The Mechanism of Low-Carbon Development’s Effect on Employment Quality in Chinese Cities—Based on the Government Perspective

Abstract

The impact of low-carbon development on employment quality is multidimensional. On the one hand, it may enhance employment quality through technological innovation and industrial upgrading; on the other hand, structural adjustments and industrial shifts may adversely affect the development of employment quality. This study uses panel data from 281 cities in China from 2008 to 2022 to construct a model of the mechanisms through which low-carbon development affects employment quality in Chinese cities, with a focus on the role of government in this process. The study finds that fiscal decentralization somewhat weakens the positive impact of low-carbon development on employment quality, while government regulation, by promoting green transformation and optimizing resource allocation, enhances the positive effects of low-carbon development on employment quality. Furthermore, panel threshold effect analysis shows that both fiscal decentralization and government regulation have threshold effects, with threshold values of 0.174 and 59.26, respectively. Once these thresholds are surpassed, the degree of influence on the relationship between low-carbon development and employment quality changes.

1. Introduction

In recent years, “high-quality employment” has appeared in government work reports several times, reflecting the government’s emphasis on improving employment quality and the orientation of future employment policies. As the largest developing country with a large population and high population density, China has a unique employment environment. The differences in regional economic development, supporting industries, and geographical location have led to significant heterogeneity in employment situations. At the same time, climate change issues such as global warming pose a serious threat to human survival. According to the research of the IPCC, high concentrations of carbon dioxide are the main cause. In the past 100 years, the global temperature has risen by about 0.6 degrees Celsius, and extreme weather occurs frequently. Low-carbon development has become an important strategy for the international community to address climate change and promote harmonious coexistence between the economy and the environment.

From the perspective of the government, the impact of low-carbon development on employment is complex and multidimensional. It not only creates employment opportunities and improves employment quality by giving rise to emerging industries and promoting the transfer of the employment structure, but also makes some workers in high-carbon industries face unemployment or retraining, reducing employment quality in the short term and decreasing employment positions in traditional high-carbon industries. Therefore, how to ensure and improve employment quality during low-carbon development and achieve coordinated development between the two has become a key issue that the government urgently needs to solve. Studying the mechanism of the impact of low-carbon development on the employment quality of Chinese cities has important practical significance.

Under the background of globalization, from the government’s perspective, the mechanism of the impact of low-carbon development on the employment quality of Chinese cities presents diverse characteristics. Some studies point out that low-carbon related policies such as carbon tax policies [1], environmental regulations [2,3,4], emission trading policies [5,6] and low-carbon city pilot policies [7,8] can create employment opportunities, optimize the employment skill structure and promote the skill upgrading of the employment market through means such as incentivizing green investment of enterprises, optimizing production processes, improving environmental protection standards and expanding the scale of enterprises. In terms of specific industries and groups, green and low-carbon development provides high-quality employment opportunities for vulnerable groups such as migrant workers, and models such as green manufacturing support the expansion of the labor employment scale of enterprises [9,10]. However, some studies also show that strict environmental regulations may increase the costs of enterprises, reduce production scale, and lead to the reduction in employment positions in specific industries such as high-pollution industries [11,12]. Environmental regulations may also trigger industry transfer, reduce employment quality, sacrifice the employment of groups with low education levels, and the emission trading system has an inhibitory effect on the labor employment of enterprises [13,14,15,16,17,18]. In addition, other studies have found that there are nonlinear relationships such as U-shaped and inverted U-shaped between environmental regulations and the total employment volume, employment structure, employment scale, and high-quality employment, and different nonlinear characteristics also appear in different industries and cities [19,20,21,22,23]. Some studies also hold that the overall impact of some low-carbon development policies such as carbon taxes [24] and support for environmental protection industry policies [25] on the employment market is relatively limited, and there is no significant large-scale impact [26].

2. Theoretical Mechanism

The impact of low-carbon development on employment quality is a complex, multidimensional issue. At the government level, fiscal decentralization and environmental regulation are two important policy tools that, while promoting low-carbon development, have profound effects on employment quality, as illustrated in Figure 1. The implementation mechanisms and pathways of fiscal decentralization and environmental regulation can be explored from multiple perspectives.

2.1. Analysis of the Mechanism of Fiscal Decentralization

Firstly, the impact mechanism of fiscal decentralization on low-carbon development can be traced back to the autonomy of local governments in resource allocation and policy implementation. Fiscal decentralization grants local governments greater fiscal autonomy, enabling them to more flexibly formulate and implement low-carbon development policies that suit local conditions. According to the “Fiscal Federalism Theory,” local governments have inherent advantages in acquiring information and executing policies, allowing them to better identify and meet the needs of local economic development. This advantage helps promote the application of clean energy and energy-saving technologies and can stimulate employment growth in related industries. For example, local governments can create new job opportunities by setting up special funds, offering tax incentives, and attracting enterprises and investors into the low-carbon sector. Therefore, flexible fiscal decentralization policies among governments can potentially lead to a “race-to-the-top” competition. Based on this, the study proposes Hypothesis H1:

H1: 

Fiscal decentralization moderates the relationship between low-carbon development and employment quality.

