Research on the Impact of the County-to-District Reform on Environmental Pollution in China

Abstract

Based on the panel data of 267 prefecture-level cities in China from 2003 to 2016, this paper adopts propensity score matching (PSM) and difference-in-difference (DID) as research methods to test and analyze the impact effect of the county-to-district reform on the environmental pollution. The results show that: (1) The county-to-district reforms have significantly increased the urban environmental pollution. After changing the time and space sample size of the reformed cities, there is no obvious difference in the estimated results; (2) In terms of time, the impact of the county-to-district reforms on environmental pollution has a short-term dynamic, and there is a difference between industrial wastewater pollution and industrial waste-gas pollution; (3) By region, the eastern cities have significantly increased the level of environmental pollution after the county-to-district reforms, both the coefficient and the significance level of the cities in the Mid-West are weaker than those in the East, and presents Eastern > Central > Western; (4) Mechanism testing shows that the county-to-district reforms significantly expand urban space and agglomerate population. The former exacerbates the effects of environmental pollution, while the latter suppresses the growth of environmental pollution. Therefore, it is necessary for the government to reduce the institutional constraints of population migration to big cities and blind land expansion so as to promote pollution reduction.

1. Introduction

In the past 40 years of reform and opening up, China has witnessed a rapid development of urbanization, but the problem of environmental pollution is becoming more and more serious. It is obvious that environmental pollution can easily do great harm to human health and lead to a series of diseases [1,2]. High-quality development requires not only urban and economic growth but also an environment of high quality. Environmental pollution has significantly reduced the quality of economic development [3]. As President Xi Jinping said, “Clear waters and green mountains are invaluable assets”. Reducing environmental pollution has become an important way for people to pursue a high quality of life. For the past two decades, county-to-district reform has been a common method used by the Chinese government to adjust administrative divisions. It has made great contributions to expanding the space for urban development and promoting the development of urbanization. Counties and districts are not only the difference between rural and urban economies. It is also the difference between the management system and the financial system. However, in 2021 and 2022, China’s National Development and Reform Commission successively proposed strict control over the reform of county-to-district. County-to-district reform has been the focus of geographers, economists, and administrators. It promotes urbanization [4], and it also promotes economic growth [5] while restraining housing prices [6]. Did the reform of county-to-district lead to environmental pollution?

Few scholars directly answer the above question through reliable empirical analysis. Cao et al. (2022) found that the merger of cities and counties can improve the level of centralized management, such as finance and environmental governance, thereby reducing urban PM2.5 emissions [7]. The city’s PM2.5 is only part of the city’s pollution. This paper is mainly based on the perspective of urbanization (land urbanization and population urbanization) to study the impact of the reform of county-to-district on environmental pollution. The study found that urbanization [8], economic growth [9], economic agglomeration [10], and environmental regulation [11] are all important factors affecting environmental pollution. Li and Deng’s study found that environmental protection taxes can curb smog pollution [12]. Jiang et al.’s empirical study found that national development zones can reduce local and surrounding environmental pollution [13]. Similarly, Spain’s emissions tax mitigated greenhouse gas emissions [14]. Ikram et al.’s (2021) research shows that Pakistan promotes green technology development through measures such as improving the national security environment and reducing taxes [15]. Vitunskiene et al. found that EU countries realize the transition from fossil energy to bioenergy through biological self-sufficiency [16]. D’Adamo et al. found that a unified European model breaks down barriers between different countries and promotes mutual cooperation. EU countries achieve sustainable energy development through government regulation and subsidies [17]. On the whole, the reform from the government has basically reduced environmental pollution. However, we still need to empirically examine the environmental effects of the reform.

Among them, the research results related to the relationship between urbanization and environmental pollution are the most relevant to this paper. The study of the relationship between urbanization and environmental pollution is one of the hot spots of scholars at home and abroad. Some scholars believe that urban expansion leads to environmental pollution [18,19,20]. Urbanization significantly increases carbon emissions and the greenhouse effect [21] and disrupts ecosystem balance [22]. Some scholars believe that urban expansion restrains environmental pollution; environmental pollution is worse in small cities in developing countries [23]. Some scholars have found an inverted U-shaped relationship between urbanization and environmental pollution [24,25].

