{"type":"survey","doc_desc":{"title":"IDN_1997_IFLS_v01_M","idno":"DDI_IDN_1997_IFLS_v01_M","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Ducumentation of the DDI"}],"prod_date":"2012-07-23","version_statement":{"version":"Version 01 (July 2012)"}},"study_desc":{"title_statement":{"idno":"IDN_1997_IFLS_v01_M","title":"Family Life Survey 1997","sub_title":"IFLS2","alt_title":"IFLS 1997","translated_title":"Survai Aspek Kehidupan Rumah Tangga Indonesia 1997"},"authoring_entity":[{"name":"RAND Corporation","affiliation":"RAND Corporation"},{"name":"University of California, Los Angeles","affiliation":"UCLA"}],"production_statement":{"producers":[{"name":"MACRO International","affiliation":"MACRO International","role":"Developed the data-entry software and had responsibility for some of the data processing"}],"funding_agencies":[{"name":"National Institute on Aging","abbreviation":"NIA","role":"Funding"},{"name":"National Institute for Child Health and Human Development","abbreviation":"NICHD","role":"Funding"},{"name":"United States Agency for International Development","abbreviation":"USAID","role":"Funding"},{"name":"World Health Organization","abbreviation":"WHO","role":"Funding"},{"name":"John Snow (OMNI project)","abbreviation":"","role":"Funding"},{"name":"Hewlett Foundation","abbreviation":"","role":"Funding"},{"name":"Futures Group (the POLICY project)","abbreviation":"","role":"Funding"},{"name":"International Food Policy Research Institute","abbreviation":"IFPRI","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"RAND Family Life Surveys","affiliation":"RAND Corporation","email":"ifls-supp@rand.org","uri":"www.rand.org"}]},"series_statement":{"series_name":"Integrated Survey (non-LSMS) [hh\/is]","series_info":"The Indonesian Family Life Survey (IFLS) is an on-going longitudinal survey in Indonesia. The sample is representative of about 83% of the Indonesian population and contains over 30,000 individuals living in 13 of the 27 provinces in the country. A map identifying the 13 IFLS provinces is available on the Rand Family Life Surveys web site.The first wave of the IFLS (IFLS1) was conducted in 1993\/94 by RAND in collaboration with Lembaga Demografi, University of Indonesia. IFLS2 and IFLS2+ were conducted in 1997 and 1998, respectively, by RAND in collaboration with UCLA and Lembaga Demografi, University of Indonesia. IFLS2+ covered a 25% sub-sample of the IFLS households. IFLS3, which was fielded in 2000 and covered the full sample, was conducted by RAND in collaboration with the Population Research center, University of Gadjah Mada. IFLS4, fielded in 2007\/2008 on the same 1993 households and splitoofs, was conducted by RAND in collaboration with the Center for Population and Policy Studies (CPPS) of the University of Gadjah Mada and Survey Meter.\n\nPanel Study details are as follows:\n1993 (baseline): In-home, face-to-face interview with household head, spouse and sample of their children and sample of other adult household members. \n1997: Follow-up all households, all 1993 \"main\" respondents and all 1993 household members born before 1967.\n1998: Follow-up of 25% sub-sample (not funded by NIA) Interview selected household members (1993) and all household members (1997 & 1998).\n2000: Follow-up all households, all 1993 \"main\" respondents, all 1993 household members born before 1967, sample of other 1993 household members. \n2007: Fieldwork November 2007 to May 2008, public release Spring 2009.\n\nSample Sizes:\n1993: 7,200 households;22,000 individual interviews\t\n1997: 7,500 households;33,000 individual interviews\t\n1998: 2,000 households;10,000 individual interviews \t\n2000: 10,400 households;39,000 individual interviews"},"study_info":{"abstract":"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.\n\nIn 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.\n\nThe 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.\n\nThe 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.\n\nThe 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.\n\nFirst, 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.\n\nSecond, 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.\n\nThird, 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.\n\nFourth, 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.\n\nFifth, in all waves of the survey, detailed data were collected about respondents\u00b9 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.