This study examines the impact of economic growth, corruption, health, and poverty on environmental degradation for three countries from ASEAN, namely Indonesia, Malaysia, and Thailand using annual data over the period of 1994-2014. The relationship between environmental degradation (pollution) by carbon dioxide (CO2) emissions and economic growth is examined along with some other variables, namely health expenditure, poverty, agriculture value added growth, industrial value added growth, and corruption. The ordinary least squares (OLS) method is applied as an analytical technique for parameter estimation. The empirical results reveal that almost all variables are statistically significant at the 5% level of significance, whereby test rejects the null hypotheses of non-cointegration, indicating that all variables play an important role in affecting the environment across countries. Empirical results also indicate that economic growth has significant positive impact, while health expenditures show significantly negative impact on the environment. Corruption has significant positive effect on environment in the case of Malaysia; while in the case of Indonesia and Thailand, it has insignificant results. However, for the individual analysis across countries, the regression estimate suggests that economic growth has a significant positive relationship with environment for Indonesia, while it is found insignificantly negative and positive in the case of Malaysia and Thailand, respectively, during the period under the study. Empirical findings of the study suggest that policy-makers require to make technological-friendly environment sequentially to surmount unregulated pollution, steady population transfers from rural areas to urban areas are also important, and poverty alleviation and better health provision can also help to improve the environment.
We explore the local dynamics, flip bifurcation, chaos control and existence of periodic point of the predator-prey model with Allee effect on the prey population in the interior of $\mathbb{R}^*{_+^2}$. Nu-merical simulations not only exhibit our results with the theoretical analysis but also show the complex dynamical behaviors, such as the period-2, 8, 11, 17, 20 and 22 orbits. Further, maximum Lyapunov exponents as well as fractal dimensions are also computed numerically to show the presence of chaotic behavior in the model under consideration.
The main purpose of this work is to analyze the impact of environmental degradation proxied by CO2 emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO2 emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO2 emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO2 emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare.