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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. (2013). Sumner, Andy ; Edward, Peter.
In: Working Papers in Economics and Development Studies (WoPEDS).
RePEc:unp:wpaper:201310.

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  1. Who are likely to be the future poor in Indonesia? Evidence on primary school non-completion from six rounds of the Demographic and Health Survey, 1991-2012. (2014). Sumner, Andy.
    In: Working Papers in Economics and Development Studies (WoPEDS).
    RePEc:unp:wpaper:201406.

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  1. 2. INDONESIAN DEVELOPMENT SINCE 1984 2a. Economic development 2
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  2. 4a. Income per capita trends, 1984–2030 The first set of graphs show income per capita. Figures5 and 6 respectively show GNI per capita by Atlas method and GDP per capita by PPP. Indonesia is compared to a set of populous and fast growing economies, namely, China, Brazil, India and Nigeria. The graphs show that Indonesia may cross the threshold in the next 1–2 years into the ‘Upper Middle-Income Country’ classification and could attain high-income country (HIC) status around 2025. These estimates are based on the‘optimistic’ economic growth scenario (meaning IMF WEO forecast extrapolated out to 2030 at 6.7% a year which is clearly an optimistic scenario).
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  3. 4b. Historical patterns of growth, 1984–2011 A second set of graphs show growth-distribution trends over the 1984–2011 period. Figures 7 and 8 show the pattern of that growth in a density curve and a fractile chart.
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  4. • Household Final Consumption (HFC) data are taken from WDI which provides annual data throughout the 1984 to 2011 period.
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  5. • We take population data for the urban and rural from Povcal for all the survey years except 2011which is not presented. For 2011 we estimate from the trends for the urban-rural shares from earlier years. The urban/rural split in the forecast populations (see annex) is based on a linear extrapolation of the change in the shares from 1990 to 2010 which is then applied to the UN total population forecast. 7
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  6. Additional charts are annexed with different base years and urban and rural density curves.These graphs show the gradual shift of the poverty peak (and decline in size of the peak) between 1984 and 2011 and thus the emergence of those in the $2–$10/day group (arguably, between day-to-day poverty and security from poverty). 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.This is consistent with Yusuf (2013, forthcoming) that the decile dispersion ratio (10% top to 10% bottom) has risen by 70% for the last ten years.
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  7. Akita, T. (2003). Decomposing regional income inequality in China and Indonesia using two-stage nested Theil decomposition method. The Annals of Regional Science 37(1), 55-77.

  8. Akita, T., & Miyata, S. (2008). Urbanization, educational expansion, and expenditure inequality in Indonesia in 1996, 1999, and 2002. Journal of the Asia Pacific Economy 13(2).

  9. Akita, T., Kurniawan, P. A., & Miyata, S. (2011). Structural Changes and Regional Income Inequality in Indonesia: A Bidimensional Decomposition Analysis. Asian Economic Journal 25, 55–77.

  10. Alisjahbana, A., & Yusuf, A. A. (2003). Poverty Dynamics in Indonesia: Panel Data Evidence. Working Paper in Economics andDevelopment Studies. Padjadjaran University: Department of Economics.

  11. Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics 95(7-8). 476-487.

  12. Alkire, S., & Santos, M. E. (2010). Acute Multidimensional Poverty – A New Index for Developing Countries. Accessed 29 June 2012. Available from <http://www.ophi.org.uk/wp-content/uploads/ophi-wp38.pdf> Armida S. A., & Manning, C. (2006). Labour market dimensions of poverty in Indonesia. Bulletin of Indonesian Economic Studies42(2), 235-261.

  13. Although Indonesia’s $2 poverty rate is surprisingly higher than poorer Southeast Asian neighbours such as Vietnam (Table 1), when Indonesia is compared to the averages of each income group (see Table 2 and Suryahadi et al., 2012; Sumner, 2012), Indonesia is certainly much closer to the upper middle-income group average in terms of ODA indicators. However, Indonesia is closer to the lower middle-income group weighted mean in terms of the proportional increase in GDP PPP per capita since 1990, the contribution of agriculture to GDP, and closer to the low-income group weighted mean in terms of primary export dependency.
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  14. Another issue of note is that the rural component 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. In fact, rather than two-thirds of the poor being rural, it is less than half of the poor in Indonesia who are rural when one uses international poverty lines. It is commonly thought international poverty lines underestimate urban poverty for methodological reasons (see Satterthwaite, Mitlin, and others). Figures 17showsthe urban/rural proportions of total poverty.Various other figures are annexed including those for the poverty gap. 24 Figure 12. Poverty, total,millions, 1984–2011 Source:Author estimates.
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  15. Asra, A. (2000). Poverty and inequality in Indonesia: estimates, decomposition and key issues. Journal of the Asia Pacific Economy 51(1–2), 91–111.

