Introduction

Since the economic reforms and “opening up” of the Chinese economy, people’s quality of life has greatly improved in China, and rapid social and economic development has occurred. However, in the past, China’s economic development relied more on labour and resource consumption to achieve traditional high-speed growth. With recent changes in demographics, energy depletion, environmental pollution, and other phenomena, there are new challenges related to how to promote the balance between economic problems and economic development to promote China’s sustainable development. The CPC Central Committee’s Proposal for Formulating the 14th Five-Year Plan for National Economic and Social Development and the Long-term Goals for the next Five-Year Period, adopted at the Fifth Plenary Session of the 19th CPC Central Committee, clearly notes that achieving new progress in ecological progress and raising people’s well-being to a new level are the two primary goals in economic and social development during the 14th Five-Year Plan period.(“Proposal of the Central Committee of the Communist Party of China on Formulating the 14th Five-Year Plan for National Economic and Social Development and the long-range Goals for the next five years” 2020).

In the Party’s 20th Congress report in 2022, the concept of “lucid waters and lush mountains are invaluable assets” was once again mentioned. In the face of severe global climate change, China still firmly promotes the transformation to a low-carbon economy. A significant improvement in the ecological environment has been made possible by the suggested notion of green development. Nevertheless, due to the extensive early development mode, green development still has a long way to go. Therefore, environmental research is gradually increasing (Zhang et al. 2021). In this context, studies on triggers for environmental improvement and promoting environmental optimisation have attracted the attention of many scholars (Yang 2022). A critical aspect of national development is the response of local governments and local attention to environmental issues. On the one hand, local governments can actively enhance the environment by means of financial resources or, through policy-guided measures, encourage pertinent firms to realise green upgrading. Several studies have demonstrated that government environmental laws can enhance the environment by driving businesses to adopt green upgrading, bringing professionals together, and lowering the cost of green development (Bi et al. 2023). Additionally, government attention can successfully carry out a significant shift in development focus to strengthen beneficial industries and foster innovation, assisting regions and businesses in promoting the development of an ecological civilisation at a lower cost and with greater efficiency (Qi et al. 2022). On the other hand, given China’s early development and the fact that its businesses rely more on the consumption of people and resources, the government can also strengthen the oversight and management of environmental protection through administrative means and compel businesses to realise energy conservation and emission reduction by creating pertinent laws and regulations. Businesses find it challenging to achieve energy savings, emission reduction, and green upgrading on their own; therefore, government oversight and regulation are necessary. The greatest illustration is the recent advancements in green business (Tu et al. 2021). Thus, one of the most important ways to encourage the optimisation of our environment may be to put the government’s environmental attention into practice.

The underlying mechanism and impact of the government’s environmental emphasis are first examined theoretically in this article. Next, utilising the long difference model based on urban panel data from 2010 to 2020, this study examines the effects, mechanisms for action, and challenges of the government’s environmental emphasis. It takes into account the variations in cities and regions. We also examine how the government’s environmental focus affects the relationship between fiscal pressure and bias. By building fiscal revenue as an instrumental variable, lagging explanatory variables, regulating urban control variables, and removing policy shocks, this work reaches reasonably trustworthy conclusions while taking into account the endogeneity difficulties in the model.

In summary, this study examines how our ecological environment has evolved and progressed from the standpoint of the government’s environmental priorities. The current body of research contributes marginally to the following areas. First, this paper concentrates on the degree to which the government values the environment and its execution, in contrast to the majority of previous studies that concentrate on the environmental advantages of an economic society and particular policies. Second, as an extension of the literature on the benefits of environmental regulation and the effects of technological progress gradually emerging in recent years, based on this perspective, this paper describes the implementation approach and theoretical logic of the government’s environmental attention, which is a supplement to the theoretical framework related to government behaviour and environmental protection. This study concludes by examining potential financial bias and the dynamic that exists between financial pressure and environmental implementation. It examines the reasoning behind the government’s actions in implementing environmental regulations and offers some empirical support for the relevant departments’ decisions.

Literature review and transmission mechanism analysis

Literature review

This section focuses on the attributes of regional green development and examines the challenges and causes that impact it. Additionally, it explores the government’s prioritisation of underlying mechanisms aimed at assisting regions in addressing these issues.

In contrast to broader environmental studies, the level of regional green development provides a more direct means of quantifying the total environmental conditions of a specific area. When considering the efficiency of green development, there is clear geographical variation (Wu and Xu 2023), and the overall efficiency can be summarised as follows: The eastern region is more extensive in terms of green development than the northeastern region is, while the western region is more extensive in terms of green development than the central region is. The efficiency of urban green development may be influenced by factors such as the level of economic growth, the industrial structure, and environmental regulation. Several locations exhibit a noticeable pattern of “low input, low output, and low pollution,” (Zhang et al.)which merits further investigation. When considering regional carbon emissions, the concentrations of population and industries are significant variables contributing to the increase in carbon emissions (Wang et al. 2023). Therefore, efforts to reduce carbon emissions should prioritise investigating and addressing these causes. The majority of recent related research has concentrated on examining the effects of tangible factors such as regional policy, alterations in infrastructure, and the digital economy. However, most of these studies disregard the primary factors contributing to the increase in carbon emissions and strategies for their mitigation. China’s “Three-year Action Plan to Win the Blue Sky Defence War” (Wang et al. 2019) has prompted regional government departments to enhance their regulation of local air pollution sources, resulting in positive social outcomes. However, this effort has also led to some degree of economic growth loss. As is evident from the aforementioned results, many indications can convey distinct attributes. To assess the total level of green development, it is important to consider several indicators of regional green development systems. Moreover, it is important to perform comprehensive research on the tangible effects of economic and social realities and their influencing mechanisms.

