70 CHAPTER 4


height-for-age z-score) start school earlier, complete more grades, and repeat fewer grades. The analysis also identifies some outlying observations among taller children (who make up less than 5 percent of the sample) that show a negative effect of the height z-score on schooling outcomes. However, it also remains highly possible that ages for these children in 1998 were under- reported, so their height z-scores were overestimated. I also find that, although better nutrition and health status in early childhood improve primary school outcomes, this positive effect diminishes over time as children age. The smaller effect observed among older siblings may also reflect the fact that the effect of nutrition on height is large among children aged less than 3 (in 1998), and height may rebound afterward.6


Second, the analysis of mathematics test results, using the sample of chil- dren aged 7–9, shows that health capital, measured by height in early child- hood, has a significantly positive effect, implying that early-childhood nutrition affects learning performance at the early stage of transition to schooling.


Empirical Strategy


This section describes the empirical framework used to assess the effects of early-childhood health capital on schooling decisions and outcomes at a subsequent stage. The schooling equation is


qijt = α + β1hijt–1 Σβ2


a Σβ1 H Hhijt–1I(hijt–1 ∈ H) + Σβ1 a aI(aijt = a) + xijtγ + µi + φj + νijt,


where i, j, and t denote household, child, and time, respectively, and qijt is schooling inputs or outcomes; hijt–1 is health capital, which is measured by the height-for-age z-score (formed at t – 1); aijt is the age of the child; xijt is a set of control variables; µi is a household-specific fixed effect; φj is child-specific fixed unobservables; and νijt is an error term.


First, it is important to control the heterogeneity that arises from the cur- rent ages. For example, cumulative years of grades repeated increases (but weakly) as children spend more time in school, that is, as their age increases. The score on the numerical tests also changes by age (and grade completed). In the analysis that follows, I assume that age structure in the sample of chil-


6 Children aged 0–5 in the 1993 sample entered school during the transition period 1993–98, while children aged 1–5 in the 1998 sample entered school during the more stable period 1998–2004. This latter period was after basic school reforms had been introduced—that is, the South African School Act in 1996 and the National Norms and Standards for School Funding in 1998—though their implementation took longer. This change might have affected child schooling behavior and parents’ decisions.


ahijt–1I(aijt = a) +


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