The Impact of Environmental Regulation on Human Sustainable Development: Evidence from China

Abstract

In recent years, the continuous progress of industrialization and rapid economic development have brought great pressure to the environment. Local governments have strengthened environmental regulation to protect the ecological environment. In order to measure the current status of human sustainable development, which is the ultimate goal of the sustainable development of society, this paper constructs the Human Sustainable Development Index to assess the human sustainable development of each province in China from 2005 to 2017. In addition, this paper empirically analyzes the direct and indirect effects of environmental regulation on human sustainable development. The result shows that China has made great progress in human sustainable development from 2005 to 2017. Although the provincial rankings of human sustainable development have changed little over the years, the inter-regional gap of human sustainable development is narrowing. Environmental regulation not only has a direct impact on human sustainable development, but also has an indirect impact through technology innovation. In addition, the increase in the proportion of tertiary industry can also improve human sustainable development. In the future, the government should take human sustainable development as the center, strengthen environmental regulation, promote technology innovation and industrial structure upgrading.

1. Introduction

At present, the accumulation of the negative effects of industrial civilization have brought more and more serious global ecological problems [1,2,3]. The environment has become a constraint to the development of society. On the one hand, environmental problems directly affect people’s quality of life, and people need a good environment to have a healthier life. On the other hand, the model of development characterized by high energy consumption and high pollution is not sustainable. Therefore, countries all over the world are confronted with the challenges of controlling various pollutants and reshaping the ecosystem [4]. There has been a shift from just focusing on GDP to focusing on the sustainability of development. For the purpose of balancing the dual goals of economic growth and environmental protection, sustainable development has become a wise choice for all countries [5]. Sustainable development is not only necessary to meet the people’s ever-growing needs for a better life and solve prominent social problems, but also an inevitable choice for sustained, sound and high-quality economic development.

The fundamental purpose of development is human development. The goal of stable economic growth and sustainable social development is for the better development of people, and human development is the most direct embodiment of social and economic development. The United Nations Development Programme (UNDP) first proposed the Human Development Index (HDI) in 1990. Many scholars believe that HDI can better reflect the economic development of a country than GDP, and has been a key indicator to evaluate the development of each country [6]. However, the HDI only describes human development from the three dimensions of income, education and health, ignoring the positive contribution of the improvement of ecological civilization to human development. The importance of environment for human development is becoming increasingly apparent. The United Nations put forward the Sustainable Development Goals (SDGs) in 2020, which are considered to be the optimal form of society in the future [7]. It puts forward 17 sustainable development goals, which put ecological issues in the forefront. A good ecological environment can improve the business environment and promote the prosperity of the market, which will greatly promote the development of the local economy and improve the quality of life of the people. In addition, the SDGS are interrelated and can be described in terms of human development and environmental sustainability [8]. Therefore, the human sustainable development, which consists of human development and environmental sustainability, is a good measure of SDGs. Seeking for human sustainable development should be the common goal of all countries in the world.

Environmental regulation is a method commonly used by the government to promote green economic development [9,10]. However, the impact of environmental regulation on human sustainable development has not been empirically analyzed. As China is the largest developing country in the world, the analysis of the impact of environmental regulation on human sustainable development in China can provide experience for China and other countries in the world to further improve human sustainable development. Therefore, the following questions are put forward: (1) What is the current human sustainable development in various provinces of China? (2) What is the impact of environmental regulation on human sustainable development? (3) What is the influence path of environmental regulation on human sustainable development?

In order to answer the above questions, this paper is processed in the following ways. Firstly, this paper constructs the HSDI by adding the dimension of sustainable development to the HDI, and calculates the human sustainable development of the provinces in China from 2005 to 2017. Secondly, this paper analyzes the effect of environmental regulation on human sustainable development. Finally, this paper further analyzes the intermediary effect of technology innovation between environmental regulation and human sustainable development.

