Survai Aspek Kehidupan Rumah Tangga Indonesia 2000
By the middle of the 1990s, Indonesia had enjoyed over three decades of remarkable social, economic, and demographic change and was on the cusp of joining the middle-income countries. Per capita income had risen more than fifteenfold since the early 1960s, from around US$50 to more than US$800. Increases in educational attainment and decreases in fertility and infant mortality over the same period reflected impressive investments in infrastructure.
In the late 1990s the economic outlook began to change as Indonesia was gripped by the economic crisis that affected much of Asia. In 1998 the rupiah collapsed, the economy went into a tailspin, and gross domestic product contracted by an estimated 12-15%-a decline rivaling the magnitude of the Great Depression.
The general trend of several decades of economic progress followed by a few years of economic downturn masks considerable variation across the archipelago in the degree both of economic development and of economic setbacks related to the crisis. In part this heterogeneity reflects the great cultural and ethnic diversity of Indonesia, which in turn makes it a rich laboratory for research on a number of individual- and household-level behaviors and outcomes that interest social scientists.
The Indonesia Family Life Survey is designed to provide data for studying behaviors and outcomes. The survey contains a wealth of information collected at the individual and household levels, including multiple indicators of economic and non-economic well-being: consumption, income, assets, education, migration, labor market outcomes, marriage, fertility, contraceptive use, health status, use of health care and health insurance, relationships among co-resident and non- resident family members, processes underlying household decision-making, transfers among family members and participation in community activities. In addition to individual- and household-level information, the IFLS provides detailed information from the communities in which IFLS households are located and from the facilities that serve residents of those communities. These data cover aspects of the physical and social environment, infrastructure, employment opportunities, food prices, access to health and educational facilities, and the quality and prices of services available at those facilities. By linking data from IFLS households to data from their communities, users can address many important questions regarding the impact of policies on the lives of the respondents, as well as document the effects of social, economic, and environmental change on the population.
The Indonesia Family Life Survey complements and extends the existing survey data available for Indonesia, and for developing countries in general, in a number of ways.
First, relatively few large-scale longitudinal surveys are available for developing countries. IFLS is the only large-scale longitudinal survey available for Indonesia. Because data are available for the same individuals from multiple points in time, IFLS affords an opportunity to understand the dynamics of behavior, at the individual, household and family and community levels. In IFLS1 7,224 households were interviewed, and detailed individual-level data were collected from over 22,000 individuals. In IFLS2, 94.4% of IFLS1 households were re-contacted (interviewed or died). In IFLS3 the re-contact rate was 95.3% of IFLS1 households. Indeed nearly 91% of IFLS1 households are complete panel households in that they were interviewed in all three waves, IFLS1, 2 and 3. These re-contact rates are as high as or higher than most longitudinal surveys in the United States and Europe. High re-interview rates were obtained in part because we were committed to tracking and interviewing individuals who had moved or split off from the origin IFLS1 households. High re-interview rates contribute significantly to data quality in a longitudinal survey because they lessen the risk of bias due to nonrandom attrition in studies using the data.
Second, the multipurpose nature of IFLS instruments means that the data support analyses of interrelated issues not possible with single-purpose surveys. For example, the availability of data on household consumption together with detailed individual data on labor market outcomes, health outcomes and on health program availability and quality at the community level means that one can examine the impact of income on health outcomes, but also whether health in turn affects incomes.
Third, IFLS collected both current and retrospective information on most topics. With data from multiple points of time on current status and an extensive array of retrospective information about the lives of respondents, analysts can relate dynamics to events that occurred in the past. For example, changes in labor outcomes in recent years can be explored as a function of earlier decisions about schooling and work.
Fourth, IFLS collected extensive measures of health status, including self-reported measures of general health status, morbidity experience, and physical assessments conducted by a nurse (height, weight, head circumference, blood pressure, pulse, waist and hip circumference, hemoglobin level, lung capacity, and time required to repeatedly rise from a sitting position). These data provide a much richer picture of health status than is typically available in household surveys. For example, the data can be used to explore relationships between socioeconomic status and an array of health outcomes.
Fifth, in all waves of the survey, detailed data were collected about respondents¹ communities and public and private facilities available for their health care and schooling. The facility data can be combined with household and individual data to examine the relationship between, for example, access to health services (or changes in access) and various aspects of health care use and health status.
Sixth, because the waves of IFLS span the period from several years before the economic crisis hit Indonesia, to just prior to it hitting, to one year and then three years after, extensive research can be carried out regarding the living conditions of Indonesian households during this very tumultuous period. In sum, the breadth and depth of the longitudinal information on individuals, households, communities, and facilities make IFLS data a unique resource for scholars and policymakers interested in the processes of economic development.
National Institute for Child Health and Human Development
Because it is a longitudinal survey, the IFLS3 drew its sample from IFLS1, IFLS2, IFLS2+. The IFLS1 sampling scheme stratified on provinces and urban/rural location, then randomly sampled within these strata (see Frankenberg and Karoly, 1995, for a detailed description). Provinces were selected to maximize representation of the population, capture the cultural and socioeconomic diversity of Indonesia, and be cost-effective to survey given the size and terrain of the country. For mainly costeffectiveness reasons, 14 of the then existing 27 provinces were excluded. The resulting sample included 13 of Indonesia's 27 provinces containing 83% of the population: four provinces on Sumatra (North Sumatra, West Sumatra, South Sumatra, and Lampung), all five of the Javanese provinces (DKI Jakarta, West Java, Central Java, DI Yogyakarta, and East Java), and four provinces covering the remaining major island groups (Bali, West Nusa Tenggara, South Kalimantan, and South Sulawesi).
Within each of the 13 provinces, enumeration areas (EAs) were randomly chosen from a nationally representative sample frame used in the 1993 SUSENAS, a socioeconomic survey of about 60,000 households. The IFLS randomly selected 321 enumeration areas in the 13 provinces, over-sampling urban EAs and EAs in smaller provinces to facilitate urban-rural and Javanese-non-Javanese comparisons.
Within a selected EA, households were randomly selected based upon 1993 SUSENAS listings obtained from regional BPS office. A household was defined as a group of people whose members reside in the same dwelling and share food from the same cooking pot (the standard BPS definition). Twenty households were selected from each urban EA, and 30 households were selected from each rural EA.This strategy minimized expensive travel between rural EAs while balancing the costs of correlations among households. For IFLS1 a total of 7,730 households were sampled to obtain a final sample size goal of 7,000 completed households. This strategy was based on BPS experience of about 90% completion rates. In fact, IFLS1 exceeded that target and interviews were conducted with 7,224 households in late 1993 and early 1994.
IFLS3 Re-Contact Protocols
The sampling approach in IFLS3 was to re-contact all original IFLS1 households having living members the last time they had been contacted, plus split-off households from both IFLS2 and IFLS2+, so-called target households (8,347 households-as shown in Table 2.1*) Main field work for IFLS3 went on from June through November, 2000. A total of 10,574 households were contacted in 2000; meaning that they were interviewed, had all members died since the last time they were contacted, or had joined another IFLS household which had been previously interviewed (Table 2.1*). Of these, 7,928 were IFLS3 target households and 2,646 were new split-off households. A 95.0% re-contact rate was thus achieved of all IFLS3 "target" households. The re-contacted households included 6,800 original 1993 households, or 95.3% of those. Of IFLS1 households, somewhat lower re-contact rates were achieved in Jakarta, 84.5%, and North Sumatra, 90.4%, but in some provinces such as West Nusa Tenggara re-contact rates were near universal, 99% (Table 2.2*). Of the contacted households, 10,435 households were actually interviewed in 2000. Of these, 3,774 are split-off households since IFLS1 and 6,661 are IFLS1 households (Table 2.2*). For users interested in panel data analysis, 6,564 households were interviewed in all three full waves of IFLS: 1, 2 and 3. That represents 90.9% of the original IFLS1 households interviewed. When one adds in the households that died since 1993, the fraction is 92.3%. The provincial distribution of contacted and interviewed households is shown in Table 2.2*.
As in 1997 and 1998, households that moved were followed, provided that they still lived in one the 13 provinces covered by IFLS, or in Riau. Likewise individuals who moved out of their IFLS households were followed. The rules for following individuals who moved out of an IFLS household were expanded in IFLS3. Target respondents for tracking were:
• 1993 main respondents,
• 1993 household members born before 1968,
• individuals born since 1993 in origin 1993 households, also in splitoff households if they are children of 1993 IFLS household members
• individuals born after 1988 if they were resident in an origin household in 1993,
• 1993 household members who were born between 1968 and 1988 if they were interviewed in 2000,
• 20% random sample of 1993 household members who were born between 1968 and 1988 if they were not interviewed in 1997.
NOTE: A detailed explanation of the whole sampling procedure including the re-contact protocols for IFLS1, IFLS 2+ and IFLS3 is available in the Overview and Field Report available under External Resources.
*See tables in User Guide Volume 1 (Overview and Field Report).