Based on the available related research, there has been a longstanding debate on the potential impact of the government, as an administrative entity, on environmental change. Starting with the initial theories of the PHE pollution paradise effect hypothesis and the environmental Kuznets curve (EKC) (Birdsall and Wheeler 1993; R 1990), which focused on the impact of government trade policies on the relationship between free trade and environmental pollution and leading up to recent studies on achieving our “two-carbon” target, it becomes evident that government decisions play a crucial role in driving environmental change (Mani and Wheeler 1998). Sun et al. 2021 employed the Super-EBM model to assess the comprehensive green efficiency of cities at or above the prefecture level in China. The findings indicate that the government’s administrative capacity behaviour has a significant influence on green efficiency. Failure to prioritise environmental protection while solely focusing on economic development will impede green efficiency. In contrast, if the government prioritises environmental protection and focuses solely on developing economic indicators, it will foster green efficiency.

Transmission mechanism

Mechanism 1 denotes the mechanism for overseeing the environment. The government places significant emphasis on the environment through the use of an environmental supervision mechanism, aiming to enhance the enforcement of regional environmental supervision policies. Additionally, environmental control measures incentivise enterprises to fulfil their environmental protection commitments by opting for sustainable and eco-friendly practices. Mechanism 2 illustrates how the government’s emphasis on environmental concerns prompts businesses to invest in green innovation technology, thereby enhancing the technological aspect of regional ecological development. Mechanism 3, on the other hand, pertains to game-like dynamics wherein the government faces a fiscal bias resulting from increased expenditure on environmental protection initiatives. This financial pressure creates a balancing act for the government, necessitating a careful equilibrium between fiscal expenditure and other priorities. Hence, due to financial constraints and biassed fiscal policies, local governments may strategically opt for specific environmental rules and associated technology (Fig. 1).

Fig. 1
figure 1

Implementation mechanism of government environmental emphasis.

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Empirical research design

Measurement model setting

This article establishes the following econometric model to evaluate the execution of the government’s environmental focus:

Assume that the data cover periods a and b, that each period a or b covers n years (n can be 1), and that the individuals involved in the study are denoted as i. (Note: p = a,b)

$${\overline{{\rm{EI}}_{ip}}}=\frac{1}{n}\mathop{\sum}\limits_{t\in p}{{\rm{EI}}}_{{it}}$$
(1)
$${\overline{{\rm{GEI}}_{ip}}}=\frac{1}{n}\mathop{\sum}\limits_{t\in p}{{\rm{GEI}}}_{{it}}$$
(2)

The difference between the two periods was calculated to eliminate the effect that does not change over time. For period a, we assume that there is:

$${\overline{{EI}}}_{{ia}}=\alpha +{\beta }_{1}{\overline{{\rm{GEI}}}}_{{ia}}+{c}_{i}+{\bar{\varepsilon }}_{{ia}}$$
(3)

It is obtained by the difference square decomposition:

$$\begin{array}{cc}{\overline{{EI}}}_{{ib}}-{\overline{{EI}}}_{{ia}} & ={\beta }_{1}\left({\overline{{\rm{GEI}}}}_{{ib}}-{\overline{{\rm{GEI}}}}_{{ia}}\right)+\left({c}_{i}-{c}_{i}\right)+\left({\bar{\varepsilon }}_{{ib}}-{\bar{\varepsilon }}_{{ia}}\right)\end{array}$$
(4)

Finally, the effect of the change in GEI on the change in EI is estimated:

$$\Delta {{\rm{EI}}}_{c}=\alpha +\beta \Delta {{\rm{GEI}}}_{c}+{\gamma}^{\prime} X+{\tau }_{p}+{\varepsilon }_{c}$$
(5)

Despite the ongoing nature of the data, there is sometimes a delay in aligning the government’s environmental focus with its actual environmental performance. Furthermore, fluctuating policies over the years have introduced uncertainty, necessitating the implementation of additional laws to both enhance and reduce annual environmental attention. To address the aforementioned issues, this research employs the long difference model (Acemoglu and Restrepo 2017; Mi et al. 2014). The explained variable \(\Delta {{\rm{GEI}}}_{{\rm{c}}}\) represents the importance of the urban environment. Three typical environmental indicators, regional green efficiency, regional air quality and regional carbon emissions, are selected as the explained variables. Therefore, the following formula can be developed:

$$\Delta {{\rm{EI}}}_{c}=\left\{\begin{array}{c}{GM}{L}_{c}\\ C{arbo}{n}_{c}\,\\ P{M}_{c}\end{array}\right.$$
(6)

The core explanatory variable \({\Delta {\rm{GEI}}}_{{\rm{c}}}\) of this paper represents the environmental importance of city \({\rm{c}}\) by the government, which is expressed according to the word frequency of the local government work report; \({\rm{X}}\) represents a series of control variables. After controlling for factors such as urban characteristics and other policies of the same period, the regression results remain robust. However, considering that there are many influences that lead to changes in explained variables at the city level, it is difficult for a single control variable to cover all of them. Therefore, this paper further adds the provincial fixed benefit \({{\rm{\tau }}}_{{\rm{p}}}\) to absorb unobserved factors at the provincial level to exclude the possible influences of provincial policies and various macro factors; \({{\rm{\varepsilon }}}_{{\rm{c}}}\) represents the error term. To prevent correlation of the error term, the standard error of the regression result is biased. Therefore, the standard errors are clustered at the provincial or city level. \({\rm{\beta }}\) is the core coefficient considered in this paper, and the implementation of the government’s environmental attention can be judged according to the positive and negative coefficients.