\n\nSixth, 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.","coll_dates":[{"start":"1997-08-01","end":"1997-12-01","cycle":"Main Fieldwork"},{"start":"1997-12-01","end":"1998-03-31","cycle":"Tracking Phase"}],"nation":[{"name":"Indonesia","abbreviation":"IDN"}],"geog_coverage":"National coverage","analysis_unit":"- Communities\n- Facilities\n- Households\n- Individuals","data_kind":"Sample survey data [ssd]","notes":"The Indonesia Family Life Survey 1997 covers the following themes:\n\n-Consumption \n-Tobacco consumption \n-Knowledge of health care providers \n-Acute Morbidity\n-Labor earnings and work histories\n-Ability to perform ADL's \n-Household and individual assets \n-Self-treatment Education and migration histories\n-Health service utilization\n-Marriage and pregnancy histories\n-Health Insurance \n-Links with non co-resident kin\n-Height, weight, waist\/hip, hemoglobin \n-Transfers and borrowing\n-Lung capacity, blood pressure, mobility \n-Household decision-making \n-Nurses' assessment of health status\n-Community support network","study_scope":"The Indonesia Family Life Survey 1997 covers the following themes:\n\n-Consumption \n-Tobacco consumption \n-Knowledge of health care providers \n-Acute Morbidity\n-Labor earnings and work histories\n-Ability to perform ADL's \n-Household and individual assets \n-Self-treatment Education and migration histories\n-Health service utilization\n-Marriage and pregnancy histories\n-Health Insurance \n-Links with non co-resident kin\n-Height, weight, waist\/hip, hemoglobin \n-Transfers and borrowing\n-Lung capacity, blood pressure, mobility \n-Household decision-making \n-Nurses' assessment of health status\n-Community support network"},"method":{"data_collection":{"data_collectors":[{"name":"RAND Family Life Surveys","abbreviation":"","affiliation":"RAND Corporation"},{"name":"Demographic Institute of the University of Indonesia","abbreviation":"LDUI","affiliation":"University of Indonesia"},{"name":"University of California, Los Angeles","abbreviation":"UCLA","affiliation":"University of California, Los Angeles"}],"sampling_procedure":"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.\n\nHousehold Survey\nWithin 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.\n\nIn 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:\n\u2022 the household head and his\/her spouse\n\u2022 two randomly selected children of the head and spouse age 0 to 14\n\u2022 an individual age 50 or older and his\/her spouse, randomly selected from remaining members\n\u2022 for a randomly selected 25% of the households, an individual age 15 to 49 and his\/her spouse, randomly selected from remaining members.\n\nIFLS2 Recontact Protocols\nIn 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.\n\nCommunity Survey (CPS )\n\nIt 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.\n\nThe CFS sought information about the communities of HHS respondents. As in IFLS1, most of the information was obtained in the following ways:\n\u2022 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.\n\u2022 In visits to local health facilities and schools, staff representatives were interviewed about the staffing, operation, and usage of their facilities.\n\u2022 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. \n\nIFLS2 gathered data from two new sources in each community:\n\u2022 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.\n\n\u2022 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.\n\nSample Selection\nTo cover the major sources of public and private outpatient health care and school types, we defined six\nstrata of facilities to survey:\n\u2022 Government health centers and subcenters (puskesmas, puskesmas pembantu)\n\u2022 Private clinics and doctors, midwives, nurses, and paramedics (kliniks, praktek umum, perawats,\nbidans, paramedis, mantri)\n\u2022 Community health posts (posyandu)\n\u2022 Elementary schools (SD)\n\u2022 Junior high schools (SMP)\n\u2022 Senior high schools (SMU)\n\nIFLS2 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.\n\nHealth Facility Sampling Frame\n 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.\n\nSchool Sampling Frame\nNames 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.\n\nFinal Samples\nNot 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.\n\nStratum Quota per EA\nHealth centers and subcenters 3\nPrivate clinics and practitioners 6\nCommunity health posts 2\nElementary schools 3\nJunior high schools 3\nSenior high schools 2\n\nTwo 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 \u201cThe Indonesia Family Life Survey (IFLS): Study Design and Results from Waves 1 and 2\u201d (DRU-2238\/1-NIA\/NICHD) for a depiction of the sample selection process.","coll_mode":"Face-to-face [f2f]","research_instrument":"Survey Instruments for the IFLS Household Questionnaires:\n\nThe 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.