The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness.

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

Does the type of transportation mode matter in the effect of freight transportation on the environmental pollution of OECD countries?

This study aims forward to explain the effect of freight transportation on environmental pollution and to investigate the role played by the usage rates of road and railway transportation modes in this relationship. As an auxiliary problem of the research, it was tried to determine whether there is a threshold value for these types of transportation and what consequences will arise in terms of environmental pollution below and above this threshold. For this purpose, the data of OECD countries for the period 2000-2018 were analyzed with the PSTR method. Analysis results showed a non-linear relationship between freight transportation and environmental pollution and that the road/rail transportation ratio plays an important role in this relationship. The determined threshold value is 68.18% for road freight transport and 29.55% for rail freight transport. Below the determined threshold values, as the amount of cargo transported increases, the rate of carbon emission increase gradually increases in both types of transport. Above the threshold values, road transport increases the rate of increase even more, while rail transport decreases this rate of increase. Within the scope of these results, countries should develop policies to increase the use of railways in freight transport while reducing the use of roads.

The impact of green innovation resilience on energy efficiency: A perspective based on the development of the digital economy.

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening-energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process.

Examining the nonlinear impact of human capital on environmental degradation in N-11 countries: an application of the PSTR approach.

The emergence of globalization and human capital has played a crucial role in the economic integration of countries, leading to the growth of the economies and a reduction in carbon dioxide (CO2) emissions. This study highlights the importance of investing in human capital development to control ecological degradation and promote sustainable economic growth. This paper employs the PSTR method to investigate the threshold impact of GDP, globalization, information communication technology, and energy consumption on CO2 emissions. The study examines two regimes, with a single threshold to analyze the transition of human capital on these variables. The results reveal that human capital developments play a central role in controlling ecological degradation due to reduced CO2 emissions. Based on the empirical findings, this research study offers corresponding policy suggestions.

Threshold nonlinear relationship between renewable energy consumption and agriculture productivity: the role of foreign direct investment and financial inclusion.

Global warming is a life-threatening risk to mankind and its survival; to combat this risk, the considerable contribution of renewable energy cannot be overlooked for sustainable growth globally. The aim of this paper is to scrutinize the threshold level and asymmetric connection among renewable energy consumption, foreign direct investment, financial inclusion, and agricultural productivity in dissimilar regimes of the different income levels of 123 countries from 1995 to 2019 by applying an advance technique PSTR (panel smooth transition regression) model. The PSTR model results imply that the connection between renewable energy consumption and agricultural productivity at all the estimates is non-linear. Moreover, in all countries, there is a positive and significant connection among renewable energy consumption, foreign direct investment, financial inclusion, and agricultural productivity in both low and high regimes, except the carbon emission, which has a negative and significant impact on agricultural productivity. Based on the results of this study, the recommendations are as follows: (i) to increase renewable energy consumption, efficient-energy resources should be used by farmers for the agricultural process; (ii) the dependence on non-renewable energy resources should be minimized and shifted towards natural and renewable resources.

Impact of Environmental Regulation on Carbon Emissions in Countries along the Belt and Road-An Empirical Study Based on PSTR Model.

