Counties In China Research Articles

Digital Finance and County Ecological Performance—New Evidence from China Counties

As a new product that combines finance and digital technology, digital finance is of great significance to the governance of the ecological environment. Based on the panel data of 2128 counties in China from 2014 to 2020, the fixed effect model and a panel threshold model are established, and the direct impact, heterogeneity, and transmission paths of digital finance development on ecological environment quality are empirically analyzed. The results demonstrate that the progress of digital finance has a significant negative effect on ecological environmental performance, and robustness tests support this conclusion. Additionally, industrial agglomeration and structural transformation are crucial mechanisms through which digital finance hinders ecological environmental performance. Moreover, the adverse influence of digital finance development on the ecological environment is particularly pronounced in densely populated areas, county-level cities, and non-poverty-stricken counties. Fourthly, based on the development level of digital finance itself, digital finance has a double threshold effect on the performance of county ecological environment. When digital finance is at a low level and a high level, its negative impact on eco-environmental performance is the greatest. Between the low level and the high level of digital finance, digital finance has the greatest negative impact on the performance of the ecological environment. Finally, suggestions are put forward to promote the green development of digital finance, foster balanced regional development, and expedite industrial transformation in underdeveloped regions.

A study on the impact mechanism of internet embedding on rural E-commerce entrepreneurship

In the context of the rapid development of global Internet and e-commerce, rural e-commerce entrepreneurship has become an important driving force for rural e-commerce development. Using micro-survey data from five national e-commerce demonstration counties in China, this paper empirically examines the impact of Internet embedding on rural e-commerce entrepreneurship and the mediation effect of social capital. The results show that farmers are more likely to choose an independent entrepreneurship channel than a cooperative entrepreneurship channel when the Internet is embedded in rural areas. Then, social capital plays a suppressing effect between Internet embedding and farmers’ e-commerce entrepreneurial choices. In addition, under the condition of Internet embedding, farmers with more social capital are more likely to choose cooperative e-commerce entrepreneurship channels.

Do county financial marketization reforms promote food total factor productivity growth?: a mechanistic analysis of the factors quality of land, labor, and capital

Improving food total factor productivity is a necessary way to break the double constraint of resources and environment, and promote the transformation of the food production system and the realization of the sustainable development goal of zero hunger. Based on the panel data of 729 counties in China from 2010 to 2019, this paper analyzes the effect of county financial marketization reform on food total factor productivity by using a two-way fixed effects model, focusing on the mechanism of the quality of factors such as land, labor and capital. The results show that county financial marketization reform promoted food total factor productivity growth by promoting technical progress, while technical efficiency did not play a significant role. Heterogeneity analysis shows that the effect of county financial marketization reform on grain total factor productivity is not significantly different in eastern and central China. There is a significant difference in the western region, where county financial market reform hindered the growth of grain total factor productivity. In terms of different functional areas of grain production, the facilitating effect is only played in the main grain production area, and the inhibiting effect is played in the main grain marketing area. Mechanistic analysis shows that the county financial marketing reform promoted the growth of food total factor productivity by improving the quality of labor and land, while the quality of agricultural capital has a masking effect. On this basis, it is necessary for the government to implement differentiated financial market-oriented reform strategies, and to guide and encourage county financial institutions to provide financial services to improve the quality of agricultural labor and farmland through tax incentives and loan interest subsidies.

Exploring teacher identity tensions and coping strategies in a comparative case study of primary school teachers’ narratives

ABSTRACT Teacher professional identities are considered crucial to link teachers’ personal experiences with the social and professional changes needed for improved learning in schools. In this research study, we aim to investigate teachers’ identity tensions and coping strategies in four different school contexts in Nanqi (a pseudonym) County in China. A constructivist perspective guided the choice of a qualitative approach to inquiry in this study. Ambiguities, tensions, and culturally specific references coexisted in teacher professional identities and individual teachers’ ethical and emotional pursuit of integrity and purpose at work. Employing the research strategy of narrative inquiry, this study suggested forms of tensions when teachers attempt to align their multiple and often conflicting sub identities in changing and diversifying school contexts, namely, emotional tensions, social tensions, developmental tensions and ethical tensions. Our research findings detail the circumstances that trigger different types of identity tension and how teachers experience and respond to them in different ways, which link with different working contexts and teachers’ focus of professional development. The results also reveal the need for greater recognition of ‘negative’ aspects of teachers’ professional identity development and the value of longitudinal research designs to further facilitate the exploration.