Community and Facility Survey:
The community-facility survey sought information about the communities of household respondents. We followed the procedures of IFLS2 to obtain most of our information, but added some new modules and one new book:
• The official village/township leader and a group of his/her staff were interviewed about aspects of community life. Supplementary information was obtained by interviewing the head of the community women's group, who was asked about the availability of health facilities and schools in the area, as well as more general questions about family health and prices of basic commodities in the community.
• In visits to local health facilities and schools, staff representatives were interviewed about the staffing, operation, and usage of their facilities.
• Data were extracted from community records, and data on prices were collected through visits to up to three markets or sales points in the community.
• As in IFLS2, we interviewed a social activist in the community about a project in which he or she was involved.
• We collected information on a set of social safety net programs that the Government of Indonesia initiated in 1998 to try to ameliorate negative impacts of the economic crisis, which began at the end of 1997. Some of this information we obtained from our usual sources described above, but in one case, for the health component, a new book was added to obtain information on the newly created national social safety net program for health (JPS/BK).Respondents for this book were generally the village midwife or a member of the local public clinic staff who was appointed to run the program for the community.
• Various information related to the new Regional Autonomy laws were also added to serve as a base line on the Decentralization Program that the government of Indonesia embarked upon in early 2001.
• Another new addition of IFLS3 was to interview the official village/township leader of the communities to which IFLS respondents had moved (different from the 312 original IFLS1 communities) to obtain a minimal amount of information on communities to which households had re-located. We collected information on factors such as total population, conditions of the village, access to the village, electricity availability, water and health service in the village and main sources of income.
To cover the major sources of public and private outpatient health care and school types, we defined six strata of facilities to survey:
• Government health centers and subcenters (puskesmas, puskesmas pembantu)
• Private clinics and practitioners including doctors, midwives, nurses, and paramedics (klinik,
praktek umum, perawat, bidan, paramedis, mantri)
• Community health posts (posyandu)
• Elementary schools (SD)
• Junior high schools (SMP)
• Senior high schools (SMU) / Senior vocational high schools (SMK)
IFLS3 used the same protocol for selecting facilities as IFLS1 and IFLS2. We wanted the specific schools and health providers for detailed interviews to reflect facilities available to the communities from which household respondents were drawn. Rather than selecting facilities based solely on information from the village leader or on proximity to the community center, we sampled schools and health care providers from information provided by household respondents. A difference with IFLS1 and IFLS2 was in the amount of household information available to construct sampling frames. In IFLS3, the tracking of households that moved to or near the EA (in the same village/ kecamatan) had been done during main survey instead of after. This enabled us to add facilities to the sample frame from locally- tracked households. This strategy was adopted since it was felt that the tracked household information would cover facilities in the EA.
Health Facility Sampling Frame. For each EA, we compiled a list of facilities in each health facility stratum from household responses about the names and locations of facilities the respondent knew about. Specifically, we drew on responses from book 1, module PP of the household survey, which asked (typically) the female household head if she knew of health facilities of various types, such as government health centers. The names and locations provided were added to the sampling frame.Household respondents did not need to have actually used a health facility for it to be relevant to the facility sample. Though someone in the household may well have used a facility that was mentioned, any facility known to the respondent was relevant. Requiring actual use of a facility was rejected because it was judged that that approach would yield a more limited picture of community health care options (since use of health care is sporadic) and possibly be biased by factors such as what illnesses were common around the time of the interview.
School Sampling Frame. Names of candidate schools were obtained from household responses to book K, module AR, in which (typically) the household head verified the name and location of all schools currently attended by household members under age 25. Therefore, unlike the health facility sampling frame, each school in the candidate list had at least one member of an IFLS household attending.
Final Samples. Not all identified health facilities and schools were eligible for interview. A facility was excluded if it had already been interviewed in another EA, if it was more than 45 minutes away by motorcycle. The facilities that were located in another area were eligible for interview so long it was in our reachable area (about 45 minutes away by motorcycle). We set a quota of facilities to be interviewed in each stratum in each EA. The goal was to obtain, for each stratum, data on multiple facilities per community. The quotas were different for different strata. For example, a larger quota was set for private practitioners than for health centers because Indonesian communities tend to have more private practitioners than health centers.
Stratum Quota per EA
Government Health centers and subcenters 3
Private clinics and practitioners 6
Community health posts 2
Elementary schools 3
Junior high schools 3
Senior high schools 2
Two forms were used in developing the facility sample for each stratum. Sample Listing Form I (SDI) provided space to tally household responses and ascertain which facilities met the criteria for interview and were not duplicates of each other. Those facilities constituted the sampling frame and were listed on the second form, Sample Listing Form II (SDII), in order of frequency of mention. The final sample consisted of the facility most frequently mentioned plus enough others, randomly selected, to fill the quota for the stratum. Note that because we sampled randomly from sample frames constructed by householder knowledge of facilities in 2000, we may not necessarily have re-sampled facilities that were sampled in IFLS1 or 2.
