Provincial-level Data Research Articles

Does government transparency promote firm innovation? Evidence from China

ABSTRACT This study investigates the relationship between government transparency and firm innovation, exploring the mechanisms through which government transparency influences firm innovation using Chinese provincial-level and firm-level data from 2013 to 2020. The findings reveal a significant positive association between government transparency and both firm innovation input and output. Mechanism analysis suggests that government transparency enhances firm innovation by fostering improvements in the regional institutional environment. Furthermore, the study identifies heterogeneity in the effects, indicating that state-owned enterprises (SOEs) and high-tech firms derive greater benefits from government transparency. This research contributes to the existing literature by addressing the role of government transparency in promoting firm innovation and offers valuable insights for practical applications.

Geographical variations and predictors of coronary artery disease mortality in Turkiye: an environmental and behavioral analysis

ObjectiveThis study aims to analyze the geographical variations and identify key environmental and behavioral predictors of coronary artery disease (CAD) mortality in Turkiye.MethodsA 10-year longitudinal province-level data was used to identify change trajectories of CAD mortality. Environmental determinants (such as air quality and climatic conditions) and behavioral factors of alcohol consumption and smoking were examined for their association with CAD mortality change trajectories using Ordinal Logistic Regression models.ResultsThe study revealed significantly different trajectoriesof CAD mortality across Turkiye. Environmental factors, particularly air quality (Particulate Matter-10 variation) and climatic conditions (humidity and temperature variations), were heavily associated with the level of CAD mortality. Behavioral factors, notably alcohol consumption and smoking, also exhibited a significantly positive association. Humidity, sunlight, and temperature remained as key predictors of CAD after controlling for smoking and alcohol consumption.ConclusionThe study underscores the importance of addressing environmental and lifestyle factors in CAD management and prevention strategies. The findings suggest the necessity for region-specific interventions and public health policies tailored to the unique characteristics of each province in Turkiye. This research contributes to a deeper understanding of the multifactorial nature of CAD mortality, providing valuable insights for future research to investigate causal associations, healthcare planning, and policy-making.Trial registrationOur study has been registered in ClinicalTrials.GOV system with a procotol ID of CAD001.

Does Domestic Market Integration Promote an Increase in the Export Value of Manufacturing?

Based on provincial-level data from China from 2008 to 2022, this study examines the impact of market integration on manufacturing exports. Market integration significantly enhances the export value of manufacturing. Mediation effect analysis indicates that market integration fosters export growth by promoting corporate innovation and economies of scale. Heterogeneity analysis confirms the differences between industries. Heavy industries are more affected by international competition and technological advancements. Light industries benefit more from market integration.

Association of environmental and behavioural factors with cardiovascular disease mortality.

Recognizing the rising concern of environmental impacts on health, the study aims to explore how specific environmental factors such as air pollution, humidity, and temperature variations contribute to the prevalence of cardiovascular disease (CVD) mortality, emphasizing the role of air quality, climate variables, and lifestyle factors in the disease mortality specifically. Analysis of province-level data on CVD mortality in Turkey from 2010 to 2019, assessing the correlations with environmental and lifestyle factors like particulate matter, sulfur dioxide, meteorological variables, and smoking and alcohol consumption. The study employs the SAS TRAJ procedure and Ordinal Logistic Regression for statistical analysis. The multiplicity correction was done through Benjamini-Hoechberg false discovery rate (FDR) approach. As expected, both smoking and alcohol consumption were found to be significantly associated with CVD mortality (odds ratio (OR): 1.10, 95% CI: 1.08, 1.11, P-value<0.0001). While median Air Pressure and Humidity were among the most significant markers with OR of 1.10 indicating an increasing CVD mortality, their variability metrics such as coefficient of variation (CV) showed significant protective effects with OR of 0.37 and 0.89, respectively. Temperature and its variability seemed to be protective overall. Our research highlights the significant influence of environmental factors on cardiovascular health, especially air pressure and humidity, beyond the known factors such as smoking and alcohol consumption. These findings suggest the need for comprehensive public health strategies that address both environmental and lifestyle risk factors to effectively reduce the burden of cardiovascular diseases.

