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This paper examines the impact of digital financial inclusion (DFI) on household energy poverty. We develop a simple theoretical model to explain the energy poverty alleviation effect of DFI. Using multidimensional household energy consumption survey data, we find that DFI reduces the incidence of household energy poverty by about 33.5 % and the intensity of energy poverty by 24.6 %, driven mainly by improvements in energy efficiency and an increase in household off-farm work, resulting in a stronger role in rural and low-income groups. However, the threshold model demonstrates that the Internet and digital tools are a prerequisite for this pro-poor energy effect to be realized. Notably, DFI, while exhibiting spatial spillover effects, exacerbate energy poverty in neighboring areas due to the siphoning effect. [ABSTRACT FROM AUTHOR]

This paper proposes a theoretical model of voluntary intermunicipal cooperation and empirically tests its assertions through the French municipalities' choices of transferring their competences to the intermunicipal level. Using an original threshold models inference procedure, a probit model is estimated on shared competences. Two main results arise. Contrary to the decentralisation theorem prediction, citizens' preference heterogeneity does not hinder local cooperation, but fiscal potential heterogeneity does. Moreover, a zoo effect is at stake for some competences, for which a significant threshold effect in their transfer probability is identified. [ABSTRACT FROM AUTHOR]

Addressing energy poverty is integral to the United Nations Millennium Development Goals, and clean energy technology serves as an essential tool in mitigating this issue. Existing studies pay less attention to the correlation between the two. In this study, we quantify the spread of clean energy technology using patent citation information and analyze balanced panel data from 30 provinces in China spanning the years 2004 to 2019. The findings reveal that the diffusion of clean energy technology not only directly reduces energy poverty but also indirectly alleviates it by enhancing energy efficiency and fostering employment. However, the positive impact of technology on poverty is affected by human capital. Specifically, when the number of college students per 10,000 people in a province surpasses 179, technology diffusion becomes effective in alleviating energy poverty. Furthermore, the efficacy of this mitigation varies significantly based on different regions. Technologies originating from developed economies such as the United States, Japan, and the European Union exhibit a more substantial impact than domestic alternatives. Additionally, the effect of alleviating energy poverty is more significant in the eastern region. Therefore, we make policy recommendations for alleviating energy poverty through the use of incentive policies, exploring differentiated models of clean energy technology development, and strengthening international cooperation. [ABSTRACT FROM AUTHOR]

African countries are faced with many challenges, which have hindered growth and development, yet they are unable to implement policies to attract adequate external funding for addressing their growth and development challenges. Using a cross‐sectional panel data of 23 African countries, spanning 1996–2020, this study applied a novel panel structural autoregressive model and a modification of the recently introduced dynamic threshold model to analyse the foreign direct investment (FDI)‐growth‐poverty relationship at sectoral level. The study accounted for heterogeneity, simultaneity bias and cross‐sectional dependence in the modelling exercise. Findings suggest that shocks in FDI produced significant positive impact on manufacturing and services output performances in Africa in the short‐term. However, shocks in FDI did not stimulate appreciable effect on agricultural output performance over time. Moreover, the results show that the effect of FDI shocks on human development index (HDI) was greater in the short‐ to medium‐term than in the long‐term. The threshold regression results suggest that higher levels of FDI inflow and HDI are needed for macroeconomic factors to produce significant positive effects on sectoral output performance. This study therefore provided some valuable recommendations to guide evidence‐based policy making in Africa to improve sectoral output and welfare. [ABSTRACT FROM AUTHOR]

The digital economy (DE) is emerging as a crucial driver of economic growth and an effective tool for alleviating resource and environmental pressures, thereby evolving into a significant force in facilitating green transformation. This study elaborates on the theoretical mechanism of the impact of DE on green total factor productivity (GTFP), and conducts multidimensional empirical tests using panel data from 284 cities in China. The main findings are as follows: (1) DE exerts significant positive direct, indirect, and spatial spillover effects on GTFP, signifying its growing role as a robust driver of GTFP. Notably, technological innovation emerges as a key mediator of DE’s impact on GTFP. (2) The impact of DE on GTFP exhibits a distinct pattern: initially pronounced, gradually diminishing, and then rebounding as DE progresses. (3) DE tends to exacerbate, rather than alleviate, the development divide and resource curse, especially in underdeveloped and resource-rich cities where its benefits are constrained. (4) Government behavior is pivotal in influencing DE’s impact on GTFP. Supportive policies and strict environmental regulations are critical in harnessing DE’s positive contributions to GTFP. This study lays a scientific foundation for leveraging the “green attributes” of DE and offers insights into bridging the developmental disparities among cities. [ABSTRACT FROM AUTHOR]

Green insurance (GI), as an innovative product integrating environmental protection and the financial sector, not only contributes to improving regional environmental quality (EQ) but also enhances corporate environmental risk management and awareness, driving the flourishing development of green finance and the environmental protection industry. Therefore, understanding the relationship between GI and EQ is crucial. This article delves into the mechanisms through which GI influences EQ, proposing a hypothesis that suggests an inverted "U" shape impact. Subsequently, based on panel data from 30 provinces in China spanning from 2000 to 2021, nonlinear regression models and threshold regression models were constructed to test the hypothesis. The research findings indicate: (1) Results from the fixed-effects regression model demonstrate that the impact of GI on China's EQ follows an inverted "U" shape. (2) Results from the threshold regression model also reveal an inverted "U" shape impact of GI on China's EQ, with a threshold value of 2.196. (3) Economic level and industrial structure exhibit significant inhibitory effects on EQ improvement. Technological level and environmental regulations demonstrate notable promotional effects. Population size shows no significant impact on EQ improvement. The study identifies a nonlinear effect of GI on EQ improvement, surpassing existing linear effect research, deepening the understanding of its impact on EQ, and contributing to the enhancement of regional EQ. [ABSTRACT FROM AUTHOR]

