Threshold Effect Model Research Articles

Impact of “Non-Grain” in Cultivated Land on Agricultural Development Resilience: A Case Study from the Major Grain-Producing Area of Northeast China

Previous studies focused on the status and driving factors of non-grain cultivated land (NGCL), but lacked research on the impact mechanism of NGCL on sustainable agricultural development from the perspective of farmers’ household livelihoods and agricultural production factor allocation. Therefore, the concept of resilience was introduced. According to official statistics of China from 2010 to 2021, such as the local statistical yearbooks, the impact of NGCL on agricultural development resilience (ADR) in the main grain-producing area of Northeast China was explored based on the threshold effect model and the spatial lag model. The results indicate that: (1) the overall level of NGCI in the study area from 2011 to 2020 show an upward followed by a downward trend; (2) the size of agricultural labor force and average area per labor constrain the impact of NGCI on ADR, and the change can be characterized by negative to positive, increasing and then decreasing respectively, and the former is more constrained than the latter; (3) a negative effect of the NGCI trend on ADR exists without spatial spillover effect. The expansion of food production exacerbates the risk of factor mismatch, which is accentuated by the governance environment that pursues food production excessively. Establishing the NFP governance standards should consider the transformation of farmers’ livelihoods and the optimization of production factor allocation. Constructing a resilient risk management mechanism, promoting moderate scale operation and optimizing agricultural labor scale are specific paths for improving the governance mechanisms of NGCI. This study provides a theoretical reference for the development of policies and governance strategies for NGCI in underdeveloped areas.

Analysis of the Nonlinear and Spatial Spillover Effects of the Digital Economy on Carbon Emissions in the Yellow River Basin

Low-carbon development of the Yellow River Basin (YRB) is an inherent requirement for implementing ecological protection and high-quality development strategies in the YRB and an important way to achieve China’s carbon peak and neutrality goals. However, utilization of the newly emerging digital economy to reduce carbon emissions in the YRB remains a largely unexplored topic. Based on panel data obtained from 56 cities in the YRB from 2011 to 2019, the nonlinear and spatial spillover effects of the digital economy on carbon emissions were studied using spatial econometric and multiple threshold effect models. The results showed that: (1) The digital economy had an inverted U-shaped relationship with carbon emissions, initially increasing and subsequently decreasing, with a more prominent impact intensity in upstream cities; (2) The digital economy had distinct negative spatial spillover effects on carbon emissions, with more significant effects observed in the midstream and downstream; (3) The digital economy had a nonlinear threshold effect on carbon emissions. When the optimization level of the industrial structure was above a certain threshold, the digital economy reduced carbon emissions. Based on these results, we propose suggestions for accelerating the healthy growth of the digital economy while promoting carbon emission reductions across the YRB.

Research on the Heterogeneity Threshold Effect of Foreign Direct Investment and Corporate Social Responsibility on Haze Pollution

Carrying out environmental protection and governance in the process of using foreign capital to develop the economy is a realistic problem that China needs to solve urgently. In order to reduce environmental pollution, all enterprises are called upon by the local government to fulfil CSR and improve the quality of FDI use. However, previous studies have rarely explored the threshold effect of FDI and CSR on haze pollution. This paper employs the threshold effect model to explore the above problem based on panel data of 30 provinces in China from 2009 to 2018. The empirical study found the following: (1) FDI has a significantly positive double-threshold effect on haze pollution. Meanwhile, the promotion effect of FDI on haze pollution is the strongest in the two threshold ranges. (2) CSR has a significantly negative single-threshold effect on haze pollution; that is, the increase in CSR intensity inhibits haze pollution. Such a negative effect shows the characteristics of increasing marginal efficiency. (3) In addition, the provinces in different thresholds display obvious geographical distribution characteristics. Through the above analysis, it can be observed that FDI and CSR have distinct impacts on haze pollution. Thus, the country and the government can reduce haze pollution by improving the investment structure, using environmentally friendly technology, guiding enterprises to abide by business ethics and promoting social responsibilities fulfilment.

