# Study on the Coupling Relationship between Environmental Quality and Green Financial Economy Based on the Grey Correlation Analysis Model

Authors: Rui Ma; Liang Chen
Journal: Wireless Communications and Mobile Computing
 (2022)

---

## Abstract

Since the reform and opening up, there has been a great demand vacancy in the market. The development of green finance can just meet many market demands. Let it stand out among many financing schemes. As an innovative financial model that can effectively promote the global economy, green finance is of great significance to the global ecological economy and environmental state. In this article, we will discuss the economic coupling relationship between environmental quality and green finance. Because we lack a relatively perfect economic evaluation system, therefore we integrate green finance and environmental quality indicators, introduce them into relevant and suitable evaluation system indicators, and mainly analyze and judge based on the grey relational analysis model. The results show the following: (1) investigate the environmental quality and green financial comprehensive benefit development index of A, B, and C cities, judge the lagging types of the three cities, and evaluate the specific development status of the cities. (2) Collect data and calculate the coupling degree and coordination degree of cities. Their coupling levels and coordination types are summarized, respectively. (3) The higher the correlation between urban environmental quality and green financial indicators, the closer the relationship between the two indicators and the greater the mutual influence. (4) Sort them by grey relational degree. The correlation between Y1 and Z3 is the least, which is 0.55 and 0.552, respectively. Y3 can be correlated up to 0.655. The results of this paper are very good, and we get the result that green finance can promote the effective improvement of environmental quality.


---

## Body

## 1. Introduction

With the reform and development in recent decades, China’s economy keeps up with the development of science and technology and grows rapidly to the second place in the world. At the same time, environmental pollution, a by-product secretly produced behind the rapid development, gradually puzzles people’s normal work and life and hinders economic development. Because we neglected the importance of environmental protection when developing economy before, we did not pay attention to improving environmental quality. Nowadays, land desertification, earthquakes, water resources, smog, and other problems caused by rapid economic progress have led to the continuous deterioration of the environment, and people have begun to suffer the consequences and actively seek solutions. The concept of green finance is put forward in this situation. As an innovative financial development model, green finance can resolve the deep-seated contradiction between economic growth and environmental pollution and has been paid more and more attention in recent years. Based on the grey relational analysis model, this paper studies the economic coupling relationship between green finance and environmental quality. We refer to many documents as references. Literature [1] explains the development of green finance and the optimization and upgrading of industrial structure in western China. Literature [2] expounds the concept of promoting sustainable development with green financing. Literature [3] analyzes the relationship between eco-economic benefits and the correlation degree of financial support based on the financial scale, structure, and efficiency of Jiangsu Province. Literature [4] studies the influencing factors and strategies of green financial services to the real economy. Literature [5] studies the development and construction of green financial system on economic ecologicalization in Heilongjiang Province. Literature [6] introduces the coupling coordination model to measure the green finance-ecological environment system of urban agglomeration. Literature [7] analyzes and evaluates the effectiveness of green financial policy system by a double difference method. Reference [8] established a C-D function model to calculate relevant economic and ecological indicators. Literature [9] uses a grey relational method to calculate the relationship between offshore service outsourcing and its competitiveness in India. Literature [10] constructs an evaluation system suitable for the development of green finance in China. Literature [11] uses cluster analysis to construct the evaluation index system of finance-technology coupling vulnerability. Literature [12] uses coupling evaluation to calculate the development level of green finance and ecological environment in the three major economic circles. Literature [13] compiles a comprehensive index system of environmental quality to judge the relationship among green finance, environmental change, and economic growth. Literature [14] uses a grey relational analysis method to comprehensively analyze and evaluate the ecological city construction in Zhangye City. Literature [15] analyzes economic growth and environmental quality in Guizhou by grey relational grade.


## 2. Theoretical Basis

### 2.1. Green Finance Theory

Green finance is a financial policy that plays a great role in environmental protection and governance. It belongs to a kind of financing policy that emphasizes the quality of the living environment and the interests of the whole human being. When investing in peacetime, we must consider the problem of sustainable development and the potential environmental impact in the environment. Due to the rapid economic development before, many ecological environments were destroyed, resulting in a large amount of energy consumption, and the population showed a steep straight upward trend. It is also a difficult point to achieve rapid economic development on the premise of ensuring “green.” This is already a problem that most countries need to pay attention to, as shown in Figure1.Figure 1
Green finance.


### 2.2. Environmental Quality and Ecological Economy

Good and bad are the quality in “quality”; degree refers to the quantity in “quality.” Our existing environment has been produced by the earth since ancient times, and as a member of the earth, what we do on the earth will affect the “quality” of the earth’s environment to a certain extent.The green finance we want to develop is closely related to ecological economy. Human beings use principles and methods to call resources within the scope of ecological environment to promote the rapid development of social economy, thus realizing the value of resources. The concept of building a green and healthy economic model coincides with the concept of green finance, as shown in Figure2.Figure 2
Schematic diagram of the relationship among the three.


