Frontiers in Business, Economics and Management 
ISSN: 2766-824X | Vol. 5, No. 3, 2022 

 

293 

The	Spatiotemporal	Evolution	and	Influencing	Factors	
of	Urban	Economic	Resilience	in	the	Yangtze	River	
Delta	Urban	Agglomeration	
Yi Wang 

International Business School, Yunnan University of Finance and Economics, Yunnan Kunming 650211, China 

 

Abstract: Urban agglomerations are the highest form of spatial organization in the mature stage of urban development, and 
will be impacted by external risks during the development process. How to enhance the urban economic resilience of urban 
agglomerations plays an important role in the sustainable development of urban agglomerations. Based on resilience theory and 
taking the Yangtze River Delta urban agglomeration as the research object, this paper explores the spatiotemporal characteristics, 
influencing factors and predictions of urban economic resilience in the future. The study found: (1) Based on the kernel density 
estimation, the economic resilience of the Yangtze River Delta urban agglomeration has significant spatial non-equilibrium 
characteristics; (2) Based on the correlation analysis, the degree of industrial structure optimization, government financial support, 
degree of opening to the outside world, innovation investment, Financial development level, urbanization level and ecological 
level are positively correlated with urban economic resilience; based on principal component analysis, government financial 
support is a key factor affecting urban economic resilience, with a weight of 17%; (3) Based on the grayscale prediction model, 
GM(1,1) can better fit the overall urban economic resilience of the Yangtze River Delta urban agglomeration from 2011 to 2020, 
and the overall urban economic resilience of the Yangtze River Delta urban agglomeration is at a high level from 2021 to 2025, 
but there is a downward trend . This research has important guiding significance for understanding the urban economic resilience 
of urban agglomerations and how to improve the urban economic resilience of urban agglomerations and promote regional 
coordinated development. 

Keywords: Yangtze River Delta Urban Agglomeration, Urban Economic Resilience, Kernel Density Estimation, Principal 
Component Analysis, GM(1,1). 

 

1. Introduction 
With the advancement of China's new urbanization process, 

urban agglomerations have gradually replaced individual 
cities as complex regional systems of global economic 
development [1]. They are not only the main spatial carriers 
of regional social and economic development, but also the 
main regional units participating in global competition and 
international division of labor. It will become the most 
dynamic and potential growth pole for future economic 
development [2,3]. The urban spatial organization in the 
urban agglomeration is more compact and the economic 
connection is closer, which has an important strategic 
orientation for promoting regional integrated development. 
The Yangtze River Delta urban agglomeration includes "three 
provinces and one city" in geographical space. It is an 
important intersection between the "Belt and Road" and the 
Yangtze River Economic Belt. It connects the east to the west, 
connects the south to the north, and is responsible for the rise 
of the central region and the ecological protection of the 
Yangtze River Basin. important task. Data show that the 
Yangtze River Delta urban agglomeration has about a quarter 
of the country's "double first-class" universities, and the 
annual R&D expenditure and the number of valid invention 
patents account for about one-third of the country, accounting 
for 2.3% of the country's area, but contributing 20%. % of 
GDP, plays the role of a "pioneer" and "demonstration area" 
in the national productivity layout. In October 2019, the State 
Council officially approved the "Overall Plan for the 
Ecological Green Integrated Development Demonstration 
Zone in the Yangtze River Delta", emphasizing that the 

Yangtze River Delta urban agglomeration should take the lead 
in exploring the transformation of ecological advantages into 
economic and social development advantages. In December 
2019, the Central Committee of the Communist Party of 
China and the State Council issued The "Outline of the 
Yangtze River Delta Regional Integrated Development Plan" 
takes the common development of the Yangtze River Delta 
region as a major national strategy, and clarifies the strategic 
layout of "one pole, three regions and one highland" in the 
Yangtze River Delta. As one of the most active, open and 
innovative regions in the country, the Yangtze River Delta 
urban agglomeration plays a pivotal role in promoting 
sustainable economic development, but it also faces an 
imbalance between economic development and 
environmental quality development [4]. Today, China is 
facing "big changes unseen in a century". The international 
balance of power has been profoundly adjusted, the 
international situation has undergone profound changes, the 
international environment has become increasingly complex, 
and various uncertainties and instability have risen 
significantly. With the advent of the risk society, the 
construction of resilient cities has increasingly become a topic 
of common concern in the theoretical and practical circles [5]. 
The Fifth Plenary Session of the 19th Central Committee of 
the Communist Party of China put forward the goal of 
"building a resilient city" for the first time from the height of 
the national strategy, and incorporated it into the 
recommendations of the 14th Five-Year Plan and the 2035 
vision. Building a resilient city has become a national 
strategic goal and strategy. direction. Urban economic 
resilience reflects a city's ability to respond to economic crises, 



