{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-07-15","version":"1"},"project_desc":{"authoring_entity":[{"name":"Hardi Ahmed","affiliation":"World Bank","email":"hahmed13@worldbank.org"},{"name":"Damien de Walque","affiliation":"World Bank","email":"ddewalque@worldbank.org"},{"name":"Carolina Lopez","affiliation":"World Bank","email":"carolina_lopez@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Convergence or Reversal? The Evolution of the Gender Gap in Education in Sub-Saharan Africa","idno":"RR_SSA_2026_693"},"data_statement":"Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file. (Limited-access\/Restricted Data)","software":[{"name":"R","version":"4.5.3"},{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Convergence or Reversal? The Evolution of the Gender Gap in Education in Sub-Saharan Africa","date":"2026-07","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_SSA_2026_693","zip_package":"RR_SSA_2026_693.zip","dependencies":"R dependencies are listed in the file renv.lock. Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-07-15","abstract":"Despite the rapid expansion of education in Sub-Saharan Africa, the evolution of gender gaps between generations remains poorly documented at the regional scale. Using harmonized DHS and MICS data from 35 countries covering approximately 736,000 individuals, complemented by PASEC test scores for 14 francophone countries, this study traces gender differences in educational attainment and learning outcomes by birth cohort. Gender gaps in attainment narrow substantially across cohorts, with the female disadvantage falling from about 13-15 percentage points in primary and secondary attendance and 1.9 years of schooling among those born in the 1970s to near zero and statistically insignificant for those born after 1999. Gender gaps in learning outcomes vary widely across countries, with no uniform direction of disadvantage in either reading or mathematics. Country-level analyses show that females exceed males in secondary attendance and years of education in most countries among those born after 1999, and that gender gaps in learning outcomes are similarly heterogeneous across countries. Convergence in some contexts coincides with stagnation or deterioration in boys' secondary attendance rather than uniform gains for girls. Aggregate trends mask pronounced heterogeneity, with larger gaps persisting among rural, poorer, and Muslim populations.","geographic_units":[{"name":"Sub-Saharan Africa","code":"SSA"}],"keywords":[{"name":"Gender Gaps"},{"name":"Education"},{"name":"Cohort Analysis"},{"name":"Sub-Saharan Africa"}],"topics":[{"id":"I21","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Analysis of Education","parent_id":"I2"},{"id":" J16","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Economics of Gender \u2022 Non-labor Discrimination","parent_id":"J1"},{"id":" O1","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Economic Development","parent_id":"O"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Convergence or Reversal? The Evolution of the Gender Gap in Education in Sub-Saharan Africa"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time: ~ 55 minutes","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"Hardi Ahmed","affiliation":"World Bank","email":"hahmed13@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Demographic and Health Surveys (DHS)","note":"Data accessed January 2024\u2013February 2026. IR (Individual Recode, women aged 15\u201349) and MR (Men's Recode) files in Stata .DTA format for 27 countries, preserving the original DHS subfolder structure (e.g., data\/datain\/DHSMICS\/dhs\/benin\/benin_dhs_2017\/BJIR71DT\/BJIR71FL.DTA). Countries covered: Angola, Benin, Burkina Faso, Burundi, Cameroon, C\u00f4te d'Ivoire, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Uganda, Zambia, Zimbabwe. To access, register at https:\/\/dhsprogram.com and submit a data use request selecting each country and the most recent available survey round. All the datasets used are listed in data_hash_report.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"DHS Program Terms of Use","license_uri":"https:\/\/dhsprogram.com\/Data\/terms-of-use.cfm","uri":"https:\/\/dhsprogram.com","citation":"ICF. Various years. \"Demographic and Health Surveys\" [dataset]. Rockville, Maryland, USA. https:\/\/dhsprogram.com. Accessed January 2024\u2013February 2026."},{"name":"Multiple Indicator Cluster Surveys (MICS6)","note":"Data accessed June 21, 2026. MICS6 SPSS (.sav) datasets for 8 countries, located under data\/datain\/DHSMICS\/mics\/MICS\/, one subfolder per country preserving the original UNICEF folder names. Countries covered: Central African Republic, Chad, Comoros, Congo Dem. Rep., Eswatini, Guinea-Bissau, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Togo. These countries are used because no later DHS survey is available for them. To access, register at https:\/\/mics.unicef.org and download the MICS6 dataset package for each country. Note: MICS data are provided in SPSS format (.sav); run Code\/Stata\/DataPrep\/DHSMICS\/mics\/SPSSStata.do once to convert them to .dta format before running the main pipeline.  