Survai Aspek Kehidupan Rumah Tangga Indonesia 1997
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.
Developed the data-entry software and had responsibility for some of the data processing
National Institute on Aging
National Institute for Child Health and Human Development
United States Agency for International Development
World Health Organization
John Snow (OMNI project)
Futures Group (the POLICY project)
International Food Policy Research Institute
Because it is a longitudinal survey, the IFLS2 drew its sample from IFLS1. The IFLS1 sampling scheme stratified on provinces and urban/rural location, then randomly sampled within these strata. 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 cost-effectiveness reasons, 14 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, oversampling 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.
In IFLS1 it was determined to be too costly to interview all household members, so a sampling scheme was used to randomly select several members within a household to provide detailed individual information. IFLS1 conducted detailed interviews with the following household members:
• the household head and his/her spouse
• two randomly selected children of the head and spouse age 0 to 14
• an individual age 50 or older and his/her spouse, randomly selected from remaining members
• for a randomly selected 25% of the households, an individual age 15 to 49 and his/her spouse, randomly selected from remaining members.
IFLS2 Recontact Protocols
In IFLS2 our goal was to relocate and reinterview the 7,224 households interviewed in 1993. If no members of the household were found in the 1993 interview location, we asked local residents (including an informant identified by the household in 1993) where the household had gone. If the household was thought to be within any of the 13 IFLS provinces, the household was tracked to the new location and if possible interviewed there. Our willingness to track movers sets IFLS2 apart from the follow-up waves of many household surveys in developing countries, which simply revisit the original location of the household and interview whoever is found there. Our commitment to tracking movers paid off. In IFLS2 a full 94% of IFLS1 households were relocated and reinterviewed, in the sense that at least one person from the IFLS1 household was interviewed.
Community Survey (CPS )
It is often hypothesized that the characteristics of communities affect individual behavior, but rarely are household survey data accompanied by detailed data about the communities from which households are sampled. The IFLS is an exception. For each IFLS community in which we interviewed households, extensive information was collected from community leaders and from staff at schools and health facilities available to community residents.
The CFS sought information about the communities of HHS respondents. As in IFLS1, most of the information was obtained in the following ways:
• 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.
• Statistical 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.
IFLS2 gathered data from two new sources in each community:
• We interviewed someone considered an expert in the adat (traditional law) about the customary laws that influence behavior in the community. The purpose was to provide a perspective on cultural heterogeneity in Indonesia. Interviews with adat experts were not conducted in communities that were highly diverse in ethnic composition.
• We interviewed a social activist in the community about a project in which he or she was involved. Priority was given to projects providing safe water or building sanitation infrastructure. An important feature of Indonesia's economic development strategy has been the encouragement of local development initiatives by community members. We wanted to provide a perspective on such initiatives outside the formal leadership structure.
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 doctors, midwives, nurses, and paramedics (kliniks, praktek umum, perawats,
bidans, paramedis, mantri)
• Community health posts (posyandu)
• Elementary schools (SD)
• Junior high schools (SMP)
• Senior high schools (SMU)
IFLS2 used the same protocol for selecting facilities as IFLS1. We wanted the specific schools and health providers targeted for detailed interviews to reflect facilities available to the communities from which HHS 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 HHS respondents.
Health Facility Sampling Frame
For each EA, we compiled a list of facilities in each health facility stratum from HHS responses about the names and locations of facilities the respondent knew about. Specifically, we drew on responses from HHS book 1, module PP, which asked (typically) the female household head if she knew of health facilities of various types, such as government health centers. If she provided names and locations, those facilities were added to the sampling frame. HHS respondents did not need to have actually used a health facility for it to be relevant to the CFS sample. Though someone in the household may well have used a facility that was mentioned, any facility known to the respondent was relevant. We rejected requiring actual use of a facility because we judged that it 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 HHS 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.
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, or if it was located in another province. We also set a quota of facilities to be interviewed in each stratum. The goal was to obtain, for each stratum, data on multiple facilities per community. We also sought to maximize coverage of the facilities known and used by household members. For example, the larger quota for private practitioners than for health centers reflects the fact that Indonesian communities tend to have more private practitioners than health centers.
