SOCIAL WELFARE POLICIES UNDER PRESIDENT SBY Dinna Wisnu Faisal Basri Gatot A. Putra Canberra, 19 September 2014
Rhetoric versus reality Slogan (SBY in 2005): pro-growth, pro-poor, projob, (2007) pro-environment. Realities: 8 7 6.8 60 60,0 6 5.6 5.9 6.3 5.8 6.4 6.5 6.5 6.5 6.3 6.4 6.2 6.1 6.0 5.8 5.6 5.7 50 40 5 4 4.5 4.1 4.3 5.2 5.1 30 20 10 11,3 24,2 17,8 11,4 11,3 3 0 1970 1976 1978 1980 1981 1984 1987 1990 1993 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011* 2012* 2013* 2014**
The main targets of RPJMN are not achieved Indicators National Medium-Term Development Plan (RPJMN) 2010-2014 Actual Economic growth Average of 6.3-6.8 percent per year 5.98% Growth of 7 percent before 2014 2013 = 5.78% Poverty rate 8-10 percent at the end of 2014 11.25% in March 2014 Open unemployment 5-6 percent at the end of 2014 5.70% in February 2014 Source: Bappenas
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Percent Percent Poverty, unemployment, and growth Sometimes open unemployment rate and poverty rate fell more sharply despite slowing GDP growth. The quality of job creation is stiil poorly Poverty (LHS) Unemployment (LHS) GDP growth (RHS) 20 15 19,1 18,4 18,2 17,4 16,7 16,0 17,8 16,6 15,4 7,0 6,0 10 6,1 8,1 9,1 11,5 9,9 11,2 10,3 9,3 14,2 13,3 12,4 8,5 8,1 7,4 6,8 11,8 11,4 11,3 6,3 5,9 5,7 5,0 5 4,0 0 3,0 Source: BPS.
Distribution of workers by sector (%) Sector 2004 2009* 2014** Agriculture 44.5 41.1 34.6 Mining and quarrying 1.1 1.1 1.4 Manufacturing industry 11.2 11.8 13.0 Electricity, gas, and water supply 0.2 0.2 0.3 Construction 4.7 4.7 6.1 Trade, hotel, and restaurant 20.2 20.7 21.8 Transport and communication 5.7 5.7 4.5 Financial, ownership and business services 1.2 1.4 2.7 Social services 11.1 13.2 15.6 Total (million) Memo: Informal workers Formal workers 100.0 97.0 70.6 29.4 100.0 106.6 69.9 30.1 100.0 118.2 59.8 40.2 * Simple average of February and August ** February. Source: BPS-Statistics Indonesia.
Labor productivity differences across sectors remain significant (Sector labor productivity (real terms) compared with labor productivity in agriculture) Sector 2000-03 2005-08 2009-12 Agriculture 1.0 1.0 1.0 Low-end services 2.4 2.5 2.2 Manufacturing industries 5.7 5.8 5.0 Transport & communication 2.8 3.5 5.5 Financial services 21.5 20.5 14.6 Mining and quarrying 46.8 26.7 18.0 Source: World Bank, Indonesia: Avoiding The Trap, Development Policy Review 2014, p. 6.
Allocation of national state budget by function (Percent of GDP) Public service Economy Health Security & Order Social protection Education Memo: energy subsidy 2005 9.23 0.86 0.22 0.58 0.07 1.04 3.75 2006 8.48 1.17 0.36 0.72 0.06 1.35 2.84 2007 8.00 1.11 0.40 0.71 0.08 1.29 2.96 2008 10.79 1.05 0.28 0.14 0.06 1.11 4.50 2009 7.46 1.07 0.28 0.14 0.05 1.52 1.68 2010 7.32 0.81 0.29 0.22 0.05 1.41 2.17 2011 7.70 1.23 0.19 0.30 0.05 1.32 3.45 2012 7.87 1.31 0.18 0.35 0.06 1.28 3.72 2013 7.77 1.21 0.20 0.40 0.19* 1.26 3.41 * Significant increase from Rp 5 trillion in 2012 to Rp 17 trillion in 2013. However, in 2014 (budget/apbn 2014) and 2015 (draft budget/rapbn 2015) fell sharply to Rp 8 trillion, respectively. Source: Ministry of Finance and BPS-Statistics Indonesia, calculated by authors.