Modelling Uncertainties and Sensitivity Analysis of Landslide Susceptibility Prediction under Different Environmental Factor Connection Methods and Machine Learning Models

The utilization of different connection methods between landslides and environmental factors introduces uncertainty in landslide susceptibility prediction (LSP). Investigating and identifying the characteristics of this uncertainty and determining more suitable connection methods are of significant importance for LSP. This study uses original 12 environmental factors data as well as calculated data from five connection methods, namely, probability statistics (PS), frequency ratio (FR), information volume (IV), index of entropy (IOE), and weight of evidence (WOE), as model input variables. Then, four machine learnings logistic regression (LR), Bayesian networks (BN), support vector machines (SVM) and C5.0 Decision Trees (C5.0 DT) are combined with the calculated data and the original data to create 24 unique combinations of connection methods and models. Under these 24 combinations, the uncertainty analysis of LSP modeling is conducted, using Huichang County of China as an example. The analysis entails accuracy assessment, statistical analysis of landslide susceptibility indexes (LSIs), distribution patterns of LSIs and sensitivity analysis of the two uncertainty issues. The results show that: 1) LSP accuracies of the FR-, IV- and IOE-based models are comparable, but are lower than those of the WOE-based models, with those of the PS-based models being the worst. WOE has better nonlinear connection performance than the other methods. 2) LSP accuracies of individual models are slightly lower than those of coupled models, but their modeling efficiencies are higher than those of coupled models. 3) The machine learning is more sensitive than the connection method for LSP. In short, WOE-C5.0 DT has the lowest LSP uncertainty while a single machine learning can produce satisfied LSP results with high modelling efficiency.

Agricultural certification, market access and rural economic growth: Evidence from poverty-stricken counties in China

Long-term economic growth in impoverished regions has been a critical research and policy concern. Smallholder farmers require access to modern marketing and commercialization channels to transition from subsistence farming and break the shackles of poverty. Agricultural certification provides an avenue to enhance the value of farm produce and eliminate market impediments. This paper examines the impact of an agricultural certification policy implemented in China on the economic growth of poor counties. A two-way fixed-effects model was utilized along with an instrumental variable approach. We find that the agricultural certification policy contributes to economic growth in these areas and that the effects are robust to various biases and endogeneity concerns. The policy fosters rural economic growth by increasing product premiums and employment opportunities. The effects are more pronounced in non-minority counties or those with greater market access. Additionally, the policy yields favorable effects on the surrounding air quality.

Exploration on the Innovation Model of County Urbanization Development with the Resource Constraints in China

