Search Results (25)

This paper investigates the impact of Environmental, Social, and Governance (ESG) performance on the financial outcomes of 68 European and 60 U.S. banks over the period 2010–2022 using a Panel Smooth Transition Regression (PSTR) framework. Unlike traditional linear models, the PSTR approach captures the nonlinear, regime-dependent effects of ESG engagement on bank profitability, measured by ROA and ROE, and financial stability, measured by the Z-score. Our empirical findings reveal a critical ESG threshold in both regions, above which banks experience substantial improvements in profitability and resilience. Comparative analysis indicates that while ESG enhances stability slightly more in European banks, U.S. banks tend to achieve marginally higher profitability gains. Control variables, including bank size, capital adequacy, leverage, and macroeconomic conditions, also play a significant role in shaping performance. These results underscore the importance for banks to attain a minimum ESG maturity to fully realize the benefits of sustainable practices. The study provides valuable insights for bank managers, investors, and policymakers seeking to promote a sustainable and resilient banking sector across Europe and the United States. Full article

This study develops a semiparametric causal inference framework to quantify the effect of Artificial Intelligence (AI) adoption on enterprise labor structure under high-dimensional confounding. We employ the Double Machine Learning (DML) estimator proposed, which combines Neyman orthogonality and cross-fitting to achieve reliable causal identification in settings where conventional regression methods are prone to bias from high-dimensional controls and nonlinear confounding. Nuisance functions are estimated using Lasso and Random Forests, enabling flexible modeling of complex relationships between control variables and outcomes. Using an unbalanced panel of Chinese A-share listed companies spanning 2006 to 2023, we identify a significant positive average treatment effect of AI adoption on the share of high-skilled labor (estimate: 0.118; 95% CI: [0.073, 0.163]), indicating that complementarity between AI and skilled workers dominates substitution at the firm level. Heterogeneity analysis reveals that the effect is stronger in manufacturing (0.183) than in services (0.071), and more pronounced in Eastern China (0.142) than in Central and Western regions (0.079). Quantile regression further shows that the complementarity effect intensifies at higher skill quantiles. A Panel Smooth Transition Regression (PSTR) model identifies a digitalization threshold beyond which AI–skill complementarity further strengthens. Mediation analysis confirms that productivity enhancement, digital transformation, and innovation activities together account for the majority of the total effect, with productivity improvement alone contributing approximately 34%. Placebo tests and propensity score weighting validate the robustness of our findings. Full article

Financial development is widely regarded as an important factor influencing renewable energy consumption. Nevertheless, empirical studies conducted by various scholars have revealed that the effect of financial development on renewable energy consumption remains controversial. Based on this backdrop, this paper endeavors to analyze the nonlinear influence of financial development on renewable energy consumption from the perspective of moderating effects. First of all, this paper theoretically analyzes the potential moderating effects of financial development itself, urbanization, and environmental regulation on the impact of financial development on renewable energy consumption. Subsequently, leveraging the Panel Smooth Transition Regression (PSTR) model and the global panel data of 143 countries from 1996 to 2020, the empirical tests are conducted to verify these moderating effects. The results indicate that the variations in moderating variables can lead to disparities in the influence of financial development on renewable energy consumption. Specifically, with the increase in financial development level, urbanization rate, and environmental regulation intensity, the promoting effect of financial development on renewable energy consumption gradually strengthens. Finally, based on the aforementioned research findings, this paper proposes corresponding policy recommendations from the perspectives of these moderating factors. Full article

The technological revolution and industrial transformation led by digital technologies are driving the shift from global value chains (GVCs) to digital global value chains (DGVCs). To address the challenge of global climate change while achieving economic growth, many countries are prioritizing practical energy-saving and emission reduction measures, while simultaneously seeking greater trade gains through participation in digital GVCs and the international division of labor. This study examines whether participation in DGVCs reduces carbon emissions. Using balanced panel data covering 62 countries from 2007 to 2021, we employ a Panel Smooth Transition Regression (PSTR) model to investigate the nonlinear relationship between DGVC participation and CO₂ emissions embodied in digital exports (EEDE). The empirical results reveal an inverted U-shaped relationship, indicating that DGVC participation increases emissions below a digitalization threshold but reduces emissions beyond this threshold. These findings provide new evidence for the dual role of digitalization in shaping trade-related emissions and highlight the importance of stage-specific strategies. Policy implications emphasize that less-digitized economies must prioritize breaking free from carbon lock-in by pursuing green transformation alongside digital expansion. The study deepens the understanding of the trade–environment nexus in the digital era and provides actionable insights for aligning digital economic development with global climate goals. Full article

