{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-12-18","version":"1"},"project_desc":{"authoring_entity":[{"name":"Mohammad Amin","affiliation":"World Bank","email":"mamin@worldbank.org"},{"name":"Nesma Ali","affiliation":"World Bank","email":"nali4@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Productivity Gap Between Women- And Men-Run Private Hotels In Georgia: A Dea Based Meta Frontier Analysis","idno":"RR_GEO_2025_507"},"data_statement":"All datasets are limited-access and not included in the reproducibility package.","software":[{"name":"Stata","version":"18.5 MP"}],"scripts":[{"title":"Reproducibility package for Productivity Gap Between Women- And Men-Run Private Hotels In Georgia: A Dea Based Meta Frontier Analysis","date":"2025-12","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_GEO_2025_507","zip_package":"RR_GEO_2025_507.zip","dependencies":"Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2025-12-18","abstract":"The paper makes an initial attempt to account for differences in the technologies used by women- and men-run businesses, that is, technological \u201cheterogeneity\u201d, to better understand productivity differences between the two groups. We do so by applying meta frontier analysis to the efficiency of private hotels in Georgia estimated using data envelopment analysis (DEA) methodology. The exercise allows us to distinguish between productivity differences conditional on the available technology to each group (technical efficiency) and due to differences in the available technology (technology gap). We show that gender-based differences in technical efficiency and technology gap are very different in their direction, size, and distribution across low vs. high levels of efficiency. For example, women-run hotels outperform men-run hotels in technical efficiency by 21 percentage points. However, this superior performance is almost fully countered by the inferior technology used by women due to the prevailing socio-cultural and economic environment. We also uncover that the impact of technology gap in widening the productivity gap is much stronger at low levels of efficiency than at higher levels (the \u201csticky floors\u201d effect). No such evidence is found for technical efficiency or overall efficiency. Thus, the existing literature, which assumes technological \u201chomogeneity\u201d, provides at best an incomplete picture of the true nature of gender-based productivity gaps and at worst, a misleading one. Our main result survives endogeneity checks based on propensity score matching and is robust to several measures of productivity and outlier checks. Policy implications of the findings are discussed.","geographic_units":[{"name":"Georgia","code":"GEO"}],"keywords":[{"name":"Meta Frontier Analysis"},{"name":"Gender Productivity Gaps"},{"name":"Data Envelopment Analysis"},{"name":"Hotels"}],"topics":[{"id":"C13","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Estimation: General","parent_id":"C1"},{"id":" C14","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Semiparametric and Nonparametric Methods: General","parent_id":"C1"},{"id":" D24","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Production \u2022 Cost \u2022 Capital \u2022 Capital, Total Factor, and Multifactor Productivity \u2022 Capacity","parent_id":"D2"},{"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":" L83","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Sports \u2022 Gambling \u2022 Restaurants \u2022 Recreation \u2022 Tourism","parent_id":"L8"},{"id":" L89","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Other","parent_id":"L8"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Productivity Gap Between Women- And Men-Run Private Hotels In Georgia: A Dea Based Meta Frontier Analysis"}],"language":[{"name":"English","code":"EN"}],"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":"Mohammad Amin","affiliation":"World Bank","email":"mamin@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"World Bank Enterprise Surveys (WBES)","uri":"https:\/\/www.enterprisesurveys.org\/en\/enterprisesurveys","note":"Access date: April 2025.\nData access instructions: Access the Enterprise Surveys website and select Download Datasets. Log in using your credentials or the WB Staff Login if applicable. Users without access should register on the website or contact rgachina@worldbank.org for assistance.\nAfter logging in, select Enterprise Surveys under Survey Type, then choose the relevant country under Economy. Download the full dataset for Georgia (`Georgia-2023-full-data.dta`) and save it to the designated project folder using the same file name. Repeat the same steps to download the Botswana (`Botswana-2023-full-data.dta`) dataset and save it in the same folder.\nData files: Georgia-2023-full-data.dta and Botswana-2023-full-data.dta.","citation":"World Bank. (2023). \"World Bank Enterprise Surveys\" [Dataset]. World Bank. Available at www.enterprisesurveys.org.","access_type":"Data is publicly available but does not allow redistribution and it is not included in the reproducibility package."},{"name":"World Bank Enterprise Surveys (WBES) - April 2025 release ","note":"Access date: April 2025.\nData is accessible upon request from Enterprise Surveys team by email. For detailed information, please refer to the README file.\nData file: ES-Indicators-Database-Global-Methodology_April_14_2025.dta.","access_type":"Data access requires human approval and is not included in the reproducibility package.","citation":"World Bank. (n.d.). \"World Bank Enterprise Surveys\" [Dataset]. Unpublished data.","uri":"https:\/\/www.enterprisesurveys.org\/en\/enterprisesurveys"}],"reproduction_instructions":"To reproduce the findings in this study, please follow the steps below:\n1. Obtain the raw data and place it in the \"Hotels\" folder. \n3. Change the paths as indicated on README.\n4. Run `Eff_4-17-2025.do` and `Results_replication.do` sequentially. ","technology_requirements":"1.5 hours total run time. (Generating Table A7 alone takes ~1 hour and 15 minutes.)","technology_environment":"Paper exhibits were reproduced in one computer with the following specifications:\nOS: Windows 11 Enterprise\nProcessor: Intel(R) Xeon(R) Gold 5218 CPU @2.30GHz\nMemory available: 6 GB"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}