Since China has put forward the Belt and Road Initiative in 2013, research on the BRI-related countries along the Belt and Road has sprung up. With the advent of the era of carbon peak and carbon neutralization, environmental regulation, as one of the important methods to control carbon emissions, is becoming increasingly prominent. Research on the impact pathway of environmental regulation of countries along the Belt and Road on carbon emissions has important implications for environmental protection and carbon emission reduction. Based on the panel data of 38 countries along the Belt and Road from 2005 to 2018, this research applied linear Tobit model and nonlinear dynamic panel regression model (PSTR) to evaluate the direct impacts on carbon emissions from environmental regulation of countries along the Belt and Road, and to analyze the different impacts of environmental regulation on carbon emissions in terms of technical innovation, industrial structure, and energy intensity. We found that (1) the direct impact of environmental regulation on carbon emissions in the countries along the Belt and Road is positive, with slight differences between the Silk Road Economic Belt and 21st Century Maritime Silk Road (2) when technical innovation is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation significantly inhibits carbon emissions. (3) When industrial structure is at both a low and high level, environmental regulation inhibits carbon emissions, with a stronger degree of inhibition at a higher level. (4) When energy intensity is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation inhibits carbon emissions. Accordingly, we suggest that countries along the Belt and Road follow the road of sustainable and low-carbon development, which should further enhance their focus on environment protection, improve their environmental awareness, and take environmental regulation measures rationally to reduce carbon emissions. Meanwhile, relevant adjustments should be done on technical innovation, industrial structure, and energy intensity to achieve carbon emission reduction.

Nonlinear Effects of Economic Policy Uncertainty Shocks on Carbon Emissions in China: Evidence from Province-Level Data.

Based on cross-sectional data from 30 Chinese provinces from 2004 to 2017, this paper systematically examines the nonlinear effects of economic policy uncertainty (EPU) on carbon emissions and its causes using the PSTR model. It is found that the impact of EPU on carbon emissions at the provincial level in China has significant nonlinear characteristics and shows a positive and then negative pattern as the level of EPU increases. Furthermore, increased levels of EPU also cause a nonlinear migration of the effects of provincial economic and financial development, industrial structure, government spending, and environmental regulation on carbon emissions, illustrating a large amount of heterogeneity among Chinese provinces. Specifically, provinces with higher levels of economic and financial development experience a greater positive carbon emission effect from EPU, whereas provinces with lower levels of such development experience a greater negative carbon emission effect. In contrast, in provinces with irrational industrial structures, lower fiscal expenditures, and weaker environmental controls, the nonlinear carbon emission consequences of EPU are greater. Therefore, local governments should prudently adjust economic policies, improve and perfect the market information disclosure system, and afford full play to regional comparative advantages to help achieve the "double carbon goal".

Green Total Factor Productivity Growth: Policy-Guided or Market-Driven?

The green growth mode of modern economy is affected by both policy and market, but previous studies have lacked a comparison between the two effects on green economy development. Which is the leading factor of green growth: policy or market? Using the Panel Smooth Transition Regression (PSTR) model and the twelve-year data of more than 200 prefecture-level cities in China, we compared and analyzed the linear and non-linear effects of environmental regulation and marketization degree on green total factor productivity (GTFP). The results show that: (1) both environmental regulation and marketization degree have a non-linear promoting effect on GTFP. (2) GTFP is mainly market-driven rather than policy-guided. (3) Environmental regulation and marketization promote the improvement of GTFP through the industrial upgrading effect and the innovation development effect, respectively. This paper makes up for the comparative analysis gap of factors in the field of green growth and extends from the single determination of influencing factors to the importance of the comparison of influencing factors with the transition perspective. The conclusions provide a reference for the green development of countries and regions, emphasizing the importance of green development policies adapting to local conditions and time and providing evidence for market-oriented green economy development.

External debt and economic growth in Sub-Saharan Africa: does heterogeneity in the quality of public sector management make a difference?

This study empirically examines the effect of external debt on economic growth, taking into account heterogeneity in public sector management (PSM) across 31 selected sub-Sahara African (SSA) countries spanning 2005 to 2017. In this study, we contributed to existing studies by examining how differences in PSM quality complement external debt to influence economic growth. We employ the system-generalized method of moment (system-GMM) and the panel smooth transition regression (PSTR) methods for the analysis. The results without differences in PSM quality show that external debt has a significant negative effect on economic growth in SSA. However, the effect of external debt on economic growth tends to be positive for SSA countries with strong PSM quality when external debt interacts with PSM quality. Furthermore, the results show that countries with strong PSM quality experienced higher economic growth than those with weak PSM quality. The PSTR also showed strong evidence of a nonlinear relationship between external debt and economic growth and estimated the indebtedness threshold value at 45% for the selected SSA countries. The implication of the findings calls for governments in SSA to strengthen the quality of public sector management via structural reforms aimed at public sector reform, tax reforms and strengthening debt management capacity to ensure positive growth effects of external debt.