Despite the implementation of numerous procedures in the aforementioned econometric model to mitigate the bias induced by missing data, the model nevertheless unavoidably encounters endogeneity issues. City-level factors, such as urban characteristics and local government policy adjustments, can influence the implementation of government environmental attention in ways that cannot be attributed to a causal effect. Additionally, the OLS model may also be susceptible to reverse causation. Given the aforementioned factors, this study implements the following strategies to mitigate internal issues. Initially, during the robustness test, the study takes into account the potential interference resulting from other economic policies implemented during the same period and eliminates any outlier values present in the data. The research posits that the initiation of our environmentally sustainable development approach occurred in 2015, thus necessitating a reduction in the data time window to mitigate interference. In addition, to address the potential estimation bias resulting from reverse causality in the model, the key explanatory variables are delayed by one step, taking into account the government’s limited focus on environmental issues. Finally, fiscal income is leveraged as an instrumental variable when carrying out 2SLS regression to further address endogeneity problems.

Model assumptions

The government’s focus on the environment is crucial for maximising the quality of the regional environment. Increased emphasis can concurrently generate greater policy support and attention in this field (Jalil and Mahmud 2009). Historically, the government has been responsible for establishing our development framework, which plays a crucial role in achieving environmental transformation at the local level. According to the analysis provided, the following hypothesis is proposed:

Hypothesis 1: The government’s emphasis on the environment can guide its tendencies and policies and, thus affecting environmental change.

The government’s environmental focus is most clearly demonstrated through the implementation of stricter environmental policies and enhanced oversight. A significant body of literature has concentrated on the examination of governmental environmental control. Porter (Porter 1991) highlights that implementing suitable environmental standards can stimulate firms to engage in more inventive endeavours. Nevertheless, these advancements will enhance the efficiency of businesses, thus compensating for the expenses of environmental preservation and enhancing the profitability of organisations in the market (Porter and Linde 1995). The domestic and international literature provides evidence to support that idea. Hong’s research (Hong 2008) demonstrates that environmental regulation plays a distinct role in fostering technological innovation within organisations over a significant period of time, hence validating its applicability to China. Albrizio’s analysis (Albrizio et al. 2017) validates the correlation between stringent environmental regulations and the immediate increase in industrial output. Gong (Gong 2018) employed the Super-SBM model to compute and assess the unforeseen efficiency of the green economy in 30 provinces of China. This study concludes that the strength of environmental regulations imposed by local governments also has an impact on the effectiveness of environmental taxes in promoting green innovation.

Hypothesis 2: The government’s emphasis on the environment strengthens regional environmental supervision and encourages enterprises to choose green development, reflected in the “environmental regulation effect.”

A government’s emphasis on the environment can result in the implementation of more laws, increased financial assistance, and enhanced regulations, thereby stimulating corporations to engage in innovation and allocate more resources to science and technology. The correlation between environmental legislation and green innovation has been a topic of extensive discussion for an extended period. Gray (Gray 1987) found through their research that a vital factor hindering green development in China is the problem of technological change. However, as the economy has progressed and our awareness of environmental preservation has deepened, experts have come to recognise the essential role that technology plays in safeguarding the environment. Sun (Sun et al. 2020) discovers that a significant obstacle to China’s green development is the issue of technical transformation. By employing the DDD model, Cui (Cui et al. 2018) discovers that the implementation of the emission trading pilot policy for environmental protection can incentivise firms to develop innovative low-carbon technology. Porter (Jorgenson and Wilcoxen 1990) highlights that well-designed environmental rules not only do not increase expenses but also may stimulate innovation and empower companies to enhance resource efficiency. Dong (Dong et al. 2014) observes that enhancing environmental quality aligns with the trajectory of technological advancement. Enhancing environmental quality will result in a “crowding out” impact on economic productivity, prompting businesses to redirect their focus on technology advancements to meet the demands of environmental quality enhancement. When clean technology reaches a significant level of intensity, there can be a mutually beneficial relationship between environmental quality and economic growth. Yang’s research (Yang et al. 2023) demonstrates that environmental regulations have an impact on the efficiency of carbon emissions from innovative and enhanced green technologies.

Substantial investments in scientific and technological research and development, as well as technical expertise, have a favourable impact on the green development of organisations. The government’s focus on the environment has a compulsory impact on regulating polluting businesses. To minimise pollution emissions, enterprises must enhance their original production technology to foster the rapid advancement of their technological capabilities and encourage sustainable growth. Acemoglu’s research (Daron et al. 2012) reveals that temporary government action can successfully alter the trajectory of technical advancement and environmental conditions. This intervention can also stimulate the growth of a local green economy and encourage businesses to use green technology for sustainable development.

Hypothesis 3: The government’s emphasis on the environment promotes the improvement of local technology levels through increasing scientific and technological investment, which promotes regional green development and transformation and reflects the “effect of technological progress.”

