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Some figures require running additional R scripts, which are described in the Instructions for Replicators section.",{"name":70,"@type":61,"acceptedAnswer":71},"How is the data organized in the package?",{"text":72,"@type":64},"The data are split into a raw data folder and a cleaned data folder, containing country-specific job postings, skill files, and labor-indicator datasets.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},245146,1791740276,{"code":4,"msg":82,"data":83},"success",[84,88,93,98,103,108,112,117,122],{"id":85,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":86,"slug":87},11,90,"presentations",{"id":89,"doc_module":22,"doc_module_name":25,"category_name":90,"show_sort_weight":91,"slug":92},12,"Resumes",80,"resumes",{"id":94,"doc_module":22,"doc_module_name":25,"category_name":95,"show_sort_weight":96,"slug":97},14,"Invoices",70,"invoices",{"id":99,"doc_module":22,"doc_module_name":25,"category_name":100,"show_sort_weight":101,"slug":102},15,"Posters",60,"posters",{"id":104,"doc_module":22,"doc_module_name":25,"category_name":105,"show_sort_weight":106,"slug":107},16,"Social Media",50,"social-media",{"id":55,"doc_module":22,"doc_module_name":25,"category_name":109,"show_sort_weight":110,"slug":111},"Forms",40,"forms",{"id":113,"doc_module":22,"doc_module_name":25,"category_name":114,"show_sort_weight":115,"slug":116},18,"Letters",30,"letters",{"id":118,"doc_module":22,"doc_module_name":25,"category_name":119,"show_sort_weight":120,"slug":121},21,"Paper Templates",5,"papers-templates",{"id":123,"doc_module":22,"doc_module_name":25,"category_name":124,"show_sort_weight":4,"slug":125},158,"General","general-158",{"code":4,"msg":82,"data":127},{"doc_id":79,"user_id":128,"nickname":42,"user_avatar":129,"doc_module":22,"category_id":85,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":135,"language":136,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":12,"update_tm":140,"read_time":26},962084925502,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Reproducibility package for “Understanding Labor Market Demand in Real Time in Argentina and Uruguay”  \nOverview  \nThis package creates the output of the document “Understanding Labor Market Demand in Real Time in Argentina and Uruguay” using Stata. The package consists of a series of do files and databases that allow the user to reproduce all the figures, tablesand estimates that are part of the manuscript. All the material is stored in a shared folder on OneDrive. To replicate these outputs, just run the code “main_dofile.do” after modifying the user path. The replication of some figures requires to run a series of R scripts. We explain in detail how to do it in the Instructions for Replicators section.  \nData Availability  \nThe data folder is divided into a “raw” data folder and a “cleaned” data folder. The former contains the following files:  \n• ARG_postings.csv: job postings collected by Lightcast in Argentina between 2020 and 2023.  \n• CHL_postings.csv: job postings collected by Lightcast in Chile between 2020 and 2023.  \n• URY_postings.csv: job postings collected by Lightcast in Uruguay between 2020 and 2023.  \n• US_postings. dta: job postings collected by Lightcast in the United States in December 2023.  \n• US_postings_isco.dta: classification of job postings collected by Lightcast in the United States in December 2023 according to their ISCO code.  \n• ARG_skills.csv: individual skills identified by Lightcast for each posting in Argentina.  \n• CHL_skills.csv: individual skills identified by Lightcast for each posting in Chile.  \n• URY_skills.csv: individual skills identified by Lightcast for each posting in Uruguay.  \n• US_skills.csv: individual skills identified by Lightcast for each posting in the United States.  \nThese are the main files used to carry out the analysis in the paper. The “raw” data folder also contains the following secondary files:  \n• cuadros_tasas_indicadores_eph_ 09_ 24.xls: quarterly series of labor indicators for Argentina, including employment and unemployment rates.  \n• serie_empleo_ury.xlsx: monthly series of Uruguay’s employment rate.  \n• serie_desempleo_ury.xlsx: monthly series of or Uruguay’s unemployment rate.  \n• usu_individual_T322.txt: third quarter of 2022 microdata from the Encuesta Permanente de Hogares (Argentina household survey) .  \n• usu_individual_T422.txt: fourth quarter of 2022 microdata from the Encuesta Permanente de Hogares (Argentina household survey) .  \n• usu_individual_T423.txt: fourth quarter of 2023 microdata from the Encuesta Permanente de Hogares (Argentina household survey) .  \n• ECH_ 2022.csv: 2022 microdata from the Encuesta Continua de Hogares (Uruguay household survey) .  \n• uhci_dataappendix_sep2020 .xlsx: Data Appendix to the Utilization-adjusted Human Capital Index (UHCI) (Pennings, 2020) .  \n• eil_ 2307_estadisticas.xlsx: raw data from the Encuesta de Indicadores Laborales which monthly time series of job vacancy rates in Argentina.  \n• eil_ 2411_estadisticas_ 0.xlsx: updated version of the previous file.  \n• OxCGRT_compact_national_v1 .csv: raw data created by the COVID-19 Government Response Tracker (University of Oxford) which includes the daily series of the Stringency Index.  \nThe “cleaned” data folder contains the following files:  \n• ARG_postingsout.dta: modified version of the raw data of job postings in Argentina.  \n• baseUryNueva_completa.dta: modified version of the raw data of job postingsin Uruguay.  \n• CHL_postingsout.dta: modified version of the raw data of job postings in Chile.  \n• US_postingsout: modified version of the raw data of job postings in the United States.  \n• skills_ARG4_cat&noncat. dta: modified version of the raw data of skills in Argentina (classification of skills) .  \n• skills_CHL4_cat&noncat. dta: modified version of the raw data of skills in Uruguay (classification of skills) .  \n• skills_URY4_cat&noncat. dta: modified version of the raw data of skills in Uruguay (classification of skills) .  \n• skills_usa_categorizadas","cbCair2Kj4EuM7FH","https://ap.wps.com/l/cbCair2Kj4EuM7FH","pdf",364930,6,"English","# Overview\n# Data Availability\n## Raw data folder\n## Cleaned data folder","[{\"question\":\"What does the reproducibility package provide for the manuscript?\",\"answer\":\"It provides Stata do files and databases to reproduce all figures, tables, and estimates included in the manuscript.\"},{\"question\":\"How are the outputs replicated using the code?\",\"answer\":\"Run main_dofile.do after modifying the user path. Some figures require running additional R scripts, which are described in the Instructions for Replicators section.\"},{\"question\":\"How is the data organized in the package?\",\"answer\":\"The data are split into a raw data folder and a cleaned data folder, containing country-specific job postings, skill files, and labor-indicator datasets.\"}]","Reproducibility package - Understanding Labor Market Demand in Real Time in Argentina and Uruguay | PDF",1789225351]