Can green finance improve eco-efficiency? New Insights from China.

Achieving economic development and ecological protection simultaneously is an inevitable selection for sustainable development in today's world, so it is crucial to improve eco-efficiency (EE). According to Chinese panel data at the provincial level between 2010 and 2020, this research explores the nexus between green finance (GF) and EE. The results denote that GF can significantly improve EE, and the higher the level of EE, the stronger the effect of improvement. The upgrading of industrial structure, optimization of energy structure, enterprises' concern for environmental protection and the public's attention to the environment are all favorable factors that can enhance the promotion effect of GF on EE. Additionally, this facilitation can only be played under a good external environment and mature internal conditions. Our findings can provide new insights for improving EE by developing GF.

Construction of China's food security evaluation index system and spatiotemporal evolution.

Food security is a vital material foundation for a nation's development and has been a topic of significant concern on the international stage in recent years. With a population exceeding 1.4 billion, China is not only a major producer but also a substantial consumer of food. Ensuring food security in China is not only a top priority for its socio-economic development but also a driving force in maintaining the stability of the global food supply chain and reducing the number of hungry people worldwide. However, a lack of comprehensive research into the Chinese food security system remains. This study addresses this gap by constructing a comprehensive evaluation framework encompassing four dimensions: food supply, accessibility, production stability, and sustainability. Utilizing the Moran's Index and generating LISA (Local Indicators of Spatial Association) maps, we analyze the spatial correlations of food security. The Dagum Gini coefficient and kernel density estimation are applied to assess heterogeneity and spatial disparities. Furthermore, this research employs the Exponential Smoothing (ETS) model to forecast food security trends. The findings reveal that the overall composite food security score exhibited fluctuations, initially increasing and reaching its peak of 0.407 in 2003, followed by a subsequent sharp decline after 2019. Spatially, food security exhibits correlations, with the Huang-Huai-Hai Plain and Northeast regions consistently showing high-high clustering. In contrast, the Western and Southern regions exhibit low-low clustering at specific periods. The Dagum Gini coefficient indicates that overall food security disparities are relatively small. However, these disparities have gradually expanded in recent years, with inter-group differences becoming predominant after 2005. As indicated by the kernel density estimation, the dynamic distribution of food security initially widens and then narrows, suggesting a shift from dispersed to concentrated data distribution. This phenomenon is accompanied by polarization and convergence trends, particularly evident after 2015. According to the ETS model, the study forecasts a substantial risk of declining food security in China over the next decade, largely influenced by the ongoing pandemic. In conclusion, this research provides a comprehensive assessment of the changing status of food security in China. It offers early warnings through predictive analysis, addressing the existing research gaps in the field of food security.

What impacts do green bonds have on carbon emissions and how? A dynamic spatial perspective in China.

Green bonds are adopted to exclusively finance or refinance green projects and thus is an important policy instrument for sustainable development. The development of these eco-friendly projects benefits the reduction of carbon emission. What impacts do green bonds have on carbon emission intensity and how? This issue needs to be revealed, including the dynamic spatial interactive rules and regional heterogeneity. This is especially true for China, with its vast territory and a short history of green bonds. Different with existing literature, this paper collects the data of the amount of green bond issued in each province in China rather than the policy dummy variable of green bond. The spatio-temporal interactions of both the impact of green bonds and the related mechanisms are studied. A dynamic spatial Durbin model (DSDM) combined with a STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model reveals the negative impacts of green bonds on carbon emissions and the spatio-temporal interactions. On this basis, the mediation model is introduced to clarify the three impact mechanisms of green bonds and find the predominant role of technology mechanism. In addition, different characteristics in spatial interactive rules and impact mechanisms of green bonds are found in various regions of China. Finally, the study proposes some policy recommendations on how to effectively reduce carbon emissions with green bonds.

The role of GICT and environmental regulation in affecting ecological footprint.

