Green technology innovation is imperative to sustainable and environmentally sound economic development and is currently facing increasingly serious environmental threats. However, existing research has overlooked the uncertainties in economic policies. Based on the logical relationship between environmental regulation, economic policy uncertainty, and green technology innovation, this study empirically analyzed the quantitative relationship among these three variables using the xed-effect panel method and provincial panel data from 2000 to 2017 for 30 administrative regions of China. The results show that environmental regulation is positively correlated with green innovation, whereas economic policy uncertainty has a negative in uence on green innovation, thereby regulating the relationship between the remaining two factors. Moreover, considerable regional heterogeneity exists in these causal in uences, i.e., environmental regulation promotes green innovation in the eastern and middle regions but not signi cantly in the west. The uncertainty actively moderates the impact of environmental regulation on green innovation in all regions with an adjustment coe cient of approximately 0.8; however, it inhibits green innovation in different degrees, especially in the eastern and middle regions. Based on empirical results, we conclude that strict and appropriate environmental regulations are necessary and effective in China to encourage green technology innovation, especially in regions with uncertain economic policies.
Environmental tobacco smoke (ETS) and outdoor air pollution had independent adverse effects on respiratory health of non-smoking women and improvement in air quality had produced some but non-significant benefits.
In this paper, we extend the Johansen-Ledoit-Sornette (JLS) model by introducing fundamental economic factors in China (including the interest rate and deposit reserve rate) and the historical volatilities of targeted and US equity indices into the original model, which is a flexible tool to detect bubbles and predict regime changes in financial markets. We then derive a general method to incorporate these selected factors in addition to the log-periodic power law signature of herding and compare the prediction accuracy of the critical time between the original and the new JLS models (termed the JLS-factor model) by applying these two models to fit two well-known Chinese stock indices in three bubble periods. The results show that the JLS-factor model with Chinese characteristics successfully depicts the evolutions of bubbles and “antibubbles” and constructs efficient end-of-bubble signals for all bubbles in Chinese stock markets. In addition, the results of standard statistical tests demonstrate the excellent explanatory power of these additive factors and confirm that the new JLS model provides useful improvements over the standard JLS model.
Green technology innovation is imperative to sustainable and environmentally sound economic development and is currently facing increasingly serious environmental threats. However, existing research has overlooked the uncertainties in economic policies. Based on the logical relationship between environmental regulation, economic policy uncertainty, and green technology innovation, this study empirically analyzed the quantitative relationship among these three variables using the fixed-effect panel method and provincial panel data from 2000 to 2017 for 30 administrative regions of China. The results show that environmental regulation is positively correlated with green innovation, whereas economic policy uncertainty has a negative influence on green innovation, thereby regulating the relationship between the remaining two factors. Moreover, considerable regional heterogeneity exists in these causal influences, i.e., environmental regulation promotes green innovation in the eastern and middle regions but not significantly in the west. The uncertainty actively moderates the impact of environmental regulation on green innovation in all regions with an adjustment coefficient of approximately 0.8; however, it inhibits green innovation in different degrees, especially in the eastern and middle regions. Based on empirical results, we conclude that strict and appropriate environmental regulations are necessary and effective in China to encourage green technology innovation, especially in regions with uncertain economic policies.
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