  16. Available from www.measuredhs.com/pubs/pdf/DHSG1/Guide_DHS_Statistics.pdf Solt, F. (2008) Standardized World Income Inequality Database. Social Science Quarterly 9(2): 231-242 Skoufias, E. (2001), Changes in regional inequality and social welfare in Indonesia from 1996 to 1999. Journal of InternationalDevelopment13, 73–91.
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  17. Baliscan, A. M., Pernia, E. M., & Asra, A. (2010). Revisiting growth and poverty reduction in Indonesia: what do subnational data show? Bulletin of Indonesian Economic Studies 39(3), 329-351.

  18. Bardosono, S., Sastroamidjojo, S., & Lukito, W. (2007). Determinants of child malnutrition during the 1999 economic crisis in selected poor areas of Indonesia. Asia PacificJournal of Clinical Nutrition 16(3), 512-526.
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  19. Booth (1999) argued that initial conditions were crucial in differentiating this more recent Southeast Asian miracle from the older East Asian ‘miracle’. 6 Figure 1. Indonesia: Income per capita, 1984–2011 Source: WDI (2013).
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  20. Booth, A. (2000). Poverty and Inequality in The Soeharto Era: An Assessment.

  21. Bulletin of Indonesian Economic Studies 36(1), 73-104. 29 Cameron, L. (2000). The Impact of the Indonesian Financial Crisis on Children: An Analysis using the 100 Villages Data. Innocenti Working Paper 81. Florence: UNICEF.

  22. Chandy, L. and Gertz, G. (2011) Poverty in Numbers: The Changing State of Global Poverty from 2005 to 2015, Policy Brief 2011-01, Washington, DC: Global Economy and Development at Brookings, The Brookings Institution Deaton, A. (2011) ‘Measuring Development: Different Data, Different Conclusions’, paper presented at the 8th AFD-EUDN Conference, Paris Dhanani, S., & Islam, I. (2002). Poverty, Vulnerability and Social Protection in a Period of Crisis: The Case of Indonesia. World Development 30(7), 1211-1231.

  23. Fields, G. S., Cichello, P. L., Freije, S., Menéndez, M., & Newhouse, D. (2003). For Richer or for Poorer? Evidence from Indonesia, South Africa, Spain, and Venezuela. Journal of Economic Inequality 1, 67-99.

