Proposal for a Pilot Project on Community Based Monitoring System in Indonesia

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1 Proposal for a Pilot Project on Community Based Monitoring System in Indonesia The SMERU Research Institute INTRODUCTION 1.1 Background Indonesia experienced a period of sustained reduction in poverty prior to the economic crisis in Between 1970 and 1996, the poverty rate fell by approximately 50%. Due to the crisis however, the poverty rate increased to a level unseen since the mid 1980s. Table 1 shows that the poverty headcount rate increased from 15.6% in 1996 to 27.4% in In addition, the vulnerability to poverty rate also increased from 18.1% in 1996 to 33.7% in When disaggregated by urban and rural areas, the rural poverty rate increased by 69% and rural vulnerability increased by 77%. Urban areas were hit much harder, as the poverty rate increased by 137% and vulnerability by 150%. Table 1. Household Distributions across Poverty Categories in Indonesia, 1996 and 2002 (%) Poverty Category Change (percentage points) Poor: - Transient Poor Chronic Poor Total High Vulnerability: - Low Level of Consumption High Variability of Consumption Total Total Vulnerable Group Average Vulnerability to Poverty Source: Suryahadi et al., forthcoming. 1 Profile of SMERU is in appendix 4. 2 A household is considered vulnerable when it has more than a 50% risk of falling into poverty in the next period. 1

2 According to latest available data, in 2002 most of the impact of the crisis had dissipated as can be seen from the above table. Urban and rural poverty rates diminished to 5.4% and 23.7% respectively as compared to the corresponding rates of 16.8% and 34.5% in 1999 while total vulnerability was 18.1%, down from 33.7% in Although the impact of the crisis was more severe in urban areas than in rural areas, in terms of rising poverty rates, analysis of the poverty data reveals that between 1996 and 2002 incidence of poverty actually increased by 16.2% in rural areas while in urban areas it decreased by 23.4%. Another estimation found that changes in rural and urban poverty rates are much more volatile if disaggregated at provincial level. Between February 2000 and 2002, rural East Kalimantan experienced a 78.1% drop in poverty, the highest decrease among rural areas. Meanwhile, rural South Sumatra experienced a 129.5% increase, the highest increase among rural areas, while urban South Sumatra experienced a 29.7% decrease. On the other hand, urban Southeast Sulawesi experienced a 195.2% increase in poverty while its rural areas experienced an increase of only 19.9% 3. Although income inequality in Indonesia was relatively low compared to other countries 4, Indonesia s Gini of 0.32 in 2002 was an increase compared to 1999, when the Gini was 0.3. These regional variations can be explained in terms of the general multidimensional nature of poverty, which in the case of Indonesia, has been further coupled with the heterogeneity of the country. Indonesia is a country consisting of thousands of islands, hundreds of languages, and local cultures. Centrally planned national scale poverty alleviation programs may not, therefore, be adequate and best suited to the specific needs of local areas 5. There is a need to understand the regional dimension and poverty alleviation efforts which would work most effectively when it is tailor-made according to specific local conditions. 3 See appendix 2 for full results. 4 Indonesia s Gini Index is lower than neighboring countries such as Malaysia, Singapore, and the Philippines, even lower than the average of high income countries (Sudjana & Mishra, 2004). 5 The Government of Indonesia is currently formulating a PRSP based on PPA (Participatory Poverty Assessment). It is still work-in-progress. 2

3 Thus, since the local conditions and the problems faced by the communities are best understood by themselves, it calls for a monitoring system that is conducted and owned by the community viz. Community Based Monitoring System (CBMS). 1.2 Existing CBMS in Indonesia: BKKBN Indonesia already has a local monitoring system: BKKBN. It was initially created to monitor the implementation of the National Family Planning program. Then in 1994, BKKBN data was enhanced with a module to measure family welfare and BKKBN has been publishing its annual version of family welfare data ever since. It has the system in place, and it has cadres from neighborhood level all the way up to the central BKKBN in Jakarta who are experienced in conducting local monitoring. BKKBN has identified twenty-three welfare indicators 6 and classifies families into the following five categories: KPS (keluarga pra-sejahtera or pre-prosperous family ) if it fulfills any of the criteria listed in 1 to 5. KS1 (keluarga sejahtera 1 or just prosperous family ) if it fulfills all the criteria listed in 1 to 5. KS2 (keluarga sejahtera 2 or prosperous 2 family ) if it fulfills all the criteria listed in 1 to 14. KS3 (keluarga sejahtera 3 or prosperous 3 family ) if it fulfills all the criteria listed in 1 to 21. KS3 Plus ((keluarga sejahtera 3 plus or prosperous 3 plus family ) if it fulfills all the criteria listed in 1 to 23. The BKKBN data gathering mechanism is shown in figure 1 while reporting flow is shown in figure The BKKBN welfare indicators are in appendix 1. 7 PPKBD (Pembantu Pembina KB Desa) is Village Family Planning Assistant Supervisor; PLKB (Petugas Lapangan KB) is Family Planning Field Worker; PKB (Penyuluh KB) is Family Planning Extension Officer; PPLKB (Penyelia PLKB) is PLKB Supervisor 3

