The IFLS Study Design
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 1215%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 these behaviors and outcomes. The survey contains a wealth of information collected at the individual and household levels, including multiple indicators of economic well-being (consumption, income, and assets); education, migration, and labor market outcomes; marriage, fertility, and contraceptive use; health status, use of health care, and health insurance; relationships among coresident and non-coresident family members; processes underlying household decision-making; transfers among family members and inter-generational mobility; 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, the analyst 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 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 this 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.
Contributions of the IFLS
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. The IFLS is the only large-scale longitudinal survey publicly available for Indonesia. Because data are available for the same individuals from multiple points in time, the IFLS affords an opportunity to understand the dynamics of the world we are living in today.
In IFLS1 7,224 households were interviewed, and detailed individual-level data were collected from over 22,000 individuals. In IFLS2, 94% of IFLS1 households and 91% of IFLS1 target individuals were reinterviewed. In IFLS3, 95.3% of IFLS1 households were recontacted and in IFLS4 the recontact rate was 93.6%. Among IFLS1 dynasty households (any part of the original IFLS1 households, 90.3% were either interviewed in all 4 waves or died, and 87.6% were actually interviewed in all four waves. These recontact rates are as high as or higher than most longitudinal surveys in the United States and Europe. High reinterview 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 reinterview 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 the IFLS instruments means that the data support analyses of interrelated issues not possible with single-purpose surveys. Because data are available for the same individuals from multiple points in time, the IFLS affords an opportunity to understand the dynamics of behaviour, at the individual, household and family and community levels.
Third, the 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, migration, and work.
Fourth, the IFLS collected extensive measures of health status, including self-reported measures of general health status, symptoms, pain, doctor diagnosed chronic conditions, time spent on different physical activities, and biomarker measurements conducted by a nurse (height, weight, leg length, blood pressure, pulse, waist and hip circumference, hemoglobin level, total and HDL cholesterol,grip strength, 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. 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.
Fifth, in all waves of the survey, detailed data were collected about respondents communities and public and private facilities available for their health care and schooling. The community-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 the IFLS span the period from several years before the 1998 financial crisis hit Indonesia, to just prior to it hitting, to one year, three years and now ten 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 the IFLS data a unique resource for scholars and policymakers interested in the processes of economic development.