 

294 

mitigate external shocks, and resist external risks, and its 
importance cannot be overstated. Generally speaking, the 
higher the resilience of a city's economy, the stronger the 
city's ability to resist external shocks, and the less the city's 
economic development is affected by external shocks [6]. The 
urban economic resilience of the Yangtze River Delta urban 
agglomeration has an important impact on the sustainable 
economic development of the Yangtze River Delta urban 
agglomeration and its radiating role. How to achieve self-
breakthrough in the uncertain external environment is a new 
issue for the Yangtze River Delta urban agglomeration in the 
new era. become a research hotspot. 

2. Literature Review and Methods 

2.1. Literature Review 
At present, the research on the Yangtze River Delta urban 

agglomeration has achieved relatively rich research results. 
Scholars have studied the economic growth [7], spatial 
pattern [8], spatial spillover effect [9], integration boundary 
effect [10], innovation efficiency [11], and innovation output 
differences of the Yangtze River Delta urban agglomeration 
from different perspectives. spatiotemporal evolution [12], 
spatiotemporal characteristics of carbon emissions [13], etc. 
Y. Peng, X. Chen (2011), based on the traditional Cobb-
Douglas production function, incorporated trade intermediary 
agglomeration factors into the new production function model, 
and found that trade intermediary agglomeration has a 
significant role in promoting economic growth in the Yangtze 
River Delta region; P.F. Chai, Z.W. Huang (2014) studied the 
spatial pattern of the Yangtze River Delta urban 
agglomeration based on the theory of coordinated 
development, and found that the Yangtze River Delta region 
is gradually transforming from a single center to a multi-
center model; T. Zhou (2015) studied the urban agglomeration 
in the Yangtze River Delta from an interactive perspective. 
Spatial spillover effects, the study found that the industrial 
development of the Yangtze River Delta urban agglomeration 
has significant spatial correlation, with the characteristics of 
spatial value chain layout; L. Huang, X.Y. Wang, Y. Xiong 
(2018) used the Theil index second-order decomposition 
method and exploratory spatial data. The analysis method and 
the geographic detector method study the spatial and temporal 
evolution of the innovation output difference of the Yangtze 
River Delta urban agglomeration. The study finds that the 
relative difference of the innovation output of the urban 
agglomeration has a decreasing trend, and the intra-regional 
heterogeneity plays a significant role, and the innovation 
output varies in space. There is an uneven agglomeration 
distribution in the urban agglomeration; L. Xu (2021) studied 
the innovation efficiency of the Yangtze River Delta urban 
agglomeration from the perspective of input and output, and 
found that the innovation efficiency of the Yangtze River 
Delta urban agglomeration was positively correlated with the 
urban R&D investment; Zhou Z.Z. Zhou, L. Xu (2022) By 
building an economic convergence analysis model and a 
relative β-convergence model, the study found that the 
integration of the Yangtze River Delta urban agglomeration 
has a good development trend, and the integration boundary 
of the Yangtze River Delta urban agglomeration presents a 
significant mediating effect; H C.F. Han, F.L. Song, M.M. 
Teng (2022) used spatial autocorrelation, Kernel density 
estimation, systematic clustering and other methods are used 
to study the spatiotemporal characteristics of carbon 

