaja, and Sumatro 2012).
This is important,
since rural poverty dominates the poverty count in Indonesia
when the national
poverty line is used. Suryahadi, Hadiwidjaja, and Sumatro
(2012, 216) estimate
that rural poverty composed two-thirds of total poverty in 2010.
Studies focused on inequality trends typically use Susenas data
and com-
pute the Gini coefficient or the Theil index. In general, they
agree that inequal-
ity was relatively low or declining before the 1997–98 crisis
(Akita, Kurniawan,
and Miyata 2011) and that inequality did not increase
drastically as a result of
Lines 211
economic growth (Van der Eng 2009). There are some
detractors, however, who
argue that inequality was high or increasing before the crisis
(Frankema and
Marks 2009; Leigh and Van der Eng 2010; Van Leeuwen and
Foldvari 2012); or that

growth has largely been distributionally neutral, although areas
such as Java have
grown slightly faster than the national average (Hill 2008; Hill,
Resosudarmo, and
Vidyattama 2008); or that inequality, mainly intragroup and
urban–rural inequal-
ity, has increased in the aftermath of the crisis (Akita 2002;
Akita and Miyata 2008;
Skoufias 2001; Suryadarma et al. 2005; Suryadarma et al. 2006)
and intraregional
inequality (Yusuf, Sumner, and Rum 2014, in this issue).
INDONESIA AND INTERNATIONAL POVERTY LINES:
METHODOLOGY
The Growth, Inequality, and Poverty (GrIP) model, described in
detail in Edward
and Sumner (2013a, 2013b, 2014), allows us to compare trends
in poverty and
inequality over time across countries and across different input
assumptions,
and to make projections based on these trends. Our main
objective in using the
GrIP model is to construct a truly global model of consumption
distribution that
allows ready comparison of different assumptions and
approaches to estimat-
ing poverty (such as comparisons of estimating poverty by using
survey income
or expenditure means and estimating poverty by using national
account [NA]
income means).
Survey distributions (quintile and upper and lower decile data)
are taken, in
the following order of preference, from the World Bank’s
PovcalNet database, the

World Bank’s World Development Indicators, or the United
Nations University’s
World Income Inequality Database V2.0c (May 2008). Survey
means are taken
from PovcalNet, and NA means are taken from World
Development Indicators.
All analysis and results are in 2005 PPP dollars.
The data for Indonesia in the GrIP model, as shown in table 1,
are as follows:
• Decile values and survey means are taken from PovcalNet,
which provides
data at three-yearly intervals from 1984 to 2005 and annually
thereafter up to
2011 (values for intermediate years are determined by
interpolation).
• Data on household expenditure (household final consumption)
are taken from
World Development Indicators, which provide annual data from
1984 to 2011.
• Urban and rural population data are taken from PovcalNet for
all the survey
years except 2011, which is not presented. We estimate the 2011
figures from
the trends in urban–rural shares in earlier years. The urban–
rural split in the
projected populations is based on a linear extrapolation of the
change in the
shares from 1990 to 2010, which we then applied to the United
Nations’ total
population forecast.6
In order to produce future projections of income and poverty,

we use similar
assumptions to those of Karver, Kenny, and Sumner (2012) and
derive the forecast
rates from the IMF’s World Economic Outlook (WEO). The
estimates are based on
6. This approach has now been superseded by the recent
publication of the BPS and Bap-
penas population projections (See McDonald 2014).
TABLE 1 Share of Consumption, Rural and Urban, by Income
Distribution, 2015–30
(%)
0%–10% 0%–20% 20%–40% 40%–60% 60%–80% 80%–100%
90%–100%
Decile 1 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Decile 10
Rural
2015 3.0 7.0 10.8 15.6 22.9 43.8 26.9
2020 3.1 7.0 10.9 16.1 24.1 42.0 24.0
2025 3.1 7.1 11.0 16.5 25.2 40.2 21.2
2030 3.1 7.1 11.2 17.0 26.3 38.4 18.3
Urban
2015 3.7 8.1 11.6 16.0 22.7 41.8 25.6
2020 3.5 7.5 10.8 15.5 23.1 43.1 26.1
2025 3.3 7.0 10.0 15.0 23.5 44.5 26.5
2030 3.1 6.4 9.2 14.6 24.0 45.9 27.0

Source: Authors’ estimates derived from Growth, Inequality,
and Poverty (GrIP) model v.1.0, described
in detail by Edward and Sumner (2013a, 2013b, 2014).
Note: Shares extrapolated based on current trends.
the average growth rate during 2010–17. We use the following
three scenarios for
GDP PPP growth estimates for Indonesia for 2010–30:
• optimistic economic growth, which assumes that the average
national growth
rate in the WEO is sustained to whatever point in the future,
producing an
average of 6.7% aggregate economic growth per year
• moderate economic growth, which is the ‘optimistic’ GDP
growth rate minus
one percentage point (based on the assumption that IMF
projections are on
average 1% too high, as Aldenhoff 2007 has demonstrated),
producing an
average of 5.7% aggregate economic growth per year
• pessimistic economic growth, which is half of ‘optimistic’
GDP growth,
producing an average of 3.4% aggregate economic growth per
year
Comparing these scenarios with past rates of aggregate growth
suggests that
the ‘optimistic’ growth rate is indeed optimistic, but not overly
so. The average
aggregate growth rate since the Asian financial crisis is 5.3%
per year (from 2000
to 2011) and the aggregate growth rates of 2010 and 2011 are

much closer to the
‘optimistic’ growth scenario, at 6.2% and 6.5% respectively.
We use three inequality scenarios to illustrate the impact of
different inequality
assumptions on future poverty:
• static inequality from 2011 onwards
• extrapolated inequality, in which dynamic changes in
distribution are estimated
by linear extrapolation of the trends calculated from 1990 to
2010 (table 1)
• lowest inequality, which represents a return to the distribution
with the lowest
level of inequality in the PovcalNet dataset for Indonesia
(which is 1999 for
rural Indonesia and 1987 for urban Indonesia)
Lines 213
The main purpose of this dynamic inequality analysis is
illustrative—to investi-
gate the extent to which the assumption of static distribution
introduces a signifi-
cant difference to poverty projections in the calculations. We
explore the potential
implications of decreases in within-country inequality by
providing forecasts cal-
culated using the lowest inequality for Indonesia since 1984.
If we considered inequality trends of the past decades, we

