Family Life Survey 2007 - Indonesia

Abstract
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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.

Geographic coverage
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National coverage

Analysis unit
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- Communities
- Facilities
- Households
- Individuals

Kind of data
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Sample survey data [ssd]

Sampling procedure
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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
2000,
• 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.

Mode of data collection
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Face-to-face [f2f]

Research instrument
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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:

Community Questionnaires
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:Shops/Stalls
Book Prices: Informant
Book Posyandu: Community Child Health Post
Book Posyandu Lancia: Community Elderly Health Post

School Questionnaire
Book School: Elementary, Junior High and Senior High Schools
Book Mini-CFS: Community characteristics for non-IFLS communities

Cleaning operations
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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
clarify answers.

Response rate
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The recontact rate (including deaths) in IFLS4 among IFLS1 individuals is 81.7%.

摘要
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至1990年代中叶，印度尼西亚已经历了超过三十年的显著社会、经济和人口结构变革，并正处于跻身中等收入国家的门槛。自1960年代初以来，人均收入增长了十五倍以上，从约50美元增至超过800美元。在此期间，教育水平的提升以及生育率和婴儿死亡率的下降，反映了在基础设施方面的巨大投资。
在1990年代末，随着印度尼西亚陷入影响亚洲大部分地区的经济危机，经济前景开始发生变化。1998年，印尼盾崩盘，经济陷入衰退，国内生产总值预计下降了12-15%-这一降幅与大萧条相当。
几十年的经济进步之后紧接着几年的经济衰退的总体趋势，掩盖了整个群岛在经济发展和经济衰退方面的巨大差异。部分原因是印度尼西亚巨大的文化和民族多样性，这也使得印度尼西亚成为研究社会科学家感兴趣的个体和家庭层面行为和结果的良好实验室。
印度尼西亚家庭生活调查旨在为研究行为和结果提供数据。该调查包含大量在个体和家庭层面收集的信息，包括经济和非经济福祉的多个指标：消费、收入、资产、教育、移民、劳动力市场结果、婚姻、生育、避孕使用、健康状况、医疗保健和医疗保险的使用、共同居住和非共同居住家庭成员之间的关系、家庭决策背后的过程、家庭成员之间的转移以及社区活动的参与。除了个体和家庭层面的信息外，IFLS还提供了IFLS家庭所在社区以及为这些社区居民服务的设施方面的详细信息。这些数据涵盖了物理和社会环境、基础设施、就业机会、食品价格、健康和教育设施的可及性以及这些设施提供的服务质量和价格。通过将IFLS家庭的数据与其所在社区的数据联系起来，用户可以解决许多关于政策对受访者生活的影响的重要问题，并记录社会、经济和环境变化对人口的影响。