Does energy intensity matter in the nexus between energy consumption and economic growth regarding capital-energy substitution?

This article investigates how the non-linear connection between energy consumption and economic development is influenced by energy intensity level in the context of energy-capital substitution. We firstly analyze the substitutability/complementarity between energy and capital by estimating VES production function within the standard Solow growth model framework for 58 countries over the period of 1975-2017. The selected countries are classified into four groups according to their relative energy intensity levels and their accessibility to energy. The estimation findings reveal that energy and capital are complements in the final output for each country group. Hence, in this paper, as further analysis, the study examines whether or not energy consumption always fosters economic growth. We investigate the non-linear link between energy consumption and economic development by constructing a panel smooth transition regression (PSTR) model for each country group and looking at the impact of energy intensity in this relationship. The empirical results provide that for each country group, there is a threshold level for energy intensity. Regardless of whether a country is a net energy exporter or net energy importer, it needs to use energy efficiently and not exceed the ideal energy intensity level in both production and consumption to maintain long-term economic growth.

Exploring the Effects of Tourism Development on Air Pollution: Evidence from the Panel Smooth Transition Regression Model.

Based on the theoretical framework of the Environmental Kuznets Curve (EKC), this study investigates whether tourism development can decrease air pollution. This study applies the panel smooth transition regression approach and panel data for 2005-2019 from 283 prefecture-level cities in China to examine the nonlinear effect of tourism development on PM2.5, emissions. Our results reveal that the effects of tourism on PM2.5, emissions vary according to the modes of tourist arrivals. At the national level, the effect of tourism on PM2.5 emissions exhibits an inverted-U shape. At the regional level, tourism exerts a U-shaped impact on PM2.5 emissions in eastern China, and tourism is nonlinearly negatively associated with PM2.5 emissions in central and western China. An important theoretical contribution of our study is the proposal and validation of the U-shaped tourism-induced EKC hypothesis.

Can the Digital Economy Facilitate Carbon Emissions Decoupling? An Empirical Study Based on Provincial Data in China.

The digital economy plays a dual role in the process of global carbon emissions decoupling; for this reason, its overall impact direction and mechanism are worth discussing. This paper attempts to answer the question of the role of the digital economy, based on a review of the existing literature. By constructing a panel smooth transition regression (PSTR) model, this paper empirically tests the effect of the digital economy on carbon emissions decoupling, based on panel data from 30 provinces in China from 2010 to 2019. In order to study the impact mechanism of the digital economy on carbon emissions decoupling, the mediating effect of industrial structure optimization is analyzed through a mediating effect model; the moderating effect is also explored by analyzing the network centrality characteristics of the digital economy. The core-periphery analysis method is adopted to group the samples to test the impact heterogeneity of the digital economy on carbon emissions decoupling. Based on this empirical analysis, the following conclusions are drawn. First, the digital economy has a promoting effect on carbon emissions decoupling, but this effect gradually weakens with the development of the digital economy. Second, the digital economy can promote carbon emissions decoupling through industrial structure optimization, and network centrality has a positive moderating effect on this mechanism. Third, heterogeneity exists in the promoting effect of the digital economy on carbon emissions decoupling, which is reflected in the different intensities of the promotion effect between the core nodes and the peripheral nodes in the network; the attenuation range of the promotion effect is also different when the regime switches.

The Threshold Effect of FDI on CO2 Emission in Belt and Road Countries.