Research has demonstrated that the government has a crucial role in fostering the advancement of environmental conservation. In other words, the government establishes a legally enforceable structure, oversees the establishment of key institutions, and regulates the actions of the primary entities in the market. The current research focuses on the bias of fiscal expenditure towards environmental protection, which aims to foster the advancement of environmental initiatives. However, it also examines the contradiction posed by fiscal pressure, which hinders the progress of environmental undertakings. Wei (Wei and Jiang 2018) argues that green fiscal expenditure can address the issue of ecological environmental externalities and internalise the ecological environment. Hu (Hu and Yang 2022) used panel data from 31 provinces in China from 2007 to 2020 to test the relationships and underlying mechanisms among fiscal environmental protection expenditures, financial pressure, and green development. They find that fiscal environmental protection expenditure has a positive effect on green development, but fiscal pressure has a negative effect on the inhibition of green development. Zhang (Zhang et al. 2019) noted that fiscal pressure may be due to factors such as maintaining the primary livelihood of people and other rigid fiscal expenditures, which leads to skewed support for the green sector. Therefore, fiscal expenditure may be biased towards the application areas with quick results in the short term. Nevertheless, at the expense of green development, areas require continuous support in the long term.

Hypothesis 4: Fiscal bias and fiscal expenditure influence the government’s environmental emphasis, so the importance of implementing an environmental emphasis needs to be balanced.

Construction of main indicators and typical facts

Explained variable

This study investigated the importance of implementing the government’s environmental intervention by using three indicators: urban green efficiency, urban carbon emissions, and urban air quality.

The construction of urban green efficiency refers to Yu’s method (Yu and Ping 2021) and uses the super-efficiency SBM model and the Globe Malmquist–Luenberger index to calculate green total factor productivity. The specific input-output indicators are shown in Table 1.

Table 1 Green total factor input-output.
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When calculating urban carbon emissions, major emission factors such as energy consumption, urban transportation consumption, and urban heat energy should be considered. Therefore, the carbon emissions from gas, natural gas, liquefied petroleum gas, electricity, and heat are weighted to obtain the total carbon emissions of each city. The specific calculation methods for energy consumption and carbon emissions refer to the method of Wu and Guo (Wu and Guo 2016). The measurement of urban air quality needs to consider data availability and comprehensive rationality. Therefore, referring to the method of Cao (Cao et al. 2021), the average annual PM2.5 concentration data of prefecture-level cities in China provided by the Center for Socioeconomic Data and Application of Columbia University in the U.S. are taken as the indices for measuring urban air quality.

Explanatory variable

The prioritisation of environmental protection by prefecture-level city governments can facilitate the establishment of more rigorous environmental policies, thereby fostering the green and sustainable growth of the local economy. These policies should encompass the adoption of clean energy sources, the restriction of pollution, and the advancement of sustainable industry. This study used the technique of word frequency statistics to objectively and fully analyse the text information contained in the work reports of prefecture-level city governments. The aim is to identify the main areas of attention in the government’s work. This study chooses 270 prefecture-level cities to assure the comprehensiveness of the data and to account for discourse analysis. The work reports are categorised into ten categories, each consisting of 125 keywords. These categories include environmental protection, environmental pollution, energy consumption, collaborative development and environmental cogovernance, ecological protection, development concepts, green production, green life, green ecology, and green system construction. Once the keywords are identified, the Python library Jieba, is used to systematically extract the relevant information from 270 government activity reports of prefecture-level cities spanning from 2010 to 2020. By tabulating the word frequency of keywords in Table 2 and removing redundant calculations, the frequency of keywords for each prefecture-level city is summarised and aggregated.

Table 2 Keywords of environmental importance.
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In addition, industrial structure, population density, financial development level and marketization level are also used as control variables in this paper. The proportions of tertiary industry and secondary industry used in the industrial structure and population density data are obtained from the population density indicators of each city in the Statistical Yearbook of Chinese cities. The financial development level is the sum of deposits and loans at the end of the year/GDP. The marketization level is calculated as the city’s general budget expenditure/GDP.

Typical facts about core metrics

Following the initial description and statistical analysis of one independent variable and three dependent variables, we can make the following conclusions. (1) In recent years, particularly after China introduced the idea of green development in 2015, there was a noticeable increase in overall green efficiency, air quality, and the total volume of carbon emissions. Notably, the levels of PM2.5 have been decreasing. Nevertheless, the rate of expansion has decreased, indicating an annual improvement in our environmental quality, with noticeable variations across different regions. (2) The government’s focus on the environment in the selected range has a clear and noticeable upwards pattern. Furthermore, similar to the environmental conditions in China, there was a more pronounced enhancement observed after 15 years. Figure 2 demonstrates a parallel trend between the environmental significance of local governments and the environmental variables of China during the observation year. It is evident that there is a correlation between the two variables, and it is possible to extensively analyse the causal relationship.

To maintain the spatial continuity of the study area and the consistency of the analysis results, this paper fully considers the accessibility of the data. Therefore, the panel data of 270 prefecture-level cities from 2010 to 2020 are selected as samples. The data sources include the China City Statistical Yearbook, the China Statistical Yearbook, and the City Statistical Bulletin.

Fig. 2
figure 2

Trend of green efficiency, carbon emission, air quality and environmental attention.

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Data sources and descriptive statistics

In order to maintain the spatial continuity of the study area and the consistency of the analysis results, this paper fully considers the accessibility of the data. Therefore, the panel data of 270 prefecture-level cities from 2010 to 2020 are selected as samples. Data sources include the China City Statistical Yearbook, the China Statistical Yearbook, and the City Statistical Bulletin.

Descriptive statistics of the main variables are shown in Table 3.