### 2.3. Coupling Coordination Theory

Generally speaking, coupling relationship refers to some kind of connection originated from physics and usually exists in electricity. Use this relationship to measure the affinity between systems. This system coupling shows a relatively balanced state of structure and function. This kind of benign state can be cycled, and the system can complement each other and finally achieve an orderly state process.Coordination is an important point in this theory, and the coupling state of the system needs coordination very much. If the system is not coordinated, its development will not be smooth and successful. Develop in coordination and gradually reach a balanced state between things. This is the most ideal ultimate goal. Through this purpose, people evaluate and judge things, solve uncoordinated problems encountered in the process, and solve various contradictions, so as to develop scientifically and orderly.


### 2.4. Complex System Theory

A complex system is a system composed of a large number of units interacting with each other, and its activities are nonlinear, often forming complex organizations with numerous levels. Compared with a complex system, a simple system is a system that simplifies and describes laws with the reductionist thinking of classical physics.Complex system theory can highlight the field characteristics of various research topics and plays a more important role than simple systems. It can help researchers to look at the problems waiting to be studied as a complete whole, in which the relationship of various elements is interrelated and interacted with each other, rather than being single, independent, and irrelevant. It can be said that the function and development of the system are the result determined by the development of each subsystem complementing each other. This theory has helped many researchers to make use of its complexity and complete the theoretical support of research topics.We regard environmental quality as complex system A; think of green finance as complex system B. We combine A and B systems and form an A-B composite system through continuous development and change, that is, an environmental quality-green financial economy composite system. This can reflect the complex characteristics between A and B systems, support the theory of this paper, and make a good foreshadowing for the later research.


## 2.1. Green Finance Theory

Green finance is a financial policy that plays a great role in environmental protection and governance. It belongs to a kind of financing policy that emphasizes the quality of the living environment and the interests of the whole human being. When investing in peacetime, we must consider the problem of sustainable development and the potential environmental impact in the environment. Due to the rapid economic development before, many ecological environments were destroyed, resulting in a large amount of energy consumption, and the population showed a steep straight upward trend. It is also a difficult point to achieve rapid economic development on the premise of ensuring “green.” This is already a problem that most countries need to pay attention to, as shown in Figure1.Figure 1
Green finance.


## 2.2. Environmental Quality and Ecological Economy

Good and bad are the quality in “quality”; degree refers to the quantity in “quality.” Our existing environment has been produced by the earth since ancient times, and as a member of the earth, what we do on the earth will affect the “quality” of the earth’s environment to a certain extent.The green finance we want to develop is closely related to ecological economy. Human beings use principles and methods to call resources within the scope of ecological environment to promote the rapid development of social economy, thus realizing the value of resources. The concept of building a green and healthy economic model coincides with the concept of green finance, as shown in Figure2.Figure 2
Schematic diagram of the relationship among the three.


## 2.3. Coupling Coordination Theory

Generally speaking, coupling relationship refers to some kind of connection originated from physics and usually exists in electricity. Use this relationship to measure the affinity between systems. This system coupling shows a relatively balanced state of structure and function. This kind of benign state can be cycled, and the system can complement each other and finally achieve an orderly state process.Coordination is an important point in this theory, and the coupling state of the system needs coordination very much. If the system is not coordinated, its development will not be smooth and successful. Develop in coordination and gradually reach a balanced state between things. This is the most ideal ultimate goal. Through this purpose, people evaluate and judge things, solve uncoordinated problems encountered in the process, and solve various contradictions, so as to develop scientifically and orderly.


## 2.4. Complex System Theory

A complex system is a system composed of a large number of units interacting with each other, and its activities are nonlinear, often forming complex organizations with numerous levels. Compared with a complex system, a simple system is a system that simplifies and describes laws with the reductionist thinking of classical physics.Complex system theory can highlight the field characteristics of various research topics and plays a more important role than simple systems. It can help researchers to look at the problems waiting to be studied as a complete whole, in which the relationship of various elements is interrelated and interacted with each other, rather than being single, independent, and irrelevant. It can be said that the function and development of the system are the result determined by the development of each subsystem complementing each other. This theory has helped many researchers to make use of its complexity and complete the theoretical support of research topics.We regard environmental quality as complex system A; think of green finance as complex system B. We combine A and B systems and form an A-B composite system through continuous development and change, that is, an environmental quality-green financial economy composite system. This can reflect the complex characteristics between A and B systems, support the theory of this paper, and make a good foreshadowing for the later research.


## 3. Study on the Coupling Relationship between Environmental Quality and Green Financial Economy

### 3.1. Establishment of the Index System

#### 3.1.1. Construction Principle

When constructing the evaluation index system of environmental quality and green finance, we need to follow certain principles: (1) systematic principle, (2) dynamic principle [16], (3) typicality principle [17], (4) the principle of conciseness and scientificalness, (5) principle of comparability, (6) operable principle, (7) principle of quantification, and (8) comprehensive principle. Through these principles, we can create a fair, comprehensive, scientific, and coordinated index system to help us study better.


