1. Introduction
The environmental problems caused by global warming have seriously affected the ecological environment and the sustainable development of society. From 2000 to 2019, global carbon dioxide emissions increased by 40%. Therefore, reducing carbon emissions and other harmful gases has become a common goal for all countries to combat climate change [
1]. As the world’s largest CO
2 emitter, China’s emission reduction initiatives have attracted widespread global attention [
2]. China has implemented a series of action plans for the prevention and control of air pollution, resolutely fought the battle against pollution, won the battle to protect the blue sky, and concentrated on overcoming prominent ecological and environmental problems. Among a range of environmental policies, the carbon emissions trading Scheme (CETs) is the most influential. The plan is a major institutional innovation that uses market mechanisms to regulate greenhouse gas emissions and reduce air pollution while facilitating the transition to a green and low-carbon economic development model, contributing to the realization of sustainable environmental goals, and fighting for blue skies [
3,
4].
In 2013, the Chinese government initiated carbon emission trading pilot programs in key regions, including Beijing, Shanghai, Tianjin, Chongqing, Hubei, Guangdong, and Shenzhen. These programs successfully established carbon emission trading markets in the pilot areas and began online trading activities. Subsequently, in December 2016, Fujian Province launched its carbon trading market, marking the country’s eighth carbon trading pilot initiative. From 2017 onwards, the carbon emission trading market has gradually expanded its coverage from pilot areas to encompass the entire nation, with a particular focus on the power generation industry as an entry point for market expansion. By August 2020, the carbon emission market in pilot provinces and cities has expanded to encompass nearly 3000 enterprises across more than 20 industries, including steel, electricity, and cement [
5]. Notably, the national carbon emission trading market was officially launched in July 2021 [
6]. By July 2022, this market had facilitated the trading of 194 million tons of carbon emission allowances, equivalent to a total value of nearly 8.5 billion yuan. Consequently, the CETs have emerged as an indispensable tool in the government’s efforts to regulate and mitigate overall greenhouse gas emissions in China.
As a typical market-based environmental governance policy, the CETs can effectively reduce carbon emissions through market incentives and technological innovation based on the theory of property rights [
7,
8]. Previous literature focused on the construction of DID models to study the effects of CETs on improving energy efficiency [
9], reducing carbon emissions [
10], promoting technological innovation [
11,
12], and controlling air pollution [
13,
14]. However, few studies have explored the spatial effects of CETs on carbon efficiency. Carbon efficiency, which represents the level of productivity achieved at a given level of carbon emissions, serves as a crucial indicator for assessing carbon emission performance. The implementation of the CETs not only influences the carbon emission efficiency within the pilot areas but also has spillover effects on the carbon emissions of neighboring cities, thereby generating spatial dependencies [
15]. This spatial spillover effect manifests itself in the transmission of the promotion or inhibition effect of the CETs on carbon efficiency from one local region to its neighboring regions. However, the traditional Difference-in-Differences (DID) model fails to account for this spatial aspect, potentially resulting in estimation bias. To address this limitation, this study employs a multi-period Spatial Difference-in-Differences (SDID) approach to comprehensively analyze the spatial effects of the CETs and provide a more nuanced understanding of their impact.
The existing literature mainly explores the emission reduction effect of CETs at the provincial level, while there is little literature focusing on the influencing factors of carbon emission efficiency at the city level. More importantly, the second batch of pilot implementation in Fujian in 2016 was taken into account in the model, and there might be deviations in policy evaluation if a single-period DID was adopted. For example, Shao and Zhang (2022) [
16] analyzed the emission reduction effect of CETs based on China’s provincial panel data rather than the city level. Zhang et al. (2020) [
10] tested the effect of CETs on energy and environmental efficiency by using the single-period DID instead of taking the pilot in Fujian in 2016 as the second batch and using the multi-period DID analysis model. We considered the prefecture-level city as the research object and Fujian, the second batch of cities, and used the multi-period SDID model to make the empirical results more accurate and reliable.
In addition, the existing literature has not yet reached a consensus on the influence mechanism of the CETs on carbon efficiency, ignoring the intermediary role of labor resource allocation and green technology innovation in the influence channel. This paper argues that the CETs can effectively promote carbon emission efficiency in the pilot and surrounding areas through two potential channels. Firstly, the implementation of the CETs can reduce the degree of labor mismatch, make the allocation of labor resources more reasonable, and thus promote the improvement of carbon emission efficiency [
17]. Secondly, green technology innovation brought about by the pilot CETs is considered an important driving force for the low-carbon transition [
18,
19].