In conclusion, the relationship between urbanization and environmental pollution is highly uncertain, and differences in time, space, city type, and pollution source indicators will affect theoretical and empirical results. Confronted with inconsistent conclusions, county-to-district reform is a policy of administrative division adjustment in order to alleviate the strain on land resources and promote urbanization. It provides a new perspective for examining the relationship between urbanization and environmental pollution. Therefore, based on the panel data of prefecture-level cities and above in China from 2003 to 2016, this paper uses the PSM-DID methods to test the “net” effect of the reform of county-to-district on environmental pollution.

The possible marginal contributions of this paper are as follows: (1) The paper provides a new empirical perspective and method for the impact of urban expansion on environmental pollution by examining the quasi-natural experiment of the reform of county-to-district; (2) The effect of policy evaluation on the reform of administrative division by the reform of county-to-district; (3) The findings of this paper provide an empirical basis for the policy regulation of urbanization development in China. We conclude that population urbanization and land urbanization produce differentiated environmental pollution. This study provides empirical support for the gradual liberalization of household registration restrictions and adjustment of land supply strategies in big cities.

2. Literature and Research Hypothesis

The reform of county-to-district promotes urbanization while having a short-term economic growth effect [5]. However, economic growth and environmental pollution are closely linked. Therefore, the reform of county-to-district will have an impact on environmental pollution. The development of large cities is accompanied by the double expansion of urban population size and urban space [26,27]. The reform of county-to-district is expanding urban land scale [6], promoting population agglomeration [4]. The population expansion and regional area expansion of Chinese cities are significantly correlated with urban PM2.5 [28], which further proves that there is a certain connection between the county-to-district reform and environmental pollution.

The urban land expansion system is highly correlated with the ecological environment system [29]. Local governments in China have a strong preference for land finance, which further promotes the consumption of agricultural land and the expansion of urban built-up areas by local governments. Local governments develop industrial land and commercial and residential land on a large scale, auction industrial land at low prices, build industrial parks and development zones on a large scale, lower the environmental access threshold for enterprises, and promote investment attraction. Driven by the “performance-based” assessment, too much attention is paid to the short-term performance of the local economy, while the crude, homogeneous, and low-end development of the local manufacturing industry has produced large-scale environmental pollution [30]. At the same time, urban expansion is accompanied by a lot of infrastructure construction, which leads to more pollution [31]. Scholars found that the reform of county-to-district promoted local productive expenditures but not local public facilities, social services, or other livelihoods expenditures [32], and local governments’ investments in environmental pollution control at the same time were obviously insufficient. New city expansion has a lower opportunity cost than old city renovation, hence the rise of urban sprawl in various cities. Construction land expansion has a negative impact on the ecological environment and severely damages the vegetation in built-up areas of cities [33]. Therefore, urban land expansion creates a positive effect on environmental pollution. In summary, the article proposes that:

Hypothesis 1.

The reform of county-to-district promotes the spatial expansion of urban land and increases the development and utilization of land, thus exacerbating urban environmental pollution.

However, urban expansion integrates urban resources, creating industrial agglomeration, economic agglomeration, and population agglomeration. When the positive environmental externality of agglomeration is greater than the negative externality, the net effect of industrial agglomeration on environmental pollution is to suppress environmental pollution [34]. Agglomeration produces the following effects:

(1) Scale effect: Firstly, scholars have found that through effective management and professional division of labor, industrial parks or development zones as a whole have a lower pollution reduction cost effect. Secondly, the industrial association is beneficial to the flow of enterprise resources in the agglomeration area and reduces pollution emissions. Finally, the spillover effect between enterprises (clean emission reduction technology) is beneficial to regional emission reduction;

(2) Structural effect: The development of urbanization means the transformation of industrial structure, the rapid development of the tertiary industry, and the service industry releases lower pollution [35];

(3) Technological effect: The development of a high-end manufacturing industry reduces direct emissions, and the construction of a “smart city” reduces environmental pollution through scientific and technological innovation [36];

(4) Social effect: The reform of county-to-district changes the identity and sense of household registration identity of residents in counties that have been withdrawn and merged [37], which helps improve residents’ cognition of environmental protection. Among the four effects, the social effect is based on the microanalysis at the individual level of residents, while the study in this paper is based on the macro level, such as industry and structure. Therefore, the first three effects are mainly considered. The above analysis tells us that population agglomeration and expansion have a negative effect on environmental pollution. Secondly, it is further proposed that:

Hypothesis 2.

