Chinese Provincial Panel Data Research Articles

How does the digital economy affect carbon emissions from tourism? Empirical evidence from China

The rise in carbon emissions linked to the tourism industry has challenged its long-standing reputation as an eco-friendly sector. In parallel, the digital economy's evolution has introduced a series of transformations within tourism. This necessitates a thorough examination of the intricate interplay between the digital economy and carbon emissions in the tourism sector. With the help of Chinese provincial panel data, this study uncovers a compelling relationship marked by an inverted "U" curve through two-way fixed model, moderated effects model and threshold regression analysis. Intriguingly, an increase in road density shifts the inflection point of this curve to the lower left. As road density reaches a critical threshold of 0.361, it not only amplifies the elasticity of the inverted "U" curve but also accelerates the timeline to reach peak tourism-related carbon emissions. This study underscores a significant practical implication: while digital technology exacerbates carbon emissions from tourism at this stage, the dampening effect of digital technology is to be expected as the development of industrial manufacturing brings better transportation. However, the timing of the tipping point may be earlier or later for different regions, depending on whether the local level of industry is sufficiently developed.

Research on Territorial Spatial Development Non-Equilibrium and Temporal–Spatial Patterns from a Conjugate Perspective: Evidence from Chinese Provincial Panel Data

Clarifying the intrinsic nature and formation mechanisms of the territorial spatial development non-equilibrium, optimizing the allocation of territorial resources, promoting regional balanced development, and alleviating regional development disparities have become common endeavors of all countries seeking to enhance development quality. This study, based on the land use and socio-economic data of 31 provinces and cities in China from 2006 to 2020, utilized the kernel density estimation method and ArcGIS spatial analysis to explore the spatiotemporal evolution characteristics of China’s territorial spatial development non-equilibrium. The research findings are as follows: (1) From 2006 to 2020, both the land development intensity and land supply capacity showed an increasing trend, with increases of 21.4% and 8.03%, respectively. However, their spatiotemporal evolutions significantly differed. (2) The state of the territorial spatial development non-equilibrium in China significantly improved, with a rising trend in the territorial spatial equilibrium degree. Regional disparities in the territorial spatial equilibrium degree decreased. The number of provinces and cities in a state of underdevelopment decreased from 23 to 8, while the number in an equilibrium state increased from 7 to 21. The central and western regions showed more significant improvements in the territorial spatial equilibrium degree and a greater reduction in regional disparity when compared to the eastern and northeastern regions. (3) China exhibited distinct regional disparities in the territorial spatial equilibrium degree. The overdeveloped areas were Beijing and Shanghai. The underdeveloped regions were primarily concentrated in western areas, including Sichuan, Yunnan, and Xinjiang. The high-level equilibrium regions were predominantly located in the southeastern coastal provinces and the central plains region, while the low-level equilibrium regions included Inner Mongolia, Ningxia, Qinghai, and the three northeastern provinces. (4) From the perspective of the number of agglomeration types, the order is HH (high–high) > LH (low–high) > LL (low–low) > HL (high–low), and China’s TSED exhibits a spatial proximity peer effect. The innovation of this study consists of the following aspects: (1) The clarification of the fact that the essence of equilibrium does not require an exact 1:1 match, as with “two horses”; rather, it entails the maintenance of a slight surplus of land supply capacity over land development intensity. This approach allows the possibility of future sustainable development by leaving room for expansion. (2) The differentiation between high-intensity conjugation (in terms of both quantity and quality) and low-intensity conjugation (quantity only) from a conjugate perspective. This categorization aids in a more comprehensive and in-depth understanding of the territorial spatial development non-equilibrium and its spatiotemporal patterns. It provides crucial information for the formulation of sustainable national territorial development plans and the promotion of a regional development equilibrium.

