Two-way Fixed Effects Model Research Articles

Technological anxiety: Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood. Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an “icing on the cake” or “adding fuel to the fire” needs further study. This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy. First, from the theoretical logic and the economic development law, this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs. Then, based on the panel data of 269 cities in China from 2006 to 2021, we use the two-way fixed effect model, dynamic threshold model, and two-stage intermediary effect model. The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism. Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the “creation effect”. In other words, advanced digital technology has created additional jobs, and the overall supply of employment in the labor market has increased. The conclusion is still valid after the endogeneity identification and robustness test. In addition, the positive effect has a nonlinear effect on the network scale. When the installation density of industrial robots exceeds a particular threshold value, the division of labor continues to deepen under the combined action of the production efficiency and compensation effects, which will cause enterprises to increase labor demand further. Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions. This study concludes that in the digital China era, the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market. This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

The Impact of Environmental, Social, and Governance Disclosure Quality on Stock Price Volatility in Heavily Polluted Industries - Based on Chinese Listed Companies

Facing natural disasters caused by the destruction of ecosystems, the world is paying increasing attention to the protection of ecosystems. Meanwhile, investors are particularly concerned about enterprises' environmental, social, and governance (ESG) performance, which is considered to be crucial to long-term development and value improvement. Currently, access to ESG information relies mainly on proactive disclosure by companies. Although China attaches great importance to corporate ESG disclosure, the quality of many companies' ESG disclosures remains poor, especially in heavily polluted industries. As China’s financial market matures, more and more investors may utilize stock price volatility to assess investment risk and then make investment decisions. Therefore, this paper aims to examine the impact of ESG disclosure quality on stock price volatility in heavily polluted industries. Taking listed companies in China's heavily polluted industries as the research object, this paper explores the impact of ESG disclosure quality on stock price volatility in heavily polluted industries by building a two-way fixed-effects regression model. This paper chooses Bloomberg Data Terminal's scores on ESG disclosure quality of companies and takes 2012 to 2020 as the research interval. Ultimately, this paper launches the study based on 693 data from 77 sample companies. After regression analysis and robustness test, the following conclusion is drawn: ESG disclosure quality and stock price volatility of heavily polluted companies show a positive correlation.

Can Artificial Intelligence Effectively Improve China’s Environmental Quality? A Study Based on the Perspective of Energy Conservation, Carbon Reduction, and Emission Reduction

The “technological dividends” brought by AI development provide a new model for the country to achieve green governance, enhance enterprises’ ability to manage pollutant emissions during production and operations, and create a new driving force for improving environmental quality. In this regard, this paper systematically examines the impact of AI on environmental quality in China by employing provincial panel data spanning from 2000 to 2020. Focusing on energy conservation, carbon reduction, and emissions mitigation, the analysis is conducted through the application of a two-way fixed-effects model and mediation effects model to explore both the effects and the mechanisms of AI’s influence on environmental quality. The findings indicate that the development and implementation of AI contribute positively to China’s efforts in energy conservation, carbon reduction, and emissions mitigation, ultimately leading to an enhancement in environmental quality. This conclusion remains valid after multiple robustness checks. Mechanism tests reveal that the optimization of regional energy structures, advancements in green technological innovation, and upgrades in industrial structures serve as crucial pathways through which AI facilitates energy conservation, carbon reduction, and emissions mitigation. Heterogeneity analysis uncovers a notable “path dependence” effect in China’s AI development; regions characterized by higher material capital investment, more advanced technological market development, and greater levels of marketization experience a relatively more pronounced impact of AI on the enhancement of environmental quality. This study offers direct references and practical insights for countries globally to foster AI development, enhance environmental quality, and advance high-quality economic growth amid the ongoing wave of digital and intelligent transformation.

Climate risk and green total factor productivity in agriculture: The moderating role of climate policy uncertainty.

In light of the escalating global warming and the escalating frequency of extreme weather events, the agricultural sector, being a fundamental and pivotal industry worldwide, is encountering substantial challenges due to climate change. Using Chinese provincial panel data for 2000-2021, this paper utilizes a two-way fixed-effect model to investigate the impact of Climate Risk (CR) on green total factor productivity in agriculture (AGTFP), with China's climate policy uncertainty (CPU) being introduced as a moderating variable within the research framework to scrutinize its influence in this context. The findings reveal a noteworthy adverse effect of CR on AGTFP, further exacerbated by CPU. Heterogeneity analysis results show that there is a clear regional variation in the effect of CR on AGTFP across different Chinese regions, with CR significantly inhibiting AGTFP development in the northern regions and provinces in major grain producing regions. Consequently, there is a pressing necessity to bolster the establishment of climate change monitoring infrastructures, devise tailored climate adaptation strategies at a regional level, and enhance the clarity and predictability of climate policies to fortify the resilience and sustainability of agricultural production systems.