4 Level Central Province Kabupaten/Kota (district) Kecamatan Village Community Neighborhood Data collection conducted by BKKBN BKKBN BKKBN PPLKB PLKB/PKB PPKBD/Sub-PPKBD Cadre Figure-2 BKKBN Reporting Flow BKKBN is not however, without weaknesses. Firstly, the amount of data collected is huge, which makes mistakes unavoidable. Secondly, there is a high variation in enumerators ability that could affect data quality. Thirdly, enumerators subjectivity may play a significant role since the survey contains highly subjective criteria such as families religious practices. Fourthly, the data does not capture transitory shocks to income as it is based on relatively fixed information. Fifthly, the data is susceptible to changes by local government officials. 4

5 All these weaknesses make BKKBN unreliable. Comparisons have shown that BKKBN data disagrees with consumption-based measures of poverty at the household level. During the crisis in 1997, the government preferred BKKBN to Susenas/Podes data to target poor households in the Social Safety Net (SSN) program. For example, the subsidized rice and health programs explicitly used the BKKBN household classification for targeting. In addition, the school scholarship program also took into account BKKBN family status in order to select the beneficiaries; priority was given to the children belonging to households from the lowest socio-economic strata, who were selected from the two lowest BKKBN categories. However, the outcomes of the programs were not satisfactory. According to a study, in the subsidized rice program the undercoverage was 50% while the leakage was 75% 8. On the other hand, the scholarships program only covered 5.8% of poor students and 3.6% of non-poor students. Some of the targeting problems however, may be caused by the misuse of BKKBN data; a tracking survey conducted by SMERU to track the subsidized rice program found that most of the village heads distributed the rice evenly among the households regardless of their economic status. This may have contributed significantly to the mistargeting, irrespective of BKKBN data. Similarly, school principals also did not use BKKBN data as the selection criteria in the school scholarship program. The study also stated that targeting the beneficiaries of social safety net or poverty reduction programs requires, among other things, community involvement for the program to be both effective as well as socially and politically acceptable. Finally, and most importantly, it suffers from lack of funding. BKKBN is now decentralized and the decision regarding the continuation of the collection of data is taken by the district heads 9. Unfortunately, latest information suggests that only 99 out of 400 districts in Indonesia have institutionalized BKKBN into the government structure, as most local officials do not realize the importance of CBMS. Thus, the continuation of BKKBN data is in serious jeopardy. 8 Undercoverage is the fraction of people who were eligible but did not receive the program, while leakage is the fraction of people who did not need assistance but received assistance. 9 There are five government levels in Indonesia: central, provincial, kabupaten (district), kecamatan (subdistrict), and village. In 2001 the government enacted decentralization laws that transferred most powers down to the kabupaten level. This includes the decentralization of BKKBN. 5

6 Other than BKKBN, there is no other annual community monitoring system covering a comparable time span and area. Most monitoring systems were set up during the crisis and consequently only had several years worth of data and have since stopped running. In addition, none of them are on the same level as BKKBN in terms of coverage, as they only covered selected areas. These monitoring systems include Kecamatan Crisis Impact Survey in 1998 and SMERU s Community Based Monitoring in West Java and West Lombok in A significantly longer running monitoring system is Rand Corporation s Indonesia Family Life Survey, a series of panel household surveys that was conducted in 1993, 1997, 1998, and 2000, but was only representative of the 13 provinces surveyed. In 2001, the provinces of East Java, West Nusa Tenggara, and Jakarta conducted a poverty assessment with the help of BPS (Indonesia Statistics). However, there has not been any update on the studies. Finally, the government of District of Sika in East Nusa Tenggara is currently conducting a poverty census, although SMERU investigation found that the government does not really have any idea what to do with the data. 1.3 Rationale for a CBMS pilot project in Indonesia There are several strong reasons to pursue a CBMS pilot project in Indonesia. Firstly, monitoring in Indonesia mainly uses data gathered from the National Socioeconomic Survey (Susenas) and Village Potential (Podes) survey 10. However, the crisis has proven that these surveys are inadequate, too aggregated, and not responsive to the quickly changing nature of the crisis. When the survey data is ready for dissemination after being processed, analyzed, and published, it becomes obsolete. Secondly, as already mentioned in the beginning, there is a large variation in poverty levels between provinces in Indonesia and between urban and rural areas. This calls for poverty 10 SUSENAS is a nationally representative household survey, and has two main components. The first one is Core SUSENAS. It is conducted annually, while the second component, Module SUSENAS, which gathers detailed consumption of households, is conducted every three years. The Core covers about 200,000 households and 800,000 individuals while Module covers about 65,000 households that are randomly chosen from the Core. On the other hand, PODES is a complete enumeration of all villages in Indonesia. It is conducted three times in a 10-year period and is usually done before a census. It collects information on the characteristics of each village (i.e. land size, population, and water supply) and available infrastructure in that village (i.e. number of schools, hospitals, doctors, markets, transportation modes, and financial institutions). 6