The rest of this paper is organized as follows. Section 2 reviews the earlier studies. Section 3 calculates the Human Sustainable Development Index. Section 4 presents the model and data. Section 5 presents the empirical results, including mediating effect analysis and robustness test. Section 6 concludes the study with important findings and puts forward the policy implications.

2. Literature Review

2.1. Environmental Regulation

Environmental regulation is an important means of environmental governance by the government, including a series of related policies or measures [11]. Environmental regulation is a key measure to solve environmental pollution and improve resource utilization [12]. To be specific, environmental regulation increases the cost of pollution treatment for enterprises, prompting enterprises to seek more efficient and green production technologies to reduce production costs and improve product quality [13]. Therefore, environmental regulation has an important impact on industrial structure [14] and economy growth [15].

2.2. Human Sustainable Development

The HDI, which includes income, health and education, is a good measure of human development and upends the long-standing system of measuring only material growth [16]. It has been praised for its simple operation and intuitive advantages when evaluating and comparing human development between regions [17]. Many scholars have found that GDP [18], public expenditure [19,20], environmental quality [21], education [22], social capital [23] and other factors can affect human development.

However, human sustainable development includes economic sustainability [24], social sustainability [25] and environmental sustainability [26]. HDI can be used to measure economic and social development, but it lacks environmental factors, which is an indispensable part of comprehensive measurement of human development [16]. Many scholars have extended HDI by adding environmental factors. Ture used the ecological footprint to modify HDI and construct the Ecologically Sustainable Human Development Index (E-SHDI), and compared the values and rankings of HDI and E-SHDI internationally [27]. Bravo added the dimension of sustainable development to HDI [28]. Paula and Kolosta proposed the Sustainable Development Index (SDIs) based on the contradiction between economic development and environmental protection [29]. Hickel proposed the Sustainable Development Index (SDI), which addresses the defect that the Human Development Index does not consider ecological issues, and proves that SDI is a strong sustainability indicator when measuring the ecological efficiency of various countries [30]. On this basis, Chen further proposed HSDI, which includes three dimensions: environmental, economic and social, which is conducive to a comprehensive assessment of regional sustainable development [31].

2.3. Environmental Regulation and Human Sustainable Development

Many scholars have proved that environmental regulation can promote green economic growth [32]. However, this is from an economic perspective. The current development is human-centered, so it is necessary to measure the impact of environmental regulation on human sustainable development. On the one hand, environmental regulation has a positive effect on human sustainable development. To be specific, environmental regulation can reduce pollution, which improves the quality of the environment. A good environment can reduce the possibility of people contracting diseases, thus prolonging people’s lives, ensuring people’s healthy life and longevity, which helps to improve people’s health. A good environment can also attract talents and gather educational resources, which helps to improve people’s education. In addition, environmental regulation can promote industrial upgrading and thus improve people’s income. On the other hand, environmental regulation also has a negative effect on human sustainable development. Environmental regulation may lead to the closure of enterprises, people’s unemployment and income reduction, thus reducing human sustainable development. Therefore, the impact of environmental regulation on the human sustainable development is still unclear and needs to be further studied. Therefore, this paper proposes the following hypothesis:

H1. 

Environmental regulation can improve human sustainable development.

2.4. The Mediating Effect of Technology Innovation

According to the compensation effect of innovation, environmental regulation can stimulate enterprises to carry out technological innovation activities, and then promoting economic growth, which is the claim of the famous Porter hypothesis [33,34]. Technology innovation can enhance human sustainable development in the following ways. Firstly, technology innovation can reduce pollution, which improves people’s health. Secondly, technology innovation can optimize the industrial structure, which promotes sustainable development. In addition, technology innovation is conducive to the improvement of productivity, thus promoting economic development and increasing residents’ income. Finally, technology innovation will increase people’s awareness of the importance of knowledge, which in turn will promote people’s education.