emissions in the Yangtze River Delta urban agglomeration. 
The study found that the carbon emission core density in the 
Yangtze River Delta region presents an obvious "unipolar" 
phenomenon, and carbon emissions show a significant 
positive spatial correlation. The above research has laid an 
important foundation for the integrated development of the 
Yangtze River Delta urban agglomeration, but it has not 
considered the impact of external risks on urban development, 
that is, the resilience of urban economic development in the 
Yangtze River Delta urban agglomeration. There is little 
research. In the face of increasingly complex domestic and 
foreign environments, a series of external shocks or internal 
disturbances that may occur will have an impact on the 
economic system [14]. For example, the new crown epidemic 
has hindered my country's economic growth, and the heavy 
rain in Henan has posed a greater threat to the development 
of cities. External risks have brought a huge impact on urban 
economic development and social stability. The emergency 
response capabilities of Chinese cities to deal with risks, 
disasters and crises are not yet It is very complete, and the 
urban system is still relatively fragile [5]. Based on this, 
building a more resilient economy and society is of great 
significance for enhancing the anti-risk capability of urban 
agglomerations and further promoting the high-quality 
development of my country's economy. "Resilient city" has 
also become an important goal of my country's urban 
construction. The connotation of "resilience" was first applied 
to the physical discipline, referring to the ability of the system 
to return to its original state after being stressed, to Holling 
(1973) [15] introduced it to the ecological discipline and 
defined it as engineering resilience, to Reggiani et al. (2002) 
[16] introduced this concept into the study of economics, 
considering regional economic resilience as the ability to 
resist shocks [8]. Wink (2014) [17] introduced the concept of 
resilience into urban economics for the first time, and he 
believes that resilience is a kind of ability to avoid, resist, 
adapt or respond to external shocks. Based on the perspective 
of evolutionary resilience, Martin R, Sunley P (2015) [18] 
further defined the connotation of resilience as four aspects: 
vulnerability, resistance, robustness and resilience. In general, 
the connotation of resilience has undergone a change in the 
cognition of "engineering resilience - ecological resilience - 
social and ecological resilience (evolutionary resilience) - 
contextual resilience" [19]. The resilience theory lays the 
foundation for this study. Considering that urban economic 
resilience is a measure of how urban economic development 
responds to external risks, this paper focuses on the research 
on urban economic resilience. Economic resilience can be 
understood as the ability of a regional economy to actively 
carry out self-adjustment and structural transformation in 
response to external shocks [20], and it can also be understood 
as the ability of an economy (including individuals, 
households, regions and countries) to cope with external 
disturbances [21]. In the theoretical study of economic 
resilience, evolutionary economic geography explores why 
some regions can "unlock" and realize economic 
transformation and upgrading, while some regions cannot get 
rid of "path dependence" and gradually go into recession [21]. 
Scholars' research on economic resilience using the relevant 
theories of economic geography mainly focuses on the 
measurement of economic resilience and its influencing 
factors. In the measurement of economic resilience: 
Guillaumont (2009) [22] uses economic vulnerability 
indicators to measure economic resilience, the smaller the 



 