This study examines the influence of social capital, intellectual capital, resource rents, and investment capital on the economic performance of the 18 member states of the European Union from 2005 to 2022. Principal component analysis and factor analysis are employed to construct composite measures of social and intellectual capital. The empirical model integrates static panel estimations with Monte Carlo simulations and Panel Smooth Transition Regression (PSTR) to examine nonlinear and regime-dependent growth functions. Investment capital exerts a greater influence on growth when intellectual capital is above a certain threshold, but social capital and resource rents exhibit diverse effects across various regimes; this is consistent with semi-endogenous growth models. In regimes with low intellectual capital, resource rents adversely influence growth, consistent with the resource curse concept; however, this effect diminishes as intellectual capital rises. Finally, partial least squares structural equation modeling indicates that social capital, investment capital, and resource rents influence economic growth, with this effect mediated by intellectual capital. The findings underscore the necessity for the European Union to cultivate and enhance knowledge-based assets while reducing reliance on resource rents to achieve more resilient and sustainable economic development. Full article

Climate warming leads to earlier onset and shortened duration of the freeze–thaw period in the eastern Tibetan Plateau, which has complex effects on vegetation growth. We assessed the spatiotemporal changes in the freeze–thaw period, evaluated its relationship with Normalized Difference Vegetation Index (NDVI from remotely sensed data), used the Panel Smooth Threshold Regression (PSTR) model to quantify the nonlinear impacts and identify critical thresholds, and applied ridge regression to explore the dominant mechanisms under different climatic conditions. The results showed the following: (1) The duration of the freeze–thaw transition period showed strong latitudinal zonality, with stronger spring disturbances than autumn ones. The trend of soil freeze–thaw status in high-altitude areas is the most significant, with a significant increase in the complete thaw period (CTP) and a significant decrease in the complete freeze period (CFP). (2) The earlier onset of the spring freeze–thaw period (SFTTP) and the CTP benefits vegetation growth in both early and late seasons. The delayed autumn freeze–thaw period (AFTTP) benefits early-season vegetation growth but is less favorable for late-season growth. The delayed CFP is beneficial for vegetation growth throughout the year. (3) The CTP’s boost to NDVI collapses at an onset date of 110 days and duration of 190 days. The AFTTP’s benefit peaks at an onset date of 300 days. (4) Temperature and the CTP are key drivers of NDVI changes, especially in the mid-to-late growing season. Arid areas respond strongly to freeze–thaw disturbances, while moderate precipitation areas are less affected. This study is the first to quantitatively analyze the nonlinear mechanism of the freeze–thaw–vegetation relationship, offering a new theoretical basis. Full article

Under the “dual carbon” targets, the influence of environmental regulation on carbon emissions is critical, and the moderating role of environmental decentralization should not be overlooked. Using provincial panel data from China, this study builds a Panel Smooth Transition Regression Model (PSTR) with environmental decentralization as the threshold variable to examine the nonlinear relationship between environmental regulation and carbon emissions. The study finds that when environmental decentralization is below the threshold, raising the intensity of environmental regulation leads to a significant reduction in carbon emissions; however, once decentralization surpasses the threshold, strengthened environmental regulation may result in a rise in carbon emissions. Three subcategories of decentralization exhibit similar threshold effects, but their direct emission reduction effects are heterogeneous. This research offers empirical evidence supporting the optimization of the distribution of environmental responsibilities across central and local governments, as well as for formulating regionally differentiated emission reduction policies. Full article

As one of the important driving forces of sustainable development in coastal areas, foreign direct investment (FDI) has provided new ideas for exploring optimal strategies. This analysis explores the linear impact of FDI on sustainable development in coastal areas with 53 cities in China from 2012 to 2020. Accordingly, a dynamic panel smoothed transition regression (PSTR) model is used to analyze the non-linear impact of FDI on sustainable development, with transition mechanisms of industrial structure and technological innovation level. The findings reveal that the non-linear effect of FDI on the sustainable development of coastal areas is obvious. When the coastal area’s industrial structure is more optimized, and the level of technological innovation is higher, the promotion effect of FDI on sustainable development is more obvious. Further, the threshold effect of industrial structure and technological innovation is different. The threshold conversion rate of industrial structure is faster, but the threshold effect of technological innovation is stronger. Regionally, the impact of FDI on the sustainable development of coastal adjacent areas is significant, but not on the sustainable development of inland areas due to the few FDI inflows. This analysis offers guidance for policymakers to further develop the tertiary industry, increase financial investment in innovation in coastal areas and encourage enterprises to improve their independent innovation capacity. Full article

