Indonesia - Gender equality : poverty, vulnerability and social protection : Indonesia - Gender equality

73063  ENGLISH Indonesia has experienced an improvement in narrowing the gender gap in some key areas of endowment (e.g. health and education), opportunities, voice and agency, and necessary legislation for gender mainstreaming, but challenges remain. Gender parity index in education has been achieved. Maternal health has significantly improved. There are no pronounce gender disparities in infant and under five mortality rates and other health outcomes. Women labor’s participation rate continues to grow with better return for educated women than men. Women’s political representation has increased. Challenges persist in MMR, HIV/AIDS, stunting and wasting, gender streaming in education, economic opportunities, access to legal justice, and voice and agency in influential decision makings. These challenges juxtapose the emerging trends of human trafficking and non-women friendly policies at sub national levels. The key achievements and outstanding-issues are presented in the eight Policy Briefs, developed by the Government (the Ministry of National Planning and The Ministry of Women’s Empowerment and Child Protection) and development partners (the World Bank, AusAID, CIDA, The Netherlands Embassy, DFID, and ADB). Policy Brief 1: Gender Mainstreaming has been adopted since the issuance of Presidential Instruction No 9/2000. Presidential Instruction No 3/2010 and other ministerial regulations on gender mainstreaming further stipulate efforts on equitable and inclusive development. The emerging non- women friendly legislation at the local level signifies the importance of enforcing the aforementioned legislative and policy frameworks, coordination among national ministries and all levels of public institutions, and replication of good practices. Policy Brief 2: Gender Equality and Health in Indonesia shows positive results and remaining challenges in the four key health areas related to the MDGs. Important efforts have been made to increase women’s access to health services but Indonesia needs to work hard on reducing the high maternal mortality rate, increasing access to water and sanitation as well as HIV prevention and treatment for the increasing number of adult women living with HIV. Policy Brief 3: Gender Equality and Education has been one of the key achievements for Indonesia. The MDG targets on gender parity in net enrollment are on track to be met by 2015, especially if disparities at the provincial level are addressed. Focus is now on systematic measures to increase access to improved outcomes from a more gender responsive education. The challenge remains to mainstream a gender perspective in education which involves assessing the implication of any planned educational actions (legislation, policies or programs) to boys and girls, in all areas and at all levels. Policy Brief 4: Employment, Migration, and Access to Finance remain a challenge in that without proper measures may impede development. The average annual growth of women entering labor market is higher than men, but women continue to face lower labor’s participation and higher unemployment rates, poorer quality work and lower wages, limited access to resources, discrimination in hiring and promotion, and a higher level of economic informality. Women constitute most of self- employed, unpaid family workers, and migrant workers, making them susceptible to personal and financial insecurity, trafficking and other human rights violations. Closing these gender gaps requires focusing on the equal employment opportunities, link and match of women’s trainings and skills with the labor market, underlying factors of labor market segmentation, and wage gaps and career opportunities.  ENGLISH Policy Brief 5: Poverty, Vulnerability and Social Protection has been one of the current highest government’s development priorities. Whilst the national poverty rate fell from 16.7% (2004) to 13.3% (2010) and poverty rates amongst female-headed households (FHH) remain lower than male-headed households (MHH), the overall rate of poverty reduction for FHH is lower than MHH. This is notwithstanding the well-targeted FHH in all Social Protection programs. Improved targeting techniques will reduce exclusion and inclusion errors and ensure that more poor households receive social protection. The challenge will be to ensure the new targeting mechanisms to include poverty indicators which reflect characteristics of poor and vulnerable FHHs and the male-female intra-household equal access to program benefits. Policy Brief 6: Gender Equality in Disaster Management