7 alleviation efforts that address the specific needs of each region and a monitoring system owned and maintained by the community themselves. Thirdly, the enactment of decentralization and regional autonomy policies in place in January 2001 provided for not only administrative but also political and fiscal decentralization. This means district and village-level governments are now more influential in carrying out programs and policies, including key social policies such as health and education. These have reversed the New Order s centralized approach. After decentralization, the districts have the right to design their own programs and to determine the budget allocation for spending, including health and education, although the amount of money transferred to each district is still determined by the central government. Figure 3. Basic Structure of Government Authorities According to Law No. 22/ Law 22/1999 has recently been replaced by Law 32/2004. The structure of authorities remains as in Figure 3 and the power to allocate budget still lies with the district government. 7

8 The responsibilities and functions of the district governments have largely expanded, while those of the central and provincial governments have contracted. As a result, there is now a conducive environment to establish and execute a local monitoring system as the basis for the poverty alleviation efforts tailor made to suit the local needs. Fourthly, in relation to decentralization, assessments of poverty are currently carried out mostly by village heads, who logically would tend to overstate poverty conditions in their villages in order to garner additional funding, and therefore support from villagers. Poverty conditions could be determined more accurately by having more objective characteristics as the basis for poverty measurements Finally, BKKBN has laid a solid foundation. We can develop a new and improved community monitoring system, overcoming the above-mentioned flaws of the BKKBN. We have gained the full cooperation of BKKBN for this project, which enables us to tap into its vast resources. With all these reasons in mind, we propose to conduct a pilot CBMS project that uses all the strengths of BKKBN, such as experienced enumerators and far-reaching scope, and eliminate its weaknesses. Since the purpose of this project is to promote the importance of conducting periodic local monitoring activity to local stakeholders, there are two main purposes of this project. Firstly, to show local stakeholders that a more relevant, intuitive, and whose results are available in relatively shorter time 12 socioeconomic indicator than BKKBN is available. Specifically, the project will gather additional household information that is necessary in order to create a composite index that will summarize all the multidimensional aspects of poverty into a single figure. Construction of such an index is the first effort to be undertaken in Indonesia. Secondly, this project will demonstrate the importance of CBMS as a robust policymaking tool to local government officials by demonstrating other uses of the data such as simple tabulations of different household characteristics. 12 According to our expectations, data collection and analysis should take five months, much shorter than Susenas, which takes 18 months, and comparable to the current BKKBN. 8

9 2.0 METHODOLOGY 2.1 Sample Selection We propose this pilot project to be restricted to the province of Java. We would select two kabupaten, one where BKKBN is still in place and the other where BKKBN is no longer institutionalized. The first one is Cianjur in West Java and the other is Demak in Central Java. From each kabupaten we will choose two kecamatan, and one village in each kecamatan, making a total of four villages. Every household in the villages will be visited. The kecamatan chosen will take into account the distance from the kabupaten capital. One kecamatan will be far from the Kabupaten capital whereas the other will be near. The sample is not meant to be representative of the kabupaten or kecamatan. Table 2 outlines basic socio-demographic information of Cianjur and Demak. Table 2. Characteristics of Chosen Kabupatens Name of Kabupaten Cianjur Demak Number of Sub-districts/kecamatan Number of Villages Number of Communities Number of Neighborhoods Population Number of Households Number of Pre-prosperous and Just Prosperous households in Source: PODES 2003 The villages chosen in Cianjur are Parakantugu in Kecamatan Kadupandak and Cibulakan in Kecamatan Cugenang, while the villages that will be visited in Demak are Jungpasir in Kecamatan Wedung and Kedondong in Kecamatan Demak. Basic information on each village is in Table Location of the villages is in Appendix 3. 9

