Two-way Fixed Effects Model Research Articles

Impacts of ESG Disclosure on Corporate Carbon Performance: Empirical Evidence from Listed Companies in Heavy Pollution Industries

With the increasing severity of global climate change, environmental issues have become a key factor constraining sustainable economic development. Environmental, social, and corporate governance (ESG) is in line with the concept of enterprises’ sustainable development, and it is significant to study the mechanism of ESG disclosure on corporate carbon performance for the low-carbon transformation of enterprises. Based on the panel data of Chinese heavily polluting companies, a two-way fixed-effects model is used to analyze the relationship theoretically and validate the empirical data. It is found that ESG disclosure significantly contributes to corporate carbon performance, and corporate carbon performance will increase by 1.2% for each level of ESG disclosure. A series of robustness tools, such as endogeneity tests, replacement of critical variables, and control variable treatment, further verify that the main findings are robust and reliable. Heterogeneity analysis shows that the growth and ownership attributes of heavily polluting firms can lead to a heterogeneous characterization of the impact of ESG disclosure on firms’ carbon performance. In addition, the institutional environment and media attention moderate the relationship between ESG disclosure and corporate carbon performance. The results of this study provide empirical support for promoting carbon performance in China’s heavy-polluting industries and achieving the “double carbon” goal.

Local government debt and labor income share: Evidence from China.

This study employs a CES production function to construct a theoretical model of labor income share and uses a two-way fixed effects model to test the causal effects of local government debt (LGD) on the labor income share of enterprises. Local government debt governance policies are utilized as exogenous shocks, and a DID (Difference-in-Differences) model is applied for endogeneity testing. The results have passed a series of robustness checks. The findings suggest that LGD decreases the share of firms' labor income. The mechanism analysis suggests that LGD lowers the labor remuneration of residents, the employment of labor in enterprises, and the size of bank loans mainly; while raising the cost of using funds in enterprises. Moreover, this negative effect is more apparent in non-state-owned enterprises, small and medium-sized enterprises, and enterprises with high financing constraints. This study presents new evidence on how the labor income share of enterprises is affected from the perspective by local governments in China. It has important implications for further deepening local government debt governance and achieving common prosperity.

Can a poverty alleviation programme really help vulnerable rural households? Insights from China

ABSTRACT Poverty alleviation through relocation (PAR) is an important component of poverty alleviation programmes and relocates vulnerable rural households from inhospitable areas to help them get out of poverty. To examine the impact of a poverty alleviation programme on rural households’ ability to establish a sustainable livelihood, this article analyzes the influence of PAR on rural households from the perspective of livelihood vulnerability in a two-way fixed effects model. We have found that PAR significantly reduced rural households’ livelihood vulnerability, and the longer the households remained relocated, the stronger the effect. PAR reduced livelihood vulnerability by lowering exposure and increasing adaptive capacity. Moreover, adaptive capacity increased with the relocation time. Finally, the influence of PAR was stronger in rural relocation than urban relocation, but the influence of relocation time was opposite. Given this, the government should improve the construction of the resettlement areas to reduce the risk exposure of the relocated population. Industry and employment assistance need to be implemented to enhance their adaptive capacity. Finally, it’s necessary to promote the social integration of urban relocated households and help them adapt to life in new communities to accelerate the reduction of livelihood vulnerability.

Examining the Effects and Operational Mechanisms of Green Credit on Carbon Emissions in Chinese Regions

The utilization of a green financial system, particularly through the implementation of green credit, plays a pivotal role in fostering environmentally sustainable, low-carbon economic growth and facilitating the transition toward a more ecologically responsible economy. This paper employs a two-way fixed-effects model, utilizing provincial panel data spanning from 2012 to 2020, to investigate the influence of green credit on regional carbon emissions within different regions of China. The results reveal a significant reduction in carbon emissions as a consequence of the green credit program’s implementation. The analysis of the pathway indicates that green credit is instrumental in mitigating carbon emissions by instigating shifts in the energy mix, with evidence suggesting a partial mediating effect. Furthermore, a heterogeneity analysis discovered that the suppressive impact of green credit on carbon emissions is more pronounced in the eastern and western regions of China, while it is less significant in the central and northeastern areas. The implications of this study provide robust evidence in support of the role of green credit in reducing carbon emissions and can serve as a valuable resource for policymakers aiming to promote the expansion of green credit programs and, in turn, contribute to substantial reductions in carbon emissions.

