Environmental regulation and marine economic resilience: An institutional synergy perspective.

Growing economic and industrial activities have put a large strain on the marine environment and ecosystem, presenting the marine economy with a tradeoff between economic expansion and environmental conservation. Though the Porter hypothesis depicts a win-win situation, it is crucial to consider the conditions under which environmental regulations generate positive effects. This paper is to study how the synergy between market-based and government-based environmental regulations affects marine economic resilience, whereas maintaining economic resilience is a prerequisite for promoting innovation and productivity. The findings indicate that each 1 % increase in the synergistic level of environmental regulations resulted in a 0.234 % improvement in marine economic resilience. The heterogeneity tests indicate that the relationship is still significant if the marine economy characterizes high industrial diversity, high industrial upgrading, and large scale, while environmental regulation in coastal provinces that marine industrial structure is not advanced negatively affects marine economic resilience.

Nonlinear impact of digital economy on carbon intensity: the moderating role of low-carbon regulation.

The development of the digital economy is an effective way to mitigate the carbon emission problem in the broader setting of the significant data era and green development. Based on the panel data of 271 cities in China from 2011 to 2019, this paper constructs a bidirectional fixed model to analyze the nonlinear effect of the digital economy (DE) on carbon intensity (CI) and the moderating role of low-carbon regulation from theoretical and empirical perspectives. The results show that (1) DE has an enormous inverted U-shaped impact on CI. The findings remain after introducing instrumental variables to mitigate endogeneity and robustness tests. (2) Low-carbon regulation (CP) can strengthen the inverted U-shaped impact between the two and shift the inflection point to the left. (3) Heterogeneity analysis shows that the inverted U-shaped effect of DE on CI is more significant in the central and western regions, high human capital (HC) regions, and high urbanization regions. (4) The mediating effect of energy mix (EM) and green technology innovation (GTI) still hold after introducing instrumental variables to alleviate the endogenous effect of the intermediary effect. This study suggests that the adoption of carbon emission reduction strategies, which will more effectively lower carbon intensity CI, should go hand in hand with the development of DE.

What drives the growth of china's mariculture production? An empirical analysis of its coastal regions from 1983 to 2019.

China's mariculture (i.e., seafood farming in the ocean) production has grown rapidly. It ranks the first in the world and has made a huge contribution to solving human food security and nutrition issues. This study aimed to examine the development process of China's mariculture since 1983, clarify the main driving factors for the growth of mariculture production, and analyze whether China's experience can help other major producers in the world. Using the data on China's 10 coastal regions, this study applied the Logarithmic Mean Divisia Index (LMDI) from both the national and regional perspectives to analyze the main driving factors for the growth of China's mariculture production from 1983 to 2019. The results indicate that China's total mariculture production showed an overall upward trend and the major driving factor for the increase changed from the initial labor force to unit production. The primary factor for the increase in the Circum-Bohai Sea was labor, whereas that in the South China Sea, Yellow Sea and East China Sea was unit production. China's mariculture production has expanded from resource-driven to efficiency-driven. This study has practical significance for policy formulation and the future development direction of mariculture. This study provides a universally applicable methodology, and has reference significance for the world's major mariculture producers to further study the sustainable growth of mariculture production.

How does environmental regulation influence green technological innovation? Moderating effect of green finance.

The main factor behind green economic development is green technology innovation (GTI). Environmental regulation and green finance (GF), as important ways to promote ecological civilization construction, run through the entire procedure of GTI. The purpose of this study is to investigate the influence of heterogeneous environmental regulation on GTI and the moderating effect of GF on GTI from both theoretical and empirical perspectives, to provide useful ideas for China's economic reform path selection and environmental governance system optimization. This paper uses information from 30 provinces between 2002 and 2019, and a bidirectional fixed model was constructed. The results show that: First, regulatory environmental regulation (ER1), legal environmental regulation (ER2), and economic environmental regulation (ER3) all have greatly boosted the degree of GTI in each province. Second, GF acts as a highly effective moderator between heterogeneous environmental regulation and GTI. Finally, this article investigates how GF can act as a moderator in various circumstances. The beneficial moderating effect of it is found to be more pronounced in inland areas, areas with weak spending on research and development, and areas with high energy consumption. These research results provide valuable references for accelerating the green development process in China.

Can environmental regulation promote the green output bias in China's mariculture?

The green output bias of technological progress is the key factor driving the green transformation of mariculture. This study considers whether environmental regulation can promote the green output bias. Utilizing data envelopment analysis (DEA), we decomposed the green output biased technological progress index (OBTC) and constructed the index to measure the output bias between output value and pollutant emissions. The results show spatial and temporal differences in the green output bias, with different bias values for three major Chinese coastal regions during the study period. As the bias value mainly fluctuates around the zero value, the degree of green output bias must be enhanced. Considering the heterogeneity of environmental regulation, we empirically study the relation that exists between environmental regulation and green output bias. Our findings indicate a U-shaped relation between two categories of environmental regulation and the green output bias. Green technology partially intermediates the mechanisms by which these environmental regulations influence green output bias. Our results have implications for policymakers and other stakeholders for strengthening environmental regulation, promoting green technological innovation, and the scientific planning of the species and scale of mariculture to promote sustainable development.

Study on green output bias of China's mariculture technological progress.

With the rapid development of mariculture, environmental pollution is becoming more and more serious. It is particularly important to study the green output bias of technological progress for the long-term sustainable development of mariculture. Based on the input-output data of the mariculture in 10 Chinese coastal areas from 2008 to 2018, the DEA-Malmquist index decomposition method is used to calculate the output-biased technological progress index and combines with the change of marginal substitution rate of output factors in different periods to identify the bias of technological progress between output factors and analyze the green output bias of mariculture technological progress. The results show that green technological progress is a crucial factor affecting green total factor productivity's growth in China's mariculture. During the study period, the number of regions where technological progress tends to reduce pollutant emissions shows a fluctuating upward trend, and the degree of technological progress toward green output is high. There are obvious differences among regions. The green output bias of technological progress in the South China Sea area is the highest, followed by the East China Sea area, and the Bohai Sea area is poor. Specifically, the green output bias of technological progress in Fujian, Guangdong, and Hainan is higher, while the green output bias of technological progress in Tianjin, Hebei, Shandong, and Guangxi is lower. According to the research results, corresponding policy suggestions are provided to realize the green and sustainable development of China's mariculture.