Table 3 Descriptive statistics of panel data.
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Empirical results and analysis

Baseline regression results

Table 4 presents the initial regression findings on the government’s focus on improving urban green efficiency, reducing urban carbon emissions, and enhancing urban air quality. It also indicates the government’s efforts in implementing these environmental initiatives. The baseline regression findings of the government’s emphasis on urban green efficiency, urban carbon emissions, and urban air quality are presented in Columns (1), (4), and (7), respectively. In the model, the fixed effect of provinces is included to eliminate the influence of unobserved characteristics that may be present at the provincial level where the city is situated. This approach is used to avoid mistakenly considering clustering at the province level as the criterion. These findings indicate that the government’s focus on the environment can have a substantial impact on enhancing a city’s ecological efficiency, elevating PM2.5 levels, and ameliorating air quality. However, this approach may also result in heightened carbon emissions. Further deliberation may be needed. This paper conducts regression analysis using four control variables, namely, regional industrial structure, population density, financial development level, and marketization level, in addition to the benchmark regression. This approach is used to account for the potential impact of other city-level characteristics on regional environmental conditions. The regional industrial structure, population density, financial development level, and marketization level results are displayed in Columns (2), (5), and (8), respectively. These results remain statistically significant and have not changed compared to the original coefficients. This study clusters the standard error at the city level, given that all the variables used in the benchmark regression are at the prefecture level. It concurrently manages the predetermined benefits of provinces and the varying characteristics of cities. The results from Columns 3, 6, and 9 are consistent with the baseline regression. The regression coefficients, both positive and negative, remain significant and consistent. Regardless of the inclusion of urban characteristic variables or the utilisation of any arbitrary clustering method, the government’s focus on the environment can enhance green efficiency, air quality, and carbon emission levels. This phenomenon requires additional analysis and deliberation.

Table 4 Baseline regression results: Implementation of environmental importance by the government.
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Robustness test

While this paper’s benchmark regression results attempt to mitigate the issue of missing variables by incorporating province-fixed effects and city-level control variables, it is important to acknowledge that there may still be other urban characteristics or economic and social policies during the same period that could influence the empirical findings. Thus, this paper employs subsequent techniques for robustness testing.

Eliminate interference from concurrent policies

In addition to the government’s environmental concerns, other policies can affect green efficiency and the quality of carbon emissions. (1) Development of the digital economy. The development of a digital economy can improve the green efficiency of cities by eliminating the dividends of the regional industrial structure and adjusting the structure of human capital (Da and Dan 2023). When the regional digital economy is fully developed, it can have a positive impact on the local ecological environment. Therefore, this paper controls the “national big data comprehensive pilot area.” (2) Internet development. On the one hand, the development of the internet can promote the progress of urban green innovation by increasing the number of regional green invention patents (Liu et al. 2022). On the other hand, it can reduce regional transaction costs, which will affect environmental development. In addition, this approach can reduce the search and information communication costs of the carbon trading market, which will affect the regional environment (Bai and Sun 2021). In view of this, this paper selects the “Broadband Pilot in China” as a control. (3) Smart city. Transportation, waste management, energy savings, and the production of alternative performance sources play prominent roles in the development of innovative city pilots. Smart cities can promote the development of urban green innovation by strengthening the informatization level, improving the environmental governance capacity of local governments, and upgrading the human capital structure (Jing and Wu 2022). Therefore, this paper uses as a control the “Smart City Pilot” policy. To control the interference of the above policies in the same period, a virtual index of related policies is constructed. When the city implements the above policies during the sample period, the value is 1. Otherwise, it is 0. The regression results are shown in Table 5.

Table 5 Baseline regression results: Implementation of Government environmental Emphasis (continued).
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In conclusion, this paper uses as controls the policies of the “National Big Data Comprehensive Pilot Zone”, “Broadband Pilot Zone in China”, and “Smart City Pilot Zone” during the same period. As seen from the results in Table 2, the results remain robust after the above interference is eliminated, proving the reliability of the conclusions of this paper.

Eliminating outliers

With a substantial data sample, it is common to encounter outliers, which are data points that deviate greatly from the rest and might disrupt statistical outcomes. This document contains data that have been specifically modified to mitigate the impact of some outlier values on the study. The 1 and 99% markers are used to handle extreme values. Values less than 1% are assigned a value of 1%, while values greater than 99% are assigned a value of 99%. The conclusive outcomes are displayed in Table 6. The regression results for the government’s emphasis on green efficiency, carbon emissions, and air quality are consistent with the previous findings, even after the data have been trimmed, as shown in Table 6. Hence, the data results remain strong and reliable even after the removal of outliers.

Table 6 Robustness test: concurrent policy.
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Shortening the time window

The Fifth Plenary Session of the 18th CPC Central Committee in 2015 introduced the idea of green development, signifying the formal initiation of China’s approach towards environmentally friendly, ecological, low-carbon, and circular development. To minimise the influence of other prospective policies, the data in this research are restricted to only the period following the official establishment of the concept of green development in 2015, hence eliminating any potential interference from other policies. Upon reducing the temporal window, the data in Table 7 remain statistically significant and exhibit consistency with the preceding text, thus indicating the robustness of the results.

Table 7 Robustness test: Concurrent policy.
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Discussion of endogeneity

While the government’s focus on the environment in China demonstrates strong uniformity, this study addresses potential biases by incorporating provincial fixed effects, control variables, and concurrent policies into the regression model to eliminate the influence of city and provincial factors. However, it is important to note that the model may still be susceptible to reverse causality. For instance, the baseline regression analysis reveals a positive link between a government’s focus on environmental issues and urban carbon emissions. This could be attributed to the economic development model, which prioritised high carbon emissions in the initial years, leading to increased government attention towards environmental concerns. The following strategies are implemented to mitigate inherent issues.