#### 3.1.2. Index Weight

(1)
Standardization treatment of range methodXij represents the index value of item i in the j-th region; Yij represents the standardized data (i=1,2,⋯,m;j=1,2,⋯,n).Positive indicators [18]:
(1)Yij=Xij−minXijmaxXij−minXij.Negative indicators:(2)Yij=maxXij−XijmaxXij−minXij.(2)
Weight calculation by entropy methodThe normalized matrix is obtained:(3)X′=Xijm×n.Calculate entropyHj [19]:
(4)Hj=−K∑i=1mfij∗lnfiji=1,2,⋯,m;j−1,2,⋯,n.Among them,K=lnm−1; at the same time, in order to avoid the meaninglessness of lnfij, there is
(5)fij=1+Xij′∑i=1m1+Xij′.(3)
Calculate the information weightwj′(6)wj′=1−Hjn−∑j=1nHj.


#### 3.1.3. TOPSIS Evaluation Method

(1)
Processing data(7)yij′=xij∑i=1mxij,(8)Y′=yijm×n,(9)wj=w1,w2,w3,⋯,wn.Formula (7) is constructed as a normalized decision matrix of formula (8), and then, the matrix is multiplied by formula (9). After processing, we can get the weighted normalized decision matrix as
(10)A=aijm×n=wj×yij′m×n.(2)
Determine positive and negative ideal solutions(11)aj+=maxa1j,a2j,a3j,⋯,amj,(12)aj−=mina1j,a2j,a3j,⋯,amj.(3)
Solving distance of the Euclidean formula(13)dj+=∑j=1naij−aj+2,(14)dj−=∑j=1naij−aj−2.(4)
Calculate closenessB [20](15)Bi=dj−dj++dj−0≤Bi≤1.


#### 3.1.4. Comprehensive Index System

Because of the introduction of complex system theory, we construct a complex system of environmental quality-green financial economy, so this paper integrates the two indicators as comprehensive indicators to build the system, as shown in Tables1 and 2.Table 1
Construction of the comprehensive evaluation system.
Comprehensive indexCriterion layerAgent indexAttributeGreen financeGreen credit [21]Proportion of interest expenses of high energy-consuming industriesNegativeGreen investmentProportion of environmental protection investmentForwardEnvironmental qualityEnergy consumption [22]Total energy consumptionNegativePer capita energy consumptionNegativeTotal energy consumption per unit GDPNegativeEnvironmental pollutionTotal industrial emissionsNegativeTotal amount of industrial solid wasteNegativeTotal amount of wastewater discharge [23]NegativeEnvironmental governanceTotal green coverage area [24]ForwardPer capita green areaForwardHarmless rate of domestic garbageForwardProportion of investment expenditure on environmental pollution controlForwardTable 2
Variable setting of the index system.
VariableNameSymbolControl variableOptimization of industrial structure [25]LISPopulation densityLPDEnergy consumption structureLESLevel of economic developmentLPGDPThreshold variableLevel of economic developmentLPGDPGreen technology innovation levelLGTMediating variableGreen technology innovation levelLGTCore explanatory variableGreen financial developmentGFExplained variableEcological environment qualityEQ


### 3.2. Evaluation Model of Comprehensive Development Level

In order to fully reflect the economic coupling relationship between environmental quality and green finance, we also adopt a comprehensive evaluation index method. By calculation, we can get the corresponding value.(16)Ui=∑i=1mBijUi=Ei,Fi,(17)TEF=αEi+δFi.Infer the comprehensive development, as shown in Table3.Table 3
Discrimination table of the lag type.
ContrastE<FE=FE>FType of lagThe development of green finance lags behindSynchronous development typeLag of environmental quality development


### 3.3. Coupling Model Construction

(1)
Coupling degree(18)C=2∗u1u2u1+u221/2.The larger the calculated results, the stronger the coupling and the greater the mutual influence. We delimit the range of the calculation results of the coupling degree, as shown in Table4.
(2)
Coupling coordination degree(19)T=αu1+βu2,(20)D=CT.(3)
Coupling priority(21)p=u1u2.Table 4
Value range of the coupling degree.
Stage of coupling stateValue range of the coupling degreeLow coupling0,0.3Antagonism0.3,0.5Running-in0.5,0.8Highly coupled0.8,1.0


### 3.4. Analysis of the Grey Relational Analysis Model

(1)
Reference sequence and comparison sequence(22)Y=Yq,q=1,2,⋯,n,(23)Xi=Xiq,q=1,2,⋯,n,i=1,2,⋯,m.(2)
Dimensionless data(24)Y∗=YqYl,q=1,2,⋯,n,i=1,2,⋯,m,(25)X∗=XiqXil,q=1,2,⋯,n,i=1,2,⋯,m.(3)
Absolute difference(26)Δik=Yi∗−Xi∗,i=1,⋯,n,k=1,⋯,m.(4)
Correlation coefficient(27)ςiq=miniminqΔiq+ρmaximaxqΔiqΔiq+ρmaximaxqΔiq.(5)
Correlation degree(28)ri=1N∑q=1Nςiq,i=1,⋯,m,q=1,⋯,n.(6)
Correlation degree sortingThe larger the value, the higher the ranking order and the closer the connection between the reference sequence and comparison sequence. On the contrary, the more distant it is.