The 14th Five-Year Plan for China proposes to promote the urbanization process from a county perspective, presenting an unprecedented opportunity to develop county urbanization. However, in the context of relatively limited resources, insufficient funds, and comparatively lower land values in Chinese counties, how to promote county urbanization remains the primary challenge, which has not been studied yet. This study first analyzes the necessity of promoting county urbanization from four dimensions: national development strategy, industrial policy development, local government status, and enterprise development demands using literature research and survey interviews. Based on field research conducted in 32 counties in China, the strengths, weaknesses, opportunities, and threats (SWOT) analysis is carried out on the county urbanization process in this study. By analyzing the developmental status and challenges of major urban areas, expansion areas of counties, and their surrounding countryside, this paper proposes a “three-level gradient integration” concept for the spatial integration of county urbanization. Furthermore, the mechanism of multi-agent linkage to promote county urbanization was explored based on the theory of urban governance and the characteristics of county urbanization. Subsequently, relying on the analysis of policies, such as land acquisition and integrated land improvement, and adopting modes, such as “Investor + Engineering Procurement Construction + Operation” (investor + EPC + O) and renovate–operate–transfer (ROT), we propose a pathway for promoting county urbanization through the linkage of government, enterprises, and residents. This study provides insight into promoting the county urbanization process. Additionally, each country faces the common issue of how to use limited resources to promote regional development, and this article can provide valuable insights and inspiration for addressing this shared issue by the principle of adapting to local conditions and adhering to the concept of efficient market and proactive government.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction (LSP) models, the influences of random errors in landslide conditioning factors on LSP are not considered, instead the original conditioning factors are directly taken as the model inputs, which brings uncertainties to LSP results. This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP uncertainties, and further explore a method which can effectively reduce the random errors in conditioning factors. The original conditioning factors are firstly used to construct original factors-based LSP models, and then different random errors of 5%, 10%, 15% and 20% are added to these original factors for constructing relevant errors-based LSP models. Secondly, low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method. Thirdly, the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case. Three typical machine learning models, i.e. multilayer perceptron (MLP), support vector machine (SVM) and random forest (RF), are selected as LSP models. Finally, the LSP uncertainties are discussed and results show that: (1) The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties. (2) With the proportions of random errors increasing from 5% to 20%, the LSP uncertainty increases continuously. (3) The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors. (4) The influence degrees of two uncertainty issues, machine learning models and different proportions of random errors, on the LSP modeling are large and basically the same. (5) The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide susceptibility. In conclusion, greater proportion of random errors in conditioning factors results in higher LSP uncertainty, and low-pass filter can effectively reduce these random errors.

An evaluation of the economic benefits of rooftop distributed photovoltaic projects in the whole county in China

To promote the realization of the “dual carbon target”, the implementation of rooftop distributed photovoltaic (RDPV) projects in the whole county will usher in large-scale development in China. However, comprehensive investigations into the economic benefits of RDPV projects in the whole county are still rare. This paper thus aims to evaluate the economic benefits of RDPV projects when considering multiple factors. The net present value (NPV), internal rate of return (IRR) and payback period (PBP) were used to analyze the financial feasibility of RDPV projects. The particle swarm optimization (PSO) algorithm was adopted to optimize the economic benefits of RDPV projects by calculating the different installation ratios of different building types, including industrial and commercial buildings, government buildings, public buildings, and residential buildings. A case study verified the feasibility of the optimization model of the economic benefits of RDPV projects in the whole county in China. The results revealed that the self-use ratio of power generation greatly impacted the economic benefits of RDPV projects and a single RDPV project became economically feasible when the self-use ratio of power generation was greater than 87.753%. When considering the limitations of the self-use ratio of power generation, installed capacity, and grid connection mode of different building types, compared to the single RDPV project, the economic benefits of RDPV projects on a county scale were not financially feasible based on the optimization model, which had an NPV of about −10.35 million yuan. Industrial and commercial buildings had the highest proportion of RDPV systems installed among the four building types, while residential buildings had the lowest proportion. The current results demonstrate the economic benefits of RDPV projects in the whole county, which will promote the development of RDPV projects and reduce carbon emissions in China. Therefore, this study is expected to provide investors of RDPV with recommendations for both decision-making and making scientific plans for the government.

Impact of capitation prepayment on the medical expenses and health service utilization of patients with coronary heart disease: a community policy intervention program in a county in China

BackgroundMedical costs have been rising rapidly in recent years, and China is controlling medical costs from the perspective of health insurance payments.ObjectivesTo explore the impact of the capitation prepayment method on medical expenses and health service utilization of coronary heart disease (CHD) patients, which provides a scientific basis for further improvement of the payment approach.MethodsThe diagnosis records of visits for CHD in the database from 2014 to 2016 (April to December each year) were selected, and two townships were randomly selected as the pilot and control groups. Propensity score matching (PSM) and difference-in-difference (DID) model were used to assess changes in outpatient and inpatient expenses and health service utilization among CHD patients after the implementation of the capitation prepayment policy.ResultsThere were eventually 3,900 outpatients and 664 inpatients enrolled in this study after PSM. The DID model showed that in the first year of implementing the reform, total outpatient expenses decreased by CNY 13.953, drug expenses decreased by CNY 11.289, as well as Medicare payments decreased by CNY 8.707 in the pilot group compared to the control group. In the second year of implementing the reform, compared with the control group, the pilot group had a reduction of CNY 3.123 in other expenses, and a reduction of CNY 6.841 in Medicare payments. There was no significant change in inpatient expenses in the pilot group compared to the control group, but there was an increase of 0.829 visits to rural medical institutions, and an increase of 0.750 visits within the county for inpatients.ConclusionsThe capitation prepayment method has been effective in controlling the outpatient expenses of CHD patients, as well as improving the medical service capacity of medical institutions within the Medical Community, and increasing the rate of inside county visits for inpatients.