The policy objectives of affordable housing programs in China are two-fold: on the one hand, they are designed to assist low- and moderate-income families and reduce inequality; on the other hand, they are intended to lower commodity housing prices. However, the effects of affordable housing land on housing prices, particularly the between-city variation and the mechanisms behind the market effects, have not been sufficiently examined, making it difficult to evaluate the housing policy and improve it accordingly. In this study, we address these gaps by using a prefecture-level panel dataset covering 2009–2020, obtained from national land and housing transaction information platforms. We use a threshold model to investigate the threshold effect of population size and a mediating model to uncover the channels through which the supply of affordable housing land affects housing prices. The results confirm that the affordable housing land supply can have a beneficial influence in terms of slowing down the increase in housing prices. The population size plays a significant role in explaining the between-city market effect variations. In cities with a population greater than 10.78 million, increasing the supply of affordable housing land would cause the housing prices to increase. Meanwhile, in cities with smaller populations, increasing the supply of affordable housing land could lower the housing prices. The underlying mechanisms of the market effects vary across cities with different population sizes. Although affordable housing land crowds out commodity housing land in all cities, housing demand diversion only exists in cities with a smaller population. At present, China is experimenting with city-specific housing policies; our findings imply that decision makers should explore additional policy options, besides building on incremental construction land, in order to make housing more affordable in supercities in China. [ABSTRACT FROM AUTHOR]

Abstract This study explores the role of financial support in the digital transformation of Chinese A-share-listed companies from 2001 to 2020. By utilizing the moderating effect model and threshold regression model, this study finds the following results: (1) Digital transformation positively impacts innovation, and the support of banking and capital markets further strengthens this impact. (2) With the development of banking and capital markets, the impact of digital transformation on innovation changes from negative to positive, which is also reflected in the subsamples of Eastern companies, small and medium-sized companies (SMEs), and non-SMEs. (3) The study reveals that only the capital market in the non-Eastern region has no threshold, and capital market support is effective only for non-SMEs when it reaches a higher level. These findings have important implications for policymakers in promoting digital transformation through financial support and help companies understand how to use financial support to improve competitiveness.

This study explores the role of financial support in the digital transformation of Chinese A-share-listed companies from 2001 to 2020. By utilizing the moderating effect model and threshold regression model, this study finds the following results: (1) Digital transformation positively impacts innovation, and the support of banking and capital markets further strengthens this impact. (2) With the development of banking and capital markets, the impact of digital transformation on innovation changes from negative to positive, which is also reflected in the subsamples of Eastern companies, small and medium-sized companies (SMEs), and non-SMEs. (3) The study reveals that only the capital market in the non-Eastern region has no threshold, and capital market support is effective only for non-SMEs when it reaches a higher level. These findings have important implications for policymakers in promoting digital transformation through financial support and help companies understand how to use financial support to improve competitiveness. [ABSTRACT FROM AUTHOR]

The analysis of energy use not only sheds light on lightening the increasing pressures from energy systems but also improves the flexibility and reliability of power systems. As the highest carbon emission country in the world, detailed evaluation of China's carbon emission trading scheme (ETS) on the energy use is sensitive to energy sectors and highlights the importance of energy utilization in current society. Yet, because of the presence of a possible discontinuity caused by policy implementation, this study uses synthetic control method (SCM) to confirm whether there is a cutoff for energy use after the ETS implementation. Furthermore, threshold regression model is integrated to estimate the causal relationship when there is a discontinuity. SCM is used to verify which has caused the discontinuity for threshold regression model, and threshold regression model is used to quantify and estimate the causal relationship which SCM cannot evaluate. Through the data analysis, it is found that ETS makes effect on energy use deduction in most of pilot ETS regions while the effect is affected by economic development, population, industry, and research. Some suggestions on how to reduce energy use conclude this paper. [ABSTRACT FROM AUTHOR]

Industrial coagglomeration (ICA) is an important factor affecting the regional air environment. The atmospheric environmental efficiency (AEE) of the Yangtze River Delta urban agglomeration (YRDUA) from 2012 to 2020 was evaluated based on the hybrid-dynamic DEA model. And the industrial coagglomeration (ICA) was calculated by the location entropy model. Then, nonlinear relationships between ICA and AEE were measured based on the threshold regression model. Spatial correlation characteristics of AEE were furtherly measured based on Moran's I, and the spatial impact of ICA on AEE was revealed through the spatial Durbin model. The results showed that the impact of ICA on AEE in the YRDUA during the study period presented a U-shaped single threshold effect, and the ICA effectively improved AEE after crossing the threshold value. The AEE of YRDUA had significant spatial correlation and dependence, and each city showed four local agglomeration characteristics of "high-high," "high-low," "low-low," and not significant. ICA had an enhancement effect on the local AEE while having a negative effect on the surrounding AEE. The four control variables of economic development, industrial structure, scientific and technological level, and openness improved AEE to varying degrees and produced positive spatial spillover effects. Carbon emissions inhibited AEE and produced negative effects. Suggestions include speeding up the transformation of energy supply mode, replacing material consumption with the input of service elements, promoting the two-way free flow of innovation factors, increasing the application of clean energy and energy-saving technologies, and relying on intelligent manufacturing to break through the boundaries of enterprise resources, could be solutions to optimize the relationship between ICA and AEE. [ABSTRACT FROM AUTHOR]