However, fiscal decentralization can also lead to imbalanced resource allocation and goal deviations. Some local governments may prioritize economic growth in the short term and allocate more funds to traditional high-energy consumption, high-pollution industries, neglecting the long-term potential of low-carbon industries and employment-promoting projects. This misallocation of resources not only slows the creation of high-quality jobs in low-carbon industries but also exacerbates structural contradictions in the labor market, weakening the overall positive impact of low-carbon development on employment quality. Additionally, fiscal decentralization could lead to “race-to-the-bottom” competition among local governments, where some may lower environmental standards and relax regulations to attract investments. This not only undermines low-carbon economic development but may also worsen disparities in employment quality across regions. Based on this, the study proposes Hypothesis H2:

H2: 

The moderating effect of fiscal decentralization has a threshold effect.

2.2. Analysis of the Mechanism of Government Regulation

The government promotes the adoption of cleaner, more efficient production technologies, reduces pollution emissions, and improves resource utilization efficiency by setting carbon emission limits and pollution discharge standards. According to “Externality Theory” and the “Porter Hypothesis,” strict environmental regulations can drive companies to innovate, leading to a win-win scenario for both the economy and the environment in the long term. Government regulations not only help optimize the industrial structure and foster green innovation but also create more high-quality and sustainable job opportunities. For example, the transformation of traditional high-pollution, high-energy industries not only reduces environmental harm but also generates numerous new green industries and job opportunities, offering workers broader career development space and higher salaries. Based on this, the study proposes Hypothesis H3:

H3: 

Government regulation moderates the relationship between low-carbon development and employment quality.

However, government regulation may also have some potential negative effects. On one hand, excessive regulation may cause some high-pollution, high-energy industries to face transformation or shutdown, directly reducing the number of jobs and increasing urban unemployment pressure. As the industrial structure adjusts, the employment structure must also shift, requiring workers to transition from traditional industries to new, green, environmentally friendly sectors. This process involves challenges such as skills matching and retraining, and may result in employment difficulties for some workers due to skill mismatches or age factors. Furthermore, the high skill requirements of emerging green industries may disadvantage low-skilled workers in the labor market, affecting their job quality and income stability. More broadly, government regulation may exacerbate regional economic imbalances. Some regions that depend on high-pollution industries may face greater economic transition pressure and employment challenges, while regions that successfully transition to green economies may attract more job opportunities, further widening the employment gap between cities. Based on this, the study proposes Hypothesis H4:

H4: 

The moderating effect of government regulation has a threshold effect.

In summary, fiscal decentralization and government regulation play different roles in the mechanism through which low-carbon development affects employment quality. While fiscal decentralization grants local governments greater autonomy in resource allocation, it may also lead to imbalanced resource distribution or deviations from the low-carbon development goals, thus weakening the positive impact of low-carbon development on employment quality to some extent. In contrast, government regulation strengthens the positive effects of low-carbon development on employment quality by promoting green transformation, optimizing resource allocation, and creating high-quality jobs. Therefore, it is crucial to appropriately set the intensity and methods of government regulation, balancing environmental protection, economic development, and employment quality, as this is key to achieving sustainable development goals.

3. Materials and Methods

3.1. Data Sources

The data used in this study come from the annual “China Urban Statistical Yearbook,” “China Environmental Statistics Yearbook,” and statistical yearbooks and government bulletins from various cities. The monetary units used in this study are based on constant 2004 prices. An interpolation method is used to address any outliers or missing values in the data.

3.2. Variable Selection

3.2.1. Dependent Variable: Employment Quality

Employment quality (eq): Based on a review of the existing literature on employment quality, this study follows the principles of comprehensiveness, representativeness, availability, and measurability. It constructs an employment quality evaluation index system, which includes 5 dimensions and 24 sub-indicators. Panel data from 281 cities from 2008 to 2022 are analyzed to derive the employment quality index for these cities.

3.2.2. Core Explanatory Variable: Low-Carbon Development

This study defines low-carbon development as the GDP value generated per unit of carbon emission, or carbon productivity. This indicator comprehensively reflects the basic characteristics of energy consumption, emissions, and economic output, and provides a more accurate perspective for the quantitative evaluation of low-carbon development. The study adopts the IPCC’s carbon emission coefficients and calculates CO2 emissions generated by burning major fossil fuels (coal, oil, and natural gas) based on the total energy consumption. The low-carbon development level is then calculated by dividing the regional GDP by the carbon emissions in each city (Formula (1)).

$${Ce}_{it}={\displaystyle \frac{{GDP}_{it}}{{{Co}_2\mathrm{e}\mathrm{m}\mathrm{i}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s}}_{it}}}$$

(1)

where ${GDP}_{it}$ represents the regional GDP of city i in year t.