A win-win opportunity for economic growth and carbon emissions reduction in China: The perspective from correcting energy price distortions

Distorted energy prices undermine resource allocation efficiency and threaten China's economic growth and reduction of carbon emissions. This study examines the price distortions for fossil and renewable energy based on Chinese provincial panel data and estimates the influence of distorted energy prices on the coordination of economic growth and carbon emissions reduction (CECR). The results show that the energy price distortions significantly inhibit CECR and especially distorted coal price has the most inhibitory impact. The impact is regionally differentiated, with the eastern region (E region) being more negatively affected by price distortions in oil, natural gas, and renewable energy. Coal price distortion is a greater impediment to coordinated development in the Central-Western regions (C–W regions). Therefore, the correction of energy price distortions (CEPD) becomes key to achieving a win-win situation for both economic growth and carbon emissions reduction (ECR). Further analysis reveals that the scenario of correcting actual energy prices is more conducive to promoting CECR, with a growth potential of 1.81 %, and the growth potential in C–W regions is greater than in E region. This study both provides for China and the emerging economies a useful expansion of the market's decisive role in the allocation of resources and a reference for exploring the win-win of ECR.

Exploring the Impact of the Digital Economy on China's Export Implied Carbon Intensity: A Provincial Panel Data Analysis

Exploiting the positive effect of digital economy on reducing the implied carbon intensity of exports is an important path to promote the green and low-carbon transformation of China's export trade. In view of this, using the Chinese provincial panel data from 2008 to 2020 to scrutinize the consequential impact and intricate mechanisms at play between these variables. Employing a robust methodology, including fixed-effects models, mediating-effects models, and threshold models, the analysis delves into the multi-faceted impact of the digital economy on export implied carbon intensity. It is found that (1) The enhancement of the digital economy can significantly reduce the implied carbon intensity of exports. (2) The digital economy further diminishes the implied carbon intensity of exports through the mediating influences of industrial structure and technological progress. (3) The relationship between the digital economy, industrial structure, and technological progress exhibits a noteworthy non-linear dynamic concerning export implied carbon intensity.

Spatiotemporal Heterogeneities in the Impact of Chinese Digital Economy Development on Carbon Emissions

The digital economy plays an important role in reducing the global warming process. This paper explores the spatiotemporal heterogeneity impacts of the digital economy on provincial carbon emissions and its underlying mechanisms. Initially, this paper examines the inhibitory impact of the digital economy on carbon emissions, alongside the mediating role of economic agglomeration, at a theoretical level. Subsequently, it empirically explores the quantitative associations among the digital economy, economic agglomeration, and carbon emissions by utilizing Chinese provincial panel data spanning from 2000 to 2021. This investigation employed static and dynamic spatial Durbin models as well as mediation models to analyze the interrelationships. The results firstly revealed that the digital economy notably diminishes carbon emissions, with economic agglomeration playing a significant mediating role. This conclusion remained consistent even after substituting the explanatory variables and weight matrix, modifying the sample period, and conducting other robustness tests. Secondly, the impact of the digital economy on carbon emissions exhibited spatial spillovers. Compared with the impact on the local area, the impact on neighboring provinces was found to be weaker. Thirdly, carbon emissions showed a significant “snowball” effect in the time dimension. This paper emphasizes the important role of digital technology in curbing carbon emissions, and it provides some policy insights for studying the digital economy, economic agglomeration, and carbon emissions. Furthermore, it offers valuable insight and suggestions to reduce carbon emissions and realize the goal of the “dual-carbon” strategy.

Research on the impact of digitalization on green development: An empirical analysis from the low-carbon strategy perspective.

With the collision between the green and low-carbon economy and the accelerating digital economy, how to realize the effect of "1+1>2" has gradually become an important topic for contributing to the high-quality development of regions and enterprises. Entrepreneurship in the digital age continues to exhibit new characteristics, and its impact on green development is also more closely related. This article focuses on the context of the low-carbon strategy, incorporating the digitalization level, entrepreneurship, and green development into the same framework. It then takes 2011-2021 Chinese provincial panel data and enterprise panel data as samples to conduct research. The results indicate the following: (1) The digitalization level has a significant positive promoting effect on the green development of regions and enterprises, and blockchain technology has the strongest promoting effect on the green development of enterprises. (2) The digitalization level drives the green development of regions and enterprises through three channels: entrepreneurs' innovative spirit, entrepreneurs' entrepreneurial spirit and entrepreneurs' contract spirit. Entrepreneurship is the intermediary bridge for the digitalization level to promote green development. (3) Environmental regulations partially serve as "accelerators" of the impact of green development. The findings of this article will provide empirical support for evaluating the impact of digitalization on green development and offer useful insights for better stimulating and cultivating entrepreneurship in the new era to empower comprehensive green development.

