A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions

Bangladesh's recent doorway to the spectacular growth trajectory is largely associated with the shared contributions of globalization, FDI, trade, economic growth, urbanization, energy consumption, innovation, and institutional quality that affect its natural environment. Earlier studies hardly incorporated these dynamics together especially innovation and institutional quality to examine their impacts on environmental degradation in Bangladesh. This study attempts to scrutinize the effect of globalization, foreign direct investment, economic growth, trade, innovation, urbanization, and energy consumption on CO2 emissions in the presence of institutional quality in Bangladesh over the period 1972-2016 by utilizing dynamic ARDL simulations' model by Jordan and Philips (2018). The investigated results depict that globalization; foreign direct investment, and innovation have a negative effect on CO2 emissions in improving environmental quality while economic growth, trade, energy consumption, and urbanization positively impact CO2 emissions and hence stimulate environmental degradation both in the long and short run. Besides, institutional quality measured by the political terror scale (PTS) affects CO2 emissions positively and thereby degrades the quality of the environment in both the long and short run. Therefore, policy implication should go toward encouraging globalization, foreign direct investment and innovation; and the sensible utilization of income growth, trade potentials, energy consumption, urbanization and institution is required for the sake of environmental quality in Bangladesh.

Impact of globalization, foreign direct investment, and energy consumption on CO 2 emissions in Bangladesh: Does institutional quality matter?

Impact of economic policy uncertainty on CO2 emissions in the US: Evidence from bootstrap ARDL approach

Improving environmental quality across South Asia has become one of the utmost important policy agendas of the concerned governments. The susceptibility of the majority of the South Asian countries to multifaceted climate change adversities has motivated the need to identify the factors that can function to ensure environmental sustainability within this region. Although several studies have highlighted the importance of globalization and cleaner energy use in tackling the environmental woes of the South Asian countries, very little is known regarding the impacts of regional trade and renewable energy transition in this regard. Hence, this paper aims to scrutinize the effects of enhancing intra-regional trade integration and undergoing renewable energy transition on per capita carbon dioxide emissions in the context of six South Asian nations between 1990 and 2016. Besides, the impacts of economic growth, financial development, and urbanization on carbon dioxide emissions are also examined. The results from the recently developed cross-sectionally augmented autoregressive distributed lag regression approach, accounting for cross-sectional dependency and slope heterogeneity issues, reveal that facilitating trade among the South Asian neighbors reduces carbon emissions both in the short-and long run. Moreover, enhancing the share of renewable energy in the aggregate energy consumption figures is also found to reduce carbon dioxide emissions in both the short-and long-run. Furthermore, both regional trade integration and renewable energy transition are found to jointly reduce carbon dioxide emissions in South Asia. The results also authenticate the existence of the environmental Kuznets curve hypothesis while financial development and urbanization are found to boost carbon dioxide emissions only in the long run. Hence, the findings from this study impose key policy takeaways concerning environmental sustainability within South Asia.

The effects of regional trade integration and renewable energy transition on environmental quality: Evidence from South Asian neighbors?

Due to rapid economic growth and development, human demand for natural resources is growing in Bangladesh, which causes climate change, loss of biodiversity, soil degradation, and environmental hazard. Few studies have been conducted to investigate the determinants of ecological footprint and air quality (PM2.5) in Bangladesh between 1990 and 2016. This paper also investigates the existence EKC hypothesis in both ecological footprint and PM2.5 case. Single structural break analysis has employed to know the break point while estimating integration of each variable. After estimating the integration, we have employed ARDL bound testing approach to co-integration to show the long run relationship among the urbanization, natural resources, population density, economic growth, ecological footprint and PM2.5. For the robustness about the long run relationship among the variables, we also employ Bayer and Hanck joint co-integration. The results from both models demonstrate that urbanization, population density and energy consumption are major determinants of ecological footprint and PM2.5. However, technological innovation and natural resources are reducing the ecological footprint and PM2.5. The both the models provide evidence of existence of EKC hypothesis in case of Bangladesh. This study also has suggested some important policy implications regarding the environmental sustainability. 

Determinants of Ecological Footprint and PM2.5: Role of Urbanization, Natural Resources and Technological Innovation

Effects of renewable and non-renewable energy consumption on CO2 emissions in India: Empirical evidence from disaggregated data analysis

The study examined the relationship between some macro-economic variables and unemployment in India, it focuses on the impact of some macroeconomic variables on unemployment for the period 1991-2017.Cointegration test and its associated vector error correction model (VECM) and Granger causality test were used in the analysis. The variables such as unemployment rate (UNEMP), real gross domestic product (RGDP) used as common proxy for economic growth, consumer price index used as proxy for inflation, Gross fixed capital formation, literacy rate and labour force were employed in the investigation. Stationarity test was conducted through the application of the Augmented Dickey - Fuller (ADF) test, and the results indicated that all the variables became stationary after first differencing. Furthermore, the result of the Johansen cointegration test revealed that significant long run relationship exists among UNEMP, GDP, INFL, LF, LR and GFCF. Similarly, VECM shows that the economic unemployment of India is somewhat predictable by the given explanatory variables. In the VECM, intercept β_0 is positive 0.147108 and significant at 1% level indicating overall unemployment’s increases proportionately during that period. Finally, the result of the Granger causality test indicated unidirectional relationship between UNEMP and RGDP with causality running from RGDP to UNEMP. From gross domestic product, domestic private investment (GFCF) and labour force significantly causing unemployment as per there probability value. There is bi-directional Granger causality between labour force and unemployment Based on these findings, the study therefore recommends that government should as a matter of urgency create more employment opportunities in order to absorb the teeming population of the unemployed work force in the country through modernization of the agricultural sector, bring in modern equipment in the facilities of agriculture to make the sector more attractive to all citizens despite one’s qualifications and profession.

Jayantee Sahoo

Papers

Effects of renewable and non-renewable energy consumption on CO2 emissions in India: Empirical evidence from disaggregated data analysis

The relationship between unemployment and some macroeconomic variables: Empirical evidence from India