Regional price differences of medical services: evidence from China

BackgroundPrice levels of medical services may vary across regions with different income levels, which would raise concerns about the equal access to medical services. This study aimed to estimate the spatial price index of medical services to measure price levels across 31 provincial regions in China.MethodsPrice data were collected from medical service price schedule in each region. Two methods based on the Purchasing Power Parities were used to estimate the spatial price index and measure price differences across regions. The two-way fixed effects models were used to examine the association between medical service price levels and income levels, and further investigate the impacts of price differences on utilization of medical services and medical expenditure.ResultsThe consistent estimation results were given by two methods. Medical service price level in the highest-price region was found to be 74% higher than the lowest. There was a significant negative correlation between price levels and income levels, as well as price levels and the utilization of outpatient services. Moreover, we also found a 1% increase in medical service price level was significantly associated with a 0.34% and 0.24% increase in the medical service expense per outpatient visit and per inpatient respectively.ConclusionsRegions in China had significant gaps in medical service price levels. Policymakers should pay more attention to regional price differences and take great measures such as enhancing financial protection to ensure the equal access to medical services and better achieve the universal health coverage.

How does the digital economy affect the green transition: The role of industrial intelligence and E-commerce

As a new economic form, the digital economy (DE) significantly impacts green development. However, the impact of the DE on green total factor productivity (GTFP) remains controversial. A two-way fixed effect model is constructed to explore the impact of DE on green development. It is found that (1) there is a U-shaped relationship rather than a positive relationship between DE and GTFP. (2) Industrial intelligence and e-commerce are essential for DE to affect GTFP. (3) The DE affects GTFP mainly by promoting efficiency progress rather than technological progress. In addition, in regions where government attention to the DE is higher than others, the DE substantially contributes to GTFP. The potential of integrating the DE and the real economy needs to be further tapped. This paper presents pertinent policy suggestions and provides new empirical evidence and valuable reference for promoting green development.

Land revenue and government myopia: Evidence from Chinese cities

While the impact of land revenue has been widely analyzed, there is little empirical research on the impact of land revenue on government planning horizon, especially government myopia. In response, this study investigates the effects of land revenue on local government myopia within the context of the land leasing system in China. Measuring government myopia with textual analysis and machine learning, we empirically test the hypothesis based on a two-way fixed effects model and a series of robustness checks with instrumental variables (IV) in addressing endogeneity. Our results indicate that local governments with larger land revenue tend to be more myopic, and the greater uncertainty of land revenue increases the likelihood of government myopia, with the evidence that local governments prioritize short-term economic growth over long-term investments in social welfare.

Artificial Intelligence and Technological Innovation: Evidence from China’s Strategic Emerging Industries

Artificial intelligence (AI) is the driving force for the leapfrog development of science and technology, the optimization and upgrading of industry, as well as the overall leap in productivity. Using panel data of strategic emerging firms in Chinese A-Share Listed companies from 2012 to 2022, this study empirically examines the impact of AI on technological innovation through a two-way fixed-effects model. The study discovered that technological innovation capability can be greatly enhanced by the degree of AI present in strategic emerging industry businesses. This conclusion remains valid following a series of robustness tests. The mechanism study demonstrates how the degree of AI increases businesses’ capacity for technological innovation by lowering funding constraints and boosting R&D investment. According to heterogeneity analysis, AI has varying empowering effects on different industries within strategic emerging industries. Its strongest empowering effect is observed in the western region, with the central and eastern regions seeing the weakest effects. Additionally, the promotion effect of AI is greater for state-owned enterprises than for non-state-owned enterprises. To better play the role of AI in encouraging the technical innovation of firms in strategic emerging industries, it is required to establish dedicated funds, create an AI technology innovation platform, and develop differentiated regulations.

The Impact of Digital Economy Development on Improving the Ecological Environment—An Empirical Analysis Based on Data from 30 Provinces in China from 2012 to 2021

The rapid progress in science and technology has ushered in a new era of organized and efficient development within the digital economy. China has repeatedly emphasized the need for high-quality development that prioritizes ecological conservation. The central challenge is to balance economic growth with environmental protection, ensuring sustainable development. Understanding the environmental impact of the digital economy is critical for achieving green growth in China. This paper investigates the relationship between the digital economy and ecological protection, using data from 30 provinces and cities in China between 2012 and 2021. Through empirical analysis, including a two-way fixed effect model, mechanism analysis, regional difference analysis, and robustness tests, the study found a significant negative correlation between the digital economy and environmental pollution. This indicates that the development of the digital economy can effectively improve the ecological environment. In the information age, seizing the opportunities presented by the digital economy is crucial. By deepening the digital industry and leveraging digital technologies, China can enhance enterprise production, promote innovation, and create a positive feedback loop between economic development and environmental optimization. However, it is essential to recognize regional disparities in digital economy development and work to narrow these gaps, ensuring balanced and sustainable growth across the country.