The Impact of Farm Structure on Agricultural Growth in China

Farm structure has changed significantly since the land transfer policy was introduced in China. The quantity of and land area utilized by scale farmers and new agricultural entities are increasing, while the numbers of smallholders are decreasing. To analyze the impact of farm structure on agricultural growth in China, this study used provincial-level panel data from 2010 to 2021 and a fixed-effects model for empirical testing. The results show that (1) the structural change among farmers has a positive effect on agricultural growth, accounting for 16% of the contribution; (2) compared with scale farmers, new agricultural entities (NAEs) play a stronger role in improving agricultural growth, which is approximately five times higher than that of the former; and (3) unlike scale farmers, who only promote agricultural growth in central and major grain-producing areas, new agricultural entities have a positive effect on the entire area. Therefore, this study emphasizes the role of human capital in agricultural growth, especially in terms of promoting new agricultural entities, supporting land transfer, and optimizing farm structure.

New energy technology innovation and energy poverty alleviation in China

Energy poverty has received attention, but in-depth research on the relationship between new energy technology innovation and energy poverty is lacking. Using data from 30 Chinese provinces spanning 2006 to 2020, we examine the impact of new energy technology innovation on energy poverty in China. We collect provincial-level patent data and energy poverty evaluation indicators, categorizing them into four subsystems: energy use level, energy capacity, energy use structure, and energy investment management. Findings indicates: (1) New energy technology innovation significantly alleviates energy poverty in China. This is primarily attributed to improvements in energy supply and residents' income. (2) The effectiveness of new energy technology innovations in alleviating energy poverty is enhanced by provincial transportation development and technology market activity but diminished by urbanization. (3) New energy technology innovations lead to notable increases in energy use level and energy capacity, a decrease in energy use structure, and no significant impact on energy investment management. (4) Innovations from enterprises, university and research institutes significantly contribute to alleviating China's energy poverty. However, innovations from industry-university-research collaborations and other innovators do not significantly affect China's energy poverty. Our findings provide valuable insights for theoretical research and energy poverty policy design.

Evaluating impacts of ICT development on wages of workers

At the provincial level, there is a research gap in discussing the causality and internal mechanism between ICT development and wages of workers. The study utilizes the province-level balanced panel data over the period 2006–2021 in China, clarifies the impact and internal mechanism of ICT development on wages of workers, and uses the DID method to identify the causality between the two. This study found that there is a positive correlation between ICT development and workers’ wages, and skill level is a mediate transmission channel. Moreover, ICT development has a positive impact on workers’ wages in the central and western regions. Besides, compared to low-wage workers, high-wage workers gain more information dividends. The findings of this study have reference significance for policymakers. First, for the central and western provinces in China, it is necessary to actively develop the ICT industry, cultivate high-tech enterprises, and improve local ICT development levels. Second, we should improve the skill level of workers and enhance their competitive advantage in employment. Third, each province should continue to expand the enrollment scale of higher education institutions, and improve the quality of labor force.

The Buffering Effect of Higher Education Expansion on the Okun’s Law in China

This paper studies the short-run relationship between the labor market and economic fluctuations using China’s province-level data and further investigates how higher education expansion policy influences this relationship. Following Okun’s law framework, we show that besides total employment, labor force participation also responds to economic fluctuations, resulting in a low sensitivity in the unemployment rate. Based on the interacted variable analysis, we also find that economic growth tends to have larger impacts on labor market indicators during economic downturns than upturns. Lastly, we provide novel evidence that higher education expansion buffers the relationship between the labor market and aggregate demand conditions during economic downturns. This paper sheds some light on achieving more inclusive economic growth in emerging economies through education policy.

