An Empirical Study on the Impact of Regional Population Age
Structure on Urban and Rural Economic Growth
CHIEN-HSIEN WU1, TZU-KUANG HSU2
1Program of Technology Management, Chung Hua University, Hsinchu, TAIWAN
2Department of Business Administration, Chung Hua University, Hsinchu, TAIWAN
Abstract: - Whilst the shift in population structure remains one of the pivotal factors influencing urban and
rural economic growth, a thorough probe into the relationship between the two is of important significance for
beefing up economic growth in both urban and rural areas. On the basis of the results of literature analysis, this
paper analyzes the theories related to regional population structure and urban and rural economic growth, builds
an analysis model of the impact of regional population structure on urban and rural economic growth, and
selects Fujian Province as the research object, combining multiple linear regression to carry out empirical
analysis. Our results reveal that the shift in population structure would boost economic growth to a certain
extent, yet due attention must be paid to improving the quality of population in order to avoid the decline in
economic growth rate caused by the increase in old-age dependency ratio.
Key-Words: - Shift in population structure, Economic growth; Demographic transition, Demographic dividend,
Empirical research, Regional economic development.
Received: December 11, 2021. Revised: September 11, 2022. Accepted: September 28, 2022. Published: October 21, 2022.
1 Introduction
The change of population age structure is a
historical, comprehensive and complex natural and
social process, and an important factor to promote
China's regional economic development. However,
China's advantages in population structure will
continue to wane in the years to come. In tandem
with the ongoing decline in birth rate and death rate,
the demographic dividend China is currently
reaping will dwindle over time, [1], [2], the
deep-seated problems such as the aging of the
population and the heavy burden of labor support
accumulated in the process of population
development have become increasingly prominent.
The age structure of the population plays a role in
supporting various fields of economic development
in the process of change. The change of the age
center to the non working age stage, to some extent,
has led to economic and social risks such as the
weakening of the driving force supporting
economic development and the reduction of
development quality, which will restrict the
long-term development of China's regional
economy.
In the context of economic development speed
and structural depth adjustment, as well as the
urgent transition of population age structure, it has
become an extremely urgent task for Chinese
scholars and government departments to study the
impact of population age structure on economic
growth.In the important period of economic
transformation, in-depth qualitative and
quantitative research on the relationship between
the population age structure and economic growth,
and a clear understanding of the path, degree of
influence and future development direction of the
change in the population age structure on economic
growth have certain theoretical and practical value
for a comprehensive understanding and correct
understanding of the economic effects of the
change in the population age structure in China's
regions and the formulation of relevant policies.
2 Journals Reviewed
The most basic structure in the population structure
is the age structure of the population. How the
change of the age structure of the population affects
economic growth is a typical problem with Chinese
characteristics. Scholars at home and abroad have
launched a long-term multi angle exploration on
this.
Whether changes in the age structure of the
population affect economic growth. In foreign
countries, based on endogenous technology model,
human capital theory and life cycle theory of
savings, Malmberg took Sweden's population data
from 1950 to 1989 as the research object to verify
the economic effect of age structure, that is, the
increase in the proportion of people under 29 and
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Chien-Hsien Wu, Tzu-Kuang Hsu
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over 75 years old will inhibit economic growth,
while the increase in other age groups will promote
economic growth, Among them, the largest
contribution to economic growth is the proportion
of people aged 50-64, [3]. Thomas and other
scholars introduced the population age structure
variable into the neoclassical growth model,
analyzed the data of OECD countries from 1950 to
1990, and found that the per capita GDP growth of
OECD countries can be explained by the change of
age structure to a large extent, [4]. Bjö rn used the
data of Denmark, Finland and other countries from
1950 to 1992 to test the impact of age structure
distribution on economic growth, the results show
that the increase of the proportion of working age
population can significantly promote economic
growth, [5]. Jinying Wang and other scholars
studied the data of 17 OECD countries from 1960
to 2016 and found that the change of population
age structure has a profound impact on the
economic structure of OECD countries, [6]. At
home, in recent years, the relationship between the
age structure of China's population and economic
growth has gradually attracted the attention of the
academic community. Xibao Guo and other
scholars believe that the decline of the proportion
of working age population in China, like most
middle-income countries, is not conducive to
entering the high-income stage, [7]. Dewen Wang
believed that the "demographic dividend"
generated by the decline in the burden of
population support caused by the change in the age
structure of the regional population has a high
contribution rate to the rapid growth of the regional
economy, and is one of the strong drivers of
regional economic growth. With the aging age
structure of the regional population, the
demographic dividend tends to decrease and will
eventually close, [8].
