Evaluating the Determinants of Sub- National Growth in Indonesia Neil Andrew McCulloch Bambang Suharnoko Sjahrir
Outline of the Presentation The concentration of economic activity How has regional inequality changed over time? What drives sub-national growth What doesn t drive growth Income Convergence Spatial Divergence Model Regression results Growth acceleration/deceleration Difference regressions Conclusions
Uneven distribution of resources and economic activity Java represents 6% of the country s land area but accommodates almost 60% of the population Island Land Area* (in %) Population (in %) GDP (in %) 1993 2005 1993 2005 Sumatra 24.86 21.84 21.77 25.54 27.18 Java & Bali 6.80 59.12 58.91 53.94 51.76 Kalimantan 27.28 5.56 5.69 11.20 11.34 Sulawesi 10.52 7.42 7.48 5.41 5.45 Maluku + Nusa Tenggara 9.51 5.04 4.96 1.99 2.23 Papua 21.03 1.02 1.19 1.92 2.04
Indonesia Unity in Diversity I (District share of national GDP, 2003)
Indonesia - Unity in Diversity II (per capita GDP, 2003))
Richer provinces have more concentrated economic activity 2003 NAD.2.3.4.5.6 NTT Maluku Sultra Sulsel Jateng NTB Lampung Sulteng Jambi Jatim Jabar Sulut Yogya Sumbar Kalteng Kalbar Sumsel Kalsel Sumut Bali 1000000 1500000 2000000 2500000 Real GRDP Per Capita 2003 Top 20% district share of GRDP Fitted values
but per capita GDP is evenly distributed 2003.1.2.3.4.5 NTT Maluku Sultra NTB Jateng Lampung Sulsel Jambi Bkulu Sulteng Jatim Jabar Yogya Sulut NAD Kalbar Kalsel Bali Sumbar Sumut Sumsel Kalteng 1000000 1500000 2000000 2500000 Real GRDP Per Capita Gini Coef of district GRDP PC Fitted values
Richer provinces do have more concentrated populations 2003.1.2.3.4.5 NTT Maluku Sultra Sulsel Lampung NTB Jateng Sulteng Bkulu Sulut Jatim Jabar Yogya Sumut Sumbar NAD Kalteng Sumsel Kalsel Kalbar Bali Jambi 1000000 1500000 2000000 2500000 Real GRDP Per Capita Gini Coef of district population Fitted values
Inequality is higher between districts than provinces since the 1990s 0.500 0.450 0.400 0.350 0.300 0.250 0.200 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Gini Coefficient 2000 2001 2002 2003 Provincial GDP PC Kabupaten/Kota GDP PC
Inequality is higher between provinces than within provinces GRDP PC GRDP non oil&gas PC 1998 2000 2003 1998 2000 2003 GE(0) 0.297 0.263 0.242 0.26 0.229 0.213 within province 0.168 0.165 0.157 0.157 0.154 0.147 between province 0.129 0.098 0.085 0.103 0.075 0.066
Most provinces are becoming more concentrated Prov Name Top 20% district share of GRDP (1998) Top 20% district share of GRDP (2003) Change NTB 20.4 37.4 16.9 Lampung 29.5 32.0 2.5 Kalsel 44.2 46.7 2.5 Sulteng 30.7 32.6 2.0 Sulsel 50.4 52.3 1.8 Jateng 47.7 49.5 1.8 NTT 29.0 30.8 1.7 Jatim 57.5 58.9 1.4 Jambi 24.4 25.7 1.3 Sumut 44.5 45.3 0.9 Riau 53.3 54.1 0.8 Yogya 29.0 29.7 0.7 Sultra 25.9 26.3 0.4 Bali 23.9 24.3 0.4 Sumbar 41.0 41.3 0.3 Jabar 43.1 43.3 0.2 Kalteng 28.4 28.6 0.2 Sulut 30.0 29.7-0.3 Sumsel 40.3 39.9-0.4 Kaltim 56.7 55.7-1.0 Kalbar 28.0 26.7-1.3 Papua 68.1 66.1-2.0 Maluku 34.6 30.8-3.8 NAD 70.6 62.7-7.9
Population is more dispersed Prov Name Top 20% district share of Population (1998) Top 20% district share of Population (2003) Change Kalteng 30.2 35.4 5.2 Yogya 28.4 29.5 1.2 Kalsel 35.3 36.5 1.2 Sulut 26.0 26.8 0.8 Lampung 29.6 30.4 0.7 Kalbar 23.8 24.4 0.6 NTB 24.9 25.3 0.5 Maluku 32.1 32.4 0.4 Sumbar 29.0 29.4 0.4 Sumut 43.1 43.5 0.4 Jatim 37.5 37.4-0.2 Kaltim 33.2 32.7-0.5 Bali 18.9 18.1-0.8 Jambi 19.3 18.5-0.8 NAD 42.1 40.9-1.2 Sulsel 39.8 38.5-1.3 Riau 29.0 26.7-2.4 Sumsel 34.7 32.1-2.7 Jabar 41.1 36.7-4.4 Papua 36.4 31.4-5.0 NTT 32.9 27.4-5.5 Jateng 41.5 32.1-9.5