and Climate Adaptation highlights the gendered differentiated impact of disasters. There has been significant learning from Aceh Tsunami on good practices for gender responsive disaster management. These need to inform and further strengthen all related national and local-level policies, institutions and programs to tackle the root causes of gender-based vulnerabilities, ensure use of gender analysis and sex-disaggregated data, as well as give equal weight to men’s and women’s rights and capacities. Policy Brief 7: Women’s Voice in Politics and Decision Makings in Indonesia has increased due to, among others, affirmative action for women candidacy and political participation in 2008. Women’s representation in the Parliament (DPR) increased from 11% (2004-2009) to 18% (2009-2014). Representation remained below the desired 30% and inadequate in other critical areas of public service and decision-making roles. Significant disparities within political parties and across levels of national and sub national government constrain the MDGs’ achievement for women’s empowerment. Indonesia’s Constitution and legal framework assure the equal rights of women. Strengthening current laws/regulations as well as implementation and monitoring could more effectively address women’s institutional and socio-cultural barriers. Policy Brief 8: Violence Against Women (VAW): Domestic Violence and Human Trafficking in Indonesia show both important progress and outstanding issues. More efforts are needed for law enforcement, capacity building of service provider and wider community, and extend services to urban and rural areas. The increased trend of human trafficking demands more integrated efforts for prevention, protection, prosecution and reintegration.  POLICY BRIEF 5 POVERTY, VULNERABILITY AND SOCIAL PROTECTION T his Policy Brief provides an overview of key gender equity issues in addressing vulnerability and social protection of the poor. President Susilo Bambang Yudhoyono has declared poverty reduction to be his government’s highest development priority. The national poverty rate fell from 16.7% in 2004 to 13.3% in 2010, with no differences between men and women’s consumption based poverty rates. Poverty rates amongst female-headed households (FHH) remain lower than male-headed households (MHH). Over 2004-09, however, while there is a slightly higher percentage of poor MHH than FHH, the overall rate of poverty reduction is slower for FHH than for MHH and the poverty rate for urban FHH is increasing. This is despite the fact that a significantly higher percentage of FHH than MHH benefit from all Social Protection (SP) programs. Improved targeting techniques will reduce exclusion and inclusion errors and ensure that more poor households receive social protection. The challenge will be to ensure that poverty indicators which reflect characteristics of poor and vulnerable FHHs are also included in new targeting mechanisms and that male and female household members have equal access to program benefits within the household. slower for FHH than for MHH. (Note: The depth of pov- Current Status: erty is measured by the poverty gap which adds-up •• Poverty Reduction the extent to which individuals on average fall below the poverty line. The poverty severity index is the squared poverty gap index and highlights the level of Poverty data reveals specific gender gaps inequality by putting more weight on the very poor). in poverty reduction, particularly affecting urban female headed households. The main issues relating to gaps between male and P overty reduction has been slow overall, without female headed households include (see Table 1): significant differences between sexes. While there •• FHH represent 14.6% of all households, 15.5% of are more poor MHH than FHH, the rate of reduction all urban households and 13.8% of all rural house- in poverty among FHH is slower than for MHH, and holds. Approximately half of all FHH and 47.4% of poverty among urban FHH is actually increasing. Pov- all MHH are urban. There is no difference between erty depth and severity indicators are fairly low for men and women’s poverty rates, which is approxi- both types of households and they are slightly lower mately 14%. Over the last 5 years (2004-2009), the for FHH, although the rate of reduction is significantly poverty headcount rate decreased by 2.6 percent- 1 NEW brief 5.indd 1 6/13/2011 2:19:50 AM  POLICY BRIEF 5 age points for men and 2.4 for women. (Note: All reducing more slowly for FHH than for MHH in rural temporal trend lines in this brief are between 2004 areas. The poverty rate for rural FHH has decreased and 2009). There is a slightly