Social Activist Sampling Frame. Sampling was also used to identify the social activists to be interviewed. Three community projects that most involved and covered people in the community and that comprised our frame of projects were listed. One project was randomly selected and an activist who worked on that project was selected for interview. If it was not possible to interview or meet any activists of that project then the next project from the list was chosen. If the community was not currently running any project, past community projects that had ever been run were selected.
Of the contacted households, 10,435 households were actually interviewed in 2000. Of these, 3,774 are split-off households since IFLS1 and 6,661 are IFLS1 households (Table 2.2 User Guide Volume 1/Overview and Field Report). For users interested in panel data analysis, 6,564 households were interviewed in all three full waves of IFLS: 1, 2 and 3. That represents 90.9% of the original IFLS1 households interviewed. When one adds in the households that died since 1993, the fraction is 92.3%. The provincial distribution of contacted and interviewed households is shown in Table 2.2 of the User Guide Volume 1 /Overview and Field Report.
Community and Facility Survey:
In all waves, interviewing quotas were met. In IFLS3 over 900 public health clinics and subclinics;over 1,900 private health facilities; over 600 community health posts and over 2,500 schools were interviewed. Table 3.2 of the User's Guide Volume 1 shows the number of facilities interviewed in each province, by stratum.
The IFLS sample, which covers 13 provinces, is intended to be representative of 83% of the Indonesian population in 1993. By design, the original survey over-sampled urban households and households in provinces other than Java. It is therefore necessary to weight the sample in order to obtain estimates that represent the underlying population. The Weights section of the User's Guide Volume 2 discusses the IFLS3 sampling weights that have been constructed for use with the household data. An overview of the weights from IFLS1, 2 and 3 is provided in Table 3.1 of the User's Guide. The reader should consult the IFLS1 and IFLS2 User’s Guides for details concerning IFLS1 and 2 weights.
There are two types of weights for IFLS3 respondents. In constructing these, IFLS follows the overall procedures used to construct weights for IFLS2, with some alterations because of the inherent differences in having three waves instead of only two (see the IFLS2 User’s Guide for details of the IFLS2 weights). The IFLS3 longitudinal analysis weights are intended to update the IFLS1 weights for attrition so that the IFLS3 panel sample (those IFLS3 households or individuals who were IFLS1 households or members in 1993), when weighted will be representative of the Indonesian population living in the 13 IFLS provinces in 1993. All respondents who were interviewed in IFLS3 but were not in an IFLS1 household roster are not assigned longitudinal weights; those will be missing in the data. We have also constructed longitudinal analysis weights for panel households and individuals who were in all three full waves of IFLS (IFLS1, 2 and 3). These weights are also intended to make this sub-sample of households or individuals representative of the 1993 population.
The IFLS3 cross-section analysis weights are intended to correct for sample attrition from 1993 to 2000, and then to correct for the fact that the IFLS1 sample design included over-sampling in urban areas and off Java. The cross-section weights are matched to the 2000 Indonesian population in order to make the attrition-adjusted IFLS sample representative of the 2000 Indonesian population.
Dates of collection
Long Distance Tracking Phase
Mode of data collection
Data collection supervision
Team supervisors were selected among the prospective candidates at the end of the interviewers’ training. They were selected based on criteria such as the previous experience, knowledge of the local area, knowledge of the questionnaires and leadership qualities.
CAFE supervisors were recruited from those who had previously held this role, plus some new persons who had shown promise during training. Each pair of household and community-facility teams was supervised by either a Field Coordinator or an Assistant Field Coordinator (with backstopping from a Field Coordinator). Field and Assistant Field Coordinators were recruited as much as possible from those with supervisory experience in IFLS2 and 2+.
Supervisory training was held for all senior personnel: potential household and community-facility survey and CAFE supervisors, Field and Assistant Field Coordinators; in Yogyakarta during the first two weeks of May 2000. Most of these personnel had participated during the household or community-facility survey pre-tests. This “training of trainers” included reviewing all parts of the survey: household, communityfacility, health, CAFE, tracking and the management information systems. The idea was to make everyone who had senior positions and would be involved in training of enumerators completely familiar with all aspects of the survey.