Credit term structure and corporate indebtedness

At present, one of the major issues that seriously plague the high-quality development of the real economy globally is the current prevalence of high indebtedness and high leverage, as well as the financing problems of manufacturing enterprises. This paper empirically investigates the extent of the impact of bank credit term structure on corporate indebtedness and its mechanism using Chinese provincial panel data from 2003-2020 as the research sample. The results show that, firstly, long-term bank credit term structure can reduce corporate liabilities and mitigate corporate liability risks, and this result still holds after endogeneity analysis and robustness tests such as lagging credit term structure by one period, using instrumental variable method, and replacing explanatory variables. Second, income effect and innovation effect are two important mechanisms by which credit term structure affects corporate liabilities. Finally, the heterogeneity results show that the credit term structure of firms in the central and western regions has a more pronounced effect on corporate indebtedness than in the eastern regions. Therefore, this paper suggests optimizing the credit term structure, promoting the effective support of credit for the sustainable development of the real economy, taking full account of regional differences, and creating a more favorable environment for enterprise financing and development.

Impact Of Preschool Education Financial Expenditures on The Number of Full-Time Preprimary Teachers in Rural Regions--An Analysis Based on Chinese Provincial Panel Data, 2012-2021

Education is an essential problem concerning the whole society, creating citizens with well-educated is the foundation of a good country. Financial expenditure on education is the basic supplement and support of advanced education. However, preschool education has lower attention compared to other seminars. There is a certain gap in allocation. Therefore, the focus of this study is on how education spending affects the number of rural kindergarten teachers, using the quantitative analysis method, from the Economy Prediction System (EPS) database to collect the corresponding panel data of China's provinces during the decade 2012-2021 to analyze and hypothesize, and finally concludes as follows. The amount of kindergarten full-time teachers in rural areas is obviously and positively related to the total investment in preprimary education, and this relationship is more significant in the western region. The study also found that among the items of financial expenditures on preschool education. Spending on products and services, as opposed to pay, benefits, and assistance for individuals and families, had a greater impact on the amount of kindergartens full-time teachers in rural areas. Through the path analysis in the study, we can know that the educational financial expenditure can increase the number of full-time kindergarten teachers in rural areas by increasing the number of kindergartens and students.

Can digitalization effectively promote green energy efficiency? The linear and nonlinear relationship analysis.

In light of the integration of digitalization and the energy revolution, digitalization can be integrated into the energy industry to develop energy-saving technologies and improve resource allocation efficiency. On the basis of 2013-2019 Chinese provincial panel data, this paper measures the level of green energy efficiency based on the super-EBM-DEA model and analyzes the linear relationship, nonlinear relationship, and potential mechanism between digitalization and green energy efficiency. The findings indicate that (1) overall, both China's digitalization and green energy efficiency formed a steady upward trajectory during the sample period. Digitalization showed a spatial characteristic of extending and spreading from the eastern region to the central and western regions. Green energy efficiency was characterized by obvious regional heterogeneity. (2) Progress in digitalization has a significant driving effect on green energy efficiency. Subdimensional analysis shows that this driving effect mainly comes from digital development and digital transactions. (3) The impact of digitalization on green energy efficiency presents a threshold effect of economic agglomeration (with a threshold of 0.0257 and a marginally increasing, positive driving trend) and population agglomeration (with a threshold of 4.2750 and a marginally decreasing, positive driving trend). (4) Decomposing changes in green energy efficiency into scale efficiency and pure technical efficiency, this study shows that pure technical efficiency gains due to digitalization are the main driver of green energy efficiency improvements. Finally, some specific policy recommendations are proposed.