higher percentage of by 8%, while it has decreased by 16% for MHH. poor MHH than FHH, based on consumption mea- •• An examination of the depth (poverty gap index) sures of poverty. Consumption measure of poverty and severity (poverty gap squared) of poverty is defined by the value of per capita consumption among male and female headed households re- per day/month. The poverty rate is 11.7% for MHH, veals similar trends. While the actual levels for and 10.6% for FHH. The rate of reduction in poverty MHH and FHH are currently similar and relatively is slower for FHH than for MHH. Poverty decreased low, the reduction is more pronounced for MHH by 18% among MHH and by 5.3% among FHH. The than for FHH, particularly in urban areas, where near-poverty rate is 22.25% for MHH and 19.44% the depth of poverty has reduced by 21% for MHH for FHH. The poverty line for the near-poverty rate compared to 7% for FHH, and severity of poverty = poverty line * 1.2. The very poor rate is the same has reduced 25% for MHH and 19% for FHH. In ru- decreased(4%) for by 18% both MHH  among and FHH and  5.3%The MHH.  by among poverty line  FHH. The for  near  is 22.25% Ͳpoverty rateral areas both depth and severity of poverty has for MHH and the 19.44%  for FHH. very poor rate = poverty  The poverty line  for the(See line*0.8.  nearͲpoverty rate = poverty line * Figure 1.2. The very poor rate is the same (4%) for both FHH and MHH. The poverty line  for the by 16% among MHH and 13% among decreased 1) =povertyline*0.8.(SeeFigure1) verypoorrate FHH. (See Table 1)   Figure1 Figure 1:: Poverty Rates Poverty (2004-2009), Rates by sex (2004Ͳ2009), byof individual sex and head-of- ofindividual andheadͲofͲhousehold  1: Consumption Table1:Consumption household Table based povertybasedpovertymeasures measure   National Urban Rural Indicator(%) 2004 2009 Change 2004 2009 change 2004 2009 change MHHaspercentage 86 85 85 84 (0) 87 86 (1) (0) oftotalHH FHHaspercentage 14 15 15 16 0 13 14 3 3 oftotalHH %ofallurbanMHH    42 47 14    %ofallurbanFHH    46 51 11    Poorindividualsin 17 14 12 11 (12) 20 17 (14) (14) thepopulation PoorMHH 14 12 (19) 11 9 (17) 17 14 (16) PoorFHH 11 11 (5) 8 8 9 14 13 (8) NearpoorMHH 25 22 (9) 20 17 (14) 28 27 (4) NearpoorFHH 21 19 (8) 15 15 (3) 26 24 (7) MHHP1Ͳdepth 2.50 2.01 (19.64) 1.96 1.54 (21.31) 2.88 2.42 (15.83) FHHP1 2.04 1.78 (12.61) 1.57 1.46 (6.90) 2.44 2.12 (13.28) MHHP2Ͳseverity 0.67 0.53 (21.19) 0.55 0.41 (24.77) 0.76 0.64 (16.23) FHHP2 0.56 0.46 (16.85) 0.48 0.39 (19.42) 0.62 0.54 (13.04)   Source : Susenas Source: 2004, Susenas2004, 2009, 2009, World WorldBank Bank calculations.Note: calculations.Note: households/femaleͲheadedhouseholdsratioformeasure. M/FisMale/FemaleM/F for measure. MH/FH is male-headed households / female-headed households ratio for is measure. ratiofor MH/FHisratio Male/Female maleͲheaded   Source: Susenas 2004, 2009, World Bank calculations. (Individuals is poverty headcount  measure. Source:rate Susenas  2004, by sex  2009, World of individuals  Bank in poor  calculations. households. HOH  (Individuals  is poverty is poverty rate  headcount of households ƒ  individuals by  rate by sex of Possible explanations  in poor  for the slower rate of poverty reduction for FHH than for MHH include:FHHtypicallyonlyhaveoneadultincomeearner(intheabsenceofaworkingmale households. HOHispoverty head-of-household rateofhouseholdsbyheadͲofͲhouseholdgender). gender).  •• Possible explanations for the slower rate of pov- adult), coupled with coping strategies used by FHH to maintain relatively equal levels of consumption such as keeping children out of school for income generation or saving on ƒ •• While overall the rate of poverty reduction in ur- While overall the rate of poverty reduction in urban areas is slower than inschool  rural  fees. Indeed while the percentage of poor children (between the ages of 6 and 15)  areas, erty reduction for FHH than for MHH include: FHH not in school are even at national level (approximately 18% for both MHH and FHH) there therearesomesignificantgenderdifferences.ThepovertyrateforurbanFHHhas ban areas is slower than in rural areas, there are increased are opposite  trends  in urban and rural areas. There is a higher rate of poor children out of by 9.2%, while it has decreased by 17% for MHH. Among the nearͲpoor inschool typically only have one adult income earner (in the urban  in poor urban FHH (19%) than in MHH (15%), while there is a lower rate of children  areas outofschoolinruralFHH(17%)thanMHH(20%).Ontheotherhand,thereisconsistentlya some significant gender differences. The poverty poverty reduction is higher for MHH at 14% than for FHH at 3%. Given the