Quantitative Assessment of Spatial–Temporal Characteristics of Agricultural Development Level in China: A County-Level Analysis

Main Functional Area Planning (MFAP) is a significant initiative in China, aimed at promoting coordinated socio-economic progress while ensuring resource capacity and environmental sustainability. However, there is a lack of quantitative assessments of China’s county-level agricultural development level (ADL) following the implementation of the MFAP. In this study, a coupled “agricultural product-agricultural space-agricultural population” evaluation index system which was based on plan requirements, remote sensing imagery, statistical data, and industry-specific information was proposed for assessing the development level of agricultural after implementing the MFAP, and we utilized the system to evaluate the ADL of 2850 counties across China from 2009 to 2015 at the county level. The results indicate that MFAP has played a positive role in driving agricultural development in China. From 2009 to 2015, the ADL of counties in China showed an upward trend, and the agricultural development within the “Seven regions & Twenty-three belts” reached a high level, with the proportion of the top three districts and counties in the agricultural development zone increasing from 86.78% to 88.72%. The spatial distribution of ADL ratings shows a central > east > northeast > west pattern, with the western regions exhibiting the fastest growth rate. Moreover, targeted policies were provided for pathway optimization and upgrading the level of agricultural development of regions with different levels of development within the seven main agricultural production areas and others.

Has the largest-scale poverty alleviation relocation in human history promoted urbanization? An empirical analysis from China

ABSTRACT Poverty alleviation resettlement (PAR) programme is the largest-scale poverty alleviation relocation in human history, but its impact on urbanization has received little academic attention. To fill this important gap, this study first proposed a theoretical framework of the “pressure-state-response-effect” (PSRE) of PAR promoting urbanization. Then, we regarded PAR as a quasi-natural experiment and used the PSM-DID model to assess the impact of PAR on urbanization based on the panel data of 2,081 counties in China from 2013 to 2020. Results showed that PAR had a significant positive impact on the urbanization rate of these counties, with a growth rate of 0.64%. Further mechanism analysis showed that industrial upgrading could expand the impact of PAR implementation on promoting urbanization. Additionally, PAR in the eastern and western, hilly and mountainous counties could improve the urbanization level more than that in the central and plain counties. The effectiveness of PAR varied across regions, requiring consideration of local socioeconomic complexity rather than a one-size-fits-all approach. Our findings would have important reference value for other developing countries to formulate their anti-poverty strategies to achieve the 2030 UN Sustainable Development Goals.

Return migration and in-situ urbanization of 79 migrant sending counties in China: Characteristic and driving factors

As the country with the largest number of migrants, China has shown a trend of return migration in recent years. However, the characteristics and mechanism of emerging in-situ urbanization of migrants have not been fully revealed. We construct an analytical framework considering China's situation based on the push-pull theory in the urban-rural dichotomy. Using cell phone data from 79 migrant-sending counties, we calculate the in-situ urbanization rate and apply a simple regression model to analyze its driving factors. The findings show that rural income and fiscal investments are the main pull factors, while economic slowdown in cities acts as push factors.In-situ urbanization is the dual effect of improving living standards and reducing urban employment opportunities. To support China's efforts in New-type Urbanization, improving living standards and expanding off-farm employment opportunities of migrant-sending counties are suggested.