Amidst the compounded challenges posed by global climate change and urbanization on forest ecosystems, the integration of urbanization control measures within a climate-focused framework may offer an avenue for breakthroughs. This study delves into the impact of climate, specifically hydrothermal conditions, on the complex interplay between urbanization (Urb) and forest ecological function (Eco) in the Yellow River Basin (YRB) in China. Our findings reveal: (1) The application of a coupled coordination model reveals a stronger alignment between urbanization and forest ecological function in the warm and humid regions in the YRB. (2) Through the cross-sectional threshold regression model, we elucidate the diverse responses of Urb to Eco across varying climate gradients. Among them, annual precipitation shows a double-threshold effect at 532.34 mm and 694.18 mm. As precipitation increases, the impact of Urb shifts from negative to positive on Eco. Moreover, in regions with precipitation below 532.34 mm and above 694.18 mm, the absolute value of response coefficients of Eco to Urb is amplified. Annual average temperature displays a single-threshold effect at 10.11 °C, leading to a transition from negative to positive impact as temperature rises. This study establishes the climate-based threshold system that governs the urbanization–forest ecological function relationship. [ABSTRACT FROM AUTHOR]

Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.

The information technology revolution carries a digital dividend and also breeds the mechanism of inequality, and the high-quality development of information technology is of great significance in improving the state of economic inequality. The article utilizes the relative deprivation index and Gini coefficient to quantify the level of economic inequality status and then establishes an evaluation index system combined with the entropy weight TOPSIS method to calculate the level of information technology development. Subsequently, the panel data of 31 provinces and cities in China from 2017 to 2022 are taken as the research object, and the corresponding variables are selected to construct the double-difference model and the threshold regression model. The direct and nonlinear effects of IT application on economic inequality improvement are analyzed through regression. The effect of the level of IT development on the relative deprivation index and Gini coefficient is significantly negative at the 1% level, with regression coefficients of -0.094 and -0.081, respectively, and the relative deprivation index and Gini coefficient have decreased by 187.88% and 117.65%, respectively, over the 13 years after the implementation of IT reform policies. The level of information technology development has two threshold values of 5.412 and 5.634 for the state of economic inequality, and either below the first threshold or above the second threshold significantly reduces the income gap arising from economic inequality. Information technology development can effectively alleviate the state of economic inequality, reduce the economic income gap, and lay the foundation for achieving common prosperity.

Integrating the traditional dance system into the university dance performance course helps optimize the dance performance mode of college students, better cultivate students’ dance disciplinary literacy, and realize the innovative development of the traditional dance system. This paper firstly integrates the traditional dance system into the design framework of teaching resources of university dance performance courses. It constructs a unit-type dance performance teaching mode by combining the characteristics of the traditional dance system. Secondly, taking University Z of City B as the research object, the teaching comparison method is used to verify its teaching effect, the threshold regression model is introduced to explore the influencing factors of the dance performance course, and the parameters of the model are estimated by the least squares method. Finally, the data were used to quantitatively compare the students’ pre- and post-test scores of the modular dance performance teaching, and the threshold regression model of the dance performance course was subjected to benchmark regression and robustness test. The results showed that the experimental group’s mean value of mastery of traditional dance movements reached 87.53±7.05 points, a 31.98% improvement over the control group’s performance. The existence of single and double thresholds of policy prerequisites and subject selectivity on the level of university dance performance course design can realize the integration of traditional dance system and university dance performance course design, and provide a new way to innovate dance movements.

In the context of moral character formation within higher education, this research critically examines standardized education systems’ influence on student management quality across universities and colleges in China. Analyzing annual reports from institutions in 31 provinces using sophisticated threshold regression models, the study quantitatively demonstrates the positive impact of education system standardization on management quality, with a 1% standardization increase resulting in a 0.527% enhancement in management effectiveness. The investigation further uncovers the threshold effects of humanization, professionalism, and system participation on student management, highlighting the importance of a humanized education approach. Notably, the research elucidates the mediating impact of teaching quality on this relationship, advocating for reinforcing educational system standardization and teaching quality as essential strategies for improving student management and academic quality.

Digital media animation can better promote folk culture inheritance and innovation, and at the same time, folk culture also provides rich inspiration materials and cultural elements for the creation of digital media animation. In this paper, the mathematical structure of the threshold regression model is first sorted out, and the parameters of the model are estimated by using the search method and the smooth least squares method. Secondly, it analyzes the promotion effect of digital media animation on the dissemination of folk culture, takes the 2D animated short film “Red Bank” as a research example, and designs a questionnaire to obtain the research data. Finally, the benchmark regression model and threshold regression model were established with folk culture dissemination as the dependent variable, and benchmark regression, robustness test, and threshold effect verification were conducted. The results show that the audiovisual language, creation method, and display medium of digital media animation are significantly correlated with folk culture dissemination at 1% level, and its R2 fit value reaches 0.7439. The level of development of digital media technology has an obvious double-threshold effect on the dissemination of folk culture, and its double-threshold value is 1.028 and 2.251 respectively. Digital media animation can enhance the dissemination medium of folk culture, expand the dissemination medium, and improve the quality of folk culture. Communication media and enhance the influence of folk culture.