Has the Advancement of the Digital Economy Improved the Well-being of the Population? --Empirical Study Based on Chinese Provincial Panel Data

Promoting the long-term prosperity of a country by exploring the relationship between the digital economy and residents' happiness holds great significance. This research quantifies the extent of digital economy progress through the utilization of the Critic approach. The investigation assesses the evolution in disparities in digital economy development levels across various provinces. Since happiness is a discrete ordered response variable, this paper utilizes an ordered probit model to investigate the impact relationship, incorporating individual characteristic variables. Furthermore, this study takes the sense of social justice as the mediating variable to test whether the development level of digital economy has a mediating effect on residents' happiness. The empirical results imply that the disparity in digital economy development levels among provinces gradually decreases over time, and boosting digital economy development positively make contributions to improving residents' happiness. The impact effect comprises both direct and indirect effects; specifically, digital economy development directly affects residents' happiness and indirectly influences it by enhancing their sense of social fairness. Based on these conclusions, this paper offers relevant recommendations to promote national prosperity and enhance residents' happiness.

How artificial intelligence affects the labour force employment structure from the perspective of industrial structure optimisation

To investigate how artificial intelligence (AI) affects the structure of labour force employment, we integrate robotics adoption and employment into this study's model. Based on Chinese provincial panel data from 2010 to 2019, fixed, mediating and threshold effects models and a spatial heterogeneity model were used to empirically test the impact of AI on the employment structure from the perspective of industrial structure optimisation and its mechanisms of action. The findings demonstrate that the impact of AI on the labour force employment structure reflects unique characteristics for China and promotes the advancement of the nation's employment structure. The influence of AI on the labour force employment structure follows a non-linear pattern, fostering labour force employment structure optimisation and upgrading from the perspective of industrial structure optimisation. Further investigation reveals the influence of spatial spillover effects from AI on employment structure optimisation. These research findings have theoretical value and practical significance for optimising China's employment structure in the context of AI.

Impacts of green taxation on the green transformation of manufacturing industry: an empirical analysis based on Chinese provincial panel data

Impacts of green taxation on the green transformation of manufacturing industry: an empirical analysis based on Chinese provincial panel data

Does digital technology innovation promote low-carbon development in agriculture?: A spatial econometric analysis based on 31 provinces in China.

China's traditional agriculture has grown quickly but at the cost of excessive pollution and energy consumption. Therefore, low-carbon development in agriculture is crucial to achieving "carbon neutrality" and "carbon peaking." With the development of China's digital economy and the construction of digital villages in recent years, digital technology innovation (DTI) is probably going to a significant role in lowering agricultural carbon emissions (ACEs). Based on Chinese provincial panel data from 2006 to 2021, we analyze the spatial and temporal evolution characteristics of DTI and ACE, explore the impact and the pathways of DTI on ACE using a spatial econometric model, and reveal this impact's heterogeneity and nonlinear character. The findings show that DTI and ACE increased significantly throughout all Chinese provinces. DTI agglomeration is becoming stronger, whereas ACE displays a tendency for discontinuous distribution. DTI is essential in promoting low-carbon development in agriculture, and there are significant spatial spillover effects due to technology spillovers. Heterogeneity analysis indicates that DTI has positive impacts on local agriculture in different regions. However, there is variation in the impact's degree. The mechanism test's findings show how DTI reduces ACE by improving technology and enhancing resource endowment. The relationship between DTI and ACE exhibits an inverted "U" curve, and the level of economic development is the threshold variable that constrains the relationship between the two variables. To achieve a regional balanced low-carbon development in agriculture through DTI, it is important to emphasize the impact of DTI on reducing carbon emissions and to encourage the transfer of mature technology from high-level regions to low-level regions.

The impact of digital economy on high-quality economic development: Research based on the consumption expansion.