The main explanatory variable, government environmental importance, is one of the three explained variables

The three explanatory variables pertaining to the implementation of the government’s environmental focus are challenging to influence throughout the lag period. Hence, by adopting the key explanatory variable with a lag of one period, we prevent the possibility of reverse causation. The regression findings are displayed in Columns (1), (2), and (3) of Table 8. This study concludes that the government’s focus on the environment has a substantial impact on green efficiency, carbon emissions, and PM2.5 levels. This aligns with the coefficient findings from the benchmark regression discussed earlier, confirming the reliability of the results. The above conclusions do not exhibit reverse causality.

Table 8 Robustness test: outliers are eliminated.
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The instrumental variable method is used to further alleviate the endogeneity problem studied

This study employs local government financial revenue as an instrumental variable for 2SLS regression. Government fiscal revenue plays a significant role in determining the extent to which environmental regulations are implemented, as per the correlation theory of instrumental variables. Conversely, the government’s financial revenue has challenges in directly influencing green efficiency, carbon emissions, and air quality. While it may have an influence, its impact is limited to the implementation of environmental issues through fiscal spending. This satisfies the exclusivity hypothesis and serves as a more reliable instrumental variable. Therefore, government fiscal revenue is likely to be utilised as an instrumental variable (Wang and Xia 2023). Columns (4), (5), and (6) in Table 8 present the 2SLS regression results for China’s green efficiency, carbon emission, and air quality, respectively. The government’s environmental focus remains substantial even after incorporating instrumental variables and addressing the issue of endogeneity through exclusion. The regression results align with those presented in the prior paper. Furthermore, these instrumental factors were successfully tested via the Unidentifiable Test and the Weak Instrumental Variable Test, demonstrating their efficacy. To summarise, the study findings of this paper remain strong and reliable.

Dynamic panel - system GMM regression results

Instrumental variables can partially mitigate the issue of reverse causality discussed above, but completely eliminating the endogeneity problems caused by common trends is challenging. Hence, we employed the dynamic panel regression method to further examine the relationships between variables. Additionally, we utilised the system general moment estimation method (System GMM) for parameter estimation.

The three aforementioned variables, namely, green efficiency, carbon emission, and PM value, are dependent variables in the model configuration. The government’s environmental significance is considered the primary explanatory factor, and additional important control variables are included. Hysteresis is included in the explanatory variables to create a dynamic panel, and the results are displayed in Table 9. The outcomes of the three models align with those previously mentioned. All three models have AR(2) test results that exceed 0.1. Additionally, the P-value of the Sargan test is less than 0.1. These findings suggest that there is no longer any autocorrelation in the residual term of the model. As a result, the system GMM estimation results show promise. The findings of this study remain strong, even when considering the need to appropriately address internal issues such as missing variables and two-way causality.

Table 9 Robustness test: Shorten the time window.
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Heterogeneity analysis

The classified samples of cities in different regions of China possess distinct features that reflect the diverse environmental conditions that are governed by the government. These characteristics may vary depending on the specific classifications applied. Thus, this research examines the diversity that arises from varying levels of urbanisation and categorises China into four regions: eastern, central, western, and northeastern.

Urban size heterogeneity

This paper categorises cities into large cities and small and medium-sized cities based on their population size. The classification was performed according to the Notice on the Adjustment of City Size Division Standards issued by the State Council, which defines large cities as those with a population of more than 300 W. According to the above criteria, there are a total of 270 cities, 40 of which are classified as large cities and the remaining 230 as small or medium-sized cities. The data presented in Table 9 demonstrate a significant disparity in the government’s focus on environmental issues across small and medium-sized communities compared to large cities. The regression findings for small and medium-sized cities align with the outcomes of prior studies conducted at the national level. Conversely, the outcomes of large urban areas are not substantial. There are two possible reasons for this phenomenon: either the positive impact of green development in large cities is diminishing early, or the economic growth pressure in these cities is substantial. The policy exhibits a greater inclination towards economic development.

Geographical location heterogeneity

China’s economic and social growth is relatively constant; however, there are distinct geographical variations across the eastern, central, western, and northeastern regions. Resource allocation in the eastern coastal and inland areas varies, resulting in distinct policy inclinations and varying capacities for government execution across regions. Accordingly, the government’s implementation of environmental focus may lead to differences in various regions. Subsample regression is performed based on the province in which the city is located. The findings presented in Table 10 demonstrate that the outcomes observed in the eastern and western regions exhibit greater significance and consistency with the aforementioned conclusions. Conversely, the data obtained from the central and northeastern regions do not reveal any significant findings. Due to its distinctive geographical characteristics, the eastern region exhibits favourable economic growth and effective governmental policies, which contribute to its strong commitment to environmental preservation. The development focus of the western region is primarily on environmental protection and the sustainable development of green resources, with a heightened emphasis.

Table 10 Endogeneity test results.
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Analysis of the mechanism of government emphasis on environmental implementation

Environmental regulation perspective

According to the above literature review and theoretical analysis, environmental regulation is essential for the government to implement environmental policies. On the one hand, improving the environmental regulation intensity of local governments can promote the transformation of the production mode of enterprises and improve the pollution reduction effect. On the other hand, environment regulation also dramatically affects regional green production efficiency progress. Therefore, this paper studies environmental regulation from the perspective of environmental regulation.