Assessing the Effectiveness of Air Pollution Control Policy Mixes: A Case from China

ABSTRACT In recent years, there have been extensive theoretical discourse on policy mixes. Nevertheless, empirical research on the factors contributing to their effectiveness remains limited. This study examines the relationship between two features in policy mixes design, namely intensity and balance, as well as their impacts on policy effectiveness. Using provincial-level data from China (2013–2018), this paper explores how these features enhance policy outcomes. Our findings indicate that, the intensity of command-and-control policy instruments has a significant impact on improving policy effectiveness. Besides, balanced policy mixes are more effective when there is less scrutiny of the environmental performance assessment.

Digital finance and capital mobility: Evidence from cross-regional investment of listed companies in China

This study examines the role of digital finance in dismantling regional barriers to capital flow and in fostering the creation of a unified market. Using the provincial-level digital finance index and data on subsidiaries by listed companies, we demonstrate how digital finance index effectively enhances cross-regional investment. Our findings are robustly supported by extensive tests. We propose two potential mechanisms through which digital finance may influence the level of cross-regional investment by listed companies: first, by reducing the degree of segmentation in capital markets between regions and second, by lowering firms' capital costs and financial constraint. Our results indicate that the impact of digital finance on cross-regional investment is particularly pronounced in environments with higher competition, and among companies without political connections. Additionally, our research indicates that in regions with higher financial regulation, digital finance can better facilitate capital flow. This study provides new research perspectives and evidence on the influence of digital finance on the development of the real economy and the promotion of capital mobility.

Digital Economy, Green Dual Innovation and Carbon Emissions

The digital economy serves as a pivotal catalyst for sustainable and eco-friendly development. This study employs a suite of advanced econometric models, including the fixed effects, mediation, threshold and moderation model, to elucidate the intricate dynamics by which the digital economy influences carbon emissions through the lens of green innovation. Building on the existing research on digital economy, green technology innovation and carbon emissions, this paper takes a dual-innovation perspective and divides green technology innovation into disruptive green technology innovation and incremental green technology innovation. And from the government and the public level, it explores how social concerns affect the effect of digital economy on carbon emissions. The analysis is grounded in a comprehensive dataset encompassing a decade of provincial-level data from 2011 to 2021 across China’s 30 provinces. The benchmark regression outcomes indicate the digital economy’s ability to substantially cut down carbon emissions; the threshold effect and mediating effect models demonstrate that a single-threshold effect exists and that disruptive and progressive green technological innovations mediate such ability. Additional research reveals that the digital economy’s impact on carbon emissions could be positively moderated by public and governmental attention. Eastern and western regions in China, as well as those with high levels of foreign investment and low levels of technological transaction activity, are more affected by the digital economy in terms of carbon emission reduction. Our conclusions offer practical recommendations for digital economy’s coordinated advancement and carbon emissions mitigation, and guide local governments to achieve sustainable development goals (SDGs).

Polluting industries: Does green industrial policy encourage green innovation? Chinese perspective evidence

This study investigates the efficacy of green industrial policies in stimulating green innovation within China's polluting industries, over the period 2011–2022. Focusing on 30 provinces, we assess the dynamic relationship between green industrial policy implementation and innovation in environmentally detrimental sectors. Employing Difference-in-Differences (DID) and Propensity Score Matching DID (PSM-DID) models, we analyze comprehensive provincial-level data to quantify the impact of policy measures on green technological advancements. The results reveal a significant positive correlation between green industrial policies and the rate of green innovation, particularly in regions with higher pollution levels. These findings suggest that well-structured green industrial policies can serve as effective catalysts for fostering sustainable technological innovations in polluting industries. Policy implications highlight the necessity of targeted, region-specific approaches to maximize the potential of green industrial policies in promoting environmental sustainability and economic growth.

Climate Change, Biased Technological Advances and Agricultural TFP: Empirical Evidence from China

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies.

