What is the Relationship of Energy Transition and Green, Low-Carbon, High-Quality? Based on the DID method

1.   Introduction and literature review

In 2015, the 21st United Nations Climate Change Conference adopted the Paris Agreement, in order to keep the increase in average temperature of global below 2°C during the 21st century and limiting warming to 1.5°C over pre-industrial­ized water. To facilitate the execution of Paris Agreement and promote China’s concurrent objectives of achieving peak carbon emissions and attaining car­bon neutrality, transform China’s industrial structure, energy framework, and consumption and production patterns is imperative. This fundamental shift to a green and low-carbon economy necessitates an energy transformation as a critical factor in realizing these dual-carbon goals. Energy transition signifies the evolution of human energy utilization patterns, progressing fr om firewood to coal, then subsequently fr om coal to oil and gas, followed by a shift fr om oil and gas to renewable energy sources, ultimately advancing from carbon-based fuels to carbon-free alternatives. This transformation of the energy system encompasses essential components such as forms of energy, employed technol­ogies, structural changes in energy sources, management strategies, and related aspects. In the energy sector, China has implemented a number of policies designed to achieve the energy system transformation of green and low-car­bon, comprising “the Opinions on Improving the Institutional Mechanisms and Policies and Measures for the Green and Low-Carbon Transformation of Energy” “the 14th Five-Year Plan for a Modern Energy System”, and “the Medium- and Long-Term Plan for the Development of the Hydrogen Energy Industry (2021­2035)”. The report of the 20th CPC National Congress advocates for the further advancement of the energy revolution, encourages the formulation and estab­lishment of a new and renewable energy system, facilitate the low-carbon and efficient use of energy.

In the 4th meeting on the comprehensive deepening of reform, the central government proposed to concentrate on critical field of social and economic pro­gression and to establish a spatial framework for green, low-carbon, and high-qual­ity development (hereafter referred to as G-LC-HQ). The relationship between energy transition and G-LC-HQ has attracted considerable scholarly attention in recent years, leading to the emergence of two primary viewpoints: First, the promo­tion theory, which posits that advancements in new and clean energy can stimulate economic growth and enhance sustainable development. Second, the inhibition theory posits that the energy transition incurs economic costs and suggests that clean energy may not effectively facilitate green and low-carbon development due to various economic and social conditions.

The new-energy model city (hereafter referred to as NEC) represents a significant pilot policy and institutional initiative for China’s energy transition. Panel data spanning the years 2005 to 2020 from 270 prefecture-level cities is utilized in this paper, employs the super-efficient SBM model to measure GTFP for assessing urban G-LC-HQ levels, and applies Difference-in-Differences (DID), models of mediating effect moderating effect to quantitatively evaluate enhancement effects, mechanisms, and heterogeneous influences of the NEC on urban G-LC-HQ. There are three marginal contributions: ®In measuring GTFP, non-expected outputs encompass not only the conventional three waste outputs but also carbon emissions, thereby providing a more comprehensive assessment of urban G-LC-HQ levels. @ By employing green technological innovation and foreign direct investment (FDI) to form mediating variables, along with digital economy as a moderating variable, we investigate the transmission mechanisms and moderating effects of energy transformation on enhancing urban G-LC-HQ, aiming to offer optimized pathways for energy transition in other cities. ® We analyze the heterogeneous impacts of energy transition across different geo­graphical locations, levels of financial development, and environmental system foundations; comprehensively summarizing the experiences of demonstration cities to provide differentiated policy implementation strategies for establishing NECs.

2.    Institutional context, theoretical analysis and research hypotheses

2.1.   Institutional Context

In 2001, China accessed to the WTO, the country has experienced rapid eco­nomic growth, maintaining double-digit GDP growth rates for an extended period. However, this development has been excessively dependent on traditional fossil energy sources—particularly coal—resulting in increased greenhouse gas emis­sions and exacerbating issues such as climate change and environmental pollu­tion. Between 2010 and 2013, haze events occurred consecutively in numerous cities across the country, with widespread and persistent hazy conditions preva­lent during winter in the eastern and central of China. This phenomenon signifi­cantly compromised travel safety and adversely affected residents’ health, posing challenges to the advancement of sustainable economy and society. This captured the attention of government. China has increasingly prioritized the promotion and application of new and renewable energy sources. The report from the 18th Party Congress in 2012 emphasized the need to “facilitate energy production and con­sumption revolution, regulate total energy consumption, support the advancement of energy-saving and low-carbon sectors as well as new and renewable energy sources, and ensure national energy security.” Furthermore, it identified energy transformation and development as a critical component of ecological civilization construction. In 2013, the Third Plenary Session of the 18th Central Committee of the Communist Party of China proposed the concepts of “enhancing the system for energy, water, and land conservation and intensive utilization” as well as “ensuring the market plays a crucial role in energy distribution”. In 2014, General Secretary Xi Jinping put forth a new energy security strategy of “four revolutions and one coop­eration”, revolutions in energy consumption, supply, technology and institutions, and the strengthening of all-round international cooperation.