With regard to the impact of changes in the age
structure of the population on China's economic
growth, existing studies have not reached a
consistent conclusion. The main point of view is
that the changes in the age structure of the
population in a long period after the reform and
opening up have promoted China's economic
growth, but at this stage, the impact is uncertain,
mainly because of the particularity of the age
structure of China's population. For example, the
age structure of China's population is showing the
deepening of aging The implementation of the
second child policy has led to the increase of child
dependency ratio and other characteristics, which
has brought many uncertainties to China's future
economic development. In addition, most of the
current studies focus on the impact of population
age structure on economic growth and the role of
characteristics of different development stages of
population age structure on economic growth.
There is less in-depth analysis on the impact
mechanism of population age structure on
economic growth. In this regard, many studies have
focused on the relationship between the change of
population age structure and economic variables.
These studies contain the relationship between
population age structure and economic growth.
These documents can be summarized as the impact
of population age structure on China's investment,
savings, public expenditure, import and export,
consumption and other fields. From these studies, it
can be found that the change of population age
structure is widely concerned by society, one of the
important reasons is that the change of population
age structure will affect the economic growth of the
country by affecting various regions. This paper
sorts out these studies as the empirical basis for
studying the mechanism of the change of
population age structure on economic growth.
3 Theories about Regional Population
Structure and Urban/Rural Economic
Growth
3.1 Theories about Population Structure
On the basis of literature review, we hereby divide
the theories about population structure into two
categories, i.e., the theory of demographic
transition, and the theory of demographic change
and economic growth.
1.Theory of demographic transition
Originating at the beginning of the 20th century,
the theory of demographic transition is the
conclusions drawn by comparing the demographic
statistics and the economic development status in
the same period, [9], [10]. Today, in parallel with
the burgeoning development of economic
globalization and urbanization, death rate and birth
rate continue to slide downwards, and the
population growth rate has been lingering at a low
level for a long time. All of these are reflective of
the main points of the theory of demographic
transition. The theory of demographic transition has
close links to economic development, and the
integration of the two has given rise to the
"Five-stage Theory" of demographic transition, as
shown in Figure 1.
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Fig. 1: Five-stage theory of demographic transition
As shown in Figure 1, in Stage 1, population
growth remains static. In Stage 2, economic growth
drives up the population growth rate. In Stage 3,
population growth slows down due to further
economic growth. In Stage 4, population growth
comes to a halt. In Stage 5, death rate gradually
surpasses the birth rate, leading to negative
population growth.
2.Theory of Demographic Change and Economic
Growth
After a detailed analysis of this theory as
explained in previous studies, we have constructed
an equation to model the relationship between the
two. Here, we have
A
as the workforce in the
region,
B
as the total population in the region,
C
as elderly people aged over 60 in the region, and
D
as children in the region. We can then get the
old-age dependency ratio
, the young-age
dependency ratio
and the total-age dependency
ratio
for this region. Using
w
to represent the
GDP created by people of working age in this
region, the relationship between population and
economic growth can be modelled as:
1GDP
GDP N NA
(1)
It can be seen from Equation (1) that different
population structures would have different impact
on the local economic development. This Equation
can be used as the theoretical basis for the
empirical analysis part of this study.
3.2 Relationship between Population
Structure and Economic Growth
A large number of scholars have focused their
research on the association between demographic
outcomes and economic growth, whilst ongoing
literature review and research efforts have
produced three types of perspectives on the
association between population structure and
economic growth, i.e., pessimistic theory of
population growth, optimistic theory of population
growth, and neutral theory of population growth,
[11].
The pessimistic theory of population growth
argues that population growth will lead to a
shortage of social materials, thus resulting in
negative economic growth. This perspective is
incomprehensive and can only be used to analyze
agricultural societies. With the boom in industrial
development, this theory could no longer
comprehensively explain the relationship between
population growth and economic growth, and thus
optimistic theory of population growth came into
being. According to the optimistic theory of
population growth, population growth can boost
investment and consumption, thereby shoring up
economic growth. In the wake of technology
advances, the drawbacks of this theory gradually
came to the surface, and the neutral theory of
population growth was proposed in such a context.
