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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]

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]

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]

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]

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]

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]

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]

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]

This paper analyzed the coupling relationship between the carbon market and power market and constructed a threshold regression model of carbon cost pass-through to electricity prices. Furthermore, a system dynamics model was built based on "electricity-carbon" market. The results show that first, the carbon market and power market operate independently but are interrelated. The two markets will work when Chinese emission allowances and carbon prices are effectively connected with carbon emissions and electricity prices. Second, because the electricity price formation mechanism is mainly regulated by China's government, the carbon price has a significant negative effect on the electricity price since the operation of the national carbon trading system. There is no obvious linkage effect between the CO 2 cost and electricity price. Third, under the current policies and market mechanism, the carbon price will experience the process of "remain low-rapid rise-remain high". The carbon price will drive the on-grid price and sales price up. The allowance auction mechanism and carbon cost direct pass-through can effectively reflect CO 2 cost in the electricity price. In the long term, introducing auctioning in the carbon market and reforming electricity price formation in the power sector will tap the emission reduction potential. [Display omitted] • Design of coupling relationship between China's electricity market and national ETS. • Measure the carbon cost pass-through rates in electricity market. • Build the system dynamics model of national ETS and electricity market. • Explore the factors that affect the effectiveness of CO 2 cost pass-through. [ABSTRACT FROM AUTHOR]

The relationship between agricultural production factor prices and production performance has long been a topic of academic discussion. However, current research has paid relatively little attention to the problem of scale efficiency losses in agricultural production caused by deviations in farmland prices. In order to explore the development direction needed to improve China's agricultural competitiveness, we analyzed the deviation mechanism of farmland prices in China and the loss of scale efficiency of agricultural production due to high farmland prices, starting from the perspective of farmland price deviation. Accordingly, based on 1188 micro-farm household survey samples, a threshold regression model was used to provide empirical support for our theoretical analysis in two dimensions: full samples and differentiation of farmland use types. The empirical results show that the problem of high farmland prices prevails throughout China, with the mean farmland price deviation (abbreviated as DEV) in Chinese provinces reaching 1.42, and it is especially high in Shandong (1.88), Henan (1.67), and Heilongjiang (1.59). The deviation is mainly caused by China's special resource endowment and farming culture. At the same time, the current scale efficiency of agricultural production in Chinese provinces is inadequate, with a mean value of only 0.70, and approximately 65% of farmers' actual input size is significantly lower than the optimal input size. The threshold effect test shows that the effect of farmland cost increase on agricultural production scale efficiency exhibits a structural shift from promoting to inhibiting as the degree of farmland price changes from low to high. In particular, in the scenario of overpriced farmland (DEV ≥ 1.16), farmland cost increase inhibits the growth of China's agricultural production scale efficiency. In addition, there is heterogeneity across farmland uses, with grain crops being more likely to be scale-efficient (0.74) than nongrain crops (0.62). The threshold regression results between the grain and nongrain groups further reveal that in the high farmland price scenario, grain crops are more severely inhibited by the rising cost of farmland than nongrain crops. Ultimately, we propose an optimal solution to improve the performance of agricultural production in China in two dimensions: reducing farmland cost and promoting service scale operation. [Display omitted] • The reality of high farmland prices exists in China. • The current scale efficiency of agricultural production in China is still insufficient. • Structural changes emerge in the impact of rising farmland cost on scale efficiency due to farmland price deviation. • Farmland with grain crops is more severely affected by higher farmland prices than nongrain crops. [ABSTRACT FROM AUTHOR]

Rather than attempting to balance the environment with the economy (i.e., a zero-sum game), a theoretically better long-term approach would be to achieve harmonious development in which both the environment and the economy benefit. To provide insights into this suggestion, we analyzed the relationships between environmental quality and economic development in China through a threshold regression model based on panel data from 292 cities from 2007 to 2018. We found that the relationship between environmental quality and economic development represented a negative interaction before or after the relationship passed through a zone of temporary balance, but that attaining a high urbanization level (in this case study, 81.0%) could improve the efficiency and capital utilization rate of environmental governance and change the impact from negative to positive, thereby achieving harmonious development rather than a zero-sum game. The government should therefore take measures to increase urbanization so as to achieve more harmonious development of the environment and economy (i.e., a win–win situation). [ABSTRACT FROM AUTHOR]

