4.1 Family life in Indonesia
As in other developing countries with high growth rates, fertility rates in Indonesia have decreased while life expectancy has increased in the last decades (Frankenberg, Chan, and Ofstedal 2002). Intergenerational linkages are strong (according to adat, traditional law, children are required to care for their parents), and coresidence is common, especially when parents are not working. Since the social security system is underdeveloped, elder parents rely on their children as they grow older. Johar and Maruyama (2011) study coresidence in Indonesia and find that family decisions are often driven by the gains and costs of children. They show, using data from the Indonesian Family Life Survey, that the proportion of elderly parents living with a child has dropped from approximately 65% in the 1990s to slightly above 50% in 2007. However, the authors find no evidence of adverse economic events affecting the probability of cohabitation. Instead, cohabitation correlates positively with having a large number of children, and parents more often live with their married daughters than with their married sons. Nonetheless, the extreme ethnic diversity of Indonesia makes any attempt at generalization difficult. Buttenheim and Nobles (2009) study marriage behavior in Indonesia from an ethnic lens. Depending on the ethnic group, a newly wed couple might adopt virilocal (living with the husband’s parents), uxorilocal (living with the wife’s parents), ambilocal (living with either or both spouses’ parents) or neolocal (forming a new household) practices. The length of coresidency and the conditions under which it ends also vary between ethnic groups.
That being said, on Indonesia’s largest island, Java, nuclear households seem to be the norm (Buttenheim and Nobles 2009), at least in the last decade. Kevane and Levine (2003) make use of the area-specific post-marriage residence patterns to examine whether virilocality correlates with low investment patterns in girls (since girls in these areas are moving off after marriage, parents may be less inclined to invest in them). They find that
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although virilocal regions have other norms unfavorable toward women, the women in these regions do not display any significant disadvantages in terms of education, height or weight. Witoelar (2006) studies home leave in Indonesia from the remaining household’s perspective and finds that household size and the maximum education of a member are important determinants of household division.
Hsin (2007) looks at the time allocation of children in Indonesia using time diary data.
She finds that girls of all birth ranks and all sibship sizes work in some kind of activity (market or household), and dedicate more than twice the amount of time to work relative to boys. Complementary qualitative evidence from focus group discussions in a rural village in Java suggests that parents want similar education for their children, and rarely substitute school for work. Thomas et al. (1999) compare Indonesian households before and after the economic crisis that hit the country in 1997-1998, showing that although a significant negative impact was felt throughout the wealth distribution, the largest increase in food consumption as a share of the budget was found in the poorest families.
Furthermore, the decline of health and education in consumption shares was particularly large in households with relatively more children in ages 10 to 14.
Finally, the ”missing daughters” problem prevalent in other regions of Asia does not seem to exist in Indonesia. Kevane and Levine (2000) document past and present gender favoritism in Indonesia, and contend, looking at birth spacing and nutrition allocations from 1940 to 1990, that there has been no son preference in Indonesia during this period.
They argue that there has been a slight gender difference in educational attainment and inheritance, but that the gaps have narrowed in recent times (and disappeared altogether for primary education). Furthermore, in their article on post-marriage residency, they present evidence that son preference does not exist in virilocal areas. Using the 2010 census, Guilmoto (2015) nuances these results, showing that in some regions, patterns of son preference do emerge.
