This preprint has been published elsewhere.
DOI of the published preprint https://doi.org/10.1590/0103-6351/6960
Preprint / Version 1

Measuring structural upgrading: applying principal component analysis in a global value chain framework

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DOI:

https://doi.org/10.1590/0103-6351/6960

Keywords:

global value chains, industrial upgrading, input-output analysis

Abstract

The main objective of the article is to analyze, based on the analysis of principal components and data grouping, the relationship between structural upgrading indicators and the inclusion of those countries in the GVCs for a group of 43 countries. To achieve this objective, the study builds six upgrading indicators in three dimensions: product, process and functional. In addition to these six indicators, the study uses an indicator that measures the complexity of countries' productive structures. The results show that structural complexity has a positive and statistically significant relationship with the share of wages in income, and more capital-intensive countries also have higher levels of labor productivity and employment associated with exports. The study also shows a diversity of development patterns related to participation in GVCs and the structural upgrading process

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Posted

05/30/2022

How to Cite

Measuring structural upgrading: applying principal component analysis in a global value chain framework . (2022). In SciELO Preprints. https://doi.org/10.1590/0103-6351/6960

Section

Applied Social Sciences

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