IMPLEMENTATION OF FUZZY C-MEANS AND FUZZY POSSIBILISTIC C-MEANS ALGORITHMS ON POVERTY DATA IN INDONESIA

Cluster analysis involves the methodical categorization of data based on the degree of similarity within each group to group data with similar characteristics. This study focuses on classifying poverty data across Indonesian provinces. The methodologies employed include the Fuzzy C-Means (FCM) and Fuzzy Probabilistic C-Means (FPCM) algorithms. The FCM algorithm is a clustering approach where membership values determine the presence of each data point in a cluster. On the other hand, the FPCM algorithm builds upon FCM and Possibilistic C (PCM) algorithms by incorporating probabilistic considerations. This research compares the FCM and FPCM algorithms using local poverty data from Indonesia, specifically examining the Partition Entropy (PE) index value. It aims to identify the optimal number of clusters for provincial-level poverty data in Indonesia. The findings indicate that the FPCM algorithm outperforms the FCM algorithm in categorizing poverty in Indonesia, as evidenced by the PE validity index. Furthermore, the study identifies that the ideal number of clusters for the data is 2.

Impact of migrants on communicable diseases in Thailand

BackgroundWhile foreign migrants contribute to economic development, they may impact public health by transmitting communicable diseases to the local population. With its geopolitical position, Thailand has been a primary destination for migrants from neighbouring countries in Southeast Asia and beyond. This positioning makes it a focal point for examining the complexities of migration dynamics and its implications for public health. Through a quantitative analysis, this paper investigates the influence of foreign migrants on physical health issues in Thailand, exploring their impact on various types of communicable diseases. The utilization of provincial-level data from Thailand offers insights into the localized effects of migrant populations on public health within the country. These insights can serve as a valuable resource for researchers and policymakers who conduct comparative analyses, facilitating a deeper understanding of the complex relationship between international migration and public health worldwide.MethodsA spatial panel autoregressive model (SAR) is applied on the provincial level communicable diseases and socio-economic data in Thailand from the period 2016 to 2021.ResultsThe results indicate that the influence of foreign migrants on communicable diseases in Thailand varies depending on the type of disease. While an increase in migrants correlates with a higher prevalence of respiratory and other communicable diseases, it conversely reduces the prevalence of vaccine-preventable diseases. Additionally, we found that migrants do not significantly impact the prevalence of food- and water-borne diseases, insect-borne diseases, animal-borne diseases, or sexually transmitted diseases in Thailand. Additionally, other factors, such as GPP per capita, unemployment, poverty, and technology access, strongly correlate with most types of communicable diseases.ConclusionAs revealed by this study, the increase in migrants leads to a rise in respiratory and other communicable diseases, as well as a decrease in vaccine-preventable diseases, which carries significant policy implications. These results urge policymakers, the Ministry of Labour, and the Ministry of Public Health to implement tailored policies and measures to enhance public health and effectively mitigate the risk of communicable diseases transmitted by migrants in the future.

Exploring the Supporting Role of Finance in the Development of Clean Energy in China Based on the Panel Vector Autoregressive Model

The efficient development and widespread utilization of clean energy hold global significance, particularly for developing countries like China, which has committed to carbon peak and neutrality targets. In this context, the financial sector plays a crucial role in supporting the renewable energy industry, ensuring a reliable energy supply for economic growth. To statistically assess the impact of financial characteristics—such as financial efficiency, financial size, and green finance—this paper employs a panel vector autoregressive (PVAR) model with province-level data from China spanning the period 1991 to 2018. The key findings demonstrate that (1) financial factors significantly contribute to the development of clean energy in China, and among these factors, financial scale has a greater impact than financial efficiency and green finance; (2) there are distinct regional variations in how financial development affects the clean energy sector, and the role of financial scale is particularly pronounced in the central and western regions of China while the impact of financial efficiency on the clean energy industry is not significant across all regions; and (3) other drivers—including industrial structure, financial expenditure, and technological advancements—also spur the growth of the clean energy industry. However, due to diminishing marginal effects, the forces driving its growth may gradually diminish. Therefore, the article proposes critical policy suggestions for promoting clean energy development in China. These policies should consider the regional context and address both financial and non-financial aspects. Understanding the interplay between finance, regional dynamics, and clean energy development is crucial for achieving sustainable and resilient energy systems in China.

