Does technology innovation matter for environmental pollution? Testing the pollution halo/haven hypothesis for Asian countries

Can new urbanization pilot policies promote green technology innovation in cities: Empirical evidence from China

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities.

Impacts of pilot carbon emission trading policies on urban environmental pollution: Evidence from China

The trading of carbon emissions is a crucial regulatory method to address environmental pollution issues. This study takes China's carbon emission trading pilot policy established in 2013 as a quasi-natural experiment and uses the DID model to empirically test the urban panel data from 2006 to 2019. The results show that the carbon emission trading pilot policy can effectively reduce urban environmental pollution, and this effect is more noticeable in mid-western cities, northern cities, cities with fewer resources, and large-scale cities. In addition, to address the urban environmental pollution problem through this policy, the government is encouraged to raise its environmental protection awareness and put more effort into the innovation of technology. In general, this study uses carbon emission trading policies from China to confirm that market-based incentive environmental regulation tools can effectively reduce environmental pollution in urban areas. These findings can provide more theoretical support and empirical evidence for the government to use mechanisms of the market to effectively solve pollution problems, improve ecological environment quality, and accelerate the realization of green economy.

History and future of water footprint in the Yangtze River Delta of China

Quantifying the drivers of water footprint evolution in the Yangtze River Delta is vital for the optimization of China's total water consumption. The article aims to decompose and predict the water footprint of the Yangtze River Delta and provide policy recommendations for optimizing water use in the Yangtze River Delta. The paper applies the LMDI method to decompose the water footprint of the Yangtze River Delta and its provinces into five major drivers: water footprint structure, water use intensity, R&D scale, R&D efficiency, and population size. Furthermore, this paper combines scenario analysis and Monte Carlo simulation methods to predict the potential evolution trends of water footprint under the basic, general, and enhanced water conservation scenario, respectively. The results show that (1) the expansion of R&D scale is the main factor promoting the growth of water footprint, the improvement of R&D efficiency, and the reduction of water intensity are the main factors inhibiting the increase of water footprint, and the water footprint structure and population size have less influence on water footprint. (2) The evolution trend of water footprint of each province under three scenarios is different. Compared to the basic scenario, the water footprint decreases more in Shanghai, Zhejiang, and Anhui under the general and enhanced water conservation scenario. The increase in water footprint in Jiangsu under the enhanced scenario is smaller than that of the general water conservation scenario.

Determinants of ecological footprint in European countries: Fresh insight from Bayesian model averaging for panel data analysis

This study examines the determinants of the ecological footprint of production in European countries from 1992 to 2020. Using partial and semipartial correlation analyses and Bayesian Model Averaging (BMA) approach for the first time, the research identifies key variables affecting ecological footprint. Using Bayesian methods, posterior inclusion probabilities (PIPs) were calculated for each variable's coefficient estimates, revealing their relative importance. Biocapacity, energy consumption, industrialization, financial development, life expectancy, and globalization displayed notably high PIPs, indicating their strong influence on the ecological footprint. In addition, the study employs cointegration tests to examine the long-run relationship between ecological footprint and explanatory variables. The results indicate significant cointegration between these variables across panels, supported by various test statistics. In the Weighted Pooled DOLS estimation, biocapacity, energy consumption, and life expectancy significantly influence the ecological footprint, while industrialization, financial development, and globalization exert a comparatively smaller impact. Researchers and policymakers should consider these determinants for effective sustainable development planning. These findings underscore the intricate interplay of factors shaping the ecological footprint and offer insights for effective policy interventions towards sustainable development.

Does environmental regulation caused by air pollution reduce shadow banking for non-financial companies? Based on the exit perspective of implicit government guarantee

As China's economy enters the stage of high-quality development, the sustainability of development becomes increasingly important. Therefore, this study takes air quality index as the explanatory variable, the level of shadow banking as the explained variable, and environmental regulation as the intermediary variable to empirically study whether environmental regulation caused by air pollution will affect the shadow banking of non-financial enterprises. The findings suggest that air pollution is likely to strengthen environmental regulation, thereby reducing the level of shadow banking, as air pollution strengthens environmental regulation, leading to the reduction of implicit government guarantees, while enterprises tend to abandon or minimize reliance on these guarantees and reduce leverage. The mechanism test shows that the ESG performance of non-financial firms weakens the process by which air pollution reduces the degree of shadow banking of non-financial firms, while the short-sightedness of management enhances this process. Heterogeneity analysis shows that this process is more significant under the effect of market-driven environmental regulation and in private enterprises and enterprises in regions with large industrial scale. Therefore, the policy implication is that government should continue to strengthen environmental law enforcement in future supervision, as this can not only reduce pollution levels but also reduce systemic financial risks. Enterprises should also increase their sense of social responsibility.