Competitive strategy, development zone policy and firm growth: Empirical evidence from China.

Competitive strategy plays an important role in achieving superior profits, but there is still much to be explored in terms of the effect on firm growth. This study focuses on exploring the relationship between competitive strategy and firm growth in emerging economies. We focus on how the development zone policies moderate this relationship. This study uses a two-way fixed-effect model to analyze data for 527 manufacturing firms listed in China's Shanghai and Shenzhen A-shares from 2012-2021. Our empirical analysis showed that there is a significant positive relationship between low-cost strategy and firm growth and a significant negative relationship between differentiation strategy and firm growth. Compared with national development zones, firms in provincial development zones choose low-cost strategies that are more conducive to growth. Compared with provincial development zones, firms in national development zones choose differentiation strategies that are more conducive to growth. These findings contribute to understanding the mechanisms by which competitive strategy affects firm growth in different regional institutional contexts in emerging economies. The results of the study also have reference value for the government to optimize the development zone policies.

How does outward foreign direct investment affect enterprise green transition? Evidence from China

The international investment literature consistently indicates that enterprises, functioning as pivotal components of the economic system, engage in diversified outward foreign investment activities, thereby catalyzing the transition towards a greener and more sustainable economy and society. Based on the overseas investment data of Chinese listed companies from 2009 to 2019, this paper adopts a comprehensive approach comprising the two-way fixed effects model, propensity score matching technique, and difference-in-differences set up to evaluate the impact of the enterprise's overseas investment quantity and decision-making of host countries on green development. The findings explore that an increase in outward investment quantity facilitates the enterprise's green transition, which withstands robustness testing, including the decomposition of the green transition index, adjustments to the sample timeframe, and exclusion of corporate samples from top-tier cities. Such promoting effects are more pronounced among listed companies investing in low- and middle-income countries, as well as those located in provinces aligned with the Belt and Road Initiative in China. Further, an enterprise's overseas investment decision-making by the proposal of the BRI has exhibited a substantial and enduring enhancement of green development. This discovery underscores a pragmatic trajectory for the enterprise's green transformation, driven by proactive engagement in high-level openness.

Long-term effects of child nutritional status on the accumulation of health human capital

Research on the impact of childhood nutrition on adult health and human capital has been extensively studied in developed countries, but research in China on this topic is limited. Nowadays, for children's nutritional status, while significant progress has been made in addressing childhood undernutrition in China, regional disparities persist, conversely, the prevalence of childhood overweight continues to rise. For adults' health human capital, the burden of chronic non-communicable diseases among Chinese residents is gradually increasing, over 50% of Chinese residents are overweight or obese, with obesity being one of the risk factors for other chronic diseases. Therefore, this study uses national representative data from 1991 to 2015 China Health and Nutrition Survey (CHNS), matched with individual information from their childhood, to examine the relationship between childhood nutrition and adult health human capital. Based on the two-way fixed effects models and logit models, the study finds that childhood nutrition status measured by height-for-age z score (HAZ) significantly and continuously has been influencing adult health human capital measured by height, BMI, self-rated health (SRH), whether have been sick in last four weeks (SH). BMI-for-age z score (BMIZ) significantly and continuously influence adult health human capital measured by BMI, blood pressure, and perceived stress (PS). Among that, this study places special emphasis on the long-lasting effects of late childhood and adolescence (ages exceeding 6) on the progressive height accumulation and sustained presence of elevated blood pressure. In conclusion, reducing childhood overweight and promoting linear growth and development throughout the whole childhood can reduce the future burden of disease on the nation.