Effects of modern agricultural demonstration zones on cropland utilization efficiency: An empirical study based on county pilot

The establishment of modern agricultural demonstration zones, as an important initiative to promote the modernization of agriculture, has attracted much attention as to whether its promotion and demonstration can bring about a benign enhancement of the cropland utilization efficiency. This study uses the difference-in-difference model, and with the help of the data of 1872 counties in China from 2006 to 2020. The study shows that the agricultural demonstration zones significantly improve the utilization efficiency of cropland, while there is strong regional heterogeneity in this effect, with a greater degree of promotion in some regions that are lagging in agricultural development. Further mechanism analysis reveals that superior agricultural resource endowment and strong government financial support can positively moderate this effect. However, over-industrialization will inhibit this positive effect.

The impact of digital financial inclusion and urbanization on agricultural mechanization: Evidence from counties of China.

This paper expounds the theoretical logic among digital inclusive finance, urbanization, and agricultural mechanization level, puts forward the research hypothesis, and then selects the county unbalanced panel data of 1309 counties in China from 2014 to 2020 based on the two-way fixed model with standard error clustering to county level and mediating effect model for empirical data regression analysis. Through baseline regression analysis, mediation effect analysis, and heterogeneity analysis, the findings of this paper are as follows. First, digital financial inclusion has a significant positive effect on the growth of agricultural mechanization. Second, digital inclusive finance at the county level can also indirectly affect the growth of agricultural mechanization through urbanization. That is, agricultural mechanization has an intermediary effect between the financial agglomeration at the county level and the growth of farmers' income. Third, the impact of county-level digital financial inclusion on the growth of agricultural mechanization level is significantly heterogeneous, and the promoting effect is significant in areas with balanced grain production, national-level poor county or contiguous areas of dire poverty, and areas with a good foundation for digital financial inclusion. By analyzing digital inclusive finance, urbanization, and agricultural mechanization, this paper proposes targeted policy recommendations. First, the government can promote agricultural mechanization by developing digital financial inclusion. Second, the government should guide and accelerate the process of digital financial inclusion, promoting urbanization thereby amplifying the positive impact of digital financial inclusion on agricultural mechanization. Third, given the heterogeneity of the impact of digital financial inclusion on agricultural mechanization, local development should focus on developing different dimensions of digital financial inclusion according to specific conditions.

Fertilization can accelerate the pace of soil microbial community response to rest-grazing duration in the three-river source region of China.

Overgrazing leads to grassland degradation and productivity decline. Rest-grazing during the regreen-up period can quickly restore grassland and fertilization is a common restoration strategy. However, the effects of rest-grazing time and fertilization on soil microorganisms are unclear in the alpine grasslands. Therefore, the experiment of rest-grazing time and fertilization was carried out to explore the response of soil microorganisms to rest-grazing time and fertilization measures. A field control experiment with rest-grazing time and fertilization as factors have been conducted from the time when grass returned to green till the livestock moved to the summer pasture in Dawu Town of Maqin County of China. The primary treatment we established was the five rest-grazing time, including rest-grazing time of 20 days, 30 days, 40 days, 50 days, and traditional grazing was used as a check group. At the same time, the secondary treatment was nitrogen addition of 300 kg·hm-2 in each primary treatment. The results showed that the total phospholipid fatty acid (total PLFA), actinomyces (Act), and arbuscular mycorrhizal fungi (AMF) showed an ever-increasing biomass with the increase of rest-grazing time and the highest was at 50 days of rest-grazing, and they were all significantly higher than CK. In addition, soil microbial biomass carbon-nitrogen ratio (MBC/MBN) had great influence on the change of microbial community. Applying nitrogen fertilizer can increase the maximum value of biomass of all PLFA groups and the biomass of all PLFA groups changed in an "inverted V" shape with the increase of rest-grazing time. Besides, instead of MBC/MBN, NO3 --N was positively correlated with the biomass of all PLFA groups, which actively regulated the trend of microbial functions. The longer rest-grazing time is more conducive to the biomass of all PLFA groups. However, applying nitrogen fertilizer could break this pattern, namely, the 30 days rest-grazing would be beneficial to the biomass of all PLFA groups. These findings provide key information that rest-grazing during the regreen-up period is benefiscial to the all PLFA groups and fertilization could change the response of microorganisms to rest-grazing, which provide reference measures for the restoration of degraded alpine meadows.