Under the background of the global "carbon neutrality" goal, it is of great significance to study the environmental effect of FDI in rapid economic development. This paper proposes an original framework to determine the relative influence of five factors on the Belt and Road countries with a strong FDI-CO2 association. Based on the panel smooth transition regression (PSTR) model, we establish country-specific and time-specific FDI-CO2 coefficients for 59 Belt and Road countries during 2003-2018. These coefficients are assumed to change smoothly as a function of five threshold variables, considered the most important in the literature devoted to the FDI-CO2 correlations. The results show that the degree of GDP per capita, industrialization, openness, and total factor productivity significantly influences the FDI-CO2 relationship. However, they showed obvious heterogeneity. The coefficient of elasticity of the environmental effects of FDI smoothly transitions between the different intervals, the relationship between GDP per capita and FDI-CO2 coefficient shows a bell-shaped change, the relationship between degree of trade openness and FDI-CO2 coefficient also shows a bell-shaped change, the relationship between industrialization level and FDI-CO2 coefficient shows an inverted N-shaped change, the change of a country's technological level shows a bell-shaped relationship with the FDI-CO2 coefficient. The results indicate that PSTR model can be used to study the threshold effect on FDI's influence on carbon dioxide emissions and the individual and time differences in coefficients of elasticity, to provide a new research perspective and new conclusions on the environmental effect of FDI in rapid economic development.

Nonlinear Relationship between Financial Development and CO2 Emissions-Based on a PSTR Model.

The contradiction between financial development and environmental pollution has become increasingly prominent with economic development. The discovery of the link between financial development and carbon dioxide emissions will aid in the development of solutions to this problem. This paper uses a panel smooth transition regression (PSTR) model to examine the impact of financial development on carbon dioxide emissions using panel data from 28 Chinese provinces from 2005 to 2021. The PSTR model can solve the problem of minimizing potential outliers ignored in the previous literature, while taking into account the endogeneity and heterogeneity of the model and obtaining more reliable results. According to the findings, financial development has a nonlinear effect on carbon dioxide emissions. Furthermore, the positive effect of financial development on carbon dioxide emissions occurs via the scale and structural effects, while the negative effect occurs via the technological effect, which takes up more space. Moreover, financial added value and the financial scale demonstrate a smooth transition, while financial efficiency and foreign direct investment demonstrate a positive influence.

Threshold Effect in the Relationship between Environmental Regulations and Haze Pollution: Empirical Evidence from PSTR Estimation.

The impact of environmental regulations (ER) on haze pollution control has been continuously debated in the field of sustainable development. This paper explores the direct and indirect threshold effects of ER on haze pollution, and five underlying mechanisms-technological innovation (TI), industrial structure (IS), foreign direct investment (FDI), urbanization (UR), and electricity consumption (EC)-are adopted to investigate the indirect threshold effects. Panel data, over the period 2008-2018, of 284 Chinese cities were used and the threshold effects were predicted endogenously based on the panel smooth transition regression (PSTR) model. The results showed the following: (1) For the direct threshold effect, there exists a U-shaped relationship between ER and haze pollution. ER significantly reduced haze pollution when ER < 38.86 due to "cost effects". However, ER increased haze pollution after the threshold owing to the "green paradox", which was not significant. (2) For the indirect threshold effect, when TI = 0.37, IS = 39.61, FDI = 7.25, and UR = 42.86, the relationships between ER and haze pollution changed. The changes and corresponding reasons for the indirect threshold effects are discussed in detail. (3) After a comprehensive analysis, the threshold effects have obvious regional distribution characteristics and internal connections. Finally, based on the results, it is essential for governments to enact appropriate environmental regulatory policies and enhance inter-regional synergies in environmental governance.

The influence of linear feedback control suppression under the calculation of fractional financial system on the upgrading of high-tech industries.