Currently, most standard environmental regulation variables in academic circles refer to Zhang’s method (Chen et al. 2021). The frequency of the phrase environmental protection at different prefecture-level cities is selected for research; the three wastes method (Xu and Ma 2023) is used for estimation. Nevertheless, both approaches have the potential to intersect with other factors in this study, potentially causing discrepancies in the outcomes. Thus, this paper examines this underlying mechanism by using environmental penalty statistics from different cities in Peking University’s Talisman over the years as a measure of the strength of environmental regulation. The dependent variable in Table 11 (1) is the statistics on environmental penalties. The coefficient for the government’s environmental attention is found to be significantly positive, suggesting that an increase in the government’s level of environmental attention can lead to a greater intensity of environmental regulation by local governments. To further validate this underlying mechanism by examining the level of environmental regulation over the years, it is observed that the majority of prefecture-level cities experienced an increase in environmental regulation intensity after the Fifth Plenary Session of the 18th CPC Central Committee introduced the concept of promoting green development in 2015. Using 2015 as the reference point, the data were split into two groups for sequential regression analysis. The regression findings for weak and strong environmental legislation are displayed in Columns (2) and (3) of Table 3, respectively. The government’s focus on the environment is not substantial when environmental laws are weak, but it has a notable positive association when environmental rules are robust. The level of government prioritisation of the environment is not substantial when environmental regulations are weak, but it is significantly and positively associated with strong environmental regulations. This demonstrates that in China, enhancing the intensity of environmental regulations can also enhance the environmental consciousness of local governments and increase their focus on the environment through government actions and other methods.

Table 11 Endogeneity test results.
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Technological progress perspective

Technological progress is a crucial method to promote regional green development. The government can enhance regional green development by strengthening support for technological progress in China. The experience of developed countries is sufficient. Many foreign studies discuss the role of government environmental attention in technological progress (Porter 1991). Despite the limited number of relevant studies conducted in China, the theoretical applicability of the government’s emphasis on the environment in relation to technological growth remains valid. Due to the government’s high regard for the environment, regions can benefit from improved conditions and increased support to enhance technological advancements and promote the advantages of green growth. This article uses the number of green inventions, green utility models, and the RD index at the city level as proxy variables to measure technological advancement. A city that has made substantial investments in technology and holds numerous green patents is likely to generate a positive impact on technological advancement. The greater the amount of a city’s investment in research and technology is, the more it can demonstrate its focus on technological advancement. The regression results presented in Table 12 demonstrate a substantial positive relationship between the government’s environmental emphasis and both the number of green patents and the RD index. According to Table 12, a focus on the environment by local governments can enhance the advancement of regional technology and increase attention on technology by cities. This further demonstrates the impact of the government’s environmental focus on technological progress. Technological advancement is crucial for cities to attain environmentally sustainable and economically prosperous development.

Table 12 Heterogeneity of city size.
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Extended analysis

The government’s execution of environmental measures has been analysed previously. Nevertheless, it is necessary to contemplate the reasons behind the government’s failure to implement its environmental focus in specific instances. Based on the aforementioned findings, the government’s focus on the environment has significantly enhanced both green efficiency and air quality, albeit at the expense of higher carbon emissions. In addition, fiscal measures are crucial for local governments to achieve environmental goals and are vital in driving China’s sustainable growth. Nevertheless, the allocation of financial resources has consistently been a crucial aspect of regional development, mostly driven by the financial strain faced by local governments and pressure from economic expansion (Zhe and Tan 2022). Will the government’s prioritisation of the environment change due to economic leaning or financial constraints? Fiscal bias immediately results in a concentrated focus on local development. Nevertheless, local governments will take into account the equilibrium and trade-off between fiscal bias and financial pressure when enacting programmes due to budgetary constraints. The presence of budgetary bias and pressure can help to elucidate the dynamics at play in the government’s execution of environmental policies. This research develops an interaction term that combines the indicators of fiscal bias, fiscal pressure, and the government’s environmental priority. Subsequently, the measurement model is derived as follows:

$$\Delta {{\rm{EI}}}_{c}=\alpha +\zeta \Delta A{{\rm{GEI}}}_{c}\times {D}_{i}+{\gamma}^{\prime} X+{\delta }_{c}+{\theta }_{i}+{\varepsilon }_{{ci}}$$
(7)

One of the variables being analysed is local government finance, which includes two aspects: financial pressure and financial bias. The coefficient of the interaction term is the main focus of this study. The fixed effect of the city remains constant, while the other parts of the model are consistent with the benchmark model established earlier. This paper discusses Tian’s methodology for measuring fiscal bias and financial pressure. (Tian et al. 2021). This research examines the implementation of environmental policies by using the terms “fiscal environmental protection expenditure” or “fiscal general budget expenditure” to represent the concept of fiscal green bias. The financial pressure on local governments is measured by the ratio of revenue to the spending gap in the general public budget.

The key explanatory variable in Column (1) is the interaction between the government’s environmental emphasis and its budgetary bias, as indicated by the results in Table 13. The interaction term coefficient suggests that the government’s focus on the environment will result in a distortion of government financing. A government’s heightened focus on the environment in Column (2) further intensifies the financial burden on local governments. The government’s environmental focus has effectively enhanced green efficiency and air quality while concurrently leading to an increase in carbon emissions. The rationale behind this phenomenon may be easily elucidated. The government places increased emphasis on the green economy and air quality since they are considered crucial elements for driving economic development in the modern day and enhancing the overall living environment. Nevertheless, the prevalence of a high-carbon emission industrial structure remains very widespread in China. Tourism continues to play a significant role in the economic development of our country, contributing substantially to local government tax revenue. Local governments must consider the immediate effects on the economy and tax income (Ma and Xuan 2022), which further supports the diverse outcomes found in the heterogeneity analysis of previous articles (Tables 14–17).

