EARLY-CHILDHOOD NUTRITION, SCHOOLING, AND SIBLING INEQUALITY 73
In the analysis, I use the information on nurses, community healthcare workers, and traditional birth attendants since a preliminary examination sug- gested that they are particularly important (that is, statistically significant). Since I also include age fixed effects when estimating schooling equations in the household fixed-effect model, the average cohort effects are controlled. I also use the weight-for-age z-score as an instrument to eliminate mea- surement errors in the height z-score. Results will be compared between the two different sets of instruments. The first-stage regression results are shown in Table 4.1, where the identi- fying instruments are jointly significant. Interestingly, the result (controlling for age fixed effects) implies that in communities with some nurses in 1993, younger children (those who were born more recently) have gained height relative to older children. On the other hand, older children have gained height (relative to younger children) in communities which had community healthcare workers and traditional birth attendants in 1993. The difference may imply some endogeneity of the initial allocation of healthcare person- nel. However, the fact that I examine intrahousehold variations in child health outcome makes this issue less problematic. On the other hand, the weight-for-age z-score has a significant positive effect on the height-for-age z-score.
Data Sources
The analysis requires information from different points in time for the same individuals. In this chapter, I use data from the KIDS of 1993, 1998, and 2004 (see Chapter 1). The sample was population self-weighted in the first round in 1993, based on the 1991 population census, and enumeration-based weights were introduced in 1998. The 1993 and 1998 surveys provide information on anthropometric measures and health outcomes of children, enabling us to construct age-standardized z-scores for height. The 2004 survey provides some detailed information on schooling decisions and outcomes. Our analysis combines the nutritional status of pre-primary-school-age children in 1998 and 1993 and their schooling inputs and outcomes until 2004.10 In the principal analysis, I use as schooling variables (1) age schooling started, (2) grade completed (conditional on current age), (3) number of grades repeated, and (4) mathematics test results. For age schooling started, the 2004 survey asks for the calendar year in which the child started primary school.
10 Constructing individual-level panel data from the 1998 and 2004 surveys, we have screened out observations recorded in multiple households (multiple memberships). The details of this procedure are available from the author.
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