Exploring the interrelationship among health status, CO2 emissions, and energy use in the top 20 highest emitting economies: based on the CS-DL and CS-ARDL approaches

Air pollution and life expectancy in the USA: Do medical innovation, health expenditure, and economic complexity matter?

Regardless of a country's income level, air pollution poses a significant environmental threat to human health. Long-term exposure to air pollution often triggers cardiovascular and respiratory diseases. Thus, air pollution significantly reduces life expectancy worldwide. The USA is one of the world's largest polluters of CO2 emissions, often used to represent air pollution. In this context, the main objective of this study is to examine the relationship between air pollution and life expectancy in the USA. In doing so, we control for the role of medical innovation, health expenditures, economic complexity, and government effectiveness using data for the period 1995-2019. The results indicate the existence of a cointegration relationship in the proposed model. The long-run coefficients are statistically positive for medical innovation and negative for CO2 emissions, economic complexity, and government effectiveness. On the other hand, health expenditures are ineffective in terms of life expectancy. Accordingly, medical innovation raises life expectancy, whereas CO2 emissions, economic complexity, and government effectiveness decrease it. Higher economic prosperity and health expenditures are not always beneficial to life expectancy. Therefore, policymakers need to take action to reduce air pollution and increase the comprehensiveness of economic prosperity benefits and health expenditure efficiency.

Assessing the impacts of crop production on climate change: An in-depth analysis of long-term determinants and policy implications

This research investigates the long-term determinants of carbon emissions in three diverse regions-Europe and Central Asia (ECA), Sub-Saharan Africa (SSA), and the Middle East and North Africa (MENA)-spanning 1990 to 2020. Utilizing advanced econometric models and analyses, including the Regularized Common Correlated Effects Estimator (rCCE), Common Correlated Effects Estimator (CCE), and Mean-Group (MG) approach, the study explores the intricate relationships between carbon emissions, crop production, emissions per agricultural production, energy consumption, renewable energy consumption, per capita GDP, and population. Region-specific nuances are uncovered, highlighting the varying dynamics: ECA exhibits intricate and non-significant relationships, SSA showcases significant effects of population dynamics and green technology adoption, and the MENA region reveals a nuanced interplay between emissions per agricultural production.The findings underscore the universal efficacy of green technology adoption for mitigation. Strategies for mitigating carbon emissions in the agricultural sector require diversified energy transition approaches, emphasizing efficiency enhancements, green technology adoption, and tailored population management strategies based on regional intricacies. Counterfactual simulations indicate the potential efficacy of strategic measures targeting crop production to reduce carbon emissions, while acknowledging the nuanced relationship between economic growth and emissions. Policymakers are urged to recognize the persistence in emission patterns, emphasizing the importance of targeted interventions to transition towards more sustainable trajectories. Overall, the research provides essential insights for crafting effective policies at both regional and global scales to address the complexities of climate change mitigation in the agricultural sector.

The nexus among CO2 emission, health expenditure and economic development in the OECD countries: New insights from a cross-sectional ARDL model

To find a way to realize sustainable development, this paper applied a cross-sectional ARDL (CS-ARDL) method to explore the interaction between carbon emissions, economic development, and health care expenditure for OECD countries. Firstly, we conduct a cross-sectional test to check whether the data is confronted with this issue. Secondly, we conduct a panel unit root test and cointegration test to confirm whether the ARDL-based method is suitable for our data. Thirdly, we analyze the results and provide possible explanations. Lastly, we conduct a short-term causality test to detect the connection between different variables. The main conclusion of our study includes: 1) Health care is a necessity in OECD countries. 2) Environmental deterioration places a heavy burden on health care expenditure in OECD countries. 3) Health care expenditure of last year negatively affects health care expenditure. 4) There is a short-run causality relationship from CO2, economic development, and dependency rate of youth to health care expenditure in OECD countries. Related policy proposals are provided according to our analysis of the results.