  24. Figure 11. Share of GNI to poorest 40%, middle 50% and top 10 %, 1984–2011 Source:Author estimates. 0.20 0.25 0.30 0.35 0.40 0.45 1984 1989 1994 1999 2004 2009 Total Rural Urban 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 1984 1990 1996 2002 2006 2008 2010 1987 1993 1999 2005 2007 2009 2011 1984 1990 1996 2002 2006 2008 2010 Percentageshareofdistribution D1 to D4 D5 to D9 D10 Total Rural Urban 23 4d. Trends in poverty reduction, 1984–2030 Finally, poverty trends are presented. Figures 12 to 14 show total, rural and urban poverty headcounts in millions of people from 1984–2030 and the total poverty gap in US$bn (2005 PPP$). Figures 15 to 17 show the rural proportion by $1.25, $2 and $10 poverty lines. The two Suryahadi et al., (2012) spikes in poverty are clearly visible.
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  25. Figure 13. Poverty, total, millions, 1984–2030 (optimistic growth, three distribution scenarios) Source:Author estimates. 0.0 20.0 40.0 60.0 80.0 100.0 120.0 1980 1985 1990 1995 2000 2005 2010 2015 Total poverty as % of population $1.25 $2 $10 0.0 50.0 100.0 150.0 200.0 250.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Povertyheadcount(millions) $1.25 Headcount $2 Headcount $10 Headcount Static, Optimistic Extrapolated, Optimistic Best, Optimistic 25 Figure 14. Total Poverty Gap (TPG), US$bn (PPP), 1984–2030 (optimistic growth, three distribution scenarios) Source:Author estimates.
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  26. Figure 15. Income poverty, rural, millions, 1984–2030 (optimistic growth, three distribution scenarios) Source:Author estimates. 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 TotalPovertyGap($billions) $1.25 TPG $2 TPG $10 TPG Static, Optimistic Extrapolated, Optimistic Best, Optimistic 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Povertyheadcount(millions) Rural, $1.25 Headcount Rural, $2 Headcount Rural, $10 Headcount Static, Optimistic Extrapolated, Optimistic Best, Optimistic 26 Figure 16. Income poverty, urban, millions, 1984–2030 (optimistic growth, three distribution scenarios) Source:Author estimates.
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  27. Figure 2. Indonesia, ODA indicators, 1984–2011 Source: WDI (2013). 0 500 1000 1500 2000 2500 3000 3500 4000 4500 GNI per capita, Atlas method (current US$) GDP per capita, PPP (constant 2005 international $) 0 2 4 6 8 10 12 14 16 19841986198819901992199419961998200020022004200620082010 Net ODA received (% of GNI) Net ODA received (% of central government expense) Net ODA received (% of gross capital formation) 7 Figure 3. Indonesia, sectoral proportion of GDP, 1984–2011 Source: WDI (2013).
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  28. Figure 4. Indonesia, sectoral proportion of labour force, 1984–2011 Source: WDI (2013). 0 10 20 30 40 50 60 Agriculture, valu e added (% of GDP) Industry, value added (% of GDP) Services, etc., val ue added (% of GDP) 0 10 20 30 40 50 60 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 Employment in agriculture (% of total employment) Employment in industry (% of total employment) Employment in services (% of total employment) 8 Indonesia,though,fares reasonably well in relative assessments to other countries.
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  29. Figure 5. GNI per capita, 1984–2030 (optimistic growth from 2011) Source:Author estimates. 0 5000 10000 15000 20000 25000 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 GNIpercapita(constant2010$,Atlasmethod) Indonesia China Brazil India Nigeria LIC-LMIC LMIC-UMIC UMIC-HIC 19 Figure 6. GDP (PPP) per capita, 1984–2030 (optimistic growth from 2011) Source:Author estimates.
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  30. Figure 9. Theil, 1984-–011 Source:Author estimates. 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 1984 1989 1994 1999 2004 2009 Total Rural Urban 22 Figure 10. Gini, 1984–2011 Source:Author estimates.
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  31. Figure A10. Total poverty gap (TPG), $1.25 US$bn (PPP) Source: Author estimates. -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 10 100 1,000 10,000 100,000 <=IncomeDensityPopulation=> Income ($ PPP per capita pa) - log scale 1984 1990 2000 2011 $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 Input Criteria 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 TotalPovertyGap($billions) Total, $1.25 TPG Rural, $1.25 TPG Urban, $1.25 TPG Static, Optimistic Extrapolated, Optimistic Best, Optimistic 48 Figure A11. Total poverty gap (TPG), $2 US$bn (PPP) Source: Author estimates.
