O papel da complexidade econômica para o desalinhamento e volatilidade cambial nos BRICS (1995 a 2021)

• Ano de defesa: 2025
• Autor(a) principal: Souza, Guilherme de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Economia
• Palavras-chave em Português: Complexidade econômica; desalinhamento e volatilidade cambial; ARDL e GMM; BRICS; Economic complexity; exchange rate misalignment and volatility; CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA; Economia; Países do BRICS; Política cambial; Análise e Perspectiva Econômica; ODS::ODS 9. Indústria, Inovação e infraestrutura - Construir infraestrutura resiliente, promover a industrialização inclusiva e sustentável, e fomentar a inovação.
• Link de acesso: https://repositorio.ufu.br/handle/123456789/44896; http://doi.org/10.14393/ufu.di.2025.14

The objective of this dissertation is to present an analysis of the impact of economic complexity on misalignment and exchange rate volatility in the BRICS countries between 1995 and 2021. In this context, the work investigates whether the variables economic complexity index, GDP per capita differential in relation to the United States, interest rate differential in relation to the United States, inflation differential in relation to the United States and international reserves as a proportion of GDP were relevant to explain the misalignment and volatility of the real effective exchange rate in the BRICS countries. For this purpose, ARDL and GMM models were estimated, considering the analysis period from 1995 to 2021. The results indicated that, in the ARDL model estimations, the variables with statistically significant long-term coefficients were: economic complexity index significant in 3 models (negative and expected sign) in models 1 and 2 of the misalignment for Brazil and in model 2 of the misalignment for South Africa. In addition, other variables that presented significance were the GDP per capita differential (negative sign) and international reserves, in the model applied to the Brazilian exchange rate misalignment. For South Africa, all variables presented statistical significance (negative sign) in model 2 of the misalignment. Regarding exchange rate volatility, fewer significant variables were found. China stands out, as it presented significant coefficients for the following variables: economic complexity index (positive sign), GDP per capita differential (negative sign), international reserves (positive sign) and interest rate differential (positive sign). In the GMM models, many coefficients were significant, and the instruments used were considered valid. In addition, it is important to highlight that the ECI variable presented statistical significance and negative impact (expected sign) in seven models, namely the five misalignment models 1 for Brazil, China, Russia and South Africa, in addition to misalignment model 2 for China and India. Finally, statistical significance and a negative sign were also observed in volatility model 1 for Russia.