3.2.3. Moderating and Threshold Variables

Fiscal Decentralization is measured by the ratio of general government fiscal revenue to general government fiscal expenditure. This ratio serves as an important indicator of local governments’ fiscal autonomy and decision-making capacity. It reflects the flexibility and independence of local governments in allocating fiscal resources, which in turn influences their ability and commitment to support specific policies or projects—such as low-carbon technology development, green industry cultivation, and employment promotion initiatives. By comparing fiscal revenues and expenditures, insights can be gained into the government’s policy orientation and implementation priorities, especially in relation to its attention to and investment in the labor market.

Government Regulation is assessed using an environmental regulation indicator. Drawing on existing studies, this paper employs the utilization rate of general industrial solid waste as a proxy for environmental regulation. As a critical tool for addressing environmental pollution and ecological degradation, environmental regulation enforces stringent environmental standards to effectively control industrial emissions, protect public health and ecosystems, and promote sustainable development. At the same time, it facilitates structural adjustments in the economy by encouraging the transformation of high-pollution industries toward low-carbon and green alternatives. This not only enhances industrial competitiveness but also generates high-quality employment opportunities. Furthermore, environmental regulation represents a necessary function of government in fulfilling its public responsibilities and safeguarding citizens’ environmental rights, thus reflecting its commitment to improving public quality of life.

3.2.4. Control Variables

Economic Density: Economic density refers to the economic output per unit of land area, which reflects the concentration and vibrancy of regional economic activity. Regions with higher economic density typically exhibit more robust economic activity and greater production efficiency, which may positively influence employment quality. This study defines economic density as regional gross domestic product/land area of the administrative region.

Industrial Structure: Industrial structure refers to the composition between and within various sectors of the economy. Low-carbon development is often accompanied by adjustments to the industrial structure, such as a shift from traditional high-carbon industries to low-carbon and environmentally friendly sectors. Such transitions may have significant effects on employment quality due to varying demands on labor skills, working environments, and wage levels across different industries. This study defines the industrial structure as the proportion of added value of the primary industry in GDP *1+ the proportion of added value of the secondary industry in GDP *2+ the proportion of added value of the tertiary industry in GDP *3.

Urbanization Level: Urbanization level refers to the proportion of a region’s population that resides in urban areas. Areas with higher urbanization levels tend to have better infrastructure, more abundant public services, and greater employment opportunities, all of which may positively impact employment quality. This study defines the level of urbanization as the permanent urban resident population/the total permanent resident population.

Industrialization Level: Industrialization level reflects the degree and development status of a city’s industrial sector. Low-carbon development is often intertwined with the deepening and transformation of industrialization, such as the shift from high-energy, high-emission industries to green, low-energy industries. This shift may affect employment quality by altering labor demand structures, skill requirements, and workplace environments. This study defines the industrialization level as industrial added value/regional gross domestic product.

Informationization Level: The informationization level reflects the development and application of information technology in a city. With advancements in information technology, informationization has become a key indicator of a region’s modernization. Improvements in informationization may positively affect employment quality by enhancing production efficiency and optimizing management processes. This study defines the level of informatization as (the number of employed people in the post and telecommunications industry in each city/the total population of each city)/(the number of employed people in the national post and telecommunications industry/the total national population).

3.3. Model Setting

3.3.1. Moderating Effect Model

To explore the role of government in the effect of low-carbon development on employment quality, the interaction terms between low-carbon development and fiscal decentralization, and low-carbon development and government regulation are introduced into the model, constructing the following moderating effect models:

$${Eq}_{it}={\beta }_0+{\beta }_1{Ce}_{it}+{\theta }_j\sum X_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(2)

$${Eq}_{it}={\beta }_0+{\beta }_1{Ce}_{it}+{\beta }_2{Czfq}_{it}+{\beta }_3{\left(Ce\times Czfq\right)}_{it}+{\theta }_j\sum X_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(3)

$${Eq}_{it}={\beta }_0+{\beta }_1{Ce}_{it}+{\beta }_2{Zfgz}_{it}+{\beta }_3{\left(Ce\times Zfgz\right)}_{it}+{\theta }_j\sum X_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(4)

where ${Czfq}_{it},{Zfgz}_{it}$ are, respectively, the level of fiscal decentralization and the level of government regulation of city i in year t. The explanations of the remaining variables are consistent with the previous text.

3.3.2. Panel Threshold Effect Model

The impact of low-carbon development on employment quality is multidimensional, and this influence may vary across different stages of low-carbon development. In other words, there may exist a nonlinear and dynamic relationship between the two. To examine whether such nonlinear relationships exist among the variables, this study adopts the panel threshold regression model proposed by Hansen as the analytical tool.

The core idea of this model lies in identifying and estimating one or more threshold variables and their corresponding threshold values. By analyzing the sample data, the model is able to divide the data into distinct intervals and test whether the parameters within these intervals differ significantly.