To sum up, environmental regulation can improve human sustainable development by promoting technology innovation. This paper proposes the following research hypothesis:

H2. 

Technology innovation mediates the relationship between environmental regulation and human sustainable development.

3. Construction of Human Sustainable Development Index

3.1. The Dimension of the Index

In order to accurately and objectively measure the human sustainable development in China, this paper constructs the HSDI based on the HDI proposed by the United Nations. Considering the environmental protection problems existing in economic and social development, the HSDI includes the green development index (GDI), which reflects sustainable development. As a result, the HSDI considers the harmonious symbiotic relationship between human, society and nature from the four dimensions of income, health, education and sustainability. The change of measurement from three to four dimensions elevates the ecological environment to a new height. The HSDI can not only fully cover the connotation of human development in the new era, but also meet the realistic needs of human social development. With reference to the calculation instructions for the HDI released by the UNDP in 2018, the selection of sub-indicators of the HSDI and their specific thresholds were determined in accordance with the calculation principles of being targeted, simple, transparent, representative and easy to operate.

(1)

Income Index (II)

Income is the guarantee of a decent life for the people, and the economic foundation still plays a decisive role in human development. The income index is calculated as per capita GDP (PGDP).

(2)

Health Index (HI)

Health is a necessary condition for people to pursue a better life in the new era, and it is also the only way to promote the sustainable development of mankind. The HI uses life expectancy as a measure of the number of years a generation born at the same time could live if mortality rates remained unchanged across all age groups.

(3)

Education Index (EI)

The demand for education is the instinctive demand for people to constantly pursue happiness. Education can improve human capital, provide people with the technical knowledge needed to earn higher income, provide better human resources for the country, promote the development of economy and society, and inject impetus into the sustainable development of human beings. The EI is the average years of education, which is calculated by the average of the total number of years of academic education received by a group in a specific region in a specific period.

(4)

Green Development Index (GDI)

The GDI is expressed as carbon emission intensity. Carbon emission intensity objectively reflects the progress of green development and is equal to the ratio of carbon dioxide emissions to GDP of a certain region in a certain period.

3.2. Index Calculation

Statistical indicators include positive indicators and inverse indicators, among which the carbon emission intensity belongs to the inverse indicator, while other indicators belong to positive indicators. In order to make the calculated indicators comparable, this paper conducts dimensionless processing for these indicators, adopts different processing formulas for positive and negative indicators, and normalizes all sub-indicators from 0 to 1. The calculation formula is shown in Formulas (1) and (2):

$$\mathrm{Positive}\mathrm{indicators}: {\mathrm{Y}}_{ij}=\frac{x_{ij}-\min \left(x_{ij}\right)}{\max \left(x_{ij}\right)-\min \left(x_{ij}\right)}$$

(1)

$$\mathrm{Negative}\mathrm{indicators}: {\mathrm{Y}}_{ij}=\frac{\max \left(x_{ij}\right)-x_{ij}}{\max \left(x_{ij}\right)-\min \left(x_{ij}\right)}$$

(2)

i represents different sub-indicators, j represents different provinces, $x_{ij}$ represents the original value, ${\mathrm{Y}}_{ij}$ represents the standardized value, $\max \left(x_{ij}\right)$ represents the maximum value of the sub-index, and $\min \left(x_{ij}\right)$ represents the minimum value of the sub-index.

Referring to the geometric mean method of calculating the Human Development Index in the 2018 report of the UNDP, the HSDI calculation formula in this paper is shown in Formula (3).

$$\mathrm{HSDI}={(II\times HI\times EI\times \mathrm{GDI})}^{1/4}$$

(3)

According to the definition, the $HSDI\in \left[0,1\right]$. The higher the value is, the higher the human sustainable development is.

3.3. Calculation Results

This paper calculated the annual HSDI of each province in China from 2005 to 2017 (except Tibet, HK, Macau and Taiwan, due to lack of data), as shown in

Table 1. The HSDI of each province from 2005 to 2017.