To establish a resource-conserving and environment-friendly society and accurately handle the relationship among social progress, economic development, resource utilization, and environmental protection, the National Energy Adminis­tration promulgated “The Announcement of the National Energy Administration on the Establishment of NEC (Industrial Parks) List (The First Batch Notice)” in 2014. The announcement compiled the development plans of 81 NECs, mandating the demonstration cities to take sustainable development as the objective, establish the strategy of giving priority to the advancement of renewable energy, make full use of local renewable energy sources including biomass energy, geothermal energy, solar energy, wind energy, etc., and actively facilitate the utilization of all kinds of new energy sources and renewable energy technologies in construction, transportation, heating, power supply of cities, etc., and enhance the renewable energy sources utilization rate. It incorporated new energy construction into urban development planning and annual plans and put forward binding targets. The set percentage of energy substitution targets was completed in 2015 and the construction of NEC with low-carbon, harmonious and sustainable development was expedited.

2.2.    Theoretical analysis and research hypotheses

Energy transition policies are, to a certain extent, binding and guiding, and are characterized by distinct environmental regulation. In the short term, the pres­sure to lim it and phase out production in traditional energy sectors has altered the original production methods of the industries, while giving rise to so-called “brown unemployment” within these industries. Meanwhile, the advancement of new energy sources, coupled with innovations in production processes and equip­ment to support them, has entailed larger production costs for enterprises, reduced enterprise competitiveness, and had a very limited impact on output growth or even been unfavorable to economic growth. However, in the long run, the energy transition is bound to trigger the new energy integration into the traditional energy industry, achieving the substitution and driving the progress of related industries, for instance new energy equipment manufacturing, electric vehicles, new mate­rials, smart grids, and so forth. These industries development rapidly can gener­ate a large number of new employments. At the same time, the energy transition policy offers corresponding financial and technical support to the demonstration city, strengthens the endogenous power of G-LC-HQ, and stimulates enterprises to undertake technological innovation to transform the production process, so that while ensuring the desired output, it can also effectively decrease environmental pollution and carbon emissions.

H1.: The energy transition will promote urban G-LC-HQ.

Energy transition promotes the innovation of urban green technology, which in turn boosts G-LC-HQ. Green technology innovation has dual externalities, namely, technology and environment. Due to the characteristics of “high investment, dif­ficult technology and long return cycle”, it leads to its inherent drawbacks under the market economic system. Therefore, environmental regulation has become a considerable impetus for green technology innovation. Energy transition, as a flex­ible command-based environmental regulation, can facilitate energy technology innovation throughout the energy sector, generating an innovation compensation effect. At the macro level, the advancement, production and transportation of new energy require sophisticated production technologies. Consequently, various types of investment bodies can promote the concentration of talents with high-tech or high-end skills, research and development capital and other innovation factors, thereby enhancing the city’s degree of green technological innovation. At the micro level, the NEC will compel enterprises to adopt green production approaches and undertake green technological innovation through the incentives and constraints imposed by local governments, thereby enhancing the vitality of green innovation.

In the process of China’s high-quality development, the resource environment represents the strategic capital for the development of economic. Green technol­ogy innovation can generate economic value directly, while also alleviating CO₂ and the existence of spatial correlation effects. The introduction of new technologies makes a positive contribution to enhancing production efficiency, reducing costs, expanding market size, providing new employment opportunities, etc., and inject­ing impetus into economic growth. For instance, green technological innovation can transform the manufacturing processes and flows of enterprises, lower the cost of pollution control, and develop green products. It can also significantly mitigate the impact of product production and consumption on the environment, conserve pro­duction resources, and enhance enterprises’ market competitiveness. In accordance with the foregoing analysis, this study advances the ensuing research hypotheses.

H2.: The energy transition can contribute to urban G-LC-HQ by facilitating green technology innovation.