Spatial-temporal characteristics of geological disaster resilience in poverty and disaster-prone areas in China: a case study of Ganzi Prefecture

Under the tremendous challenges of frequent disasters, disaster resilience is imperative for risk reduction and sustainable management in poverty and disaster-prone areas. Ganzi Prefecture has a complicated topography and vulnerable ecosystems. Geological disasters have historically been the most serious risks in the region. To fully understand the potential risks and strengthen resilience, the study investigates the resilience level of 18 counties in Ganzi. Firstly, the paper develops a multidimensional index system based on the Baseline Resilience Indicators for Communities (BRIC) framework. And the entropy weighting method is used to calculate Ganzi's disaster resilience level from the aspects of "society-economy-infrastructure-environment." Then, the study uses exploratory spatial data (ESDA) to analyze the spatial-temporal evolution of disaster resilience. Finally, Geodetector is used to investigate the main driving factors of disaster resilience and their interactions. The results indicated that Ganzi's disaster resilience had maintained an upward trend from 2011 to 2019, with significant spatial divergence, which shows high resilience in the southeast and low resilience in the northwest. The economic indicator is the driving factor in the spatial difference of disaster resilience, and the interaction factor has a significantly stronger explanatory power for resilience. Therefore, the government should strengthen ecotourism development to help alleviate poverty in special industries and promote synergistic regional development.

Trade of environmental versus non-environmental goods and carbon emissions in high and middle-income countries

The environmental goods and services industry consists of the activities that generate products and services to monitor, avoid, restrict, reduce, or repair environmental risk and decrease non-renewable energy resource usage. Although the environmental goods industry does not exist in many countries, mainly developing countries, through international trade, its impacts are reaching developing countries. This study examines the impact of environmental and non-environmental goods trade on emissions in high and middle-income countries. For empirical estimation, the panel ARDL model is applied using the data from 2007 to 2020. The results indicate that importing environmental goods decreases emissions while imports of non-environmental goods increase the emissions in high-income countries in the long run. It is found that imports of environmental goods in developing countries decrease emissions in both the short and long run. However, in the short run, the imports of non-environmental goods in developing countries have an insignificant impact on emissions.

The Impact of Fintech Development on Air Pollution

Over the past 40 years of reform and opening-up, China has achieved rapid economic and technological growth at the cost of severe air pollution. The emerging Fintech, as the result of financial institutions' adapting to the latest digital technology, might be a solution to reduce air pollution. This paper investigates the impact of Fintech development on air pollution using a two-factor fixed effects model based on data for prefecture-level cities in China from 2011 to 2017. The findings show that Fintech development can effectively reduce air pollution emissions, and this conclusion is proved to be robust throughout a series of tests. The mechanism analysis shows that Fintech reduces air pollution by promoting digital finance and green innovation.

Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

Digital transformation, industrial structure change, and economic growth motivation: An empirical analysis based on manufacturing industry in Yangtze River Delta

China is in a critical stage of economic growth mode transformation. The digital transformation of the manufacturing industry may create new impetus and new models for economic growth. Taking the manufacturing industry of 25 prefecture-level cities in the Yangtze River Delta region as the research object, we explore the digital transformation process of the manufacturing industry and verifies its theoretical mechanism of promoting economic growth through the industrial structure. A panel model based on the improved Feder two-sector model and a multiple mediating effect model are established to explore the dynamic mechanism of manufacturing digital transformation to promote economic growth through industrial restructuring. The results show that the digital transformation of the manufacturing industry in the Yangtze River Delta region of China is relatively high, and the speed of digital transformation has been accelerating in recent years. The digital transformation of the manufacturing industry can promote the change in industrial structure and form a new driving force for economic growth. The key is to improve the level of industrial structure and extend the length of the industrial chain. Based on these, we propose measures to promote the transformation and upgrading of industrial structure for the sustainable development of China's economy.

Spatio-temporal effect of provincial technological innovation on environmental pollution in China

The relationship between technological innovation (TL) and environmental pollution (EP) and its action mechanisms are complex and controversial aspects of discussion. Using the spatial autocorrelation analysis, standard deviation ellipse analysis, kernel density function, spatial econometric model, this study analyzed the spatial distribution, evolution characteristics, and influencing factors of the EP and TL from 2000 to 2020 in China. Results found there was a significant spatial autocorrelation between the EP and TL in 2000-2020. The standard deviation ellipse of EP was broadly distributed in the "southwest-northeast" direction, indicating that EP presented a trend of concentration in the direction of "southwest-northeast." The moving trajectory of the center of gravity for the EP in 2000-2020 was essentially moved from the northeast to southwest. Overall, the national level of TL exhibited a "north-south change, high in the east, and low in the west" trend. Regional differences were gradually expanding, and the polarization was evident. Regardless of using least squares method (OLS) or quantile regression (QR) models, TL, human capital (HC), and industrial structure (IS) all had an inhibitory effect on the EP at the effective significance level. Total population (TP), foreign direct investment (FDI), and local fiscal expenditure (LFE) were positively related to the EP.