Therefore, this study uses data from prefecture-level cities in China to construct an SDID model and examine the spatial spillover effect of CETs on carbon emission efficiency. The Moreland index of carbon emission efficiency from 2004 to 2019 is calculated to confirm the presence of spatial correlation in carbon emission efficiency, providing a foundation for the subsequent analysis using a multi-period SDID model to test the spatial spillover effects of multi-batch CETs on carbon efficiency. Additionally, this study employs an intermediary effect model to investigate the potential mediating roles of labor resource allocation and green innovation in the influencing mechanisms.
This paper mainly contributes to the following three aspects: First, this paper considers the first and second batches of pilot cities and explores the spatial spillover effect of CETs on urban total factor carbon emission efficiency (TFCEE) by constructing a multi-period SDID model. Most of the existing literature uses DID to explore its environmental effects while ignoring the spatial spillover effect of CETs. Second, a mediation effect model is constructed with labor resource allocation and green technology innovation as the mediating variables, and the mechanism of CETs on the carbon emission efficiency of the pilot and surrounding cities is further analyzed. Most of the previous studies only discussed the impact of CETs on carbon emissions efficiency but did not deeply explore the channels of their impact on carbon emissions efficiency. Third, this paper uses total factor carbon emission efficiency to measure carbon efficiency. The measurement of carbon emission efficiency mainly uses single-factor carbon emission efficiency. However, the definition of carbon emission efficiency in this paper is to obtain maximum economic benefits and minimum CO2 emissions on the premise that labor, capital, and energy input remain unchanged.
The structure of the paper is as follows:
Section 2 shows the literature review;
Section 3 is the theoretical analysis and research hypothesis;
Section 4, Methods and Data, introduces the research design of the paper;
Section 5 shows the empirical results;
Section 6 is further analysis;
Section 7 summarizes the research conclusions and policy recommendations.
2. Literature Review
Since the European Union established the world’s largest carbon emissions trading market in 2005, scholars have been concerned about its effectiveness in reducing carbon emissions [
20]. Some scholars have proposed that the CETs, as a typical market-oriented environmental governance policy, are more effective than traditional government regulation in carbon reduction. However, due to differences in basic national conditions and technical levels, scholars have yet to reach a unified conclusion on the emission reduction effect of CETs. On the one hand, certain scholars hold the view that the carbon reduction effect resulting from the implementation of CETs is not substantial. For example, Streimikiene and Roos (2009) [
21] studied the carbon emission data of European countries and found that the EU emission trading system has not been able to reduce carbon dioxide emissions at a low cost, and the CETs are not strong in reducing carbon emissions. On the other hand, some scholars believe that the CET policies can effectively achieve carbon emission reduction and improve carbon emission efficiency. For example, Camila et al. (2018) [
22] believe that the CETs have a stronger effect on carbon reduction than the carbon tax and other mechanisms. Zhang and Zhang (2019) [
23] and Shen et al. (2017) [
24] respectively point out at the national and enterprise levels that the implementation of China’s carbon trading pilot policies can effectively promote the emission reduction of the whole country and enterprises. Zhang et al. (2020) [
10] pointed out that the implementation of CETs significantly reduced industrial CO
2 emissions in pilot areas, and the average carbon emission efficiency of China’s seven CETs increased year by year.
Meanwhile, scholars have gradually explored the carbon emission reduction mechanisms of CETs. Lin and Huang (2022) [
20] found that the inhibition effect of carbon emissions is realized through government implementation rather than market mechanisms. Meanwhile, Cai and Ye (2022) [
2] pointed out that CETs can promote low-carbon development by improving the efficiency of low-carbon technologies. Dong et al. (2022) [
13] believed that CETs indirectly affect carbon emissions by improving the innovation level of cities and guiding the location choice of local industries. However, this literature ignores the indirect effects of labor resource allocation and green technology innovation on the influence channels of carbon trading pilot policies on carbon emissions.
In addition, most scholars use the traditional differential method to explore the economic impact of CETs. For example, Zhang et al. (2020) [
10] used the DID method to assess the impact on carbon emissions after the implementation of the CETs in pilot cities and found that in all seven pilot regions of the carbon trading policy, the emission reduction effect of the CETs was significant. Shao and Zhang (2022) [
16] employed the DID method to examine the 31 provinces in China from 2000 to 2015. Their findings indicated that the implementation of CETs in pilot areas effectively led to a reduction in local carbon emissions. However, previous literature focused on the provincial level did not take the two groups of pilot cities into account in the model and ignored the spatial effects of CETs. Since the CETs are implemented gradually in two groups of cities, the traditional DID method is limited in evaluating the policy’s effect. Moreover, the implementation of CETs in a specific region may have spillover effects on the carbon emission intensity of neighboring areas, which the conventional DID model might not adequately capture, leading to potential biases in assessing these effects. To address this limitation, scholars have extensively utilized the Spatial Difference-in-Differences (SDID) model, which combines spatial econometrics with the DID framework, to examine the impacts of various policies. The SDID model allows for the consideration of spatial interactions and dependencies among regions, providing a more comprehensive understanding of the spatial spillover effects of the CETs on carbon emission intensity.
