{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-01-15","version":"1"},"project_desc":{"authoring_entity":[{"name":"Hector Daniel Segura Jimenez","affiliation":"World Bank","email":"hsegurajimenez@worldbank.org"},{"name":"Hernan Winkler","affiliation":"World Bank","email":"hwinkler@worldbank.org"},{"name":"Pawel Gmyrek","affiliation":"ILO","email":"gmyrek@ilo.org"},{"name":"Mariana Viollaz","affiliation":"World Bank","email":"mviollaz@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Disruption Without Dividend? How The Digital Divide And Task Differences Split GenAI\u2019s Global Impact","idno":"RR_WLD_2025_528"},"data_statement":"Some data is limited-access\/restricted and has not been included in the reproducibility package. For more details, please refer to the README file.","software":[{"name":"R","version":"4.5.1"},{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Disruption Without Dividend? How The Digital Divide And Task Differences Split Genai\u2019s Global Impact","date":"2026-01","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_WLD_2025_528","zip_package":"RR_WLD_2025_528.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":"2026-01-15","abstract":"This paper examines how Generative Artificial Intelligence (GenAI) could affect labor markets globally, with particular attention to the uneven distribution of risks and opportunities between advanced and developing economies. Cross-country differences in occupational structure suggest that developing economies face lower aggregate automation exposure than developed countries but comparable potential for task augmentation. However, disparities in digital infrastructure create an asymmetry: workers in positions vulnerable to automation typically maintain sufficient internet connectivity to experience displacement effects even in low-income settings, while those who could benefit from GenAI augmentation face substantial digital infrastructure gaps that may prevent them from realizing productivity gains. This finding suggests that developing countries may experience the disruptive effects of GenAI faster than its productivity benefits. On the other hand, conventional occupational exposure measures systematically overestimate GenAI's impact in developing countries by assuming uniform task content across economies. Using PIAAC and STEP survey data, we demonstrate that workers in developing countries perform substantially fewer non-routine analytical tasks\u2014GenAI's primary targets\u2014even within occupations classified as highly exposed. These findings highlight the importance of adapting GenAI exposure measures to developing countries' distance from the technology frontier.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"Generative Artificial Intelligence"},{"name":"Automation"},{"name":"Digital Divide"},{"name":"Occupational Exposure"},{"name":"Task Automation"},{"name":"Technological Diffusion"}],"topics":[{"id":"J24","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Human Capital \u2022 Skills \u2022 Occupational Choice \u2022 Labor Productivity","parent_id":"J2"},{"id":" O33","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Technological Change: Choices and Consequences \u2022 Diffusion Processes","parent_id":"O3"},{"id":" J21","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Labor Force and Employment, Size, and Structure","parent_id":"J2"},{"id":" O15","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Human Resources \u2022 Human Development \u2022 Income Distribution \u2022 Migration","parent_id":"O1"},{"id":" L86","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Information and Internet Services \u2022 Computer Software","parent_id":"L8"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Disruption Without Dividend? How The Digital Divide And Task Differences Split Genai\u2019s Global Impact","authors":"Pawel Gmyrek, Mariana Viollaz, Hernan Winkler"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Runtime: 1 hour 15 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":"Hernan Winkler","affiliation":"World Bank","email":"hwinkler@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) Xeon(R) Gold 6226R CPU @ 2.90GHz\n\u2022 Memory available: 16.0 GB\n\u2022 Software version: R 4.5.1, Stata 19.5 MP","reproduction_instructions":"Once users have access to all the data, to reproduce the findings, a new user needs to:\n1. Update the file path in `01_Country_level_GenAI_exposure\/main_for_01.R` script and run the code.