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  32. Figure A12. Total poverty gap (TPG), $10 US$bn (PPP) Source: Author estimates. 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 TotalPovertyGap($billions) Total, $2 TPG Rural, $2 TPG Urban, $2 TPG Static, Optimistic Extrapolated, Optimistic Best, Optimistic 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 TotalPovertyGap($billions) Total, $10 TPG Rural, $10 TPG Urban, $10 TPG Static, Optimistic Extrapolated, Optimistic Best, Optimistic 49 Figure A13. Rural and urban poverty, millions, 1984–2011 Source: Author estimates.
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  33. Figure A14. Rural poverty as a % total, $1.25 Source: Author estimates. 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 1980 1985 1990 1995 2000 2005 2010 2015 Rural, $1.25 Headcount Rural, $2 Headcount Rural, $10 Headcount Urban, $1.25 Headcount Urban, $2 Headcount Urban, $10 Headcount 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 1980 1990 2000 2010 2020 2030 2040 Rural poverty as % of total poverty $1.25 Static, Optimistic Extrapolated, Optimistic Best, Optimistic 50 Figure A15. Rural poverty as a % total, $2 Source: Author estimates.
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  34. Figure A16. Rural poverty as a % total, $10 Source: Author estimates. 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 1980 1990 2000 2010 2020 2030 2040 Rural poverty as % of total poverty $2 Static, Optimistic Extrapolated, Optimistic Best, Optimistic 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 1980 1990 2000 2010 2020 2030 2040 Rural poverty as % of total poverty $10 Static, Optimistic Extrapolated, Optimistic Best, Optimistic
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  35. Figure A2. Fractile chart, 1984–2011 Source: Author estimates. 0.0 50.0 100.0 150.0 200.0 250.0 300.0 10 100 1000 10000 100000 Percentagechangeofconsumptionpercapita Fractile location ($ PPP per capita pa) 1984 to 2011 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate:HFC Filled: Yes NA/S option: 1 InputCriteria 0.0 50.0 100.0 150.0 200.0 250.0 300.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Percentagechangeofconsumptionpercapita Fractile location (%) 1984 to 2011 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate:HFC Filled: Yes NA/S option: 1 InputCriteria 44 Figure A3. Fractile chart, 1987–2011 Source: Author estimates.
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  36. Figure A4. Fractile chart, 1987–2011 Source: Author estimates. 0.0 50.0 100.0 150.0 200.0 250.0 300.0 10 100 1000 10000 100000 Percentagechangeofconsumptionpercapita Fractile location ($ PPP per capita pa) 1987 to 2011 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate:HFC Filled: Yes NA/S option: 1 InputCriteria 0.0 50.0 100.0 150.0 200.0 250.0 300.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Percentagechangeofconsumptionpercapita Fractile location (%) 1987 to 2011 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 InputCriteria 45 Figure A5. Fractile chart, 1990–2010 Source: Author estimates.
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  37. Figure A6. Fractile chart, 1990–2010 Source: Author estimates. 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 10 100 1000 10000 100000 Percentagechangeofconsumptionpercapita Fractile location ($ PPP per capita pa) 1990 to 2010 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 InputCriteria 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Percentagechangeofconsumptionpercapita Fractile location (%) 1990 to 2010 Global average $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 InputCriteria 46 Figure A7. Density curve, 1984–2011, all Indonesia Source: Author estimates.
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  38. Figure A8. Density curve, 1984–2011, Indonesia urban Source: Author estimates. -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 10 100 1,000 10,000 100,000 <=IncomeDensityPopulation=> Income ($ PPP per capita pa) - log scale 1984 1990 2000 2011 $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 Input Criteria -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 10 100 1,000 10,000 100,000 <=IncomeDensityPopulation=> Income ($ PPP per capita pa) - log scale 1984 1990 2000 2011 $1.25 a day $2 a day $10 a day $50 a day Aggregate: HFC Filled: Yes NA/S option: 1 Input Criteria 47 Figure A9. Density curve, 1984–2011, Indonesia rural Source: Author estimates.
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  39. Fischer, A.M. (2010) ‘Towards Genuine Universalism within Contemporary Development Policy’, IDS Bulletin 41, 36–44 Frankema, E., & Marks D. (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.