Using the 2018 CHARLS data, this paper empirically analyzes the impact of income on the depression level of elderly people. Research has found that as income increases, the level of depression among the elderly significantly decreases, thereby improving their mental health level. The multiple ⁃ threshold regression estimation results indicate that income has a dual threshold effect on the depression level in elderly people. The effect of income is non⁃linear, and as the income level increases, the positive impact of income on the mental health of the elderly decreases. Further research shows that urban and male elderly people have higher income thresholds, while rural and male elderly people exhibit more complex non⁃linear changes. Finally, this paper suggests improving the security level for the elderly and sharing the fruits of economic and social development; developing human resources for the young elderly and ensuring their re⁃employment; encouraging elderly people to participate in social activities and providing non⁃cash social support. [ABSTRACT FROM AUTHOR]

The policy objectives of affordable housing programs in China are two-fold: on the one hand, they are designed to assist low- and moderate-income families and reduce inequality; on the other hand, they are intended to lower commodity housing prices. However, the effects of affordable housing land on housing prices, particularly the between-city variation and the mechanisms behind the market effects, have not been sufficiently examined, making it difficult to evaluate the housing policy and improve it accordingly. In this study, we address these gaps by using a prefecture-level panel dataset covering 2009–2020, obtained from national land and housing transaction information platforms. We use a threshold model to investigate the threshold effect of population size and a mediating model to uncover the channels through which the supply of affordable housing land affects housing prices. The results confirm that the affordable housing land supply can have a beneficial influence in terms of slowing down the increase in housing prices. The population size plays a significant role in explaining the between-city market effect variations. In cities with a population greater than 10.78 million, increasing the supply of affordable housing land would cause the housing prices to increase. Meanwhile, in cities with smaller populations, increasing the supply of affordable housing land could lower the housing prices. The underlying mechanisms of the market effects vary across cities with different population sizes. Although affordable housing land crowds out commodity housing land in all cities, housing demand diversion only exists in cities with a smaller population. At present, China is experimenting with city-specific housing policies; our findings imply that decision makers should explore additional policy options, besides building on incremental construction land, in order to make housing more affordable in supercities in China.

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Promoting industrial structure optimization and improvement on the basis of environment regulation based on “China's carbon peak and carbon neutralization” turns out to be a requirement that cannot be avoided for achieving China's economic growth with high quality. In this study, a dynamic game model for enterprises and governments in local areas with two phases, covering a polluting production sector and a clean production sector, is built for analyzing the influence mechanism of environment regulation of local governments on industrial structure optimization. Panel data of 286 cities on the prefecture level and above from 2003 to 2018 served as samples. The direct and dynamic impacts of environment regulation on industrial structure optimization are empirically tested, and the threshold model is adopted to test whether industrial structures and resource endowment will affect the effect of environment regulation on industrial structure optimization. Lastly, the effect exerted by environment regulation on industrial structure optimization is tested by region. The empirical results show that there is a nonlinear correlation of environment regulation and industrial structure optimization. Once the environment regulation intensity reaches a certain inflection point, it will hinder industrial structure optimization. When regional resource endowment and the secondary industry's ratio are used as threshold variables, environment regulation has a threshold effect on industrial structure optimization. The effect exerted by environment regulation on industrial structure optimization has regional heterogeneity.

The digital transformation in developing countries is crucial in determining whether environmental regulations can better facilitate green technological innovation. This paper constructs a theoretical model to deduce the relationships among digital transformation, environmental regulations, and green technological innovation. Empirical research is conducted using a two-way fixed-effects model and a threshold regression approach, based on provincial panel data from China spanning the years 2013 to 2020. The results indicate that environmental regulation inhibits green technological innovation. However, digital transformation, by reducing cost pathways, can promote the efficiency of green technological innovation under environmental regulation. This moderating effect exhibits a nonlinear threshold characteristic. Regarding dimensions of digital transformation, the level of digital investment shows no threshold, while both the level of digital application and the scale of digital integration exhibit threshold effects. Presently, in China, digital transformation effectively incentivizes green technological innovation under environmental regulation. Therefore, increasing digital investment, advancing digital applications, and fostering digital integration are inevitable choices to drive green technological innovation under the pressure of environmental regulation.

Amidst the compounded challenges posed by global climate change and urbanization on forest ecosystems, the integration of urbanization control measures within a climate-focused framework may offer an avenue for breakthroughs. This study delves into the impact of climate, specifically hydrothermal conditions, on the complex interplay between urbanization (Urb) and forest ecological function (Eco) in the Yellow River Basin (YRB) in China. Our findings reveal: (1) The application of a coupled coordination model reveals a stronger alignment between urbanization and forest ecological function in the warm and humid regions in the YRB. (2) Through the cross-sectional threshold regression model, we elucidate the diverse responses of Urb to Eco across varying climate gradients. Among them, annual precipitation shows a double-threshold effect at 532.34 mm and 694.18 mm. As precipitation increases, the impact of Urb shifts from negative to positive on Eco. Moreover, in regions with precipitation below 532.34 mm and above 694.18 mm, the absolute value of response coefficients of Eco to Urb is amplified. Annual average temperature displays a single-threshold effect at 10.11 °C, leading to a transition from negative to positive impact as temperature rises. This study establishes the climate-based threshold system that governs the urbanization–forest ecological function relationship.

