Effect of foreign direct investment on CO2 emission with the role of globalization, institutional quality with pooled mean group panel ARDL.

This study utilized the Pooled Mean Group estimator to investigate the effect of renewable energy consumption, electricity consumption, economic growth, institutional quality, and globalization on carbon dioxide emission with an updated dataset for 10 economies for the time period from 1985 to 2018. Results of Harris-Tzavalis's test and Levin-Lin-Chu's test show that the utilized regressand and regressors are stationary at I(0) and I(I) that conform that the pooled mean group estimator panel ARDL can be utilized. Results of Kao and Pedroni cointegration tests show that cointegration exists amongst the variables. Empirical results of pooled mean group (PMG) revealed that renewable energy consumption helps to diminish the environmental degradation while foreign direct investment, electricity consumption, and economic growth and institutional quality positively affect the degradation of the environment. The findings show that globalization in the long run adversely and significantly influences the environmental degradation; globalization reduces the environmental degradation in the long run while in the short run, globalization positively and significantly influences the environmental degradation. Results of the panel VAR and VECM model indicate electricity consumption and institutional quality, and globalization positively affects environmental degradation. Further policies are recommended based on the findings.

The impact of macroeconomic and financial development on carbon dioxide emissions in Pakistan: evidence with a novel dynamic simulated ARDL approach.

This paper has empirically explored the impact of macroeconomic and financial development on CO2 emissions by utilizing a novel dynamic simulated ARDL model for annual time series data from 1982 to 2018 for Pakistan. The results of a novel dynamic simulated ARDL disclosed that the growth of stock market, FDI, economic growth, and consumption of oil wield a positive impact on CO2 emission, while domestic credit exerts a negative effect on CO2 emission both in the short and the long run in Pakistan. The stock market development and domestic credit wield a significant influence on carbon dioxide emission in Pakistan both in the long and the short run. FDI exerts significant impact only in the long run, while economic growth and consumption of oil wield significant impact only in the short run on CO2 emission in Pakistan. This study opens up new visions for the economy of Pakistan to sustain financial and economic growth by protecting environment from pollution through its efficient national environmental policy, fiscal policy, and monetary policy.

Impact of globalization, economic factors and energy consumption on CO2 emissions in Pakistan.

This research scrutinizes the impact of globalization, economic factors and energy consumption on CO2 emissions in Pakistan from 1971 to 2016 by utilizing dynamic ARDL simulations model Jordan and Philips (2018). Dynamic ARDL simulations model has capability to predict the actual positive and negative change in the independent variables and its effect on the dependent variable. The examined results of dynamic ARDL simulations indicates that Energy consumption, financial development, trade, foreign direct investment, economic globalization, social globalization and political globalization have positive effect on CO2 emissions in Pakistan while urbanization, economic growth and innovation have negative effect on CO2 emissions in Pakistan while in the short run the examined results of dynamic ARDL simulations indicate that energy consumption, urbanization, economic growth, financial development, economic globalization, social globalization and political globalization have positive effect on CO2 emissions in Pakistan while trade, innovation and foreign direct investment have negative effect on CO2 emissions. Based on the results of this study policy implications are suggested for Pakistan.

Asymmetric impact of oil prices on stock returns in Shanghai stock exchange: Evidence from asymmetric ARDL model.

This study scrutinized the asymmetric impact of oil prices on stock returns in Shanghai stock exchange with data (January 2000 to December 2018) by using asymmetric ARDL model. The examined results of asymmetric autoregressive distributed lag model indicate that cointegration exists between the oil prices and the stock returns. Results of asymmetric autoregressive distributed lag model confirm that both in the long run and the short run increase in oil prices have a negative impact on the stock returns of Shanghai stock exchange while decrease in the oil prices has a positive impact on the stock returns. The examined results of this study recommend that oil prices dynamically contribute incompetence in stock prices in such a way that impact the profits of investors in stock market.

Effect of energy consumption and economic growth on carbon dioxide emissions in Pakistan with dynamic ARDL simulations approach.

Environmental degradations are mainly caused by the use of different energy resources for economic growth. This research examined the influence of energy consumption (coal consumption, oil consumption, and gas consumption) and economic growth on environmental degradation in Pakistan. This research used newly developed method dynamic ARDL simulations to scrutinize the actual influence of positive and negative change in the use of coal consumption, oil consumption, and gas consumption for energy and economic growth on environmental degradation in Pakistan. The examined results of dynamic ARDL indicate that economic growth, coal consumption, oil consumption, and natural gas consumption have positive impact on the environmental degradations in Pakistan both in short run and long run. It is suggested that environmental degradations can be reduced by promoting renewable energy sources for energy.