Research on the mechanism and countermeasures of digital economy development promoting carbon emission reduction in jiangxi province

The digital economy is an important driving force for China’s economic transformation and upgrading, while ‘carbon peak and carbon neutrality’ is the target vision to be achieved in China. As an important support area for the rise of central China, it is an urgent question to investigate whether the development of the digital economy in Jiangxi Province can contribute to the realization of carbon emission reduction. Based on the panel data of 11 urban areas in Jiangxi Province from 2011 to 2020, the article empirically investigates the impact of the digital economy on regional carbon emissions and its mechanism of action by using the two-way fixed-effect model, mediated-effect model, and panel threshold-effect model. The study shows that, firstly, the digital economy has a significant carbon emission reduction effect, and the conclusion still holds after a series of endogeneity and robustness tests. Second, the carbon emission reduction effect of the digital economy differs among different regions, and the carbon emission reduction effect of the digital economy is more obvious in northern Ganzhou and regions with high carbon emission levels. Again, the intermediary effect suggests that the digital economy can promote carbon emission reduction by strengthening the control of foreign investment introduction. Finally, the panel threshold effect analysis with urbanization as the threshold variable shows that there is a non-linear correlation between the effects of the digital economy on carbon emissions. The findings of this paper provide a feasible path and policy reference for Jiangxi Province’s digital economy to contribute to carbon emission reduction goals.

The Effect of Outward FDI on Capabilities of Sustained Innovation: Evidence from China

Based on theoretical analysis, this paper examines the impact of China’s outward foreign direct investment on regional capabilities of sustainable innovation. Empirical tests are used to analyze the mechanism of OFDI in regional capabilities of sustainable innovation. OFDI’s impact on sustainable innovation is tested through the fixed effect, mediation effect, and threshold effect models by using provincial panel data from 30 provinces in China from 2008 to 2019. The results show that OFDI promotes regional capabilities of sustained innovation. Moreover, the effect of OFDI on sustainable innovation is found to be mediated by regional human capital accumulation. Furthermore, this study also finds that regional absorptive capacity and financial market development are two significant threshold variables in the process by which OFDI affects sustainable innovation. Before the threshold variables exceed the threshold level, OFDI encourages sustainable innovation, but this positive association becomes stronger after threshold variables reach the threshold level. The results have strong policy implications, which will be useful for local governments to make policies with the aim to maximize the benefits of OFDI and encourage sustainable innovation.

How Operation Scale Improve the Production Technical Efficiency of Grape Growers? An Empirical Evidence of Novel Panel Methods for China’s Survey Data

The agricultural production technical efficiency is the key to improving the sustainability of an agricultural section. Taking survey data of 314 grape growers in Fujian Province, China, this paper presents the impact of operation scale on their technical efficiency under a rain-shelter cultivation mode. Through the threshold effect model, we find an inverted U-shape trend between operation scale and the growers’ technical efficiency, and the threshold is 18 mu. We also further introduce the employee input to analyze the mediating effect. The test results show that with the expansion of operation scale, the efficiency loss caused by greater employee input gradually suppresses the positive impact of economies of scale on technical efficiency—that is, there is a significant suppressing effect. Hence, this paper argues that, in the process of promoting agricultural green production, the government should guide farmers to a ‘natural flow’ to moderate scale management by reducing transaction costs, such as land transfer costs, and should not blindly encourage growers to expand their scale. At the same time, research and development of labor-saving technologies should be enhanced to reduce labor demand and cost in the production process.