Declining number of general practitioners can impair influenza vaccination uptake among Italian older adults: Results from a panel analysis

BackgroundSeasonal influenza vaccination coverage in Italian older adults is insufficient and well below the minimum target of 75%. In Italy, most influenza vaccine doses are administered by general practitioners (GPs), whose number has been declining. In parallel, the number of patients per GP and GP workload increased dramatically, which theoretically may impair vaccination counselling. In this ecological study, we aimed to assess whether influenza vaccination coverage in older adults is associated with the density of GPs having high number of patients.MethodsThe study outcome was the influenza vaccination coverage rate in adults aged ≥ 65 years and registered in 20 Italian regions over the last 23 years. The independent variable of interest was the proportion of GPs with more than 1,500 adult patients, which is an imposed normative ceiling. This latter variable was considered as a proxy of GP overload. By adopting a panel regression approach, different specifications of fixed- and random-effects models were run to assess the association of interest, when adjusted for several social structural, economic and healthcare-related variables.ResultsOver the last two decades, most regions showed a negative association between influenza vaccination coverage rates and the density of GPs with a high number of patients. This latter negative association was confirmed (P < 0.05) in different panel model specifications. In particular, in the fully adjusted two-way fixed-effects model, each 10% increase in the number of GPs with more than 1,500 patients was associated with a 1.7% decrease in influenza vaccination coverage. However, this association was present only in region-years where at least 18% of GPs were deemed overloaded.ConclusionsIn the upcoming years, the number of Italian GPs is projected to decline further. At the same time, the aging Italian population will determine an even greater workload for GPs. This study demonstrated that increased GP workload may partially explain the spatiotemporal variation in influenza vaccination uptake in the Italian elderly. With the imperative of increasing or at least maintaining influenza vaccination coverage rates, several short- and mid-term initiatives should be implemented in order to optimize GP workload during seasonal immunization campaigns.

Towards sustainable development: Can green digital finance become an accelerator for reducing pollution and carbon emissions in China?

As a fusion of financial ''digitalization'' and ''greening'', green digital finance is crucial for ecological quality enhancement. Based on panel data from 285 cities in China spanning 2011 to 2021, this study aims to examine the synergistic impact of Green Digital Finance (GDFO) on Pollution and Carbon Reduction (PCR). The two-way fixed effect model, moderated effect model, and threshold model are employed to study the direct, transmission, and non-linear effects of GDFO on PCR. Results indicate that GDFO significantly enhances PCR in urban areas, and this conclusion remains valid after several robustness tests. Mechanically, encouraging green technology innovation, promoting industrial structure upgrading, and enhancing financial supervision are effective channels for strengthening the impact of GDFO on PCR. At varying levels of green digital finance and financial supervision, the marginal impact of GDFO on PCR exhibits double threshold characteristics in the form of "U-shaped" and "inverted U-shaped". Furthermore, the impact of GDFO on PCR is more pronounced in the eastern and western regions, resource cities, and cities with a high level of financial development, excellent digital infrastructure, and robust environmental regulation. This study offers theoretical support and empirical evidence for deepening the GDFO to promote PCR at the city level.

Corporate credit mismatch, financial leverage and corporate investment efficiency

We empirically test the relationship between credit mismatch and corporate investment efficiency. The study analyzes the heterogeneity of mismatch direction, corporate nature, and corporate life cycle. Results reveal that corporate credit mismatch has a significant negative impact on corporate investment efficiency; corporate financial leverage fully mediates this impact, indicating that corporations may increase their financial leverage to bridge financing gaps in cases of credit mismatch. This practice, however, may bring about greater financial risk and affect corporate investment efficiency. This study provides an important reference for enterprises and financial institutions for optimizing the financing environment, ensuring the effective allocation of financing resources, promoting the sustainable development of enterprises, thereby enhancing overall economic efficiency. This study also provides new ideas and future directions for studying corporate financing and investment behavior.