The reform of county-to-district can unify urban and rural markets, agglomerate the urban economy, promote urban population agglomeration and expansion, and restrain urban environmental pollution.

With the exception of first-tier cities such as Shanghai and Shenzhen, construction land has moved from “incrementalization” to “stocking”. In the past two decades, China has been in a state of “sprawl” compared to European countries that have followed the path of compact urban development [38]. The overall rate of land urbanization has far exceeded the rate of population urbanization. Therefore, the environmental pollution effects of land urbanization are presumed to be greater than those of population urbanization.

In conclusion, the following is proposed:

Hypothesis 3.

The net effect of the county-to-district on environmental pollution is positive. That is, the reform of county-to-district promotes environmental pollution.

3. Methods and Data

3.1. Research Methods

In the article, the PSM-DID method [39] was chosen for empirical testing. It is divided into two steps.

(1) Propensity score matching (PSM). Since the approval of reform city samples is set by the government in accordance with certain standards (sufficient population, area, and economic scale), it is easy to form estimation bias if we directly use the DID method. We chose to use the PSM method first to avoid errors. We usually use logistic regression to calculate propensity scores. The commonly used matching methods are nearest neighbor matching, radius matching, and kernel matching. Two types of cities were selected from the sample cities for the analysis, where cities that never experienced county abolition reforms between 2003 and 2016 were the control group and cities that experienced one or more were the treatment group. Due to the inconsistency of the time of the county abolition reform occurrence, the article adopts a multi-period year-by-year matching method. Since 2000–2004 was one of the peak periods of county abolition reforms in China, simply removing the pre-2003 sample may weaken its average effect, so the 2003 treatment group sample adds cities that were abolished from 1998 to 2002. The 1-to-1 nearest neighbor matching method was used to eliminate the control group and the treatment group that failed to match, and the remaining city samples were the treatment and control groups for the reform of county-to-district. The matched cities in the control group may correspond to more than one city in the treatment group, and the number of occurrences of all control group cities is counted as the weight in the double difference test.

(2) Difference in difference method (DID) is a common method for policy effect evaluation. The DID method is a quasi-natural experimental method, the basic idea of which is that in order to assess the net effect of policy implementation, the entire sample is divided into a “treatment group” (which is affected by the policy) and “control group” (which is not affected by the policy). In this paper, the measurement equation of the impact of county abolition on environmental pollution is set as:

$$pollut{e}_{it}=\mathsf{\alpha }+{\beta }_{1}Refor{m}_i\times Afte{r}_t+{\beta }_{2}Refor{m}_i+{\beta }_{3}Afte{r}_t+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\epsilon }_{it}$$

(1)

In Equation (1), the subscript $i$ represents the city,$t$ is the time, and $pollut{e}_{it}$ is the emission indicator after taking the natural logarithm. $Control{s}_{it}$ is the control variable that affects the change of the pollution emission level with cities and time, and ε is the residual. Due to the inconsistency of reform time, the study adopts the multi-period double difference method to use all cities without county reform as the control group and cities with county reform as the experimental group. The interaction $Refor{m}_i\times Afte{r}_t$ is 1 when a city i specifically carried out the county-to-district reform in a certain year t; otherwise, the DID interaction term of the city is equal to 0. In this paper, we control both the time fixed effect ${\gamma }_t$ and the local fixed effect ${\mu }_i$ to exclude the influence of the time factor and individual city factor. Therefore, a panel data regression analysis is conducted according to Equation (2).