\nThe 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). \n\nThe 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>. \n\nBook K: Control Book and Household Roster.\nBook 1: Expenditures and Knowledge of Health Facilities.\nBook 2: Household Economy.\nBook 3A: Adult Information (part 1).\nBook 3B: Adult Information (part 2).\n(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).\nBook 4: Ever-Married Woman Information.\nBook 5: Child Information.\nBook US: Physical Health Assessments.\nBook EK: Cognitive assessments.\n\nSurvey Instruments for the IFLS Community and Facility Survey Questionnaires:\n\nAs 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. \n\nBook 1. Collected a wide range of information about the community. It was addressed to the head of the community in a group interview. \nBook 2. Provided a place to record statistical data about the community.\nBook 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. \nBook 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. \nBook 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. \n\nHealth Facility Questionnaires\nSeparate books were designed for each health facility stratum:\nBook PUSK for government health centers .\nBook PP for private doctors and clinics .\nBook Posyandu for community health posts .\n\nSchool Questionnaires\nThe 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. \n\nA detailed description of the Community and Facility Survey instruments is provided in Volume 1 of the IFLS2 documentation, made available as External Resources.","coll_situation":"Interviewer training was conducted in two phases (classroom training and field practice) and took place in three sites. HHS interviewers received three weeks of classroom training. CAF\u00c9 editors were chosen from this group and given about one week of specialized training. Local HHS supervisors were also selected from interviewer candidates and given special training. CFS interviewers were trained simultaneously and received 10 days of classroom training. Local CFS supervisors were selected from this group. All health workers were trained at one time in Jakarta.\n\nField work \nA total of 23 pairs of teams (HHS + CFS) were sent into the field. There were two phases of fieldwork:\nthe main fieldwork period (August-December, 1997) and the tracking phase (December, 1997-March, 1998). Each pair of teams was assigned a route that would take them to 8-12 enumeration areas. The HHS team interviewed first, with the CFS team visiting the same EA about two weeks later, after the household interviews were completed. Teams worked in only one province, but some provinces required multiple teams. After the main fieldwork ended, some interviewers moved to different provinces to help locate and reinterview movers during the tracking phase.The sequence of main fieldwork is outlined in Volume 1 of the Survey documentation available under External Resources.\n\nTracking.\nOnce each team had completed work in its assigned EAs, the HHS interviewers were given additional tracking assignments for households or individuals that had not been located during the main fieldwork period but were thought to reside in the province. In addition to being provided with the names of the households and individuals that needed to be tracked, the teams were given all the information that had been collected in the origin EA (for example from local informants) about the potential whereabouts of each case. We tried to attain the highest possible reinterview rate and to minimize differences in reinterview rates across EAs. If an EA showed a low recontact rate that we thought could be raised through revisits (for example, if households had been located in the original EA but had not been able to participate at the time the team was there, or if information on movers was inadequate), the teams were asked to return and try to recontact households or to obtain better information on movers.\n\nManaging the tracking information was centralized in Jakarta, and tracking assignments were made from there after consultation with the team\u2019s Field Coordinator and Assistant Field Coordinator. Tracking progress was monitored daily from Jakarta based on faxed reports from the field. Records of each household\u2019s and target individual\u2019s interview status were maintained in an electronic database, which was developed from the survey data entered during the main fieldwork and updated as cases were completed. The fact that we had information on who needed to be tracked along with their whereabouts played an important role in the success of our tracking.