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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/60181
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dc.creatorRebeca Maria Nepomuceno Limapt_BR
dc.creatorLuciano Ferreira Gabrielpt_BR
dc.creatorFrederico Gonzaga Jayme Juniorpt_BR
dc.date.accessioned2023-10-27T19:59:54Z-
dc.date.available2023-10-27T19:59:54Z-
dc.date.issued2022-
dc.citation.volume81pt_BR
dc.citation.issue322pt_BR
dc.citation.spage27pt_BR
dc.citation.epage51pt_BR
dc.identifier.doihttps://doi.org/10.22201/fe.01851667p.2022.322.82471pt_BR
dc.identifier.issn0185-1667pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/60181-
dc.description.abstractEl objetivo de este trabajo es analizar empíricamente cómo la ma-nufactura dividida en subsectores por intensidad de investigación y desarrollo (I+D) incide en el nivel de complejidad económica (eci). Para ello, utilizamos dos métodos: 1) paramétrico a través de mínimos cuadrados ordinarios dinámicos (pdols), y 2) no paramétrico: a) análisis envolvente de datos (dea) y b) descom-posición de Malmquist. Los resultados econométricos sugieren que la asignación de trabajadores a la manufactura de elevado nivel de I+D tiene un impacto positivo en el nivel de eci de todos los países de la muestra analizada, mientras que en los sectores de menor I+D hay un mayor impacto en los países emergentes, pero menores efectos (o negativos) sobre los países avanzados. En general, los resultados no paramétricos indican que la relación entre la eficiencia de los subsectores manufactureros y la comple-jidad económica presenta forma de U invertida. Se presta especial atención a Brasil, cuyo nivel de recuperación de la industria ma-nufacturera fue insuficiente para explicar la productividad total de los factores en el periodo analizado.pt_BR
dc.description.resumoThis paper aims to analyze empirically how manufacturing, disaggregated into subsectors by research and development (R&D) intensity, influences the level of economic complexity (eci). For this, two methods were used: 1) the parametric by Panel Dynamic Ordinary Least Squares (pdols) and 2) the non-parametric: a) Data Envelopment Analysis (dea) and b) Malm-quist Decomposition. The econometric results suggest that the allocation of workers in the manufacture of high R&D level has a positive impact on the eci level of all the countries in the sample analyzed, whereas in the sectors of lower R&D there is a greater impact in emerging countries, but lower effects (or negative) on advanced countries. In general, the non-par-ametric results present the relationship between efficiency in manufactur-ing subsectors and economic complexity as an inverted U shape. Special attention is given to Brazil, which manufacturing catching up was under-performed in explaining total factor productivity in the analyzed periodpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentFCE - DEPARTAMENTO DE CIÊNCIAS ECONÔMICASpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofInvestigación Económica-
dc.rightsAcesso Abertopt_BR
dc.subjectEconomic complexitypt_BR
dc.subjectEconomic developmentpt_BR
dc.subjectData envelopment analysispt_BR
dc.subject.otherEconomiapt_BR
dc.subject.otherDesenvolvimento econômicopt_BR
dc.subject.otherPaises emergentespt_BR
dc.titleManufacturing and economic complexity: a multisectorial empirical analysis based on parametric and non-parametric methodspt_BR
dc.title.alternativeComplejidad económica e industria: un análisis empírico multisectorialpt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.revistas.unam.mx/index.php/rie/article/view/82471pt_BR
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