Balancing the housing supply structure is important for the healthy development of the real estate market. China has invested considerable effort in improving the rental housing market in recent years. To explore the asymmetric effects of the rental housing supply scale on house prices, we constructed an analysis framework for the rental and sales markets based on substitution between owning and renting. Then, we reviewed the development of China's rental housing market and used a threshold regression model to empirically study 29 large and medium-sized cities during the period 2008–2019. The results indicated that there was weak substitution between owning and renting a dwelling in China's housing market. On the premise that weak substitutability cannot be changed, measures for increasing the supply of rental housing could not attract consumers to the rental housing market and thus could not curb increases in house prices. The substitution of rental housing and self-owned housing was vital for explaining the linkage between rental housing supply and housing price. Under the low substitutability regime, increasing the supply scale of rental housing caused house prices to rise significantly. Instead, in some cities with the high substitutability, increasing the supply of rental housing could lower house prices. And our findings implied that decision-makers should pay attention to irregularities in the rental market and stimulate the endogenous motivation of both supply and demand instead of relying on exogenous means. • We clarified the source of the weak substitution relationship between rental and self-owned housing. • An analysis framework for the rental and sales markets based on supply-and-demand theory was constructed. • A threshold regression model was used to study the effect of the supply scale of rental housing on house prices. • The substitution of rental and owned housing was vital for the linkage between rental housing supply and housing price. • When weak substitutability cannot be changed, increasing the supply of rental housing could not curb the rise of house prices. [ABSTRACT FROM AUTHOR]

This paper estimates the transport energy consumption of 30 provinces in China from 1997 to 2011. By applying the STIRPAT model, the relationship between urbanization and transport energy consumption using control variables such as population, GDP per capita and the proportion of tertiary industry in GDP is investigated. Considering the disparities of income, the impacts of urbanization on transport energy consumption might be distinct. Therefore, this paper estimates the income threshold value and analyzes the effects of urbanization on transport energy consumption in the light of income differential using the panel threshold regression model. Based on the results, some policy suggestions are offered. [ABSTRACT FROM AUTHOR]

Improving the ecological well-being performance (EWP) of natural resources and environmental consumption in relation to human well-being, within the ecological boundary, is necessary for sustainable development. This study used the Super-SBM model to measure the urban EWP of urban agglomeration in the middle reaches of the Yangtze River (MRYRUA) in 2020. The spatial differentiation characteristics of EWP in the MRYRUA were identified. The heterogeneity in the direction and size of the influencing factors of EWP at different urban hierarchy (UH) levels was empirically tested by establishing a threshold model. The results are as follows: (1) In 2020, the EWP of the study area showed a trend of high levels in the southwest and low levels in the northeast. The EWP presented a multi-center "core-periphery" distribution, and the characteristic of "central collapse" was evident. The UH level of the middle and lower hierarchy-level cities was inconsistent with its EWP. (2) A non-single linear relationship was found between the influencing factors of the EWP of the MRYRUA and the EWP. The impacts of technological progress, industrial structure, environmental regulation, and population density on the EWP of the MRYRUA all showed threshold characteristics. (3) Heterogeneity and stages were both observed for the influencing factors of EWP under different UH levels. The effect of technological progress on EWP presented the characteristics of bidirectional and two-stage developments, and environmental regulation presented the features of a significant positive three-stage development. Both industrial structure and population density presented two-stage aspects, but the former acted in a negative direction, while the latter served in a positive order. This study provides a theoretical basis for the government to formulate differentiated regional policies and promote the coordinated improvement of EWP among cities at all hierarchy levels in the urban agglomeration. This study is of great significance to the sustainable development of urban agglomerations. Its results can provide a reference for other urban agglomerations, metropolitan areas, and city clusters worldwide to coordinate economic development, ecological protection, and to improve people's well-being.

