Did industrial and export complexity drive regional economic growth in Brazil?

PLoS One. 2024 Dec 5;19(12):e0313945. doi: 10.1371/journal.pone.0313945. eCollection 2024.

Abstract

Research on productive structures has shown that economic complexity conditions economic growth. However, little is known about which type of complexity, e.g., export or industrial complexity, matters more for regional economic growth in a large emerging country like Brazil. Brazil exports natural resources and agricultural goods, but a large share of the employment derives from services, non-tradables, and within-country manufacturing trade. Here, we use a large dataset on Brazil's formal labor market, including approximately 100 million workers and 581 industries, to reveal the patterns of export complexity, industrial complexity, and economic growth of 558 micro-regions between 2003 and 2019. Our results show that export complexity is more evenly spread than industrial complexity. Only a few-mainly developed urban places-have comparative advantages in sophisticated services. Regressions show that a region's industrial complexity is a significant predictor for 3-year growth prospects, but export complexity is not. Moreover, economic complexity in neighboring regions is significantly associated with economic growth. The results show export complexity does not appropriately depict Brazil's knowledge base and growth opportunities. Instead, promoting the sophistication of the heterogeneous regional industrial structures and development spillovers is a key to growth. This study demonstrates that industrial complexity, which accounts for all employment sectors, provides a more accurate basis for designing effective and inclusive industrial policies in emerging economies like Brazil, compared to export-based complexity.

MeSH terms

  • Brazil
  • Commerce / economics
  • Economic Development* / trends
  • Employment / economics
  • Humans
  • Industry* / economics

Grants and funding

BFC would like to express his gratitude for the financial support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Finance Code 001, and DH for the support of CNPq (406943/ 2021-4 and 315441/2021-6). F.L.P. acknowledges the financial support provided by FCT Portugal under the project UIDB/04152/2020 -- Centro de Investigação em Gestão de Informação (MagIC). No additional external funding was received for this study.