$$pollut{e}_{it}=\mathsf{\alpha }+{\beta }_1(Refor{m}_i\times Afte{r}_t)+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\mu }_i+{\gamma }_t+{\epsilon }_{it}$$

(2)

3.2. Variables and Data Sources

Explained variables. Environmental pollution mainly comes from industrial production, and the explanatory variables are derived from industrial wastewater (IWW) emissions and industrial waste gas (IWG) (sulfur dioxide) emissions of prefecture-level cities in the China Urban Statistical Yearbook (2004–2017), while to exclude the interference of population size factors, both per capita wastewater emissions (PIWW) and per capita waste gas (PIWG) (sulfur dioxide) emissions are selected in this paper. The logarithm is taken in the model. The data of 267 prefectural-level cities in China are kept after sorting by removing the cities with serious missing data.

Explanatory variables. The reform variables were obtained from the official website of the Ministry of Civil Affairs of the People’s Republic of China (http://www.mca.gov.cn (accessed on 15 January 2020)), and the administrative division adjustment documents promulgated by the Ministry of Civil Affairs of the State Council from 1999 to 2018 were manually collated and checked for consistency with the Handbook of Administrative Divisions of China (1999–2018) to avoid omissions.

Control variables. Controlling for the main influencing factors affecting urban pollution. The data were obtained from the China Urban Statistical Yearbook (2004–2017) and some provincial and municipal statistical yearbooks. Economic development level: using GDP per capita to measure the level of urban economic development, due to the possible inverted U-shaped relationship between economic growth and environmental pollution, adding the squared term of the logarithm of GDP per capita. Industrial structure (IS): urban pollution mainly comes from industrialized emissions; therefore, this paper adds the proportion of secondary industry added value to GDP. Foreign investment: using FDI per capita to take the logarithm measure, due to the home country’s emission constraints, foreign firms shift their production to developing countries. Science and technology level (TE): the development of the science and technology level is measured by the fiscal per capita expenditure on science and technology. The above variables are taken as logarithms. The results of descriptive statistics for each variable are shown in

Table 1. Descriptive statistical analysis of variables.

Variable	Mean	Std. Dev.	Min	Max	Observations
IWW	8.477	1.007	4.477	11.421	3738
IWG	10.589	1.012	4.159	13.434	3738
PIWW	2.568	0.852	−2.282	5.749	3738
PIWG	4.680	1.022	−1.558	7.844	3738
Reform	0.190	0.393	0	1	3738
perGDP	10.089	0.803	7.771	13.056	3738
(PerGDP) 2	102.432	16.164	60.383	170.451	3738
IS	0.487	0.103	0.027	0.859	3738
FDI	3.705	1.712	−3.233	7.770	3731
TE	3.155	1.722	−8.653	8.341	3737

(PerGDP) ² is the squared term of the logarithm of GDP per capita.

.

4. Results

4.1. Propensity Score Matching Analysis

Parallelism tests were done on the control variables of the treatment and control groups after matching for each year (2003 to 2016, 14 years in total), and the deviation was less than 10% for each year, indicating a high degree of similarity between the matched samples of cities in the treatment and control groups. In total, 97 cities in the treatment group and 66 cities in the control group were retained from the matching. It can be seen that there are multiple treatment group cities corresponding to the same control group cities. The matched treatment group samples and the control group samples satisfy the parallel trend hypothesis and the common support hypothesis, which provide valid samples for the subsequent double difference method.

4.2. Overall Regression Effect

The overall effect of the reform on urban environmental pollution was examined by Equation (2), with columns (1) to (4) in

Table 2. The benchmark regression results of the policy reform of county-to-district.