would be more
likely to think that inequality will rise further. Yusuf, Sumner,
and Rum (2014, in
this issue) use various measures and disaggregations in
discussing in some depth
the trend in inequality during the last 20 years, and note the
unequivocal rises in
inequality across various measures but a much smoother rise in
inequality when
a consistent methodology is used compared with the BPS data
series (on which
PovCal is based).7
Figure 2 shows the Gini coefficient based on the GrIP data. It
illustrates that
inequality in Indonesia rose in between 1984 and 2011. In light
of the rising pat-
tern of inequality since the late 1990s, projections of future
poverty based on static
or falling inequality should be viewed with these part trends in
mind (meaning it
is unlikely that inequality will remain static or fall in Indonesia
without major pol-
icy interventions). The graphs are consistent with the story that
although growth
was broad-based at the lower end of the distribution, that there
were greater gains
in the middle and at the top end of the distribution (and thus
inequality rose). At
the bottom end of the distribution, the share of expenditure in
total household
expenditure recorded in Susenas of the poorest 40% shrank
during 2001–10 in
both urban and rural areas (figure 3), which is consistent with
the slowing of pov-
erty reduction noted earlier. Of concern to policymakers is that

rising inequality
will slow the rate of poverty reduction if there is a fall in the
share of the lower
end of the distribution; it may also slow economic growth or
shorten the growth
7. See discussion by Yusuf, Sumner, and Rum (2014, in this
issue).
FIGURE 2 Indonesia’s Gini Coefficient, 1984–2011
Total
Rural
Urban
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011
0.20
0.25
0.30
0.35
0.40
0.45

episode, or both (see, for example, Cornia, Addison, and Kiiski
2004; Berg and
Ostry 2011; Easterly 2005).
We use international poverty lines of $1.25 per person per day
(in PPP dollars)
and $2.00 per day, and we add a poverty line of $10.00 per day.
The $1.25 line is
now approximately equivalent to the current PPP dollar value of
the 2012 Indone-
sian national poverty line, which has been getting closer to the
$1.25 international
poverty line since the revisions to the setting of Indonesia’s
national poverty line
in 1998. We include the $2.00 poverty line because it is well
established as the
World Bank’s moderate international poverty line, which is
close to the median
poverty line across all developing countries ($2.36 per person in
2008) (Ravallion
2012, 25).8
We introduce a $10.00-per-day poverty line on the basis that
this threshold
broadly separates those with ‘rich world’ lifestyles from those
with ‘developing
world’ lifestyles.9 Given the inevitable degree of arbitrariness
in the precise loca-
tion of these thresholds, the $10.00 line seems a reasonable
point of separation.
López-Calva and Ortiz-Juarez’s (2011) study of Chile, Mexico,
and Brazil sug-
gests that $10.00 is an approximate security-from-poverty line,
and that the risk of

falling below the national poverty lines of those countries (of
$4.00–$5.00 in PPP
8. The mean for developing-country poverty lines is $4.64 per
person per day—which is
rather higher than the median, because poverty lines can be
$11.00–$12.00 (the mean in
Latin America, the Caribbean, and Eastern Europe) or closer to
$4.00 (the mean in East Asia
and Pacific) (Ravallion 2012, 25).
9. From the GrIP model, 87% of the population of high-income
countries are above $10.00
per person per day, while 98% of the populations of low-income
and lower-middle-income
countries are below this level.
FIGURE 3 Share of Expenditure in Total Household
Expenditure
Recorded in Susenas of the Poorest 40%
(%)
Urban
Rural
Total
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011
15
16
17
18

19
20
21
22
23
24
25
in detail in Edward and Sumner (2013a, 2013b, 2014).
Lines 215
dollars) was as low as approximately 10% at an initial income
of $10.00 per per-
son per day. The authors refer to this as a ‘vulnerability
approach to identifying
the middle classes’. Further, Birdsall, Lustig, and Meyer (2013)
note that $10.00
is the mean per capita income of those who have completed
secondary school
across Latin America, suggesting that the completion of such
schooling is asso-
ciated with some kind of greater security.10 We propose that
those living above

the $2.00-per-day line but below the $10.00-per-day line could
be referred to as
the ‘global insecure’, and those living above the $10.00-per-day
line the ‘global
secure’.
To validate our data, we compare the Gini coefficient from the
GrIP model to
those from BPS and PovcalNet. We find a close correlation. The
GrIP model tends
to underestimate the Gini coefficient, owing to the way that the
model extrapo-
lates and interpolates across the distribution. GrIP uses a
method for estimating
fractile shares of income from ventiles and deciles. It is
extremely difficult to esti-
mate from this data the detailed distribution across
(particularly) the top 5% of
the distribution. The method in GrIP is designed to be
inherently conservative in
this region (see Edward 2006, 1692) so that GrIP slightly
underestimates Gini coef-
ficients for individual countries. We would expect the BPS Gini
coefficient to be
slightly higher, which they are. PovcalNet also underestimates
the national Gini
coefficient; GrIP is close to PovcalNet, and it may arguably be
better given that its
estimates are closer to those of BPS. PovcalNet uses a kernel
distribution method
and GrIP a linear distribution method to estimate the
distribution detail from the
decile and quintile data, which yields slightly different
estimates of the Lorenz
curve and hence of the Gini coefficient.