Research studies have recently diverted attention towards the determinant of ecological footprints, but related issues have not provided consistent results. Based on the IPAT model (environmental impact (I) is decomposed into three elements: population (P), affluence (A, economic growth), and technology level (T)), this paper empirically explores the validity of the green information and communication technology (GICT)-induced environmental Kuznets curve (EKC) hypothesis. The research applies a quantile regression (QR) that tests over 95 countries' panel data for the period 2000-2017 by using six types of ecological footprint (EF) as environmental degradation indicators and environmental regulations (ERs) as interaction variables. We confirm the vital role that GICT plays in lessening cropland, forest area, and grazing land, while increasing its impact on built-up land. Additionally, the findings partially support the existence of an inverted U-shaped GICT-induced environmental EKC hypothesis for a decreasing impact on cropland, forest area, and grazing land via consideration of non-market-based ER as the interaction term. GICT does not notably reduce carbon-absorption land usage; however, improvements of GICT and non-market-based ER in those nations have been accompanied by lower environmental degradation.

What does export diversification do for energy demand? Evidence from the Global North.

This paper contributes to the trade-energy literature by examining the effect of export product diversification on the energy demand of 30 countries located in the Global North over the period 1980-2014. A nonparametric time-varying coefficient panel data model with fixed effects is employed for its ability to produce robust outcomes in the presence of parameter instabilities, nonstationarity, regime shifts, and time variations. As a second step, the paper also utilizes the nonparametric fixed effects extension of Driscoll and Kraay, which is robust to spatial/cross-sectional dependence, as well as to autocorrelation and heteroscedasticity. The results indicate that export diversification lowers overall energy demand in the Global North, and the size of the impact has been on a gradual increase over the years. The paper concludes that if a conscious effort is made to ensure that product diversification is towards energy-efficient goods, export product diversification can serve as a useful strategy for managing energy consumption and mitigating its negative environmental effects.

The asymmetric effect of temperature, exchange rate, metals, and investor sentiments on solar stock price performance in China: evidence from QARDL approach.

The study investigates the asymmetric effect of temperature, exchange rate, metals (rare metals and electrical conductors), and investor sentiments on solar stock price performance in China. The novel econometric techniques, i.e., QARDL (quantile autoregressive distributive lag) approach and Granger causality-in-quantiles to analyze the results. In both short- and long-run estimations, the findings suggest that rare metals (cadmium, germanium, indium, and selenium) and electrical conductors (silver, aluminum, and copper) have significant and positive linkage with solar energy stocks at different quantiles based on bullish, bearish, and normal market conditions. On the other hand, negative effects are found for temperature, RMB exchange rate, and investor sentiments in both the short- and long-run. In the short run, the effect of exchange rate varies across different quantiles but it confines to only lower quantiles (bearish market condition) in the longer run. Solar stocks are more prone to investor sentiments under higher quantiles (bullish market conditions). Lastly, we find that temperature is not merely a behavioral anomaly for the solar energy market as it spreads across middle quantiles (normal market conditions) in the longer run. The findings of Granger causality in quantiles further confirm the results of QARDL.

Optimal behavior of environmental regulations to reduce carbon emissions: A simulation-based dual green gaming model.

As carbon emissions are one of the major problems of an emission-generating firm (EGF), there is a dire need to reduce them, and so this study fills this gap in the literature by considering the optimal behavior of environmental policies. This research develops policy measures under a duopoly game model such as carbon emission tax (CET) and subsidy on green investment (SGI). Additionally, we formulate a simulation model to measure the optimal behavior of CET, SGI, and production quantity to maximize profit and carbon emission reduction. The findings indicate that when green investment decreases, the EGFs are better able to pay CET and the government is also capable of providing SGI. Moreover, a lower unit production cost reduces more carbon emissions versus a higher unit production cost. In this way, the government receives revenue due to CET implementation and an EGF obtains revenue due to SGI. Both parties gain benefits at the same time and play important roles in cutting carbon emissions to make the environment clean. This study helps governments in finding their own optimal CET and SGI. An optimal SGI assists decision-makers at reducing carbon emissions and targeting profit maximization.

Environmental regulation, innovation capability, and green total factor productivity: New evidence from China.