	IWW	IWG	PIWW	PIWG	IWW	IWG	PIWW	PIWG
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Reform×After	0.085 *	0.211 ***	0.145 ***	0.271 ***	0.080 *	0.178 ***	0.116 **	0.214 ***
	(1.86)	(4.06)	(2.82)	(4.26)	(1.75)	(3.52)	(2.35)	(3.55)
Control variables	No	No	No	No	Yes	Yes	Yes	Yes
Year-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
City-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	2282	2282	2282	2282	2277	2277	2277	2277
R-squared	0.994	0.994	0.949	0.963	0.994	0.995	0.954	0.967
F	13.81	52.26	12.79	40.83	10.19	45.88	21.47	46.48

t values are in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

without adding any control variables and columns (5) to (8) with control variables. The results show that the reform has a significant positive effect on each pollution indicator regardless of whether control variables are added or not, indicating that the reform significantly improves urban pollution levels. Among them, the reform of county-to-district significantly increases wastewater emissions per capita by 11.6% and exhaust gas emissions per capita by 21.4%, while significantly increasing wastewater emissions by 8% and exhaust gas emissions by 17.8%. Therefore, the reform of county-to-district significantly increases the level of urban environmental pollution, and Hypothesis 3 is valid.

4.3. Robustness Tests

In order to test the stability of the effect of county-to-district on environmental pollution, this paper selects a more concentrated time period of county-to-district from 2011 to 2016. As shown in columns (1) to (4) of

Table 3. Robustness test.

	2011–2016				Excluding the Reform Cities in 1999–2002
	IWW	IWG	PIWW	PIWG	IWW	IWG	PIWW	PIWG
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Reform × After	0.084 **	0.117 **	0.130 ***	0.163 ***	0.087 *	0.080	0.106 **	0.099 *
	(1.97)	(2.10)	(2.71)	(2.58)	(1.86)	(1.52)	(2.19)	(1.75)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
City-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	978	978	978	978	1843	1843	1843	1843
R-squared	0.998	0.997	0.979	0.981	0.981	0.985	0.894	0.939
F	28.16	82.35	54.56	87.55	9.20	25.84	14.49	27.20

t values are in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

, county-to-district significantly aggravates the emission level of each environmental pollution. At the same time, excluding the cities of county abolition from 1999 to 2002, the test results are shown in columns (5) to (8) of Table 3, although weakened compared to the results in Table 2, the county-to-district still aggravates the emission level of urban environmental pollution. Therefore, the estimated results that county-to-district has an exacerbating effect on environmental pollution are robust.

4.4. Time Dynamic Effect Test

In this paper, to test the dynamic effect of county-to-district reform on environmental pollution, Equation (3) is used. The variable j represents time, 0 is taken in the year of county abolition and 1 in the first year, and $tim{e}_j$ is 6 time dummy variables, which represent the year from the beginning of county abolition to the 5th year, respectively. The test results are shown in

Table 4. The regression results of the time dynamic effects.

	IWW	PIWW	IWG	PIWG
	(1)	(2)	(3)	(4)
Reform year	0.107 **	0.124 **	0.062	0.078
	(2.10)	(2.24)	(1.09)	(1.15)
Year 1 after reform	0.141 **	0.151 **	0.091	0.101
	(2.54)	(2.53)	(1.47)	(1.37)
Year 2 after reform	0.070	0.090	0.054	0.085
	(1.16)	(1.39)	(0.81)	(0.80)
Year 3 after reform	0.080	0.101	−0.049	−0.028
	(1.18)	(1.38)	(−0.65)	(−0.31)
Year 4 after reform	0.059	0.076	−0.063	−0.046
	(0.81)	(0.97)	(−0.77)	(−0.47)
Year 5 after reform	0.101	0.123	−0.064	−0.042
	(1.32)	(1.49)	(−0.75)	(−0.41)
Control variables	Yes	Yes	Yes	Yes
Year and city fixed effect	Yes	Yes	Yes	Yes
Observations	2277	2277	2277	2277
R-squared	0.994	0.955	0.995	0.967
F	8.44	17.34	35.84	36.22

t values are in parentheses, ** p < 0.05.