Can the Sci-Tech Innovation Increase the China’s Green Brands Value?—Evidence from Threshold Effect and Spatial Dubin Model

Based on the perspective of the innovation value chain, sci-tech innovation is divided into two stages: R&D and achievement transformation. This paper uses panel data from 25 provinces in China as the sample. We utilize a two-way fixed effect model, spatial Dubin model, and panel threshold model to discuss the impact of two-stage innovation efficiency on the value of the green brand, the spatial effect of this impact, and the threshold role of intellectual property protection in the process. The results indicate that: (1) the two stages of innovation efficiency have a positive impact on the value of green brands, and the effect of the eastern region is significantly better than that of the central and western regions. (2) The spatial spillover effect of the two stages of regional innovation efficiency on the value of green brands is evident, especially in the eastern region. (3) The innovation value chain has a pronounced spillover effect. (4) The single threshold effect of intellectual property protection is significant. When the threshold is crossed, the positive impact of the two stages of innovation efficiency on the value of green brands is significantly enhanced. (5) The influence of economic development level, openness, market size, and marketization degree on the value of green brands shows remarkable regional differences. In conclusion, this study contributes to understanding green brands' growth and provides important implications for developing independent brands in various regions of China.

Impact of Population Aging on Carbon Emissions in China: An Empirical Study Based on a Kaya Model.

As the world's largest developing country, China is facing the serious challenge of reducing carbon emissions. The objective of this study is to investigate how China's aging population affects carbon emissions from the production and consumption sides based on an improved Kaya model. The advantage of the Kaya model is that it links economic development to carbon dioxide generated by human activities, which makes it possible to effectively analyze carbon emissions in relation to the structure of energy consumption and human activities. Based on different energy consumption structures and technological innovation levels, a threshold effect model is constructed. The results show that: (1) There is an inverted U-shaped curve relationship between population aging and carbon emissions in China. (2) Energy consumption structure and technological innovation thresholds can be derived for the impact of population aging on carbon emissions, with thresholds of 3.275 and 8.904 identified, respectively. (3) Population aging can reduce carbon emissions when the energy consumption structure does not exceed the threshold value. (4) There is no significant intervention effect of technological innovation on the relationship between population aging and carbon emissions. Based on the research results, some countermeasures and suggestions to reduce carbon emissions are proposed.

Impact of digital economy development on carbon emission intensity in the Beijing-Tianjin-Hebei region: a mechanism analysis based on industrial structure optimization and green innovation.

Under the "Digital China" strategy and "Carbon Peaking and Carbon Neutrality" goal, it is significant to explore the carbon reduction effect from the digital economy development in a multi-dimensional way. Based on the panel data of 13 cities in the Beijing-Tianjin-Hebei (BTH) region from 2011 to 2019, this study uses mechanism test model, threshold effect model, and spatial Durbin model which empirically test the influence mechanism and spatial spillover effect of digital economy development on regional CEI. The research found that (1) the digital economy development in the BTH region can reduce regional CEI, and it passes the endogenous test; (2) the digital economy indexes of 13 cities in the BTH region have significantly increased with time evolution, but there is obvious spatial unevenness; the CEI of each city except Tianjin decreases significantly with time evolution, and Tianjin shows a trend of decreasing and then increasing; (3) digital economy has a positive spatial correlation, showing the characteristics of "H-H" and "L-L" clustering. Furthermore, the digital economy has a spatial spillover effect on the CEI of neighboring cities; (4) the digital economy development can promote the industrial structure rationalization and upgrade, improves the urban green innovation quantity and quality, then reduces the regional CEI through them; and (5) the impact strength of digital economy on CEI varies at different threshold intervals of the mechanism variable.

Do Environmental Regulation and Foreign Direct Investment Drive Regional Air Pollution in China?