This study seeks to expand upon existing empirical results about the effect of debt on corporate profitability. Indicators Debt ratio (DR) and Return on Equity (ROE) were used to examine the relationship between debt and corporate profitability. The input data for the analysis represented the financial data of companies operating in the construction industry in Slovakia. The total sample included 7,529 companies. After excluding companies with extreme values, the sample consisted of 6,402 companies. Indicators ROE and DR were used in the given research. To determine the debt threshold, a threshold regression model was applied. Using this model, a nonlinear relationship between debt and profitability was found. An indebtedness threshold has also been identified. Once the threshold is exceeded, the positive relationship between indebtedness and ROE changes to negative. The results, in particular those which indicate a significant non-linear relationship between debt and profitability, are particularly useful for all stakeholders (internal and external) interacting with analyzed companies. AcknowledgmentsThe research was prepared within the grant scheme VEGA 1/0741/20 – The application of variant methods in detecting symptoms of possible bankruptcy of Slovak businesses in order to ensure their sustainable development.

The effect of public indebtedness on output has attracted much public attention in the aftermath of the financial crisis. The study examined the impact of public debt on per capita GDP growth of South Africa using quarterly data spanning from 1960 to 2019. This study applied the threshold regression model to find the tipping point of public debt at an aggregated level and disaggregated level, domestic and foreign debt. The findings of the threshold regression revealed a non-linear impact of total public debt; domestic debt and foreign debt on growth with a turning point - beyond which the debt-to-GDP ratio has a negative impact on long-term growth at about 34.9 percent, 30.3 percent and 4.19 percent of GDP respectively. The findings of this study rule out the policy option for excessive dependence on higher debt to stimulate economic growth for South Africa. Thus, the South African government should ensure that public debt management policies are consistent with the growthmaximizing public debt threshold. [ABSTRACT FROM AUTHOR]

Serious air pollution has occurred in China since 2012. With the increasing investment in technological innovation in China, the role of green technological innovation in reducing air pollution has attracted more and more attention. By constructing the spatial Durbin model and threshold regression model and using the statistical data of China's provinces, this study explores the spatial effects and threshold characteristics of China's green technology innovation on the environmental pollution of China's air pollution-intensive industrial agglomeration. The research objective is to find out the spatial effects and threshold characteristics of green technology innovation on the environmental pollution of China's air pollution-intensive industrial agglomeration. The results show that thermal power, etc., air pollution-intensive industrial are important sources of sulfur dioxide emissions; however, their degree of concentration is gradually increasing, resulting in rising sulfur dioxide emissions in these areas. When the level of green technological innovation is greater than 8.0523, its inhibition effect on sulfur dioxide emissions in these industries is significantly increased. Improving green technology innovation ability in thermal power, etc., air pollution-intensive industrial agglomeration areas can effectively reduce pollution in the atmosphere. The level of green technology innovation in key zones must be increased to adjust the concentration of pollution-intensive industries, improve China's industrial structure, and reduce atmospheric environment pollution. [ABSTRACT FROM AUTHOR]

Questions persist on the relationship between tourism dependence and economic growth in ethnic tourism areas. This study addresses such gaps by constructing a threshold regression model based on socio-economic data from 2006 to 2019 for nine sites in Enshi Prefecture of central China. ArcGIS and other open-source data were also used to visualize changing tourism resources in the region. Findings suggest that tourism dependence (the ratio of tourism-based GDP to overall GDP) significantly promotes economic growth in ethnic minority areas. However, the positive influence of tourism dependence on economic growth appears dynamic and non-linear — rising at first before falling when tourism dependence exceeded a threshold of 34%, with effects varying by site and year. Methods and findings make crucial theoretical contributions to understanding tourism dependence and poverty alleviation linkages. This paper also highlights the importance of political support and balanced investment in diverse industries to minimize decreasing returns beyond tourism dependence thresholds in destinations worldwide. [ABSTRACT FROM AUTHOR]

Land-use transition (LUT) refers to the change in the land-use form corresponding to the regional economic and social development. At different stages of LUT, changes in the land-use scale and structure may lead to carbon source transfer by affecting industrial transfer and carbon sinks, resulting in changes in the total carbon emission transfer (CET) from the land use in the whole region. The clarification of the relationship between LUT and CET is of great importance for the sustainable development of the regional economy and society and the realization of carbon peak and carbon neutrality. In this paper, we firstly conducted a theoretical analysis of the nonlinear relationship between LUT and CET, then took the Middle Reaches of the Yangtze River in China as an example to explore the characteristics of LUT and CET, and finally constructed a threshold regression model to verify their nonlinear relationship. The following main findings were obtained. (1) From 2000 to 2020, profound LUT had occurred in the Middle Reaches of the Yangtze River, with continuous decreases in farmland, substantial increases in construction land, and a first decrease and then increase in forest land; farmland is the main contributor to construction land and forest with a contribution rate exceeding 60%. (2) During the study period, the CET in the Middle Reaches of the Yangtze River exhibited certain regular characteristics. The phase characteristics of the carbon sink changes follow an intensification–moderation–reintensification–remoderation pattern, and those of the carbon source transfer and net carbon emissions follow an intensification–reintensification–moderation–remoderation pattern. In addition, carbon sink changes are far from enough to offset the effect of carbon source transfer. (3) The nonlinear relationship between LUT and CET was confirmed by the threshold effect at the economic development level, industrial optimization level, and technological progress level. The nonlinear relationship between the LUT and the carbon sink changes in the Middle Reaches of the Yangtze River is on the left side of the U-shaped curve and that between the LUT and the carbon source transfer or net carbon emissions is on the left side of the inverted U-shaped curve. [ABSTRACT FROM AUTHOR]