The low-carbon transition of China's power sector: Scale effect of grid upgrading

Whether grid upgrading in China, centered on building trans-regional transmission lines, can promote a low-carbon transition in the power sector is controversial. Since there is no precedent to follow, various countries are interested in learning from China's experience. This paper adopts a two-way fixed effects model based on panel data for 30 Chinese provinces from 2007 to 2019 to reveal the nonlinear relationship between grid upgrading and renewable energy generation. The research finds that: (1) A U-shaped relationship exists between grid upgrading and renewable energy generation, which is robust to a series of robustness checks. (2) When the ratio of transmission lines over Extra High Voltage (EHV) exceeds 0.152, grid upgrading has a scale effect in promoting renewable energy generation to achieve a low-carbon transition in the power sector. (3) Building the EHV grid has made a significant contribution to renewable energy generation, particularly in resource-intensive areas. Conversely, building Ultra High Voltage (UHV) grids has not observed such a positive impact. Finally, targeted policy recommendations are put forward for the low-carbon transition of China's power sector.

Inviting oversight: Effects of forest certification on deforestation in the Brazilian Amazon

In the American tropics, logging is almost always highly selective, leaving most of the forest standing and available for future harvest under sustainable forest management. However, forest that has been logged is often more accessible to deforestation agents such as farmers. Thus, areas legally designated for sustainable forest management in reality may be more susceptible to illegal deforestation. Third-party certification of sustainable forest management is one strategy for protecting such forest. In this paper, we estimate the effect of certification by the Forest Stewardship Council (FSC) on deforestation, drawing on data from the years 2001 to 2019. We observe strong selection effects resulting in systematic differences between certified forest areas and other forest areas designated for sustainable forest management, and we find that after controlling for those selection effects, inviting oversight by FSC reduces the probability of deforestation. Our study design compares forests “treated” with FSC certification to “control” forests designated for sustainable forest management but not (yet) certified in the two Brazilian states of Pará and Rondônia. Adopting pixel-based analyses, we first create a matched sample of treated and control pixels and then estimate GLMM models, with two-way fixed effects (TWFE) models as a robustness check.We find that where forest managers have obtained certification and thus invited oversight by FSC auditors, rates of forest loss are lower (although the results are not fully robust across regions). The estimated effects vary across regions, likely due to varying socioeconomic and policy contexts and competing land uses. We conclude that especially in settings of low governance capacity and high deforestation pressure, certification can contribute to long-term forest conservation by reducing deforestation rates.

How exports affect green technology innovation in small- and medium-sized enterprises? Evidence from Chinese companies listed on the growth enterprise market.

Using matched data from China Stock Market and Accounting Research (CSMAR) and Wind databases, this paper explores the impact of exports on the green technology innovation (GTI) of small- and medium-sized enterprises (SMEs). The mechanisms are analyzed through a two-way fixed effects model. First, exports contribute significantly to GTI of SMEs. Second, exports mainly contribute to GTI of SMEs by attracting government subsidies and increasing firms' environmental awareness. Third, from the perspective of heterogeneity, exports significantly positively impact GTI of SMEs especially in medium- and low-technology industries and in eastern China. The impact of exports on GTI is also examined by replacing core variables, modifying the sample for robustness testing, and utilizing both urban river density and distance from the center of the city to the nearest port as instrumental variables for endogeneity test. With the continuous development of international import and export trade, enterprises increase GTI research and development by attracting government subsidies, improving the quality of disclosed information, and increasing environmental awareness.

Does the Digital Economy Promote Industrial Collaboration and Agglomeration? Evidence from 286 Cities in China

Relying on high penetration and strong diffusion capabilities, the digital economy is becoming a new driving force for industrial integration and development. It is of great significance to promote the coordinated development of manufacturing and producer services. This paper took panel data on 286 prefecture-level cities and above in China from 2011 to 2019 as its research object, and used the two-way fixed effect model, threshold effect model, and the Spatial Durbin Model (SDM) as its econometric testing methods. This analysis explored the impact of the digital economy on the synergetic agglomeration between manufacturing and productive service industries in China. The results of the research showed that the synergetic agglomeration of industries is significantly promoted by the digital economy. This conclusion was still valid after an endogeneity test was carried out. The digital economy’s role was found to mainly involve promoting knowledge spillovers and expanding the market size. An in-depth analysis of the digital economy has enabled the collaborative agglomeration of manufacturing and producer services in large, medium-sized, and small cities. The digital economy had the greatest effect on small cities, followed by medium-sized cities and large cities. The synergetic aggregation between the manufacturing and high-end producer services industries is significantly promoted by the digital economy. However, it was not found to have had a significant effect on the synergetic agglomeration between the manufacturing and low-end producer services industries. The impact of the digital economy on industrial collaborative agglomeration is nonlinear. Only when the level of the digital economy exceeds the threshold can the promoting effect of the digital economy on industrial collaborative agglomeration be manifested. In summary, the development of the digital economy was found to have promoted industrial collaboration and agglomeration in the study areas and their neighboring regions in the study period. The research results of this article are of great significance for achieving the goal of the “two-wheel drive” of the manufacturing and producer services industries, as well as high-quality economic development in China.