With economic development, air pollution is becoming increasingly serious, which affects the sustainable development of the global economy. In order to explore policy measures to curb air pollution, this paper selects data from 30 regions in China and explores their impact studies on air pollution from the perspectives of environmental regulation and foreign direct investment using a systematic GMM model. Then, the threshold effect model is selected to verify their nonlinear relationship. The conclusions are as follows: (1) Environmental regulation does not pass the significance test. There is no significant “U-shaped” or “inverted U-shaped” relationship between environmental regulation and air pollution. In the eastern region, there is an inverted U-shaped relationship, which is consistent with the environmental Kuznets curve (EKC) hypothesis, and the effect in the central and western regions is higher than in the eastern region of China. (2) The entry of foreign direct investment (FDI) aggravates the environmental pollution problem in China, and the overall status quo is consistent with the pollution haven hypothesis, which shows an inverted U-shaped curve between FDI and air pollution. The eastern region does not have any U-shaped relationships. The other two regions show an inverted U-shaped curve between foreign direct investment and air pollution; these two regions are still in the left half of the curve, and the increase in foreign capital will lead to aggravation of the pollution status quo. (3) The industrial structure will aggravate air pollution in the whole country and the central and western regions; the eastern region shows a suppression effect, but this is not significant. Urbanization exacerbates air pollution in the central and western regions but has an insignificant effect in the eastern region. The level of economic development increases air pollution in all regions. The expansion of the population size brings a large amount of production and living pollution, which aggravates environmental pollution. The research in this paper can provide theoretical references for regional policies to control air pollution.

The Impact of High-Quality Energy Development and Technological Innovation on the Real Economy of the Yangtze River Economic Belt in China: A Spatial Economic and Threshold Effect Analysis

The sustainable economic development of the Yangtze River Economic Belt is a significant part of China’s regional development strategy. The article selects panel data from 11 provinces of the region from 2004 to 2020 and constructs a spatial economic model and a threshold effect model to investigate the impact of energy development and technological innovation on the real economy of this region. The result indicates that technological innovation plays a significantly beneficial role in supporting the development of the local real economy, while its spatial spillover effect to neighboring provinces is not significant. Energy development has a significant negative impact on both the local real economy and that of the neighboring provinces. Such impact is shaped by the threshold effect of the level of technological innovation.

How Fintech Affects Economic Development

Based on the annual provincial panel data from 2011 to 2020, this paper uses fixed-effect panel model and threshold-effect model to study the impact of fintech on economic development. The results show that fintech has a significant positive impact on economic development and heterogeneity, and the contribution of fintech to economic development is relatively high in the eastern region. Further using the threshold effect model, it is found that different levels of fintech have different effects on economic development.

Can China’s Digital Inclusive Finance Alleviate Rural Poverty? An Empirical Analysis from the Perspective of Regional Economic Development and an Income Gap

Digital inclusive finance (DIF) plays an active role in preventing poverty-stricken groups from returning to poverty and reducing poverty. This paper empirically tests the impact of DIF on rural poverty alleviation using panel data from 30 Chinese provinces from 2011 to 2020 as a sample. It employs multiple linear regression, mediation effect models, and threshold effect models. The results show that: (1) DIF and its three sub-indicators (coverage breadth, depth of use, and digitalization degree) have significant poverty reduction effects, and the findings hold even when endogeneity is taken into account; (2) a study of regional heterogeneity found that DIF and its sub-indices, coverage and depth of use in the eastern region, have the greatest effect on the poverty alleviation of rural residents, and the effects in the central and western regions have the least effect; (3) the mediation effect test found that DIF could indirectly promote poverty alleviation in rural areas by promoting regional economic growth and narrowing the urban-rural income gap. The Sobel test shows that the mediating effect of regional economic growth is greater than the mediating effect of the urban-rural income gap; (4) it is found through the threshold effect test that regional economic growth has a double threshold effect on rural poverty alleviation, and as the threshold value continues to increase, the poverty reduction effect increases in turn. Therefore, this paper puts forward policy suggestions for the aspects of accelerating the development of DIF in rural areas, implementing regionally differentiated poverty reduction strategies according to local conditions, promoting regional economic growth, and narrowing the urban-rural income gap.

Basic research investment, innovation capability improvement, and economic growth efficiency.

