Elsevier

Journal of Public Economics

Volume 81, Issue 3, September 2001, Pages 345-368
Journal of Public Economics

Early childhood nutrition and academic achievement: a longitudinal analysis

https://doi.org/10.1016/S0047-2727(00)00118-3Get rights and content

Abstract

Many policymakers propose early childhood nutrition programs as a way to increase students’ academic achievement. This paper investigates the nutrition–learning nexus using a unique longitudinal data set that follows a large sample of Filipino children from birth until the end of their primary education. We find that better nourished children perform significantly better in school, partly because they enter school earlier and thus have more time to learn but mostly because of greater learning productivity per year of schooling. Our cost–benefit analysis suggests that a dollar invested in an early childhood nutrition program in a developing country could potentially return at least three dollars worth of gains in academic achievement, and perhaps much more.

Introduction

In recent years, policy-makers have increasingly promoted early childhood nutrition programs as a way to raise living standards in developing countries (World Bank, 1993, Young, 1996), as well as among the US poor (GAO, 1992). Proponents of such programs argue that improved diet, particularly in the crucial first years of life, enhances intellectual development and, ultimately, academic success (see Brown and Pollitt, 1996). Their view is that, in addition to having direct health benefits, early childhood nutrition programs and broader food security initiatives could also be an instrument of education policy. Yet, the evidence in support of this view is surprisingly sparse (Behrman, 1996).

Behind this lack of evidence is a paucity of good data, specifically data that allow one to address the problem of spurious correlation between nutritional status and academic achievement (conditional on other academic inputs). Such correlation could arise from parental behavior; for example, parental allocations of nutritional inputs may respond to unobserved variation in learning efficiency (e.g., child ability or motivation) both across and within households. In principle, the problem could be addressed using data generated from an experiment in which treatment and control groups of infants are randomly selected from a malnourished population. The treatment group is provided an improved diet during the first few years of life and a decade or so later both groups are given school achievement tests. One could then estimate the relationship between academic achievement and indicators of early childhood nutrition, such as height, using treatment status as an instrumental variable for the latter.1 But because of the ethical and practical issues raised by this ideal experiment, it has yet to be carried out on a large scale and perhaps never will be.2 Approaching this ideal experiment, at least in terms of length of follow-up, is the INCAP study in Guatemala (Pollitt et al., 1993), in which significantly positive effects of early childhood supplementary feeding on cognitive skills in adolescence are found. However, the experiment has two drawbacks: First, it compares just two distinct nutritional interventions, each in only two villages, without a pure control group. Second, the nutritional supplements were provided in a central feeding station, so that individual participation was voluntary, not randomized.

In this paper, we estimate the impact of nutrition on learning using nonexperimental data collected in Cebu, Philippines over a period of 12 years. A large sample of children was followed from shortly before their birth and up through primary school, providing information on early childhood nutrition and subsequent school performance, as measured by achievement tests. Achievement test scores and other information are also available for the younger siblings of the original children. Our study is thus the first to combine longitudinal information on children with data on their siblings to investigate the nutrition–learning nexus.

Though we will argue shortly that no nonexperimental study can hope to replicate the ideal experiment described above, we believe that our structural production function analysis makes considerable progress in sorting out the causal relationship between nutrition and learning. In particular, we find that better early childhood nutrition raises academic achievement. Our analysis also illuminates the pathways through which nutritional status in the first years of life affects learning in a developing country. Part of the advantage that well-nourished children enjoy arises from the fact that they enter school earlier and thus have more time to learn. The rest of their advantage stems from greater learning productivity per year of schooling. We find little evidence that early nutritional status influences learning effort in the form of school attendance, time spent on homework, and so forth.

The remainder of this paper is organized as follows. We lay out a framework for estimation in Section 2 and describe our data in Section 3. Section 4 presents the results of our estimation and in Section 5 we use these results in a policy evaluation. We summarize our findings in Section 6.

Section snippets

Empirical strategy

Our analysis focuses on the achievement production function, which relates early childhood nutrition and other academic inputs to a child’s scholastic output as measured by a score on an achievement test. The academic input on which we focus is the nutritional history of the child in the early years of life. However, as a practical matter, measuring cumulative nutrition inputs is extremely difficult, and a simple alternative is to use the child’s height-for-age as a summary statistic for the

The Cebu longitudinal health and nutrition survey

Our data come from the Cebu Longitudinal Health and Nutrition Survey (CLHNS), which was carried out in the Metropolitan Cebu area on the island of Cebu, Philippines.12 Metro Cebu includes Cebu City, the second largest city in the Philippines, and several

Achievement production function

The central results of this paper are presented in Table 2. Besides the sex and height-for-age Z-score of the child at the time of school enrollment, the achievement production function includes the age of enrollment, time spent in school, and time not in school; these variables sum to give current age, which is potential time in school.14

Policy implications of findings

It remains for us to assess the economic significance of the nutrition–learning nexus. It is one thing to say that better nutrition significantly improves school performance, but quite another thing to say that this education effect should seriously enter into the cost–benefit calculus of nutrition interventions, let alone wholly justify such interventions as some nutritionists have argued. In this section, we use our production function results to estimate the achievement benefits of a

Conclusion

In this paper, we have studied the relationship between early childhood nutrition and subsequent academic achievement using a unique longitudinal data set, one that follows a large sample of children in a low income country from birth to the end of their primary school education. Several important empirical findings emerge from this analysis. First, heterogeneity in learning endowments, home environment, or parental “tastes” for that matter, cannot fully explain why malnourished children

Acknowledgements

Financial support for this project was provided by USAID, the Asian Development Bank, and the World Bank (RPO #679-57). We wish to thank the Office of Population Studies at the University of San Carlos in Cebu, Philippines and the Carolina Population Center at the University of North Carolina for their collaboration in the collection and analysis of the data. Azot Derecho and Nauman Ilias provided capable research assistance. We are also grateful to Harold Alderman, Andrew Foster, Michael

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