000150491 001__ 150491
000150491 005__ 20251017144638.0
000150491 0247_ $$2doi$$a10.1016/j.strueco.2024.09.014
000150491 0248_ $$2sideral$$a142691
000150491 037__ $$aART-2024-142691
000150491 041__ $$aeng
000150491 100__ $$0(orcid)0000-0001-8704-4476$$aCalvo-Calvo, Elena$$uUniversidad de Zaragoza
000150491 245__ $$aTextile offshoring along global value chains (GVCs): Impacts on employment and gender wage gaps
000150491 260__ $$c2024
000150491 5060_ $$aAccess copy available to the general public$$fUnrestricted
000150491 5203_ $$aGlobalization has a significant impact on the international distribution of production, which in turn affects the global distribution of employment and income. Yet, previous studies have often overlooked the gender implications associated with the evolution of global value chains (GVCs). In this context, the textile sector is considered critical for explaining the most recent trends in female employment, particularly in developing countries.
The main objective of this paper is to examine the impacts of textile offshoring on female participation in the labor market and on gender employment and wage gaps between 1991 and 2019. Specifically, it aims to understand prior premises as the expected increase in female workers due to the delocalization of the sector, the implications of these premises when countries begin to upgrade and their role in reducing gender inequalities.
To achieve this, we devised a multi-sectoral and multi-regional input-output (MRIO) model with a high level of disaggregation of 189 countries and 26 sectors, expanded to include male and female jobs and wages by sector and country. We also conducted a structural decomposition analysis (SDA) on the forces driving the evolution of gender gaps.
Our findings show that the gender employment gap grew in the global textile sector between 1991 and 2019, caused primarily by the role played by China and India in the textile supply chain. Gender wage gaps continue to linger, however, despite having narrowed in most of the countries analyzed.
000150491 536__ $$9info:eu-repo/grantAgreement/ES/DGA/S40-23R$$9info:eu-repo/grantAgreement/ES/MCINN/PID2019-106822RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2022-140010OB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2023-148401OB-I00
000150491 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000150491 590__ $$a5.5$$b2024
000150491 592__ $$a1.406$$b2024
000150491 591__ $$aECONOMICS$$b43 / 617 = 0.07$$c2024$$dQ1$$eT1
000150491 593__ $$aEconomics and Econometrics$$c2024$$dQ1
000150491 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000150491 700__ $$0(orcid)0000-0003-3113-1698$$aDuarte, Rosa$$uUniversidad de Zaragoza
000150491 700__ $$0(orcid)0000-0003-4802-600X$$aSarasa, Cristina$$uUniversidad de Zaragoza
000150491 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico
000150491 773__ $$g72 (2024), 122-132$$pStruct. chang. econ. dyn.$$tStructural Change and Economic Dynamics$$x0954-349X
000150491 8564_ $$s2011557$$uhttps://zaguan.unizar.es/record/150491/files/texto_completo.pdf$$yVersión publicada
000150491 8564_ $$s2496354$$uhttps://zaguan.unizar.es/record/150491/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000150491 909CO $$ooai:zaguan.unizar.es:150491$$particulos$$pdriver
000150491 951__ $$a2025-10-17-14:30:26
000150491 980__ $$aARTICLE