## 3.1. Establishment of the Index System

### 3.1.1. Construction Principle

When constructing the evaluation index system of environmental quality and green finance, we need to follow certain principles: (1) systematic principle, (2) dynamic principle [16], (3) typicality principle [17], (4) the principle of conciseness and scientificalness, (5) principle of comparability, (6) operable principle, (7) principle of quantification, and (8) comprehensive principle. Through these principles, we can create a fair, comprehensive, scientific, and coordinated index system to help us study better.


### 3.1.2. Index Weight

(1)
Standardization treatment of range methodXij represents the index value of item i in the j-th region; Yij represents the standardized data (i=1,2,⋯,m;j=1,2,⋯,n).Positive indicators [18]:
(1)Yij=Xij−minXijmaxXij−minXij.Negative indicators:(2)Yij=maxXij−XijmaxXij−minXij.(2)
Weight calculation by entropy methodThe normalized matrix is obtained:(3)X′=Xijm×n.Calculate entropyHj [19]:
(4)Hj=−K∑i=1mfij∗lnfiji=1,2,⋯,m;j−1,2,⋯,n.Among them,K=lnm−1; at the same time, in order to avoid the meaninglessness of lnfij, there is
(5)fij=1+Xij′∑i=1m1+Xij′.(3)
Calculate the information weightwj′(6)wj′=1−Hjn−∑j=1nHj.


### 3.1.3. TOPSIS Evaluation Method

(1)
Processing data(7)yij′=xij∑i=1mxij,(8)Y′=yijm×n,(9)wj=w1,w2,w3,⋯,wn.Formula (7) is constructed as a normalized decision matrix of formula (8), and then, the matrix is multiplied by formula (9). After processing, we can get the weighted normalized decision matrix as
(10)A=aijm×n=wj×yij′m×n.(2)
Determine positive and negative ideal solutions(11)aj+=maxa1j,a2j,a3j,⋯,amj,(12)aj−=mina1j,a2j,a3j,⋯,amj.(3)
Solving distance of the Euclidean formula(13)dj+=∑j=1naij−aj+2,(14)dj−=∑j=1naij−aj−2.(4)
Calculate closenessB [20](15)Bi=dj−dj++dj−0≤Bi≤1.


### 3.1.4. Comprehensive Index System

Because of the introduction of complex system theory, we construct a complex system of environmental quality-green financial economy, so this paper integrates the two indicators as comprehensive indicators to build the system, as shown in Tables1 and 2.Table 1
Construction of the comprehensive evaluation system.
Comprehensive indexCriterion layerAgent indexAttributeGreen financeGreen credit [21]Proportion of interest expenses of high energy-consuming industriesNegativeGreen investmentProportion of environmental protection investmentForwardEnvironmental qualityEnergy consumption [22]Total energy consumptionNegativePer capita energy consumptionNegativeTotal energy consumption per unit GDPNegativeEnvironmental pollutionTotal industrial emissionsNegativeTotal amount of industrial solid wasteNegativeTotal amount of wastewater discharge [23]NegativeEnvironmental governanceTotal green coverage area [24]ForwardPer capita green areaForwardHarmless rate of domestic garbageForwardProportion of investment expenditure on environmental pollution controlForwardTable 2
Variable setting of the index system.
VariableNameSymbolControl variableOptimization of industrial structure [25]LISPopulation densityLPDEnergy consumption structureLESLevel of economic developmentLPGDPThreshold variableLevel of economic developmentLPGDPGreen technology innovation levelLGTMediating variableGreen technology innovation levelLGTCore explanatory variableGreen financial developmentGFExplained variableEcological environment qualityEQ


## 3.1.1. Construction Principle

When constructing the evaluation index system of environmental quality and green finance, we need to follow certain principles: (1) systematic principle, (2) dynamic principle [16], (3) typicality principle [17], (4) the principle of conciseness and scientificalness, (5) principle of comparability, (6) operable principle, (7) principle of quantification, and (8) comprehensive principle. Through these principles, we can create a fair, comprehensive, scientific, and coordinated index system to help us study better.


## 3.1.2. Index Weight

(1)
Standardization treatment of range methodXij represents the index value of item i in the j-th region; Yij represents the standardized data (i=1,2,⋯,m;j=1,2,⋯,n).Positive indicators [18]:
(1)Yij=Xij−minXijmaxXij−minXij.Negative indicators:(2)Yij=maxXij−XijmaxXij−minXij.(2)
Weight calculation by entropy methodThe normalized matrix is obtained:(3)X′=Xijm×n.Calculate entropyHj [19]:
(4)Hj=−K∑i=1mfij∗lnfiji=1,2,⋯,m;j−1,2,⋯,n.Among them,K=lnm−1; at the same time, in order to avoid the meaninglessness of lnfij, there is
(5)fij=1+Xij′∑i=1m1+Xij′.(3)
Calculate the information weightwj′(6)wj′=1−Hjn−∑j=1nHj.