: the pollution indicators show variability, and the wastewater discharge and per capita wastewater discharge are significantly positive in the year of county abolition and the first year, with the largest result in the first year. From the second year, the estimated coefficient is positive but no longer significant, indicating that the county abolition reform increases industrial wastewater discharge in the short term. Industrial waste gas discharge is not significant from the year of county abolition to the fifth year, indicating that the county abolition reform increases industrial waste gas discharge. The time dynamics do not have a significant effect on industrial waste gas emissions, probably due to the stronger mobility and diffusion of the atmosphere, and the coefficient of the reform becomes negative from the third year onwards, indicating that the effect of county abolition on industrial waste gas emissions turns to inhibit pollution.

$$pollut{e}_{it}=\mathsf{\alpha }+{{\displaystyle \sum }}_{j=0}^5{\beta }_{j}Refor{m}_i\times Afte{r}_t\times tim{e}_j+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\mu }_i+{\gamma }_t+{\epsilon }_{it}$$

(3)

4.5. Sub-Regional Heterogeneity Test

China’s economy is extremely regional, and the east is better than the central and western regions in terms of total economic volume and population concentration. However, due to the mismatch of land resources [40], the central and western regions have more land indicators. Meanwhile, the local governments of central and western cities have built a large number of development zones and industrial parks, but enterprises pay more attention to the quality business environment, convenient transportation conditions, and industrial chain structure in choosing locations for investment. The eastern region has better investment attractiveness than the central and western regions. The eastern region attracts more industrial enterprises than the central and western regions after the removal of counties and the establishment of districts. Therefore, the eastern region may be more likely to increase the level of environmental pollution than the central and western regions. The regression equation is shown in Equation (4), which divides all cities in the sample into eastern, central, and western regions, and region_k represents the three regional dummy variables. The results are shown in

Table 5. Regional heterogeneity effects of reform.

	IWW	PIWW	IWG	PIWG
	(1)	(2)	(3)	(4)
Reform × After × Eastern	0.062	0.149 **	0.243 ***	0.331 ***
	(1.03)	(2.31)	(3.67)	(4.19)
Reform × After × Central	0.196 **	0.164 *	0.119	0.087
	(2.13)	(1.66)	(0.241)	(0.72)
Reform × After × Western	0.028	0.015	0.097	0.085
	(0.34)	(0.18)	(1.09)	(0.80)
Control variables	Yes	Yes	Yes	Yes
Year and city fixed effect	Yes	Yes	Yes	Yes
Observations	2277	2277	2277	2277
R-squared	0.994	0.954	0.995	0.967
F	9.32	19.52	41.63	42.36

t values are in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

. Except for the insignificant reform coefficient corresponding to the wastewater discharge in column (1), the reform of removing counties and setting up districts in the eastern region has a strong positive effect on the pollution emission index. It indicates that the removal of counties and districts significantly aggravates environmental pollution in the eastern region, while it is not significant for the central and western regions. The massive convergence of industrial enterprises in the eastern region makes the increase in pollution emissions more significant. The coefficients of the three regions are the largest in the east, the second largest in the center, and the smallest in the west, which is highly consistent with the level of regional economic development in China. In addition, columns (1) and (2) indicate that the reform of county-to-district significantly exacerbates industrial wastewater discharge in the central region.

$$pollut{e}_{it}=\mathsf{\alpha }+{\beta }_1{{\displaystyle \sum }}_{k=1}^3{\beta }_{k}Refor{m}_i\times Afte{r}_t\times regio{n}_k+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\mu }_i+{\gamma }_t+{\epsilon }_{it}$$

(4)

4.6. Mechanism Analysis

The empirical test shows that the effect of county abolition reform on environmental pollution is positive, so what is the mechanism of county abolition reform on environmental pollution? This paper will test the mechanism of the effect of county abolition on environmental pollution in two major parts based on the second part of the mechanism analysis. First, the effect of environmental pollution is examined in terms of the land expansion caused by the reform of county-to-district; second, the effect of environmental pollution is examined in terms of the population agglomeration formed by the reform of county-to-district. Urban built-up area was used to measure land urbanization, and population density was used to measure urban population urbanization. In this paper, Equations (5) and (6) are used to test the mediation mechanism.

$$M_{it}=\mathsf{\alpha }+{\beta }_{1}Refor{m}_i\times Afte{r}_t+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\mu }_i+{\gamma }_t+{\epsilon }_{it}$$