Studies have found that the digital economy plays a positive role in promoting high-quality economic development. Meanwhile, the digital industrialization and industrial digitalization have given rise to new demands and supply modes of consumption. It is necessary to analyze the role of consumption expansion in the impact of digital economy on high-quality economic development. Based on Chinese provincial panel data, we first applied the entropy weight method to construct the digital economy index and the high-quality economic development index. And on this basis, it was verified that the digital economy can positively promote the high-quality development of the inverted U-shaped structural economy. Then we separately used the mediation and the threshold effect models to analyze the role of consumption expansion in empowering high-quality development in the digital economy. Regional heterogeneity was further taken into account. The results dedicate that consumer demand and the digital economy have a partial or complete mediating effect. The promotion of high-quality development by the digital economy can be affected by the threshold of consumption expansion, which is manifested in the marginal incremental effect due to the growth of consumption supply. On the contrary, the growth of consumer demand has led to the inverted U-shape of the digital economy to promote high-quality economic development. In the heterogeneity analysis, the threshold effect also varied greatly. This research enriches the theoretical achievements and reveals the impact of consumption expansion on the digital economy affecting the high-quality development, which may provide certain reference for other countries and regions.

Can environmental protection tax drive manufacturing carbon unlocking? Empirical evidence from China

IntroductionChina’s environmental protection tax policy has emerged as a pivotal force in steering the country towards reduced pollution and carbon emissions. This study focuses on evaluating the impact of the environmental protection tax on carbon unlocking within the manufacturing industry, offering crucial insights to address the dual challenges of industry development and carbon emission reduction.MethodsUtilizing Chinese provincial panel data spanning from 2004 to 2020, we gauge the carbon unlocking efficiency of the manufacturing industry using the super-efficiency slacks-based measure (SBM) model with undesired outputs. Additionally, we empirically examine the impact of the environmental protection tax policy on manufacturing carbon unlocking through the propensity score matching difference-in-differences (PSM-DID) model.ResultsOur findings indicate a significant enhancement in the carbon unlocking efficiency of the manufacturing industry due to the implementation of the environmental protection tax policy. Compared with the provinces (municipalities) that did not raise the environmental protection tax rate standard, the carbon unlocking efficiency of manufacturing in the provinces (municipalities) that raised the environmental protection tax rate standard increased by 11.6%, and the dynamic effect shows that the policy effect increases gradually over time. Further mechanism tests reveal that an environmental protection tax improves manufacturing carbon unlocking efficiency mainly by stimulating manufacturing firms to increase environmental protection investment and green technology innovation. Moreover, there is heterogeneity in the policy effect of the environmental protection tax, and its impact on manufacturing carbon unlocking is more significant in the central and western regions and regions with higher levels of legalization.DiscussionTherefore, we should adhere to the policy orientation of low-carbon development in manufacturing, accelerate green technological innovation in manufacturing, and coordinate the special advantages of each region according to local conditions to bring into play the role of an environmental protection tax in reducing carbon and improving efficiency.

Facilitating fertility decline through economic development: a principal-agent analysis of local bureaucratic incentives in China’s fertility transition

Despite close associations, political science had weak explanatory power for fertility transition. It often depicts the political processes of fertility transition as direct and coercive policies and mechanical execution without consideration of indirect bureaucratic processes. Drawing on principal-agent and economic-driven theories, this study established a novel model using 1980–2000 Chinese provincial panel data: local officials facilitated fertility decline through economic development for career advancement. System generalized method moments (GMM) and ordered logistic regression (OLM) results showed: (1) gross domestic product (GDP) per capita growth (OR = 0.012) and total fertility rate (TFR) decline (OR = 0.026) increased promotion odds, while excessive TFR decline (over 37% within one term) decreased it; (2) the critical age (59) and tenure year (one year before leaving office) positively associated with GDP per capita, industrialization, and lower TFR; (3) GDP per capita and industrialization negatively associated with TFR. Facilitating fertility decline via economic development was an efficient, low-risk strategy for local officials compared to radical birth control campaigns. It was the first study applying principal-agent theory to explain how bureaucratic processes enabled fertility transitions. It combined political and economic-driven theories on fertility transition, advancing political demography and refining the social science paradigm on fertility transition.