As is well known, expenditure survey data (such as those from
Susenas and
thus those from PovcalNet for Indonesia) understate income
inequality since they
ignore savings (for example) while top incomes largely escape
surveys (Leigh
and Van der Eng 2010). Those are inherent shortcomings of all
such surveys, not
just Susenas. The decile data in PovcalNet, and on which GrIP
is based, are, in
general, widely recognised as likely to underestimate inequality
and the incomes
of the rich—so it is not surprising that the GrIP results reflect
these shortcomings
in the underlying data. Nugraha and Lewis (2013) use Susenas
data to argue that
the different forms of non-market income should be taken into
account. We find
(see below) that in the GrIP data the $10.00 poverty line
questions the quality of
information on higher incomes.
PAST TRENDS AND FUTURE PROJECTIONS, 1984–2030
In figures 4–9, we consider growth, distribution, and poverty
during 1984–2011
and, where appropriate, project their trends to 2030. The
discussion is grouped by
trends in (a) income per capita; (b) patterns of economic
growth; and (c) poverty.
We use the scenario of optimistic economic growth to show the
extent of possi-
bility (and because it is close to the higher end of the
Indonesian’s government’s
own target range). The data for other growth scenarios are
presented in Sumner
and Edward’s (2013) study.

10. In contrast, Ravallion (2010) uses a higher threshold, the US
poverty line of $13.00 per
person per day.
Trends in Income per Capita, 1984–2030
Extrapolation of Indonesia’s GNI per capita (Atlas method) to
2030 suggests that
Indonesia’s GNI per capita (Atlas method) would cross $12,000
between 2025 and
2030 if the ‘optimistic’ economic growth scenario held (that is,
the IMF’s WEO
forecast extrapolated to 2030 at 6.7% a year, which is clearly
optimistic). Such
projections of GNI per capita (using the Atlas method) show
that Indonesia may
cross the threshold into the upper-middle-income country
classification in 2015
and could become a high-income country between 2025 and
2030.
Patterns of Growth, 1984–2011
Figures 4 and 5 show Indonesia’s density curve and growth
incidence curve. Fig-
ure 4 shows the gradual shift of the poverty peak (and the
decline in size of the
peak) between 1984 and 2011, and thus the emergence of the
‘global insecure’ in
Indonesia. The rise in consumption is particularly visible in the
middle and at the
top end of the distribution (the bottom half of the graph). The
change between

2000 and 2011 is quite striking.
In figure 4, consumption per capita (in 2005 PPP dollars) is
plotted on a log scale
on the horizontal axis. The vertical lines represent the $1.25-
per-day, $2.00-per-day,
and $10.00-per-day consumption levels (and in this figure we
add a $50.00-per-
day to show consumption at the top of the distribution). The
population curves
plotted above the horizontal axis represent the number of people
living at each
consumption level. The segment to the left of the $2.00 line
represents the propor-
tion of the 2011 population who were living on less than $2.00
per day. The verti-
cal density axis is dimensionless (it is normalised so that the
area bounded by the
FIGURE 4 Density Curve by International Poverty Lines, 1984–
2011
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4

0.6
0.8
10 100 1,000 10,000 100,000
$1.25 $2.00 $10.00 $50.00 per day
1984
1990
2000
2011
Population density
Income density
Income (PPP$ per capita)
Note: PPP = purchasing power parity.
Lines 217
population curve and the horizontal axis aggregates to unity).11
The lower curves
(plotted negatively) work in the same way, but they represent
the consumption of
the people living at any given level of consumption (as shown

on the horizontal
axis). The area between the consumption curve and the
horizontal axis indicates
how much the corresponding population (as indicated by the
population curve)
collectively consumes per year (in 2005 PPP dollars).
Figure 5 is the growth incidence curve (percentage changes in
real con-
sumption). The horizontal axis represents fractile rank ordered
by the level of
consumption. The vertical axis represents the percentage change
in consumption
per capita with plots for 1984–2011, 1990–2011, and 2000–
2011.12 The figure shows
that the broad base to economic growth over the periods at the
lower end of the
distribution is accompanied by more significant benefits
accruing to the top 15%–
25% of the population over the period.
11. In theory, it would be possible to assign to this axis a value
for actual population count,
but that would also require us to specify a bandwidth along the
horizontal axis over which
that aggregation was calculated. Since this is a log-scale, that
bandwidth would not trans-
late readily into a simple concept such as the current ‘X
thousand people per dollar of
consumption’. Our approach thus allows us to present the
population and consumption
curves in one graph on the same scale.
12. There is some sensitivity to the base years whenever
drawing a growth incidence curve.
For example, if for Indonesia we take 2003 as the base year (as
in the World Bank’s [2014,

38] report) and consider the 2003–11 period, we get the lowest
growth incidence possible
for the lower deciles (just 1.3% per year for the poorest 40%).
FIGURE 5 Change in Consumption per Person, by Fractile,
1984–2011, 1990–2011, and 2000–2011
0 10 20 30 40 50 60 70 80 90 100
0
50
100
150
200
250
$1.25 per day $2.00 per day $10.00 per day
%
Fractile location (%)
1984–2011
1990–2011
2000–2011

FIGURE 6 Past and Projected Poverty Headcounts (Total) by
International Poverty
Lines and in Three Inequality Scenarios, 1984–2030
(millions)
$10.00 per day
$2.00 per day
$1.25 per day
Static inequality
Extrapolated inequality
Lowest inequality
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014
2017 2020 2023 2026 2029
0
50
100
150
200
250
Note: Projected headcounts assume an optimistic level of

economic growth from 2011 to 2030.
FIGURE 7 Past and Projected Poverty Headcounts (Rural) by
(millions)
$10.00 per day
$2.00 per day
$1.25 per day
Static inequality
Lowest inequality
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014
2017 2020 2023 2026 2029
0
50
100
150
200
250

Lines 219
Trends in Poverty, 1984–2030
Figures 6 to 8 show total, rural, and urban poverty headcounts
in millions of peo-
ple from 1984–2030, and estimates of poverty by $1.25, $2.00,
and $10.00 poverty
lines (see also appendix table A1). In considering the trends of
poverty in Indo-
nesia, it is evident that the curve for poverty reduction is not
very smooth. The
two spikes noted by Suryahadi, Hadiwidjaja, and Sumatro
(2012) are visible in
figure 6. The data suggest that the end of $1.25 and $2.00
poverty in 2015–25 is
plausible under the scenario of optimistic economic growth if
distribution returns
to the lowest inequality level. This scenario is unequivocally
optimistic, however,
and simply illustrates what is possible.13
Figure 6 also shows that $10.00-per-day poverty will not start to
fall until 2025.
And if we accept the basis of a $10.00, ‘security from poverty’
poverty line, the
end of extreme and moderate poverty could be accompanied by
an increase in the
number of the ‘global insecure’ (possibly to 200 million by
2030).14 Conversely, we