The measurement of carbon emission efficiency in previous literature has predominantly relied on single-factor methods, which may introduce measurement deviations [
25,
26]. To overcome these shortcomings, this study employs the Slack-Based Measure (SBM) model with non-expected outputs to comprehensively evaluate the total factor carbon emission efficiency of 253 prefecture-level cities in China. By incorporating relaxation variables into the objective function, the non-expected SBM model offers a more comprehensive and accurate measurement of carbon emission efficiency. In line with the approach taken by Gao et al. (2022) [
27], this paper extends the SBM model to include carbon dioxide emissions as an undesirable output, thereby capturing a more comprehensive assessment of total factor carbon emission efficiency.
In summary, previous literature has laid a certain foundation for studying the economic effect of CETs, but there are some limitations: First, most of the studies used the seven provinces of the first batch of pilots in 2013, without considering the second batch of pilots in Fujian Province in 2016. So, the traditional single-period DID may lead to inaccurate estimates. Secondly, the spatial spillover effect of CETs on carbon emission efficiency has been largely neglected in the existing literature. Although the implementation of CETs in pilot cities may have repercussions on the carbon emissions of neighboring cities, the spatial dimension of CETs has been largely overlooked. Consequently, the understanding of the spatial spillover effect of CETs on carbon emission efficiency remains limited and requires further scholarly attention. Thirdly, the previous studies did not provide a comprehensive analysis of the impact mechanism of CET policies on carbon emission efficiency, ignoring the mediating role of labor resource allocation and green technology innovation. Fourthly, most of the literature uses single-factor methods to measure carbon emissions efficiency, and few have taken environmental factors into account to measure the total factor carbon emission efficiency.
3. Theoretical Analysis and Research Hypothesis
Based on the inter-regional competition for strategic energy efficiency, the emission reduction effect of CETs implemented in the pilot regions will not only have a demonstration effect on neighboring regions [
28] but will also exert intangible pressure on enterprises in non-pilot regions. Companies in non-pilot regions will monitor their carbon emissions and increase their carbon efficiency to reduce them and avoid high emission costs when they are included in the carbon market in the future [
29,
30]. On the other hand, as an important market-based environmental regulatory instrument, CETs can induce firms to engage in technological innovation, helping firms with carbon quota restrictions reduce their carbon emissions and even gain additional benefits by upgrading their technology. The technological innovations undertaken by firms in these pilot areas may be transferred to surrounding areas, effectively reducing the carbon intensity of non-pilot areas through technology spillovers and contributing to carbon efficiency. However, carbon trading pilot policies may also have negative spatial spillover effects. The implementation of the CETs may increase the cost of excessively carbon-emitting firms in the pilot areas, and surrounding cities may then become potential areas to take over high-carbon industries. The relocation of enterprises with high CO
2 emissions from the pilot area to surrounding regions can potentially lead to an upsurge in carbon emissions within the surrounding cities. This phenomenon poses a challenge to the enhancement of carbon efficiency. Based on the above analysis, we propose the following hypothesis.
Hypothesis 1a: The CETs have a positive spatial spillover effect on the TFCEE of neighboring cities.
Hypothesis 1b: The CETs have a negative spatial spillover effect on the TFCEE of neighboring cities.
The implementation of CETs has the potential to optimize labor resources and effectively improve carbon emission efficiency. By promoting free competition and the unrestricted exchange of resources within trading markets, CET policies facilitate the efficient allocation of resources. One key aspect is the market mechanism of carbon trading, which enables a rational allocation of labor by distinguishing between inefficient and efficient participants. Inefficient players are required to purchase carbon credits from efficient businesses to operate within emission limits. This process of buying and selling quotas allows for the movement of labor capital, leading to a more efficient allocation of resources. Additionally, market-oriented trade promotes labor mobility, allowing labor to flow from sectors with low efficiency to sectors with high efficiency. This reduces labor mismatch and optimizes the allocation of labor resources within the pilot zone, extending to the integration of labor resources in neighboring cities and the optimal allocation of labor resources in neighboring regions [
27]. Therefore, the implementation of CETs can promote the flow of labor resources across regions and reduce labor mismatches. Moreover, the rational allocation of labor resources can also contribute to the reduction of carbon dioxide emissions in the production process of labor-intensive products. It is worth noting that the carbon emissions of intermediate products are closely related to the export volume of labor-intensive products, suggesting that the rational allocation of labor resources may significantly enhance the carbon emission efficiency of local and surrounding cities. Based on the above analysis, we propose the following hypothesis.