The role of industrial intelligence in peaking carbon emissions in China

As industrial intelligence empowers economic advancement and technological progress, its capacity to enable decarbonization during China's low-carbon transition remains uncertain. Existing literature concentrates on the environmental impact of information and communication technologies or uses single-dimension measuring indicators, failing to capture the comprehensiveness of industrial intelligence. Based on the concept of full-cycle management, this study constructs a comprehensive index to evaluate industrial intelligence from intelligent inputs, intelligent production capacity, and intelligent outputs. Using 2006–2020 Chinese provincial panel data and fixed-effects models, we analyze the effects, mechanisms and thresholds of industrial intelligence on carbon emissions. The results show that: (1) The level of industrial intelligence plays a role in reducing carbon emissions after a certain threshold. (2) Industrial intelligence reduces carbon emissions by advancing green technology and optimizing production structure. (3) Industrial intelligence mitigates carbon emissions in eastern and north China but not western China. According to current growth rates of industrial intelligence, nine Chinese provinces may achieve a carbon peak through industry intelligence by 2030. (4) Moreover, industrial intelligence's carbon emission reduction effect is significant in labor- and technology-intensive industries but does not work in capital-intensive industries. These revelations have meaningful implications for orienting industrial intelligence development and decarbonization initiatives.

The Effects of the Digital Economy on Carbon Emission: Evidence from China

ABSTRACT This study used Chinese provincial panel data from 2011 to 2019 to analyze the impact of the digital economy on carbon emissions and the mediating effect of industrial structure. The key findings are as follows: (1) industrial structure has a mediating effect on the influence of the digital economy on carbon emissions; (2) the direct impact of the digital economy on local carbon emissions is greater than the indirect impact on nearby carbon emissions; and (3) the digital economy has a noticeable effect on carbon emissions in the eastern and central regions of China, but not in the western region.

Can rural human capital inputs enhance agricultural total factor productivity? - Based on the dualistic economic structure perspective

<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: arial, helvetica, sans-serif;">Human factor inputs are key to promoting agricultural modernisation. Traditional economic theory suggests that improving human capital is the key to boosting agricultural productivity, but can this conclusion hold in China's dualistic economic structure? We use Chinese provincial panel data from 2000-2017 to examine the impact of rural human capital inputs on agricultural total factor productivity. We find that, on the whole, rural human capital inputs have a negative effect on agricultural total factor productivity, and that there is a "rural human capital trap". Mechanism analysis reveals that rural human capital inputs, on the one hand, cause labour loss and reduce the quality of agricultural workers, while on the other hand, they may promote the application of mechanization, which has both positive and negative effects on agricultural total factor productivity. Heterogeneity analysis finds that this negative effect is more pronounced in the central region of China because of the serious loss of rural labour. This study provides new policy insights for further improving the structure of rural education inputs and promoting human capital accumulation in agriculture.</span></p>

Does energy resource misallocation affect energy utilization efficiency? Evidence from Chinese provincial panel data

Along with the rapid development of society, the position of energy has become more prominent in recent years. However, energy resource misallocation has been a common phenomenon, which has been a brake on energy efficiency promotion and regional low carbon development. Therefore, this study serves to investigate interprovincial energy resource misallocation in China across five typical industries from 2003 to 2017 by an improved Gini Coefficient method. Then a panel data model is built to explore whether energy resource misallocation has a significant impact on energy efficiency. Results show that the national energy resource misallocation index (MI), on average, fell from 0.461 in 2003 to 0.363 in 2017, presenting a decreasing trend, which means that China's interprovincial energy resource misallocation has been effectively alleviated. Furthermore, we find that the energy resource misallocation has a significant negative effect on interprovincial energy efficiency. More specifically, a 1% decrease in the energy resource MI causes a 0.268% increase in energy efficiency. In addition, the urbanization level, industrial structure, and the proportion of fossil energy could inhibit the improvement of energy efficiency, while the increase in economic level could exert a positive effect on the improvement of energy efficiency.