Industrial upgrading and the forest resource curse: evidence from provincial panel data in China

Transportation investment has served as one of the most promising economic instruments to lower transportation costs and promote economic growth. To enhance the effectiveness and efficiency of such kind of capital investments, one critical issue is to gain a better understanding of the pathways that transportation investment would have to influence economic growth. By using a provincial panel data in China, this study attempts to investigate how transportation investments impact economic growth through a variety of pathways. Structural equation modeling (SEM) is applied to understand the relationship between transportation investment, investment in relevant sectors, industrial structure, employment growth, and economic development. It finds that investment in transportation sectors can promote economic growth through direct and multiple indirect pathways. The indirect pathways can improve economic performance through the investments in relevant sectors, growth of industry and employment growth. These impacts would be significantly changed under diverse spatial and temporal conditions.

The mediating effect of financial development on CO2 emissions: An empirical study based on provincial panel data in China

Economic development plays an important role in regional employment quality. Taking provincial panel data in China during 2010–2019 as a sample, we constructed an employment quality and economic development quality indicator system. The system conducted a comprehensive evaluation model with entropy weight to measure provincial employment and economic development quality indexes. The system also applied fixed-effect panel regression models to research the influence of economic development quality on regional employment quality. The results showed that employment structure affected the regional employment quality index, followed by social security. There were regional differences in the employment quality index, among which the employment quality index in the eastern area was higher, and it was at its lowest in the western region. The sharing economy was a critical factor in economic development quality, which had significant regional heterogeneity. Economic growth had the most significant and positive influence on employment quality, followed by the sharing economy and economic structure. In addition, the consumer price index and the urban–rural gap substantially affected employment quality. However, education expenditure played a significant inhibitory role in employment quality. Economic development quality had the most significant effect on eastern employment quality, followed by the central region, and it had the least effect in the west.

PurposeSince 2013, China has implemented targeted poverty alleviation policies, successfully eradicating absolute poverty nationwide by 2021. The fiscal funds allocated for poverty alleviation have significantly contributed to reducing poverty in impoverished areas. However, to date, there has been a lack of scholarly research specifically examining the effects of these fiscal poverty alleviation funds on both poverty reduction and economic growth. This study aims to address two key questions: What role do fiscal poverty alleviation funds play in reducing poverty? Additionally, do these funds contribute to economic growth?Design/methodology/approachProvincial panel data in China from 2010 to 2020 are used to test the impact of fiscal poverty alleviation funds on poverty reduction and economic growth. The empirical study of this paper primarily employs panel data within difference and two-stage least squares (2SLS) estimation for causal identification.FindingsPoverty alleviation funds positively influence China’s economic growth and significantly reduce the rural poverty rate. During the sample period, the contribution of poverty alleviation funds to economic growth reached 7.3%, and the contribution to the reduction of the poverty incidence rate was 8.4%.Originality/valueThe key contribution of this study lies in its novel approach of using empirical methods to probe the impacts of fiscal poverty alleviation funds on provincial economic growth. Additionally, this paper also empirically tests the mechanisms by which fiscal poverty alleviation funds promote growth and reduce poverty, mainly by improving the infrastructure development conditions in impoverished areas.

Based on a panel of 31 provinces and cities from 1990 to 2019, we first conduct an empirical analysis using the maximum likelihood (ML) procedure to examine the effects of various disasters (i.e. droughts, floods, earthquakes, storms, typhoons and low and freezing temperatures) on the medium‐term economic growth of China and its three economic regions (i.e. the eastern, central and western regions). We identify the transmission channels through which these disasters affect economic growth by investigating the medium‐term relationships among disasters, capital accumulation, human capital accumulation and total factor productivity. The interprovincial empirical analysis demonstrates that the effects differ across the economic regions. Thus, disasters affect economic growth through different channels but mainly through capital stock. Further research indicates that the growth effect of disasters largely benefits from Chinese government expenditures on disaster relief.

This paper empirically studies the relationship among inclusive finance, industrial structure upgrading and farmers’ income, using the panel data of 28 provinces in China from 2006 to 2016.The research finds that inclusive finance can significantly promote the increase of farmers’ income. Moreover, the Upgrading of Industry Structure (UIS) is the intermediary mechanism of inclusive finance to promote the increase of farmers’ income, and this intermediary mechanism is heterogeneous among farmers with different income levels. Finally, the promotion effect of the UIS on farmers’ income is affected by the threshold effect of inclusive finance. Compared with the development level of low inclusive finance, the promotion effect of the UIS on farmers’ income is stronger under the development level of high inclusive finance. According to the results of empirical analysis, we suggest that the development strategy of inclusive finance should aim at the industrial development in rural areas, promote the organic connection between farmers and modern agricultural industry, and drive farmers to increase their income through the transformation and upgrading of rural industries.

