Extent of the relationship between Economic Growth and its determinants in Europe from 2000 - 2021

• Autor(a) principal: Vaz, Filipa Maria Vasco
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.6/13864
• topic: Capital Físico; Capital Humano; Conhecimento Tecnológico; Corrupção; Crescimento Económico; Importações; Trabalho; Domínio/Área Científica::Ciências Sociais::Economia

The current nexus between energy, education and economic growth leads to the development of theoretical, hybrid and integrated economic models. In this research, we take into consideration variables that measure technological knowledge (R&D sector expenditures), physical capital (gross fixed capital formation), human capital (population with education), labour (employed population), politics (corruption perception index) and energy (imports of energy products) to verify their impact on the economic growth of several countries. Different equations were considered in the validation of the theoretical model and a series of econometric techniques were used and estimated, such as specification tests, basic and bias-corrected fixed and random effects models, and the generalized method of moments. This research emphasizes the importance of economic, political, social and energy variables to explain their impact on the economic growth behaviour of the European Union member states. Thus, we conducted a study based on panel data for the 27 EU member states from 2000 to 2021. The empirical results obtained are mostly in line with current economic theory. As expected, in the extended equation 5, the variables Gross Fixed Capital Formation, Total Education Labor, Energy Dependence and Corruption Perception Index have a positive impact in most of the estimated models. On the other hand, the variables R&D Expenditure and Total Education Population had a negative impact on the fixed and random effects estimators with bias correction, as well as on the robust GMM estimator.