295 

vulnerability of a country's economy, the stronger the 
economic resilience; Briguglio L, CordinaG, FarrugiaN, et al 
(2009) [23] constructed an indicator system to measure 
economic resilience. To measure economic resilience, it 
includes four indicators: macroeconomic stability, 
microeconomic market efficiency, governance and social 
cohesion; Ringwood L, Watson P, Lewin P, et al (2019) [24] 
use employment indicators to measure regional economic 
resilience; Y.W. Chen, G.L. Ding (2020) [25] The degree of 
agglomeration, the level of economic growth, the gap 
between the rich and the poor, the optimization of the urban 
industrial structure and the sensitivity of the urban economy 
construct a comprehensive index of urban economic 
resilience; R.G. Su, X.L. Zhao (2020) [26] used the 
employment growth rate index to measure the urban economy 
toughness. In exploring the influencing factors of economic 
resilience: Z. Zhang, Z.G. Li, X. Hu (2021) [27] constructed 
a spatial Durbin model and found that within the dimension 
of urban agglomeration, local economic resilience is 
continuously strengthened with the improvement of industrial 
agglomeration level, and also There are significant spatial 
spillover effects. Z C.Y. Zhao, S.P. Wang (2021) [28] 
constructed a panel data model and found that economic 
agglomeration significantly promoted the improvement of 
urban economic resilience. R.G. Su, X.L. Zhao (2022) [29] 
constructed various econometric models such as fixed effect 
model and quantile model, and found that the upgrading of 
manufacturing industry significantly promotes urban 
economic resilience, but the promotion effect shows a 
downward trend. Industrial upgrading has a positive 
moderating effect in promoting urban economic resilience, 
and presents heterogeneity characteristics; G.H. Hua, Y.J. 
Chen eration has a significant role in promoting urban 
economic resilience. There is regional heterogeneity in the 
mediating effect of innovation. The economic development of 
the urban agglomeration in the Yangtze River Delta has a 
"pioneering" role in the long-term development of the urban 
agglomeration in China. However, there are few literatures in 
the existing research that discuss the urban economic 
resilience of the urban agglomeration in the Yangtze River 
Delta, and there is no impact on the economic resilience of 
the urban agglomeration in the Yangtze River Delta. Factors 
are systematically sorted out. On the one hand, the research 
on the urban economic resilience of the Yangtze River Delta 
urban agglomeration can help to have a better understanding 
of the resilience of different cities to external shocks, and on 
the other hand, it can provide some experience for other urban 
agglomerations to deal with external risks when developing 
their economies. This paper mainly answers three questions: 
First, are there regional differences in the economic resilience 
of the Yangtze River Delta urban agglomeration? Second, 
what factors can affect the resilience of their cities? Third, 
what is the future trend of urban economic resilience in the 
Yangtze River Delta urban agglomeration, and how to 
improve urban economic resilience? By answering the above 
three questions, it will help to improve the economic 
resilience of urban agglomerations and enhance the ability of 
urban agglomerations to resist external risks. Based on this, 
the possible marginal contributions of this paper include: 
evaluating the spatiotemporal characteristics of urban 
economic resilience in the Yangtze River Delta urban 
agglomeration through kernel density estimation, exploring 
which factors can have an important impact on urban 
economic resilience through correlation analysis and 

principal component analysis, and Predict the dynamic trend 
of urban economic resilience in the Yangtze River Delta urban 
agglomeration from 2021 to 2025. The research in this paper 
expands the application of economic resilience in urban 
agglomerations and provides new empirical evidence for 
promoting regional integration. 

2.2. Research Methods 
This paper mainly uses kernel density estimation, 

correlation analysis and principal component method and 
grey prediction model GM(1,1). Among them, kernel density 
estimation is used to intuitively and vividly reveal the spatial 
and temporal distribution characteristics of urban economic 
resilience in the Yangtze River Delta urban agglomeration. 
Correlation analysis and principal components method test 
which factors can affect urban economic resilience and 
determine the weight of each factor. GM (1,1) is used to 
predict the changes in the overall economic resilience of the 
Yangtze River Delta urban agglomeration from 2021 to 2025. 

2.2.1. Kernel Density Estimation 
As a non-parametric estimation method, kernel density 

estimation can describe the distribution shape of random 
variables with a continuous density curve. By approximating 
the probability density of the variables, the kernel density 
estimation results reflect the location, shape and ductility of 
the variable distribution information [31]. Due to its weak 
dependence on the model and good statistical properties, this 
method has been widely used in the study of spatial 
distribution differences. Calculated as follows: 

 

𝐾 𝑥
1

√2𝜋
exp

𝑥
2

1  

 

𝑓 𝑥
1

𝑛
𝐾

𝑋 𝑥
ℎ

2  

 
Among them：𝑛 is the number of observations, 𝑋 is the 

observation point value, 𝑥  is the average value, h is the 
bandwidth, and K(.) is the kernel function. 

2.2.2. Correlation Analysis and Principal Component 
Analysis 

This paper studies the influencing factors of urban 
economic resilience through correlation analysis. In order to 
visually show which factors have an important impact on 
urban economic resilience, this paper analyzes by drawing 
scatter plots of core variables and influencing factors and 
fitting curves. After obtaining which factors will affect the 
urban economic resilience, the principal component analysis 
method is used to calculate the weight of each influencing 
factor [32,33], and then the key factors affecting the urban 
economic resilience are obtained. 