(5)

$$pollut{e}_{it}=\mathsf{\alpha }+{\beta }_{1}Refor{m}_i\times Afte{r}_t+{\beta }_2{M}_{it}+\mathsf{\lambda }{{\displaystyle \sum }}_{n}Control{s}_{it}+{\mu }_i+{\gamma }_t+{\epsilon }_{it}$$

(6)

(1) County-to-district, land urbanization, and environmental pollution

In the first step, to test the effect of county removal on urban land expansion, the multiplicative difference term is regressed on the area of urban built-up area, and if the coefficient is significant, then the reform of county-to-district promotes land urbanization. In the second step, to test the effect of county removal on environmental pollution, the multiplicative difference term is regressed on the environmental pollution variable (taken as per capita emissions), and if the coefficient is significant, then the reform of county-to-district leads to environmental pollution. In the third step, the multiplicative difference term and built-up area are regressed on the environmental pollution variable at the same time, and if the coefficient of the multiplicative difference term is not significant or significant but the coefficient decreases, then it indicates that the reform of county-to-district expands urban land area and aggravates environmental pollution [36].

As shown in column (1) of

Table 6. The county-to-district reform, land urbanization, and environmental pollution.

	Built-Up Area	PIWW	PIWG	PIWW	PIWG
	(1)	(2)	(3)	(4)	(5)
Reform × After	0.207 ***	0.116 **	0.214 ***	0.090 **	0.185 ***
	(10.07)	(2.35)	(3.55)	(2.42)	(3.00)
Built-up area				0.031	0.141 **
				(0.59)	(2.20)
Control variables	Yes	Yes	Yes	Yes	Yes
Year-fixed effect	Yes	Yes	Yes	Yes	Yes
City-fixed effect	Yes	Yes	Yes	Yes	Yes
Observations	2277	2277	2277	2277	2277
R-squared	0.955	0.954	0.967	0.954	0.967
F	170.33	21.47	46.48	20.41	44.48

t values are in parentheses, *** p < 0.01, ** p < 0.05.

, the reform of county-to-district significantly increases the area of urban built-up areas and promotes urban land expansion, and the first step holds. The results of the second step are shown in columns (2) and (3): the reform of county-to-district is significant at the 5% level for wastewater per capita and at the 1% level for waste gas per capita, and the coefficients are both positive, indicating that the reform of county-to-district aggravates urban industrial pollution emissions, and the second step is satisfied. The results of the third step are shown in columns (4) and column (5): after adding the built-up area variable, the reform coefficient is still significant, but the coefficient decreases, meanwhile, the variable built-up area coefficient is positive, and the third step is verified. Combining the above three steps of empirical analysis, it is shown that the reform of county-to-district intensifies the urbanization of land and produces pollution in the urban industrial environment. Therefore, Hypothesis 1 holds.

(2) County-to-district, urbanization of the population, and environmental pollution

As shown in

Table 7. The influence of county-to-district reform on land and population urbanization.

	PD	PIWW	PIWG	PIWW	PIWG	EI	PD	PIWW	PIWG
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Reform × After	0.218 ***	0.116 **	0.214 ***	0.075	0.103 *	0.218 ***	0.065 ***	0.618 **	0.601 *
	(9.91)	(2.35)	(3.55)	(1.50)	(1.70)	(9.91)	(5.94)	(2.25)	(1.78)
PD				−0.186 ***	−0.510 ***
				(−3.81)	(−8.66)
EI							0.652 ***
							(88.16)
Reform × After × EI								−0.056 *	−0.090 **
								(−1.86)	(−2.46)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
City-fixed effect	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	2277	2277	2277	2277	2277	2277	2277	2277	2277
R-squared	0.924	0.954	0.967	0.955	0.968	0.979	0.982	0.967	0.967
F	125.21	21.47	46.48	21.26	49.46	1495.48	1112.40	20.60	44.56

t values are in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

, column (1) indicates that the reform of county-to-district significantly promotes population agglomeration, and when the population density variable and the reform variable are regressed on both the wastewater per capita and the exhaust gas per capita variables, the coefficients of the reform variables in columns (4) and (5) are significantly lower compared to columns (2) and (3), while the coefficient of the population density variable is negative, indicating that the agglomeration of the population helps reduce environmental pollution. Therefore, the reform of county-to-district boosts urban population density (PD) and suppresses environmental pollution.