  40. Friedman, J. (2005). How responsive is poverty to growth? A regional analysis of poverty, inequality and growth in Indonesia, 1984–1999. World Institute for Development Economics Research Discussion Paper no. 2003/57. Helsinki: WIDER.

  41. Friedman, J., & Levinsohn, J. (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 Glassman, A. Duran, D. and Sumner, A. (2011) Global Health and the New Bottom Billion: What Do Shifts in Global Poverty and the Global Disease Burden Mean for GAVI and the Global Fund?, CGD Working Paper, Washington, DC: Center for Global Development 30 Hill, H. (2008). Globalization, Inequality, and Local-level Dynamics: Indonesia and the Philippines. Asian Economic Policy Review3, 42–61.

  42. Future changes are estimated by linear extrapolation of the trends calculated from 1990 to 2010 (see Table 3); • ‘Best-ever distribution’ = a scenario representing a return to the lowestinequality historical distribution in the PovcalNet dataset for Indonesia (which is 1999 for rural Indonesia and 1987 for urban Indonesia).
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  43. Hill, H., Resosudarmo, B. P., & Vidyattama, Y. (2008). Indonesia's Changing Economic Geography. Bulletin of IndonesianEconomic Studies 44(3), 207-435.

  44. If one compares income per capita in Indonesia and the country groups as a percentage of OECD high-income countries (HICs), in PPP terms, income per capita in Indonesia in 1990 was 18% of OECD high-income countries weighted average and only slightly rose to 19% in 2008 (above the low-income countries weighted mean and some distance from the upper middle-income country average).
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  45. Indeed, Suryahadi et al., (2012) note poverty has only risen twice in Indonesia: during the 1996–9 economic crisis due to job losses and hyperinflation and again in 2005–6 due to inflation caused by domestic fuel price rises and the rises in the cost of rice (which were caused by the 2004 ban on rice imports – see McCulloch 2008).
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  46. Kanbur, R. and Sumner, A. (2011a) Poor Countries or Poor People? Development Assistance and the New Geography of Global Poverty, Working Paper 2011-08, Ithaca, NY: Charles H. Dyson School of Applied Economics and Management, Cornell University Kanbur, R. and Sumner, A. (2011b) Poor Countries or Poor People? Development Assistance and the New Geography of Global Poverty, CEPR Working Paper, London: CEPR Koch, S. (2011) Poverty Reduction in a Changing Development Landscape’, paper presented at DSA-EADI Conference, York, UK Lanjouw, P., Pradhan, M., Saadah, F., Sayed, H., & Sparrow, R. (2001). Poverty, Education and Health in Indonesia: Who Benefits from Public Spending? Mimeograph. Washington DC: World Bank.

  47. Leigh, A., & van der Eng, P. (2010). Inequality in Indonesia: What can we learn from top incomes? Journalof Public Economics93(1-2), 209-212 McCulloch, N., & Grover, A. (2010). Estimating the National Impact of the Financial Crisis in Indonesia by Combining a Rapid Qualitative Study with Nationally Representative Surveys. IDS Working Paper. Brighton: IDS.

  48. McCulloch, N., Weisbrod, J., & Timmer, P.C. (2007). Pathways out of poverty during an economic crisis: an empirical assessment of rural Indonesia. World Bank Policy Research Working Paper 4173. Washington DC: World Bank Miranti, R. (2010), Poverty in Indonesia 1984–2002: the impact of growth and changes in inequality, Bulletin of IndonesianEconomic Studies, 46(1), 79-97.

  49. Miranti, R., & Resosudarmo, B. P. (2005) Understanding regional poverty in Indonesia: is poverty worse in the east than in the west? Australasian Journal of Regional Studies11(2), 141–54. 31 Newhouse, D. (2005). The Persistence of Income Shocks: Evidence from Rural Indonesia. Review ofDevelopment Economics 9, 415–433 Pakpahan, Y. M., Suryadarma, D., & Suryahadi, A. (2009). Destined for destitution: intergenerational poverty persistence in Indonesia. SMERUResearch Institute Working Paper. Jakarta: SMERU Pradhan, M. (2009), Welfare Analysis with a Proxy Consumption Measure: Evidence from a Repeated Experiment in Indonesia. FiscalStudies 30, 391–417.

  50. Mortality inequalities in times of economic growth: time trends in socioeconomic and regional inequalities in under 5 mortality in Indonesia, 1982-1997. Journal ofEpidemiology and Community Health 60(1) 62-68.
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  51. Povc al 0.3 05 0.2 93 0.2 92 0.2 93 0.3 13 0.2 90 0.2 97 0.3 40 0.3 41 0.3 56 GrIP 0.3 04 0.2 91 0.2 95 0.2 99 0.3 22 0.3 04 0.3 11 0.3 58 0.3 29 0.3 44 0.3 39 0.3 39 0.3 53 0.3 18 4. HISTORICAL PATTERNS AND PROJECTIONS, 1984–2030 In the figures (5-17) presented below we can consider growth, distribution and poverty from 1984–2011 and make projections to 2030 where appropriate. The graphs are grouped by:(a) income per capita trends; (b) historical patterns of growth; (c) trends in inequality; and (d) trends in poverty.
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  52. Pradhan, M., Suryahadi, A., Sumarto, S., & Pritchett, L. (2000). Measurements of Poverty in Indonesia: 1996, 1999, and Beyond, PolicyResearch Working Paper 2438. Washington, DC: World Bank.