The energy transition attracts FDI, which in turn promotes G-LC-HQ. The exe­cution of the NEC will be straightforwardly associated with attracting FDI about the new energy industry into the region. “NECs Evaluation Indicator System and Explanation (Trial)” stipulates that NECs should meet the conditions that the energy consumption of per-unit industrial added value above the magnitude falls below the “mean level” of the province wh ere they are located, or the decrease in energy consumption per unit above the scale in the Eleventh Five-Year Plan exceeds the mean rate of decrease in energy consumption per unit above the scale of the prov­ince wh ere they are located. Although, in accordance with the “pollution refuge” hypothesis, NECs will encounter greater environmental regulatory pressures under strict target requirements, which will exert a “squeeze effect “ on enterprises closely related to traditional energy sources. However, in the long term, the implementation of the NEC broadens the path for enterprises to reduce energy consumption, low­ers the “environmental cost” for enterprises, facilitates the advancement of low-en­ergy consumption and high value-added enterprises, and enhances the efficiency of energy utilization and attracts more FDI in clean technologies.

Over the past few years, with the intensification of the globalization process, global economic and social development has been unfolding at an unprecedented pace, and one of the notable trends is the growing impact of FDI on national economies. The resource advantages of investors in aspects such as technology, capital, and management experience frequently offer robust support for the eco­nomic growth and progression of the host country, and directly exert an influence on the level of G-LC-HQ of the host country. Specifically, on the one hand, in the view of technological innovation, FDI can enhance the effectiveness of the green economy by stimulating autonomous and imitative innovation to reduce energy consumption and save innovation costs, which in turn generates spillover effects to boost economic development. On the other hand, in the viewpoint of indus­trial structure optimization, FDI inflows can accelerate the optimization and advancement for the industrial structure of the host country, reduce the amount of high-energy-consuming and high-carbon-emitting enterprises, and accelerate the host country’s abilities to enhance environmental quality and raise economic development level. In accordance with the foregoing analysis, this study advances the ensuing research hypotheses.

H3.: The energy transition can facilitate urban G-LC-HQ by attracting FDI.

Amid the advancement of cloud computing, artificial intelligence big data et al., countries across the globe are encountering a profound revolution in informa­tion technology. The digital economy has arisen as a significant engine of the global economy. Different levels of digital economy evolution can bring about different influence on the energy transition in promoting G-LC-HQ. The digital economy has transformed traditional production model, which can realize inter-temporal information processing and data dissemination, and enhance the efficiency of factor allocation such as research and evolution throughout the transformation process of enterprises, thus facilitating the driving impact of energy transforma­tion on urban G-LC-HQ. During the process of energy transition, many small and medium-sized enterprises (SMEs) face pressure to transform and face operational risks, and the advancement of the enterprise digital economy should send out positive signals to talents in other regions, leading to an inflow of talent resources to enhance the degree of enterprise innovation. The advancement of the digital government not only hastens the landing speed of new energy industry projects but also optimizes the regional business environment. The approval time and process for traditional energy companies in their transformation to new energy in new businesses are reduced. The reduction of institutional transaction costs stimulates the innovation vitality of the enterprise. Digital inclusive finance breaks the temporal and spatial limitations of traditional finance and enhances financial services efficiency, thereby being able to broaden the financing channels of the new energy industry and reduce financing costs. The key to energy transforma­tion and upgrading resides in the combination with digital technology, which can be extensively applied to high-efficiency photovoltaic, large-capacity wind power, new energy exploration and exploitation, and complex grid operation and con­trol, etc. Strengthen the upstream and downstream synergetic collaboration of the new energy industry chain to facilitate energy transformation and upgrading through energy digital industrialization, so as to promote the urban G-LC-HQ. In accordance with the foregoing analysis, this study advances the ensuing research hypotheses.

H4.: Digital economy positively regulates the energy transition’s promotion for urban G-LC-HQ.

Although the energy transition can promote urban G-LC-HQ in multiple ways, heterogeneity exists in the effectiveness of policies among cities in different regions due to the variations in regional conditions. Firstly, the influence of energy transi­tion on urban G-LC-HQ may vary significantly among eastern, central, western, and northeastern cities due to dissimilar economic bases, energy structures, and devel­opment orientations. Secondly, the construction of NECs demands a substantial amount of financial support fr om each city. As a result, the NEC effects among cities with diverse levels of financial development are heterogeneous. energy transition, as an environmental regulation, different environmental institutional bases will bring about certain differences in response to policy shocks. In accordance with the fore­going analysis, this study advances the ensuing research hypotheses.

3.    Model Construction and Variable Selection

3.1.   Basic Regression Model

In this paper, the implementation of the policy of creating NECs is utilized as a quasi-natural experiment to investigate the influence of energy transition on the city’s G-LC-HQ using DID. The model is established.

