[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-108536-en":3,"doc-seo-108536-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},108536,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Background Note 8 - Transition from Brown to Green Jobs: its Potential, Poverty and Distributional Impacts in Argentina","This background note analyzes the transition from brown to green jobs in Argentina using 2016–2019 Argentina household survey text data. Machine learning is applied with O*NET-based definitions of green jobs and Vona et al. (2018) definitions of brown jobs, estimating green and brown shares at about 6% and 3% of total employment. Findings indicate no gender differences, while brown workers are generally younger, less educated, and concentrated in the bottom income distribution. Transition patterns are often easy, but retraining is key when greener alternatives are harder to match and when wage step-downs occur.","| \u003Cbr>Authorized\u003Cbr> |\n| --- |\n| ic Disclosure\u003Cbr>\u003Cbr> |\n| Pub l |\n| sure Authorized\u003Cbr>\u003Cbr> |\n| Pub l ic Disclo\u003Cbr> |\n| thorized\u003Cbr>\u003Cbr>BACKGROUND NOTE 8. TRANSITION FROM BROWN TO GREEN JOBS: ITS |\n| Disc losure Au\u003Cbr>\u003Cbr> POTENTIAL, POVERTY AND\u003Cbr> |\n| Public\u003Cbr>\u003Cbr>DISTRIBUTIONAL IMPACTSIN ARGENTINA\u003Cbr> |\n| Authorized\u003Cbr> |\n| b l ic Disclosure\u003Cbr>\u003Cbr> |\n| Pu\u003Cbr> |\n|  |\n| \u003Cbr>November 3, 2022 |\n\nTable of Contents  \n1. Introduction................................................................................................................3  \n2. Methodology ..............................................................................................................6  \n2.1. Argentina household survey: mapping CNO to ISCO .........................................................6  \n2.2. Definition of green and brown occupations.......................................................................8  \n3. Results: number of green and brown jobs and main characteristics .................... 10  \n3.1. Number of green and brown jobs ................................................................................... 10  \n3.2. Comparison of socioeconomic traits of green and brown jobs ...................................... 10  \n3.2.1. Gender........................................................................................................................................ 10  \n3.2.2. Age, education, geographical location, and income distribution ............................................ 11  \n4. Green jobs transition .............................................................................................. 14  \n5. Conclusions............................................................................................................. 17  \n6. References .............................................................................................................. 18  \nAppendix 1. Aggregate checks results .............................................................................. 20  \nAppendix 2. Differences among green and brown employment ...................................... 22  \nBackground Note 8. Transition from Brown to Green Jobs: its Potential, Poverty and Distributional Impacts in Argentina  \nPrepared by Agustín Arakaki, Mariana Conte Grand, Fabián González, Penny Mealy, Lourdes Rodríguez Chamussy, Julie Rozenberg  \nThis work relies on text data from the Argentina household surveys for the 2016-2019 period. It uses machine learning together with a definition of green jobs as defined in O*NET and of brown jobs as defined by Vona et al. (2018) , to find that green and brown account for approximately 6 and 3 per cent of total employment, respectively. Results show that while there are no gender differences among green and brown jobs, brown jobs are performed by individuals who are generally younger, have lower education levels, and belong to the bottom of the main income distribution , which require monitoring to avoid impacts on more vulnerable people. When looking at transition from brown to green jobs, the findings are that there are occupations for which transition would be natural: workers will easily find a greener job and will receive higher incomes, and so there will be no need of any supporting policy. Only in a few cases it would be difficult to find a greener job (because dissimilarity is low), and if found, it will be less paid. Retraining would be key in those circumstances. There are even less cases for which an employee would perform similar tasks in a brown and green occupation but would have to accept a greener job that would mean to step down in terms of pay. This work provides estimates of workers benefits and costs of decarbonization in Argentina, which could be complemented with costs of retraining and compensations, net tax impacts for the government as well as other private costs and externalities.  \nKeywords: green jobs, brown jobs, just transition, Argentina  \nJEL codes: J0, O1, Q5  \n1. Intro","cbCaiiBFZ0l4c5cQ","https://ap.wps.com/l/cbCaiiBFZ0l4c5cQ","pdf",1814839,3,1,23,"English","en",105,"# Introduction\n# Methodology\n## Argentina household survey: mapping CNO to ISCO\n## Definition of green and brown occupations\n# Results: number of green and brown jobs and main characteristics\n## Number of green and brown jobs\n## Comparison of socioeconomic traits of green and brown jobs\n# Green jobs transition\n# Conclusions\n# References\n# Appendix 1. Aggregate checks results\n# Appendix 2. Differences among green and brown employment","[{\"question\":\"How are green and brown jobs defined in this report?\",\"answer\":\"Green jobs are defined using O*NET criteria, while brown jobs follow the definitions by Vona et al. (2018). These definitions are then applied through machine learning to the household survey data.\"},{\"question\":\"What is the estimated share of green and brown employment in Argentina?\",\"answer\":\"Green and brown jobs account for approximately 6% and 3% of total employment, respectively, based on the model applied to 2016–2019 survey data.\"},{\"question\":\"What do the results say about poverty and distributional impacts?\",\"answer\":\"Brown jobs are performed by workers who are generally younger, have lower education levels, and belong to the bottom of the main income distribution, requiring monitoring to avoid impacts on more vulnerable groups. During transitions, wages can increase in natural transitions but may decline when greener matching is difficult, making retraining important.\"}]","Background Note 8 - Transition from Brown to Green Jobs: its Potential, Poverty and Distributional Impacts in Argentina | PDF",1784472147,58,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"background-note-8-transition-from-brown-to-green-jobs-its-potential-poverty-and-distributional-impacts-in-argentina","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":20},"https://docshare.wps.com/document/research-report/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/background-note-8-transition-from-brown-to-green-jobs-its-potential-poverty-and-distributional-impacts-in-argentina/108536/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-07-29","2026-07-19",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"How are green and brown jobs defined in this report?","Question",{"text":76,"@type":77},"Green jobs are defined using O*NET criteria, while brown jobs follow the definitions by Vona et al. (2018). These definitions are then applied through machine learning to the household survey data.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What is the estimated share of green and brown employment in Argentina?",{"text":81,"@type":77},"Green and brown jobs account for approximately 6% and 3% of total employment, respectively, based on the model applied to 2016–2019 survey data.",{"name":83,"@type":74,"acceptedAnswer":84},"What do the results say about poverty and distributional impacts?",{"text":85,"@type":77},"Brown jobs are performed by workers who are generally younger, have lower education levels, and belong to the bottom of the main income distribution, requiring monitoring to avoid impacts on more vulnerable groups. During transitions, wages can increase in natural transitions but may decline when greener matching is difficult, making retraining important.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]