印度尼西亚家庭生活调查在多个方面补充和扩展了现有可用于印度尼西亚以及一般发展中国家的调查数据。
首先，相对而言，可用于发展中国家的规模较大、纵向调查很少。IFLS是印度尼西亚唯一的大型纵向调查。由于数据涵盖了同一个人在不同时间点的信息，IFLS为理解个人、家庭和社区层面的行为动态提供了机会。在IFLS1中，共采访了7,224个家庭，并从超过22,000个个体中收集了详细的个体级数据。在IFLS2中，94.4%的IFLS1家庭被重新联系（采访或去世）。在IFLS3中，重新联系率为95.3%的IFLS1家庭。事实上，近91%的IFLS1家庭是完整的面板家庭，即在IFLS1、2和3的三个波次中都被采访。这些重新联系率与美国的多数纵向调查和欧洲的多数纵向调查相当。高重新采访率部分得益于我们致力于追踪和采访那些从原始IFLS1家庭搬走或分家的人。高重新采访率在纵向调查中显著提高了数据质量，因为它们减少了由于非随机流失而导致的偏差风险。
其次，IFLS工具的多功能性意味着数据支持分析单用途调查无法分析的相互关联的问题。例如，家庭消费数据和关于劳动力市场结果、健康结果以及社区层面的健康计划可用性和质量的详细个体数据，使得人们可以研究收入对健康结果的影响，同时也可以研究健康是否反过来影响收入。
第三，IFLS在大多数主题上收集了当前和回顾性信息。有了关于当前状况的多个时间点的数据和关于受访者生活的广泛回顾性信息，分析师可以将动态与过去发生的事件联系起来。例如，可以探索近年来劳动力结果的变化作为早期关于教育和工作决策的函数。
第四，IFLS收集了广泛的健康状况指标，包括自我报告的一般健康状况、患病经历以及由护士进行的身体评估（身高、体重、头围、血压、脉搏、腰围和臀围、血红蛋白水平、肺活量和从坐着位置反复站起来的时间）。这些数据提供了比家庭调查中通常可用的数据更为丰富的健康状况图景。例如，这些数据可以用来探索社会经济地位与健康结果之间的各种关系。
第五，在调查的所有波次中，都收集了关于受访者社区和可为其提供医疗保健和学校教育的公共和私人设施的详细数据。可以将设施数据与家庭和个体数据结合起来，研究例如健康服务可及性（或可及性的变化）与各种健康保健使用和健康状况之间的关系。
第六，由于IFLS的波次跨越了经济危机袭击印度尼西亚数年之前、危机前夕以及危机发生后一年和三年这一时期，因此可以就印度尼西亚家庭在这一非常动荡时期的居住条件进行广泛的研究。总之，IFLS关于个人、家庭、社区和设施的纵向信息广度和深度，使其成为学者和政策制定者研究经济发展过程的独特资源。
地理覆盖范围
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全国覆盖
分析单位
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- 社区
- 设施
- 家庭
- 个人
数据类型
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样本调查数据 [ssd]
抽样程序
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由于IFLS4是一项纵向调查，因此其样本来自IFLS1、IFLS2、IFLS2+和IFLS3。IFLS1抽样方案在省份和城市/乡村位置上进行分层，然后在这些层内进行随机抽样（参见Frankenberg和Karoly，1995年，以获取详细说明）。选择省份以最大化人口代表性，捕捉印度尼西亚的文化和社会经济多样性，并在考虑到国家规模和地形的情况下进行成本效益调查。主要是出于成本效益的考虑，排除了当时存在的27个省份中的14个。结果样本包括印度尼西亚27个省份中的13个，占人口的83%：苏门答腊岛上的4个省份（北苏门答腊、西苏门答腊、南苏门答腊和廖内），所有5个爪哇省份（雅加达特别市、西爪哇、中爪哇、日惹和东爪哇），以及覆盖剩余主要岛屿群的4个省份（巴厘、西努沙登加拉、南卡里曼丹和南苏拉威西）。
在每个13个省份中，从1993年SUSENAS（约60,000户家庭的社会经济调查）使用的全国代表性样本框架中随机选择了人口普查区域（EAs）。IFLS在13个省份中随机选择了321个人口普查区域，对城市EAs和较小省份的EAs进行了过度抽样，以促进城市-乡村和爪哇-非爪哇的比较。
在选定的EAs内，根据从地区BPS办公室获得的1993年SUSENAS名单随机选择了家庭。家庭被定义为居住在同一住宅内且共享同一烹饪用具的成员群体（这是BPS的标准定义）。每个城市EAs选择了20户家庭，每个乡村EAs选择了30户家庭。这种策略最大限度地减少了在农村EAs之间昂贵的旅行成本，同时平衡了家庭之间的相关成本。IFLS1的最终样本量为7,000户完成的家庭，共抽样了7,730户家庭。这种策略基于BPS的经验，大约90%的完成率。事实上，IFLS1超过了这一目标，并在1993年底和1994年初对7,224户家庭进行了采访。