This study explores the relationship between the proportion of basic research investment in R&D expenditure and regional economic growth efficiency and its influence path. A panel of data from 31 China's provincial was analysed by the fixed-effects model over 2009 to 2019. Empirical results highlight that: (1) the increase in the proportion of basic research investment has a significant promoting effect on regional economic growth efficiency, but it presents an "inverted U-shaped" impact path. Meanwhile, the threshold effect model test results reveal that basic research investment plays a more significant role in promotion when the per capita income level exceeds a certain threshold. (2) The test results of the mediating effect model indicate that the improvement of the level of human capital is the intermediate channel through which the investment in basic research affects regional economic growth efficiency, while the mediating effect of the increase of knowledge storage on the process of the investment in basic research affecting regional economic growth efficiency is not supported by data. Potential policy measures are discussed.

Does economic growth target constraint put pressure on green energy efficiency? Evidence from China.

Building a sustainable energy system and achieving sustainable economic growth has always been China's development goal. However, under the promotion incentive and information asymmetry, local governments may choose to sacrifice the ecological environment to maintain expected economic growth goals. This paper analyzes the relationship between economic growth targets and green energy efficiency (GEE) by using panel data models and spatial econometric techniques. Moreover, the mediation effect model and threshold effect model are used to study their influence mechanism and the possible nonlinear relationship. The results indicate that economic growth targets reduce the efficiency of GEE. The impact of environmental regulation on GEE is "U" shaped. Environmental regulation plays a positive moderation role between economic growth targets and GEE. Additionally, higher levels of technological innovation, industrial upgrading, and environmental regulation result in a reduction in the negative effects of economic growth targets on the GEE. However, the improvement in the foreign direct investment can increase the negative influences of economic growth targets on the GEE.

The Effect of Heterogeneous Environmental Regulations on Carbon Emission Efficiency of the Grain Production Industry: Evidence from China’s Inter-Provincial Panel Data

Examining the impact of heterogeneous environmental regulations on the carbon emission efficiency of the grain production industry will help to provide a theoretical basis and decision-making reference for achieving the goal of carbon peaking and sustainable agricultural development. Based on the panel data of 30 provinces in China, the DEA-SBM method was used to measure the grain production industry’s carbon emission efficiency from 2011 to 2019. Separating environmental regulations into formal environmental regulations and informal environmental regulations in two parts, then the two-way fixed effect model, threshold effect model, and intermediary effect model are used to test the influence of heterogeneous environmental regulations on the grain production industry’s carbon emission efficiency. The results show that: (1) the grain production industry’s carbon emission efficiency continues to improve but still has space for improvement. (2) the relationship between formal environmental regulations and the grain production industry’s carbon emission efficiency exhibits a “U-shaped” curve; informal environmental regulations have a significantly positive effect on improving the grain production industry’s carbon emission efficiency. The conclusion is still valid after the robustness test. (3) A threshold mechanism test found that there is a single threshold effect between the formal environmental regulations and the grain production industry’s carbon emission efficiency, but it does not cross the “U” inflection point. (4) there is a “U” shaped non-linear mediating effect in the influence of formal environmental regulations on the grain production industry’s carbon emission efficiency; informal environmental regulations also have an intermediary transmission path of production agglomeration of the grain production industry. This study supplies a new perspective for promoting the grain production industry’s carbon emission efficiency.

Can China’s digital inclusive finance help rural revitalization? A perspective based on rural economic development and income disparity

