This study explores the impact of environmental policies and human development on the CO2 emissions for the period of 1995–2015 in the Group of Seven and BRICS economies in the long run through panel cointegration and causality tests. The causality analysis revealed a bilateral causality between environmental stringency policies and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and a unilateral causality from CO2 emissions to the environmental stringency policies for Canada, China, and France. On the other hand, the analysis showed a bilateral causality between human development and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and unilateral causality from CO2 emissions to human development in Brazil, Canada, China, and France. Furthermore, the cointegration analysis indicated that both environmental stringency policies and human development had a decreasing impact on the CO2 emissions.
The Bornova Flysch Zone (BFZ), located between the Menderes Massif and the İzmir-Ankara Suture in westernmost Anatolia (Turkey), forms the westernmost part of the Anatolide-Taurides. The BFZ comprises intensely sheared Upper Cretaceous-Palaeocene matrix and blocks of various origins. The matrix of the BFZ is mainly made up of unfossiliferous flysch-type sediments (alternations of sandstones and shales). In Bornova (İzmir, western Turkey) and its surroundings, these clastics locally include planktic foraminiferabearing pelagic micritic limestone and calcareous shale lenses and interbeds (Beytitepe Limestone). As a result of studies focusing on the planktic foraminifera-bearing pelagic interlayers in three areas (Gökdere, Işıklar and Kocaçay areas) around Bornova, a detailed planktic foraminiferal biostratigraphy of the rocks is documented for the first time. The thickness of the laminated micritic limestones attains 360 m in the Gökdere area. Occurrences of late Maastrichtian species such as Abathomphalus mayaroensis (Bolli), Contusotruncana contusa (Cushman), Globotruncanita conica (White) and Racemiguembelina fructicosa (Egger) within planktic foraminifera assemblages obtained from the laminated micritic limestones and red calcareous shales in the three areas suggest a late Maastrichtian age for these rocks. The occurrence of various species of Globanomalina, Morozovella, Igorina and Parasubbotina within the calcareous shales in the Işıklar area suggests a late Palaeocene age. The Kocaçay area has well-preserved outcrops showing the stratigraphy of the matrix, despite the more complex geology. The upper Maastrichtian laminated micritic limestones are gradationally overlain by upper Maastrichtian calcareous shales. The calcareous shales are represented by rich planktic foraminiferal assemblages and include blocks derived from laminated micritic limestones. The upper Mastrichtian calcareous shales are overlain by Palaeocene red calcareous shales. Poor assemblages including Parasubbotina varianta (Subbotina), Subbotina triangularis (White), Subbotina cf. velascoensis (Cushman), Globanomalina compressa (Plummer) and Globanomalina planoconica (Subbotina) indicate a late Palaeocene age for the lower part and a latest Palaeocene age for the upper part of the calcareous shale sequence. Therefore, the age of conglomerates and flysch overlying the calcareous shales should be latest Palaeocene or younger in the Kocaçay area.
Education is one of the Sustainable Development Goals (SDGs) of the United Nations and is also a vital factor for nearly all the other SDGs. Therefore, factors underlying educational attainment are crucial for achieving the SDGs by 2030. In this context, the financial system has become critical in building various schools and covering educational expenditures such as teachers’ salaries, teaching materials, and training. This paper uses static and dynamic regression methods to study the impact of financial sector development, remittances, real GDP per capita, information and communications technologies (ICT) development, and globalization on educational attainment in 18 emerging economies over the 2000–2020 period. The results indicate that financial development, remittances, real GDP per capita, ICT development, and globalization positively impact educational attainment. Real GDP per capita, ICT development, globalization, and financial development have the highest impact of these factors. In contrast, remittances have a limited positive influence on educational attainment compared with other variables.
Environmental sustainability is one of three pillars of sustainability. However, a significant worldwide deterioration in the environment has been experienced since the Industrial Revolution, but the efforts to protect the environment date back to the 1970s. In this context, many economic and non-economic factors underlying environmental degradation have been investigated until today, but the influence of economic freedom indicators and education on the environment have been relatively less analyzed and the researchers have mainly focused on the influence of economic and institutional variables on the environment. Therefore, this paper investigates the reciprocal interplay among economic freedom indicators, education, and environment in EU member states over the 2000–2018 term by using a causality test with cross-sectional dependency and heterogeneity and taking the research gap into consideration. The causality analysis indicates that market-oriented economic structure and education can be beneficial in combatting environmental degradation.
Electricity load forecasting is crucial for electricity generation companies, distributors and other electricity market participants. In this study, several forecasting techniques are applied to time series modeling and forecasting of the hourly loads. Seasonal grey model, support vector regression, random forests, seasonal ARIMA and linear regression are benchmarked on seven data sets. A rolling forecasting model is developed and 24 hours of the next day is predicted for the last 14 days of each data set. This day-ahead forecasting model is especially important in day-ahead market activities and plant scheduling operations. Experimental results indicate that support vector regression and seasonal grey model outperforms other approaches in terms of forecast accuracy for day-ahead load forecasting.
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