RESILIÊNCIA E COMPLEXIDADE ECONÔMICA: UMA NOVA ABORDAGEM PARA O DESENVOLVIMENTO SUSTENTÁVEL

Abstract

This thesis contributes by proposing a theoretical approach and conducting empirical tests on the effects of the relationship between resilience and economic complexity in promoting sustainable development. Therefore, the objective is to provide an integrated approach that connects resilience, economic complexity, and sustainable development, offering a new perspective to address contemporary global challenges. In socioecological systems, such as economic ones, resilience can determine the ability to interact and combine multiple factors, enabling these systems to adapt or transform in the face of constant shocks or disturbances. On the other hand, economic complexity reflects a region's productive capacity and economic development based on the diversity and sophistication of the products that this economy can produce. Thus, economic complexity can also be a determining factor in creating new forms of production, adaptive capacity, and the transformation of economic and environmental systems. Based on these concepts, more complex economies generally have a greater capacity for growth and development due to their ability to innovate and adapt to new contexts, contributing to greater resilience and sustainable development. In this context, the thesis advances by empirically demonstrating that the relationship between resilience and economic complexity affects countries' adaptation to climate change impacts and regions' ability to recover from economic crises while minimizing the environmental impacts of long-term economic growth. To empirically test the proposed approach, the first empirical exercise employed a GMM System model on a sample of 118 countries, where the dependent variable was the ND-GAIN Index. This index is used in the literature to analyze countries' adaptive capacity, emphasizing environmental, economic, and social issues that influence resilience to climate change. This test revealed that economic complexity positively and significantly affects climate resilience, even in countries with different income levels. The second test utilized Spatial Seemingly Unrelated Regression Models (Spatial SUR) for 503 immediate regions in Brazil. Spatial SUR models allow for testing implicit relationships between variables due to spatial externalities, which are indirect effects that one spatial unit can have on others without these effects being directly observable or intentional. The results showed that the effects of economic complexity on the dependent variables, economic resilience and CO2 emissions, are non-linear, confirming the Environmental Kuznets Curve in the equation of the second variable. Additionally, the test showed an implicit relationship between economic resilience and emissions through the positive correlation between the model's equations. Finally, the results of this thesis have relevant practical implications, as they present economic complexity as a strategic alternative for resilience, particularly for adaptation to climate change and economic recovery after crises, while controlling the environmental degradation caused by economic growth.