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., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Taking 286 cities above the prefecture level in China as the research object and the research period from 2003 to 2019, through the two-way fixed effect model, this paper empirically analyzes the impact of the city level on environmental collaborative governance. The threshold regression model is used to reveal the nonlinear relationship between urban levels and environmental collaborative governance and to analyze the phase characteristics of different urban levels for environmental collaborative governance. The results show that: (1) The city level has a significant role in promoting collaborative environmental governance. (2) The regression results of the three major sections show that the urban level promotion in the eastern region has the strongest promoting effect on the coordinated environmental governance, and the western region is the weakest. (3) The impact of the city level on collaborative environmental governance is nonlinear. When the city scale reaches a certain critical point, its impact on the collaborative environmental governance tends to intensify.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yan, Tang, Wang and Gao.)

R&D investment is the source of technological innovation of pharmaceutical enterprises, but it will be restricted by the funding level, especially in the context of major public health emergencies occurring more frequently, therefore exploring the impact of monetary policy uncertainty on the R&D investment smoothing behavior of pharmaceutical manufacturing enterprises has important theoretical and practical value. Based on the relevant data of Chinese pharmaceutical manufacturing enterprises from 2012 to 2018, this paper studies the impact of monetary policy uncertainty on R&D investment smoothing behavior of pharmaceutical enterprises, and investigates whether there is a threshold effect. First, our results demonstrate that the empirical test results of this article support the hypothesis of R&D investment smoothing behavior of pharmaceutical manufacturing enterprises. Second, there is a negative correlation between monetary policy uncertainty and R&D investment smoothing behavior, and the shorter the period is, the higher the financing constraints of pharmaceutical enterprises are, and the more obvious the negative correlation is. Third, financing constraints have a single threshold effect on the R&D investment smoothing behavior of pharmaceutical manufacturing enterprises, with a threshold of -13.7693. Moreover, this conclusion can better promote the virtuous circle of the real economy of financial and pharmaceutical manufacturing enterprises. It is recommended that pharmaceutical manufacturing enterprises establish and improve the enterprise R&D reserve system, reduce the risk of R&D investment, play the role of R&D smoothing, and realize the sustainable development of enterprise R&D.

As the largest CO 2 emitter in the world, China plays a crucial role in global CO 2 emission reduction. Meanwhile, as the largest developing country, China gives top priority to economic development, especially balanced regional development. In order to narrow regional development inequality, China has formulated some economic zone plannings to weaken market segmentation. However, existing studies pay little attention to the impacts of intra-national trade barrier on CO 2 emissions within China. This is the first study to investigate the impact of market segmentation on urban CO 2 emissions in China, taking the Yangtze River Delta region as a sample that is the most developed region with a high economic integration in China. Using a city-level panel data set during the period of 1995–2014 and the fixed effect model, we verify the nonlinear relationship between market segmentation and urban CO 2 emissions measured by three indicators, i.e., total CO 2 emissions, per capita CO 2 emissions and CO 2 emissions per unit of GDP. We also use the generalized method of moments (GMM) to control the endogeneity problem, and further adopt the threshold regression model to check the robustness of the baseline results. The results show that there is a U-shaped curve relationship between market segmentation and urban CO 2 emissions. A low level of market segmentation restrains CO 2 emissions, while a high level of market segmentation promotes CO 2 emissions. This finding is helpful to understand CO 2 emission trends and narrow regional economic inequality accompanied with the implementation of China's economic zone plannings. • We investigate the impact of market segmentation on urban CO 2 emissions in China. • We use a city-level panel data set in the Yangtze River Delta region over 1995–2014. • We use fixed effect model, generalized method of moments and threshold regression model. • There is a U-shaped curve relationship between market segmentation and CO 2 emissions. • Technique and composition effects are dominant when market segmentation level is high. [ABSTRACT FROM AUTHOR]