Where you live matters: The impact of offline retail density on mobile shopping app usage

Consumers residing in different areas have varying levels of access to local retail stores. In contrast, with the prevalence of mobile internet, consumers have gained widespread access to mobile shopping. This research examines the impact of local offline retail density on consumers’ mobile shopping app usage and heterogeneity across consumer segments and different types of shopping apps. We use a unique dataset of individual-level mobile app usage with real-time location information across 1622 counties in China and employ the control function approach to address the endogenous retail density. Overall, the findings show that local offline retail density has a negative effect on mobile shopping app usage frequency and duration, indicating that consumers in areas with lower offline retail density engage more in mobile shopping app usage. This negative effect is weaker for consumers with higher mobility. Also, we find that this negative effect is weaker for shopping apps selling more technically complex products such as electronics than for those selling less technically complex products such as clothing and cosmetics. These results offer managerial implications for online retailers to launch targeting strategies to enhance consumer engagement with their shopping apps.

EP17.04-05 Research and Analysis on the Situation of Prevention and Treatment Capability of Cancer in County of China

EP17.04-05 Research and Analysis on the Situation of Prevention and Treatment Capability of Cancer in County of China

Does green location-oriented policy enhance ecological resources and reduce air pollution? Empirical analysis from counties in China

Green location-oriented policy plays a vital role in improving the ecological security. Using the multi-phase difference-in-difference (DID) method, this study evaluates the impact of national key ecological functional areas (NKEFA) on ecological resources and environmental pollution. There are several important findings. Firstly, NKEFA effectively enhances ecological resources and reduces air pollution, the policy effect only manifests after two years of implementation. Secondly, NKEFA has indirectly improved air quality by promoting technological innovation, advanced industrial structure, and regional ecological resource quality. Moreover, the relationship between NKEFA and ecological resources is negatively regulated by industrialization and economic agglomeration, while the relationship between NKEFA and air pollution is positively regulated by them. Thirdly, NKEFA has the strongest impact on enhancing ecological resources in the eastern region, and it is more effective in reducing air pollution in the central and eastern regions compared to the western regions. Furthermore, the NKEFA demonstrates the greatest effectiveness in promoting ecological resources and reducing air pollution in water and soil conservation areas. However, there is a spatial spillover effect, which suggests that this policy has some negative impacts on the surrounding counties’ ecological environment.

Impacts of subsidy for export of pig to domestic market on the spatial distribution of pig production and related nitrogen losses in China

The uneven distribution of pig production may create pollution hotspots and severe environmental costs at the local level; however, there is little information available about the socioeconomic driving forces behind the spatial distribution of pig production and its potential environmental costs. Here, we collected time series data (1990, 2012 and 2017) of pig production and multiple socioeconomic indicators from 2333 counties in China to remedy this knowledge gap. Our results indicate that, the poverty level, pork self-sufficiency rate, feed availability per head and environmental pollution risk were all played negligible roles in determining the spatial distribution of pig production at the county level in China between 1990 and 2017. The spatial distribution of pig production was more impacted by the so-called subsidy policy for export of pig to domestic market (hereinafter called pig subsidy policy), which aimed to subsidize counties exporting large amounts of pigs to other counties. In 2017, approximately 181 million head of pig was exported to domestic market from subsidized counties, and these counties received a subsidy amount of US$ 450 million. However, the total environmental cost, considering the human health, ecosystem and climate change damages of nitrogen losses of the pigs exported to domestic market, was US$ 4.5 billion, 10 times of the subsidy. If all the subsidies were fully designated to reduce ammonia emissions from the industrial pig production, the total cost could be reduced by US$ 1.6 billion; however, this was not enough to cover all the damage. Overall, the spatial distribution of pig production was strongly impacted by the pig subsidy policy in China. Applying $400 million of pig subsidy to ammonia emissions reduction could reduce external environmental costs by 31 % and deliver $1.3 billion in socioeconomic benefits. The total subsidy needs to be increased and used smartly in the future to reduce nitrogen losses from the production chain.