In this study, the selected threshold variables are fiscal decentralization and government regulation. The panel threshold regression model is specified as follows:

$${Eq}_{it}={\mu }_0+{\mu }_1{Ce}_{it}\times {\rm I}\left(q\le {\gamma }_1\right)+{\mu }_2{Ce}_{it}\times {\rm I}\left(q>{\gamma }_1\right)+{\sigma }_j\sum X_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(5)

In the model, ${\rm I}$(·) denotes an indicator function, which takes the value of 0 when the expression in the parentheses is false, and 1 when it is true. q represents the threshold variable. According to whether the threshold variable q is greater than the threshold value γ_1, the sample interval can be divided into two regions, and the two regions are distinguished by the slope values 1 and 2, and 1 and 2. The definitions of the remaining variables are consistent with those previously described. Similarly, based on the single-threshold model, it is also possible to consider scenarios with multiple thresholds. The two-threshold model is specified as follows:

$${Eq}_{it}={\mu }_0+{\mu }_1{Ce}_{it}\times {\rm I}\left(q\le {\gamma }_1\right)+{\mu }_2{Ce}_{it}\times {\rm I}\left({\gamma }_1<q\le {\gamma }_2\right)+{\mu }_3{Ce}_{it}\times {\rm I}\left(q>{\gamma }_2\right)+{\sigma }_j\sum X_{jit}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(6)

In this case, ${\gamma }_1<{\gamma }_2$, and the estimation process for the two-threshold model is similar to that of the single-threshold model. Specifically, the second threshold value is estimated under the condition that the first threshold value is held fixed.

4. Results

4.1. Analysis of the Mechanism of Low-Carbon Development’s Effect on Employment Quality

4.1.1. Government’s Moderating Effect on Employment Quality

Based on Equations (3) and (4), this study explores the moderating effects of fiscal decentralization and government regulation on low-carbon development’s impact on employment quality. The Hausman test results suggest the use of the fixed effects model. The results of testing the moderating effects of fiscal decentralization and government regulation are shown in

Table 1. Test results of fiscal decentralization and government regulation.

	(1)	(2)	(3)	(4)
	Eq (Total)	Eq (Total)	Eq (Pilot Projects of Low-Carbon Cities)	Eq (Pilot Projects of Low-Carbon Cities)
Ce	0.055 **	0.078 **	0.034 *	0.054 **
Ce*Czfq	−0.146 **		0.277 ***
Ce*Zfgz		0.002 ***		0.001 **
Czfq	−0.167 *	0.596 ***	0.293 *	0.034
Zfgz	0.001 *	0.002 **	0.001	0.010 *
_cons	−0.341 **	−1.303 ***	−0.684 *	−0.686 *
adj. R2	0.8052	0.5268	0.634	0.628
Control variable	Yes	Yes	Yes	Yes
Time effect	Yes	Yes	Yes	Yes
Urban effect	Yes	Yes	Yes	Yes
Sample size	4215	4215	1318	1318

Note: In this article, *, **, and *** respectively indicate significance at the 1%, 5%, and 10% levels.

. During the examination of the government’s moderating role, the interaction between low-carbon development and fiscal decentralization was found to be negative, indicating that fiscal decentralization weakens the positive impact of low-carbon development on employment quality. In contrast, the interaction between low-carbon development and government regulation was positive, showing that government regulation promotes the positive effect of low-carbon development on employment quality.

(1)

There is a negative interaction between low-carbon development and fiscal decentralization, with a coefficient of −0.146, significant at the 5% level. This result indicates that fiscal decentralization, to some extent, weakens the positive effect of low-carbon development on employment quality. The underlying reason may be that, although fiscal decentralization grants local governments greater autonomy in resource allocation, it can also lead to unbalanced resource distribution or deviation from the goals of low-carbon development. Local governments, driven by short-term economic growth considerations, may allocate more resources to traditional high-energy-consuming and high-pollution industries, while neglecting the long-term development potential of low-carbon industries and employment promotion initiatives. This “race to the bottom” phenomenon results in resource misallocation, which not only slows the creation of high-quality jobs in the low-carbon sector but also exacerbates structural contradictions in the labor market, thereby weakening the overall positive impact of low-carbon development on employment quality.

(2)

There is a significant positive interaction effect between low-carbon development and government regulation, with a coefficient of 0.002, significant at the 1% level. This finding indicates that the government, through the implementation of strict and effective environmental regulatory policies, has not only successfully driven the green transformation of industrial structures but also significantly promoted the improvement of employment quality. Environmental regulation policies, by setting clear environmental standards and emission limits, have reduced corporate pollutant emissions and improved resource utilization efficiency. In this process, the green transformation of traditional industries has created new employment opportunities, while a range of emerging industries centered around green and low-carbon development have also emerged. These industries often require highly skilled and highly qualified labor, thereby boosting overall employment quality. Moreover, government regulation has guided the flow of social capital into the low-carbon sector, promoting the prosperity and development of the green job market.

(3)

Further analysis was conducted on the moderating effects of fiscal decentralization and government regulation in low-carbon pilot cities, as shown in columns (3) and (4) of Table 1. The results indicate that fiscal decentralization in low-carbon pilot cities enhances the impact of low-carbon development on employment quality, and government regulation likewise strengthens the effect of low-carbon development on employment quality.