The impact of household wealth gap on individual’s mental health

BackgroundImproving the individual’s mental health is important for sustainable economic and social development. Although some studies found that household wealth gap may affect individuals’ mental health, few studies have clarified the causal relationship between household wealth gap between mental health in China. This study examines the impact of the household wealth gap on individuals’ mental health using data from the 2012–2018 China Family Panel Survey.MethodsThis study first used the two-way fixed effects model to investigate the impact of household wealth gap on individuals’ mental health. Considering the endogeneity, the two-stage least square and propensity score matching were employed to examine the impact of household wealth inequality on individuals’ mental health.ResultsThe results show that the household wealth gap has negative impact on individuals’ mental health. A series of robustness tests support this conclusion. The results of heterogeneity analysis show that the impact of household wealth gap on mental health is more pronounced among middle-aged and elderly individuals, residents with lower education levels, and rural residents. The results of the mechanism analysis suggest that the household wealth gap may affect individuals’ mental health by influencing the individual’s health insurance investment and neighborhood relations. In addition, the household wealth gap not only significantly negatively affects individuals’ mental health in the short term but also in the medium- to long-term.ConclusionThese findings suggest that the government should take various measures to narrow the wealth inequality between families, which may effectively improve the mental health of residents.

The digital economy and environmental pollution: New evidence based on the support of logistics development

As the world's largest manufacturing and export country, environmental preservation in China has received widespread public attention. Although existing literature has focused on the relationship between the digital economy (DE) and environmental degradation from the supply side, it fails to incorporate the role of logistics and demand side. This study employs two-way fixed-effects model and two-stage least square method (2SLS) to empirically evaluate the emission abatement effect mechanisms of the digital economy under local logistics development for China's 31 provinces from 2015 to 2019, constructing an integrated framework and narrowing the gaps of existing studies. The empirical results suggest that digital economy growth can have an inhibitory effect on pollution emissions, while logistics development has a negative moderating effect on this impact. These conclusions still hold after a series of robustness tests to eliminate the influence of outliers and regionally differentiated policy interference. Mechanism analysis indicates that technological innovation, changes in industrial structure and consumption structure are significant mediating mechanisms, while logistics development provides indispensable support for the above mediation effect. Hence, this study overall implies that to further unleash the potential of emission abatement effect, adequate attention should be given to exerting the advantages of the digital economy and weighing the green transformation of logistics, enhancing the public's sense of environmental happiness worldwide.

The role of renewable energy alliances in enhancing corporate innovation: Evidence from China

The increasing importance of innovation-driven development requires empowering enterprises as the main drivers of innovation in emerging energy technologies. The existing literature primarily emphasizes government support for renewable innovation, with limited research on external collaborations. This paper searches and collects announcements of listed renewable energy companies regarding strategic alliances during 2009–2021 to explore whether renewable energy alliances promote innovation and their mechanism to motivate innovation efforts, using the Two-way Fixed Effects Model. The main results suggest that renewable energy alliances increase innovation output significantly. The mechanism analysis reveals that establishing renewable energy alliances indirectly enhances innovation output via transaction cost savings and alleviates financing constraints. The heterogeneity analysis indicates that factors such as firm ownership, size, knowledge absorption capacity, green investor concerns, and enterprise life cycle significantly impact the innovation incentives from renewable energy alliances. This paper enriches the research on the drivers of renewable energy innovation and provides policy insights for encouraging autonomous innovation in renewable energy enterprises.