Province	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	Average
Beijing	0.60	0.63	0.67	0.68	0.70	0.72	0.76	0.79	0.82	0.83	0.86	0.89	0.93	0.76
Tianjin	0.52	0.55	0.57	0.61	0.63	0.65	0.71	0.74	0.76	0.78	0.80	0.83	0.86	0.69
Hebei	0.33	0.34	0.36	0.39	0.40	0.41	0.46	0.47	0.49	0.50	0.50	0.51	0.53	0.44
Shanxi	0.31	0.33	0.36	0.39	0.39	0.41	0.46	0.48	0.49	0.49	0.50	0.51	0.55	0.44
Neimenggu	0.31	0.34	0.39	0.42	0.45	0.48	0.54	0.56	0.57	0.59	0.60	0.63	0.61	0.50
Liaoning	0.39	0.41	0.44	0.47	0.49	0.51	0.56	0.59	0.62	0.63	0.63	0.59	0.61	0.53
Jilin	0.33	0.36	0.39	0.42	0.44	0.47	0.51	0.53	0.56	0.57	0.58	0.60	0.61	0.49
Heilongjiang	0.34	0.36	0.38	0.41	0.41	0.44	0.48	0.50	0.53	0.54	0.54	0.55	0.57	0.47
Shanghai	0.60	0.63	0.66	0.68	0.69	0.69	0.72	0.74	0.75	0.77	0.79	0.82	0.86	0.72
Jiangsu	0.40	0.43	0.46	0.48	0.50	0.53	0.58	0.60	0.63	0.64	0.66	0.68	0.70	0.56
Zhejiang	0.40	0.44	0.46	0.49	0.51	0.52	0.57	0.60	0.62	0.62	0.62	0.65	0.67	0.55
Anhui	0.24	0.27	0.28	0.31	0.33	0.35	0.41	0.44	0.46	0.48	0.49	0.50	0.52	0.39
Fujian	0.34	0.36	0.39	0.41	0.45	0.47	0.52	0.53	0.55	0.57	0.58	0.60	0.63	0.49
Jiangxi	0.24	0.28	0.31	0.34	0.36	0.36	0.43	0.45	0.48	0.49	0.50	0.51	0.53	0.41
Shandong	0.36	0.40	0.42	0.45	0.46	0.48	0.52	0.54	0.56	0.58	0.59	0.60	0.62	0.51
Henan	0.29	0.31	0.34	0.37	0.38	0.38	0.43	0.45	0.47	0.49	0.49	0.50	0.53	0.42
Hubei	0.28	0.32	0.35	0.38	0.40	0.42	0.47	0.50	0.52	0.53	0.56	0.57	0.59	0.45
Hunan	0.28	0.31	0.34	0.36	0.38	0.40	0.45	0.46	0.49	0.51	0.53	0.55	0.57	0.43
Guangdong	0.41	0.43	0.46	0.48	0.50	0.51	0.56	0.57	0.58	0.59	0.61	0.63	0.66	0.54
Guangxi	0.25	0.29	0.31	0.33	0.35	0.37	0.43	0.43	0.46	0.48	0.48	0.50	0.51	0.40
Hainan	0.12	0.33	0.35	0.37	0.39	0.41	0.46	0.49	0.50	0.52	0.53	0.54	0.57	0.43
Chongqing	0.28	0.31	0.34	0.37	0.39	0.41	0.47	0.49	0.51	0.54	0.55	0.58	0.60	0.45
Sichuan	0.23	0.27	0.30	0.32	0.34	0.36	0.41	0.44	0.45	0.46	0.48	0.48	0.51	0.39
Guizhou	0.13	0.16	0.19	0.22	0.23	0.24	0.30	0.32	0.36	0.38	0.38	0.40	0.44	0.29
Yunnan	0.14	0.17	0.19	0.21	0.23	0.25	0.29	0.32	0.34	0.35	0.37	0.38	0.41	0.28
Shaanxi	0.27	0.31	0.34	0.37	0.39	0.42	0.46	0.49	0.52	0.53	0.55	0.56	0.58	0.45
Gansu	0.18	0.20	0.23	0.26	0.27	0.30	0.35	0.37	0.39	0.41	0.41	0.43	0.44	0.33
Qinghai	0.12	0.21	0.23	0.26	0.28	0.29	0.34	0.35	0.39	0.40	0.39	0.41	0.43	0.32
Ningxia	0.22	0.27	0.30	0.34	0.36	0.37	0.42	0.43	0.46	0.46	0.48	0.51	0.52	0.39
Xinjiang	0.24	0.29	0.32	0.34	0.35	0.37	0.42	0.44	0.46	0.48	0.48	0.49	0.52	0.40