Given China' rapid transformation, its economy is currently experiencing a change from a rugged development style to a sustainable development style with green development being critical to this transformation. Increasing green total factor productivity (GTFP) is now considered one of the significant signs of economic growth. With increasingly stricter environmental laws and regulations and a broad application of innovation capability (ICY) in modern life, this research investigates the impact mechanisms of both environmental regulations (ER) and ICY on GTFP, offering robust empirical results from panel data of 30 provinces in China covering the period 2006-2017. The results indicate that both ICY and ER effectively promote GTFP, but compared to ER, ICY has a heterogeneous effect on GTFP. Moreover, ICY plays a mediating role in ER and GTFP, while ER promotes GTFP through ICY. Accordingly, the paper puts forward some suggestions, such as to optimize and improve the ER policy, enact an innovation-driven development strategy, widely use ICY technology, and strengthen monitoring and supervision.

The criticality of tourism development, economic complexity, and country security on ecological footprint.

What kinds of countries are likely to be prosperous and have a sustainable environment at the same time? How might countries reorient their policy setting to be more capable of suppressing environmental degradation? To explore these questions, this research examines data from 99 countries for 2006-2017, takes the six major forms of ecological footprint (EF) as indicators of environmental quality, and probes the environmental Kuznets curve (EKC) hypothesis via quantile regression approach. We find that tourism development leads to greater environmental degradation, with tourism development particularly corresponding to more usage of carbon absorption land and cropland. The lower the country security is, the better is the environmental quality. Economic complexity also worsens environmental quality. However, country security weakens the negative influence of tourism development and economic complexity on environmental quality, specifying that better country security stalls the negative impact of tourism and economic complexity on environmental quality. Results mostly support the tourism- and country security-induced EKC hypotheses in fishing footprint, whereas economic complexity-induced EKC is generally validated in cropland footprint. Finally, we present that tourism arrivals, economic complexity, and country security have varying impacts across diverse ecological footprint quantiles.

CO2 emissions, income inequality, and country risk: some international evidence.

This research explores the effects of income inequality and country risk on CO2 emissions and examines whether the effects change across countries with different development stages or income levels. A new panel quantile regression approach is used to conduct a comprehensive analysis of the impacts of affecting factors on CO2 emissions at various quantiles, while addressing econometric challenges such as endogeneity and heterogeneity. From a global perspective, we can conclude that the marginal impact of inequality on emissions drops constantly with decreasing country risk at 10th to 50th quantiles, which even performs negative, whereas at the other quantiles, the marginal impact of inequality always remains negative. When we focus on the different income groups, the nexus of inequality emissions is negative first and then positive with decrease of country risk in low-income countries but shows no significant in low-middle- and upper-middle-income countries. Additionally, we validate the detrimental impact of income inequality in upper-income countries. Besides, country risk adversely moderates the nexus of inequality and emissions in low- and upper-income countries. Empirical results confirm that the nexus of inequality emissions lies in country risk, income level, and existing emission degree. These findings provide some important recommendations for policy-makers.

Gasoline demand elasticities in the world's energy gluttons: a time-varying coefficient approach.

In this paper, we estimate the price and income elasticities for gasoline demand in selected energy gluttons-China, India, USA, Russia, and Japan. Specifically, we employ a time-varying parameter approach which adequately deals with potential parameter instabilities and nonlinearities and effectively captures price and income elasticity variations over time, with each time period having its own set of coefficients. Our empirical findings reveal the following: gasoline consumption is price-inelastic and income-inelastic, there are movements in both the price and income elasticities, and the movements generally correspond with business cycle patterns of each of the countries; overall, sensitivity to price and income changes increase during periods of economic crises. Constant elasticity models overestimate price and income elasticities, and income is predominantly more elastic than price. Our conclusion is that policy mechanisms that are price-based such as gasoline taxes are likely to be unsuccessful in achieving consumption-cum-pollution reduction objectives in the energy gluttons. Such policies may, however, be effective if they ensure that gasoline prices rise at a greater rate than income. Such policies may also be useful for revenue-raising purposes.

The impact of outward foreign direct investment on green innovation: the threshold effect of environmental regulation.