## 3.1.3. TOPSIS Evaluation Method

(1)
Processing data(7)yij′=xij∑i=1mxij,(8)Y′=yijm×n,(9)wj=w1,w2,w3,⋯,wn.Formula (7) is constructed as a normalized decision matrix of formula (8), and then, the matrix is multiplied by formula (9). After processing, we can get the weighted normalized decision matrix as
(10)A=aijm×n=wj×yij′m×n.(2)
Determine positive and negative ideal solutions(11)aj+=maxa1j,a2j,a3j,⋯,amj,(12)aj−=mina1j,a2j,a3j,⋯,amj.(3)
Solving distance of the Euclidean formula(13)dj+=∑j=1naij−aj+2,(14)dj−=∑j=1naij−aj−2.(4)
Calculate closenessB [20](15)Bi=dj−dj++dj−0≤Bi≤1.


## 3.1.4. Comprehensive Index System

Because of the introduction of complex system theory, we construct a complex system of environmental quality-green financial economy, so this paper integrates the two indicators as comprehensive indicators to build the system, as shown in Tables1 and 2.Table 1
Construction of the comprehensive evaluation system.
Comprehensive indexCriterion layerAgent indexAttributeGreen financeGreen credit [21]Proportion of interest expenses of high energy-consuming industriesNegativeGreen investmentProportion of environmental protection investmentForwardEnvironmental qualityEnergy consumption [22]Total energy consumptionNegativePer capita energy consumptionNegativeTotal energy consumption per unit GDPNegativeEnvironmental pollutionTotal industrial emissionsNegativeTotal amount of industrial solid wasteNegativeTotal amount of wastewater discharge [23]NegativeEnvironmental governanceTotal green coverage area [24]ForwardPer capita green areaForwardHarmless rate of domestic garbageForwardProportion of investment expenditure on environmental pollution controlForwardTable 2
Variable setting of the index system.
VariableNameSymbolControl variableOptimization of industrial structure [25]LISPopulation densityLPDEnergy consumption structureLESLevel of economic developmentLPGDPThreshold variableLevel of economic developmentLPGDPGreen technology innovation levelLGTMediating variableGreen technology innovation levelLGTCore explanatory variableGreen financial developmentGFExplained variableEcological environment qualityEQ


## 3.2. Evaluation Model of Comprehensive Development Level

In order to fully reflect the economic coupling relationship between environmental quality and green finance, we also adopt a comprehensive evaluation index method. By calculation, we can get the corresponding value.(16)Ui=∑i=1mBijUi=Ei,Fi,(17)TEF=αEi+δFi.Infer the comprehensive development, as shown in Table3.Table 3
Discrimination table of the lag type.
ContrastE<FE=FE>FType of lagThe development of green finance lags behindSynchronous development typeLag of environmental quality development


## 3.3. Coupling Model Construction

(1)
Coupling degree(18)C=2∗u1u2u1+u221/2.The larger the calculated results, the stronger the coupling and the greater the mutual influence. We delimit the range of the calculation results of the coupling degree, as shown in Table4.
(2)
Coupling coordination degree(19)T=αu1+βu2,(20)D=CT.(3)
Coupling priority(21)p=u1u2.Table 4
Value range of the coupling degree.
Stage of coupling stateValue range of the coupling degreeLow coupling0,0.3Antagonism0.3,0.5Running-in0.5,0.8Highly coupled0.8,1.0


## 3.4. Analysis of the Grey Relational Analysis Model

(1)
Reference sequence and comparison sequence(22)Y=Yq,q=1,2,⋯,n,(23)Xi=Xiq,q=1,2,⋯,n,i=1,2,⋯,m.(2)
Dimensionless data(24)Y∗=YqYl,q=1,2,⋯,n,i=1,2,⋯,m,(25)X∗=XiqXil,q=1,2,⋯,n,i=1,2,⋯,m.(3)
Absolute difference(26)Δik=Yi∗−Xi∗,i=1,⋯,n,k=1,⋯,m.(4)
Correlation coefficient(27)ςiq=miniminqΔiq+ρmaximaxqΔiqΔiq+ρmaximaxqΔiq.(5)
Correlation degree(28)ri=1N∑q=1Nςiq,i=1,⋯,m,q=1,⋯,n.(6)
Correlation degree sortingThe larger the value, the higher the ranking order and the closer the connection between the reference sequence and comparison sequence. On the contrary, the more distant it is.


## 4. Experimental Analysis

### 4.1. Comprehensive Benefit Index Analysis

#### 4.1.1. Single-City Analysis

We choose the data of a total of ten years from 2012 to 2021 to analyze and evaluate this certain city. Examine its environmental quality and green financial development index. The main purpose of this test is to do a pretest, so as to explore the accuracy of the two indicators, as shown in Figure3.Figure 3
Comprehensive benefit index—single city.The overall trend of the two development indicators is on the rise. Only from 2013 to 2014, the development of environmental quality was relatively unstable, and there was a certain decline in development; the development of green finance in 2015 is excellent. This shows that the development of the city is very good, and the two indicators complement each other and influence together.


