Survai Aspek Kehidupan Rumah Tangga Indonesia 2007
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.
Non-governmental Research Institution in Indonesia
National Institute on Aging
National Institute for Child Health and Human Development
Australian Agency for International Development
World Bank, Jakarta
Because it is a longitudinal survey, the IFLS4 drew its sample from IFLS1, IFLS2, IFLS2+ and IFLS3. 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.3 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.4 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.
IFLS4 Re-Contact Protocols
The target households for IFLS4 were the original IFLS1 households, minus those all of whose members had died by 2000, plus all of the splitoff households from 1997, 1998 and 2000 (minus those whose members had died). Main fieldwork went on from late November 2008 through May 2009. In total, 13,995 households were contacted, including those that died between waves, those that relocated into other IFLS households and new splitoff households. Of these, 13,535 households were actually interviewed. Of the 10,994 target households, we re-contacted 90.6%: 6,596 original IFLS1 households and 3,366 old splitoff households. An additional 4,033 new splitoff households were contacted in IFLS4. Of IFLS1 dynastic households, we contacted 6,761, or 93.6%. Lower dynasty re-contact rates were achieved in Jakarta (80.3%), south Sumatra (88%) and north Sumatra (88.6%). Jakarta is of course the major urban center in Indonesia, and Medan, Indonesia's second largest city is in north Sumatra. It has always been the case for IFLS that in these two metropolitan areas it is hardest to find panel households. On the other hand, in places like west Nusa Tenggara and east Java, re-contact rates were extremely high (99.3% and 98.1% respectively of dynastic households). IFLS4 rules for tracking individuals who had moved 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
• 20% random sample of 1993 household members who were born between 1968 and 1988 if they
were not interviewed in 2000.
One small change in IFLS4 was that whereas in IFLS3 new babies born since IFLS2 were to be tracked if they were considered household members in 2000, now they were to be tracked even if they were not considered household members in 2007, that is they had moved out in earlier years, but were still alive.
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 attached in the External Resources section.
The recontact rate (including deaths) in IFLS4 among IFLS1 individuals is 81.7%.
There are two types of weights for IFLS4 respondents. Their construction follows the overall procedures used to construct weights for IFLS3, with some alterations because of the inherent differences in having four waves instead of only three . The IFLS4 longitudinal analysis weights are intended to update the IFLS1 weights for attrition so that the IFLS4 panel sample (those IFLS4 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 IFLS4 but were not in an IFLS1 household roster are not assigned longitudinal weights; those will be missing in the data. Also constructed, are the longitudinal analysis weights for panel households and individuals who were in all four full waves of IFLS (IFLS1, 2, 3 and 4). These weights are also intended to make this sub-sample of households or individuals representative of the 1993 population. For users who would rather not use inverse probability weights to correct for attrition (there are numerous assumptions required to properly use these weights), they can use the 1993 household or individual weights with the 2007 data, to get to 1993 population estimates that correct for the IFLS sample design.
The IFLS4 cross-section analysis weights are intended to correct both for sample attrition from 1993 to 2007, 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 2007 Indonesian population, again in the 13 IFLS provinces, in order to make the attrition-adjusted IFLS sample representative of the 2007 Indonesian population in those provinces. Cross-section weights are also reported,and these only correct for sample design, and not for attrition, just like the longitudinal weights.
These ILFS4 weights are defined and described in detail in the Weights section of the Users Guide Volume 2, available under External Resources.
Dates of collection
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 showed a good understanding of the questionnaires, plus who were versatile with computers. 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 data entry experience in prior waves of IFLS.
Supervisory training was held for all senior personnel: potential household and community-facility survey and CAFE supervisors, Field and Assistant Field Coordinators; in Salatiga, Central Java, from August 27-September 15 2007. 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, community-facility, 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.
The household questionnaire in IFLS4 was organized like its earlier counterparts and repeated many of the same questions to allow comparisons across waves. The IFLS1 questionnaire contained many retrospective questions covering past events. IFLS4 followed IFLS2 and 3 in asking full retrospectives of new respondents. Respondents in IFLS4 were considered to be panel respondents if they had answered individual books in IFLS3. Panel respondents were usually only asked to update the information, from the information they provided in IFLS3, although in some cases they were asked to recount histories since 2000. Enumerators had pre-printed forms for every individual they interviewed, containing the answers from which the information was to be updated. For example, in module CH in book 4, women are asked questions about their biological children. Children who were born before 2000 and listed in the relevant sections (CH and BA) of IFLS3 would be listed on the preprinted forms and the enumerator would prompt the respondent with the children born to-date then and then update the information in CH.
Table 2.7 in the User Guide Volume 1 shows the questionnaire structure and contents, and a detailed explanation of the structure of the questionnaire is also available in section 2.2 (Household Survey Instruments) of the same User Guide.
The Household Questionnaire is organized into books as follows :
Book T: Tracking Book
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 (Retrospective Information)
Book 3B: Adult Information Part 2 (Current Information)
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. Specific Measurements Listed in Appendix B
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 INFORMANT: Public Perception on Government Programs and Public Services
Book ADAT: Traditional law and community customs
Health Facility Questionnaires
Book Puskesmas: Government Health Center
Book Private Practice: Doctors, Health clinics and other private health service providers
Book Traditional Practitioner
Book PRICES: Market
Book Prices: Informant
Book Posyandu: Community Child Health Post
Book Posyandu Lancia: Community Elderly 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
As household interviewers completed questionnaire books, they turned them over to the CAFE team, which entered the data, edited the data, and resolved any questions or inconsistencies with the interviewers. Sometimes interviewers returned to the respondents to
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.
IFLS1 is copyrighted by RAND and Lembaga Demografi. IFLS2 is copyrighted by RAND.