How Poverty Alleviation Improves Girls’ School Completion in Rural China? The Role of Health

Description

This repository contains the replication package for the paper “How Poverty Alleviation Improves Girls’ School Completion in Rural China? The Role of Health”, accepted for publication in Economic Modelling. The package includes all analysis code, documentation, and publicly shareable materials necessary to support replication and verification of the empirical analysis. Some components of the analysis rely on restricted-access community-level data from the China Health and Nutrition Survey (CHNS), which cannot be publicly redistributed due to data-use agreements. All empirical results reported in the paper are generated using the original restricted-access CHNS data. To facilitate transparency and verification, the replication package includes the full original code used in the paper, along with synthetic placeholders for restricted variables that allow users to execute the complete code pipeline. Researchers with authorized access to the CHNS community-level data can fully reproduce all reported results using the provided code. This approach complies with the journal’s reproducibility policy while respecting data confidentiality requirements.

Steps to reproduce

Replication Instructions 1.Download and extract the replication package into a local directory on your computer. 2.Open Stata and set the working directory to the extracted folder using the cd command (e.g., cd "C:\Your\Directory\Path"). 3.Run the provided do-files in the following order to replicate the results: oMain_code.do for all tables and figures in the main text. oAppendix_code.do for all tables and figures in the appendix. Ensure that all datasets and code files are stored in the same directory. The scripts are designed to run without modification under this structure. Data Availability All data files used here are derived from the China Health and Nutrition Survey (CHNS), which is publicly available at: https://www.cpc.unc.edu/projects/china/data/ Preprocessed datasets are included for convenience. Users must comply with the original data licensing terms.

Institutions

• Central University of Finance and Economics

  Beijing, Beijing
• Chinese Academy of Social Sciences

  Beijing, Chaoyang District

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