  53. Pradhan, M., Suryahdi, A., Sumarto, S., & Pritchett, L. (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.

  54. Priebe, J., Klasen, R., & Weisbrod, J. (2009). Rural Income Dynamics in Post-Crisis Indonesia. Proceedings of theGermanDevelopment Economics Conference, Frankfurt, 2009, No. 29.

  55. Pritchett, L. (2010). How good are Good Transitions for Growth and Poverty? Indonesia since Suharto, For Instance. Paper presented at the Indonesia Update, ANU, September 24 2012.
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  56. Pritchett, L., Suryahadi, A., & Sumarto, S. (2000). Quantifying vulnerability to poverty: A proposed measure, with application to Indonesia. SMERU Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  57. Ravallion, M and Lokshin, M. (2007) Lasting Impacts of Indonesia’s Financial Crisis. Economic Development and CulturalChange 56(1), 27-56.

  58. See Sumner (2012). The selected studies are catalogued in the Thomson Reuter’s (ISI) Web of Knowledge database by keywords: “Indonesia AND (poverty OR inequality)”. There is, of course, a bias that only studies published in English are included. That said, a large number of these studies identified are written by Indonesian scholars 10 chronic – meaning long-run – poverty (Suryahadi & Sumarto 2001, 2003a, 2003b).
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  59. Skoufias, E., Suryahadi, A., & Sumarto, S. (2000). Changes in Household Welfare, Poverty and Inequality during the Crisis. Bulletinof Indonesian Economic Studies, 36(2), 97-114. 32 Strauss, J., Beegle, K., Dwiyanto, A., et al (2004). Indonesian Living Standards Before and After the Financial Crisis: Evidence from the Indonesia Family Life Survey. Santa Monica, CA: RAND Corporation.

  60. Studies focused on long-run trends in expenditure poverty typically use the Susenas survey data over a long period of time, and use either the national monetary poverty lines of the Bureau of Statistics or a variation of the poverty lines calculated by Pradhan, Suryahadi, Sumarto and Pritchett(2001). The consensus from these studies is as follows: consistent with the data provided in the previous discussion, absolute poverty declined in Indonesia during the Soeharto years (Asra 2000; Booth 2000; Friedman 2005). However, poverty was still significant before the 1997/8 financial crisis, and may have been underestimated due to national poverty lines being set too low (Asra 2000). Further, welfare improvements slowed in the period after the 1997/8 crisis (Friedman 2005; Friedman & Levinsohn 2002; Lanjouw et al. 2001; Skoufias et al. 2000; Suryahadi et al., 2012). Much of this was due to an increase in 5
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  61. Studies focused on the long-run relationship between expenditure poverty and economic growth typically use the Susenas data, and either the national BPS monetary poverty lines or a variation of the poverty lines calculated by Pradhan et al.(2001). The consensus from these studies is as follows: overall, economic growth in Indonesia has benefited the poor, with a high and stable growth elasticity of poverty even after the 1997/8 crisis (Baliscan et al. 2010; Friedman 2005; Suryahadi et al. 2012; Timmer 2004). However, economic growth in different sectors is associated with quite different impacts on poverty, notably economic growth in the services sector, as noted above, is found to be more beneficial to the incomes of the poor than economic growth in agriculture (Fane & Warr 2002; Suryahadi et al. 2006; 2012).

  62. Sumarto, S., Suryadarma, D., & Suryahadi, A. (2006). Predicting Consumption Poverty Using non-consumption Indicators: Experiments Using Indonesian Data. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  63. Sumner, A. (2010) Global Poverty and the New Bottom Billion, IDS Working Paper 349, Brighton: IDS Sumner, A. (2012a) ‘Where do the Poor Live?’, World Development 40.5, 865-877 Sumner, A. (2012b) ‘From Deprivation to Distribution: Is Global Poverty Becoming A Matter of National Inequality?, IDS Working Paper, Brighton: IDS Sumner, A. 2012C Poverty and inequality in Indonesia since the Asian financial crisis: a literature review, Brighton: IDS Suryadarma, D., Artha, R. P., Suryahadi, A., & Sumarto, S. (2005). A Reassessment of Inequality and Its Role in Poverty Reduction in Indonesia. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  64. Suryadarma, D., Widyanti, W., Suryahadi, A., & Sumarto, S. (2006). From Access to Income: Regional and Ethnic Inequality in Indonesia. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  65. Suryahadi, A. & Sumarto, S. (2003), Poverty and Vulnerability in Indonesia Before and After the Economic Crisis. AsianEconomic Journal 17, 45–64.