Table 13 Geographical location heterogeneity.
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Table 14 Geographical location heterogeneity (continued).
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Table 15 Mechanism test: Environmental regulation perspective.
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Table 16 Mechanism testing: Technological progress.
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Table 17 Fiscal bias and financial stress.
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Conclusion and policy implications

The government’s focus on environmental issues is crucial for achieving ecological policy creation and promoting green growth in China. This article assesses the execution of the prefecture-level municipal government’s environmental policies and their significant impact based on word frequency data extracted from work reports. The study revealed that the government’s focus on environmental issues has a substantial impact on enhancing regional green efficiency and air quality. This particularly influences the rise in carbon emissions, notably in the eastern and western areas of China. The government’s focus on the environment has two positive effects. First, it leads to stricter local environmental regulations, which in turn promote environmental protection. Second, it encourages the development of and investment in local technology and science, which promotes China’s ecological green development. This demonstrates the clear impact of environmental regulation and technological progress.

According to the results of this extended analysis, the aforementioned circumstance, which results in an increase in carbon emissions, leads to the conclusion that the government’s environmental focus might concurrently amplify its fiscal bias and fiscal pressure, as examined from the standpoint of fiscal bias and pressure. Nevertheless, this necessitates local governments to engage in trade-offs and strike a balance between the two factors during the process of decision-making and execution. The prioritisation of green efficiency and air quality leads to enhanced economic efficiency and a healthier living environment. Nevertheless, the absence of emission reduction will have a detrimental effect on tax revenue and the economy in the immediate term. This phenomenon can be attributed to the varying levels of emphasis placed on environmental concerns by local governments in different regions and cities of varying sizes. Additionally, local governments may exhibit inconsistency in their actions due to the diverse tax burdens resulting from disparities in local economic and social development levels, as well as industrial structures. When assessing green development, local governments will prioritise optimising measures that directly benefit the economy and society.

Conversely, measures such as carbon emissions, which have a greater influence on regional economic growth and are strongly linked to regional industrial composition and financial income, have a lesser effect. Certain places may even tolerate or accept such occurrences in the short term, leading to an increase in carbon emissions within the region. Future studies on this topic should not only continue to examine the impact of elements such as financial pressure and fiscal bias on the government’s attention but also explore the influence of local governments on decision-making related to diversified development. The findings of this study provide valuable insights for the Chinese government in implementing environmental policies and achieving a balanced implementation process. Additionally, these findings have significant policy implications for optimising China’s ecological environment and promoting green sustainable development:

Initially, it was imperative for the government to prioritise the environment and create favourable circumstances to facilitate environmental progress. Undoubtedly, China’s local governments exhibit a greater level of concern towards the environment, and their execution of environmental policies is characterised by a positive outlook. Nevertheless, it is evident from the above analysis that there are substantial variations in the environmental implementation capacity of local governments in China, both at the regional and city levels. Factors such as the regional development level, internal information, and local/regional priorities will greatly impact the extent to which environmental concerns are prioritised and acted upon. Local governments must prioritise environmental concerns and create favourable conditions for local sustainable development. This includes offering enhanced tax incentives to encourage businesses to adopt eco-friendly practices, providing support for businesses to undergo green transformations, and alleviating the challenges faced by local sustainable development.

Furthermore, it is imperative to enhance rational local environmental legislation. This study clearly demonstrates that there is a harmonious relationship between the government’s focus on the environment and the strictness of environmental regulations. Furthermore, a moderate level of emphasis on the environment can successfully enhance the quality of the local environment. Hence, it is crucial for local authorities in China to recognise that the successful implementation of environmental legislation necessitates governmental backing and effective oversight. Local governments must implement corresponding local legislation and regulations in alignment with policies and enhance their environmental management and governance capacities. In addition, it is important to effectively oversee associated sectors through the implementation of comprehensive environmental regulatory measures.

Furthermore, fostering the development of green technology innovation and advancing technical growth are crucial. The rapid development of China’s economy and society has made technological innovation crucial for achieving environmental optimisation and promoting green development. Utilising new technologies can enhance manufacturing efficiency, minimise surplus emissions, and enhance the environment. Alternatively, the combination of cutting-edge technology and creative individuals can foster beneficial collaboration to significantly enhance environmental efficiency. This approach is crucial for efficiently implementing the government’s environmental initiatives and achieving sustainable and eco-friendly growth in the region. Local governments should enhance their support for green innovation research and development and promote widespread green innovation within society through tangible measures such as favourable legislation and incentives for scientific research accomplishments.

Local governments should strive to achieve a balance between fiscal bias and financial pressure and construct a long-term strategic vision that takes into account both economic and social growth. The Chinese government should refrain from engaging in high-polluting and high-emitting industries solely for immediate tax revenue and economic expansion and instead adopt a more forward-thinking approach. Local governments must possess a comprehensive understanding of the significance of environmental conservation and sustainable development. While the fiscal preference for prioritising the environment may result in immediate financial strain, the long-term benefits significantly surpass the drawbacks. China must decisively abandon the development approach of prioritising pollution and addressing it later, and instead adopt the principle of valuing pristine natural resources to foster sustainable local development.