rapid absence of a working male adult), coupled with higher rate rate  ofchildrenworkinginruralareasthaninurban areas,andthisishigherin  of poor FHH (12%) than in MHH (8%). The percentage of poor working children among urban FHH urbanization in Indonesia this needs to be investigated and addressed further. rate for urban FHH has increased by 9.2%, while it  Poverty coping strategies used by FHH to maintain rela-  is decreased from 12% to 2% over the same period which saw an increase in urban FHH also reducing more slowly for FHH than for MHH in rural areas. The poverty rate poverty, for  rural  possibly   indicating  past reliance of urban FHH on income from child labour (see has decreased by 17% for MHH. Among the near- FHHhasdecreasedby8%,whileithasdecreasedby16%forMHH. tively equal levels of consumption such as keeping Table2).   poor in urban areas poverty reduction is higher for children out of school for income generation or ƒ An examination  of  the  depth  (poverty  gap  MHH at 14% than for FHH at 3%. Given the rapid index)  and  severity  (poverty  gap  squared)  of povertyamongmaleandfemaleheadedhouseholdsrevealssimilartrends.Whiletheactual saving on school fees. Indeed while the percent- 3 MHHof levels for rate urbanization and in Indonesia  FHH are currently this  similar and needs to  relatively low,be   the reduction age  is of morepoor  children (between the ages of 6 and pronounced  for MHH than investigated  foraddressed and FHH, particularly  in urban further. is where  areas, Poverty also  the depth15) of poverty not in  school are even at national level (ap- hasreducedby21%forMHHcomparedto7%forFHH,andseverityofpovertyhasreduced 25% for MHH and 19% for FHH. In rural areas both depth and severity of poverty has decreasedby16%amongMHHand13%amongFHH.(SeeTable1)  2   NEW brief 5.indd 2 6/13/2011 2:19:54 AM 2  POLICY BRIEF 5 proximately 18% for both MHH and FHH) there are Current Status: opposite trends in urban and rural areas. There is a higher rate of poor children out of school in poor •• Social Protection urban FHH (19%) than in MHH (15%), while there is a lower rate of children out of school in rural FHH While FHH tend to benefit slightly dis­ (17%) than MHH (20%). On the other hand, there proportionately from social assistance pro­ is consistently a higher rate of poor children work- tection benefits, there remain significant ing in rural areas than in urban areas, and this is inclusion and exclusion biases for both poor higher in FHH (12%) than in MHH (8%). The per- FHH and MHH. centage of poor working children among urban FHH decreased from 12% to 2% over the same pe- riod which saw an increase in urban FHH poverty, M ales and females are equally distributed among households receiving social assistance, but fe- male-led households are consistently more likely than possibly indicating past reliance of urban FHH on income from child labour (see Table 2). any other sub-group to be beneficiaries, even if they have high levels of consumption. This suggests that Table2:NonͲconsumptionpovertymeasures Table 2: Non-consumption poverty measures  National Urban Rural communities consider them more deserving of assis- Indicator(%) 2004 2009 change 2004 2009 change 2004 2009 Change tance than other households. While FHH are not spe- MHH Notinschool* 14 12 (21) 9 10 (6) 18 13 24 cifically targeted by social protection programs (with Workingchildren** 4 5 7 1 2 (67) 6 6 (3) Poornotinschool* 23 18 (28) 19 15 24 25 20 20 the exception of PEKKA, see below), decisions regard- Poorworkingchildren** 6 7 11 3 3 (29) 7 8 (12) FHH ing which households should receive assistance are Notinschool* 15 12 (22) 10 11 (12) 19 13 29 Workingchildren** 7 8 10 7 4 46 8 11 (32) often made at the community level, and FHH are often Poornotinschool* 25 18 (42) 24 19 19 26 19 25 Poorworkingchildren** 9 9 Ͳ 12 2 83 7 12 (69) considered poorer than MHH based on local level per- Source:Susenas2004,2009,WorldBankcalculations.*age6Ͳ15**age10Ͳ14 Source : Susenas 2004, 2009, World Bank calculations. * age 6-15 ** age 10-14  ceptions and knowledge. However, for both FHH and ƒ Other nonͲincome or consumption based indicators of poverty which are typical of FHH include the absence or sale of assets and absence or use of savings for consumption as MHH, there are significant inclusion and exclusion bi- •• Other non-income or consumption based indica- opposed to production. Currently there is insufficient analysis on this issue and further researchisneededtoexaminepossiblecausesoftheincreaseinurbanpovertyamongFHH, ases (some non poor households who are not eligible tors of poverty which are typical of FHH include as well as the