10 Table 3. Basic Information on Chosen Villages Parakantugu Cibulakan Jungpasir Kedondong Number of Households Number of Pre-prosperous and Just Prosperous households in Share of Agricultural Households (%) Distance to Kecamatan Office (km) Distance to Kabupaten Capital (km) Source: PODES Information to be collected and Research Instruments We propose to include some of the BKKBN welfare indicators and add several other variables, which would be primarily objective in nature. The indicators are listed in Table 4. To ensure that enumeration is quick and data processing is straightforward, most of the indicators will be collected at the household rather than individual level and most of them can be answered with a yes/no response. Table 4. Welfare Indicators to be Collected (Preliminary List) Type of Information Indicators Household Level Information Demographic Education Employment Food Security Health Age and sex of household head Marital status of household head Household size Education level of household head This household has a school-age member who is out of school* Number of working-age household members who are working* Number of school-age household members who are working The spouse is working Occupation that provides the most income in this household This household receives income from outside the household Number of meals a day* Staple food usually consumed Household members consume meat, chicken, or fish at least once a week* Type and place of treatment sought during illness* Main source of drinking water Whether drinking water is boiled 10

11 For women respondents and if there is a child <5 years old Ownership of toilet facilities and type used Use of contraceptives among adult/married household members* Incident of child and/or infant death in the family Whether Received routine antenatal and/or postnatal care from health officials during pregnancy for each child under 5 years old Each child under 5 years old has been immunized. Assistance during delivery for each child under 5 years old Asset Ownership Political and Security Village Level Information Ownership status of house House size, number of rooms* House material and characteristics* Ownership of durable goods, including productive assets Source of light Source of cooking fuel Number of farm animals Whether buy new clothing at least once a year* Access to formal credit market in the last 5 years Savings* Participation in last political process at national and local level Whether has been a victim of crime in last 12 months, type of crime Access to information (television, radio, newspaper)* Availability of school Availability of health center Availability of vocational training facility Availability of market Number of market days in a week Availability of police station Type of road in village, accessibility during rainy season Availability of public transportation Main water source in village Availability of post office, bank, telecommunications kiosk Note: * adapted in part or in whole from BKKBN indicators. Since our purpose from the beginning is to enhance BKKBN data, 11 out of the 23 BKKBN indicators in Appendix 1 are also included in our indicators. We mostly exclude BKKBN s ambiguous indicators, for example the family has the ability to improve its religious knowledge., as we concentrate on easily quantifiable household characteristics. In order to measure welfare as accurately as possible, the ideal would be to collect consumption expenditure data of each household. The difficulty in collecting such data 11

12 however, has been widely recognized. In addition, consumption data could be unreliable and could over/underestimate household welfare. In order to avoid this problem, we shall estimate long-run household wealth using a procedure introduced and defended by Filmer and Pritchett (1998). This method proposed the use of asset ownership information such as house condition, toilet facilities, etc. as an alternative to recording detailed consumption expenditure. Since the result of estimating welfare using assets was only slightly different to using detailed consumption expenditure but much easier to collect, Filmer and Pritchett argued that their method is better, especially for calculating long-run household welfare. For the poverty index, we are considering several types of analysis to provide weightings, such as Multiple Correspondence Analysis (MCA) and Principle Components Analysis (PCA). We will compare the indexes with consumption-based poverty measurement from SMERU s calculation 14 and BKKBN results in order to see the agreement before settling on which method to use 15. These weightings are simple enough to be understood by districtlevel officials. We will use a household questionnaire for collecting household data, where both household head and the female member/s of the family would be the respondents for the respective relevant portions. Village level information would be elicited using a structured checklist 16. A common grievance of BKKBN data is that it could be easily tampered with. To remedy this, the variables that we gather will record more detailed household characteristics; village leaders and enumerators would not know the weighting/importance of each variable until it is processed; and tampering with data after processing will render the already-processed weightings obsolete, thus making the results invalid. In short, the data and the processing method that we use ensure that data-tampering is harder and the result more objective. 14 SMERU calculates provincial urban-rural poverty rate using Susenas, and has been working on a major project to estimate poverty in each village in Indonesia since We use consumption-based poverty measure and BKKBN results as a tool to choose which method we will settle on, rather than choosing a priori whether to use PCA or MCA. We do not think that consumption-based poverty measure or BKKBN is better than the multidimensional poverty index. 16 To make the enumeration process as simple as possible, there will be no Focus Group Discussion (FGD) or other qualitative methods of extracting information. 12