Hypothesis 2: The CETs promote TFCEE in the pilot and surrounding cities by optimizing the allocation of labor resources.
Green technology innovation brought about by the CETs is considered to be the key to achieving emission reduction breakthroughs. Both traditional theories and empirical studies emphasize that technological innovation is one of the important factors affecting CO
2 emission efficiency, especially green R&D activities [
31]. The implementation of green technology innovation in enterprises can bring economic and environmental benefits by reducing raw material input and energy consumption. According to the new economic growth theory, different levels of technological progress will lead to regional differences in economic productivity [
32], which will further affect the level of CO
2 emissions. However, the academic circle has not reached a unified conclusion on the emission reduction effect of green technology innovation. On the one hand, green technology innovation can optimize production technology and curb carbon emissions by promoting the progress of cleaner production technology and the efficiency of CO
2 treatment and conversion [
33,
34]. In the meantime, innovations in green technology can effectively increase carbon efficiency by improving the energy efficiency of enterprises in their operations and then curbing carbon emissions by strengthening end-pipe controls [
35,
36]. In addition, the green technology innovation carried out by enterprises in the pilot areas may be transferred to surrounding cities, effectively reducing the carbon emission intensity of non-pilot cities through technology spillover and thus improving carbon emission efficiency. Based on this, we propose Hypothesis 3:
Hypothesis 3: The CETs promote TFCEE in the pilot and surrounding cities by promoting green technology innovation.
The influence mechanism depicted in
Figure 1 illustrates the potential mechanisms examined in this study. The CETs can exert direct effects on the carbon emission efficiency of both the pilot and surrounding cities, which can vary in either positive or negative spatial spillover effects. Furthermore, the CETs may indirectly enhance the carbon emission efficiency of these cities by optimizing the allocation of labor resources and promoting the adoption of green technology innovation. Hence, there exists the possibility of a mediating effect facilitated by labor resource allocation and green technology innovation within the influence channel.
7. Conclusions and Policy Recommendations
This study examines the impact of carbon emission trading policies (CETs) on carbon emission efficiency in a sample of 253 prefecture-level cities in China. Firstly, the findings indicate a significant positive spatial effect and spatial spillover effect of carbon trading policies on the enhancement of carbon emission efficiency. Various robustness tests, such as employing the PSM-DID model and alternative spatial weight matrices, are conducted to validate the robustness of the results. Secondly, a mediating effect model is developed to examine the mediating role. The results demonstrate that CETs can significantly enhance carbon emission efficiency in pilot cities and neighboring cities by optimizing labor resource allocation and promoting the adoption of green technology innovation. Thirdly, regional heterogeneity is explored by categorizing cities into eastern, central, and western regions. The results reveal that the implementation of carbon trading policies exhibits a stronger effect on carbon emission efficiency in the eastern cities compared with the central and western cities.
Based on the above analysis, this study proposes several policy recommendations. Firstly, it is recommended to strengthen and expand the implementation of the carbon trading pilot policy. The results indicate that the policy not only enhances carbon emission efficiency within the cities themselves but also stimulates neighboring cities to improve their carbon emission efficiency. Therefore, the government should establish a unified carbon emission trading system across all pilot cities, enhance the carbon trading mechanism and rules, and lay the groundwork for the broader implementation of CETs. Drawing on the experiences of pilot cities, the scope of policy implementation can be expanded [
50], leading to the establishment of a comprehensive carbon emission trading market nationwide.
Secondly, optimizing the allocation of urban labor resources and promoting green technology innovation are crucial to maximizing the effectiveness of CETs in emissions reduction. Since the carbon trading policy demonstrates the potential to improve emission reduction through labor resource optimization and the advancement of green technology innovation, the government can regulate the flow of labor resources in the carbon trading market by issuing regulations and provisions that ensure rational allocation of labor resources, consequently effectively controlling urban carbon emissions. Additionally, increased funding for green technology innovation in cities and the implementation of incentive policies to encourage enterprises to engage in green technology innovation can be instrumental. By fostering advancements in clean production technology, the efficiency of carbon dioxide conversion can be improved, leading to reduced carbon emissions [
51].
Thirdly, targeted regional emission reduction strategies should be implemented by the government. Given the evident regional imbalance in China’s development, it is essential to acknowledge that the carbon trading pilot policy exhibits the strongest promotion effect on carbon emission efficiency in eastern cities. Consequently, the government should assume a leading role in developing emission reduction strategies specific to the eastern region [
52]. This initiative would stimulate development and progress in the central and western regions, thereby raising the overall carbon emission efficiency level across China.