#### 4.1.2. Multicity Analysis

In this section, we choose three cities with different development situations from 2017 to 2021. After collecting relevant statistics, the experimental data are processed. Finally, the evaluation value is calculated by the TOPSIS comprehensive evaluation method, and then, the comprehensive benefit index is calculated by using a coupling model. Among them, we set the environmental quality evaluation index asE and set the green financial evaluation index as F. The corresponding indexes of A city are set as E1 and F1; correspondingly, those of city B are E2 and F2; those of city C are E3 and F3. This paper investigates the environmental quality and green financial development index of A, B, and C cities and judges the lagging types of the three cities.We use chart data to show the economic development level relationship between environmental quality and green finance in A, B, and C cities. The processed data of the three cities are judged according to the lag type discrimination table, as shown in Figure4.Figure 4
Comprehensive benefit index—multiple cities.We can find that the development and changes of environmental quality and green finance in the three cities are very uneven, unbalanced, and unstable. For A city, the index inE1 index in 2018 is as high as 0.5347, which is the year with the highest development level in five years; except for 2018, the overall environmental quality level shows a slow upward trend. From 2017 to 2020, the F1 index showed an upward trend, but by 2021, the development of green finance showed a cliff-like decline, and the index level was even lower than that in 2019, showing a retrogressive state. Therefore, combined with E1 and F1 index data, we can judge that city A belongs to the type of lagging development of green finance.For city B, theE2 index is generally balanced, without much development and change; the development of the F2 index in five years is fast and slow, and the data is very unstable. In view of this, we can judge that city B belongs to the lagging type of environmental quality development.TheE3 index first gradually declined from 2017, and then, the index level began to rise in 2021. The F3 index is to continuously improve the development level of green finance in five years. It gradually increased from the lowest of only 0.3143 to 0.5087. We judge that city C belongs to the type of lagging development of green finance from 2017 to 2018. From 2019 to 2021, it belongs to the type of lagging development of environmental quality.


### 4.2. Coupling Coordination Degree Analysis

After analyzing the comprehensive benefit index of A, B, and C cities from 2017 to 2021, similarly, we need to calculate their coupling degree and coordination degree and then make a further analysis of urban economic development. Set the comprehensive economic index asT, the coupling degree is C, and the coupling coordination degree is D, as shown in Figures 5–7.Figure 5
Coupling coordination degree—A city.Figure 6
Coupling coordination degree—B city.Figure 7
Coupling coordination degree—C city.The coupling and coordination curve of A city grows slowly until 2020 and then begins to decline in 2021. The curve of city B is very unstable, and the overall trend is “W,” and the curve shows a downward and upward trend alternately. The overall trend of the C city curve has been rising. After calculating the corresponding data of the coupling degree and coordination degree of A, B, and C cities, we summarize the coupling level and coordination type of these three cities, respectively, as shown in Tables5–7.Table 5
Judgment of the coupling level and coordination type—A city.
YearCoupling levelCoordination typeA city2017Low-level coupling stageMild disorder2018Antagonistic stageMild disorder2019Antagonistic stageOn the verge of maladjustment2020Antagonistic stageOn the verge of maladjustment2021Antagonistic stageMild disorderTable 6
Judgment of the coupling level and coordination type—B city.
YearCoupling levelCoordination typeB city2017Antagonistic stageMild disorder2018Low-level coupling stageModerate disorder2019Antagonistic stageMild disorder2020Low-level coupling stageModerate disorder2021Low-level coupling stageMild disorderTable 7
Judgment of the coupling level and coordination type—C city.
YearCoupling levelCoordination typeC city2017Antagonistic stageMild disorder2018Antagonistic stageOn the verge of maladjustment2019Antagonistic stageOn the verge of maladjustment2020Antagonistic stageOn the verge of maladjustment2021Antagonistic stageOn the verge of maladjustment


### 4.3. Grey Relational Analysis

Here, we aim to explore the grey correlation between environmental quality and green finance. It is mainly divided into 9 indicators according to environmental quality. For convenience, they are named Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9, respectively. Green finance is divided into three indicators, namely, Y1, Y2, and Y3, respectively. After calculating the grey relational degree, we need to divide the strength and weakness of the grey relational degree, as shown in Table8.Table 8
Grey relational grade division method.
Partition intervalCorrelation degree0<D<0.35Weak correlation0.35<D<0.65Medium correlation0.65<D<0.85Strong correlation0.85<D<1.0Strong correlationWe calculate the grey correlation degree of each index of the city. The higher the correlation degree, the closer the relationship between the two indexes and the greater the influence on each other. We can find that there is a strong correlation between Z1 and Y3. There is a strong correlation between Z2 and Y2; Z3 was moderately correlated with Y1; there is a strong correlation between Z4 and Y3; there is a strong correlation between Z5 and Y2; there is a strong correlation between Z6 and Y3; there is a strong correlation between Z7 and Y3; there is a strong correlation between Z8 and Y2; there is a strong correlation between Z9 and Y2, as shown in Figure8.Figure 8
Correlation degree of each index.Finally, the average grey correlation degree of each index is sorted. Among them, except the Y3 index is a strong correlation index, other indexes are medium correlation indexes. The correlation between Y1 and Z3 is the least, which is 0.55 and 0.552, respectively. The correlation of the Y3 index is as high as 0.655, as shown in Figure9.Figure 9
Sorting of the average correlation degree.