How Does Fintech Development Affect Financing Constraints of Smes? Evidence From China

Abstract Small and medium-sized enterprises (SMEs) play an indispensable role in China’s economy through making huge contributions to GDP, national employment, financial innovation and government taxation. However, SMEs in China have long faced financing constraints due to their inherent problems, such as financial information asymmetry, immature governance mechanisms, and lack of collateral under the traditional financial system, which have hindered their long-term development. In recent years, financial technology (Fintech) has entered a rapid development track, especially in China, providing new ideas and methods for solving the financing difficulties of SMEs from a technical perspective. In order to examine this, this paper measures the degree of financing constraints through the cash flow sensitivity of cash model and explores how the Fintech development affects financing constraints of SMEs in China and how this impact further communicated to the performance and the risks of SMEs by adopting two-way fixed effects models. The results show that Fintech could alleviate the financing constraints of SMEs. Furthermore, the mediating role of ownership is identified, presenting a better mitigating effect of Fintech on the financing constraints for private SMEs. In addition, both the performance and the risks of SMEs showed the upward single-sided U-shaped relationship with the increase of the Fintech development index, which indicates that Fintech could amplify performance while magnifying the risks of SMEs. The findings of this paper offer an important implication for China that regulatory authorities should consider and balance the financing constraint mitigation effect and risk amplification effect of Fintech.

Bridging the Urban-Rural Gap: The Influence Mechanism of Digital Platform Development on the Urban-Rural Income Gap

Studying the impact of digital platform development on the urban-rural income gap can further clarify the pro-poor and inclusive nature of the digital economy, which is of great significance for bridging the urban-rural divide and promoting common prosperity. This paper uses the panel data of 274 prefecture-level cities from 2015 to 2021 to construct a two-way fixed-effect model to explore the impact and internal mechanism of digital platform development on the urban-rural income gap. The results show that the development of digital platforms can significantly reduce the income gap between urban and rural areas, and the results are robust. The mechanism analysis shows that digital platforms can narrow the income gap between urban and rural areas by promoting the upgrading of industrial structure and narrowing the gap between urban and rural capabilities. Heterogeneity analysis shows that there are still obvious regional differences in the impact of digital platform development on the reduction of urban-rural income gap, and the economically developed regions can give full play to the positive effects of digital platforms. It is proposed that the government should accelerate the construction of rural platform infrastructure and data element market, promote the upgrading of industrial structure, stimulate the supply of internal and external factors, and improve farmers' digital skills to improve farmers' income, thereby narrowing the income gap between urban and rural areas, and formulate differentiated policies to support regional cooperation and achieve high-quality development.

The Effects of Recreational Cannabis Legalization on Recidivism

This paper investigates the effect of recreational cannabis legalization on the chance of returning to prison for ex-offenders. While there have been ongoing debates on the relationship between cannabis and public safety, there is no previous study about how cannabis legalization affects the chance of recidivism for ex-offenders. Using national corrections data between 2006 and 2019, this study employs a difference-in-difference model (Two-way Fixed Effects model, TWFE) using the different timing of cannabis legalization across states. Also, this model adopts an alternative difference-in-difference estimate proposed by de Chaisemartin and D’Haultfœuille to address a potential bias of the traditional TWFE estimate due to the heterogeneous effects of different treatment timings. The results from both models do not imply that cannabis legalization affects the chance of returning to prison within one year after release. The main result holds true for different specifications, including altering the definition of neighboring states or substituting cannabis sales dates for legalization dates. Nor are there effects for subgroups based on ex-offenders’ characteristics.

Outward Foreign Direct Investment and Supply Chain Concentration: Evidence from China

The potential risks arising from excessive supply chain concentration have received more and more attention. In practice, high supply chain concentration hinders firms’ sustainable development, especially for firms in emerging markets. However, how to reduce supply chain concentration remains an underexplored problem. Outward foreign direct investment (OFDI) has been an important strategy for firms to reallocate and optimize their supply chain relationships. Thus, we tried to explore whether OFDI can serve as an effective method to reduce supply chain concentration by analyzing their relationship. Using the data of Chinese A-share listed firms from 2008 to 2022, this paper empirically examines the impact of OFDI on supply chain concentration through a two-way fixed-effects model. We find that OFDI significantly reduces supply chain concentration, and this conclusion still holds after using alternative measures of the independent variable and dependent variable, endogeneity treatment, the Heckman two-stage model test, controlling for provincial factors, and excluding special samples. Channel analysis reveals that OFDI reduces supply chain concentration mainly through increasing market share, enhancing innovation capacity, and improving reputation. Cross-sectional analysis shows that the negative effect of OFDI on supply chain concentration is more pronounced in state-owned firms, firms under high industry competition, and high-tech firms. Our findings have important implications for firms to build sustainable supply chain relationships and strengthen supply chain resilience, and for policymakers to guide OFDI reasonably. Future research could further explore the effect of firms’ investment decisions on supply chain configuration.

