Investimento estrangeiro direto, inovação regional e capacidade de absorção no Brasil

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Cassânego, Vitor Melão
Orientador(a): Moralles, Herick Fernando lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de São Carlos
Câmpus São Carlos
Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
IED
FDI
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/17555
Resumo: Foreign direct investment (FDI) has been seen by the literature as an influential factor in the technological evolution of host-countries innovation ecosystems, with several developing nations such as Brazil aiming to attract FDI as a way to potentialize their development through innovative output. However, the evidence on whether FDI configures a source of positive or negative influence on regional innovation capabilities is definitely mixed. Furthermore, despite the existence of studies regarding emerging economies, there is a gap when it comes to the regional level in Brazil. We intend to contribute to the literature by examining whether regional MNEs are inducing high or low-intensity innovations in this last context. Thus, this study aims to complement academic investigations by analyzing the influence of multinational enterprises (MNEs) on regional innovation intensity in Brazil in the state of São Paulo using a unique regional-level FDI database in a panel ranging from 2010 to 2016. The results indicate that the presence of MNEs boosts the production of high and low-intensity inventions, slightly more for the latter than the former. In other words, FDI is better for the production of inventions in general, which can later become innovation, but even more so for utility models and certificates of addition. These findings corroborate with various regression specifications and alternative estimation methods explored throughout the academic literature while remaining robust to endogeneity issues.