Are people following the jobs? Change in top 20% district share of GRDP -.08 -.06 -.04 -.02 0.02 Jateng NTT Papua Jabar Riau Sumsel Sulsel Jambi Jatim Sumut Yogya Bali Sumbar NAD Lampung Kalsel Sulut Kaltim Kalbar Maluku -.1 -.05 0.05 Change in top 20% district share of population Kalteng
Typical District performance (Median) Growth Rate in % Gini Coefficient 1993-1997 1999-2001 2001-2005 1993 1999 2001 2005 Sumatra 5.8 5.5 3.5 0.26 0.31 0.27 0.27 Kalimantan 5.7 6.2 2.7 0.38 0.37 0.39 0.42 Java & Bali 5.7 1.3 3.1 0.35 0.38 0.40 0.39 Sulawesi 5.3 5.5 3.0 0.16 0.20 0.19 0.23 Maluku + Nusa Tenggara 5.2 3.7 2.8 0.23 0.20 0.32 0.29 Papua 4.5 5.3 3.1 0.57 0.68 0.57 0.57 Total 5.6 3.5 3.0 0.37 0.41 0.39 0.39 Eastern Indonesia 5.2 4.8 2.9 0.41 0.49 0.41 0.40 Western Indonesia 5.7 2.9 3.1 0.34 0.37 0.38 0.38 Java 5.6 1.4 3.2 0.36 0.38 0.41 0.40 Off Java 5.5 5.0 3.0 0.38 0.42 0.38 0.38
Indonesia s sub-national growth varies greatly across districts SULAWESI SUMATRA KALIMANTAN MALUKU JAVA BALI PAPUA NUSA TENGGARA
About the data A panel dataset of 292 districts in Indonesia that includes the following variables: GRDP Level and growth of GDP in constant and current prices GRDP by sector Indicate natural resource endowments Educational Level of human resource endowments Population Level and growth Infrastructure Extent and quality of roads and communications Ethnic diversity Ethno-linguistic factionalization Geographical Land locked or not Political Background of district leader, political supports from local parliament, margin of victory. Transport Distance to provincial town, major cities and Jakarta Investment Level and growth Governance Variety of investment related governance indicators
Outline of Model Basic growth model i.e. gip = β 0 + β1yi0 + β1gnborp + β2popeduc + β3geog + β4infr + ε i0 Look at three periods: 1993-1997, 1999-2001, 2001-2005 OLS and panel approach Include a range of spatial variables Consider spatial autocorrelation
What is good for GDP isn t always good for growth Share of population had junior high school education 0 1 2 3 4 5 0.0 5.1.15.2.25 S h are p eo ple eve r/be ing in ju nio r Se con d ary S ch ool pe r to tal p opu lation ;S U S9 3 R ea l GR D P p er cap ita (in m io Rp ), BP S 1 99 3 Fitted valu es -. 1 0.1.2 0.0 5.1.15.2.25 S h are p eo ple eve r/be ing in ju nio r Se con d ary S ch ool pe r to tal p opu lation ;S U S9 3 G eo m etric A verag e Grow th R eal GR D P 1 99 3-2 0 03 Fitted v alue s
What is good for GDP isn t always good for growth Share of HH with telephone 0 1 2 3 4 5 0.0 2.0 4.06.0 8.1 Share of HH with telephone, PODES 1993 Real GRDP per capita (in mio Rp), BPS 1993 Fitted values -. 1 0.1.2 0.0 2.0 4.06.0 8.1 Share of HH with telephone, PODES 1993 Geometric Average Growth Real GRDP 1993-2003 Fitted values
Agriculture based districts are poorer, but it doesn t mean lower growth 0 1000000 2000000 3000000 4000000 5000000 -.1 0.1.2 0.2.4.6 Share of agriculture to total GRDP, 1993 GRDP Per Capita 1993 (in Rupiah) Fitted values 0.2.4.6 Share of agriculture to total GRDP, 1993 Geometric Average Growth Real GRDP 1993-2003 Fitted values
Manufacturing based districts are richer, but doesn t mean higher growth 0 1000000 2000000 3000000 4000000 5000000 -.1 0.1.2 0.2.4.6.8 0.2.4.6.8 Share of non oil & gas manufacturing to total GRDP, 1993Share of non oil & gas manufacturing to total GRDP, 1993 GRDP Per Capita 1993 (in Rupiah) Fitted values Geometric Average Growth Real GRDP 1993-2003 Fitted values