13 2.3 Institutional Arrangement and Implementation of the project In order to promote a sense of ownership of the CBMS among the community members, the pilot project will involve several institutions to serve as a steering committee, both at national and kabupaten level. At the national level, the steering committee will be constituted of officials from BKKBN, Indonesia Statistics, BAPPENAS (Indonesian National Planning Agency), Ministry of People s Welfare, and Dr. Sudarno Sumarto from SMERU. Mr. Daniel Suryadarma, a researcher with SMERU, will lead the project with assistance from Ms. Hastuti, Ms. Nina Toyamah, Ms. Sri Budiyati, and Ms. Manasi Bhattacharyya, all of whom are SMERU researchers. Dr. Asep Suryahadi, SMERU s Deputy Director for Research, will serve as the advisor. At kabupaten level, we will involve Bappeda (Local Planning Agency) officials and possible relevant NGOs. We will utilize BKKBN s system down to kecamatan level and the BKKBN network (cadres, school teachers etc.) at village level will conduct the data collection. In addition, we will seek prior permission from respective government officials at provincial, district and sub-district level. There will be a consultation workshop in January 2005 to gain input and comments from various stakeholders on the CBMS design, including the welfare indicators. A pre-test will be conducted prior to the survey, where the results will be used to finalize the indicators. In the villages, SMERU researchers will orient the data collectors using simple manuals and supervise the fieldwork. 2.4 Transfer of CBMS to Local Government This pilot project is an attempt to rejuvenate community-based monitoring in Indonesia. Currently, the only government institution that conducts periodic community-based monitoring, BKKBN, has lost its credibility, and unfortunately, most of its funding in the district level since it was transferred to district-level government after decentralization in The scope has been reduced to merely recording changes to the data instead of a structured monitoring of household welfare in the district. Thus, it is important to return local governments confidence in CBMS. 13

14 SMERU believes that the best way to do that is by demonstrating the reliability of the survey results and by providing evidence on how this CBMS is better than BKKBN in terms of promoting welfare of the people. This is the reason why at the end of the pilot project there will be a workshop to disseminate the findings to national and local stakeholders, especially to promote the main benefits of CBMS as a local policy tool to government officials: (i) to assess local socioeconomic conditions and devise programs to alleviate specific problems in an area. As already mentioned in the beginning, local knowledge is especially important in the decentralization era, where most service delivery and programs are designed and executed by local government; and (ii) to increase awareness of the multidimensional nature of poverty in contrast to single poverty measurements. Finally, SMERU will produce an interactive CD and guidebooks about the pilot project and disseminate them to district leaders throughout Indonesia as the first step to introduce the benefits of CBMS. Furthermore, SMERU is prepared to train interested local government officials to process and use the data. There may be concern that the cost of CBMS is too great for it to be fully funded by district governments. However, investigations have found that local governments have the funds available. The poverty assessment projects in 2001 in three provinces that are mentioned at the end of section 1.2 cost each provincial government about Rp5 billion (roughly US$555,555), while the budget for the poverty census in Sika is Rp1.5 billion (about US$166,667). In the actual CBMS, data collection and flow will be similar to Figure 2. However, the differences between this CBMS and BKKBN are: processing will be done at the district level, and provincial and national levels will only receive the processed results; and the processed data will also be disseminated back to the village level. Thus, the users of the data will be village leaders, district governments, and the national government. This ensures better targeting and more relevant programs for the people. 14

15 2.5 Timetable The following table outlines the proposed timeline of the study. Activities 1.Consultation Workshop 2.Design of the research instruments 3.Pretest 4. Revision of the research tools and Training 5. Data Collection 2005 Jan Feb Mar Apr May Jun Jul Aug Sept 6. Processing and Analysis 7. Workshop (to share the findings) 8. Final Report 15

16 Financial Budget Budget Site selection: 2 provinces, 2 districts, 2 sub-districts, 4 villages Institutional arrangement: SMERU: 2 advisors + 4 researchers National level 4 (BKKBN, Bappenas, Other institutions: Kesra, BPS) District level 4 (@ = 2 Pemda/BKKBN staff/former staff) Village level (@ 1 BKKBN staff/former staff + 1 BKKBN cadre + RWs + RTs) Cianjur: The average of Rw, RT and Household per village = 7 RWs; 27 RTs; Note: 1520 households Demak: The average of Rw, RT and Household per village = 5 RWs; 24 RTs; 1044 households Details # pax unit price unit # of unit Rp Total Salary SMERU: Advisors 2 15,000,000 month 2 60,000, ,016,000 Researchers 4 9,000,000 month 6 216,000,000 Others: National: BKKBN 1 2,000,000 month 3 6,000,000 National: Bappenas, Kesra, BPS 3 2,000,000 month 1 6,000,000 District 4 month 2 16

17 500,000 4,000,000 Village: BKKBN (staf+cadre) 8 100,000 week 2 1,600,000 Village: Enumerator (5440 HH) 152 3,000 respondent 36 16,416,000 Preparation Workshop in Jakarta 20 65,000 per pax per wshop 1,300,000 13,800,000 Workshop cost 12,500,000 workshop 1 12,500,000 Pre test in Cianjur Rent a car 1 450,000 day 2 900,000 2,550,000 Perdiem of SMERU researchers 4 300,000 night 1 1,200,000 Communication cost 4 100,000 lumpsum 400,000 Photo copy 50,000 lumpsum 50,000 Training in Cianjur Rent a car 1 450,000 day 3 1,350,000 19,800,000 Perdiem of SMERU researchers 2 300,000 night 2 1,200,000 Perdiem of national Team (BKKBN) 1 300,000 night 2 600,000 Communication 3 lumpsum 17