IFLS4重新联系协议
IFLS4的目标家庭是原始IFLS1家庭，减去到2000年所有成员都已去世的家庭，以及1997年、1998年和2000年的所有分家家庭（减去成员已去世的家庭）。主要实地工作从2008年11月底至2009年5月进行。总共联系了13,995户家庭，包括在波次之间去世的家庭、迁入其他IFLS家庭和新分家家庭。其中，实际采访了13,535户家庭。在10,994户目标家庭中，我们重新联系了90.6%：6,596户原始IFLS1家庭和3,366户旧分家家庭。在IFLS4中，还联系了4,033户新分家家庭。在IFLS1世系家庭中，我们联系了6,761户，或93.6%。在雅加达（80.3%）、南苏门答腊（88%）和北苏门答腊（88.6%）等地区实现了较低的世系重新联系率。雅加达当然是印度尼西亚的主要城市中心，印度尼西亚第二大城市棉兰位于北苏门答腊。IFLS一直以来的情况是，在这两个大都市区，找到面板家庭最难。另一方面，在西努沙登加拉和东爪哇等地区，重新联系率极高（世系家庭的99.3%和98.1%）。IFLS4关于追踪已搬家的个人的规则如下：
• 1993年的主要受访者，
• 1993年出生在1968年之前的家庭成员，
• 1993年原家庭中自1993年以来出生的个人，如果他们是1993年IFLS家庭成员的孩子，则也包括在分家家庭中，
• 1988年出生后如果他们在1993年的原家庭中居住，则包括1988年出生的个人，
• 如果他们在2000年接受了采访，则包括1968年至1988年之间出生的1993年家庭成员，
• 如果他们在2000年没有接受采访，则包括1968年至1988年之间出生的1993年家庭成员的20%随机样本。
IFLS4中的一个小的变化是，在IFLS3中，如果自IFLS2以来出生的新生儿在2000年被视为原家庭的家庭成员，则要追踪他们，现在即使他们在2007年不是家庭成员（即他们在早年搬出去，但仍然活着），也要追踪他们。
注意：关于整个抽样程序，包括IFLS1、2+和3的重新联系协议的详细说明，可在外部资源部分附带的概述和实地报告中找到。
数据收集方式
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面对面 [f2f]
研究工具
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IFLS4的家庭问卷组织方式与其早期版本类似，并重复了许多相同的问题，以允许跨波次进行比较。IFLS1问卷包含许多关于过去事件的回顾性问题。IFLS4遵循IFLS2和3，对新的受访者进行了全面的回顾性调查。IFLS4中的受访者被认为是面板受访者，如果他们已在IFLS3中回答了个人手册。面板受访者通常只被要求更新IFLS3中提供的信息，尽管在某些情况下，他们被要求回顾自2000年以来的历史。对于每个被采访的个体，都有预先打印的表格，其中包含要更新的答案。例如，在手册4中的CH模块，向女性询问她们生物学孩子的相关问题。在IFLS3的相关部分（CH和BA）中列出在2000年之前出生的孩子将列在预先打印的表格上，然后调查员将提示受访者至今为止出生的孩子，然后更新CH中的信息。
表2.7在用户指南第1卷中显示了问卷结构和内容，关于问卷结构的详细说明也可在同一用户指南的2.2节（家庭调查工具）中找到。
家庭问卷按照以下方式组织：
书T：跟踪手册
书K：控制手册和家庭名单
书1：支出和医疗设施知识
书2：家庭经济
书3A：成人信息第1部分（回顾性信息）
书3B：成人信息第2部分（当前信息）
代理书：成人信息代理 - 包含了3A、3B和4书中大多数部分缩短版本的成人个体信息，在采访时不可用。
书4：已婚妇女信息
书5：儿童信息
书US1 & US2（所有）：身体健康评估。具体测量值见附录B
书EK（7-24岁受访者的认知评估）
社区和设施问卷（COMFAS）针对村长和社区代表（分组访谈）。其组织如下：
社区问卷
书1：社区历史和特征
书2：社区统计
书PKK：村庄妇女组织
书SAR：服务可用性名单
书INFORMANT：公众对政府项目和公共服务的看法
书ADAT：传统法律和社区习俗
医疗设施问卷
书Puskesmas：政府卫生中心
书私人执业：医生、医疗诊所和其他私人医疗服务提供者
书传统从业者
书PRICES：市场
书PRICES：商店/摊位
书Prices：信息提供者
书Posyandu：社区儿童健康站
书Posyandu Lancia：社区老年人健康站
学校问卷
书学校：小学、初中和高中
书Mini-CFS：非IFLS社区的社区特征
数据清理操作
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随着家庭采访员完成问卷手册，他们将它们交给CAFE团队，该团队录入数据、编辑数据，并解决与采访员之间的任何疑问或不一致之处。有时采访员会回到受访者那里澄清答案。
响应率
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IFLS4中IFLS1个人的重新联系率（包括死亡）为81.7%。