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Investment in human capital is associated with higher economic and non-economic gains in the future for the individual, the household, and at the aggregate level for the economy. In my dissertation, I examine three different policy oriented questions that are relevant for improving health and education, two important dimensions of human capital. First, I characterize the socioeconomic factors that determine health status among children. Second, I extend the above question to capture the extent to which poor nutrition during childhood affects an individual's future physical well-being. The association between nutritional deficiency at young ages and subsequent health status captures the extent to which children can recover from some of the deficits in health status caused by early malnourishment. To address these questions, empirical evidence is drawn using observations on children between ages 3 and 59 months in 1993, who are followed through the 1997 and 2000 waves of the Indonesian Family Life Survey (IFLS). The results suggest that (1) it is parent's genetic endowments, household income, and community infrastructure availability that is important for improving children's health outcomes. (2) Poor nutrition at young ages will cause some, but not severe retardation in the growth of future height indicating partial recovery from chronic malnutrition. Finally, I also outline the socioeconomic determinants of schooling enrollment and relative grade attainments among primary school age children. To address this question, I use data from the 1994, 1999, and 2004 waves of the Ethiopian Rural Household survey (ERHS). I find that it is household income that has the most important role in explaining schooling outcomes. The results also bring out the impact of past schooling outcome in explaining current schooling attainments. There exists a strong positive association between past schooling outcomes and current schooling outcomes. The empirical methodology followed in this dissertation address a number of econometric concerns such as measurement error, omitted variables, attrition, sample selection, endogeneity, and instrument relevance.
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