18 cost 100, ,000 Cost of district teams: transportation & meal 2 100,000 day 2 400,000 Cost of village teams: transportation & meal ,000 day 2 11,600,000 Foto copy 150,000 lumpsum 150,000 Training cost 2,000,000 day 2 4,000,000 Cost of supporting staff 2 50,000 day 2 200,000 Training in Demak Rent a car 1 450,000 day 3 1,350,000 28,057,500 Ticket Jakarta - Central Java (SMERU+Nationa l) 952,500 return ticket 3 2,857,500 Taxi Jakarta - Airport 3 150,000 lumpsum 450,000 Perdiem of SMERU researchers 2 300,000 night 2 1,200,000 Perdiem of national Team (BKKBN) 1 300,000 night 2 600,000 18

19 Communication cost 3 100,000 lumpsum 300,000 Cost of district teams: transportation & meal 2 100,000 day 2 400,000 Cost of village teams: transportation & meal ,000 day 2 16,400,000 Foto copy 300,000 lumpsum 300,000 Training cost 2,000,000 day 2 4,000,000 Cost of supporting staff 2 50,000 day 2 200,000 Field work Monitoring in Cianjur Rent a car 1 450,000 day 8 3,600,000 10,500,000 Perdiem of SMERU researchers 2 300,000 night 7 4,200,000 Perdiem of national Team (BKKBN) 1 300,000 night 2 600,000 Communication cost 3 300,000 lumpsum 900,000 Foto copy 1,200,000 lumpsum 1,200,000 19

20 Monitoring in Demak Rent a car 1 450,000 day 8 3,600,000 13,607,500 Ticket Jakarta - Central Java (SMERU+Nationa l) 952,500 return ticket 3 2,857,500 Taxi Jakarta - Airport 3 150,000 lumpsum 450,000 Perdiem of SMERU researchers 2 300,000 night 7 4,200,000 Perdiem of national Team (BKKBN) 1 300,000 night 2 600,000 Communication cost 3 300,000 lumpsum 900,000 Foto copy 1,000,000 lumpsum 1,000,000 Workshop In Jakarta ,000 per pax per wshop 5,000,000 26,500,000 Perdiem for district & village team ,000 night 1 3,000,000 Ticket Jakarta- Central Java:district & village team 5 1,000,000 lumpsum 5,000,000 20

21 Ticket Jakarta- Cianjur: district & village team 5 200,000 lumpsum 1,000,000 Workshop cost 12,500,000 workshop 1 12,500,000 Reporting Report production 17,000 report 300 5,100,000 59,933,333 CD Interactive 61,667 CD ,333,333 Distribution 5,000 report/cd 500 2,500,000 Dissemination 20,000,000 dissemination 2 40,000,000 Office overhead (office expenses, procurement, bank charges) 23,317,160 month 6 139,902,960139,902,960 PROJECT COST (in Rp) 624,667,293 PROJECT COST (in Rp 9100/U$) 68,645 SMERU Contribution (in US $) 18,645 Requested Support (in US $) 50,000 21

22 References: Asselin, Louis-Marie Composite Indicator or Multidimensional Poverty. mimeo. CECI. Canada. Filmer, Deon, and Lant Pritchett Estimating Wealth Effects without Expenditure Data or Tears: An Application to Educational Enrollments in States of India. mimeo, World Bank, Washington DC. Reyes, Celia, Kenneth Ilarde, Lani Valencia, and Joel Bancolita Utilizing CBMS in Monitoring and Targeting the Poor: The case of Barangay, San Vicente, Palawan unity-based Monitoring System. Paper presented at PEP Research Network Meeting, Senegal. Sudjana, Brasukra and Satish Mishra Growth and Inequality in Indonesia Today: Implications for Future Development Policy. UNSFIR Discussion Paper Series No. 04/05. United Nations Support Facility for Indonesian Recovery, Jakarta. Sumarto, Sudarno and Asep Suryahadi Principles and Approaches to Targeting: With Reference to the Indonesian Social Safety Net Programs. Paper presented at Workshop on Targeting and Rapid Assessment Methodologies, Jakarta. Sumarto, Sudarno, Asep Suryahadi, and Daniel Suryadarma State of Poverty in Indonesia in mimeo, The SMERU Research Institute, Jakarta. Sumarto, Sudarno, Daniel Suryadarma, Wenefrida Widyanti, and Asep Suryahadi Local Monitoring System during the Implementation of Indonesia s Crisis: Social Safety Net Programs with Special Reference to the BKKBN System. Paper presented at PEP Research Network Meeting, Senegal. Suryahadi, Asep and Sudarno Sumarto Poverty and Vulnerability in Indonesia Before and After the Economic Crisis. Asian Economic Journal, 17(1), pp Suryahadi, Asep and Daniel Suryadarma. Forthcoming. Vulnerability to Poverty is as Fluid as Poverty. The SMERU Research Institute, Jakarta. 22