The influence mechanism of industrial policies on Chinese companies' cross-border M&A decision-making

This study explored the potential links between Chinese industrial policy and cross-border mergers and acquisitions by Chinese firms from 2009 to 2019. Based on describing China's industrial strategy and evaluating the then-current situation of Chinese enterprises' cross-border mergers and acquisitions, this empirical study constructed a two-way fixed-effect panel model and an intermediate effect model to assess the mechanism of industrial policy's influence on Chinese enterprises' cross-border mergers and acquisitions decisions. The findings were as follows: (1) Industrial policy could promote the implementation of cross-border mergers and acquisitions of Chinese enterprises; (2) By easing financial restrictions, industrial policy could improve firms' access to capital and encourage cross-border mergers and acquisitions. (3) Industrial policies could promote the high political relevance of state-owned enterprises, thus promoting the success of transnational mergers and acquisitions of enterprises. Therefore, it was significant to promote the transformation of industrial policy from subsidy-oriented to performance-oriented and rationally evaluate the risks and benefits of M&A for enterprises to complete cross-border M&A.

The Impact of Differentiated Development of the Digital Economy on Employment Quality—An Empirical Analysis Based on Provincial Data from China

In the context of the digital age, the digital economy, as a new economic model that the Chinese government is currently committed to developing, has played a positive role in driving consumption and creating employment opportunities. However, the differential development characteristics of the digital economy are becoming increasingly evident. The level of digital infrastructure and the application of digital facilities in China’s eastern regions are superior to those in the central and western regions. The increasing level of differential development in the digital economy will further accelerate the cross-regional mobility of labor. For the more developed eastern regions in China, in terms of the digital economy, the ability to empower employment is relatively high, which can create more job opportunities and attract a larger labor force seeking employment opportunities. In contrast, the central and western regions face slower development in the digital economy and relatively insufficient employment-empowering capacity, leading to labor force outflow. Proper cross-regional labor mobility can enhance the efficiency of labor resource allocation. However, excessive labor force mobility can lead to imbalanced labor resource allocation, causing job shortages and reduced employment quality in regions with an excess of labor force, while labor loss regions face labor shortages and talent drain, resulting in a loss of economic vitality in those regions. Therefore, clarifying and addressing the various negative impacts brought about by the differential development of the digital economy are crucial for improving the overall employment quality in the digital economy era. However, there is currently limited research focused on the influence of differential development levels of the digital economy on employment quality. This study delves into the impact of the differential development levels of the digital economy on employment quality and analyzes the underlying mechanisms. Based on panel data from 31 provinces and cities in mainland China from 2011 to 2020, this study uses the entropy method to calculate both the employment quality index and the digital economy index. Building upon the digital economy index, the Gini coefficient of the digital economy development level in various regions in China is calculated using the Gini coefficient formula. Subsequently, a two-way fixed-effects model empirically analyzes the impact of China’s differential development levels in the digital economy on employment quality. The research finds that the improvement in China’s differential development level in the digital economy significantly reduces employment quality. After re-calculating the Gini coefficient and the employment quality index using principal component analysis, it is found that the Gini coefficient of the digital economy still has a significantly negative impact on the employment quality index. After conducting 2SLS regression using instrumental variables, it is confirmed that there is still a significant negative correlation between the Gini coefficient of the digital economy and the employment quality index. According to the regression results, for every 1% increase in the Gini coefficient of the digital economy, the employment quality index will decrease by 0.111% to 0.361%. Through a regression analysis of the mechanism of action, it is found that the industrial structure plays an intermediary role in the impact of the differential development levels of the digital economy on employment quality. The improvement in the differential development levels of the digital economy is unfavorable for the transformation and upgrading of the industrial structure in the central and western regions, as well as the rational development of China’s overall industrial structure, thereby affecting the improvement of employment quality. Based on the above empirical results, the following policy recommendations are proposed: 1. The Chinese government should increase fiscal support for digital infrastructure construction in the central and western regions, continuously narrowing the gap in digital economy development levels between regions. 2. Regional governments in China should actively guide the healthy upgrading of industrial structures based on the actual conditions of each region. 3. In the digital economy era, the government should introduce relevant labor protection and social security policies based on the characteristics of emerging professions to further improve the employment quality of workers in the digital economy era.