\n2. Update the file path in `02_GenAI_exposure_by_internet_access\/main_for_02.R` script and run the code.\n3. Update the file path in `03_Task_content_job_measures\/main_for_03.do` do-file and run the code.\n4. Update the file path in `04_GenAI_exposure_task_content\/Step_2_GenAI_and_task_content.Rmd` script and run the code.\n5. Update the file path in `05_Mlogit_model_annex\/main_for_05.R` script and run the code.\n6. Update the file path in `05_Mlogit_model_annex\/03-mlogit-model-estimation` do-file and run the code.","datasets":[{"name":"EAPPOV (East Asia and the Pacific Poverty and Equity Database)","note":"Source: World Bank.\nData was accessed on May 1st, 2025.\nFiles location: \"Data\\Raw\\EAPPOV\"\nFile names: KHM_2021_CSES_v01_M_v01_A_EAPPOV_I.dta and LAO_2018_LECS_v01_M_v06_A_EAPPOV_I.dta","access_type":"Restricted data: Data is available for World Bank Staff.","citation":"World Bank.\nn.d.\nEast Asia and the Pacific Poverty and Equity Database [dataset].\nAccessed via the World Bank datalibweb Stata API.\nAccessed on May 1st, 2025."},{"name":"Global Labor Database (GLD)","note":"Source: World Bank.\nData was accessed on February 21st, 2025.\nFiles location: \"Data\\Raw\\GLD\"\nFile names: ALB_2013_LFS_V01_M_V01_A_GLD_ALL.dta; BGD_2022_QLFS_V01_M_V02_A_GLD_ALL.dta; BOL_2021_ECE_V01_M_V02_A_GLD_ALL.dta; ETH_2021_LFS_V01_M_V03_A_GLD_ALL.dta; GEO_2022_LFS_V01_M_V01_A_GLD_ALL.dta; IND_2022_PLFS_V01_M_V02_A_GLD_ALL.dta;\tLKA_2021_LFS_V01_M_V03_A_GLD_ALL.dta;\tMEX_2023_ENOE_V01_M_V01_A_GLD_ALL.dta; MNG_2022_LFS_V01_M_V02_A_GLD_ALL.dta; PAK_2020_LFS_V01_M_V04_A_GLD_ALL.dta;\tRWA_2021_LFS_V01_M_V01_A_GLD_ALL.dta;\tTHA_2021_harmonized_LFS.dta; TUR_2019_HLFS_V01_M_V03_A_GLD_ALL.dta;\tZMB_2022_LFS_V01_M_V01_A_GLD_ALL.dta; and\tZWE_2022_QLFS_V01_M_V02_A_GLD_ALL.dta.","access_type":"Restricted data: Data is available for World Bank Staff.","uri":"https:\/\/worldbank.github.io\/gld\/README.html","citation":"World Bank.\nn.d.\nGlobal Labor Database (GLD) [dataset].\nAccessed via the World Bank datalibweb Stata API.\nAccessed on February 21st, 2025."},{"name":"SEDLAC (Socio-Economic Database for Latin America and the Caribbean)","note":"Source: CEDLAS and World Bank.\nData was accessed on March 28th, 2025.\nFiles location: \"Data\\Raw\\SEDLAC\"\nFile names: ARG_2023_EPHC-S2_v01_M_v01_A_SEDLAC-03_all.rds; BOL_2023_EH_v01_M_v01_A_SEDLAC-03_all.rds; BRA_2023_PNADC-E1_v01_M_v01_A_SEDLAC-03_all.rds; CHL_2022_CASEN_v01_M_v01_A_SEDLAC-03_all.rds;\tDOM_2023_ECNFT-Q03_v01_M_v01_A_SEDLAC-03_all.rds; ECU_2023_ENEMDU_v01_M_v01_A_SEDLAC-03_all.rds;\tGTM_2023_ENCOVI_v01_M_v01_A_SEDLAC-03_all.rds;\tHND_2023_EPHPM_v01_M_v01_A_SEDLAC-03_all.rds;\tPER_2023_ENAHO_v01_M_v01_A_SEDLAC-03_all.rds;\tSLV_2023_EHPM_v01_M_v01_A_SEDLAC-03_all.rds; and\tURY_2023_ECH_v01_M_v01_A_SEDLAC-03_all.rds.","access_type":"Restricted data: Data is available for World Bank Staff.","citation":"CEDLAS and World Bank.\nn.d.\nSocio-Economic Database for Latin America and the Caribbean (SEDLAC) [dataset].\nAccessed via the World Bank datalibweb Stata API.\nAccessed on March 28th, 2025."},{"name":"LABLAC (Labor Database for Latin America and the Caribbean)","note":"Source: CEDLAS and World Bank\nData was accessed on March 6th, 2025.\nFiles location: \"Data\\Raw\\LABLAC\"\nFile names:  LABLAC_bra_2024_q03_ALL.dta; LABLAC_col_2024_q03_ALL.dta; LABLAC_cri_2024_q03_ALL.dta; LABLAC_dom_2024_q03_ALL.dta; LABLAC_ecu_2024_q03_ALL.dta; LABLAC_mex_2024_q02_ALL.dta; LABLAC_per_2024_q03_ALL.dta; LABLAC_slv_2023_q04_ALL.dta; and LABLAC_ury_2024_q02_ALL.dta.","access_type":"Restricted data: Data is available for World Bank Staff.","citation":"CEDLAS and World Bank.\nn.d.\nLabor Database for Latin America and the Caribbean (LABLAC) [dataset].\nAccessed via the World Bank datalibweb Stata API.\nAccessed on March 6th, 2025."},{"name":"Survey of Adults Skills (PIAAC)","note":"Source: OECD.\nData was accessed in April, 2025.\nFiles location: \"Data\\Raw\\PIAAC\".","uri":"https:\/\/www.oecd.org\/en\/about\/programmes\/piaac\/piaac-data.html","access_type":"Limited-access data: Data access requires purchase or human approval and is not included in the reproducibility package.","citation":"Organisation for Economic Co-operation and Development (OECD). \n2025. \nProgramme for the International Assessment of Adult Competencies (PIAAC) Cycle 1 and Cycle 2 Database [Dataset]. "},{"name":"West African Economic and Monetary Union (WAEMU) microdata","note":"Source: World Bank.\nData was accessed on August 13th, 2025.