Development of Questionnaire
The HHS and CFS questionnaires fielded in IFLS1 provided the base for the IFLS2 questionnaires. The goal was to kept the instruments as similar as possible across the two waves in substantive content and questionnaire wording to maximize comparability. Changes were made to correct mistakes and improve questionnaire flow, lessen the response burden of the female household head, accommodate the existence of both panel respondents (who had given extensive data in IFLS1) and new respondents (who had provided no prior data), and to collect new data on topics of particular interest (decision-making in the household, community participation, and women's choices about pregnancy and childbirth). A few IFLS1 questions and modules were deleted, some modules were moved to across books, skip patterns were added to differentiate content for panel vs. new respondents, and new modules and questions were added. The contents of the questionnaires and IFSL1-IFSL2 changes are summarized in Secs. 2 and 3 of this document for the HHS and CFS, respectively.
The Household Questionnaire for IFLS3 is organized as follows :
Tracking Forms T-1 and T-2
Book K: Control Book and Household Roster
Book 1: Household Expenditures and Knowledge of Health Facilities
Book 2: Household Economy
Book 3A: Adult Information Part 1 (Retrospective Information from members aged 15+ yrs)
Book 3B: Adult Information Part 2 (Current and Retrospective Information for members aged 15+ yrs)
Book Proxy: Adult Information by Proxy - Contains shortened versions of most of the sections included in books 3A, 3B, and 4 for adult individuals not available at time of interview.
Book 4: Ever-Married Woman Information
Book 5: Child Information
Books US1 & US2 (All): Physical Health Assessments
Books EK (Cognitive Assessments for Respondents aged 7-24
The Community and Facilities Questionnaire (COMFAS) is directed at the Village Head and Community Representatives (Group Interview). It is organized as follows:
Book1: Community History and Characteristics
Book 2: Community Statistics
Book PKK: Village Women’s Organization
Book SAR: Service Availability Roster
Book PM: Case studies in community participation
Book JPS-BK: Social Safety Net Program-Health Component
Health Facility Questionnaires
Book Puskesmas: Government Health Center
Book Private Practice: Doctors, Health clinics and other private health service providers
Book Posyandu: Community Health Post
Book School: Elementary, Junior High and Senior High Schools
Book Mini-CFS: Community characteristics for non-IFLS communities
RAND Family Life Surveys
Center for Population and Policy Studies
University of Gadjah Mada
Data Entry, Verification, and Data Cleaning
In the Field: CAFE Editing, Interviewer Rechecks
CAFE operations were an important ingredient to the success of IFLS. This was an innovation begun in IFLS2. Data cleaning began in the field. Interviewers filled out the paper questionnaires while in the respondents’ households, then edited their work at base camp. For both the household and community facility surveys, interviewers were responsible for turning in legible questionnaires that had been filled out as completely and accurately as possible.A process of Computer-Assisted Field Editing (CAFE) was used to help maintain data quality in the household survey data.( Interviewers handed in their completed paper questionnaires to a CAFE team at base camp. The CAFE team entered and edited the data on laptop computers, using data-entry software (ISSA) designed to detect a variety of fielding errors. Range checks identified illogical values, such as a sex value of 2 when sex was supposed to equal 1 or 3.The CAFE editor was responsible for resolving error messages with the interviewer. Some errors could be resolved fairly easily. For example, the interviewer might mis-remember the sex of a respondent interviewed earlier in the day and verify that the inconsistency was due to a careless error. Other errors required the interviewer to return to the household and check with the respondent. For example, if in section TK, a person reported income from self-employment, the interviewers checked sections UT and NT to see if we had a corresponding entry there. If not they would go back to the household to re-check. When the CAFE team’s work was finished for an EA, the data were sent to the Yogyakarta office and were electronically transmitted (via ftp) to RAND in Santa Monica. A team in Yogyakarta performed basic data quality checks, monitored re-contact rates, and provided feedback to the teams in the field.
Community-Facility Data Entry
Data entry for the community-facility survey was done in Yogyakarta by a team chosen largely from community-facility survey interviewers. The control of transcription errors by entering the data from paper questionnaires was done by comparing questionnaire and the electronic data after the data entry was done.
Time did not permit writing of programs for data entry in time to be used in the field for the Community-Facility Survey.
ID assignments were rigorously checked across Books and Survey Waves.
NOTE: See User's Guide Volume 1 for further details.
The IFLS data are placed in the public domain to support research analyses. As a user of the IFLS public use files, you are expected to respect the anonymity of all our respondents. This means that you will make no attempt to identify any individual, household, family, service provider or community other than in terms of the anonymous codes used in the IFLS.
The data are freely available on the RAND website. Users are requested to register with RAND to access survey data.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.