All the datasets used are listed in data_hash_report.","access_type":"Data is publicly available but does not allow redistribution and is not included in the reproducibility package.","license":"UNICEF Terms of Use","license_uri":"https:\/\/www.unicef.org\/legal","uri":"https:\/\/mics.unicef.org","citation":"UNICEF. Various years. \"Multiple Indicator Cluster Surveys (MICS6)\" [dataset]. New York, USA. https:\/\/mics.unicef.org. Accessed June 2026."},{"name":"PASEC Microdata (2014 and 2019)","note":"Data accessed March 9, 2026. Four files covering two waves and two grade levels: PASEC2014_GRADE2.dta, PASEC2014_GRADE6.dta, PASEC2019_GRADE2.dta, PASEC2019_GRADE6.dta. Located in data\/datain\/Learning\/Pasec\/. Countries covered (14 Francophone SSA): Benin, Burkina Faso, Burundi, Cameroon, Congo, C\u00f4te d'Ivoire, Gabon, Guinea, Madagascar, Niger, Congo Dem. Rep., Senegal, Chad, Togo. Data are restricted and available on request; contact CONFEMEN directly at https:\/\/www.pasec.confemen.org.","access_type":"Data access was granted directly to the study authors by the data owners. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License (data sharing agreement with CONFEMEN)","license_uri":"https:\/\/www.pasec.confemen.org","uri":"https:\/\/www.pasec.confemen.org","citation":"CONFEMEN. Various years. \"PASEC: Programme d'Analyse des Syst\u00e8mes \u00c9ducatifs de la CONFEMEN\" [dataset]. Dakar, Senegal. https:\/\/www.pasec.confemen.org. Accessed March 2026."},{"name":"Harmonized Learning Outcomes (HLO) Database","note":"Data accessed March 8, 2026. Used for learning outcome analysis for all non-PASEC countries (27 countries after dropping the 14 PASEC countries). File locations: data\/datain\/Learning\/WB\/hlo_database.xlsx (raw database); data\/datain\/Learning\/WB\/learning.dta (Stata version used by the pipeline).","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/datacatalog.worldbank.org\/int\/public-licenses?fragment=cc","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0038001\/Harmonized-Learning-Outcomes--HLO--Database","citation":"Angrist, N., Djankov, S., Goldberg, P., and Patrinos, H. 2021. \"Harmonized Learning Outcomes (HLO) Database\" [dataset]. World Bank. https:\/\/datacatalog.worldbank.org. Accessed March 2026."},{"name":"Africa Boundaries Shapefile","note":"Data accessed January 28, 2021. Required by all R map scripts. File locations: maps\/Africa_Boundaries-shp\/Africa_Boundaries.shp and associated .cpg, .dbf, .prj, .shx files.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Public","license_uri":"https:\/\/hub.arcgis.com\/datasets\/geoduck::africa-boundaries\/about","uri":"https:\/\/hub.arcgis.com\/datasets\/geoduck::africa-boundaries\/about","citation":"Esri. 2021. \"Africa Boundaries\" [dataset]. ArcGIS Hub. https:\/\/hub.arcgis.com\/datasets\/geoduck::africa-boundaries\/about. Accessed January 2021."},{"note":"Data accessed January\u2013February 2026. Two sets of indicators used: (1) Population, total (SP.POP.TOTL), accessed February 8, 2026. File locations: data\/datain\/Other\/population.dta; data\/datain\/Other\/Country_ID.xlsx; data\/datain\/Learning\/WB\/75ef169b-ed2e-4a3d-96fa-85d60cd6e9b5_Data.csv; data\/datain\/Learning\/WB\/75ef169b-ed2e-4a3d-96fa-85d60cd6e9b5_Series - Metadata.csv. (2) Education duration indicators (SE.PRM.DURS, SE.SEC.DURS, SE.SEC.DURS.LO), accessed January 27, 2026, used to define primary and secondary cycle lengths by country in MICS. File location: data\/datain\/DHSMICS\/mics\/WBEDUC\/WBEDUCDATA.dta.\n","name":"World Development Indicators","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","uri":"https:\/\/databank.worldbank.org\/source\/world-development-indicators","citation":"World Bank. 2026. \"World Development Indicators\" [dataset]. https:\/\/databank.worldbank.org\/source\/world-development-indicators. Accessed January\u2013February 2026"}],"reproduction_instructions":"To reproduce the findings in this paper, a replicator must:\n1. **Secure Access to Data:** Access the datasets not included in the package. See the Datasets section for more details.\n2. **Run the Package:**\n  - Update the working directory in line 39-40 of the do-file `Master.do`, and run it.\n  - Openthe R project \"GenderGapReplication.Rproj\", and restore the environment by running renv::restore() and following the prompts.\n  - Open `Master.R`, and runthe code.\n\nSince not all the data is included, the package includes the results produced by replicators. These files can be used to review the results presented in the paper.","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz, 2900 Mhz, 4 Core(s), 4 Logical Processor(s)\n\u2022 Memory available: 16.0 GB\n"},"datacite":{"creators":[{"givenName":"Hardi","familyName":"Ahmed","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Damien de","familyName":"Walque","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Carolina","familyName":"Lopez","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Convergence or Reversal? The Evolution of the Gender Gap in Education in Sub-Saharan Africa"},{"title":"RR_SSA_2026_693","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_SSA_2026_693","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}