. The data comes from China Statistical Yearbook, China Environmental Statistics Yearbook, China Education Statistics Yearbook, National Bureau of Statistics, and the Statistical Yearbook of provinces in China, etc.

3.4. Results Analysis

As shown in Figure 1, the average HSDI of each province in China from 2005 to 2017 has increased significantly, showing an overall steady rise from 0.305 in 2005 to 0.589 in 2017, with an increase of 0.284 and a growth rate of 92.99%. It indicates that the Chinese government has made remarkable achievements in improving human sustainable development. However, it can also be found that with the improvement of HSDI, its growth rate decreased from 12.57% in 2006 to 3.75% in 2017. This indicates that it is difficult for HSDI to continue to increase.

As shown in Table 1, the top three provinces with the lowest average HSDI in 2005 are Hainan (0.120), Qinghai (0.121), and Guizhou (0.129), while the top three provinces with the lowest average HSDI in 2017 are Yunnan (0.407), Qinghai (0.432), and Guizhou (0.437). The top three provinces with the largest HSDI in 2005 are Shanghai (0.604), Beijing (0.596), and Tianjin (0.521), while the top three provinces with the largest HSDI in 2017 are Beijing (0.927), Shanghai (0.860), and Tianjin (0.856). Except Hainan, there was no significant change in the provinces with the highest or lowest HSDI. This shows that China’s sustainable human development has regional imbalance, and the provincial rankings of human sustainable development have changed little over the years. Furthermore, the regions with high sustainable human development are mainly concentrated in the eastern region, followed by the central region and the western region.

The top 5 provinces with the largest growth rate are Hainan (374%), Qinghai (257%), Guizhou (239%), Yunnan (187%) and Gansu (152%), while the top five provinces with the lowest increase are Shanghai (42%), Beijing (56%), Liaoning (56%), Hebei (59%) and Guangdong (61%). The human sustainable development of each province in China has been rising significantly. The human sustainable development of provinces in the central and western regions grows faster, while that in eastern provinces rises more slowly. This shows that the inter-regional gap of human sustainable development is narrowing.

4. Methods and Data

4.1. Variables

(1)

Explained variable. Human sustainable development (HSDI), which is measured by the logarithm of the HSDI to measure the regional human sustainable development, as shown in Section 3.3.

(2)

Explanatory variable. Environmental regulation (ER), which is measured by the logarithm of the proportion of total investment in environmental pollution control in GDP.

(3)

Mediating variable. Technology innovation (TI), measured by the logarithm of the number of invention patents granted per 10,000 people in the region.

(4)

Control variables. Human sustainable development is influenced by many factors. Besides environmental regulation, human sustainable development is also influenced by the following factors:

• The industrial structure (IND), which is measured by the logarithm of the proportion of the tertiary industry.
• The foreign direct investment (FDI), which is expressed by the logarithm of the proportion of actually utilized foreign direct investment in the GDP.