\nThe tracking phase was one of the most arduous in terms of managing the work and keeping the staff motivated. We judged it important to centrally monitor success rates and set work priorities. As interviewers tired and remaining cases became more stubborn, we assigned smaller and smaller tracking teams. 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\u2019 whereabouts. Teams and sometimes respondents were visited by the RAND project directors. Interviewer bonuses were offered to increase incentives to find missing respondents.\n\nThe instruments, data entry software, and field procedures were extensively tested before the fieldwork began. Protocols for locating and reinterviewing IFLS respondents were designed during pilot tests and revised during full-scale pretests. New questions and modules were developed and tested using focus groups and pilot tests. The HHS questionnaire was tested in its entirety during two full-scale pretests.The CFS questionnaire and the health status measurements were each tested during one pretest. Pretests allowed us to evaluate questionnaire changes in a field setting.\n\nFirst Pretest of HHS Questionnaire\nThe first pretest of the HHS questionnaire, conducted in Solo, Central Java, in October 1996, focused on\nquestionnaire content and field editing protocols. Its primary objectives were to\n\u2022 Test procedures for relocating households and individuals.\n\u2022 Assess our ability to differentiate between panel and new respondents and administer the\nquestionnaire correctly, depending on the respondent's status.\n\u2022 Evaluate the advantages and disadvantages of using preprinted information from IFLS1.\n\u2022 Evaluate the length of the questionnaire, the length of each module, and the burden imposed\non different types of respondents.\n\u2022 Evaluate the content of new or heavily revised questionnaire modules.\n\u2022 Assess the feasibility of administering school achievement and cognitive tests to children\nunder age 15.\n\u2022 Evaluate the advantages and disadvantages of Computer-Assisted Field Editing (CAF\u00c9).\n\nCAF\u00c9 Procedures\nIn order to use computer-assisted field editing, all questionnaires had to be keypunched in the field. This had the advantage of completing the first round of data entry as well. \n\nThe second pretest provided convincing evidence that CAF\u00c9 was feasible: a diskette containing pretest data was available only one day after the interviews had ended. CAF\u00c9 allowed a far more thorough check of completed questionnaires than is possible with traditional manual (e.g., eyeball) methods of editing. In the pretest, CAF\u00c9 reduced missing data and cleared up confusion due to interviewer handwriting. \n\nHealth Measurement Pilot Test\nIn June 1997 we conducted a pilot test of the HHS health status measurements. It showed the importance of training health workers not only to measure respondents accurately but also to record measurements accurately on the paper questionnaire. \n\nPretest of the CFS\nThe CFS pretest was held in May 1997 in a rural area outside Jakarta. It was primarily a test of the instruments, since basic procedures and protocols for drawing the facility sample changed little between IFLS1 and IFLS2. The results were valuable in indicating how to revise the questionnaires.\nNOTE: See Survey Operations - User's Guide Volume 1 under External Resources for further details.","act_min":"The supervisors, interviewers, and CAF\u00c9 editors were recruited from within the provinces in which we interviewed by the province's Population Studies Center. CAF\u00c9 supervisors were recruited in Jakarta from computer studies academies. Local HHS supervisors were also selected from interviewer candidates and given special training.\n\nSupervisory training was held for CAF\u00c9 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.\n\nDuring the Main Fieldwork the supervisors in each EA were responsible for the following:\n\u00b7The 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. \n\u00b7The 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.\n\u00b7The 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).\n\u00b7When 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. \n\u00b7The HHS supervisor also completed a financial report and mailed it, along with the paper questionnaires and diskettes containing the electronic data, to Jakarta.\n\u00b7We 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.\n\nIn 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.","weight":"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. 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