Government Environmental Expenditure, Budget Management, and Regional Carbon Emissions: Provincial Panel Data from China

To explore the impact of government fiscal intervention on regional carbon emissions, this paper employs a two-way fixed-effects model to analyze data from 30 provinces in China, spanning the period from 2008 to 2017. This study investigates the effects of local government environmental expenditure and government budget on the per capita volume, intensity, and performance of regional carbon emissions. The results show that government environmental expenditure is beneficial to reducing regional carbon emissions and improving regional carbon emission performance. Second, the smaller the deviation between the government budget and final accounts, the more conducive it is to reducing carbon emissions. Third, we found that government environmental expenditure has the strongest inhibitory effect on regional carbon emissions in the eastern region, followed by the central region, and the weakest in the western region. Finally, government financial transparency positively moderates the inhibitory effect of government budget management on regional carbon emissions, that is, when fiscal transparency is high, the amplification effect of budget deviation on regional carbon emissions is weakened.

Under the Goal of Sustainable Development, Do Regions with Higher Energy Intensity Generate More Green Innovation? Evidence from Chinese Cities

Sustainable development is a global focal point. This study aims to analyze the relationship between energy intensity and green innovation using panel data from 285 Chinese cities spanning from 2003 to 2019. The novel element of this research is the first-time exploration of green innovation through the lens of local industry attributes. It explains the impact of energy intensity on the development of green innovation. By employing a two-way fixed-effect model, the regression analysis reveals that higher energy intensity in cities negatively influences green innovation. Robustness and mechanism tests indicate that in regions with higher energy intensity, governments issue more policies to encourage enterprises and research institutions to pursue green innovation. However, these regions have developed significant path dependence, and local enterprises are reluctant to increase green investment even when facing stringent regulations. Heterogeneity analysis proves that cities with higher levels of digitalization, R&amp;D investment, urbanization, and per capita GDP exhibit an increase in green innovation. The research and findings of this study are of significant importance for policy and strategy formulation, allowing governments and enterprises to develop targeted economic strategies to improve energy efficiency and promote green innovation, thereby achieving sustainable development goals. Potential limitations include data quality, and some key information is difficult to obtain from public sources due to confidentiality, which may result in limitations and biases in the results.

How does inter-provincial trade promote economic growth? Empirical evidence from Chinese provinces

In the face of complex domestic and international situations, the influence of domestic trade on economic growth has been paid more and more attention by the academic community while we still know little about its internal mechanism. From the perspective of China’s inter-provincial trade, based on the panel data of 29 provinces (municipalities and autonomous regions) in China from 2000 to 2021, this paper studies the impact of inter-provincial trade on economic growth by using a two-way fixed effects model. It is found that inter-provincial trade has a significant positive effect on economic growth, and each 1% increase in inter-provincial trade will increase per capita GDP by 0.19%. Furthermore, inter-provincial trade positively affects economic growth through the effect of technology improvement and industrial structure upgrading. However, the two mechanisms are heterogeneous in the eastern, central, and western regions. Among them, the technology improvement mechanism is only established in the central and western regions and the industrial structure upgrading mechanism is only established in the eastern and central regions. Finally, we suggest that governments should formulate targeted development goals and plans according to the actual situation of each region, to ensure that inter-provincial trade can play a full role in promoting economic growth.

Empirical study on the impact of the digital economy on the efficiency of agricultural product circulation under the dual carbon goals

Under the dual carbon goals, it has become an urgent practical issue to enhance the efficiency of agricultural product circulation while reducing environmental damage. This paper first constructs a theoretical model to analyze the relationship between the digital economy, green technological innovation, and agricultural product circulation efficiency. Based on panel data from 29 provinces in China (excluding Hong Kong, Macao, Taiwan, Tibet, and Hainan) from 2015 to 2021, this study utilizes a two-way fixed-effects model and a threshold regression model to analyze the impact of the digital economy on agricultural product circulation efficiency. Meanwhile, the mediating role of green technological innovation is explored in-depth through a mediating effect model. The results indicate that regional heterogeneity exists at the development level of the digital economy and in the efficiency of agricultural product circulation. The digital economy can significantly enhance the efficiency of agricultural product circulation, and green technological innovation plays a mediating role in this process. The impact of the digital economy on agricultural product circulation efficiency exhibits a dual threshold effect, where the promotion effect weakens after crossing two threshold values. Finally, this paper proposes countermeasures based on regional development status, including strengthening the application of the digital economy in agricultural product circulation, promoting green technological innovation, and reducing the thresholds for digital economy development.