Stratum Quota per EA
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 HHS responses and ascertain which facilities met the criteria for interview. 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 (selected to match a random priority order grid in the SDII) to fill the quota for the stratum. See Figure 3 in “The Indonesia Family Life Survey (IFLS): Study Design and Results from Waves 1 and 2” (DRU-2238/1-NIA/NICHD) for a depiction of the sample selection process.
The IFLS2 Sample comprised 7,224 households (HH) interviewed in IFLS1 (panel households) with 22,347 individuals who provided detailed data in IFLS1 (panel respondents). In the sample, 404 HH were not found in IFLS2, leaving 6820 HH. The goal was to interview all members of the 6820 HHs. There were 878 Split-off HH. The goal was to interview target respondent + spouse and minor children. Finally the IFLS2 interviews conducted with 20,821 target IFLS1 household members; 5,716 other IFLS1 household members and 5,416 new respondents. (See Fig. 2 in the User Guide/Volume 1 “The Indonesia Family Life Survey (IFLS): Study Design and Results from Waves 1 and 2” (DRU-2238/1-NIA/NICHD).This is available under the external resources section.
In IFLS2 a full 94% of IFLS1 households were relocated and reinterviewed. (That number includes the 69 IFLS1 households whose every 1993 member had died by 1997, according to local informants.) In addition, we conducted interviews with 878 "split-off" households. These households resulted from tracking an IFLS1 household member who had left the "origin" household and interviewing them in their new location.
Community Survey (CPS):
In both waves we met our interviewing quotas. In IFLS2 we were able to interview almost 3,400 health facilities and over 2,500 schools.
There are two types of weights for IFLS2 respondents. IFLS2 longitudinal analysis weights are intended to update the IFLS1 weights because of attrition so that the IFLS2 panel sample is representative of the Indonesian population living in the 13 IFLS provinces in 1993. All respondents who were interviewed in 1997 but were not in an IFLS1 household roster are new entrants in IFLS2; they are assigned a longitudinal analysis weight of zero. It might be argued that the full sample of respondents interviewed in IFLS2 is sufficiently similar to the Indonesian population living in Indonesia in 1997 that one could use the sample to describe that population. Since the IFLS1 sample design included over-sampling in urban areas and off Java, users will need to re-weight the sample to take these design effects into account. The IFLS2 crosssection analysis weights are intended to do just that.
Dates of collection
Mode of data collection
Data collection supervision
The supervisors, interviewers, and CAFÉ editors were recruited from within the provinces in which we interviewed by the province's Population Studies Center. CAFÉ supervisors were recruited in Jakarta from computer studies academies. Local HHS supervisors were also selected from interviewer candidates and given special training.
Supervisory training was held for CAFÉ supervisors and Assistant Field Coordinators in Jakarta in June 1997. The training acquainted staff with basic aspects of the survey and questionnaire content and helped prepare them to assist with interviewer training.
During the Main Fieldwork the supervisors in each EA were responsible for the following:
·The HHS supervisor made an advance visit to the EA to meet the leader of the community, obtain local permissions, arrange a base camp, and scout for IFLS1 households.
·The HHS supervisor monitored progress using a variety of MIS forms, observed interviews that were randomly chosen, randomly visited households to check interviewers' work, and handled financial and logistical issues.
·The HHS supervisor oversaw the collection of information about movers and worked with the team and the Field Coordinator to determine whether a mover could be tracked locally. If the mover was thought to be within a 45 minute trip by public transport, the team attempted to track the mover while working in the mover's origin EA (local tracking).
·When all HHS interviews were completed, the HHS supervisor assembled the NCR pages from the HHS questionnaires that the CFS team needed for drawing the facility sample. The HHS supervisor had the pages delivered to the CFS team, either by the Field Coordinator or a hired messenger.
·The HHS supervisor also completed a financial report and mailed it, along with the paper questionnaires and diskettes containing the electronic data, to Jakarta.
·We sent the most talented field supervisors from Lembaga Demografi to particularly difficult areas, where they worked with tracking teams and on their own to pursue respondents' whereabouts. Teams and sometimes respondents were visited by the RAND project directors.
In nine modules of the HHS questionnaire, the CFS field supervisor assigned codes to link the facility mentioned by an HHS respondent to a specific facility in the CFS data.