Since the data from 2018 onwards are not yet available, this paper uses the data of 30 provinces in China (except Tibet, HK, Macau and Taiwan, due to lack of data) from 2005 to 2017. Data are sourced from the National Bureau of Statistics, the China Statistical Yearbook, EPS database, etc. The general descriptive statistics of variables are shown in

Table 2. Descriptive statistics of variables.

Variable	Obs	Mean	Std.	Min	Max
lnIND	390	−0.824	0.218	−1.778	−0.478
lnFDI	390	−4.123	1.027	−7.867	−2.516
lnTI	390	−0.953	1.366	−3.505	3.045
lnER	390	−4.410	0.460	−5.809	−3.161
lnHSDI	390	−0.821	0.337	−2.122	−0.0755

.

4.2. Model Specification

(1)

Basic model

Based on the previous theoretical analysis, the econometric model constructed in this paper is shown in Formula (4).

$$HSD{I}_{it}={\alpha }_0+{\gamma }_0{\mathrm{ER}}_{it-1}+{\theta }_0{X}_{it}+{\epsilon }_{it}$$

(4)

In the formula, subscripts i, t are denoted as provinces and years. $HSD{I}_{it}$ represents human sustainable development, ${\mathrm{ER}}_{it}$ represents environmental regulation, and $X_{it}$ represents the control variables. Since the effect of environmental regulation on human sustainable development is a time-lag effect, this paper uses ${\mathrm{ER}}_{it-1}$ to estimate. ${\epsilon }_{it}$ was a random error term.

(2)

Mediating effect model

According to the literature review, environmental regulation can not only directly promote human sustainable development, but also indirectly promote human sustainable development through technology innovation. Following Lin et al. [35], this paper constructed the mediation effect test model, as shown in Formulas (5)–(7).

$$HSD{I}_{it}={\alpha }_0+{\gamma }_0{\mathrm{ER}}_{it-1}+{\theta }_0{X}_{it}+{\epsilon }_{it}$$

(5)

$$T{I}_{it}={\alpha }_1+{\gamma }_1{\mathrm{ER}}_{it-1}+{\theta }_1{X}_{it}+{\epsilon }_{it}$$

(6)

$$HSD{I}_{it}={\alpha }_2+{\gamma }_2{\mathrm{ER}}_{it-1}+{\beta }_{2}T{I}_{it}+{\theta }_2{X}_{it}+{\epsilon }_{it}$$

(7)

In the formula, subscripts i, t are denoted as provinces and years. $HSD{I}_{it}$ represents human sustainable development, $T{I}_{it}$ represents technology innovation, ${\mathrm{ER}}_{it}$ represents environmental regulation and $X_{it}$ represents the control variables. Since the effect of environmental regulation on human sustainable development is a time-lag effect, this paper uses ${\mathrm{ER}}_{it-1}$ to estimate. ${\epsilon }_{it}$ was a random error term.

(3)

Robustness model

The increase or decrease in human sustainable development has long-term effects, and there may be a trend of inertia. As a result, the human sustainable development of the current year may be correlated with the value of the previous year. The system-GMM can better solve the problems of the endogeneity and weak variables of instrumental variables, and the estimation results have little deviation [36]. Therefore, a two-step systems-GMM estimation method is used to test the robustness of the impact of environmental regulation on human sustainable development. The regression model is shown in Formula (8).

$$HSD{I}_{it}={\alpha }_3+{\beta }_{3}HSD{I}_{it-1}+{\gamma }_3{\mathrm{ER}}_{it-1}+{\theta }_3{X}_{it}+u_t+v_i+{\epsilon }_{it}$$

(8)

In the formula, $HSD{I}_{it}$ represents human sustainable development, Since the human sustainable development from the previous stage has an effect on the current human sustainable development, this paper includes $HSD{I}_{it-1}$ which is the first lag term of $HSD{I}_{it}$. ${\mathrm{ER}}_{it}$ represents environmental regulation, and $X_{it}$ represents the control variables. Since the effect of environmental regulation on human sustainable development is a time-lag effect, this paper uses ${\mathrm{ER}}_{it-1}$ to estimate. $u_t$ represented time fixed effect; $v_i$ represented individual fixed effect; and ${\epsilon }_{it}$ was a random error term.