13. In 1998, Thailand had similar levels of $2.00-per-day
poverty to Indonesia today. After
almost two decades of GDP growth at 3.8% per person per year
and largely static inequal-
ity, Thailand has reduced $2.00-per-day poverty to under 4.0%
of the population. A similar
pattern of growth and inequality could mean the end of poverty
in Indonesia by 2030.
14. The emergence of a substantial group of the ‘global
insecure’ raises questions for evolv-
ing public policy priorities and the balance between insurance
and risk-management
mechanisms versus ‘traditional’ poverty policy. See Dartanto
and Nurkholis’s (2013, 62)
taxonomy of chronic and transient poverty programs. See also
the detailed policy review
of Suryahadi et al. (2012).
FIGURE 8 Past and Projected Poverty Headcounts (Urban) by
(millions)
$10.00 per day
$2.00 per day
$1.25 per day
Static inequality
Lowest inequality
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014
2017 2020 2023 2026 2029

0
50
100
150
200
250
could argue that the fact that high incomes are not well captured
in the data gravi-
tates against the use of this higher poverty line.15 The $10.00-
per-day poverty rate
rose during 1984–2010 because about 99% of the population
were below this line
in 2010 (96% in 2011) and the population increased. According
to the data, up to
2010 nearly all of the population was below the $10.00 line
(and thus to the left
of the $10.00 line in figure 4), which suggests that the rich are
under-represented
in Susenas samples. Moreover, the population increased fastest

in urban areas,
meaning that poverty was becoming more urbanised.
Figure 9 shows the urban–rural proportions of total poverty.
The rural com-
ponent of total poverty by each poverty line is falling
drastically, and poverty
by international poverty lines is far more urbanised than by the
national poverty
line. Rather than two-thirds of the poor being rural, less than
half of the poor in
Indonesia are rural according to international poverty lines.
Such poverty lines
are commonly thought to underestimate urban poverty, owing to
urban–rural
price differentials and the presence of items that urban dwellers
pay for that rural
dwellers may not pay for (Mitlin and Satterthwaite 2002;
Satterthwaite 2004).
However, the data collected for PPPs and prices in Indonesia
may have a strong
urban bias, in that the International Comparison Program’s PPP
and Indonesian
government’s CPI data are typically collected in urban areas.
Thus the findings
here should be treated with caution, and further exploration is
needed on the
impact of PPP and price data in Indonesia on the urbanisation of
poverty before
making definitive conclusions.
15. For an estimate of $10.00-per-day poverty, we could add an
amount for income tax and
household savings and increase this in line with the NA-to-
survey ratio (which in 2010

was about 2.2 for Indonesia) to allow for consumption that is
not captured in surveys.
FIGURE 9 Rural Poverty as a Share of Total Poverty, 1984–
2011
(%)
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011
40
45
50
55
60
65
70
75
80
$1.25 per day
$2.00 per day
$10.00 per day

Lines 221
CONCLUSION
Indonesia experienced rapid economic development and poverty
reduction dur-
ing 1984–2011. So what do analyses of past and forecast future
patterns of Indo-
nesia’s growth, inequality, and poverty using international PPP
poverty lines tell
us? First, that Indonesia could become a high-income country
by 2030. Yet past
growth rates would probably err towards caution on this matter
as would the
experience of OECD countries where growth slowed at higher
levels of GDP per
capita. Second, that Indonesia could end $1.25-per-day and
$2.00-per-day poverty
by 2030 if economic growth meets the IMF’s WEO forecasts
and if distribution
moves to lowest inequality. Again, current and past trends
suggest that this is
very optimistic and growth would need to be accompanied by
falling inequality
from current levels. Another way of looking at this is that the
opportunity cost
of current inequality trends is an extra 10–20 years of $2.00
poverty in Indonesia.
Third, that much of the population will continue to live at levels
between day-to-
day $2.00 poverty and security from poverty (defined here as
the $10.00-per-day
line) for some time to come. Fourth, that poverty measured by
international pov-
erty lines seems to be far more urban compared to measurement
by the national

poverty line and on a steep curve to a greater urban proportion
of poverty though
this needs further exploration.
How different from the national poverty line are our findings
using interna-
tional poverty lines? In this article, we reviewed studies of
trends in expenditure
poverty, of the relation over time between expenditure poverty
and economic
growth, and of trends in inequality. On the first trend, we noted
that much research
using national poverty lines—meaning non-PPP lines—
concludes that absolute
poverty declined during the Soeharto era. Yet poverty was still
a problem in the
lead-up to the 1997–98 financial crisis, and it may have been
underestimated. Fur-
ther, welfare improvements slowed in the aftermath of the
crisis. Using consistent
international poverty lines of $1.25 and $2.00 (the first of
which is close now to the
national poverty line), we find that $1.25-per-day poverty
declined greatly during
the Soeharto era. The substantial decline of $2.00-per-day
poverty seems to date
largely from the post-Soeharto era, and the $10.00-per-day
poverty count appears
to have changed surprisingly little in 25 years. It is true that
poverty was at high
levels even before the 1997–98 crisis (more than 40% of the
population lived below
the $1.25-per-day poverty line and 80% below the $2.00-per-
day line). We find
that the rate of poverty reduction by $1.25 per day and $2.00
per day was particu-

larly fast in 2000–2005—faster than it was before the crisis—
which may reflect the
range of social programs introduced or extended after the crisis.
However, that
rate of poverty reduction has slowed since the rice-price-
induced poverty spike
in 2005–6, notably for the $1.25 poverty count and somewhat
notably for the $2.00
poverty count.
In studies of the relation between expenditure poverty and
economic growth,
we noted that research based on national poverty lines found
that, overall, eco-
nomic growth in Indonesia has benefited the poor. We find that
the benefits of
growth to those under the $2.00-per-day line have been
substantial during 1984–
2011. Economic growth appears to have benefited the poor
considerably— using
the $1.25 or $2.00 poverty lines—and overall growth has been
reasonably broad-
based at the lower end of the distribution, even though the rich
have gained most.
Some studies of trends in inequality have found that inequality
was relatively
low or declining in the lead-up to the 1997–98 crisis, and that
inequality did not
increase drastically as a result of economic growth. Others have
found that ine-