Despite mass mortality, hard clams remain among the main cultured shellfish in Taiwan. Using cross-sectional data, this study applies threshold regression modeling with stocking density and feed costs as the threshold variables to explore the nonlinear relationship between input and output factors. The findings show that the production output levels may be increased by different combinations of factor inputs and variations in input factors. More specifically, the higher output levels may be achieved by increasing labor input while reducing capital input factors in farming households with a higher stocking density (HSD > 1,087,870 inds/ha) or higher feed cost (HFC > 13,889 NTD/ha). Farming households with a lower stocking density (LSD ≤ 1,087,870 inds/ha) may enhance production output levels by increasing feed input while reducing capital inputs. Moreover, the maximum output level of HSD and HFC farming households was estimated to reach 9255 kg/ha and 9807 kg/ha, respectively. Results of the production output simulation suggest that the feeding cost per hectare in LSD households should not exceed 25,119 NTD to avoid overfeeding, which may cause culture deterioration and lower survival rates. As such, farmers are advised to adjust their feed costs according to the stocking density to maximize production output. [ABSTRACT FROM AUTHOR]

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society. [ABSTRACT FROM AUTHOR]

With the rise of “Internet + Agriculture”, existing related research has focused on the impact of Internet use on agricultural productivity. However, few studies have considered the impact on agricultural green production efficiency. This paper employed the SBM model to calculate the agricultural green production efficiency using the observation data of 459 farmers in Shaanxi, Shanxi, and Henan provinces. Further, the influencing factors, their nonlinear impact, and even the effect of using the internet on agricultural green production efficiency were analyzed. The results show that corn’s average agricultural green production efficiency is 0.44, with the main peak distributed in a low-level range. The impact of the Internet use on agricultural green production efficiency is positively moderated by rural infrastructure, household assets, and educational attainment. Age and arable land area significantly impact agricultural green production efficiency. The endogenous switching regression model (ESR) shows that the agricultural green production efficiency of farmers who do not use the internet will increase by 41.45% if they use the internet. Internet use has a “U-shaped” impact on agricultural green production efficiency, and the threshold value of the farmers’ expenditure to income ratio is 0.0886. The policy aimed at improving agricultural green production efficiency and popularizing Internet use should, therefore, focus on strengthening the emphasis on increasing agricultural green production, increasing investment in rural human capital, providing green production subsidies and green production skills training, improving infrastructure construction in rural areas, integrating and enriching agricultural-related information on the Internet.

Research background: The modern economy is characterized by extreme complexity, and in today's global world it is challenging to ensure financial stability and increase financial performance. Every enterprise tries to increase its financial performance and competitiveness. It therefore seems appropriate to look for applicable models, that can increase financial performance and competitiveness of companies. Purpose of the article: The paper deals with modelling the relationship between financial indicator of profitability and financial indicators of activity, liquidity, and indebtedness. The aim of this article is to analyse the dependence of financial indicator of profitability (return of sales - ROS) on financial indicators of activity (turnover of assets - TA), indebtedness (total indebtedness - TI, financial leverage - FL), and liquidity (net working capital to assets ratio - NWC/A) of companies in the electrical engineering industry of the Slovak Republic. Methods: The analysis was carried out using the financial indicators of 2,947 companies for the period 2017-2019. Statistica and Stata programs were used to analyse input data and develop threshold regression models. Input data analysis was performed using Kernel density estimation - Epanechnikov. Threshold regression models will be used for dependency analysis, where the threshold variables will be successively the indicators TA, TI, FL, NWC/A. Findings & Value added: Knowing the relationship between financial indicator of profitability and financial indicators of activity, liquidity, and indebtedness enables more efficient business management. Knowing the coefficients and threshold values for individual industries can be used to optimize the company's debt policy in the relevant industry. The constructed models can be a starting point to improve financial health, prosperity, and competitiveness of analysed businesses. Our analysis is an important prerequisite for developing a realistic financial plan for companies operating in the electrical engineering industry in the Slovak Republic. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development.

This paper uses the global Malmquist–Luenberger index to investigate changes in road transportation green productivity from 2010 to 2017, incorporating undesirable outputs into the analytical framework. Furthermore, the relationship between environmental regulation and green productivity is tested by the panel threshold model. At the area level, the improvement of green productivity in western China benefits from a catch-up effect and improved scale efficiency. Moreover, the driving factor improving green productivity in China's central and eastern areas is mainly the scale economy, and technology regress is the hindering factor. Research and development investment and government fiscal expenditure both show a single-threshold effect on green productivity. That is, their values in relation to thresholds cause differences in the impact of environmental regulation on green productivity. Our analysis shows that economic development can significantly promote green productivity, while highway density can significantly hinder it. Based on the evidence presented, we put forward practical suggestions for improving green productivity. [ABSTRACT FROM AUTHOR]