challenges FHH in general face in escaping poverty, in order to better target vulnerableFHH. are receiving assistance while some poor households  the absence or sale of assets and absence or use CurrentStatus:SocialProtection who are eligible are not (see Figure 1and Figure 2). Whileof  FHHsavings for consumption  tend to benefit  slightly disproportionately as opposed to produc-  from social assistance  protection benefits, there remain significant inclusion and exclusion biases for both poor FHH and MHH. tion. Currently there is insufficient analysis Males and females are equally distributed among households receiving social assistance, on this but Figure 2: Percentage of Consumption Decile Receiving BLT Benefits (2008- femaleͲled households are consistently more likely than any other subͲgroup to be 09), by sub-group issue even beneficiaries, and further  if they  have high research is needed  levels of consumption. to examine  This suggests that communities consider them more deserving of assistance than other households. While FHH are not possible specifically  targeted by causes of the  social protection increase  programs  (with thein urban exception poverty  of PEKKA,  see below), decisions regarding which households should receive assistance are often made at the among FHH, as well as the challenges FHH in gen- community  level, and  FHH  are  often  considered  poorer  than  MHH  based  on local level perceptions and knowledge. However, for both FHH and MHH, there are significant inclusion eral face and exclusion  biasesin (someescaping poverty,  non poor households in not  who are order to  eligible  arebetter tar-   receiving assistance whilesomepoorhouseholdswhoareeligiblearenot(seeFigure 1andFigure 2).  get vulnerable FHH. Figure2:PercentageofConsumptionDecileReceivingBLTBenefits(2008Ͳ09),bysubͲgroup 4   Source: Susenas 2009, World Bank calculations Source:Susenas2009,WorldBankcalculations  Among the poor, most urban households are nonͲbeneficiaries. The targeting methodology is currentlybeingrevised,withanemphasisontransparentmeasurableindicatorsofpoverty,and the implications for FHH needs to be carefully considered in the selection of these indicators (see above on non consumption indicators). The gender impact of Conditional Cash Transfers/CCT program (Program Keluarga Harapan/PKH) is different for MHH and FHH 3 indicating a difference in intraͲhousehold decision making and spending choices. FHH seems to prioritise delivery anteͲ and postͲ natal care for mothers, while MHH place more emphasis on children’shealthcare,andoverallboys’healthcarewasfavouredoverthatofgirls. NEW brief 5.indd 3 6/13/2011 2:19:59 AM   POLICY BRIEF 5 Among the poor, most urban households are non- ciaries in all deciles, for example 40% of the FHH beneficiaries. The targeting methodology is currently in the 9th decile receive Raskin, compared to the being revised, with an emphasis on transparent mea- national average of 25%. (See Table 3 and Table 5). surable indicators of poverty, and the implications for The benefits of Raskin appear to be shared by all FHH needs to be carefully considered in the selection members shared by all of receiving members households,  of receiving  households, with with children  children being favored, and withou anygenderdiscriminationin allocationamong household members.Indirecteffectssucha of these indicators (see above on non consumption being favored, and without any gender discrimi- increased investment in education (with savings from subsidized rice) also appear to be indicators). The gender impact of Conditional Cash nation in allocation genderneutral.  among household members.  Transfers/CCT program (Program Keluarga Harapan/ Indirect effects such Table as increased investment in 3:SocialProtectionPrograms PKH) is different for MHH and FHH indicating a differ- education (with savings from subsidized rice) also shared by all members of receiving households, with children being favored, and without  anygenderdiscriminationinallocationamonghousehold National  members.  Indirect  suchas effects Urban Rural increased investment in education (with savings from subsidized rice) also appear to be ence in intra-household decision making and spend- appear Indicator  genderneutral. to  be gender neutral. 