Social protection index (n=35) and SP expenditure as % of GDP Social Protection Index SP expenditure as % of GDP Japan (1) Korea (4) Singapore (6) Malaysia (8) Timor-Leste (11) China (12) Vietnam (13) Sri Lanka (15) Thailand (16) Philippines (17) India (23) Pakistan (24) Indonesia (27) Bangladesh (28) Papua New Guinea (35) 0.005 0.051 0.047 0.044 0.043 0.085 0.137 0.121 0.119 0.155 0.140 0.139 0.169 0.200 0.416 Japan (1) Korea (5) Timor-Leste (8) China (9) Vietnam (11) Malaysia (13) Thailand (14) Singapore (15) Sri Lanka (16) Philippines (18) India (24) Bangladesh (25) Pakistan (27) Indonesia (28) Papua New Guinea (35) 0.1 1.7 1.4 1.3 1.2 2.5 3.7 3.6 3.5 3.2 4.7 5.9 5.4 7.9 19.2 ( ) Rank. Sources: Asian Development Bank, The Social Protection Index: Assessing Results for Asia and the Pacific, 2013.
Knowledge & skills performance of the world s 15-year-olds students based on PISA surveys 2012 Rank Mathematics Reading Science (n=65) Country/Economy 2009 2012 2009 2012 2009 2012 1 Shanghai-China 600 613 556 570 575 580 2 Singapore 562 573 526 542 542 551 3 Hong Kong-China 555 561 533 545 549 555 4 Chinese Taipei 543 560 495 523 520 523 5 Korea 546 554 539 536 538 538 7 Japan 529 536 520 538 539 547 17 Viet Nam n.a. 511 n.a. 508 n.a. 528 50 Thailand 419 427 421 441 425 444 52 Malaysia n.a. 421 n.a. 441 n.a. 420 64 Indonesia 371 375 402 396 383 382 65 Peru 365 368 370 384 369 373 Source: OECD, PISA (The Programme for International Student Assessment) database.
Indonesia: deceleration in mathematics performance Rate of acceleration or deceleration in performance (quadratic term) on mean mathematics performance in PISA 2003 through 2012 Coef. S.E. Hong Kong-China 0.3 (0.21) Indonesia -0.7 (0.26) Jordan -0.2 (0.51) Kazakhstan m m Latvia 0.1 (0.20) Liechtenstein 0.3 (0.25) Lithuania 0.7 (0.37) Macao-China 0.4 (0.14) Malaysia m m Montenegro 0.2 (0.31) Peru m m Qatar -2.3 (0.21) Romania 0.3 (0.54) Russian Federation 0.1 (0.23) Serbia 0.0 (0.45) Shanghai-China m m Singapore m m Chinese Taipei 1.3 (0.52) Thailand 0.2 (0.17) Tunisia 0.3 (0.20) United Arab Emirates - Ex. Dubai m m Uruguay -0.6 (0.18) Source: OECD, PISA 2012 Results: What Students Know and Can Do (Volume I) - OECD 2013
Indonesia: deceleration in reading performance Rate of acceleration or deceleration in performance (quadratic term) on mean reading performance in PISA 2003 through 2012 Coef. S.E. Hong Kong-China 0.1 (0.19) Indonesia -0.4 (0.25) Jordan -0.6 (0.65) Kazakhstan m m Latvia -0.4 (0.18) Liechtenstein -0.4 (0.18) Lithuania 0.6 (0.55) Macao-China 0.8 (0.23) Malaysia m m Montenegro -0.1 (0.51) Peru 0.0 (0.31) Qatar -2.4 (0.47) Romania 1.2 (0.28) Russian Federation 0.8 (0.19) Serbia -2.0 (0.59) Shanghai-China m m Singapore m m Chinese Taipei 1.6 (0.60) Thailand 0.7 (0.20) Tunisia -0.1 (0.30) United Arab Emirates - Ex. Dubai m m Uruguay 0.2 (0.28) Source: OECD, PISA 2012 Results: What Students Know and Can Do (Volume I) - OECD 2013
Indonesia: performance in science Mean science performance in PISA 2006 through 2012 Change between Change between 2006 and 2012 2009 and 2012 Annualised change in science across (PISA 2012 - PISA (PISA 2012 - PISA PISA assessments 2006) 2009) Annual Score dif. S.E. Score dif. S.E. change S.E. Hong Kong-China 13 (5.0) 6 (4.3) 2.1 (0.85) Indonesia -12 (7.7) -1 (5.7) -1.9 (1.33) Jordan -13 (5.5) -6 (5.1) -2.1 (0.91) Kazakhstan m m 24 (4.8) 8.1 (1.56) Latvia 13 (5.4) 8 (4.6) 2.0 (0.90) Liechtenstein 3 (6.5) 5 (5.3) 0.4 (1.03) Lithuania 8 (5.1) 4 (4.4) 1.3 (0.94) Macao-China 10 (3.8) 10 (2.4) 1.6 (0.64) Malaysia m m -3 (4.5) -1.4 (1.96) Montenegro -2 (3.8) 9 (3.0) -0.3 (0.64) Peru m m 4 (5.4) 1.3 (1.94) Qatar 34 (3.7) 4 (2.3) 5.4 (0.61) Romania 20 (6.4) 11 (5.1) 3.4 (1.08) Russian Federation 7 (5.8) 8 (4.8) 1.0 (1.00) Serbia 9 (5.8) 2 (4.6) 1.5 (1.03) Shanghai-China m m 6 (4.3) 1.8 (1.50) Singapore m m 10 (2.9) 3.3 (0.93) Chinese Taipei -9 (5.5) 3 (4.0) -1.5 (0.92) Thailand 23 (5.1) 19 (4.6) 3.9 (0.82) Tunisia 13 (5.7) -3 (4.8) 2.2 (1.03) United Arab Emirates - Ex. Dubai m m 10 (5.4) 5.1 (2.75) Uruguay -12 (5.2) -11 (4.3) -2.1 (0.91) Source: OECD, PISA 2012 Results: What Students Know and Can Do (Volume I) - OECD 2013