## 4.1. Comprehensive Benefit Index Analysis

### 4.1.1. Single-City Analysis

We choose the data of a total of ten years from 2012 to 2021 to analyze and evaluate this certain city. Examine its environmental quality and green financial development index. The main purpose of this test is to do a pretest, so as to explore the accuracy of the two indicators, as shown in Figure3.Figure 3
Comprehensive benefit index—single city.The overall trend of the two development indicators is on the rise. Only from 2013 to 2014, the development of environmental quality was relatively unstable, and there was a certain decline in development; the development of green finance in 2015 is excellent. This shows that the development of the city is very good, and the two indicators complement each other and influence together.


### 4.1.2. Multicity Analysis

In this section, we choose three cities with different development situations from 2017 to 2021. After collecting relevant statistics, the experimental data are processed. Finally, the evaluation value is calculated by the TOPSIS comprehensive evaluation method, and then, the comprehensive benefit index is calculated by using a coupling model. Among them, we set the environmental quality evaluation index asE and set the green financial evaluation index as F. The corresponding indexes of A city are set as E1 and F1; correspondingly, those of city B are E2 and F2; those of city C are E3 and F3. This paper investigates the environmental quality and green financial development index of A, B, and C cities and judges the lagging types of the three cities.We use chart data to show the economic development level relationship between environmental quality and green finance in A, B, and C cities. The processed data of the three cities are judged according to the lag type discrimination table, as shown in Figure4.Figure 4
Comprehensive benefit index—multiple cities.We can find that the development and changes of environmental quality and green finance in the three cities are very uneven, unbalanced, and unstable. For A city, the index inE1 index in 2018 is as high as 0.5347, which is the year with the highest development level in five years; except for 2018, the overall environmental quality level shows a slow upward trend. From 2017 to 2020, the F1 index showed an upward trend, but by 2021, the development of green finance showed a cliff-like decline, and the index level was even lower than that in 2019, showing a retrogressive state. Therefore, combined with E1 and F1 index data, we can judge that city A belongs to the type of lagging development of green finance.For city B, theE2 index is generally balanced, without much development and change; the development of the F2 index in five years is fast and slow, and the data is very unstable. In view of this, we can judge that city B belongs to the lagging type of environmental quality development.TheE3 index first gradually declined from 2017, and then, the index level began to rise in 2021. The F3 index is to continuously improve the development level of green finance in five years. It gradually increased from the lowest of only 0.3143 to 0.5087. We judge that city C belongs to the type of lagging development of green finance from 2017 to 2018. From 2019 to 2021, it belongs to the type of lagging development of environmental quality.


## 4.1.1. Single-City Analysis

We choose the data of a total of ten years from 2012 to 2021 to analyze and evaluate this certain city. Examine its environmental quality and green financial development index. The main purpose of this test is to do a pretest, so as to explore the accuracy of the two indicators, as shown in Figure3.Figure 3
Comprehensive benefit index—single city.The overall trend of the two development indicators is on the rise. Only from 2013 to 2014, the development of environmental quality was relatively unstable, and there was a certain decline in development; the development of green finance in 2015 is excellent. This shows that the development of the city is very good, and the two indicators complement each other and influence together.


## 4.1.2. Multicity Analysis

In this section, we choose three cities with different development situations from 2017 to 2021. After collecting relevant statistics, the experimental data are processed. Finally, the evaluation value is calculated by the TOPSIS comprehensive evaluation method, and then, the comprehensive benefit index is calculated by using a coupling model. Among them, we set the environmental quality evaluation index asE and set the green financial evaluation index as F. The corresponding indexes of A city are set as E1 and F1; correspondingly, those of city B are E2 and F2; those of city C are E3 and F3. This paper investigates the environmental quality and green financial development index of A, B, and C cities and judges the lagging types of the three cities.We use chart data to show the economic development level relationship between environmental quality and green finance in A, B, and C cities. The processed data of the three cities are judged according to the lag type discrimination table, as shown in Figure4.Figure 4
Comprehensive benefit index—multiple cities.We can find that the development and changes of environmental quality and green finance in the three cities are very uneven, unbalanced, and unstable. For A city, the index inE1 index in 2018 is as high as 0.5347, which is the year with the highest development level in five years; except for 2018, the overall environmental quality level shows a slow upward trend. From 2017 to 2020, the F1 index showed an upward trend, but by 2021, the development of green finance showed a cliff-like decline, and the index level was even lower than that in 2019, showing a retrogressive state. Therefore, combined with E1 and F1 index data, we can judge that city A belongs to the type of lagging development of green finance.For city B, theE2 index is generally balanced, without much development and change; the development of the F2 index in five years is fast and slow, and the data is very unstable. In view of this, we can judge that city B belongs to the lagging type of environmental quality development.TheE3 index first gradually declined from 2017, and then, the index level began to rise in 2021. The F3 index is to continuously improve the development level of green finance in five years. It gradually increased from the lowest of only 0.3143 to 0.5087. We judge that city C belongs to the type of lagging development of green finance from 2017 to 2018. From 2019 to 2021, it belongs to the type of lagging development of environmental quality.