5. Results and Discussion

5.1. Main Results

Table 3. Main regression results.

	(1)	(2)
	FE	RE
Variables	lnHSDI	lnHSDI
lnER	0.193 ***	0.168 ***
	(0.0258)	(0.0261)
lnIND	0.939 ***	1.007 ***
	(0.0769)	(0.0723)
lnFDI	−0.0742 ***	−0.00569
	(0.0184)	(0.0161)
Constant	0.581 ***	0.814 ***
	(0.159)	(0.155)
Observations	360	360
R-squared	0.471
Number of id	30	30

Notes: *** p < 0.01.

shows the estimation results of the benchmark model of the impact of environmental regulation on human sustainable development, where column (1) shows the results of the fixed-effects regression and column (2) shows the results of the random effects regression.

According to the results of Hausman test, this paper chooses the fixed effect model for analysis. The regression results in column (1) show that the estimated coefficient of environmental regulation is positive and significant at the 1% level, which means that environmental regulation can significantly improve human sustainable development. In addition, from the perspective of control variables, increasing the proportion of tertiary industry in a region will significantly improve the local sustainable human development, while increasing foreign investment will reduce the human sustainable development. Therefore, Hypothesis 1 is confirmed, and environmental regulation can improve human sustainable development.

5.2. Mediating Effect Test

The regression results of the mediating effect analysis are shown in

Table 4. Mediating effect regression results.

	(3)	(4)	(5)
Variables	lnHSDI	lnTI	lnHSDI
lnER	0.193 ***	0.725 ***	0.0468 ***
	(0.0258)	(0.111)	(0.0135)
lnTI			0.202 ***
			(0.00633)
lnIND	0.939 ***	5.016 ***	−0.0743
	(0.0769)	(0.332)	(0.0495)
lnFDI	−0.0742 ***	−0.289 ***	−0.0158 *
	(0.0184)	(0.0793)	(0.00926)
Constant	0.581 ***	5.542 ***	−0.538 ***
	(0.159)	(0.683)	(0.0857)
Observations	360	360	360
R-squared	0.471	0.530	0.872
Number of id	30	30	30

Notes: * p < 0.1, *** p < 0.01.

. Column (1) examines the overall impact of environmental regulation on human sustainable development. It can be seen that the environmental regulation coefficient is positive (0.193) and significant. Column (2) is the effect of environmental regulation on the intermediate variable technology innovation, and the coefficient is significantly positive (0.725). The coefficients on environmental regulation and innovation in column (3) are statistically positive (0.0468) and significant. The above three regression results prove the existence of mediating effects and technology innovation plays a partial mediating role. Thus, Hypothesis 2 is verified. That is, environmental regulation not only has a direct impact on human sustainable development, but also has an indirect impact through technology innovation.

5.3. Robustness Test

The regression results of the robustness test are shown in

Table 5. Robustness test regression results.

	(7)	(8)
Variables	lnHSDI	lnHSDI
L.lnHSDI	0.856 ***	0.844 ***
	(0.00158)	(0.00219)
lnER	0.00699 ***	0.0175 ***
	(0.00185)	(0.00230)
lnIND		0.0573 ***
		(0.00395)
lnFDI		0.0186 ***
		(0.00164)
Constant	−0.0301 ***	0.133 ***
	(0.00789)	(0.0155)
Observations	360	360
Number of id	30	30
Sargan test	29.78 (0.8814)	29.52 (0.8882)
AR (1)	−3.509 (0.0004)	−3.283 (0.0010)
AR (2)	0.353 (0.7242)	0.0935 (0.9255)

Notes: *** p < 0.01. AR (1), AR (2), and the Sargan test gave the p-value corresponding to the statistic.