Can urban sprawl be the cause of environmental deterioration? Based on the provincial panel data in China

As digital transformation deepens, digital agriculture plays a crucial role in advancing the Coordinated Development Level of Ecosystem Services and Human Well-Being (CD-ESWB). However, aligning ecosystem service capacities with human development needs remains a challenge. This study investigates how digital agriculture influences CD-ESWB, using panel data collected from 30 provinces in China between 2014 and 2022. First, an index system, the Level of Digital Agriculture Development (LDAD), is discussed, followed by a quantitative analysis using the entropy-weight TOPSIS method. The CD-ESWB is then evaluated through the “Ecosystem Services–Human Well-Being” coupling coordination model. Empirical analysis, incorporating fixed effects, mediation, and moderation models, demonstrates that digital agriculture significantly enhances CD-ESWB, though its impact varies across regions. Robustness checks, including instrumental variable methods, sample interval adjustment, and variable substitution, confirm the reliability of the findings. Notably, the Technological Innovation Effect (TIE) mediates digital agriculture’s impact, while Industrial Structure Upgrade (ISU) acts as a positive moderator. This study emphasizes the importance of regional policies in promoting technological innovation and optimizing industrial structures, providing both theoretical and empirical insights into how digital agriculture shapes CD-ESWB.

In recent years, China’s economic growth speed has been slowing down, leading to the problems of overcapacity and unbalanced regional economic development, and the mismatch between industrial and financial structure is becoming intense. This paper, starting with the relationship among economic growth, industrial structure and financial structure, summarizes the research by the former scholars. On this basis, by using data of 31 provincial panel data in China from 2007 to 2016, the article aims to find out the relationship between the industrial structure and economic growth, the relationship between the financial structure and economic growth and the relationship between the interaction of financial and industrial structure and economic growth. Finally, the conclusions of this paper are obtained that the interaction between the financial structure and the industrial structure can promote the economic growth significantly. However, the matching effect of the financial structure and industrial structure in China has not been completely formed, and the industrial upgrading should be guided to be structurally reformed through the policy.

Impact of urban-rural development and its industrial elements on regional economic growth: An analysis based on provincial panel data in China

The core of how to break through the situation of “internal and external troubles” and realize regional economic growth in China is to promote the industrial structure upgrading. In order to empirically analyze the impact of the industrial structure upgrading on regional economic growth, based on the panel data of 30 provinces in China (excluding Tibet) from 2011 to 2020, this paper uses the empirical model to gradually add control variables for regression, and finally uses two robustness tests of tail treatment and province fixed effects. The results show that after introducing a series of relevant control variables, the industrial structure upgrading has a significant positive effect on regional economic growth. At the same time, based on the results of empirical research, this paper puts forward some policy suggestions, such as formulating regional differentiation policies, increasing long-term investment in innovative technology and human capital.

This paper aims to analyze how the digital economy affects industrial restructuring and examine the mediating role of the relevant factors. Based on the analysis of the effect mechanism of the digital economy development on industrial restructuring, this paper constructs an improved measuring index system of digital economy covering digital infrastructure, digital industrialization, and industrial digitalization, and measures regional digital economic growth based on provincial panel data in China from 2013 to 2020 by using the entropy TOPSIS method, empirical analyses on the impact of the digital economy on industrial restructuring, and verifies the mediating effect of human capital, technological innovation, and financial development in this process. Research findings are as follows: (i) Digital economic growth demonstrates a considerable positive effect of the speed, efficiency of industrial restructuring, and industrial structure rationalization. (ii) Digital economy indirectly boosts industrial restructuring by affecting human capital, technological innovation, and financial development. The findings in this study are of theoretical significance to interpret the effect of digital economic growth on industrial restructuring, facilitating relevant economies in the decision-making of industrial restructuring and upgrading.

Assessing the economic and environmental effects of environmental regulation in China: The dynamic and spatial perspectives

A low-carbon economy serves as a core pathway and pivotal engine for advancing the SDGs. Drawing on provincial panel data across 30 Chinese administrative regions spanning 2011–2023, the present study empirically examines how new infrastructure interacts with low-carbon economic development levels and their underlying transmission mechanisms by building an econometric model. Empirical results demonstrate that “new infrastructure” generates a notably positive facilitating impact on low-carbon economic development, with this influence being more pronounced in the central and western regions of China and policy pilot zones, while a rebound effect is identified in eastern China. Among various types of new infrastructure, information infrastructure and innovation infrastructure play particularly prominent roles, while integrated infrastructure shows a positive yet statistically insignificant impact. Mechanism analysis reveals that new infrastructure advances low-carbon economic progress primarily by curbing capital factor misallocation, while the elevation of the population urbanization level can amplify the facilitative impact of new infrastructure on the low-carbon economy. On this basis, it is imperative to raise investment in new infrastructure and enhance its systematic coordination with traditional infrastructure; implement differentiated layout strategies aligned with regional features; rationally steer the population urbanization process; and effectively facilitate the decoupling of carbon emissions from economic growth, thereby furnishing a robust underpinning for the full attainment of SDGs.

Digital economy, energy efficiency, and carbon emissions: Evidence from provincial panel data in China