This study investigates the short-term and long-term impacts of economic growth, trade openness and technological progress on renewable energy use in Organization for Economic Co-operation and Development (OECD) countries. Based on a panel data set of 25 OECD countries for 43 years, we used the autoregressive distributed lag (ARDL) approach and the related intermediate estimators, including pooled mean group (PMG), mean group (MG) and dynamic fixed effect (DFE) to achieve the objective. The estimated ARDL model has also been checked for robustness using the two substitute single equation estimators, these being the dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). Empirical results reveal that economic growth, trade openness and technological progress significantly influence renewable energy use over the long-term in OECD countries. While the long-term nature of dynamics of the variables is found to be similar across 25 OECD countries, their short-term dynamics are found to be mixed in nature. This is attributed to varying levels of trade openness and technological progress in OECD countries. Since this is a pioneer study that investigates the issue, the findings are completely new and they make a significant contribution to renewable energy literature as well as relevant policy development.
This study examines the impacts of income, energy consumption and population growth on CO2 emissions by employing an annual time series data for the period 1970-2012 for India, Indonesia, China, and Brazil. The study used the Autoregressive Distributed Lag (ARDL) bounds test approach considering both the linear and non-linear assumptions for related time series data for the top CO2 emitter emerging countries in both the short run and long run. The results show that CO2 emissions have increased statistically significantly with increases in income and energy consumption in all four countries. While the relationship between CO2 emissions and population growth was found to be statistically significant for India and Brazil, it has been statistically insignificant for China and Indonesia in both the short run and long run. Also, empirical observations from the testing of environmental Kuznets curve (EKC) hypothesis imply that in the cases of Brazil, China and Indonesia, CO2 emissions will decrease over the time when income increases. So based on the EKC findings, it can be argued that these three countries should not take any actions or policies, which might have conservative impacts on income, in order to reduce their CO2 emissions. But in the case of India, where CO2 emissions and income were found to have a positive relationship, an increase in income over the time will not reduce CO2 emissions in the country.
This research investigates the health impacts and access to health services by children who are engaged in waste collection in Dhaka, the capital city of Bangladesh. The relevant qualitative data were collected through expert interviews and personal observations, while quantitative data were gathered through a face-to-face questionnaire survey given to 50 street children who collected waste at the landfill site located in Dhaka city's Matuail area. The results indicate that 94% of these children have suffered from many health problems, such as fever and fatigue due to tiredness, dizziness, and vomiting. Consequently, a significant portion of their daily income is spent on medical treatment. This study suggests that the waste collection system must integrate modern technological, health and environmental resources so that: firstly, they do not harm waste collectors; and secondly, rehabilitate the street children and give them better access to acceptable basic amenities. This is a priority the city authorities.
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