The paper uses the panel smooth conversion fractional-order system model to divide the mechanism of financial development in high-tech industries into two systems. At the same time, the article uses a continuous state to connect these two extreme situations to investigate the nonlinear characteristics of linear feedback control that inhibit the impact of financial development on high-tech industries. Studies have shown that financial development under a low system has a significant role in promoting high-tech industries. On the other hand, financial development under the high-level system has a restraining effect on high-tech industries. There are dual-threshold characteristics between the scale of financial development and the development of high-tech industries. Firstly, the scale of financial development should be controlled within [0.553, 0.840]. Secondly, there is a single threshold between the level of financial development and the development of high-tech industries, and the level of financial development should be controlled within 0.756.

Exploring the nexus between human capital and environmental degradation: The case of EU countries.

Human capital investments have a vital role in economic growth. Therefore the effects of human capital on the environment should be analyzed for sustainable economic growth. This paper contributes to the debate on the nexus between human capital and environmental degradation. Based on 21 EU countries' panel data over the period 1994-2018, this study aims to analyze the relationship between human capital and environmental pollution in different financial development levels. We employed the panel smooth transition regression model (PSTR) to assess the nexus between the variables. According to the estimation results, human capital decreases carbon emissions in the low growth regime whereas increases in the high growth regime. Besides, human capital increases carbon emissions in both low regimes of financial development and human capital, and decreases in high regimes. The analysis indicated that as human capital improves, there will be more innovation to protect the environment, and thus there is less environmental degradation.

A threshold approach to sustainable development: Nonlinear relationship between renewable energy consumption, natural resource rent, and ecological footprint.

All over the world, humankind and nature are paying off economic development's opportunity cost through accelerated environmental degradation. Renewable energy is the best option to control and minimize environmental degradation for sustainable development. This study's primary motive is to examine the nonlinear relationship between renewable energy consumption, natural resource rent, and ecological footprint in the context of the world's top 15 renewable energy consumption economies to achieve sustainable development. Panel time-series data from 1996 to 2018 is focused on concluding the study. Panel Smooth Transition Model is used to explore the nonlinear relationship and transition between the low and high regimes because of the nonlinear behavior. The study's results suggest a negative association between renewable energy consumption and ecological footprint and a positive relationship between natural resource rent and ecological footprint in both low and high regimes in the case of these 15 economies. It is highly recommended that the nations must shift their energy consumption policies towards renewable energy sources by investing in renewable energy technology and research for a more sustainable development.

The nonlinear impact of fiscal decentralization on carbon emissions: from the perspective of biased technological progress.

The impact of Chinese-style fiscal decentralization (FD) on environmental pollution has been studied. Using data from 285 prefecture-level cities across the country from 2003 to 2018. A panel smooth transition regression (PSTR) model of fiscal decentralization's impact on carbon emissions under energy and environmental-biased technology progress is established. The research shows that biased technological progress determines the direction of the impact of FD on carbon emissions. In areas with low level of energy and environmental-biased technological progress, FD increases carbon emissions. FD reduces carbon emissions in areas with higher environmental technology level but increases carbon emissions in areas with higher energy-biased technology progress. This study has theoretical and practical significance for China's decentralization system, biased technological progress, and carbon peak target.

Financial development, international trade, and environmental degradation: a nonlinear threshold model based on panel smooth transition regression.

Environmental degradation has severely affected the natural cycle of ecosystem. It's high time now and humans should execute strategies effectively to protect the further degradation. Initially, we need to understand the ways that might affect the environment. Thus, existing research is designed to explore the nonlinear association between financial development (FD) and carbon dioxide emissions (CO2) in the context of low-income countries by employing the yearly data of 1990-2016. The panel smooth transition regression model (PSTR) is applied, and the result confirmed that the nexus between the two variables are nonlinear. Moreover, it also shows that at a low regime, FD increases the CO2 emissions but as the economy of low-income states progress to the high regime, the association between the two variables becomes negative and significant. The study also confirms that FD can reduce CO2 emissions once it reaches a certain threshold point. Based on these findings, new insights are provided for the policymakers, and several policies are suggested to improve the environmental quality in low-income countries.