  66. Suryahadi, A., & Sumarto, S. (2001). The Chronic Poor, the Transient Poor, and the Vulnerable in Indonesia Before and After the Crisis. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.
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  67. Suryahadi, A., & Sumarto, S. (2003). The Evolution of Poverty during the Crisis in Indonesia. SMERU ResearchInstituteWorking Paper. Jakarta: Social Monitoring and Early Response Unit.

  68. Suryahadi, A., Hadiwidjaja, G., & Sumatro, S. (2012). Economic Growth and Poverty Reduction in Indonesia Before and After the Asian Financial Crisis. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.
    Paper not yet in RePEc: Add citation now

  69. Suryahadi, A., Raya, U. R., Marbun, D., & Yumna, A. (2010) Accelerating Poverty and Vulnerability Reduction: Trends, Opportunities, and Constraints. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit. 33 Suryahadi, A., Hadiwidjaja, G., & Sumatro, S. (2012). Economic Growth and Poverty Reduction in Indonesia Before and After the Asian Financial Crisis. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  70. Suryahadi, A., Suryadarma, D., & Sumarto, S. (2006). Economic Growth and Poverty Reduction in Indonesia: The Effects of Location and Sectoral Components of Growth. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  71. Table 4: Indonesia, poverty headcount (millions), 2010, Survey and NA means $1.25 $2 $10 Survey mean NA mean Survey mean NA mean Survey mean NA mean Total 43.2 2.4 108.7 49.7 236.8 225.2 Urban 23.5 2.2 55.1 26.6 125.7 117.0 Rural 19.7 0.2 53.7 23.0 111.1 108.1 Source:Author estimates.
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  72. Table 5. National poverty line versus $1.25 PPP poverty line, 2007–2012 Year Poverty Line Rp/month per person PPP 2005 (Rp/$) CPI PPP (Rp/$) Poverty Line $PPP/month per person Poverty Line $PPP/day per person 2007 166,697 4193 120 5,047 33.0 1.08 2008 182,636 4193 132 5,540 33.0 1.08 2009 200,262 4193 138 5,806 34.5 1.13 2010 211,726 4193 146 6,105 34.7 1.14 2011 233,740 4193 153 6,432 36.3 1.19 2012 259,520 4193 160 6,708 38.7 1.27 Source: Yusuf (2013).
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  73. The growth incidence graph explains further (Figure 8) and shows both the broad base to economic growth over the period at the lower end of the distribution and the benefits accruing to the top 15–25% of the population over the period (various other graphs by different time periods are annexed for reference). 0 5000 10000 15000 20000 25000 30000 35000 40000 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 GDPPPPpercapita(constant2005$) Indonesia China Brazil India Nigeria 20 Figure 7. Density curve, 1984–2011 Source:Author estimates.
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  74. The main purpose of this dynamic inequality analysis is illustrative and to investigate whether the assumption of static distribution introduces a significant difference in the calculations. Because the dynamic inequality assumption introduces even more uncertainty into the forecasts we prefer only to extend those forecasts out to 2030. Recognising that within-country inequality can decrease, we explore the significance of the impact of this by providing forecasts calculated using a ‘best’ (i.e. most equal) historical distribution for Indonesia. The ‘best distribution’ is the survey distribution that had the lowest ratio of the highest quintile to the lowest quintile (Q5/Q1).
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  75. The paper is structured as follows: Section 2 provides an overview of Indonesian development since 1984 and reviews the literature relating to the long-run evolution of poverty (and inequality) in Indonesia. Section 3 outlines our methodology and section 4 our findings. Section 5 concludes.
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  76. There are some questions about use of the Susenas data pre-1990. The expansion of the Susenas to 200,000 households took place in 1993. 9
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  77. There is also a question of whether to use survey or national accounts means. In this paper we use survey means because this most closely replicates the method used by the World Bank. Elsewhere we have used the GrIP model to compare poverty estimates by both survey and NA means (See Edward and Sumner, 2013a; 2013b). 15 When NAmeans areused lower poverty estimates are generated than with survey means (see Table 4). We would therefore anticipate that estimates of global poverty that use NA means (for example, Kharas and Rogerson, 2012) would understate Indonesian poverty when compared to estimates from Povcal (in fact, many of those estimates would understate Indonesian poverty by more than Table 4 because in general they use HFC means without the global adjusting that GrIP includes to allow for the fact that HFC means are generally higher than survey means). Table 4 shows the differences between poverty counts (millions of people) for each poverty line by survey and NA means.
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  78. They link poverty to educational attainment, number of household members, physical assets, employment status, health shocks, the microcredit programmer, access to electricity and changes in employment sector, and employment status. 11 estimate rural poverty as two-thirds of total poverty in 2010 as do Dartanto and Nurkholis (2013).
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  79. This is significant as rural poverty dominates the poverty count in Indonesia when the national poverty line is used (see later discussion). Suryahadi et al., (2012, p. 216) 6
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  80. Timmer, P. C. (2004). The road to pro-poor growth: the Indonesian experience in regional perspective. Bulletin of IndonesianEconomic Studies 40(2), 177-207.