\nFiles location: \"Data\\Raw\\WAEMU\".","access_type":"Limited-access data: Data access requires purchase or human approval and is not included in the reproducibility package. See additional details in the README."},{"name":"STEP (Skills Toward Employment and Productivity) database","access_type":"Limited-access data: Data access requires purchase or human approval and is not included in the reproducibility package.","note":"Source: World Bank.\nData was accessed on March 1st, 2025.\nFiles location: \"Data\\Raw\\STEP\".\nFile names: STEP_PHL.dta; STEP Kosovo_working_S11.dta; STEP_SRB.dta; el_salvador.dta; STEP Armenia_working.dta; STEP Bolivia_working.dta; STEP Colombia_working.dta; STEP Georgia_working.dta; STEP Ghana_working.dta; STEP Kenya_working.dta; STEP Laos_working.dta; STEP Macedonia_working.dta; STEP Sri_Lanka_working.dta; STEP Ukraine_working.dta; STEP Vietnam_working.dta; and STEP Yunnan_working.dta.","uri":"https:\/\/microdata.worldbank.org\/index.php\/catalog\/?page=1&collection%5B%5D=step&ps=15","citation":"World Bank. \nSTEP (Skills Toward Employment and Productivity) databases [Dataset]. \nAvailable at https:\/\/microdata.worldbank.org\/index.php\/catalog\/?page=1&collection%5B%5D=step&ps=15.\nAccessed on March 1st, 2025."},{"name":"ILO employment data","uri":"https:\/\/ilostat.ilo.org\/topics\/employment\/","note":"Source: International Labour Organization (ILO).\nData was accessed on March 10th, 2025.\nFiles location: \"Data\\Raw\\Other\".\nFile names: Country_emp_by_ISCO2D_ILO.xlsx; Country_emp_by_occupation_ILO.xlsx.","citation":"International Labour Organization (ILO). \nn.d.. \nStatistics on employment.\nhttps:\/\/ilostat.ilo.org\/topics\/employment\/.\nAccessed on March 10th, 2025.","access_type":"Data is publicly available and included in the reproducibility package."},{"name":"International Standard Classification of Occupations (ISCO)","access_type":"Data is publicly available and included in the reproducibility package.","citation":"International Labour Organization (ILO). \nn.d.. \nInternational Standard Classification of Occupations (ISCO). ILOSTAT.\nAvailable at https:\/\/ilostat.ilo.org\/methods\/concepts-and-definitions\/classification-occupation\/.\nAccessed on March 10th, 2025.","uri":"https:\/\/ilostat.ilo.org\/methods\/concepts-and-definitions\/classification-occupation\/#elementor-toc__heading-anchor-10","note":"Source: International Labour Organization (ILO).\nData was accessed on March 10th, 2025.\nFiles location: \"Data\\Raw\\Other\".\nFile names:  mapping.csv."},{"name":"2025 GenAI scores","uri":"https:\/\/github.com\/pgmyrek\/2025_GenAI_scores_ISCO08","note":"Source: Gmyrek et. al. (2025).\nFiles location: \"Data\\Raw\\Other\".\nFile names: Final_Scores_ISCO08_Gmyrek_et_al_2025.xlsx; Exposure_Gradients.xlsx; AI_scores.dta.","citation":"Gmyrek, P., Berg, J., Kami\u0144ski, K., Konopczy\u0144ski, F., \u0141adna, A., Nafradi, B., Ros\u0142aniec, K., Troszy\u0144ski, M. 2025. Generative AI and Jobs: A Refined Global Index of Occupational Exposure, ILO Working Paper 140 (Geneva, ILO). https:\/\/doi.org\/10.54394\/HETP0387","access_type":"Data is publicly available and included in the reproducibility package."},{"name":"World Development Indicators","note":"Source: World Bank.\nData was accessed on January 12th, 2026.\nFile location: \"Data\\Raw\\Other\".\nFile names: GDP_internet_from_WDI.rds; WDI_GDP_region_data_latest24.rds; WDI_Knn_indicators_2024.rds; WDI_model_indicators_2024.rds; WDI_pop_data24.rds;\nIndicator used: population, total (SP.POP.TOTL); population ages 0-14, total (SP.POP.0014.TO); employment to population ratio, 15+, total (%) (SL.EMP.TOTL.SP.ZS); GDP per capita (USD 2021 PPP) (NY.GDP.PCAP.PP.KD); individuals using the internet (% of population) (IT.NET.USER.ZS); access to electricity (% of population) (EG.ELC.ACCS.ZS); urban population (% of total population) (SP.URB.TOTL.IN.ZS); literacy rate, adult total (% of people ages 15 and above) (SE.ADT.LITR.ZS); mobile cellular subscriptions (per 100 people) (IT.CEL.SETS.P2).\nTo see the countries and years used, please refer to the README. ","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 (CC-BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","uri":"https:\/\/data.worldbank.org\/indicator\/","citation":"World Bank.\n2026.\nWorld Development Indicators [dataset].\nAvailable at: https:\/\/data.worldbank.org\/indicator\/.\nAccessed on January 12th, 2026."}]},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}