2.2.3. Grey forecast- GM(1,1） 
Grey forecasting system refers to a forecasting system in 

which part of the information is known and part of the 
information is unknown. The basic idea is to accumulate the 
original data sequence once to generate a new sequence, 
thereby weakening the randomness of the original data and 
making it show more obvious characteristic rules [31]. The 
main task of the theory is to fully mine the known information, 
seek the mathematical laws of system operation, and make 
quantitative predictions of future changes. In grey system 
research, GM forecasting model is the basic model of grey 



 

296 

forecasting theory, and GM(1,1) model, as the core and basis 
of it, has become the most researched because of its low 
sample size, simple structure and simple calculation. The 
most widespread and widely used predictive model [34, 35]. 
The basic principle is as follows: If the original sequence is: 

 
𝑋 𝑋 1 , 𝑋 2 , … 𝑋 𝑛 3  

 
Accumulate (4) once to get: 
 

𝑋 𝑋 1 , 𝑋 2 , … 𝑋 𝑛 𝑋 1 , 𝑋 𝑡 , … 𝑋 𝑡 4  

 
Then the corresponding first-order differential equation of 

the GM(1,1) model: 
 

𝑑𝑥
𝑑𝑡

𝑎𝑥 𝑡 𝜇 2 5  

 
Among them: a is the development gray number, μ is the 

endogenous control gray number. 
remember: 
 

𝐵

⎢
⎢
⎢
⎢
⎢
⎢
⎡

1
2

𝑋 1 𝑋 2 1

1
2

𝑋 2 𝑋 3 1

⋮
1
2

𝑋 𝑛 1 𝑋 𝑛
⋮
1⎥

⎥
⎥
⎥
⎥
⎥
⎤

6  

 

𝑌

⎣
⎢
⎢
⎢
𝑋 2
𝑋 3

⋮
𝑋 𝑛 ⎦

⎥
⎥
⎥

7  

 
Construct the immediate-mean-generating sequence 𝑍  
 

𝑍 𝑘
1
2

𝑋 𝑘 1 𝑋 𝑘 8  

 
But 
 

𝐵

⎢
⎢
⎢
⎡ 𝑍 2 1

𝑍 3 1
⋮

𝑍 𝑛
⋮
1⎥

⎥
⎥
⎤

9  

 
Make 
 

𝛼
𝑎
𝜇 10  

 
Then (9) can be expressed as: 
 

𝑌 𝐵𝛼 11  
 
Solve using the least squares method: 
 

𝛼 𝐵 𝐵 𝐵 𝑌 12  
 
Therefore, the prediction model can be obtained, namely: 

𝑋 𝑘 1 𝑋 1
𝜇
𝛼

𝑒
𝜇
𝛼

13  

3. Research Design 

3.1. Data Sources 
This paper takes the Yangtze River Delta urban 

agglomeration as the research object, and discusses the 
temporal and spatial change characteristics of the urban 
economic resilience of the Yangtze River Delta urban 
agglomeration from 2011 to 2020, the influencing factors and 
its prediction on the future economic resilience of the Yangtze 
River Delta urban agglomeration. The data source is the 
"China Urban Statistical Yearbook" and the "Statistical 
Yearbook" of cities in the Yangtze River Delta. Since 
Ma'anshan and Anqing have many missing values, these two 
cities are excluded. 

3.2. Variable Design 
3.2.1. Urban Economic Resilience 

As the core variable of this study, urban economic 
resilience is based on the research methods of Martin R, 
Sunley P (2016) [18] and Z. Zhang, Z.G. Li, X. Hu. (2021) 
[27], and the change in GDP is used to measure urban 
economic resilience. The calculation method is as follows: 

 

𝑟𝑒𝑠𝑖

𝐺 ,
𝐺 ,

𝐺 ,
𝐺 ,

14  

 
Among them: 𝐺 , represents the annual growth rate of real 

GDP in region r in period t, and 𝐺 ,  represents the annual 
growth rate of real GDP in the whole country in period t. 