23 Appendix 1. BKKBN Classification Indicators There are 23 indicators used by BKKBN to categorize welfare status of Indonesian families. These indicators are: 1. Family members are able to adhere to the religious principles of the religion of their choice. 2. All family members are able to eat at least twice a day. 3. All family members have different sets of clothing for home, work, schools, and visits. 4. The largest portion of the household floor is not made of dirt. 5. The family is able to obtain modern medicines or family planning services when a child is sick. 6. The family is able to follow religious laws and customs. 7. At least once a week, the family is able to consume meat, fish, or chicken. 8. Each family member obtains at least one new pair of clothing each year. 9. There is at least eight square meters of household space for each occupant in the house. 10. All family members have been healthy within the last three months. 11. At least one family member older than 15 years of age has a fixed income. 12. All family members between 10 and 60 years of age can read and write. 13. All children between 7 and 15 years of age are enrolled in school. 14. If the family has two or more living children and is still in the reproductive age group, the family uses contraceptives. 15. The family has the ability to improve its religious knowledge. 16. The family is able to save part of its earnings. 17. The family is able to eat with able members together at least once per day and that opportunity is used for communication among family members. 18. The family normally takes part in local community activities. 19. The family undertakes recreational activities outside the home at least once every six months. 20. The family is able to obtain news from newspapers, radio, television, or magazines. 21. Family members are able to use local transportation facilities. 22. The family makes regular contributions in the form of money or goods in social activities. 23. At least one family member is active in managing a local institution. 23

24 Appendix 2. Poverty Rates among Provinces in Indonesia Province Proportional change (%) Feb Feb 2002 Urban Rural Total Jakarta West Sumatera Bali East Kalimantan Riau Central Kalimantan West Java Jambi South Kalimantan Yogyakarta North Sulawesi North Sumatera West Kalimantan East Java Central Java South Sumatera South Sulawesi Central Sulawesi Bengkulu Southeast Sulawesi Lampung West Nusa Tenggara East Nusa Tenggara Papua Aceh Maluku Indonesia - Total note: Papua, Aceh, and Maluku were excluded in Source: SMERU calculations 24

25 Appendix 3a. Census Locations in West Java Province of West Java Kabupaten Cianjur 25

26 Appendix 3b. Census Locations in Central Java Province of Central Java Kabupaten Demak 26

27 Appendix 4. Profile of the SMERU Research Institute The SMERU Research Institute is an independent institution for research and policy studies which professionally and proactively provides accurate and timely information as well as objective analysis on various socioeconomic and poverty issues considered most urgent and relevant for the people of Indonesia. With the challenges facing Indonesian society in poverty reduction, social protection, social sector improvement, development in democratization processes, and the implementation of decentralization, there continues to be a pressing need for independent studies of the kind that SMERU has been providing. The Institute aims to continue delivering its high quality analysis of a range of social, economic and governmental issues to its stakeholders, including government agencies, nongovernment organizations, donor communities, and the general public. In an effort to achieve these objectives, the Institute has conducted various kinds of research, organized and attended national as well as regional workshops, and distributed newsletters, reports and papers through its mailing list and the SMERU website. SMERU has also taken part in important policy development by circulating memorandums to government agencies to ensure that the policies created are relevant to real conditions and include all groups within society. SMERU has been doing surveys throughout Indonesia since its inception, utilizing both quantitative and qualitative techniques. Several SMERU are: A Socioeconomic Impact Evaluation of the Sulawesi Agricultural Area Development Project (SAADP), 2004 The objectives of this study were to assess [1] the economic and social impacts of SAADP since 1999; [2] they way in which the process of SAADP implementation at the local level has affected outcomes; and [3] lessons for further policy development and design for the possible follow-on project. A combination of quantitative survey and in-depth interview were used in the study. Around 600 households were interviewed in Central and Southeast Sulawesi, one-third of which were control households. 27