2004 2009 2004 2009 2004 2009 ing choices. FHH seems to prioritise delivery ante- and  receivingRaskin MHH 35 51 22 36 45 64 Table3:SocialProtectionPrograms FHH3 Table receiving Raskin Program : Social Protection 45 60 31 45 57 75 post- natal care for mothers, while MHH place more PoorMHHreceivingRaskin National 57  Urban 80 51Rural 77 58 81 Indicator 2004 2009 2004 2009 2004 2009 emphasis on children’s health care, and overall boys’ PoorFHHreceivingRaskin MHHreceivingRaskin 65 35 86  51 22 36 60 45 64 84 67 87 MHH FHH receiving receiving RaskinJamkesmas 45 60N/A 31 2745   57  75 19  33 health care was favoured over that of girls. Poor FHH MHH receiving receiving Raskin Jamkesmas  57 80N/A 51 3677   58  81 27  45 PoorFHHreceivingRaskin 65 86 60 84 67 87 PoorMHHreceivingJamkesmas MHHreceivingJamkesmas N/A  27 N/A 48  47  49  19  33 Policy Issues Poor FHH FHHreceiving receiving JamkesmasJamkesmas N/A 36N/A    5727  45 59  56 Poor MHH MHH receivingJamkesmas receiving BLT  N/A 48N/A    2447  49 15  33 PoorFHHreceivingJamkesmas N/A 57  59  56 FHHreceivingBLT MHHreceivingBLT N/A 24 N/A 41  28  54  15  33 T Poor FHH MHHBLT receiving receiving  BLT N/A 41N/A  5228    54 46  55 he social assistance programs have been delivered Poor Poor FHH MHH BLT BLT receiving receiving N/A 52N/A  6946    55 65  70 PoorFHHreceivingBLT N/A 69  65  70 under different channels such as PNPM Mandiri.  Source  Source ::Susenas Susenas 2004,  2009, World Bank calculations. Source :Susenas 2004,2004, 2009, 2009,World World Bank Bank calculations. calculations. The main issues related to social assistance programs  Table4. Table Age ofDecile Receiving Raskin,2009 (Coverage)  (Coverage) Table 44. Age . Age of of Decile Decile Receiving Receiving Raskin, Raskin, 2009 2009 (Coverage) include: Decile 1 2 3 4 5 6 7 8 9 10 Decile National 81 751     70 265 4   36 60 44 3 5 256 11 7 8 9 10   52 •• Raskin, a subsidized rice program, for the poor has Urban  National  78 6881 56   62 75  65 50 33 25 70 42 60  17 52 6 44 36 25 11 Rural 82 78 74 71 57 51 42 29 68 62 Urban  78  68  56 62  50  42 33 25 17 6 existed in Indonesia in some form since the Asian FHH 86 83 78 77 61 52 40 16 72 69 Rural Male   80 7382  67 78 62 71 56 4074 68  48  32   21 62 1057 51 42 29 Crisis in 1997-1998. Under the current Raskin pro- FHH  Female 80 7386 63   68 83  7740 32 56 78 49   22 72 69 1061 52 40 16 PerfectTargeting 100 100 100 0 0 0 0 0 0 0 gram, the National Logistics Agency (BULOG) pur- Male 80 73 67 62 56 48 40 32 21 10  Female ƒ Bantuan  Langsung 80 In73 Tunai(BLT).  subsidy 2005, 68 63  raised cuts 49 40 fuel 56 household 22 by10 32prices anaverage chases the rice from wholesalers using a subsidy of  over 125%. Perfect   BLT, an Targeting   unconditional 100 100 direct 100cash0 transfer 0  in 0four0  0 0over0  installments   year,  one funded from the implied budgetary savings from subsidy reductions, was one of the from the government. The rice is then distributed  Government ofIndonesia’sresponsestotheseprogrammedincreasesinfuelprices.Ittargeted ƒ Bantuan poor Langsung  households Tunai  who were (BLT).  benefiting In2005,  least from the subsidy cutsraised  old subsidy regime and household  were most fuel  pricesbyanaverage to villages, where eligible households are able to affected of over by  price increases.  125%.   BLT   BLT, an  was used again  unconditional  in  2008 direct cashinternational  when transfer in  crises in  installments  four both  over one year •• Bantuan financial markets and in food prices combined with another domestic reduction to fuel funded  from the Langsung Tunai (BLT)  implied budgetary . In  savings 2005,  from subsidy  subsidy  reductions, was one of the buy up to a set quantity of rice at considerably Government  of  Indonesia’s  responses  to cuts raised household fuel prices by an average  these  programmed increasesin 6 fuelprices.Ittargeted less than market prices. While the Raskin program poor households who were benefiting least from the old subsidy regime and were mos of over affected 125%.  by price BLT, an  increases. unconditional BLT was used again in direct cash  2008 when  international crises in both does not include gender specific considerations financial  markets transfer  andinstallments in four in food pricesovercombined with another one year, funded  domestic reduction to fue in its operations, FHH across all deciles are more from the implied budgetary savings from subsidy likely to receive Raskin benefits than MHH: 60% of 6  reductions, was one of the Government of Indo- all FHH and 86% of poor FHH receive Raskin, com- nesia’s responses to these programmed increases pared to 50% of all MHH and 79% of poor MHH. in fuel prices. It targeted poor households who Poor urban FHH are even more over-represented were benefiting least from the old subsidy regime among Raskin beneficiaries: 85% of poor urban and were most affected by price increases. BLT FHH receive Raskin compared to 76% poor urban was used again in 2008 when international crises MHH. FHH are over-represented as Raskin benefi- 4 NEW brief 5.indd 4 6/13/2011 2:20:02 AM  POLICY BRIEF 5   Source:Susenas2009,WorldBankcalculations Table5:AgeofDecileReceivingJamkesmas,2009(Coverage) in both financial markets and in food prices com- Table 5: Age of Decile Receiving Jamkesmas, 2009 (Coverage bined with another domestic reduction to fuel Decile 1 2 3 4 5 6 7 8 9 10 National 50 42 38 34 29 26 22 18 13 7 subsidies. 