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In recent years, environmental concerns have emerged as significant obstacles to economic advancement, leading to a critical examination of the complex relationship between environmental sustainability and economic expansion. With the economy expanding swiftly and environmental hazards intensifying, immediate action must be taken to address these problems. This necessitates innovative policies and practices that foster sustainable economic growth while minimizing environmental impact. To solve these issues, this study proposed an extensive analytical framework employing machine learning techniques, particularly artificial neural networks (ANNs), to investigate the Environmental Kuznets Curve (EKC) hypothesis. According to the EKC hypothesis, environmental degradation worsens before economic growth occurs. This study examines GDP per capita and key environmental indicators to measure economic development, using data from Anhui Province, China, from 2012 to 2019. The analysis provides empirical support for the theory and establishes a modeling framework that seamlessly integrates ML methodologies with EKC analysis, systematically examining and assessing the EKC's reliability for Anhui Province. The intricate interplay between Anhui Province's environment and economy, utilizing industrial waste gas, wastewater, and solid waste as critical indicators, evaluates environmental quality. At the same time, per capita GDP is the economic growth parameter. The findings indicate that the EKC does not adhere to an unchanging law but instead displays variations in distribution characteristics. The experimental results of the proposed ANN model demonstrate an impressive accuracy rate of 87%, outperforming five alternative models, including RF, KNN, DT, and LR. This superior model performance underscores the effectiveness of the ANN-based approach in capturing the intricate dynamics linking economic development and environmental pollution. [ABSTRACT FROM AUTHOR]

In this paper I argue that the political and economic domains are analogous for distributive purposes. The upshot of this conclusion is that because we normally think that an unequal distribution of votes is objectionable even if these inequalities are strictly necessary to improve the lives of less informed voters, so we should conclude that an unequal distribution of resources might be similarly objectionable even if strictly necessary to make the worse off better off. Leveling down economic resources is therefore sometimes morally permissible. I consider and reject three types of objections to this view. [ABSTRACT FROM AUTHOR]

This research examines the causal impact of institutional quality on economic development from a novel perspective. At the country level, we exploit variation in the natural malaria prevalence in 1900, just before vector-control methods were developed, to instrument for institutional quality using a two-stage least squares instrumental variables framework. Our instrument is a population-weighted average of malaria endemicity estimates for the year 1900 developed by the World Health Organization scientists in the 1960s. We argue that this measure of historical malaria offers more expansive geographic information about the disease environment, and our baseline IV estimates reveal that greater institutional quality causes greater contemporaneous economic growth. Next, we investigate the robustness of these baseline results to alternative explanations, including the role of geography and the role of early colonizers' experiences, as the causal link between the early disease environmental, institutional quality, and contemporary growth. As an additional test of the explanatory power of malaria endemicity in 1900 as an instrumental variable, we replace our instrument for settler mortality and replicate the core results from the seminal study on colonial origins of comparative development by Acemoglu et al. (2001). In summary, we propose that malaria endemicity estimated for 1900 holistically explains the legacy of early disease on institutional quality development and contemporary economic development, thus significantly contributing to the resolution of the geography versus institutions debate. [ABSTRACT FROM AUTHOR]

Research and Development (R&D) is the common denominator of innovation and technological progress, supporting sustainable development and economic growth. In light of the availability of new datasets and innovative indicators, in this work, we introduce a novel perspective to analyse the international trade of goods through the lenses of the nexus R&D-industrial activities of countries. We propose two new indices, RDE and RDI, summarizing the R&D content of countries' export and import baskets—respectively—and investigate their evolution in time, during the period 1995–2017, and space. We demonstrate the potential of these indices to shed new light on the evolution of R&D choices and trade, innovation, and development. In fact, compared to standard measures of countries' development and economic growth (e.g., the Human Development Index among the others tested), these indices provide complementary information. In particular, tracing the trajectories of countries along the RDE-HDI plane, different dynamics appear for countries with increased HDI, which we speculate can be reasoned with countries' availability of natural resources. Eventually, we identify two insightful applications of the indices to investigate further countries' environmental performances as related to their role in international trade. [ABSTRACT FROM AUTHOR]

Ecological degradation is a major challenge for all nations. The problem is particularly worrying for South Africa, which has recently suffered from various ecological catastrophes. Thus, the empirical study evaluates the nexus between CO2 emissions and financial development, renewable energy, economic growth and environmental-related technologies in South Africa utilizing data between 1980 and 2020. We employed autoregressive distributed lag (ARDL) and time-varying causality to evaluate these connections. The results from the ARDL show that financial development and environmental-related technologies lessen CO2 emissions while economic progress intensifies CO2 emissions. Surprisingly, renewable energy does not mitigate CO2 emissions. Furthermore, the time-varying causality shows that all the independent variables can forecast CO2 emissions at different sub-periods. Finally, our results are resilient to various policy ramifications useful in reducing CO2 emissions and associated adverse ecological consequences. [ABSTRACT FROM AUTHOR]

The dislocation between regional innovation and economic development directly influences the economic effect of regional innovation. However, no in-depth researches have been made on how to solve this problem. Using data from Henan Province, China, employing geographical detector technology, this paper focuses on testing whether the industry-university-research cooperation can contribute to coordinating the relation between regional innovation and economic development. It is shown that: 1) the industry-university-research cooperation in Henan Province is increasing gradually, and the network presents a core-edge structure, and the coupling degree between regional innovation and economic development is spatially unbalanced, which is similar to the spatial distribution of the intensity of industry-university-research cooperation; 2) as an important approach to effectively connect scientific researches with market demands, the industry-university-research cooperation can help form an interactive, interconnected, coupled and coordinated virtuous relation between regional innovation and economic development. Compared with the cooperation between organizations of the same type and the separate innovation of organizations, the improvement of the industry-university-research cooperation level can better coordinate the relation between regional innovation and economic development; 3) the cooperative innovation model between enterprises and universities can better promote the coupling between regional innovation and economic development, compared with many industry-university-research cooperation models. For underdeveloped areas lacking local knowledge base, industry-university-research cooperation should be considered as a long-term development strategy, especially using the knowledge sources of external universities and scientific research institutions to enhance innovation capability and achieve economic growth. [ABSTRACT FROM AUTHOR]