Income Convergence? -.1 0.1.2 12 13 14 15 16 17 Ln per capita Real GDP, 1993 Geometric Average Growth Real GRDP 1993-2003 Fitted values
Spatial Divergence? Growth performance is influenced by growth performance of neighboring districts -.1 0.1.2 -.5 0.5 1 1.5 Weighted Average Growth of neighbouring districts 93-03 Geometric Average Growth Real GRDP 1993-2003 Fitted values
OLS Period Regressions Geometric Average Growth in real per capita GDP 1993-1997 1999-2001 2001-2005 Ln per capita Real GDP -0.002-0.073-0.005-0.48 (4.91)** -1.53 Weighted Average Growth of neighbouring districts during the period 0.037 0.048 0.011-1.8-0.93-0.6 Share people ever/being in junior Secondary School per total population 0.045 0.028 0.012-1.03-0.16-0.32 Share of population that is urban 0.019 0.019 0.031-1.9-0.59 (3.56)** Labour Force (millions) 0.003 0.006 0.005-1.49-0.85 (2.74)** Share of manufacturing to total GRDP 0.034 0.105-0.019 (2.85)** (2.37)* -1.77 Oil and Gas is the main sector -0.034 0.053-0.011 (2.37)* -1.43-1.28 Gini coefficient of sectoral employment 0.05 0.01 0.015-1.73-0.12-0.7
OLS Period Regressions contd. Geometric Average Growth in real per capita GDP 1993-1997 1999-2001 2001-2005 Farmer's terms of trade index 0.032-0.029 0.002-1.25-1.39-0.49 Distance district to Province's Capital 0 0 0-0.76-1.83-1.04 Have to get on a boat to get to Province's Capital -0.005-0.018-0.009-0.87-0.86-1.75 Telelphones per household -0.051 0.248-0.044-0.59 (2.09)* -1.73 Ethno-linguistic fragmentation 0.003 0.037-0.003-0.59-1.85-0.64 Java dummy 0.001-0.047-0.008-0.21 (2.86)** (1.98)* Constant -0.039 1.001 0.026-0.52 (4.01)** -0.47 Observations 128 167 219 R-squared 0.25 0.29 0.14 Robust standard errors in parentheses * significant at 5%; ** significant at 1%
Fixed Effect Regressions -1-2 -3 1993-1997 2001-2005 1993-2003 Ln per capita Real GRDP, initial year -0.374-0.403-0.210 Weighted Average Growth of neighboring districts during the period Share people ever/being in junior Secondary School per total population (0.026)*** (0.026)*** (0.015)*** 0.375 0.001 0.368 (0.030)*** (0.025) (0.023)*** -0.240 0.445-0.100 (0.187) (0.106)*** (0.113) Labor force, initial year 0.116 0.083 0.022 (0.032)*** (0.019)*** (0.009)** Gini coefficient of sectoral employment 0.028-0.038 0.031 (0.096) (0.042) (0.052) Constant 3.876 5.163 2.708 (0.476)*** (0.441)*** (0.241)*** Observations 1130 1163 2048 Number of groups 240 297 250 R-squared 0.42 0.23 0.25
Accelerators and Decelerators -.1 0.1.2 Geometric Average Growth 1997-1993; pre-crisis income percapita Geometric Average Growth 2005-2001; post-decentralization income percapita -.05 0.05.1.15
Difference Regression ΔgiP = β0 + β1δx i + ΔβX i0 + Δε i Look at change between 1993-1997 and 2001-2005 If coefficient on initial condition is zero then this is the initial model Results Model does a poor job of explaining changes in growth
Summary of Key Messages Economic activity is highly concentrated in Indonesia Inequality between provinces has been falling consistently Inequality between districts rose before the crisis, but has fallen since There is evidence for simultaneous income convergence AND for spatial divergence Sectoral effects appear to stimulate growth differently in different periods However, education, geographic, infrastructure variables are not strongly associated with growth
Future Work Using an alternative (and less noisy) measure of district performance Incorporating measures of economic governance Doing the analysis at the provincial level