Copyright of Global Journal of Economics & Business Studies is the property of Gumushane University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Physical Education / Tiyu Xuekan is the property of Journal of Physical Education Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the course of China's rapid economic development, the coexistence of industrial development and dominant industrial agglomeration (AGG), along with growing environmental problems, has attracted widespread attention from scholars. Although the linear relationship between the two has been analyzed in depth in the research literature, a concomitant phenomenon, i.e., the gradual expansion in the scale of foreign direct investment (FDI), has been overlooked. By employing threshold panel regression model, this paper attempts to construct a theoretical model with embedded AGG and FDI, and incorporates other factors affecting environmental pollution (POL). For examining the mechanism of AGG on POL, we proposed a testable theoretical hypothesis, and conducted an empirical study by combining panel data of POL and AGG at the provincial level in China. The measurement index of a control variable was changed to check the robustness of our results, and the coefficient sign of each explanatory variable was not changed, confirming the robustness of main results. Overall, AGG improves regional POL, but the impact of FDI is stage-specific and roughly there are three stages. Specifically, the positive effect of AGG on POL is strong when FDI is at a low level. When the level of FDI crosses the first threshold and continues to rise, the positive effect of AGG on POL reaches its strongest; until the second threshold is crossed, the positive effect of AGG starts diminishing slowly. Concluding this, for promoting economic development and environmental protection in the region in parallel, government and enterprises should prioritize the increment in FDI, with an equalization of levels of AGG and FDI, in order to enhance the improvement effect of AGG on POL. [ABSTRACT FROM AUTHOR]

Technological innovation is increasingly becoming an important way to develop a low-carbon economy. Recently, exploring the driving path of low-carbon development has become the hot topic, however, the role of energy consumption in the carbon-reduction effect of technological innovation has been ignored. Based on China's provincial-level panel data from 2005 to 2016, this paper investigates the effect of technological innovation on energy saving and carbon emissions reduction and the role of energy consumption in the influencing process by using linear regression model, mediating effect model and threshold regression model. The results show that technological innovation has effectively promoted energy saving and carbon emissions reduction in China, with different effect coefficients between the three areas of China. Moreover, energy consumption plays a significant partial mediating role in the effect of technological innovation on carbon emissions reduction. Finally, the effect of technological innovation on carbon emissions is limited by energy consumption. Low energy consumption significantly promotes a reduction in carbon emissions through technological innovation. Once energy consumption exceeds a critical level, the promoting effect of technological innovation on carbon emissions reduction will turn into the inhibiting effect. Based on these findings, some policy recommendations are put forward to accelerate the low-carbon transformation of the economy.

This study aims to evaluate the changes in the credit risk of the health care industry in China due to the COVID-19 epidemic by the modified KMV (named by Kealhofer, Mcquown, and Vasicek) model to calculate the default distances. We observe that the overall default distance mainly first decreased and then increased before and after the COVID-19 epidemic control in China; after the epidemic was controlled, the overall credit risk was reduced by 22.8%. Specifically, as shown in subdivided industries, health care equipment and health care facilities have larger credit risk fluctuations, while health care suppliers, health care distributors, and health care services have smaller fluctuations. These results can contribute to our understanding of why the COVID-19 epidemic in China could be controlled earlier, and software facilities are more important than hardware facilities in public health safety. Our methodological innovation is to use the GARCH (generalized autoregressive conditional heteroskedasticity) model and threshold regression model to modify the important parameters of the KMV model. This method has good accuracy in the Chinese environment.

Land-use transition (LUT) refers to the change in the land-use form corresponding to the regional economic and social development. At different stages of LUT, changes in the land-use scale and structure may lead to carbon source transfer by affecting industrial transfer and carbon sinks, resulting in changes in the total carbon emission transfer (CET) from the land use in the whole region. The clarification of the relationship between LUT and CET is of great importance for the sustainable development of the regional economy and society and the realization of carbon peak and carbon neutrality. In this paper, we firstly conducted a theoretical analysis of the nonlinear relationship between LUT and CET, then took the Middle Reaches of the Yangtze River in China as an example to explore the characteristics of LUT and CET, and finally constructed a threshold regression model to verify their nonlinear relationship. The following main findings were obtained. (1) From 2000 to 2020, profound LUT had occurred in the Middle Reaches of the Yangtze River, with continuous decreases in farmland, substantial increases in construction land, and a first decrease and then increase in forest land; farmland is the main contributor to construction land and forest with a contribution rate exceeding 60%. (2) During the study period, the CET in the Middle Reaches of the Yangtze River exhibited certain regular characteristics. The phase characteristics of the carbon sink changes follow an intensification–moderation–reintensification–remoderation pattern, and those of the carbon source transfer and net carbon emissions follow an intensification–reintensification–moderation–remoderation pattern. In addition, carbon sink changes are far from enough to offset the effect of carbon source transfer. (3) The nonlinear relationship between LUT and CET was confirmed by the threshold effect at the economic development level, industrial optimization level, and technological progress level. The nonlinear relationship between the LUT and the carbon sink changes in the Middle Reaches of the Yangtze River is on the left side of the U-shaped curve and that between the LUT and the carbon source transfer or net carbon emissions is on the left side of the inverted U-shaped curve.

