No abstract

No abstract

Palavras-chave: Análise por Envoltória de Dados (DEA); Análise em janela; Complexidade econômica; Economic Complexity Index (ECI); Desenvolvimento humano.Abstract: Economic growth is not the only factor to explain human development. Therefore, many authors have prioritized studies to measure the Human Development Index. However, these indexes do not analyze how Economic Complexity can increase Human Development. This paper aimed to determine how efficiently nations from Latin America and Asia measure a country's performance in converting Economic Complexity into Human Development, between 2010 and 2014. We used Data Envelopment Analysis (DEA), through the Variable Returns of Scale (VRS) Model and Window Analysis. Results showed that in 2014, all Asian countries, except China and the Philippines, were efficient; on the other hand Cuba was the benchmark for inefficient countries. Window Analysis showed Japan, South Korea and Singapore were efficient over time. This result confirms the initial hypothesis of this article: the more complex countries are the more efficiently they create Human Development.

Research on economic diversification and complexity has made significant advances in understanding economic development processes, but has only recently explored environmental and social sustainability considerations. In this article we evaluate the current state of this emerging literature and reveal 13 research gaps. A total of 35 different keywords and methods from structured literature reviews and network science helped to identify 374 scientific articles between 1988 and 2020 and revealed a fragmented research landscape around three larger network communities: (1) industrial policies, climate change, and green growth; (2) economic complexity and its association with inequality and environmental sustainability; and (3) economic diversification, including studies on livelihood diversification in poor areas. Economic complexity research applies new empirical methods and considers both social and environmental sustainability, but seldom scrutinizes theory and policy. Industrial policy research focuses on green growth policies but tends to omit social sustainability issues and advanced empirical methods. Research on economic diversification in poor regions provides insights on the livelihood diversification of farmers, but is disconnected from the economic complexity and industrial policy research. This review helps to summarize the main contributions and shows pathways for potential mutual learning between these communities for the sake of sustainable development.

No abstract

There is much discussion on the non-linear relationship between economic growth and carbon dioxide (CO2) emissions. Additionally, the effects of Foreign Direct Investment (FDI) on the environment are ambiguous, as both beneficial (i.e., pollution-halo) and harmful (i.e., pollution-haven) effects were found. Therefore, the literature presents no consensus on either of these topics. This is especially problematic for developing regions, as these regions represent growing economies interested in receiving foreign investments, and their CO2-related research is limited. This study aims to understand the impacts of economic growth and FDI on the CO2 emissions of São Paulo state, Brazil. To perform this study, a unique dataset on regional FDI was built, and 592 municipalities were included. The analyses combine linear and non-linear estimations, and the results suggest a non-linear relationship between Gross Domestic Product (GDP) per capita and CO2 emissions, along with a negative association between FDI and CO2. Finally, this study discusses possible policy implications and contributes to the international literature.

Many developing countries have highly unequal health systems across their regions. The pandemic of COVID-19 brought an additional challenge, as hospital structures equipped with doctors, intensive care units and respirators are not available to a sufficient extent in all regions. Using Data Envelopment Analysis, we create a COVID Index to verify whether the hospital structures in 543 Brazilian microregions are adequate to deal with COVID-19 and to verify whether public policies were implemented in the right direction. The results indicate that hospital structures in the poorest microregions were the most vulnerable, although the peak of COVID-19 occurred in the richest microregions (Sao Paulo). The Southeast states could relocate hospital resources or even patients between their regions. The relocation was not possible in many states in the Northeast, as the health system poorly assisted the interior of these states. These findings reveal that the heterogeneity of microregions’ hospital structures follows the patterns of socioeconomic inequalities. We conclude that it is easier for the wealthier regions to reallocate hospital resources internally than for the poorest regions. By using the COVID Index, policymakers and hospital managers have straightforward information to decide which regions must receive new investments and reallocate underutilized resources.

Several indicators on human development and capabilities have been introduced in recent decades that measure the absolute level of deprivations and freedoms of people. However, these indicators typically do not consider to what extent regions and countries efficiently spend their limited financial resources on improving human development. This is an important shortcoming because regions typically face different financial constraints in developing social policies and promoting human development. In this article, we advance methods from data envelopment analysis (DEA) to measure absolute capability values and the social efficiency of 129 Brazilian mesoregions. We present a new indicator called the Capability Index Adjusted by Social Efficiency (CIASE) that evaluates the human development performance of regions based on their absolute levels of deprivations as well as their social efficiency in translating limited financial resources into human development. Moreover, we introduce a Deprivation and Financial Responsibility based Prioritization Index (DFRP) that helps to identify priority regions for higher public expenditures in human development. Our results for the case of Brazil show that several poor regions perform relatively better in terms of social efficiency than in terms of absolute human development. Conversely, several rich regions perform relatively worse in terms of social efficiency than in absolute values. Thus, our analysis shows how DEA methods can help to bridge perspectives that are often presented as separated issues but could be strong allies for development: attending to human deprivation and promoting social efficiency.