. The Sargan test result shows that the p values are greater than 0.3, and the p values of AR (1) are less than 0.1, while the p values of AR (2) are greater than 0.2. It indicates that there is no second-order autocorrelation and the instrumental variables used in the regression are effective, which proves that the two-step system-GMM estimation method adopted in this paper is effective and the model setting is reasonable.

Column (7) is the regression result of environmental regulation on human sustainable development, and column (8) is the regression result after introducing control variables. The regression results of columns (7) and (8) show that environmental regulation can significantly improve human sustainable development, which is consistent with the regression results of the fixed effects model in Section 5.1. In addition, the estimated coefficients of L.lnHSDI in the above regression models are both significantly positive at the 1% confidence level, indicating that the change of HSDI has obvious persistence in time.

6. Conclusions and Policy Recommendations

6.1. Conclusions

This paper mainly studies the impact of environmental regulation on human sustainable development. Firstly, this paper constructed the HSDI by adding sustainable development to the HDI. Secondly, this paper uses statistical data to measure the human sustainable development of 31 provinces in China, and analyzes its current situation and evolution trend. In addition, this paper empirically analyzes the impact of environmental regulation on human sustainable development. Finally, this paper studies the impact path of environmental regulation on human sustainable development. The following conclusions are obtained.

Firstly, China has made great progress in the overall human sustainable development from 2005 to 2017. This result ties in well with previous studies, the sustainable development of China has been greatly improved [37]. However, the provincial rankings of human sustainable development have changed little over the years. The regions with high human sustainable development are still mainly distributed in the municipalities and eastern coastal cities, while the regions with low human sustainable development are still mainly distributed in the central and western regions. This may lead to various social problems and contradictions, and affect the further development of human sustainable development. Fortunately, the inter-regional gap of human sustainable development is narrowing.

Secondly, environmental regulation can significantly improve the human sustainable development. Environmental regulation not only has a direct impact on human sustainable development, but also has an indirect impact through technology innovation. In addition, the increase in the proportion of tertiary industry can also improve human sustainable development. The conclusion of this study is an extension of the important impact of environmental regulation on green eco-efficiency [32] and high-quality economic development [35]. It can provide suggestions for the government to formulate people-oriented development policies.

6.2. Policy Recommendations

At present, the human sustainable development in China is not balanced and still needs to be improved. In order to further improve the human sustainable development, this paper puts forward the following suggestions.

Firstly, China needs to further narrow regional differences while constantly improving the overall level of human sustainable development. To be specific, the government should take human sustainable development as the center, regularly observe the dynamics of human sustainable development in various regions and give timely feedback, optimize relevant policies, promote the realization of policy objectives and improve the implementation effect of policies.

Secondly, the government should strengthen environmental regulation to promote sustainable human development. The government should also make a development plan and formulate the target according to the special situation of the region, and implement the differentiated development strategy from compiling action plan to formulating corresponding improvement plan according to local conditions, so as to improve the accuracy and effectiveness of environmental regulation and continuously improve the human sustainable development.

Finally, the government should continuously promote technology innovation, adopt innovation-driven strategy, strengthen the construction of a technology innovation system, and give full play to the important mediating role of technology innovation in the relationship between environmental regulation and human sustainable development. In addition, the government should also promote the upgrading of the local industrial structure to further promote human sustainable development.

6.3. Limitations

The conclusions and policy recommendations in this paper can provide a reference for China and other countries. However, there are still many limitations in this paper. Firstly, due to lack of data, this paper only calculated the HSDI of China from 2005 to 2017. Secondly, this paper only verifies the impact of environmental regulation on sustainable human development in the context of China. Therefore, future research can be extended in two ways. First, new data sources can be sought to verify the impact of environmental regulation on human sustainable development beyond 2018. Secondly, data from other countries or regions can be used to verify the impact of environmental regulation on human sustainable development, so as to enhance the robustness of the conclusion.