quality was high or increasing before the crisis. Further, many
have noted that
inequality has increased since the crisis. We find that total
inequality (measured
by the Gini coefficient or expenditure deciles) fell in the early
1990s (although this
masked rising urban inequality, because it was rural inequality
that fell substan-
tially). Since the crisis, however, inequality has risen. This is
potentially alarming;
rising inequality could slow not only poverty reduction but also
the rate and lon-
gevity of future economic growth.
In conclusion, we find that using international poverty lines,
which are compa-
rable across countries in PPP terms, to analyse the evolution of
poverty in Indo-
nesia complements analyses based on the national poverty line.
Our projections,
which should be taken cautiously as illustrations of what is
possible and not as
predictions, show the extent to which poverty reduction in
Indonesia is feasible
and the potential opportunity cost of rising inequality.
REFERENCES
Akita, Takahiro. 2002. ‘Regional Income Inequality in
Indonesia and the Initial Impact of
the Economic Crisis’. Bulletin of Indonesian Economic Studies
38 (2): 201–22.
Akita, Takahiro, Puji Agus Kurniawan, and Sachiko Miyata.
2011. ‘Structural Changes and
Regional Income Inequality in Indonesia: A Bidimensional

Decomposition Analysis’.
Asian Economic Journal 25: 55–77.
Akita, Takahiro, and Sachiko Miyata. 2008. ‘Urbanization,
Educational Expansion, and
Expenditure Inequality in Indonesia in 1996, 1999, and 2002’.
Journal of the Asia Pacific
Economy 13 (2): 147–67.
Aldenhoff, Frank-Oliver. 2007. ‘Are Economic Forecasts of the
International Monetary
Fund Politically Biased? A Public Choice Analysis’. Review of
International Organizations
2 (3): 239–60.
Asra, Abuzar. 2000. ‘Poverty and Inequality in Indonesia:
Estimates, Decomposition and
Key Issues’. Journal of the Asia Pacific Economy 51 (1–2): 91–
111.
Baliscan, Arsenio M., Ernesto M. Pernia, and Abuzar Asra.
2010. ‘Revisiting Growth and
Poverty Reduction in Indonesia: What Do Subnational Data
Show?’. Bulletin of Indone-
sian Economic Studies 39 (3): 329–51.
Berg, Andrew G. and Jonathan D. Ostry. 2011. ‘Inequality and
Unsustainable Growth: Two
Sides of the Same Coin?’. IMF Staff Discussion Note.
Washington DC: International
Monetary Fund.
Birdsall, Nancy, Nora Lustig, and Christian J. Meyer. 2013.
‘The Strugglers: The New Poor
in Latin America’. CGD Working Paper 337. Washington DC:
Center for Global Devel-

opment.
Booth, Anne. 1999. ‘Initial Conditions and Miraculous Growth:
Why is South East Asia Dif-
ferent from Taiwan and South Korea?’ World Development 27
(2): 301–21.
Booth, Anne. 2000. ‘Poverty and Inequality in the Soeharto Era:
An Assessment’. Bulletin of
Indonesian Economic Studies 36 (1), 73–104.
Commission on Growth and Development (2008) The Growth
Report: Strategies for Sus-
tained Growth And Inclusive Development. Washington DC:
World Bank.
Cornia, Giovanni Andrea, Tony Addison, and Sampsa Kiiski.
2004. ‘Income Distribution
Changes and Their Impact in the Post–Second World War
Period’. In Inequality, Growth,
and Poverty in an Era of Liberalization and Globalization,
edited by Giovanni Andrea Cor-
nia. Oxford: Oxford University Press.
Dartanto, Teguh, and Nurkholis. 2013. ‘The Determinants of
Poverty Dynamics in Indo-
nesia: Evidence from Panel Data’. Bulletin of Indonesian
Economic Studies 49 (1): 61–84.
Dhanani, Shafiq, and Iyanatul Islam. 2002. ‘Poverty,
Vulnerability and Social Protection in
a Period of Crisis: The Case of Indonesia’. World Development
30 (7): 1211–31.

Lines 223
Easterly, William. 2005. Inequality Does Cause
Underdevelopment. Washington DC: Center for
Global Development.
Edward, Peter. 2006. ‘Examining Inequality: Who Really
Benefits from Global Growth?’.
World Development, 34 (10): 1667–95.
Edward, Peter, and Andy Sumner. 2013a. ‘The Future of Global
Poverty in a Multi-Speed
World: New Estimates of Scale and Location, 2010–2030’.
Working Paper 327. Washing-
ton DC: Center for Global Development.
Edward, Peter, and Andy Sumner. 2013b. ‘The Poor, the
Prosperous and the “Inbetween-
ers”: A Fresh Perspective on Global Society, Inequality and
Growth’. IPC-IG Working
Paper 122. Brasília: International Policy Centre for Inclusive
Growth.
Edward, Peter, and Andy Sumner. 2014. ‘Estimating the Scale
and Geography of Global
Poverty Now and in the Future: How Much Difference Do
Method and Assumptions
Make?’ World Development 58: 67–82.
Fane, George, and Peter Warr. 2002. ‘How Economic Growth
Reduces Poverty: A General
Equilibrium Analysis for Indonesia’. UNU-WIDER Discussion
Paper 2002/19. Hel-
sinki: United Nations University World Institute for
Development Economics Research.