3.2.2. Influencing Factors 
The factors affecting urban economic resilience are 

complex. This paper draws on the research results of literature 
[11-14, 25-30], and selects the following factors to study the 
influencing factors of urban economic resilience: (1) Select 
the degree of industrial structure optimization (iso), use the 
first Measured by the proportion of the added value of the 
tertiary industry in GDP, optimizing the industrial structure 
can resist a certain degree of external risks; (2) Select 
government financial support (gfs) and use fixed asset 
investment (excluding farmers) to measure, the government 
as the urban infrastructure Important builders, whose 
financial expenditure can affect the city's economic resilience; 
(3) Select the degree of openness (open), measured by the 
number of newly established foreign-invested enterprises, to 
enhance the level of the city's opening to the outside world, 
which can attract more foreign-funded enterprises and 
provide the city Construction lays an important foundation; 
(4) Select innovation investment (innovation), measured by 
scientific and technological expenditure, innovation 
capability is the core competitiveness of a city's sustainable 
development, and enhancing the level of urban innovation can 
affect urban economic resilience; (5) Select financial The 
development level (financial) is measured by the balance of 
various RMB deposits in financial institutions. Financial 
development reflects the capital level of the city and provides 
financial support for urban economic construction; Measured 
by numbers, the level of urbanization has contributed to the 
talent pool for urban economic construction, which is 
conducive to enhancing the resilience of the urban economy; 



 

297 

(7) Select the ecological level (ecology), which is measured 
by the area of green space. The ecological level reflects the 
degree of urban green development. Ecological protection 
and economic development will enable the healthy 
development of the city, thereby enhancing the urban 
economic resilience. 

4. Empirical Results Analysis 

4.1. Dynamic Characteristics of Urban 
Economic Resilience in the Yangtze River 
Delta Urban Agglomeration 

Figure 1 reflects the overall urban economic resilience of 
the Yangtze River Delta urban agglomeration from 2011 to 
2020. It can be found from the figure that the urban economic 
resilience of the Yangtze River Delta urban agglomeration can 
be roughly divided into four stages: from 2011 to 2013, the 
urban economic resilience was in the rising stage, from 2011 
to 2012, it was in the stage of climbing over the hurdles, and 
from 2012 to 2013, the urban economic resilience With a 
great increase, it reached its peak in 2013; the urban economic 
resilience declined significantly from 2013 to 2014; the urban 
economic resilience was stable from 2014 to 2019, and the 
urban economic resilience level was at an average level; 
2019- Urban economic resilience is on a downward trend in 
2020. Overall, the urban economic resilience of the Yangtze 
River Delta urban agglomeration has not yet formed a stable 
state, and the overall urban economic resilience still has a 
large room for growth. 

 

 
Figure 1. 2021-2020 Urban Economic Resilience Trend 

Chart 
 
Figure 2 reflects the kernel density estimation results, that 

is, the spatiotemporal characteristics of urban economic 
resilience in the Yangtze River Delta urban agglomeration. It 
can be found from the figure that the urban economic 
resilience of the Yangtze River Delta urban agglomeration 
from 2011 to 2020 presents a "single peak" phenomenon. The 
center of nuclear density showed a changing trend: the center 
of nuclear density moved to the right in 2011-2014, and the 
center of nuclear density moved to the left in 2014-2020. 
Among them, the peak in 2011 was the highest, the lowest in 
2014, and the peak gradually recovered after the trough in 

2014. The width of the crest from 2011 to 2014 gradually 
became longer, the width of the crest from 2014 to 2017 
decreased again, and the width of the crest from 2017 to 2020 
increased, and the width of the crest reached its peak in 2014. 
The above analysis shows that the economic resilience of the 
Yangtze River Delta urban agglomeration has significant 
spatial and temporal disequilibrium characteristics. 

