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What Matters in Child Health: An Instrumental Variable Analysis

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Abstract

This paper studies factors that affect health and the nutritional status of children under the age of five. It attempts to identify the impact of socioeconomic factors such as household characteristics, parental education, community-level infrastructure and health knowledge on the health (measured by height and weight) of children. The study’s theoretical framework is based on the household production model and the instrumental variable technique has been implemented for estimation. Household income, illness from diarrhea and vitamin A supplements for children are treated as endogenous variables and have been instrumented. The paper uses data from Pakistan—Multiple Indicator Cluster Survey (MICS) for 2007/08 for Punjab which is a household level dataset gathered by the Punjab Bureau of Statistics. The results suggest that maternal education, health knowledge and household characteristics are important determinants of child health, among other significant indicators. The channel through which maternal education affects child health is considered to be better nurturing and healthcare since the income effect of education is controlled by household income. Household characteristics—income, the number of household members, ownership of durables—prove to significantly affect the health of children in that household. Another important finding of this paper is that female children under five have better height and weight z-scores than their male counterparts. This finding rejects the common presumption of gender bias at the household level in South Asia in early years of life.

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Notes

  1. These goals are to (i) reduce child mortality, (ii) improve mothers’ health, (iii) combat disease, and (iv) eradicate hunger.

  2. This cluster mean value is exclusive of the household being estimated, which is why it is also known as a “nonself” cluster mean.

  3. We use the z-score values for height-for-age and weight-for-age. Children’s height and weight are standardized according to the following formula: \( Z=\left( {x-\mu } \right)/\sigma \), where x is the raw score and μ and σ are the mean and standard deviation obtained from the WHO reference population, respectively (WHO 2010).

  4. According to the WHO z-scores technique, z-scores that fall within an improbable range of standard deviations are flagged and dropped from the analysis. The flagged ranges are HAZ < −6 and HAZ > 6, and WAZ < −6 and WAZ > 5.

  5. Their endogenous variables are: (i) the number of days a child has been ill with diarrhea in the last 2 weeks, (ii) the number of days a child has had any other illness in the last 2 weeks, (iii) whether a child was exclusively breastfed, (iv) whether a child has been vaccinated, and (v) whether a child was born in a hospital

  6. The DWH test determines the endogeneity of the suspected variable and, therefore, establishes whether or not an instrumental variable analysis is necessary. The Hansen J-test of over-identification is relevant whenever an endogenous variable is over-identified, i.e., when the number instruments is greater than the number of endogenous variables. The J-test determines if the instruments are correlated with the structural equation’s residuals, in which case the instruments become invalid (Wooldridge 2002).

  7. Primary level = grades 1–5, middle level = grades 6–8, secondary = grades 9–10, higher = grades 11–12, and tertiary = above grade 12.

  8. About 97 % of the household heads are males. However, there is sufficient variation in the level of education across the household heads, see Table 2.

  9. The wealth index comprises the following variables: Number of rooms used for sleeping; ownership of bicycle, motorcycle/scooter, car/truck, or animal-drawn cart; household with finished roof and/or walls; and type of fuel used for cooking.

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Authors and Affiliations

  1. Center for Research in Economics and Business (CREB), Lahore School of Economics, Main Campus: Intersection Main Boulevard, Phase VI DHA and Burki Road, Burki, 53200, Lahore, Pakistan

    Uzma Afzal

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  1. Uzma Afzal
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Correspondence to Uzma Afzal.

Appendix

Appendix

Table 4 Determinants of child health: First-stage instrument equations
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Table 5 Parsimonious model of determinants of child health: Second-stage results
Full size table
Table 6 Parsimonious model of determinants of child health: First-stage instrument equations
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Afzal, U. What Matters in Child Health: An Instrumental Variable Analysis. Child Ind Res 6, 673–693 (2013). https://doi.org/10.1007/s12187-013-9186-6

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