Programs Examined

The selection of programs for the BIA is driven primarily by data gathered in the most recent surveys available. The 2010 SUSENAS and 2007/8 IFLS both contain information on participation in a number of programs to assist the poor and on the use of other services such as education that while not necessarily targeted to the poor nonetheless have important impacts on poverty and welfare.

The SUSENAS core module gathers information on participation in several programs targeting the poor or near poor: (1) Raskin (2) Jamkesmas and (3) business credit through government programs.28 Further, as noted in section II.4.5, SUSENAS also collects information on maternal and child health services such as child vaccinations and birth attendance by medical professionals, as well as school enrollment at different levels. These are not anti-poverty programs per se but are standard outcomes for BIA and as noted have strong welfare implication. We will also examine the benefit incidence of these services. We will do this in the standard way, examining how these benefits are distributed across different income groups in the population overall, but also with a coverage perspective that considers the share of the target population (such as young children in the case of vaccinations) within each expenditure quintile that is covered by the program or service (Glick and Razakamanantsoa 2006). It should be noted that these services, and in particular education and birth attendance, need not be provided

27 _{Participation rates can also be expressed in terms of how the benefits received by a quintile compares with its}

share of total ‘needs’—i.e., of the target population for the benefit. For example, for immunizations, a quintile’s share of total immunizations over its share of the target population (all young children) equals the ratio of the quintile’s participation rate (share of children immunized) to the average participation rate (the share for all quintiles). Hence if the participation rate for the quintile equals the average participation rate (a ratio of 1.0), the quintile’s share of the benefit is the same as its share of the population in need of it. If the participation rate of the quintile is lower (higher) than the average, it receives a share less than (greater than) its share of the target population.

28 _{Including (separately) credit received in past year from government programs, from Kecamatan Development}

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exclusively by the public sector. As BIA is concerned with the distribution of public expenditure it should count only government services. Unfortunately, SUSENAS does not distinguish public and private providers for these services, so results will need to be interpreted with care. Since the wealthy are usually more likely than the poor to use private providers, public spending may be more pro-poor than our calculations, which include both, suggest.

The 2007/8 IFLS household survey gathers information on participation in several of the same programs as SUSENAS (Raskin, Jamkesmas) but also several others, notably the BLT (Unconditional Cash Transfer). Further, the IFLS administers a comprehensive community survey with information on a number of community level public goods, notably, infrastructure. These are potentially important determinants of welfare (indeed, this assumption underlies the PNPM focus on infrastructure). We will also examine the incidence of these goods or services. The main variables of interest include the following: public infrastructure for sewage and sanitation, public lighting, public library, and asphalt or paved roads.

In the case of a community public good, we assume that each person in the community benefits equally from its provision. This is a possibly incorrect assumption for some variables; for example, within a kelurahan, street lights may be installed only in wealthier neighborhoods. There is no way to go beyond this assumption without an actual mapping of public goods within communities. Still, the results should be informative. For example, if poor people are more likely to live in communities that are overall poorer (as we would expect) and such communities lack the resources to obtain or provide their own public goods, we would see a substantially non- progressive distribution of these public goods.

3 Program Coverage by Expenditure Quintile

We first look at participation rates or coverage for anti-poverty programs by household per capita expenditure quintile. We present results for urban areas as well as for rural areas and for the total population. The quintiles are constructed based on the distribution of expenditures in the area considered, rather than just the national distribution, so that each quintile represents 20% of the population of interest (urban, rural, or national). Note that the first quintile of the urban population more or less corresponds to the share of individuals below the poverty line plus those less than 20% above it, which as seen earlier is just over 18%. Therefore we can take this group to represent the poor plus near poor, or the target population for most social protection programs

3.1 Social Protection Programs and Basic Needs

As shown in Table III.3.1, 70% of individuals in the bottom 20% of the urban expenditure distribution received subsidized rice under Raskin in the three months prior to the survey. This share is larger than for all other quintiles, suggesting the benefit is somewhat targeted to the poor, but the benefits clearly extend well beyond this targeted group. More than half of those in

the 2nd quintile received subsidized rice, and even in the 4th urban quintile close to 20% of individuals benefit from this program, while some 30% of individuals in the lowest quintile did not receive the benefit. These large exclusion and inclusion errors are in accord with other quantitative analysis of targeting of Raskin (World Bank 2010b) as well as the

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Sumarto and Bell (2011) note and as the focus groups and interviews suggest, local officials and organizations are able to use their power to distribute rice to non-beneficiary households. However, it is important to note that these leakages, large as they are, remain lower in urban

areas than rural areas. In rural areas, fully 38% of those in the highest quintile report

purchases under Raskin compared with 5% of in urban areas. Since rural areas are poorer (e.g., the poorest 40% in rural areas are poorer than the poorest 40% in urban) we would expect to see this pattern to some extent, but still the data suggest better, if highly imperfect, targeting of Raskin in urban areas.

A similar pattern is seen for the health insurance program: disproportionate benefits for the poor but significant leakages to better off groups. Some 38 percent of the poorest urban quintile

benefit from Jamkesmas, compared with 27% of the next poorest. Participation is low in the highest two quintiles (11% and 4%). With more than 60% of the target population (poor and near poor households) not getting the benefit, the program is not succeeding well in the objective of providing this group with access to health care. Also noteworthy is the

fact that while the official target population for these two programs is the same—poor and near poor, or slightly less than the poorest 20% of the urban population—the shares of this group that enjoy these benefits are very different (much higher for Raskin—70% vs. 38%). However, this is not surprising given that each program is implemented by a different agency and uses different targeting approaches and databases of the poor. They also have different possibilities at the local level for leakages, with the distribution for Raskin rice likely to be especially prone to these outcomes.

The 2007/8 IFLS provides information on receipt of both conditional and unconditional transfer programs. The questions about BLT, the unconditional cash transfer program, refer to receipt both in the past year and any time previously. Although the survey extended into 2008, it was too early to capture the more recent implementation of the BLT program in 2008-9. The results in table III.3.2 instead refer to participation in the 2005 implementation, which as noted earlier was implemented to offset the impact of increases in kerosene prices arising from the first reduction of the fuel subsidy. In urban areas, targeting of BLT was roughly similar, if

slightly better, than for Jamkesmas, with some 39% in the first quintile receiving the

transfer and about 21% in the 2nd, and relatively few in the upper two quintiles. Exclusion of poor and near-poor households appears to have been very high, as almost two thirds of urban households in the lowest urban quintile reported not getting the transfer.

PKH, the conditional cash transfer, is more limited in scope as it is designed to target very poor households with children and at the time of the last IFLS round, the program was new. Only about half a percent of households overall, both in urban areas and nationally, reported participation. That said, the program, though limited, does seem to be targeted toward poorer households, as Table III.3.2 shows.