Survey Instruments for the IFLS Household Questionnaires:
The IFLS is a comprehensive multipurpose survey that asks both current and retrospective questions at the household and individual levels. The household questionnaire in IFLS2 was organized like its IFLS1 counterpart and repeated many of the same questions to allow comparisons across waves. The IFLS1 questionnaire contained many retrospective questions covering past events. In IFLS2, full retrospectives were asked of new respondents. For most sections, respondents interviewed in 1993 were only asked to update the information, starting approximately five years before the 1997 interview, so there is one year of overlap between IFLS1 and IFLS2 data.
The questionnaire was divided in books (usually addressed to different respondents) and subdivided into topical modules. Three books collected information at the household level, generally from the household head or spouse: book K, book 1, and book 2. The next four books collected individual-level data from adult respondents (books 3A and 3B), ever-married female respondents (book 4), and children younger than 15 (book 5). Individual measures of health status were recorded for each household member (book US). In IFLS2 household members between the ages of 7 and 24 were asked to participate in cognitive assessments of their skills in mathematics and Indonesian language (book EK).
The IFLS2 questionnaires are in most respects were very similar to the IFLS1 questionnaires. A more detailed description of the IFLS and the survey instruments is provided in Volume 1 of the IFLS2 documentation, made available as External Resources. IFLS documentation is now available to the public </labor/FLS/IFLS/access.html>.
Book K: Control Book and Household Roster.
Book 1: Expenditures and Knowledge of Health Facilities.
Book 2: Household Economy.
Book 3A: Adult Information (part 1).
Book 3B: Adult Information (part 2).
(Books 3A and 3B, one book in IFLS1, were separated in IFLS2 to establish a natural breaking place for the interview if respondents could not answer all the questions in one sitting).
Book 4: Ever-Married Woman Information.
Book 5: Child Information.
Book US: Physical Health Assessments.
Book EK: Cognitive assessments.
Survey Instruments for the IFLS Community and Facility Survey Questionnaires:
As with the HHS, the CFS questionnaire was divided in books (addressed to different respondents) and subdivided into topical modules. Community-level information was collected in six books: book 1, book 2, book PKK, book SAR, book Adat, and book PM. Health facility information was collected in book PUSK, book PP, and book Posyandu. Each level of school was covered in a separate book, whose contents were nearly identical: book SD, book SMP, and book SMU.
Book 1. Collected a wide range of information about the community. It was addressed to the head of the community in a group interview.
Book 2. Provided a place to record statistical data about the community.
Book PKK. Was administered to the head of the village women's group. It asked about the availability of health services and schools in the community, including outreach activities; changes in the community over time; and in detail about the prices of foods and other items.
Book SAR. The Service Availability Roster was new for IFLS2. It was added after analysis of the IFLS1 data showed that community informants provided incomplete listings of the facilities to which HHS respondents had access. The SAR gathered in one place information on all the schools and health facilities available to residents of IFLS communities.
Book Adat. This book, new in IFLS2, was administered to someone the village head identified as a local expert in the adat (traditional law) of the community.
Health Facility Questionnaires
Separate books were designed for each health facility stratum:
Book PUSK for government health centers .
Book PP for private doctors and clinics .
Book Posyandu for community health posts .
The questionnaires for the three levels of schools (elementary, junior high school, and senior high school) had similar contents. In most of the modules, the principal or designee answered questions about the staff, school characteristics, and student population. One module, investigating teacher characteristics, was addressed to teachers of Indonesian language and mathematics. Another module had the interviewer answer specific questions based on direct observation about the quality of the classroom infrastructure. The final sections recorded student expenditures, math and language scores on the EBTANAS tests for a random sample of 25 students, and counts of teachers and students.
A detailed description of the Community and Facility Survey instruments is provided in Volume 1 of the IFLS2 documentation, made available as External Resources.
RAND Family Life Surveys
Demographic Institute of the University of Indonesia
University of Indonesia
University of California, Los Angeles
University of California, Los Angeles
Data Entry, Verification, and Data Cleaning
A second round of data entry, verification of data against the paper questionnaire, and extensive data cleaning were completed for the IFLS2, beginning in the field. These procedures are described in detail in the User's Guide Volumel 2, Section. 5.
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.