Environmental regulation (ER) is a crucial tool used by governments to intervene in the environmental practices of enterprises, and it is recognized as a significant avenue to impact industrial ecological efficiency (IEE). This study uses the superefficiency SBM model to determine provincial IEE scores. Then, a panel smooth transition regression (PSTR) model is used to explore the effects of ER on IEE transition at different stages of economic growth. The main findings are as follows: Firstly, China’s IEE showed an overall upward trend, with small increments over the past two decades. Regions with higher IEE were mainly located in the east, while those with lower IEE were mostly in the less economically developed west. Secondly, the PSTR model revealed that ER had varying impacts on IEE at different stages of economic growth. ER positively influenced IEE in the early stages of economic growth. However, after surpassing the threshold of economic growth, ER began to contribute to reducing IEE scores. In addition to these findings, this study proposes a series of policy recommendations to strengthen IEE. Full article

This paper analyzes the linear and non-linear relationship between non-performing loans and bank profitability measured by the Net Interest Margin for a sample of 74 Middle Eastern and North African banks over the period of 2005–2020. We used the System Generalized Method of Moments (SGMM) as a linear approach and the Panel Smooth Transition Regression (PSTR) model as a non-linear approach. The empirical results of the SGMM approach indicated that the ratio of NPLs negatively affects bank profitability. The findings of the non-linear relationship based on the PSTR model confirmed the existence of a threshold effect. We found that below the threshold of 4.42%, the effect of NPLs is negative but not significant, while after surpassing this threshold, the effect becomes negative and significant. As for bank specifics, we revealed that bank size is positively and significantly associated with bank profitability. For industry factors, we found that more bank concentration decreases bank profitability. Regarding the financial environment, we concluded that the global financial crisis exerted a negative impact on bank profitability. Moreover, we revealed a positive and significant impact of GDP on bank profitability as well as a negative impact of inflation on bank profitability. This study has some limitations regarding the social, economic, and financial differences of the whole sample, which includes banks from the Middle East and others from North Africa. Hence, decomposing the whole sample into two sub-samples could improve the results of this paper. Full article

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. Full article

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. Full article

There is evidence for mixed effects of corporate social responsibility (CSR) on corporate financial performance. In particular, evidence is reported to be positive, negative, and insignificant. These controversies are generally explained by two opposing schools of thought, which are the social impact hypothesis and the shift of focus hypothesis. This paper attempts to contribute to the ongoing debate by investigating whether the relationship between CSR and firm financial results is nonlinear. Therefore, this research relies on a panel smooth transition regression (PSTR) model in order to calculate the value transition threshold of CSR in 70 Gulf Cooperation Council (GCC) firms from 2015 to 2020, using the CSR composite index and various CSR dimensions, which include environmental, social, and governance transition dimensions. Empirical findings indicate that investment in CSR does not help to boost corporate value until it exceeds the value transition threshold. However, when the marginal benefit exceeds the cost, CSR investment becomes a positive contributor to corporate performance. Furthermore, results indicate that the nonlinear relationship persists when using the individual CSR dimensions, i.e., governmental, social, and environmental CSR measurements. Finally, an interesting finding shows that the social CSR dimension is associated with the highest threshold level. Hence, firms should invest more in the social aspects of CSR in order to see their profitability increase. Full article

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. Full article

This study analyses the nonlinear dynamic impact of economic development on income inequality in a prudential policy regime in a panel of 15 emerging markets from 1985–2019. More importantly, we seek to extend the existing debate on this subject, with roots back to the seminal work by Kuznets and many others, and add a twist by introducing a distinction between a prudential regime (1985–1999) and a non-prudential regime (2000–2019), as well as the threshold level at which economic development reduces inequality, using Panel Smooth Transition Regression (PSTR). The Generalized Method of Moments and fixed-effect models will be used to support our baseline results. The PSTR model was adopted due to its ability to deal with features that cannot be accounted for in dynamic panel techniques, such as endogeneity, homogeneity, cross-country variability, and time instability within the model. We found evidence of a non-linear effect between the two variables, where the threshold was found to be US$13,800, above which economic development reduces inequality in selected countries, and this further confirms the Kuznets inverted U-shape in both regimes. Macroprudential policies were found to trigger development-inequality relationships. Our evidence largely suggests that policymakers ought to formulate policies that aim to attract investment, which will then create job opportunities and foster an improvement in the stan-dard of living, and also should be abreast of the level of economic development before implementing macroprudential policies. Full article