Fostering human capital development through school feeding: Evidence from Malawi

Schools involved in the home-grown school feeding program procure produce from local smallholder farmers’ organizations and store it; volunteers from local communities take turns in preparing the food every day. Children receive a warm daily meal on the school premises before school starts. Meals are prepared following predefined recipes to ensure they are healthy and nutritious.

2023-09-10

2025-07-01

First Stage Outcomes: child dietary diversity, child food insecurity experience scale
Second Stage Outcomes: child mental health/psychological wellbeing (life satisfaction, stress, depression, agency), child physical health (health status, nutritional status), child school attendance, child school progression (dropout, repetition, new enrollment), learning (reading skills, numeracy and mathematics skills), child cognitive ability (attention span, verbal working memory, fluid intelligence)

We leverage the randomized expansion of the national school feeding program in Malawi to study the impacts of a negative shock on the cost of attending school; we aim to understand if the program is effective in bringing children to the classroom and fostering better health and education, especially during the lean season when child labor has a higher opportunity-cost.
We randomize the provision of school feeding to eligible schools and compare the outcomes of children enrolled in schools where a school feeding program is implemented to the outcomes of children enrolled in schools where a school feeding program is not implemented. Out of the 88 schools in the sample, we assign 44 schools to the treatment group and 44 schools to the control group.

Not available

Randomization done in office by a computer

Primary Schools (Clusters)

Yes

88 schools

1760 children

No school feeding: 44 schools, 880 children
School feeding: 44 schools, 880 children

We base our power calculations on five measures: household food consumption scores (FCS, mean 45.5 and standard deviation 17.39), household food expenditures (mean 8.46 and standard deviation 9.55), an indicator for whether the household is worried about lack of food (mean 0.61 and standard deviation 0.49), weight-for-age (mean -1.43 and standard deviation 1.64), and height-for-age (mean -0.64 and standard deviation 1.22). Assuming 44 schools per treatment arm, 20 children per school, one follow-up observation, and power of the test of 80%, yields a minimum detectable effect (MDE) of 0.19 standard deviations for FCS, food expenditures, weight-for-age, and height-for-age, and of 0.20 standard deviations for the worry indicator. With two follow-up measurements and assuming a correlation of 0.2 between follow-up measurements, our experiment is powered to detect an effect of 0.14 standard deviations for FCS and food expenditures, 0.15 for weight-for-age and height-for-age, and 0.16 for the worry indicator. Increasing the correlation between follow up rounds to 0.5 yields an MDE of 0.16 for all indicators excluding weight-for-age, whose MDE is 0.17 standard deviations. Household FCS, food expenditure, and the worry indicator come from the 2015-2016 wave of the Malawi Living Standard Measurement Survey (LSMS). Weight-for-age and height-for-age data come from the 2019 wave of the Malawi Demographic and Health survey (DHS).