Introduction: Tea is one of strategic products in north of Iran with a history of 120 years. However, Per capita consumption of tea in Iran from 1977 to 2016 reached from 2.1 kg to 5.1 kg. Increasing consumption lead to accurate estimation of tea demand and supply and would help to adopt effective policies. Materials and Methods: annual prices and demand data is used for estimation Threshold regression model. The supply elasticities are calculated by original Nerlovian partial adjustment framework. Findings: The Hansen test showed that per capita income had two regimes (one threshold) in this study. The level of income threshold is about 20 million Rials. This study, with the estimation of nonlinear structure in tea demand, showed that, income elasticity for both high and low income level is positive and significant Conclusion: For low-income groups, tea is an inelastic and essential commodity that tends to become more elastic as income increases. Income elasticity of demand is positive and significant for both high and low income groups. The results showed that the possibility of increasing production by increasing the cultivation area is limited. [ABSTRACT FROM AUTHOR]

While numerous studies have demonstrated the effects of density and diversity on metro ridership, few studies have explored the long-term mechanisms of these effects. Employing smartcard data and multisource big data from Wuhan between 2015 and 2019, this study applied the panel threshold model to explore the long-term threshold effects of station area density and diversity on metro station-to-station ridership. The results indicated that only when development intensity and land use mix exceeded the threshold values would there be significant positive impacts on ridership at the origins and destinations, and the ridership benefits were significantly reduced when the origin intensity exceeded 1.622 or when the mix exceeded 0.635. Additionally, population density, POI mixture, bus stops and parking lots, station, and network attributes had long-term significant impacts on metro ridership. These findings can contribute to implementing differentiated land development patterns and promoting the sustainable development of TOD strategies. [ABSTRACT FROM AUTHOR]

Despite mass mortality, hard clams remain among the main cultured shellfish in Taiwan. Using cross-sectional data, this study applies threshold regression modeling with stocking density and feed costs as the threshold variables to explore the nonlinear relationship between input and output factors. The findings show that the production output levels may be increased by different combinations of factor inputs and variations in input factors. More specifically, the higher output levels may be achieved by increasing labor input while reducing capital input factors in farming households with a higher stocking density (HSD > 1,087,870 inds/ha) or higher feed cost (HFC > 13,889 NTD/ha). Farming households with a lower stocking density (LSD ≤ 1,087,870 inds/ha) may enhance production output levels by increasing feed input while reducing capital inputs. Moreover, the maximum output level of HSD and HFC farming households was estimated to reach 9255 kg/ha and 9807 kg/ha, respectively. Results of the production output simulation suggest that the feeding cost per hectare in LSD households should not exceed 25,119 NTD to avoid overfeeding, which may cause culture deterioration and lower survival rates. As such, farmers are advised to adjust their feed costs according to the stocking density to maximize production output.

In the past two decades, both housing prices and carbon emissions have risen dramatically in China. However, it is unclear whether there is a nexus between them. This study employs a dynamic panel threshold regression model using residents' income levels as the threshold variable to investigate the relationship between housing prices and per capita carbon emissions. By considering 60 Chinese housing price-monitored cities, a threshold effect of income on carbon emissions was identified with a threshold value of 2.448, which divided the full sample into two regimes to further analyse the impacts of housing prices on per capita carbon emissions at each income level. The empirical results show that housing prices have a slight but positive effect on per capita carbon emissions both at two income levels. Specifically, a 10% change in housing prices can lead to a change in the same direction in per capita carbon emissions by 0.7% and 0.2% at lower and higher average income levels, respectively. However, in small cities, limited population may contribute to the negative impact of housing prices on carbon emissions. Furthermore, the results also confirm that the urbanization rate is an important factor of per capita carbon emissions. [ABSTRACT FROM AUTHOR]

Rased on the survey data of 1 061 households in Hubei Province, this paper analyzes the impact of labor migration and village identity on farmers' participation in rural living environment improvement programs by constructing a binary logit model and a threshold regression model. The results show that; (J) Labor migration has a significant impact on farmers' participation, while the effect of village identity is significantly positive. (2) For farmers with different levels of village identity, labor migration has different effects on their participation. As the village identity becomes strong, the positive effects of labor migration on farmers' participation can be improved. In particular, when the degree of village identity exceeds the threshold value, the impact of labor migration on farmers' participation will change from negative to positive. (3) Considering the possible endogenous problems and using the length of residence as a tool variable to estimate IV Probit, the impact of labor migration and village identity on farmers' participation is robust. This paper reveals that labor migration as the link of capital elements flowing into the countryside does not cause the decline of the countryside, but creates the endowment conditions for farmers to participate in public affairs. And only by triggering the village identity can labor migration achieve its positive effect. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University (Science Edition) is the property of Journal of Zhejiang University (Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The problem of unemployment has special importance because of its economic and social dimensions. That also has become a chronic economic problems for Turkey's economy and continuing the fight against unemployment for special measures to be taken, it reveals the importance of the unemployment problem for Turkey's economy. In this study, the macroeconomic determinants of unemployment in Turkey has tried to be analyzed for 2005.1- 2018.11 period. In the study, the determinants of the number of unemployed were analyzed by using the ARDL model as well as DOLS, FMOLS and Threshold regression models. According to the findings of the ARDL model, industrial production affets negatively the number of unemployed people in line with expectations, and the CPI and interest rate affects positively. The real effective exchange rate affects the number of unemployed positively, but its coefficient is statistically insignificant. FMOLS, DOLS and Threshold Regression models have also similar results with the ARDL model for Turkish Economy. [ABSTRACT FROM AUTHOR]