Indonesia: performance in science: 2006, 2009, 2012 Mean science performance in PISA 2006 through 2012 PISA 2006 PISA 2009 PISA 2012 Mean Mean Mean score S.E. score S.E. score S.E. OECD average 2006 498 (0.5) 501 (0.5) 501 (0.5) OECD average 2009 m m 501 (0.5) 501 (0.5) Hong Kong-China 542 (2.5) 549 (2.8) 555 (2.6) Indonesia 393 (5.7) 383 (3.8) 382 (3.8) Jordan 422 (2.8) 415 (3.5) 409 (3.1) Kazakhstan m m 400 (3.1) 425 (3.0) Latvia 490 (3.0) 494 (3.1) 502 (2.8) Liechtenstein 522 (4.1) 520 (3.4) 525 (3.5) Lithuania 488 (2.8) 491 (2.9) 496 (2.6) Macao-China 511 (1.1) 511 (1.0) 521 (0.8) Malaysia m m 422 (2.7) 420 (3.0) Montenegro 412 (1.1) 401 (2.0) 410 (1.1) Peru m m 369 (3.5) 373 (3.6) Qatar 349 (0.9) 379 (0.9) 384 (0.7) Romania 418 (4.2) 428 (3.4) 439 (3.3) Russian Federation 479 (3.7) 478 (3.3) 486 (2.9) Shanghai-China m m 575 (2.3) 580 (3.0) Singapore m m 542 (1.4) 551 (1.5) Chinese Taipei 532 (3.6) 520 (2.6) 523 (2.3) Thailand 421 (2.1) 425 (3.0) 444 (2.9) Tunisia 386 (3.0) 401 (2.7) 398 (3.5) United Arab Emirates - Ex. Dubai m m 429 (3.3) 439 (3.8) Uruguay 428 (2.7) 427 (2.6) 416 (2.8) Source: OECD. PISA 2012 Results: What Students Know and Can Do (Volume I) - OECD 2013
Missing elements 1. The evidence from the tenure period of President SBY suggests that the correlation between economic growth and social welfare is not a linear one. 2. Contrary to Amartya Sen, SBY s views on social development is second only to economic growth: It is very obvious that RPJM 2010-2014, also MP3EI 2011-2025 focused more on lengthening the bureaucracy for poverty alleviation with no clear target (or benchmarking!) on healthcare and education. MP3KI was issued later 3. The mismatch of President SBY s desire to improve welfare and alleviate poverty with the budgeting 4. Lack of long-term vision
Achievements in health The performances of Indonesia under SBY in indicators of health were below the world s and East Asia s average. Low health expenditure and inefficiency have created underperformance on supply side of health services deterioration of services after implementation of universal healthcare. Rates of growth in quadratic function are different between SBY era and non SBY era for immunization of DPT and Measles. There is acceleration in both immunization of DPT and Measles at SBY era but accelerations are lower than accelerations in non SBY s era. In SBY s era, both accelerations are about 50 percent lower compared to non SBY s era. Health expenditure per capita: no significant differences between SBY era and non SBY era.
Why outcomes far from expectation 1. The challenge of using the paradigm of subsidy in social welfare and his desire to align this with poverty alleviation missed the long-term strategy for freeing people from poverty and strengthen the competitiveness of Indonesia s economy. 2. The challenge of putting down coherent strategic planning on social welfare policies and implementing it across ministries and government agencies lack of coordination, no benchmarking, no clear targets. 3. The challenge of managing social welfare policy within the frame of decentralization.