The Impact of Human Capital on Green Technology Innovation-Moderating Role of Environmental Regulations

Environmental regulation influences urban land green use efficiency: Incentive or disincentive effect? Evidence from China

China's crude economic development has led to high pollution and inefficiency of urban land use. Environmental regulation (Er) is crucial for governments to promote green growth and efficient land use. Using a dataset of 271 cities in China from 2011 to 2020, this paper investigates the threshold effect of green innovation in science and technology and industrial structure optimization on Er impacts of urban land green use efficiency (Ulee). The results show that (1) Er positively affects Ulee. (2) There is a threshold effect of green innovation in science and technology (Gin) and industrial structure upgrading (Ind) in Er affecting Ulee, and the force decreases as the threshold value increases. (3) Within the examination of heterogeneity, the impact of Er on Ulee is more significant in eastern, high levels of urbanization and large cities, but the force of action is smaller. Based on the nonlinear force of Er, it is crucial to maximize the effectiveness of green land use by giving full play to the interactive synergistic effect of the "combination box" and dynamically and flexibly adjusting the intensity of Er according to the time, place, and state of urban development.

How does trade policy uncertainty affect green innovation in the USA and China? A nonlinear perspective

Green innovations are the most critical factor in promoting environmental sustainability worldwide. Trade can speed up the adoption of green innovations by facilitating the transfer of information, skills, and technology. However, trade policy uncertainty can create significant challenges for businesses investing in eco-innovations, leading to increased risk, reduced investment, and slower progress toward sustainable technologies. Recently, a growing number of researchers have shown their interest in finding the factors that can impact green innovations, but none have investigated the influence of trade policy uncertainty on green innovations in the USA and China. In addition, none of the past studies has relied on the nonlinear assumption. This analysis fills these gaps by examining the nonlinear impacts of trade policy uncertainty on eco-innovations in China and the USA over 2000Q1-2021Q4 by employing a nonlinear ARDL model. The finding reveals that a positive shock in trade policy uncertainty results in a decrease in green innovation in the USA and China, while a negative shock in trade policy uncertainty leads to an increase in green innovation in the USA over the long run. The nonlinear models also indicate that a positive shock in trade policy uncertainty harms green innovation in both the USA and China in the short run. The robustness of these results is confirmed by the NQARDL model, which confirms that an upsurge in trade policy uncertainty lowers green innovation in most quantiles in the USA and China in the short and long run. Conversely, negative shocks in trade policy uncertainty stimulate green innovation at most quantiles in both China and the USA, in the short and long run. Thus, policymakers need to consider the potential impact of trade policies on eco-innovations and work to create stable and predictable trade environments that support the growth of renewable technologies and other sustainable solutions.