 

 
Figure 2. The spatiotemporal characteristics of urban 

economic resilience 

4.2. Analysis of Influencing Factors 
From the above empirical results, it can be seen that the 

level of economic resilience of each city in the Yangtze River 
Delta urban agglomeration is different, which is not 
conducive to the development of regional integration. 
Therefore, we should explore the influencing factors of urban 
economic resilience, and then find a corresponding path for 
improving urban economic resilience and provide a good 
solution. The solution lays the foundation. In this part, the 
scatter plot in the correlation analysis is used to explore the 
relationship of each variable on the urban economic resilience, 
and the weight of each variable is determined by principal 
component analysis, and then the key factors affecting the 
urban economic resilience are obtained. Considering the large 
differences in the data, standardize each influencing variable: 

 

𝑋∗
𝑋 𝜇

𝜎
15  

 
Among them: 𝑋∗is the standardized data, 𝑋is the original 

data, 𝜇  and 𝜎  are the mean and standard deviation of the 
original data, respectively. After processing by Equation (15), 
the data falls in a standard normal distribution with a mean of 
0 and a variance of 1, thereby eliminating the difference in the 
magnitude of the data and ensuring the robustness of the 
analysis results. Figure 3 is a scatter plot of urban economic 
resilience and various influencing factors. From the scatter 
plot, it can be found that each variable has a certain positive 
correlation with urban economic resilience. 

 



 

298 

 
Figure 3. Scatter plot of urban economic resilience and influencing factors 

 
In order to quantify the impact of each indicator on urban 

economic resilience, this paper uses principal component 
analysis to calculate the weight of each indicator. The larger 
the weight value, the greater the impact on urban economic 
resilience, and vice versa . First, perform exploratory analysis 
on the data: KMO and Bartlett coefficients are 0.803, greater 
than 0.75, and the significance level is 0.00, so the data can 
be subjected to principal component analysis. Second, 
determine the number of common factors: two common 
factors are extracted according to the principle that the 
eigenvalue is greater than 1, and the variance contribution rate 
of the common factors is 86.701%, indicating that the 
extracted common factors can better express the 
characteristics of the data and reduce the number of data loss 
of information. Third, the calculation of the weight: the "total 
variance explanation" and "component matrix" obtained by 
the principal component analysis are used to calculate the 
weight of each influencing factor. Table 2 reports the weight 
of each influencing factor. The weights of each influencing 
factor are 14%, 17%, 15%, 15%, 14%, 10% and 15% in order, 
and the top four are government financial support, degree of 
opening to the outside world, innovation investment and 
ecological environment. From the results, if the economic 
resilience of the Yangtze River Delta urban agglomeration is 
to achieve long-term sustainable improvement, it is necessary 
to continuously strengthen the construction of the above-
mentioned influencing factors, especially when developing 
the economy, the ecological environment cannot be ignored. 
Any economic growth at the expense of the environment will 
will be unsustainable. The concept of urban development that 
lucid waters and lush mountains are invaluable assets has 
been empirically tested. 

4.3. Grey Forecast 
Figure 1 shows the dynamic trend of the overall urban 

economic resilience of the Yangtze River Delta urban 
agglomeration from 2011 to 2020. Although it can be roughly 
summarized from Figure 1 that urban economic resilience can 
be divided into four stages, its changing law is difficult to 
highlight, especially the dynamic characteristics of urban 
economic resilience in the future. In order to deeply explore 

the economic resilience of the Yangtze River Delta urban 
agglomeration in the future, this paper uses GM(1,1) to make 
gray predictions. Figure 4 shows the overall urban economic 
resilience of the Yangtze River Delta urban agglomeration, 
the data fitted by GM(1,1), and the errors of the two. 

 

 
Figure 4. GM(1,1) fitting and error diagram 

 
It can be seen from the figure that the original data and the 

forecast data show a coincident trend after 2013, and most of 
the errors between the two are in the range of -0.3 to 0.3, 
indicating that the model is used to fit the economic resilience 
of the Yangtze River Delta urban agglomeration. It has a good 
effect, so this paper continues to use the model to predict the 
urban economic resilience of the Yangtze River Delta urban 
agglomeration from 2021 to 2025. Table 3 reports the 
predicted value of the urban economic resilience of the 
Yangtze River Delta urban agglomeration from 2021 to 2025. 
On the whole, the economic resilience of the Yangtze River 
Delta urban agglomeration in the next five years will have a 
high level, indicating that the Yangtze River Delta urban 
agglomeration will have a good "resistance" to the impact of 
external risks in the future. However, it cannot be ignored that, 
from the forecast results, the future urban economic resilience 
of the Yangtze River Delta urban agglomeration will show a 
downward trend. Therefore, in the future, the Yangtze River 



 

299 

Delta needs to be based on factors such as government 
financial support, degree of openness, innovation investment 
and ecological environment to improve the long-term growth 
rate. The overall urban economic resilience of the triangular 
urban agglomeration. 

