The persistent effects of school meals on multidimensional human capital: Evidence from rural China
Description
Research Hypothesis This study investigates whether access to school meals has persistent effects on children’s multidimensional human capital in rural China. The central hypothesis is that early exposure to a school feeding program enhances children’s physical health, cognitive and non-cognitive abilities in the long term. Data Description and Collection The dataset underlying this study is constructed from the 2018 China Family Panel Studies (CFPS), a nationally representative, longitudinal survey led by Peking University. The CFPS provides rich individual-, family-, and community-level data on education, health, employment, and demographics. Data Interpretation and Use The figures and tables presented in the paper summarize descriptive statistics, regression results, robustness checks, and heterogeneity analyses. This data included all code with figures and tables.
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Steps to reproduce
1. Data Source The primary data source is the 2018 China Family Panel Studies (CFPS), conducted by the Institute of Social Science Survey at Peking University. The CFPS datasets are accessible upon application via https://www.isss.pku.edu.cn/cfps/. 2. Sample Construction We restricted the sample to rural individuals aged 17–30 years in 2018 who were of school age (6–15 years) during the rollout of the Nutrition Improvement Program for Rural Compulsory Education Students (launched in 2011). Individuals were classified into the treatment group if they were exposed to the school feeding program during their compulsory schooling years based on their age and county of residence. The control group includes slightly older cohorts who were not exposed. 3. Variable Construction Treatment variable: Constructed based on individual age and county-level implementation timing of the program. Outcome variables: Health: Self-rated health, BMI, negative emotions,smoking,drinking Education and Cognitive ability: Years of schooling, completion of junior or high school,Word and math test scores Non-cognitive ability: Big Five personality traits 4. Empirical Strategy A difference-in-differences (DID) design was used, leveraging the staggered rollout of the program across counties and time. 5. Software and Tools Stata 17 was used for all data cleaning, variable construction, descriptive statistics, and regression analyses. 6. Reproducibility Stata .do files for data analysis
Institutions
- Zhejiang Gongshang UniversityZhejiang, Hangzhou
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Funders
- Zhejiang Provincial Philosophy and Social Sciences Planning ProjectGrant ID: 24NDJC138YB, 24ZJQN033Y
- National Social Science Fund of ChinaGrant ID: 24BJL059
- Zhejiang Provincial Natural Science Foundation of ChinaGrant ID: LMS25G030002
- Fundamental Research Funds for the Provincial Universities of ZhejiangGrant ID: 2024ZDPY02; 2024ZDPY03
- Tsinghua Rural Studies PhD ScholarshipGrant ID: 202324