## 4.2. Coupling Coordination Degree Analysis

After analyzing the comprehensive benefit index of A, B, and C cities from 2017 to 2021, similarly, we need to calculate their coupling degree and coordination degree and then make a further analysis of urban economic development. Set the comprehensive economic index asT, the coupling degree is C, and the coupling coordination degree is D, as shown in Figures 5–7.Figure 5
Coupling coordination degree—A city.Figure 6
Coupling coordination degree—B city.Figure 7
Coupling coordination degree—C city.The coupling and coordination curve of A city grows slowly until 2020 and then begins to decline in 2021. The curve of city B is very unstable, and the overall trend is “W,” and the curve shows a downward and upward trend alternately. The overall trend of the C city curve has been rising. After calculating the corresponding data of the coupling degree and coordination degree of A, B, and C cities, we summarize the coupling level and coordination type of these three cities, respectively, as shown in Tables5–7.Table 5
Judgment of the coupling level and coordination type—A city.
YearCoupling levelCoordination typeA city2017Low-level coupling stageMild disorder2018Antagonistic stageMild disorder2019Antagonistic stageOn the verge of maladjustment2020Antagonistic stageOn the verge of maladjustment2021Antagonistic stageMild disorderTable 6
Judgment of the coupling level and coordination type—B city.
YearCoupling levelCoordination typeB city2017Antagonistic stageMild disorder2018Low-level coupling stageModerate disorder2019Antagonistic stageMild disorder2020Low-level coupling stageModerate disorder2021Low-level coupling stageMild disorderTable 7
Judgment of the coupling level and coordination type—C city.
YearCoupling levelCoordination typeC city2017Antagonistic stageMild disorder2018Antagonistic stageOn the verge of maladjustment2019Antagonistic stageOn the verge of maladjustment2020Antagonistic stageOn the verge of maladjustment2021Antagonistic stageOn the verge of maladjustment


## 4.3. Grey Relational Analysis

Here, we aim to explore the grey correlation between environmental quality and green finance. It is mainly divided into 9 indicators according to environmental quality. For convenience, they are named Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9, respectively. Green finance is divided into three indicators, namely, Y1, Y2, and Y3, respectively. After calculating the grey relational degree, we need to divide the strength and weakness of the grey relational degree, as shown in Table8.Table 8
Grey relational grade division method.
Partition intervalCorrelation degree0<D<0.35Weak correlation0.35<D<0.65Medium correlation0.65<D<0.85Strong correlation0.85<D<1.0Strong correlationWe calculate the grey correlation degree of each index of the city. The higher the correlation degree, the closer the relationship between the two indexes and the greater the influence on each other. We can find that there is a strong correlation between Z1 and Y3. There is a strong correlation between Z2 and Y2; Z3 was moderately correlated with Y1; there is a strong correlation between Z4 and Y3; there is a strong correlation between Z5 and Y2; there is a strong correlation between Z6 and Y3; there is a strong correlation between Z7 and Y3; there is a strong correlation between Z8 and Y2; there is a strong correlation between Z9 and Y2, as shown in Figure8.Figure 8
Correlation degree of each index.Finally, the average grey correlation degree of each index is sorted. Among them, except the Y3 index is a strong correlation index, other indexes are medium correlation indexes. The correlation between Y1 and Z3 is the least, which is 0.55 and 0.552, respectively. The correlation of the Y3 index is as high as 0.655, as shown in Figure9.Figure 9
Sorting of the average correlation degree.


## 5. Conclusion

The environmental quality problem following the economic growth is an inherent contradiction and an urgent problem to be solved. In this article, we focus on environmental quality, explain the relevant methods and concepts in theory, and sort out the index system of green finance and environmental quality that adapts to the actual situation. Evaluate and judge the coupling relationship between the two economies. The results show the following:(1)
Investigate the environmental quality and green finance comprehensive benefit development index of A, B, and C cities, judge the lagging types of the three cities, and evaluate the specific development status of the cities(2)
Calculate the coupling degree and coordination degree of A, B, and C cities. Summarize the coupling level and coordination type(3)
The higher the correlation between urban environmental quality and green financial indicators, the closer the relationship between the two indicators and the greater the mutual influence(4)
Rank the grey relational grade. Except Y3 is a strong correlation index, the rest are moderately correlated indexes. The correlation between Y1 and Z3 is the least, which is 0.55 and 0.552, respectively. Y3 can be correlated up to 0.655Facts have proved that while realizing green finance, the ecological economy of the environment can be protected and developed. It can achieve effective circulation promotion effect. Of course, the research in this paper is still worthy of optimization and improvement by relevant staff. For example, our research on references and related data is not thorough enough. The amount of green financial data is small, and it still needs to expand the field. The integration of old experience and innovation is low. Therefore, we need to raise more funds to support green finance and improve environmental quality. In addition, we need to strengthen exchanges and cooperation between regions, optimize the development of an innovation pattern, and invest more green innovation ideas.



---

*Source: 4721295-2022-03-18.xml*