Frankema, Ewout, and Daan Marks. 2009. ‘Was It Really
“Growth with Equity” under
Soeharto? A Theil Analysis of Indonesian Income Inequality,
1961–2002’. Economics and
Finance in Indonesia 57 (1): 47–76.
Friedman, Jed. 2005. How Responsive Is Poverty to Growth? A
Regional Analysis of Pov-
erty, Inequality and Growth in Indonesia, 1984–1999’. UNU-
WIDER Discussion Paper
2003/57. Helsinki: United Nations University World Institute
for Development Eco-
nomics Research.
Friedman, Jed, and James Levinsohn. 2002. ‘The Distributional
Impacts of Indonesia’s
Financial Crisis on Household Welfare: A “Rapid Response”
Methodology’. The World
Bank Economic Review 16 (3): 397–423.
Hill, Hal. 2008. ‘Globalization, Inequality, and Local-Level
Dynamics: Indonesia and the
Philippines’. Asian Economic Policy Review 3 (1): 42–61.
Hill, Hal, Budy P. Resosudarmo, and Yogi Vidyattama. 2008.
‘Indonesia’s Changing Eco-
nomic Geography’. Bulletin of Indonesian Economic Studies 44
(3): 407–35.
Karver, Jonathan, Charles Kenny, and Andy Sumner 2012.
‘MDGs 2.0: What Goals, Targets,
and Timeframe?’. Working Paper 297. Washington DC: Center
for Global Development.
Lanjouw, Peter, Menno Pradhan, Fadia Saadah, Haneen Sayed,

and Robert Sparrow. 2001.
‘Poverty, Education and Health in Indonesia: Who Benefits
from Public Spending?’.
World Bank Policy Research Working Paper 2739. Washington
DC: World Bank.
Leigh, Andrew, and Pierre van der Eng. 2010. ‘Inequality in
Indonesia: What Can We Learn
from Top Incomes?’. Journal of Public Economics 93 (1–2):
209–12.
López-Calva, Luis F., and Eduardo Ortiz-Juarez. 2011. ‘A
Vulnerability Approach to the
Definition of the Middle Class’. Policy Research Working Paper
5902. World Bank,
Washington, DC.
McCulloch, Neil. 2008. ‘Rice Prices and Poverty in Indonesia’.
Bulletin of Indonesian Eco-
nomic Studies. 44 (1): 45–63.
McCulloch, Neil, and Amit Grover. 2010. ‘Estimating the
National Impact of the Financial
Crisis in Indonesia by Combining a Rapid Qualitative Study
with Nationally Repre-
sentative Surveys’. IDS Working Paper. Brighton: Institute of
Development Studies.
McDonald, Peter. 2014. ‘A Population Projection for Indonesia,
2010–2035’. Bulletin of Indo-
nesian Economic Studies 50 (1): 123–29.
Mitlin, Diana, and David Satterthwaite. 2002. ‘How the Scale
and Nature of Urban Poverty
Are Under-Estimated—The Limitations of the US$1 a Day
Poverty Line’. Paper presented

at the World Bank’s Urban Research Symposium, Washington
DC, 9–11 December.
Nugraha, Kunta, and Phil Lewis. 2013. ‘Towards a Better
Measure of Income Inequality in
Indonesia’. Bulletin of Indonesian Economic Studies 49 (1):
103–12.
Pradhan, Menno, Asep Suryahadi, Sudarno Sumarto, and Lant
Pritchett. 2001. ‘Eating
Like Which “Joneses?” An Iterative
Solution
to the Choice of a Poverty Line “Reference
Group”’. Review of Income and Wealth 47 (4): 473–87.
Ravallion, Martin, and Michael Lokshin. 2007. ‘Lasting Impacts
of Indonesia’s Financial
Crisis’. Economic Development and Cultural Change 56 (1):
27–56.
Ravallion, Martin. 2010. ‘The Developing World’s Bulging (but
Vulnerable) Middle Class’.

World Development 38 (4): 445–54.
———. 2012. ‘Benchmarking Global Poverty Reduction’.
Policy Research Working Paper
6205. Washington DC: World Bank.
Satterthwaite, David. 2004. ‘The Under-Estimation of Urban
Poverty in Low and Middle-
Income Nations’. IIED Poverty Reduction in Urban Areas Series
Working Paper 14.
London: International Institute for Environment and
Development .
Skoufias, Emmanuel. 2001. ‘Changes in Regional Inequality and
Social Welfare in Indone-
sia from 1996 to 1999’. Journal of International Development
13 (1): 73–91.
Skoufias, Emmanuel, Asep Suryahadi, and Sudarno Sumarto.
2000. ‘Changes in House-
hold Welfare, Poverty and Inequality during the Crisis’.
Bulletin of Indonesian Economic
Studies 36 (2): 97–114.
Sumner, Andy, and Peter Edward. 2013. ‘From Low Income,

High Poverty to High Income,
No Poverty? An Optimistic View of the Long-Run Evolution of
Poverty in Indonesia
by International Poverty Lines, 1984–2030’. Working Paper in
Economics and Develop-
ment Studies 201310. Bandung: Department of Economics,
Padjadjaran University.
Sumner, Andy, Asep Suryahadi, and Nguyen Thang. 2012.
‘Poverty and Inequalities in
Middle-Income Southeast Asia’. IDS Working Paper. Brighton:
Institute of Develop-
ment Studies.
Suryadarma, Daniel, Rima Prama Artha, Asep Suryahadi, and
Sudarno Sumarto. 2005. ‘A
Reassessment of Inequality and Its Role in Poverty Reduction in
Indonesia’. SMERU
Working Paper. Jakarta: SMERU Research Institute.
Suryadarma, Daniel, Wenefrida Widyanti, Asep Suryahadi, and
Sudarno Sumarto. 2006.
‘From Access to Income: Regional and Ethnic Inequality in
Indonesia’. SMERU Work-
ing Paper. Jakarta: SMERU Research Institute.