28 Study of Service Provider Absenteeism in Health and Education, This study is part of the World Bank s worldwide absenteeism study, which included Bangladesh, Nepal, India, Ethiopia, Uganda, Peru, and Morocco. SMERU carried out the survey for Indonesia, where SMERU visited 147 primary schools and 100 Puskesmas in 10 districts that represented the country twice, in October 2002 and February Three purposes of the survey were: i) to document every provider-related issue; ii) to gain an understanding of the differences in the characteristic among districts as well as among primary schools and public health centre; and iii) to look at the difference of service delivery between countries, with the focus on the impact of regional autonomy, public participation, labor policies, and income. In addition, several qualitative and quantitative-based working papers have been written using the data gathered. Study on Targeting and Implementation of the BKM Scholarship and the JPS scholarship and Block Grant Programs in 2003 The purpose of the study is to analyze the allocation mechanism and implementation of JPS and BKM scholarship programs. In particular, the study examined the effectiveness of the targeting design in reaching the poor, and the extent of households and schools dependency on the scholarships. This study focused on SD/MI and SLTP/MTs schools. The survey was conducted in three districts (Blora, Lombok Timur, and Pontianak) and one municipality (Blitar). The study collected data using semi-structured in-depth interviews from two distinct sources of information: stakeholders at the three levels of allocation (districts, sub-districts and schools) and the intended beneficiaries (schools and students). Rice for Poor Families (RASKIN): Did the 2002 Program Operate Effectively? The aim of this study was to assess the effectiveness of the Raskin program by conducting a village-level survey in selected locations and drawing on all available statistical data. The most important issues that were investigated in the sample villages were [1] who were 28

29 actually receiving the rice; [2] what was the precise quantity of their monthly allotment; and [3] how much were the recipients really paying. All aspects of the implementation of the Raskin program were investigated using in-depth interviews with local officials, such as the extent and effectiveness of public education about the intended purpose of the program, delivery and payment procedures, and the extent and reliability of independent program monitoring and evaluation. In addition, SMERU also conducted informal and confidential interviews with the villagers, small store owners, and local volunteers. Targeted Programs in an Economic Crisis: Empirical Findings from the Experience of Indonesia, 2002 This paper draws on several recent household datasets to present four empirical findings about the targeting of Indonesian crisis programs, including [1] targeted sales of subsidized rice; [2] work creation programs; [3] scholarships to students and block grants to schools; [4] targeted health care subsidies; and [5] community block grants. Within the extensive literature on the many aspects of targeting and benefit incidence of government programs, this paper has three unique features. First, the paper addressed the question of the targeting of crisis programs that were created deliberately to address the consequences of a specific economic shock. Second, it used multiple data sources, including a panel data set that span through the crisis period, to cross validate findings. Third, it made comparisons across the set of programs. The Implementation of WFP- Subsidized Rice Program of OPSM in Three Urban Areas of Java, 2000 A rapid appraisal of the OPSM-WFP ( Operasi Pasar Swadaya Masyarakat World Food Programme program) was conducted by SMERU from mid-march to early April Twenty-six kelurahan in Jabotabek, Bandung and Surabaya were visited with the following aims in mind: (1) to identify the role played by NGOs, the community, and government officials in the OPSM-WFP program; (2) to determine the effectiveness of the targeting of beneficiaries; (3) to study the way the program has been implemented; (4) to identify the 29

30 overall impact of the OPSM-WFP program; (5) to make a general comparison of OPSM- WFP and OPK; and (6)to provide useful policy advice for future food assistance programs. During the rapid appraisal, information was collected through in-depth interviews of various sources, including both the beneficiaries and non-beneficiaries of OPSM-WFP, OPK beneficiaries, volunteers or NGO personnel at the points of distribution, officials from the NGOs involved, local community leaders, kelurahan officials and Dolog and Sub Dolog officials. Rapid Assessment of Education Problems, and the JPS Scholarships and Block Grants Program in Four Provinces, 1999 The aim of the study was to [1] gain an overall understanding of the status of the education system prior to the crisis; [2] identify the factors that caused students to remain at school, to drop out, or to discontinue their studies after the onset of the crisis; [3] examine the impact of the crisis on the quality of education and how it may have facilitated further problems; and [4] assess the effectiveness of the SSN Scholarships and Block Grants Program, especially regarding the suitability of the targets, the amount and forms of assistance, the benefits and drawbacks, and the suitability of the mechanisms adopted to implement the programs. In-depth assessments were conducted in four districts in four provinces (Pontianak-West Kalimantan, Tangerang-West Java, Sleman-Yogyakarta, and Lombok Timur-West Nusa Tenggara) during October and November Rapid Assessment on JPS-BK (Social Safety net on Health), 1999 The objectives of this study were, among others, to [1] ascertain the usage of Health Care Cards by the community; [2] find out the benefits and obstacles in the use of Health Care Cards; and [3] detect possible changes in the use and quality of services at the Puskesmas and Posyandu and the reasons for such changes. SMERU interviewed related parties, and conducted Focus Group Discussions (FGD) with groups of Posyandu cadres and groups of mothers of children under five (Health Care Cardholders). 30