40% of all FHHs, and 69% of poor FHH, Urban 49 39 34 30 25 21 17 13 10 5 compared to 24% of all MHH and 52% of poor Rural 50 43 41 37 33 31 28 24 19 14 FHH 57 52 50 46 44 40 36 28 22 9 MHH receive BLT (See Table 3 and Figure 2). Ur- Male 50 41 37 32 28 24 19 16 11 7 ban FHH (28%) and MHH (15%) seem to be at the 7 most disadvantaged relative to their rural counter-  •• Program Keluarga Harapan (PKH): A pilot of a tra- parts (FHH: 53%, MHH: 32%) while there is a more ditional household Conditional Cash Transfer (CCT) even spread between poor urban (PU) and poor program, PKH, was introduced in 2007, aimed at rural (PR) households (PUFHH: 65%, PRFHH: 70%, reducing poverty and improving poor households’ PUMHH: 46%, PRMHH: 55%). human capital. The program is targeted at the very •• Jamkesmas is a free health care program aimed at poorest households and focuses on improvements making basic health services available to the poor- in socio-economic conditions, children’s educa- est 30% of the population by providing benefi- tion, the health and nutritional status of pregnant ciary households with health cards entitling them women, postpartum mothers and children under to free healthcare at local public health clinics and 6 years, and access and quality of basic education in-patient treatment in third-class public hospital and health care services. PKH applies the tradi- beds, as well as obstetric services, mobile health tional CCT design with quarterly cash transfers services, immunizations and medicines. A higher to poor households identified through statistical subsidies.40%ofallFHHs,and69%ofpoorFHH,comparedto24%ofallMHHand52%ofpoor MHHreceiveBLT(See Table3andof proportion FHH Figure receives 2).Urban Jamkesmas FHH(28%) andMHH(15%) seemtobeatthe means testing, with young children and pregnant relative most disadvantaged relative to their rural counterparts (FHH: 53%, MHH: 32%) while there is a women, who receive regular transfer ranging from to the national average, across all deciles. Among more even spread between poor urban (PU) and poor rural (PR) households (PUFHH: 65%, PRFHH:70%,PUMHH: poor FHH, 46%, PRMHH:57% receive 55%).  Jamkesmas, compared to USD 70 to USD 245 per year. The transfers are con-  ditional on the utilization of basic health services ƒ Jamkesmasisafree 48%health ofcare poor MHH. program The aimed atspread is relatively makingbasic healthserviceseven availabletothe poorest 30% of the  population across urban by providing and rural areas (See  beneficiary households Table  with 3, Table 4  entitling and children’s school attendance, and are trans- health cards them to free healthcare at local public health clinics and inͲpatient treatment in thirdͲclass and public hospital beds,  asFigure Jamkesmas 3). The services,  well as obstetric  mobilewas  services,aimed initially  health  immunizations and ferred directly to women in the recipient house- medicines.  A higher proportion of FHH receives Jamkesmas relative to the national average, holds. at formal workers but has been expanded to also across all deciles. Among poor FHH, 57% receive Jamkesmas, compared to 48% of poor MHH. cover Thespreadisrelatively the even informal across workers urbanand through ruralareas the (SeeTable 3,regulation Table4andFigure3).The Jamkesmas was initially aimed at formal workers but has been expanded to also cover the A recent PKH impact evaluation shows different no PER.24/MEN/VI/2006 from the Minister of Labor informal workers through the regulation no PER.24/MEN/VI/2006 from the Minister of Labor andTransmigration.  Transmigration. and outcomes for MHH and FHH, as well as male and  female children in all households. In FHH receiv- Figure 3:  Figure3:Percentage Percentage of Consumption ofConsumption Decile DecileReceiving Receiving Jamkesmas Jamkesmas Benefits Benefits(2009),bysubgroup (2009), by sub group ing PHK, pregnant and new mothers demonstrate larger magnitudes of increase in pre-natal visits, assisted delivery, and delivery at facility, than in MHH. However, it is in MHH where post-natal vis- its, newborn weighing, rates of immunization and treated diarrhea are increasing faster. MHH with PKH also do a better job keeping school-age chil- dren in school for more hours, while FHH receiving  PKH do a better job of