4.2 The 1980 census data
I rely on a sample of the 1980 Indonesian census to investigate the relationship between educational outcomes and older siblings’ occupational status. A subsample of the census data, gathered every 10 years, is made available online through the IPUMS project hosted at the University of Minnesota. Furthermore, intercensal data is available for 1985, 1995, 2005. The subsample fraction is 5%, and consists of 7 234 577 records for
Table 15: Descriptive statistics, 1980 census survey sample
Full sample >14 years old. >17 years old
Age 13.3 17.84 20.3
Female 0.478 0.464 0.45
Married 0.04 0.10 0.17
Ever school 0.91 0.91 0.90
Currently in school 0.66 0.35 0.21
Years schooling 3.85 5.98 6.57
Employed* 0.49 0.55 0.58
Unemployed* 0.03 0.04 0.04
Inactive* 0.48 0.41 0.38
Days worked last week† 5.9 5.9 6.0
Hours worked last week† 37.3 38.6 40.1
Self-employed† 0.31 0.31 0.33
Unpaid family work† 0.38 0.35 0.31
Employee† 0.30 0.33 0.36
Idle‡ 0.64 0.57 0.54
Housework‡ 0.33 0.41 0.44
Years schooling older sibling 5.16 6.2 6.51
Age older sibling 17.1 21.1 23.4
Older sibling female 0.457 0.427 0.417
Older sibling married 0.12 0.24 0.31
Mean age difference 3.76 3.3 3.2
Sibship size 4.2 4.5 4.6
Older sibling in school 0.418 0.178 0.095
Older sibling activity
Employed* 0.57 0.63 0.64
Self-employed† 0.33 0.34 0.35
Employee† 0.31 0.35 0.38
Unpaid family work† 0.35 0.30 0.26
Second job† 0.08 0.08 0.08
Services sector† 0.18 0.24 0.30
Inactive* 0.40 0.34 0.32
Housework‡ 0.41 0.47 0.48
Idle‡ 0.57 0.51 0.49
Observations 1 061 779 368 049 165 855
Sample: 1 061 779 Individuals between 6 and 30 years old, with at least one older sibling (12-30 y.o.) living in the household. *: Of out-of-school individuals more than 10 y.o..
†: out of employed individuals;‡: out of inactive out-of-school individuals.
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the 1980 sample. While the strong point of the census data is its size, this comes with the drawback of a relatively modest number of questions in the questionnaire. Since the census and intercensal data are cross-sectional, any siblings out of the household are unaccounted for in my estimates, and the data does not provide any information on such out-of-household members. I therefore choose to use 1980 data, since the exogenous source of variation that I will exploit, the INPRES program of school construction, was implemented nationally from 1974 through 1978. I thus aim to keep the number of siblings lost to migration and establishment of independent households to a minimum.
The IPUMS subsample is composed by households who answered a longer question-naire, containing information on dwelling characteristics, local infrastructure and assets.
The individuals of those households answered an individual form with brief information on fertility, education, activity status, occupation, health and migration. No information on income or consumption was gathered. I restrict the sample used to children of the household head, from 6 to 30 years old and who have at least one older sibling in the same age range living in the household. This reduced sample amounts to 1 061 779 observations of sibling pairs. The choice of 30 was made to include as many sibling pairs as possible. However, in practice, children of the household head still living in the household at the age of 30 are relatively rare, as can be seen in the skewed age distribution in Table 30 (Appendix). The population of older siblings is not representative of the general population in the same age range, since it excludes all individuals who have moved away from their parents. Table 15 shows some descriptive statistics from the sample. The average age difference between siblings is 3.8 years, which is somewhat reassuring since this ensures that on average, sufficient time has run between births for children to be differently exposed to the school construction program. It also indicates rather low schooling levels in Indonesia in 1980. On average children over 18 years of age in 1980 have been to school 6.5 years, which corresponds to an elementary school level.
The sample of out-of-school younger siblings is roughly partitioned in half into inactive and employed individuals (Table 16). I consider as inactive those individuals aged 10 years or more who are out of school, and who are not working or looking for work40. They come in two main categories: those who declare doing housework (domestic chores) as their main occupation, and those who are inactive for other reasons, which I classify asidle. Remaining inactive persons belong to the category ”unable to work/disabled”,
40This thus corresponds to individuals who are NLFET—not in the labor force, nor in education or training.
Table 16: Composition of the sample of out-of-school children more than 10 years old
Employed Unemployed Inactive
Self-employed 49 787 Housework 52 437
Employees 49 567 Unable to work/disabled 5 109
Unpaid family workers 62 424 Idle 100 350
Unknown 914
Total 162 692 9 600 157 896
Source: 330 188 census observations of out-of-school individuals 10-30 years old.
which represents a small share of the population. The class of active individuals contains those who are 10 years or above, out of school, and either work or look for a job. Among workers, three categories (similar in size) are distinguished: employees, self-employed and family workers.