  81. van der Eng, P. (2009). Growth and Inequality: The Case of Indonesia, 1960-1997. MPRA Paper 12725. Munich: Munich Personal RePEc Archive.

  82. van Leeuwen, B., & Foldvari, P. (2012). The Development of inequality and poverty in Indonesia, 1932-1999. CGEH WorkingPaper 26. Utrecht University: Centre for Global Economic History Wardhana, D. (2010). Multidimensional Poverty Dynamics in Indonesia (1993-2007). University of Nottingham: School of Economics.

  83. We explore the impact that a dynamic inequality estimate might have on future poverty. We use three inequality scenarios to illustrate the impact of different inequality assumptions as follows: • ‘Static inequality’ = a scenariowith static inequality from 2011 onwards; 8
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  84. Widyanti, W., Suryahadi, A., Sumarto, S., & Yumna, A. (2009). The Relationship between Chronic Poverty and Household Dynamics: Evidence from Indonesia. SMERU Research Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.

  85. World Bank (2012) PovcalNet, http://iresearch.worldbank.org/PovcalNet/index.htm (accessed 1 April 2012) World Bank (2012) World Development Indicators. Washington DC: World Bank Widyanti, W., Sumarto, S., & Suryahadi, A. (2001). Short-term Poverty Dynamics: Evidence from Rural Indonesia. SMERUResearch Institute Working Paper. Jakarta: Social Monitoring and Early Response Unit.
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Cocites

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  10. Educational Expansion and the Role of Education in Expenditure Inequality in Indonesia Since the 1997 Financial Crisis. (2017). Akita, Takahiro.
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  38. Non-Hierarchical Bivariate Decomposition of Theil Indexes. (2009). Tang, Kam Ki ; Petrie, Dennis.
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  45. Urbanization, educational expansion, and expenditures inequality in Indonesia in 1996, 1999, and 2002:. (2007). Miyata, Sachiko ; Akita, Takahiro.
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  46. Analysis of Educational Distribution in Europe: Educational Attainment and Inequality Within Regions. (2007). Tselios, Vassilis ; Rodríguez-Pose, Andrés ; Rodriguez-Pose, Andres.
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  47. What Kind of Education Does China Need? The Impact of Educational Attainment on Local Growth and Disparities. (2006). Reuter, Ulrich.
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  48. The relationship between Regional Growth and Regional Inequality in EU and transition countries - a Spatial Econometric Approach. (2005). Piras, Gianfranco ; de Dominicis, Laura ; arbia, giuseppe.
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  49. The Effects of Intraregional Disparities on Regional Development in China: Inequality Decomposition and Panel-Data Analysis. (2004). Reuter, ; Ulrich, .
    In: Econometric Society 2004 Far Eastern Meetings.
    RePEc:ecm:feam04:716.

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  50. REGIONAL INCOME INEQUALITY IN INDONESIA AND THE INITIAL IMPACT OF THE ECONOMIC CRISIS. (2002). Akita, Takahiro.
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