Suryahadi, Asep, Gracia Hadiwidjaja, and Sudarno Sumarto.
2012. ‘Economic Growth and
Poverty Reduction in Indonesia before and after the Asian
Financial Crisis’. Bulletin of
Indonesian Economic Studies 48 (2): 209–27.
Suryahadi, Asep, and Sudarno Sumarto. 2003a. ‘Poverty and
Vulnerability in Indonesia
before and after the Economic Crisis’. Asian Economic Journal
17 (1): 45–64.
Suryahadi, Asep, and Sudarno Sumarto. 2003b. ‘The Evolution
of Poverty during the Crisis
in Indonesia’. SMERU Working Paper. Jakarta: SMERU
Research Institute.
Suryahadi, Asep, Daniel Suryadarma, and Sudarno Sumarto.
2006. ‘Economic Growth and
Poverty Reduction in Indonesia: The Effects of Location and
Sectoral Components of
Growth’. SMERU Working Paper. Jakarta: SMERU Research
Institute.
Suryahadi, Asep, Umbu Reku Raya, Deswanto Marbun, and

Athia Yumna. 2012. ‘Accel-
erating Poverty and Vulnerability Reduction: Trends,
Opportunities, and Constraints’.
SMERU Working Paper. Jakarta: SMERU Research Institute.
Timmer, C. Peter. 2004. ‘The Road to Pro-Poor Growth: The
Indonesian Experience in
Regional Perspective’. Bulletin of Indonesian Economic Studies
40 (2): 177–207.
Van der Eng, Pierre. 2009. ‘Growth and Inequality: The Case of
Indonesia, 1960–1997’.
MPRA Paper 12725. Munich: Munich Personal RePEc Archive.
Van Leeuwen, Bas, and Peter Foldvari. 2011. The Development
of Inequality and Poverty
in Indonesia, 1932–1999. CGEH Working Paper 26. Utrecht:
Centre for Global Economic
History, Utrecht University.
World Bank. 2014. Indonesia Economic Quarterly: Investment
in Flux. Jakarta: World Bank.
Yusuf, Arief Anshory, Andy Sumner, and Irlan Adiyatma Rum.
2014. ‘Twenty Years of

Expenditure Inequality in Indonesia, 1993–2013’. Bulletin of
Indonesian Economic Studies
50 (2): 243–54.
A
P
P
E
N
D
IX
T
A
B
L
E
A

1
H
ea
dc
ou
n
t
(m
il
li
on
s)
a
n
d
T
ot

al
P
ov
er
ty
G
ap
(
P
P
P
2
00
5
$
bi

ll
io
n
),
b
y
In
te
rn
at
io
n
al
P
ov
er
ty

L
in
es
, 1
98
4–
20
11
19
84
19
87
19
90
19
93

19
96
19
99
20
02
20
05
20
06
20
07
20
08
20
09
20

10
20
11
R
u
ra
l
H
ea
d
co
u
n
t
$1
.2

5
79
.0
88
.1
71
.6
73
.6
59
.2
65
.8
40
.2
28

.9
37
.4
30
.1
27
.3
23
.8
19
.7
17
.3
$2
.0
0

10
8.
3
11
2.
6
11
1.
4
11
2.
4
10
8.
9
10
8.

8
92
.0
71
.0
82
.4
70
.1
66
.8
63
.3
53
.7
49

.6
$1
0.
00
12
3.
0
12
6.
0
12
7.
9
12
8.
5

12
7.
7
12
4.
9
12
1.
7
11
8.
0
11
6.
7
11
5.

4
11
4.
0
11
2.
6
11
1.
1
10
9.
7
P
op

u
la
ti
on
12
3.
0
12
6.
0
12
7.
9
12
8.
5
12

7.
7
12
4.
9
12
1.
7
11
8.
0
11
6.
7
11
5.
4

11
4.
0
11
2.
6
11
1.
1
10
9.
7
To
ta
l p
ov

er
ty
g
ap
$1
.2
5
12
.3
13
.4
9.
3
9.
5
6.

9
8.
0
3.
7
2.
7
4.
0
2.
8
2.
4
1.
9
1.
5

1.
2
$2
.0
0
39
.6
42
.5
36
.0
36
.8
30
.7

33
.6
22
.3
16
.7
20
.8
16
.9
15
.6
14
.1
11
.7
10

.5
$1
0.
00
39
4.
7
40
7.
2
40
4.
6
40
7.
4

39
5.
2
39
3.
7
36
7.
2
34
1.
5
34
8.
6
33

4.
1
32
7.
8
32
0.
8
30
4.
3
29
1.
3
U
rb
an

H
ea
d
co
u
n
t
$1
.2
5
22
.9
29
.5
26
.7

30
.2
27
.6
33
.2
23
.7
20
.9
28
.6
26
.1
25
.9

25
.5
23
.5
23
.8
$2
.0
0
35
.7
42
.2
44
.1
50

.2
49
.2
62
.0
53
.7
49
.4
62
.3
57
.7
59
.1
59
.8

55
.1
55
.4
$1
0.
00
41
.7
48
.8
56
.4
65
.0

74
.6
85
.8
97
.3
10
4.
7
11
3.
2
11
6.
5
12
0.

5
12
3.
8
12
5.
7
12
4.
1
P
op
u
la
ti
on

41
.7
48
.8
56
.4
65
.0
74
.6
85
.8
97
.3
10
9.

3
11
3.
2
11
7.
0
12
0.
9
12
4.
8
12
8.
8
13

2.
7
To
ta
l p
ov
er
ty
g
ap
$1
.2
5
3.
6
4.

8
3.
7
4.
2
3.
6
4.
0
2.
2
1.
9
3.
0
2.

6
2.
6
2.
4
2.
1
2.
1
$2
.0
0
11
.9
15
.1

13
.6
15
.3
14
.4
17
.3
13
.1
11
.7
15
.7
14
.2
14

.3
14
.2
13
.0
13
.1
$1
0.
00
13
0.
6
15
4.

7
17
2.
0
19
7.
3
21
7.
4
25
4.
3
27
1.
8
28

3.
8
31
5.
7
31
3.
9
32
4.
9
33
2.
8
33
0.
2

33
1.
6
T
o
ta
l
H
ea
d
co
u
n
t
$1

.2
5
10
1.
9
11
7.
6
98
.3
10
3.
8
86
.8
99
.0

63
.9
49
.8
66
.0
56
.2
53
.2
49
.2
43
.2
41
.1

$2
.0
0
14
4.
0
15
4.
8
15
5.
5
16
2.
6
15

8.
1
17
0.
7
14
5.
7
12
0.
4
14
4.
7
12
7.
8

12
5.
8
12
3.
1
10
8.
7
10
4.
9
$1
0.
00
16

4.
7
17
4.
8
18
4.
3
19
3.
5
20
2.
3
21
0.