In eq. (1), is an explanatory variable denoting the GTFP of city in year , is a core explanatory variable representing whether or not the innovative NEC is car­ried out in year in region. If the policy is implemented in a certain city, the variable is attributed a value of 1 for the year of implementation and the following years, or else, it is attributed a value of 0; represents a series of control variables repre­senting the effects of year on city in year; and are year fixed effects and city fixed effects, respectively; stands for a random error term; and denotes the coefficients of the constant term and the control variables; and is the coefficient of the core explanatory variables.

3.2.    Variable Measurement and Data Sources

3.2.1. Explained variable: GTFP

We construct a super-efficient SBM-GML model taking non-desired out­puts into account and employ Matlab to measure urban GTFP. Drawing on exist­ing studies, this paper measures inputs fr om three perspectives: labor, capital, and energy. Labor inputs are measured by the employee headcount per unit by the end of the year and the amounts of industrial enterprises above scale. Capital inputs are gauged by fixed asset investment, land supply area for urban construction, and scientific expenditures. Energy inputs are quantified by overall energy consump­tion. Desired output () is measured by real GDP and total social consumption, and non-desired output indicators () are assessed through sulfur dioxide, emissions of wastewater, dust, and carbon dioxide. The model is established as follows:

wh ere p denotes the target efficiency value, n represents the quantity of deci­sion-making (DMU) units, k is DMU being evaluated, each DUM has inputs, s₁ represents the quantity of desired output metrics, s₂ represents the quantity of non-desired output metrics, and is the decision-making unit.

4.    Mechanism analysis

According to H2 and H3, energy transition promotes urban G-LC-HQ through enhancing green technology innovation and FDI. To validate H2 and H3, this study develops a mediation effect model based on the benchmark regression model. Meanwhile, it employs DID of estimation, and the model is defined as follows:

StfP, ⁼ d°⁺ dtdid, ^+йХ, ⁺ ё + Q+d med, ⁼ d? ⁺ d.did, ⁺^Х, ⁺ ё,⁺ +d gtfp, - a₃+b ₃did, + b ₃med_t +d _}X, + ё,+?+d

Wh ere represents the mediating variable, encompassing green technology innovation and FDI. Table 5 presents the estimation results for green technology innovation as a mediating variable. Reg 1 reveals that the coefficient of impact for green technology innovation on GTFP is 0.0151, which is significantly positive at the 5% confidence level, suggesting that green technology innovation can substan­tially enhance urban G-LC-HQ. As shown in Reg 2, the core explanatory variables for green technology innovation passed the significance test at the 5% level, sug­gesting that energy transition can facilitate green technology innovation. The out­comes of Reg 3 presented that the energy transition coefficient is smaller than the coefficient of the baseline regression model. Therefore, green technology innova­tion exhibits a mediating effect and thereby validating H2.

Variable	Regl	Reg 2	Reg3
	GTFP	GTI	GTFP
ET		1.122** (0.473)	0.106** (0.0443)
GTI	0.0151** (0.00627)		0.0129** (0.00635)
Constant	2.884 (2.171)	39.89** (19.09)	3.115 (2-141)
City FE	YES	YES	YES
Year FE	YES	YES	YES
Observations	3111	3160	3111
R2	0.690	0.680	0.692

Table 5. Regression results of the test of the mechanism of the impact of energy transition on the GTFP of cities (green technology innovation)

Note: ***, **, and * denote 1%, 5%, and 10% significance levels; values in paren­theses indicate robust standard errors.

Table 6 presents the estimation outcomes of FDI as a mediating variable. From the results of Reg 1, the effect of FDI on GTFP is significantly positive at the 10% confidence level, suggesting that FDI can contribute to the city’s G-LC-HQ. As shown in Reg 2, the effect of energy transition on FDI was significant at the 1% level, suggesting that energy transition can attract FDI. Reg 3 shows that after con­trolling for FDI, the coefficient of energy transition on GTFP is smaller than that in the baseline regression. Therefore, FDI also has a partial mediating effect, and H3 is verified.

Variable	Regl	Reg 2	Reg3
	GTFP	FDI	GTFP
ET		1.386* (0.741)	0.121*** (0.0418)
FDI	0.00577* (0.00315)		0.00498 (0.00321)
Constant	3.537* (2.079)	-71.84* (36.83)	3.635* (2.019)
City FE	YES	YES	YES
YearFE	YES	YES	YES
Observations	3113	3,165	3,113
R2	0.690	0.797	0.693

Table 6. Regression results of the test of the mechanism of the impact of energy transition on the GTFP of cities (FDI)

Note: ***, **, and * denote 1%, 5%, and 10% significance levels; values in paren­theses indicate robust standard errors

5.    Analysis of moderating effects

The preceding analysis indicates that the digital economy enhances the influ­ence of energy transition on G-LC-HQ, so this study adopts a moderating effect model to analyze the role of the digital economy as a moderator.