The results indicate that fiscal decentralization and government regulation play different roles in the impact of low-carbon development on employment quality. Fiscal decentralization, due to imbalanced resource distribution or goal deviation, may weaken the positive impact of low-carbon development on employment quality, while government regulation, through promoting green transformation, optimizing resource allocation, and creating high-quality jobs, reinforces the positive impact of low-carbon development on employment quality. These results validate Hypotheses H1 and H3.

4.1.2. Analysis of the Government’s Threshold Effects on Employment Quality

The previous research results indicate that fiscal decentralization and government regulation exert moderating effects on the impact of low-carbon development on employment quality. However, is this moderating effect linear, or does the impact change only after surpassing a certain threshold value? To explore this relationship, this study employs a panel threshold model to analyze the extent to which employment quality development during the process of low-carbon development is influenced by government fiscal decentralization and regulation.

(1)

Threshold Effect Test

Before using the panel threshold model to test for nonlinear relationships, it is first necessary to verify whether threshold effects exist and determine the number of thresholds based on the sample data. After identifying the threshold variables, this study applies the Bootstrap method to simulate the threshold variables, conducting 300 bootstrap replications to test the critical values, and thereby determine the number of thresholds, the threshold intervals, and the specific threshold values (

Table 2. Threshold number test results.

	Threshold Variable	Number of Thresholds	F Value	p Value	10%	5%	1%
					Critical Value Level
Benchmark regression	Fiscal decentralization	One	93.68	0.000	28.455	35.33	49.549
		Two	22.59	0.140	25.426	32.324	42.996
		Three	6.58	0.890	25.65	31.251	41.847
	Government regulation	One	39.11	0.090	28.447	35.123	55.048
		Two	19.5	0.157	23.466	28.279	40.471
		Three	10.68	0.480	29.237	38.889	54.339
Robustness test I	Fiscal decentralization	One	93.94	0.000	25.975	30.281	39.244
		Two	19.36	0.187	25.708	29.394	41.205
		Three	6.54	0.870	24.576	29.984	50.343
	Government regulation	One	5.51	0.060	12.970	15.418	21.679
		Two	8.53	0.197	11.075	12.635	16.399
		Three	5.48	0.590	11.490	13.309	20.350
Robustness test II	Fiscal decentralization	One	72.24	0.000	27.307	36.312	54.577
		Two	21.84	0.143	23.444	29.822	55.654
		Three	22.51	0.333	33.347	39.513	47.460
	Government regulation	One	7.43	0.047	12.469	14.874	21.497
		Two	14.18	0.363	11.905	13.927	19.285
		Three	6.11	0.527	13.703	15.804	21.200

). To enhance the robustness of the baseline findings and to address potential endogeneity issues inherent in nonlinear models, this study also conducts two robustness tests. First, all the variables in this study were subjected to a 1% tailing process to eliminate the influence of outliers on the research results and conduct a robustness test I. Second, the study uses the lagged value of low-carbon development (L.Ce) as an alternative indicator for Robustness Test II. The results of these robustness tests further corroborate the findings of the baseline model.

According to Table 2, when fiscal decentralization is taken as the threshold variable, the F-statistics for the two-threshold and three-threshold models are not significant, whereas the single-threshold model passes the 1% significance level test, indicating that there exists a single-threshold effect of fiscal decentralization in the relationship between low-carbon development and employment quality. Similarly, when government regulation is selected as the threshold variable, the F-statistics for two thresholds and three thresholds are also insignificant, but the single-threshold model passes the 10% significance level test, confirming a single-threshold effect of government regulation in the same relationship. As shown in

Table 3. Threshold estimation results.

	Threshold Variable	Threshold	Threshold Value	95% Confidence Interval
Benchmark regression	Fiscal decentralization	Threshold 1	0.174	(0.167, 0.181)
	Government regulation	Threshold 1	59.26	(55.745, 60.44)
Robustness test I	Fiscal decentralization	Threshold 1
	Government regulation	Threshold 1	46.39	(37.760, 48.310)
Robustness test II	Fiscal decentralization	Threshold 1
	Government regulation	Threshold 1	66.980	(59.910, 68.970)

the estimated single threshold value for fiscal decentralization is 0.174, and for government regulation, it is 59.26.

According to the principles of the threshold model, the estimated threshold value corresponds to the point at which the likelihood ratio statistic (LR) approaches zero. Figure 2a presents the likelihood ratio function for the fiscal decentralization single threshold under the 95% confidence interval, while Figure 2b shows the corresponding function for government regulation. The minimum point of the LR statistic indicates the actual threshold value, and the dashed line represents the critical value of 7.35. Since the critical value of 7.35 is significantly greater than the threshold value, it can be concluded that the estimated threshold values are real and valid.

(2)

Threshold Effect Analysis

The regression results for the panel threshold effect are shown in

Table 4. Threshold effect estimation results.