Outward foreign direct investment (OFDI) in an open economy has gradually become an important source of green innovation (GI). With the rapid development of China's OFDI, this research studies the impact of OFDI on the country's GI, employing panel data of 30 provinces from 2006 to 2017. We first use the Super-SBM model to measure GI performance and then test the impact of OFDI on GI with the system GMM model. Evidence finds that the negative impact of OFDI on GI is not significant on the whole, but the results of regional regression show that impact of OFDI on GI exhibits obvious regional differences. We then utilize the dynamic threshold panel model to determine the non-linear relationship between OFDI and GI through the perspective of environmental regulation in order to avoid the bias caused by ignoring the impact of institutional factors and time dynamic change. After dividing environmental regulations into command control environmental regulation and market incentive environmental regulation, the research results show that the double threshold effects of both environmental regulations are significant. Command control environmental regulation does not play a role in promoting the effect of OFDI on GI. When the intensity of market incentive environmental regulation is low, OFDI negatively affects GI. Moreover, only when the market incentive regulation shows high intensity can OFDI significantly promote GI. With the continuous growth of China's OFDI, it is therefore necessary to determine the appropriate environmental regulation to improve the reverse spillover effect of OFDI enterprises on the country's GI.

Are geopolitical threats powerful enough to predict global oil price volatility?

Geopolitical risks have been widely linked to oil price movements in the past. Our study as an addition to this debate shows that geopolitical threats particularly play a significant role in the volatility experienced in global oil markets with attendant policy suggestions. In this study, we employed the newly developed geopolitical threats index to examine whether threats of war, terrorism, and ethnic and political violence within and between countries are powerful enough to predict volatility in global oil prices. Monthly data on global geopolitical threats index and global prices of crude were drawn upon for causality between the periods 1990:01 and 2020:04. To this effect, two volatility indices were constructed using the deviations of Brent and WTI prices from their Hodrick-Prescott filters. The ability of the geopolitical threats index to predict volatilities was examined through a battery of causality methodologies-Granger causality test in frequency domain, nonparametric test for nonlinear causality, leveraged bootstrap causality test, and Fourier Toda-Yamamoto causality test. Through various causality methodologies, we were able to ensure robustness against various problems associated with the classical linear Granger causality testing approach and ascertain that geopolitical threats are powerful and useful predictors of volatility in global oil prices.

Does technology advancement reduce aggregate carbon dioxide emissions? Evidence from 66 countries with panel threshold regression model.

The influence of technology advancement on carbon dioxide (CO2) emissions is complex and controversial, yet existing literature ignores the level of economic development in regard to its influential effect. With the panel threshold regression model, this research investigates the marginal and non-linear impacts of technology advancement on CO2 emissions along with the changes of economic development and presents the heterogeneity between different countries. The results are as follows: First, technology advancement and CO2 emissions have a non-linear inverted U-shaped relationship, which is significantly affected by different levels of economic development. When economic development exceeds a certain threshold, the impact turns from positive to negative. Second, the impact varies remarkably among different countries. We provide evidence for inverted U-shaped and N-shaped correlations in the Organization for Economic Co-operation and Development (OECD) countries and high-income countries (non-OECD), respectively. Although technology advancement always promotes CO2 emissions in middle- and low-income countries, its marginal effect is decreasing. This study not only indicates the dynamic impacts of technology advancement on CO2 emissions in different countries, but also contributes to policymakers' understanding of the "common but differentiated responsibilities" involved in mitigating CO2 emissions.

Structural breaks, tourism development, and economic growth: Evidence from Taiwan.

Our paper differs from previous studies by examining the issue of whether regime changes have broken down the stability of the long-run relationships between tourism development and real GDP in Taiwan for the 1959-2003 period. We empirically investigate the co-movements and the causal relationships among real GDP, tourism development, and the real exchange rate in a multivariate model. We use two different tourism variables-international tourism receipts and number of international tourist arrivals. To employ the unit root tests and the cointegration tests allowing for a structural break, the empirical evidence clearly shows that the causality between tourism and economic growth is bi-directional. Lastly, the international and cross-strait political change, economic shocks, and the relaxing of some tourism control and policies would break down the stability of the relationships between tourism development and economic growth. Overall, we do find the structural breakpoints, and they look to match clearly with the corresponding critical economic, political, or tourist incidents.