The development of digital inclusive finance in China can help alleviate the problems of the “three rural areas” and contribute to rural revitalization. The impact of digital inclusive finance on rural revitalization is examined by multiple linear regression, mediated effect model, and threshold effect model in a sample of 30 provinces in China from 2011 to 2020. It is found that (1) the digital inclusive finance index and its sub-indicators - the breadth of digital financial coverage and depth of digital financial use - can promote rural revitalization in China, but the digitalization degree of its sub-indicators does not have a significant linear effect on rural revitalization, but a “U” shaped relationship of first inhibiting and then promoting, with 2017 as the boundary. (2) The regional heterogeneity test reveals that the promotion effect of the digital financial inclusion index and its sub-indicators of digital financial coverage breadth and digital financial usage depth on rural revitalization is more significant in the eastern coastal and central inland provinces, and insignificant in the western remote areas. (3) The mediating effect test finds that digital inclusive finance in China can contribute to rural revitalization by promoting economic growth in rural areas and narrowing the income gap between urban and rural areas. (4) The threshold effect test reveals that there is a single threshold effect of digital inclusive finance and its three sub-indicators on rural revitalization in China. When the digital inclusive finance index and the three sub-dimensions are below the threshold value, they have a facilitating effect on rural revitalization, and after crossing the threshold value, their facilitating effect on rural revitalization becomes more significant. Based on the empirical analysis results, this paper puts forward suggestions for improving the development mechanism of digital inclusive finance, formulating differentiated financial support policies and strengthening financial supervision according to regional differences, and establishing a long-term mechanism for rural revitalization, to promote China’s rural revitalization.

Research on the impacts of dual environmental regulation on regional carbon emissions under the goal of carbon neutrality-the intermediary role of green technology innovation

As an important means to promote regional low-carbon development, environmental regulation has great theoretical and practical significance for achieving the goal of carbon-neutral development in China. Based on the panel data of 30 provinces and cities in China from 2005 to 2019, this paper first uses the intermediary effect model to analyze the impact of the implementation of environmental regulation policies on regional carbon emissions, discusses the relationship between environmental regulation, green technology innovation and carbon emissions, and further uses the threshold effect model to discuss the nonlinear relationship between environmental regulation and regional carbon emissions. The results show that: the improvement of formal and informal environmental regulation can play a role in “forced emission reduction”; Green technology innovation plays a complete intermediary role in the impact of environmental regulation on regional carbon emissions; At the same time, the impact of formal and informal environmental regulation on regional carbon emissions has a threshold effect. Among them, formal environmental regulation has a double threshold effect, the threshold values are 0.429 and 0.502 respectively, while informal environmental regulation has a single threshold effect, the threshold value is 1.803. The results of heterogeneity analysis show that there are obvious differences in the implementation effects of environmental regulation policies under different economic development levels and industrialization development stages. Therefore, we should pay attention to the mutual promotion effect of different types of environmental regulation, strengthen the collaborative emission reduction of environmental regulation and green technology innovation, and improve the level of regional green technology innovation, so as to better promote the realization of regional carbon neutrality goals.

Research on the accelerating effect of green finance on the transformation of energy consumption in China

In the face of global climate change, accelerating the transformation of energy consumption is key. This paper constructs intermediary effect and threshold effect models to empirically test the impact mechanism of urbanization on energy consumption transformation. The results show that an increase in the urbanization rate can reduce energy consumption. The development of green finance helps improve the traditional energy consumption structure dominated by fossil energy consumption through the intermediary effect. When the urbanization rate enters the high threshold range, the negative impact of green financial development on fossil energy is significantly enhanced. The research conclusion shows that with continuous improvement in the urbanization rate, the development of green finance can accelerate the transformation of traditional energy consumption, which is conducive to the realization of the goals of “reaching carbon peak by 2030 and carbon neutrality by 2060″ proposed by the Chinese government.

The impact of clean energy development on economic growth in China: from the perspectives of environmental regulation.

Given the finite nature of fossil energy and rising environmental pressures, countries are increasing focus on clean energy. By employing provincial panel data from 2003 to 2019 in China, this study sheds light on the effect of clean energy development on economic growth and the role of environmental regulation in the relationship. The study utilized moderating and threshold effect models for empirical estimation. Results show that clean energy development has a positive impact on economic growth in general. In terms of region heterogeneity, the contribution of clean energy development to economic growth is more pronounced in regions with higher levels of economic development. Furthermore, we provide evidence that market-based environmental regulation has a single threshold, which has a positive regulating effect on the relationship between clean energy development and economic growth, while administrative environmental regulation has a double threshold, which has a negative regulating effect on the relationship between the two. The findings of our study provide useful policy directions for maintaining a balance between economic growth and environmental prosperity.