Variable	Benchmark Regression		Robustness Test I		Robustness Test II
	(1)	(2)	(3)	(4)	(5)	(6)
Ce(Czfq ≤ ${\gamma }_1$)	−0.505 ***		−0.027 ***		−0.580 ***
Ce(Czfq > ${\gamma }_1$)	0.037 *		0.042 *		0.021 *
Ce(Czfq ≤ ${\gamma }_2$)		0.121 ***		0.117 ***		0.119 ***
Ce(Czfq > ${\gamma }_2$)		0.045 **		0.060 ***		0.058 ***
Coefficient	−0.017 *	−0.672 *	−0.280 *	−0.653 ***	−0.075 *	−1.170 ***
adj. R2	0.498	0.489	0.380	0.474	0.504	0.598
Control variable	Yes	Yes	Yes	Yes	Yes	Yes
Time effect	Yes	Yes	Yes	Yes	Yes	Yes
Urban effect	Yes	Yes	Yes	Yes	Yes	Yes
Sample size	4215	4215	4215	4215	4215	4215

Note: In this article, *, **, and *** respectively indicate significance at the 1%, 5%, and 10% levels.

, and the details are as follows:

(1) The impact of low-carbon development on employment quality varies across different intervals of fiscal decentralization (Czfq). When the threshold variable fiscal decentralization Czfq ≤ 0.174, fiscal decentralization suppresses the development of employment quality; whereas when Czfq > 0.174, fiscal decentralization promotes the development of employment quality.

Specifically, when the threshold variable Czfq ≤ 0.174, the coefficient of the impact of low-carbon development on employment quality is −0.505, and it is significant at the 1% level. This result indicates that when fiscal decentralization is below 0.174, it inhibits the development of employment quality. This may be due to the fact that with relatively centralized fiscal resources, local governments face financial constraints and limitations in policy implementation when promoting low-carbon development, resulting in the positive effects of low-carbon projects on the labor market not being fully realized, and even potentially leading to negative impacts due to resource misallocation.

However, when the threshold variable Czfq > 0.174, the coefficient of fiscal decentralization’s impact on employment quality becomes 0.037, significant at the 10% level, indicating that fiscal decentralization at this stage promotes the development of employment quality. This suggests that as local governments’ fiscal autonomy increases, they have greater capability and motivation to promote the development of low-carbon technologies and industries, thus facilitating employment structure optimization and the improvement in employment quality. Fiscal decentralization effectively encourages positive interaction between low-carbon development and employment quality by stimulating local governments’ initiative and innovation vitality.

It is worth noting, however, that although the coefficient changes from negative to positive, the level of statistical significance drops from 1% to 10%. This might indicate that as fiscal decentralization continues to deepen, other factors—such as market mechanisms and policy coordination—begin to play more important roles, thereby partially diluting the direct effect of fiscal decentralization on the relationship between low-carbon development and employment quality.

The above findings indicate that there is a threshold effect in the moderating role of fiscal decentralization, thereby validating Hypothesis H2. Properly managing the degree of fiscal decentralization and establishing an effective coordination mechanism between the central and local governments are crucial for achieving the dual goals of advancing low-carbon development and improving employment quality.

(2) When the threshold variable government-regulated Zfgz is ≤59.26, the impact coefficient of low-carbon development on employment quality is 0.121, and it is significant at the 5% level. When the threshold variable Zfgz > 59.26, the influence coefficient of government regulation on employment quality is 0.045, and it is significant at the 1% level. After exceeding the threshold value, low-carbon development will still promote the improvement of employment quality, but to a lesser extent.

This might be because as the intensity of government regulation further increases, other factors such as market regulation mechanisms and the innovation vitality of enterprises may be restricted to a certain extent, thereby weakening to some extent the direct promoting effect of low-carbon development on employment quality. This change may stem from the fact that government regulations, in the early stage, guided resources to be allocated to low-carbon fields, encouraged technological innovation and industrial upgrading, effectively promoting the improvement of employment quality. However, when the intensity of government regulation is too high, it may trigger the side effects of excessive market intervention, such as increasing the operating costs of enterprises and suppressing market flexibility, which to a certain extent offsets the positive impact of low-carbon development on employment quality.

The above indicates that the regulatory effect of government regulation has a threshold effect, verifying H4. Reasonably setting the intensity and approach of government regulation and balancing the relationship among environmental protection, economic development and employment quality are the keys to achieving the sustainable development goals.

4.2. Heterogeneity Analysis of the Mechanism

Based on the classification standards for resource-based cities outlined in the National Sustainable Development Plan for Resource-based Cities (2013–2020) issued by the State Council, this study conducts a heterogeneity analysis of the threshold effects across different types of resource-based cities. The results are shown in

Table 5. Estimation results of threshold effect of different types of resource-based cities.

