{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-04-14","version":"1"},"project_desc":{"authoring_entity":[{"name":"Jose Cuesta","affiliation":"World Bank","email":"jcuesta@worldbank.org"},{"name":"Natalia Pecorari","affiliation":"World Bank","email":"pecorarinatalia@gmail.com"}],"title_statement":{"title":"Reproducibility package for Female Labor Force Participation And Gendered Social Norms: A Machine Learning Analysis Of Egypt","idno":"RR_EGY_2026_626"},"data_statement":"All data sources are publicly available but not all are included in the reproducibility package.","software":[{"name":"Stata","version":"19.5 MP"},{"name":"Python","version":"3.11.7"}],"scripts":[{"title":"Reproducibility package for Female Labor Force Participation And Gendered Social Norms: A Machine Learning Analysis Of Egypt","date":"2026-04","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_EGY_2026_626","zip_package":"RR_EGY_2026_626.zip","dependencies":"Python dependencies are listed in the \"environment.txt\" file."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-04-14","abstract":"This paper addresses two gaps in the female labor force participation literature: the integrated analysis of individual, household, community, and national determinants, and the use of Machine Learning techniques to capture nonlinear dynamics. Using decision trees, we identify key drivers, thresholds, and sequences shaping women\u2019s labor participation in Egypt\u2014which remains below regional and global averages. Drawing on 2021\u201322 ArabBarometer data, we find that while gender norms matter, access to childcare is the most decisive factor. We conclude by outlining priorities for future research on the complex dynamics of female labor decision-making within and beyond Egypt.","geographic_units":[{"name":"Egypt","code":"EGY"}],"keywords":[{"name":"Female Labor Force Participation"},{"name":"Social Norms"},{"name":"Decision Trees"},{"name":"Egypt"}],"topics":[{"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":" J20","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"General","parent_id":"J2"},{"id":" D91","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making","parent_id":"D9"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Female Labor Force Participation And Gendered Social Norms: A Machine Learning Analysis Of Egypt"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time: ~ 5 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":"Modified BSD3","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"contacts":[{"name":"Jose Cuesta","affiliation":"World Bank","email":"jcuesta@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: Intel(R) Core(TM) i5-1145G7 CPU @ 2.60GHz\n\u2022 Memory available: 32.0 GB","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. \n\n2. **Run the Package:**\n     - Update the working directory in line 7 of the do-file \"main\", and run it.\n     - Restore the environment in environment.txt, and run the python scripts \"Descriptives_table\" and \"decision tree\".\nSince the original data cannot be redistributed, the package includes the outputs produced by the authors, which can be used to review the results presented in the paper.","datasets":[{"name":"Arab Barometer Wave VII","license_uri":"https:\/\/www.arabbarometer.org\/policies\/","uri":"https:\/\/www.arabbarometer.org\/surveys\/arab-barometer-wave-vii\/#data_sets","citation":"Arab Barometer. 2022. \"Arab Barometer Wave VII [dataset],\" Retrieved from https:\/\/www.arabbarometer.org\/surveys\/arab-barometer-wave-vii\/, March 2025.","access_type":"Data is publicly available but does not allow redistribution and it is not included in the reproducibility package.","note":"Arab Barometer\u2019s seventh wave is the largest publicly available survey that captures the opinions and attitudes of citizens across the Middle East and North Africa since the onset of COVID. \nThe survey took place between October 2021 and July 2022.Download the dataset using the link under Data URL and place it in the right folder. \nFiles: Data cleaning\/Data\/AB7_ENG_Release_Version6.dta\n"}]},"datacite":{"creators":[{"givenName":"Jose","familyName":"Cuesta","nameType":"Personal","affiliation":[{"name":"World Bank"}]},{"givenName":"Natalia","familyName":"Pecorari","nameType":"Personal","affiliation":[{"name":"World Bank"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Female Labor Force Participation And Gendered Social Norms: A Machine Learning Analysis Of Egypt"},{"title":"RR_EGY_2026_626","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_EGY_2026_626","language":"en"},"tags":[{"tag":"Accessible Data"},{"tag":"DOI"},{"tag":"Open Code"}],"schematype":"script"}