Evaluation of regional comprehensive development efficiency under low-carbon policy: based on optimized DDF-GML combined with unsupervised clustering method

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics.

The Impact of International Talent Inflow on Technological Innovation: The Moderating Role of Guanxi Culture and Social Trust

This paper studies the effect of international talent inflow on technological innovation and the influence of the Chinese cultural environment on their relationship. Based on provincial-level data from 2000 to 2012, we construct a static panel data model to explore the effects of international talents on technological innovation and the moderating role of Guanxi culture and social trust in the above relationship. We find that international talent inflow positively impacts technological innovation. Guanxi culture significantly negatively impacts technological innovation and negatively moderates the relationship between international talent inflow and technological innovation. Social trust significantly positively impacts technological innovation and positively moderates the relationship between international talent inflow and technological innovation. The interaction between social trust and Guanxi culture has a significant positive effect on technological innovation. The study shows that different cultural environments have an essential impact on developing international talent’s innovation ability. This paper provides evidence for the need to improve China’s cultural environment and provides important implications for the formulation of talent policies. Based on this, we suggest improving the talent introduction system, optimizing the relationship culture, and building a good social trust system to promote regional innovation.

Does carbon pricing policy improve energy efficiency? New evidence from Canadian provinces

ABSTRACT Given the increasing damage effect of climate change, the Canadian government has taken a further step to ensure that carbon pricing is implemented in all provinces to reduce its GHGs emissions as a means of addressing climate change. Thus, this paper examines the effect of carbon pricing on energy consumption which is the main source of CO2 emission to enhance our understanding beyond carbon-pricing effects on households and revenue recycling in the prior research. Our study analyzes the energy efficiency of Canada using the province-level data between 2000 and 2021, by developing an SFA production model to understand the drivers of energy consumption and then compute the total factor energy efficiency index while controlling for the role of carbon pricing. Our empirical results reveal that increased labor input, as well as output, mitigate the rising capital-induced energy consumption, while carbon pricing policy plays no significant role in influencing energy consumption. However, the effectiveness of carbon pricing is found in reducing province-level energy efficiency. This striking evidence suggests that policymakers should consider a labor-oriented energy saving scheme and conduct a comprehensive review of the current carbon pricing policy in order to align with energy efficiency interventions toward the achievement of Canada’s Paris Agreement targets.

Unraveling the Environmental, Meteorological, and Lifestyle Determinants of Hypertension Mortality in Türkiye

Hypertension is a leading risk factor for cardiovascular diseases and a significant cause of mortality worldwide. This study investigates the association of environmental, meteorological, and lifestyle factors with hypertension mortality in Türkiye from 2010 to 2019. This study analyzed province-level hypertension mortality data for 81 provinces in Türkiye from 2010 to 2019. Predictors included air quality indicators (particulate matter 10, sulfur dioxide, carbon monoxide, nitrogen dioxide, ozone), meteorological variables (air pressure, humidity, temperature, wind speed), and lifestyle factors (smoking, alcohol consumption, exposure to second-hand smoke). An ordinal logistic regression approach was employed to model the likelihood of hypertension mortality, with adjustments for multiple testing using the Benjamini-Hochberg False Discovery Rate technique. In this study, it was found that significant associations are between hypertension mortality and several predictors. Air pressure, in terms of coefficient of variation and median levels, was significantly associated with hypertension mortality. Temperature and humidity showed strong associations, with median levels and variability impacting mortality rates. Lifestyle factors, notably smoking and alcohol consumption, were also significantly associated with increased hypertension mortality. Surprisingly, exposure to smoke at home showed a slight protective effect. The study highlights the complex interplay of environmental, meteorological, and lifestyle factors in terms of influencing hypertension mortality in Türkiye. These findings emphasize the need for multifaceted public health strategies that consider these diverse influences to manage and prevent hypertension-related mortality effectively.