	Non-Resource-Based	Growth-Oriented	Mature	Regenerative
Ce(Czfq ≤ 0.155)	−0.465 **
Ce(Czfq > 0.155)	0.028 *
Ce(Czfq ≤ 0.209)		−0.366 **
Ce(Czfq > 0.209)		0.066 *
Ce(Czfq ≤ 0.191)			−0.638 **
Ce(Czfq > 0.191)			−0.007 *
Ce(Czfq ≤ 0.267)				−1.164 ***
Ce(Czfq > 0.267)				0.062 *
Coefficient	0.292 *	0.479 *	−0.735 ***	−0.429 *
adj. R2	0.521	0.157	0.256	0.379
Control variable	Yes	Yes	Yes	Yes
Time effect	Yes	Yes	Yes	Yes
Urban effect	Yes	Yes	Yes	Yes
Sample size	2535	210	900	225

Note: In this article, *, **, and *** respectively indicate significance at the 1%, 5%, and 10% levels.

.

(1)

Non-resource-based cities

For non-resource-based cities, the threshold value is 0.155, which is relatively low. This may be related to these cities’ diversified economies and low reliance on specific natural resources. Since they are not dependent on the extraction of specific resources, non-resource-based cities have greater economic flexibility and more diversified industrial structures. Therefore, even at relatively lower levels of fiscal decentralization, low-carbon development may positively impact employment quality.

When the threshold variable fiscal decentralization Czfq ≤ 0.155, the coefficient of low-carbon development’s impact on employment quality is −0.465, significant at the 5% level. When Czfq > 0.155, the coefficient becomes 0.028, significant at the 10% level. In non-resource-based cities, due to their diversified economies, development does not depend on a single resource extraction sector.

When fiscal decentralization is below the threshold (Czfq ≤ 0.155), local governments may face insufficient funding and technical support for promoting low-carbon development. Low-carbon initiatives typically require substantial initial investments and technological innovation, and limited fiscal autonomy may constrain local governments’ ability to invest in these areas. As a result, low-carbon development may struggle to take shape at scale, negatively impacting employment quality. Moreover, the early stages of low-carbon transition may pose challenges such as the pressure to transform traditional industries and the long gestation periods for emerging green sectors, leading to short-term declines in employment quality. Furthermore, limited fiscal autonomy may hinder investments in workforce training and employment services, exacerbating employment quality issues.

However, when fiscal decentralization exceeds the threshold (Czfq > 0.155), local governments in non-resource-based cities have greater fiscal autonomy to support low-carbon development. This enables more targeted investment in low-carbon technology R&D, industrial upgrading, and workforce training, thereby promoting coordinated development between the low-carbon economy and employment quality. As low-carbon industries gradually mature and labor markets adjust, employment quality is expected to improve. Compared to resource-based cities, non-resource-based cities may have greater flexibility and potential for promoting low-carbon development, as they are not restricted by the cyclical nature of resource extraction and can more freely adjust their industrial structures and development paths. Therefore, under higher levels of fiscal decentralization, non-resource-based cities are more likely to achieve a “win-win” outcome between low-carbon development and improved employment quality.

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Growing resource-based cities

For growing resource-based cities, the threshold value is 0.209, higher than the overall sample threshold of 0.174. This may be because these cities are in a stage of rapid development, with significant potential for resource exploitation and socioeconomic growth. Only after fiscal decentralization reaches a certain level do local governments have sufficient resources and capabilities to promote low-carbon development and, in turn, improve employment quality.

When Czfq ≤ 0.209, the coefficient of low-carbon development’s impact on employment quality is −0.366, significant at the 5% level. When Czfq > 0.209, the coefficient becomes 0.066, significant at the 10% level.

When fiscal decentralization is below the threshold (Czfq ≤ 0.209), due to insufficient financial and technical support and the early-stage nature of resource exploitation, low-carbon development may not yet have formed scale effects, limiting its ability to promote employment quality. Local governments may lack the fiscal autonomy necessary to effectively guide resources into the low-carbon sector, thereby limiting positive impacts on employment quality when decentralization is low.

However, as fiscal decentralization increases (Czfq > 0.209), the impact of low-carbon development on employment quality in growing cities turns positive. This may be attributed to their significant potential for economic and social development, as well as their initially heavy reliance on traditional resource extraction. Greater fiscal autonomy enables local governments to better support low-carbon projects, thus facilitating improvements in employment quality.

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Mature resource-based cities

For mature resource-based cities, the threshold value is 0.191, which is higher than the overall sample value of 0.174 but lower than the threshold for growing cities (0.209). This may be due to these cities having reached a stable stage of resource exploitation, with relatively high levels of socioeconomic development but also more rigid industrial structures.

When Czfq ≤ 0.191, the coefficient of low-carbon development’s impact on employment quality is −0.638, significant at the 5% level. When Czfq > 0.191, the coefficient is −0.007, significant at the 10% level.

When fiscal decentralization is below the threshold (Czfq ≤ 0.191), resources and funding may still be overly concentrated in traditional resource-based industries, with insufficient investment in the low-carbon sector, resulting in a significant negative impact of low-carbon development on employment quality. Although resource exploitation in mature cities is stable and their economic development is relatively advanced, their long-established industrial structures may be difficult to adjust rapidly.

Even after fiscal decentralization exceeds the threshold (Czfq > 0.191), the impact of low-carbon development on employment quality remains negative, though the magnitude of the negative impact is reduced compared to when decentralization is below the threshold. This may be because, despite greater fiscal resources, entrenched industrial rigidities and path dependence continue to limit the positive effects of low-carbon development on employment quality.

