{"id":13340,"date":"2026-09-11T10:59:16","date_gmt":"2026-09-11T07:59:16","guid":{"rendered":"https:\/\/betam.bahcesehir.edu.tr\/?p=13340"},"modified":"2026-09-11T10:59:16","modified_gmt":"2026-09-11T07:59:16","slug":"recovering-province-identifiers-from-turkish-household-labour-force-survey-microdata","status":"publish","type":"post","link":"https:\/\/betam.bahcesehir.edu.tr\/en\/2026\/09\/recovering-province-identifiers-from-turkish-household-labour-force-survey-microdata\/","title":{"rendered":"RECOVERING PROVINCE IDENTIFIERS FROM TURKISH HOUSEHOLD LABOUR FORCE SURVEY MICRODATA"},"content":{"rendered":"<p><strong>Luis Pinedo Caro<\/strong><\/p>\n<p>Official microdata from the Turkish Household Labour Force Survey (HLFS) provides geographic indicators at the NUTS-2 level (26 subregions). The way data is aggregated masks T\u00fcrkiye\u2019s 81 provinces, putting together potentially heterogeneous local economies under the same label, thus, limiting the evaluation of policies\u2019 local impact. This paper presents a strategy to recover provincial-level identifiers in the microdata of the 2004-2013 period. A sequential identification algorithm is implemented based on the car plate provincial number, complemented with a year-specific urban-rural population re-weighting at the province level. The identification is validated internally using the logic behind existing multiprovince clusters and externally against administrative registration data from the Census, the Address Based Population Registration System (ABPRS) as well as with information from the Social Security Institution (SSI) regarding major economic activities. As an empirical proof of concept, informality rates at the province level are estimated for all 81 provinces, revealing sub-regional heterogeneity previously obscured under NUTS-2 reporting.<\/p>\n<p><em><strong>pdf. <a href=\"https:\/\/betam.bahcesehir.edu.tr\/wp-content\/uploads\/2026\/09\/WP202603.pdf\">WP202603<\/a><\/strong><\/em><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Luis Pinedo Caro Official microdata from the Turkish Household Labour Force Survey (HLFS) provides geographic indicators at the NUTS-2 level (26 subregions). The way data is aggregated masks T\u00fcrkiye\u2019s 81 provinces, putting together potentially heterogeneous local economies under the same label, thus, limiting the evaluation of policies\u2019 local impact. This paper presents a strategy to [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[275,278,293],"tags":[],"class_list":["post-13340","post","type-post","status-publish","format-standard","hentry","category-economic-research","category-publications","category-working-paper"],"_links":{"self":[{"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/posts\/13340","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/comments?post=13340"}],"version-history":[{"count":1,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/posts\/13340\/revisions"}],"predecessor-version":[{"id":13343,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/posts\/13340\/revisions\/13343"}],"wp:attachment":[{"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/media?parent=13340"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/categories?post=13340"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/betam.bahcesehir.edu.tr\/en\/wp-json\/wp\/v2\/tags?post=13340"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}