 
Table 1. GM(1,1) forecast result 

year 2021 2022 2023 2024 2025 
resi 1.397 1.285 1.181 1.086 0.999 

5. Conclusions and Policy 
Recommendations 

Ecological level are positively correlated with urban 
economic resilience. The ecological environment ranks 
among the top four influencing factors, and government 
financial support is a key factor affecting urban economic 
resilience. (3) GM(1,1) can better fit the urban economic 
resilience of the Yangtze River Delta urban agglomeration, 
and the forecast results of GM(1,1) show that the economic 
resilience of the Yangtze River Delta urban agglomeration is 
at a high level from 2021 to 2025. But there is a downward 
trend. Based on the above conclusions, this paper puts 
forward the following policy recommendations: First, 
government financial support plays a pivotal role in 
improving urban economic resilience. The government 
should enhance the construction of urban infrastructure, 
including traditional infrastructure and "new economy" 
infrastructure. On the one hand, improve the comprehensive 
transportation system in the region, focus on the development 
of innovative capacity building in transportation, enhance the 
accessibility of urban agglomeration transportation, promote 
efficient division of labor and cooperation within urban 
clusters, and promote the rational and efficient flow of 
production factors; infrastructure, such as optical fibers, base 
stations, etc., use the Internet to enhance the informatization 
capabilities of urban agglomerations, enhance the digital 
economy level of urban agglomerations, and use modern 
technologies to resist external risks, thereby enhancing urban 
economic resilience. Second, continue to expand the level of 
opening to the outside world. As General Secretary Xi Jinping 
mentioned on many occasions, "China's door to opening will 
never be closed, it will only open wider and wider." By 
expanding the level of opening to the outside world, 
integrating domestic and foreign excellent management 
experience and technical capabilities, forming management 
ideas with Chinese characteristics, and continuously 
improving the core competitiveness of urban agglomerations, 
thereby enhancing the urban economic resilience of urban 
agglomerations. Third, increase investment in innovation. 
Combined with their own resource endowments, urban 
agglomerations develop information technologies such as big 
data, the Internet, cloud computing, artificial intelligence, and 
blockchain, and increase the investment of innovative 
resources in high-tech industries such as biomedicine, new 
energy vehicles, and smart logistics, as well as related The 
policy is tilted towards high-tech industries, gradually 
forming regional industrial advantages, and promoting the 
resilient development of the regional economy. Fourth, 
strengthen ecological awareness and fully consider the 
carrying capacity of ecological resources. The ecological 
environment is positively correlated with urban economic 
resilience. Therefore, to improve urban economic resilience, 
it is necessary to protect ecological space and not relax 

regulations on urban environmental pollution. Ecological and 
environmental problems have external characteristics. The 
government should actively establish an effective ecological 
compensation mechanism, an open and transparent 
environmental governance supervision and public 
participation mechanism, and vigorously develop ecological 
industries, so that economic development and environmental 
protection can develop in harmony, thereby enhancing urban 
economic resilience. In addition, the optimization of 
industrial structure, the level of financial development, and 
the level of urbanization will also affect urban economic 
resilience. Optimize the industrial structure, continuously 
enhance the position of the tertiary industry in the regional 
economy, promote the transformation and upgrading of the 
industrial structure of urban agglomerations, enhance the 
resilience of the urban economy, and reduce the impact of 
external risks on economic development; financial 
development provides financial support for regional 
construction and innovation, It is conducive to improving the 
resilience of urban economy; the improvement of 
urbanization level provides human capital for urban 
construction and lays a foundation for economic construction, 
so it is conducive to the enhancement of urban economic 
resilience. 

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