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Regenerating resource-based cities

For regenerating resource-based cities, the threshold value is the highest at 0.267. This may reflect that these cities have largely overcome resource dependence and are entering a trajectory of healthy economic and social development. However, having achieved economic transformation and industrial upgrading, regenerating cities may face greater challenges and higher standards for advancing low-carbon development.

When Czfq ≤ 0.267, the coefficient of low-carbon development’s impact on employment quality is −1.164, significant at the 1% level. When Czfq > 0.267, the coefficient becomes 0.062, significant at the 10% level.

When fiscal decentralization is below the threshold (Czfq ≤ 0.267), low-carbon development negatively impacts employment quality. Although these cities have largely escaped resource dependence, low-carbon development presents new challenges requiring significant investment and structural adjustments. Insufficient funding and technical support may cause low-carbon initiatives to adversely affect employment quality in the short term.

However, as fiscal decentralization improves (Czfq > 0.267), local governments are better positioned to support low-carbon projects, optimize economic structures, and promote industrial upgrading, thereby improving employment quality. Having already completed their resource transitions, these cities are better positioned to achieve coordinated improvements in low-carbon development and employment quality. Only when fiscal decentralization reaches a sufficiently high level can local governments have the resources and capabilities necessary to support innovation and growth in low-carbon sectors, leading to tangible improvements in employment quality.

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Declining resource-based cities

For declining resource-based cities, no significant threshold effect was detected. This may be because these cities face severe challenges, including resource depletion and economic stagnation. The heavy pressures of industrial transition and economic decline mean that even with increased fiscal decentralization, it may be difficult to rapidly improve employment quality. These cities may require stronger fiscal support and policy interventions to drive successful low-carbon transitions and improvements in employment outcomes.

5. Conclusions

5.1. Conclusions

There are significant moderating effects and threshold effects of fiscal decentralization and government regulation on the relationship between low-carbon development and urban employment quality.

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Fiscal decentralization to some extent weakens the positive impact of low-carbon development on employment quality, whereas government regulation strengthens it by promoting green transformation and optimizing resource allocation. Fiscal decentralization may dilute the effect of low-carbon development on employment quality due to unbalanced resource distribution or deviations from low-carbon objectives. In contrast, government regulation enhances the positive impact by driving green transition, improving resource allocation, and creating high-quality employment opportunities.

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There are threshold effects associated with fiscal decentralization and government regulation, with threshold values of 0.17 and 59.26, respectively. When fiscal decentralization is below the threshold of 0.17, low-carbon development inhibits improvements in employment quality; however, once fiscal decentralization surpasses the threshold, the negative effect shifts to a positive one. As for government regulation, low-carbon development promotes employment quality both below and above the threshold, but the magnitude of the positive effect decreases once the threshold is exceeded.

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Heterogeneity analysis shows that non-resource-based cities have a lower threshold. In these cities, low-carbon development negatively impacts employment quality when fiscal decentralization is low, but promotes improvement when fiscal decentralization rises. In growing resource-based cities, the threshold is higher than that of the overall sample and employment quality improves significantly after fiscal decentralization increases. In mature resource-based cities, the threshold lies between that of non-resource-based and growing cities; although fiscal decentralization reduces the suppressive effect, its impact on employment quality remains significantly negative. In regenerating cities, the threshold is the highest, and increasing fiscal decentralization can promote employment quality. However, in declining resource-based cities, no threshold effect is observed, and due to substantial transformation pressures, improvements in employment quality are difficult even with higher fiscal decentralization.

5.2. Policy Recommendations

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Improve the fiscal decentralization system in the process of promoting low-carbon economic transformation. Through adjustments in the fiscal relationship between the central and local governments, fiscal responsibilities related to low-carbon development should be rationally allocated. This would reduce the tendency of local governments to neglect environmental protection due to fiscal pressures, ensuring consistency and effectiveness in low-carbon development policies.

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Strengthen government regulation by establishing stricter environmental protection standards and industrial entry thresholds. This will guide enterprises to adopt cleaner production technologies and circular economy models, reduce pollutant emissions, and improve resource utilization efficiency. Meanwhile, market mechanisms should be utilized to promote the research, development, and application of low-carbon technologies.

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Formulate differentiated strategies according to the threshold differences across city types. Non-resource-based cities should seek higher-level fiscal support, enhance fiscal decentralization, develop diversified industries, and foster emerging low-carbon sectors. Growing resource-based cities should seize development opportunities, increase fiscal decentralization, focus on critical sectors, and improve employment quality. Mature resource-based cities should deepen fiscal decentralization, promote industrial restructuring, break structural rigidities, and strengthen the impetus for low-carbon development. Regenerating cities should leverage their advantages, enhance fiscal decentralization, support low-carbon industries, and promote coordinated progress. For declining cities, national and provincial-level support is needed; targeted transformation policies, greater transfer payments, and the guidance of social capital should be introduced to gradually improve employment quality.