discouraging waged child Source: Susenas 2009, World Bank calculations  Source:Susenas2009,WorldBankcalculations Table5:AgeofDecileReceivingJamkesmas,2009(Coverage) 5 Decile 1 2 3 4 5 6 7 8 9 10 National 50 42 38 34 29 26 22 18 13 7 Urban 49 39 34 30 25 21 17 13 10 5 NEW brief 5.indd 5 Rural 50 43 41 37 33 31 28 24 19 14 6/13/2011 2:20:09 AM  POLICY BRIEF 5 labor. Given that over half of the FHH in sample Gender sensitivity of current targeting were headed by single women and thus lacking a me­thods needs to be reviewed to ensure second wage-earner that many MHH have access that poor female headed households are to, this result indicates that CCTs such as PHK can adequately serviced in mainstream prog­ have a higher impact on single FHH where the op- rams. portunity costs of schooling, child labor, and ex- penditures are higher than for dual income MHH. There are also significant differences in the effects I ndonesia has primarily used a mixture of Proxy Means Testing (PMT), community-based and geographical targeting. PMT constructs a non-consumption and of PKH on outcomes for boys and girls. In health, non-income measure of household economic status breastfeeding behavior and rates of complete from a relatively small number of household charac- immunization increase by significantly greater teristics such as quality of materials used in housing amounts when the child is a boy, suggesting that construction, availability of electricity, source of drink- male and female children do not always share ing water and type of sanitation disposal, along with equally in the gains in positive household behav- ownership of assets such as appliances and vehicles. iors encouraged by PKH. This lends itself well to capturing poor FHH who might •• In 2001, PEKKA, a pilot program aimed at social manage to keep up basic needs consumption levels and political empowerment of poor women, and but may not have access to other services or assets. in particular FHH, was introduced. FHH are often poorer than their male-headed counterparts of Community based targeting relies on local knowl- similar characteristics, and are further disadvan- edge to identify the poor and vulnerable to deter- taged because women who head households do mine potential program beneficiaries. While this may not receive equal recognition as household heads be straightforward in small rural communities, there in their communities. The program aims to em- is a danger that they become invisible in urban ar- power poor FHH along five dimensions: (i) eco- eas where decision makers may have less knowledge nomic welfare; (ii) access to (financial) resources; about all community members. Meanwhile geograph- (iii) social and political participation; (iv) critical ical targeting involves using representative data to consciousness; and (v) control over their own lives. categorize regions with respect to priority for program It has been operational in 8 provinces between quotas or implementation. This approach determines 2001 and 2008, with around 9,000 members, and the number of poor within a population from a prior received funding to expand to 9 new provinces in nationally representative household survey or census. 2010. A second targeting method, such as PMT or communi- 6 NEW brief 5.indd 6 6/13/2011 2:20:12 AM  POLICY BRIEF 5 ty, is then often used to determine which households location, gender, age, head of household, and any will become beneficiaries within priority regions or other relevant demographic characteristic). quotas. Given that this method targets entire regions •• Policies to increase income generation and protec- rather than individual households it is not amenable tion from economic shocks (ie health shocks, eco- for gender mainstreaming. Categorical targeting has nomic crisis, disasters, etc) of poor FHH particularly also been used for smaller assistance programs target- single FHH (where there are no other working age ing particular sub-populations, such as the FHH (see adults) in urban areas, need to be re-examined and PEKKA above), or disabled. strengthened. Social assistance programs aimed at Targeting of broad-based social protection programs keeping children in school, and accessing health needs to be improved. While scaling up programs such care should target poor FHH and include condi- as PEKKA which specifically target poor FHH, or PKH tions related to equal treatment of boys and girls which is conditional on addressing women’s health within households. needs, is one way to address gender inequality, there is also scope for ensuring that poor FHH continue to •• TNP2K Working Group on Targeting to consider be included in “mainstream