In Eq. (8), is the digital economy, and the remaining variables align with those in the baseline regression, which can be used to judge the moderating effect of the digital economy based on the positive and negative coefficients of the inter­action terms between the core explanatory variables and the digital economy and significance. Using eq. 8 to estimate the effect of the digital economy on the energy transition and its implications for the city’s G-LC-HQ. The results of the regression analysis are presented in Table 7. Reg 1 indicates that the impact of the core explan­atory variables on GTFP is significantly positive at the 1% confidence level, after accounting for the level of digital economy development. From reg 2, it is evident that after adding the interaction term between the core explanatory variables and the digital economy again, the effect of the core explanatory variables on GTFP is significantly positive at 10% confidence interval. The interaction term among the digital economy and the core explanatory variables is significant at 5% confidence interval, and the signs of the coefficients for this interaction term are consistent with those of the core explanatory variables, indicating that the digital economy enhances the energy transition in relation to the city’s G-LC-HQ. H4 is verified.

Variable	Reg 1	Reg 2
	GTFP	GTFP
ET	0.118***(0.0433)	0.0679*(0.0397)
Dig	0.0689**(0.0303)	0.0590*(0.0309)
Interaction		0.104**(0.0525)
Constant	3.512*(2.039)	3.457*(2.043)
City FE	YES	YES
Year FE	YES	YES
Observations	3123	3123
R2	0.697	0.698

Table 7. Regression results of the test of the moderating effect of energy transition on GTFP of cities (digital economy)

Note: ***, **, and * denote 1%, 5%, and 10% significance levels; values in paren­theses indicate robust standard errors. The interaction term uses the product of DID and the digital economy.

6.    Research findings and policy recommendations

6.1. Findings

This study utilizes panel data from 270 prefecture-level cities spanning the years 2005 to 2020 to assess the GTFP and evaluate the level of G-LC-HQ in these cities through the application of the super-efficient SBM model. Additionally, the DID, along with mediating and moderating effect models, is employed to quanti­tatively assess the upgrading effect, elucidate the mechanisms of action, and ana­lyze the heterogeneous impacts of energy transition on the G-LC-HQ of cities. The primary findings are as follows: First, the implementation of NEC has significantly enhanced GTFP and fostered G-LC-HQ. Second, green technology innovation and FDI serve as mediating factors. The energy transition enhances urban G-LC-HQ by fostering green technology innovation and attracting FDI. Third, the interac­tion term between the digital economy and energy transition is significantly posi­tive at the 5% confidence level, suggesting that the digital economy can effectively enhance the impact of energy transition on promoting urban G-LC-HQ. Fourth, the energy transition positively influences the G-LC-HQ of cities situated in the western and northeastern regions. The energy transition significantly enhances the G-LC-HQ of cities characterized by high levels of financial development and strong environmental protection priorities, whereas its impact on the G-LC-HQ of cities with low financial development and limited environmental protection prior­ities is not statistically significant.

6.2.   Policy recommendations

First, the government should establish a robust evaluation framework to syn­thesize successful experiences of energy transition in NECs and broaden the scope of these demonstration initiatives. The findings of this study demonstrate that NEC significantly contributes to the enhancement of urban G-LC-HQ, which is critically important for China’s economic transformation and the advancement of ecological civilization. The successes and failures in the execution of NEC should be thoroughly analyzed, with replicable cases developed for extension to additional cities that possess the necessary conditions and capabilities. Simultaneously, it is essential to enhance synergistic linkages and knowledge sharing between demon­stration cities and their neighboring counterparts, as well as to strengthen col­laborative efforts in the new energy sector among cities and enterprises, thereby maximizing the policy impact of NEC construction.

Second, the mechanism analysis presented in this study indicates that energy transition can enhance urban G-LC-HQ by fostering green technological innova­tion and attracting FDI, while the digital economy serves to amplify the upgrading effect of energy transition on urban G-LC-HQ. The government should enhance the long-term monitoring mechanism that integrates incentives and constraints, while intensifying environmental protection efforts and pollution penalties for demonstration cities. Concurrently, it is essential to increase policy subsidies and tax incentives to bolster enterprises’ enthusiasm for engaging in green technologi­cal innovation. Enhance international cooperation in new energy across all dimen­sions, strengthen the construction of digital infrastructure, and facilitate the digital transformation of the energy sector.