The urbanization of the population due to the reform of county-to-district is attributed to the integration of markets and the agglomeration effect of the economy, and to measure the effect of the agglomeration of the economy, the variable economic intensity (EI) = GDP per capita× population density = GDP/urban area is introduced. Column (6) shows that the economic agglomeration of cities is promoted by the reform of county-to-district and when the economic intensity and reform variables are added to the model and the population density is regressed simultaneously, the results are shown in column (7), and compared with column (1), although the significance of the reform variable does not decrease, the reform coefficient is significantly reduced, indicating that the economic agglomeration of cities after the reform of county-to-district contributes to the population agglomeration of cities. This means that “people follow industry”. Columns (8) and (9) represent the regression results after adding the interaction terms of economic intensity and reform variables, and the coefficients of the interaction terms are both significantly negative, indicating that economic agglomeration helps to suppress urban pollution.

In summary, the reform of county-to-district promotes the integration of urban and rural markets and economic agglomeration, which helps to attract rural populations to cities, increase population density, and promote population agglomeration, while both economic agglomeration and population agglomeration help to reduce the emission of environmental pollution. Hypothesis 2 is verified.

5. Discussion

With the improvement of science and technology and the optimization of industrial structure, China’s pollution emissions have decreased year by year. Existing data show that the net effect of the reform on environmental pollution is positive, but we cannot deny the effectiveness of the reform. We speculate that the land urbanization effect of the reform is much faster than the population urbanization effect. The impact of the reforms on cities and the environment goes both ways. With the improvement of the efficiency of intensive land use and the deepening of population concentration, environmental pollution will be restrained in the future. In the short term, the government should also strictly approve the reform of county-to-district.

The findings of this paper are an effective supplement to the evaluation of administrative reform policies on the reform of county-to-district and provide theoretical support for urbanization and environmental decision-making. In view of the above discussion, it is suggested that we should: (1) Advocate intensive and economical use of land, transform urban land from “incremental” to “stock” construction, activate idle low-utility land, and actively promote compact city development; (2) Limit investment attraction from land concessions in advance; (3) Actively develop central and western city clusters to guide industries to move westward, while deploying industrial structures in eastern regions to reduce environmental pressure; (4) Gradually liberalize the restrictions on household registration in eastern coastal cities and central cities in central and western regions through the reform of the household registration system to guide population inflow.

Finally, further research questions on the impact of county-to-district on the environment may include: (1) due to data collection limitations, we only study environmental pollution at the city level, the impact of county-to-district reform on environmental pollution in county-level cities is not verified, but this is important for counties; (2) the boundary effect of environmental pollution. There is a boundary effect on the economic impact of county-to-district, and there may also be a boundary effect on the impact of environmental pollution, which deserves further study.

6. Conclusions

This paper puts forward three hypotheses through theoretical hypothesis analysis and empirically tests these three hypotheses. The main conclusions are summarized as follows:

(1) On the one hand, the reform of county-to-district expands the urban land space, and the land development has a certain negative effect on the environment, thus aggravating the environmental pollution. This is Hypothesis 1.

(2) On the other hand, the reform of county-to-district gathers urban economy and population, and the agglomeration of the population has a positive external effect to promote the reduction of environmental pollution. This is Hypothesis 2.

(3) Overall, the comprehensive environmental effect of the reform is to increase pollution emissions. The reform of county-to-district significantly exacerbates the level of industrial wastewater and industrial waste gas emissions, which is robust at the per capita level and the total level. That is, overall, the reform of county-to-district is not conducive to suppressing environmental pollution, so Hypothesis 3 is true. It is also further verified that the land urbanization effect is stronger than the population urbanization effect.

(4) In addition, from the time of reform, the reform of county-to-district has indicator short-term dynamics on environmental pollution, industrial wastewater emissions are short-term significant, and industrial waste gas is not significant. From the reform area, the reform of county-to-district has more significant environmental pollution effects on eastern regions than central and western regions.