Examining the Overall and Heterogeneous Impacts of Urban Spatial Structure on Carbon Emissions: A Case Study of Guangdong Province, China

The variation in the urban spatial structure (USS) has profound impacts on carbon emissions. Studying the relationship between the two can provide guidance for carbon neutrality strategies and the construction of low-carbon cities in China. However, there is currently a lack of comparative research on the different regions within a province. In this paper, the spatiotemporal evolution of the USS and carbon emissions, at five-year intervals from 2000 to 2020, is investigated in 21 prefecture-level cities in Guangdong Province, China, and the overall relationship of the USS to carbon emissions and their spatiotemporal variations are analyzed by using a two-way fixed-effects model and a geographically and temporally weighted regression model, respectively. The results show that, first, over the past twenty years, the scale of cities has continued to expand, with increasing continuity and aggregation in the built-up areas, while the complexity and fragmentation of their shapes have gradually decreased. Second, the gap in carbon emissions between the Pearl River Delta and other regions in Guangdong shows a trend of first decreasing and then increasing, with high values concentrated in the Pearl River Delta region and the city of Shantou in the east. Third, compared to socio-economic factors, the USS has a more direct and pronounced impact on carbon emissions. Urban expansion and the increased complexity of land patches promote carbon emissions, whereas improving urban spatial continuity and compactness can reduce carbon emissions. Fourth, the dominant spatial structure indicators of carbon emissions differ among the regions of eastern, western, and northern Guangdong and the Pearl River Delta. This study proposes spatial optimization strategies for the low-carbon development of cities in Guangdong Province, providing a new perspective for integrating urban layout and emission reduction policies.

The impact of the industrial robots on the employment rate and wages: prospects of circular economy and sustainable development

PurposeThis study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.Design/methodology/approachThe authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.FindingsThe authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.Research limitations/implicationsThe limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.Practical implicationsThis study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.Social implicationsThis paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.Originality/valueThis study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

The impact of the digital economy on inter-city carbon transfer in China using the life cycle assessment model

The haven paradise hypothesis has been widely supported in the international carbon transfer, but there is still a lack of inter-city evidence. The emergence of the digital economy in recent years has introduced unprecedented opportunities and challenges for carbon emissions reduction and carbon transfer. As the world’s largest carbon emitter and a major player in the digital economy, exploring whether the pollution haven hypothesis exists among cities in China and how the digital economy affects inter-city carbon transfer is crucial for countries to optimize their domestic carbon reduction structures. To this end, this paper employs the 2012 and 2015 Chinese Urban Household Survey data alongside input-output tables based on the life cycle assessment method to quantify the inter-city carbon transfer. In addition, the impact and mechanisms of the digital economy on inter-city carbon transfer are explored using the two-way fixed effects model. The results show that 54% of Chinese cities’ carbon emissions come from outside, with third-tier cities bearing high carbon transfer pressures, indicating the presence of the pollution haven hypothesis. The digital economy exacerbates inter-city carbon transfer by promoting market integration and facilitating industrial transfer, and it mainly promotes the transfer of high-intensity carbon emissions to third-tier cities. Considering carbon emission reduction targets, mandatory environmental regulations have strengthened the effect of the digital economy on carbon transfer. Therefore, the Chinese government needs to properly address carbon transfer by improving the collaborative carbon reduction system, enhancing carbon emission reduction efficiency, and accelerating the equitable progress of the digital economy.

Impact of digital trade on regional carbon emissions.

In the context of the dual carbon targets, digital trade brings new impetus to China's economic development to achieve low-carbon emission reduction. This article uses panel data from 30 provinces in China from 2011 to 2020, and uses a two-way fixed effect model to empirically investigate the impact of digital trade development on regional carbon emissions and its heterogeneity. The results show that the development of digital trade significantly reduces regional carbon emissions, and the conclusion is still valid after conducting the robustness tests. Digital trade can reduce regional carbon emissions by exploiting its effects of expanding economic scale, upgrading industrial structure, and promoting green technology innovation. In addition, the carbon reduction effect of digital trade varies due to differences in regions, trade openness, and carbon emission intensity. The carbon reduction effect of digital trade in central and western regions is larger than that in eastern regions, and the effect in inland regions is greater than that in coastal regions. As the degree of trade liberalization increases and carbon intensity decreases, the carbon reduction effect of digital trade will also weaken. The research conclusions have profound practical significance for achieving the carbon neutrality target, effectively addressing climate change, and promoting high-quality economic development.