6
21
9.
0
22
2.
7
22
9.
9
23
1.
9
23
4.
5
23

6.
4
23
6.
8
23
3.
7
P
op
u
la
ti
on
16
4.

7
17
4.
8
18
4.
3
19
3.
5
20
2.
3
21
0.
6

21
9.
0
22
7.
3
22
9.
9
23
2.
5
23
5.
0
23
7.

4
23
9.
9
24
2.
3
To
ta
l p
ov
er
ty
g
ap
$1

.2
5
15
.9
18
.2
13
.1
13
.7
10
.5
12
.0
6.
0

4.
6
7.
0
5.
4
5.
0
4.
4
3.
6
3.
2
$2
.0

0
51
.5
57
.6
49
.6
52
.1
45
.0
50
.9
35
.4
28
.3

36
.5
31
.1
29
.9
28
.3
24
.7
23
.6
$1
0.
00

52
5.
2
56
2.
0
57
6.
6
60
4.
6
61
2.
6
64
8.

0
63
9.
0
62
5.
3
66
4.
3
64
8.
0
65
2.
7
65

3.
6
63
4.
4
62
2.
9
S
ou
rc
e:
A
u
th
or

s’
e
st
im
at
es
d
er
iv
ed
f
ro
m
G
ro
w
th

, I
n
eq
u
al
it
y,
a
n
d
P
ov
er
ty
(
G
rI

P
)
m
od
el
v
.1
.0
, d
es
cr
ib
ed
in
d
et

ai
l b
y
E
d
w
ar
d
a
n
d
S
u
m
n
er
(

20
13
a,
2
01
3b
, 2
01
4)
.
N
ot
e:
P
P
P

=
p
u
rc
h
as
in
g
p
ow
er
p
ar
it
y.

Copyright of Bulletin of Indonesian Economic Studies is the
property of Routledge and its
content may not be copied or emailed to multiple sites or posted
to a listserv without the
copyright holder's express written permission. However, users
may print, download, or email
articles for individual use.
International Perspectives Paper
SOCW-3303, Fall 2018
nd of day on 10/07/2018
1. You will select a least developing country of your choice.
Please check the status of
your country in;

-operation and
Development (OECD):
https://data.oecd.org/
http://www.imf.org/en/data
http://www.ilo.org/ilostat/faces/ilostat-
home/home?_adf.ctrl-
state=bhb14mt84_4&_afrLoop=460832434872252#!
course, you can choose other data sources. There are so
many data sources on the
website. However, if you choose other data sources, please
consider the trustworthy
of the data sources OR please email me ([email protected]).
2. Write at least 4 pages or more analysis for that country using
the following general

outline structure:
a. What is the system of government in that country?
b. What is the status of its political economy and its
implications?
c. List the general socio-economic status of the country (e.g. per
capita income,
educational level, infant mortality rate and life expectancy): If
you use graph,
table, and some visual materials, it would be very useful for
your paper.
d. Choose and explore a topic for policy analysis (e.g.
education; health; water;
poverty, gender, trade etc.)
http://data.worldbank.org/
https://data.oecd.org/
http://www.imf.org/en/data
http://www.ilo.org/ilostat/faces/ilostat-home/home?_adf.ctrl-

state=bhb14mt84_4&_afrLoop=460832434872252%23!
http://www.ilo.org/ilostat/faces/ilostat-home/home?_adf.ctrl-
state=bhb14mt84_4&_afrLoop=460832434872252%23!
e. Suggest at least 2 social, economic, or policy strategies you
propose and why?
3. You should develop your paper to follow APA style. The
paper should be at least 4
pages or more (Times New Roman, double spaced, 12 points,
APA style, and exclude
cover and reference; it means I won’t count it for the grading,
but you must make it). you
need to upload on Blackboard. Also, I will post APA template
on Blackboard, so please
apply it to your paper.
Assessment Rubric for International Perspective Paper
Topic Unsatisfactory Marginal Proficient Exemplary

Description of the
system of
government
7 assigned points
No facts or only a few.
Very limited
understanding of the
issue or problem.
0 ~ 2 points

Several facts.
Superficial knowledge
of social issue or
problem.
3 ~ 4 points
Adequate facts.
Significant and fairly
well supported
description.

5 ~ 6 points
Detailed facts and
clearly presented. A
well-articulated and
well informed
perspective is evident.
7 points
Understanding of the
political economy
status and its
implications

9 assigned points
Very limited
understandings of the
political economy and
its implications.
0 ~ 2 points
Satisfactory evidence
in understandings of
the political economy.
Some implications

discussed.
3 ~ 5 points
Good discussion and
evidence of the
several implications
explored.
6 ~ 8 points
Thorough

discussion of the
major repercussions of
the policy.
9 points
Understanding of the
socio-economic
status and its
implications
9 assigned points
Very limited

understandings of the
socio-economic status
of the country and its
implications.
0 ~ 2 points
Satisfactory evidence
in understandings of
the socio-economic
status of the country.
Some implications
discussed.

3 ~ 5 points
Good discussion and
evidence of the socio-
economic status of the
country and several
implications explored.
6 ~ 8 points
Thorough
socio-economic status

of the country and
discussion of the
major repercussions of
the policy.
9 points
Proposal of social,
economic, or policy
strategies
15 assigned points
No evidence of

persuasive writing.
Errors in logic and
critical thinking.
Unclear about what
you are proposing.
0 ~ 5 points
Persuasive writing is
evident, but
unconvincing. Logic
and critical thinking
are weak or unclear.

6 ~ 10 points
generally sufficient.
Logic and critical
thinking are good, but
not fully
comprehensive.
11 ~ 14 points
very strong. Logic
and critical thinking
are thorough and

thoughtful.
15 points
Total: 40 points
If you have any questions or suggestions about it, please email
me
anytime ([email protected]).

Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014.docx

Recommended

Recommended

More Related Content

Similar to Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014.docx

Similar to Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014.docx (20)

More from curwenmichaela

More from curwenmichaela (20)

Recently uploaded

Recently uploaded (20)

Bulletin of Indonesian Economic Studies, Vol. 50, No. 2, 2014.docx