The neutral theory regards the quality of population
as the linchpin of economic growth, arguing that
the changes in population size and population
structure will lead to a fundamental shift in labor
productivity and working environment, which will
in turn lead to the continued changes in economic
growth. In this study, we will build our analysis on
the neutral theory of population growth to shed
light on the impact of regional population structure
on urban and rural economic growth.
4 Statistical Model and Methodology
4.1 Statistical Model
In this study, economic theories and practical
systems were introduced, and the BDS technique
was harnessed to construct an empirical statistical
analysis model. Based on nonlinear characteristics,
we performed statistical analysis on the collected
data to complete the empirical analysis. Through
literature review, we can learn that BDS is a
technique for nonlinear data analysis, [12], [13].
According to this method, let
T
be the time series
for the target region and
11
( , ,..., )
i i i m
T T T
be the
observations at this stage, in which case the
correlation integral, an estimator of spatial
probabilities across time in the region, is computed
as:
(2)
11
11
2
( , ) ( , , )* ( 1)
mm
EE
ij
t u t jj
R E q H T T q TT
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In Equation (2),
( , , )
ij
H T T q
refers to the
indicator function;
,
ij
TT
refers to the Euclidean
distance between the series
i
T
and
j
T
;
q
refers
to the bandwidth in space;
E
refers to the total
number of data samples. By dividing the series
j
T
into multiple subsamples, the resulting statistic
after testing this model can be expressed as:
(3)
In Equation (3),
()
iq
refers to the standard
deviation of a given data sample, and
( , )
m
L E q
refers to the BDS statistic, which conforms to the
normal distribution. This equation was used for the
statistical analysis of the data collected for this
empirical study.
4.2 Model Testing
After comparing multiple models, the RCM test
model, [14] was selected to test the results obtained
in this study. Assuming that the state classification
number
Z
is a measure built on a random
variable, it has two states -correct and incorrect:
(4)
In Equation (4),
N
refers to the normalized
value of
RCM
, and
ti
xj
refers to the
smoothed probability of all information in each
state in the information set. Where there are
F
states, then:
(5)
In Equation (5),
F
refers to the number of states,
T
refers to the number of samples, and
i
refers
to the data smoothed probability. When
RCM
is
close to 0, the result obtained will be more reliable.
In this study, this model was used to test the
empirical results.
4.3 Production Function Model
In this study, the production function model will be
used to complete the empirical analysis. This
model can help determine the relationship between
labor input and capital input, and the computational
process can be summarized as:
()Y O t G P
(6)
Where
Y
refers to economic output;
()Ot
refers to factors affecting economic growth, such as
technological advances;
G
refers to labor input;
P
refers to capital input;
refers to the output
elasticity of labor;
refers to the output elasticity
of capital; and
refers to the random error. In
this study, this model was utilized to probe into the
impact of intra-regional economic outcomes on
urban and rural economic growth.
5 Empirical Analysis of the Impact of
Regional Population Structure on
Urban and Rural Economic Growth
In order to systematically probe into the impact of
regional population structure on urban and rural
economic growth, we selected China's Fujian
Province as the subject of our empirical analysis.
By obtaining the relevant demographic data for
Fujian, we analyzed the demographic transition and
the shift in population structure in Fujian, and also
probed into its trends in economic growth. All data
are from China Statistical Yearbook of each year.
5.1 Descriptive Analysis of Population
Structure
Amid the ongoing population change, after the birth
rate has peaked, it will go down gradually, in which
case there will be a period during which both
children and elderly people take up a lower
proportion in the total population. This study will
build its analysis of regional population structure
on the United Nations' classification of age
structures, as shown in Table 1.
Table 1. Classification of age structures
Type
Young-age
dependenc
y ratio
Old-age
dependenc
y ratio
Proportion
of youth
and elderly
population
s
Media
n age
Youn
g
Above
45%
Below 5%
Below
16%
Below
18
years
Adult
30% to
45%
5% to 8%
16% to
35%
18-30
years
Old
Below 30%
Above 8%
Above
35%
Above
30
years
After taking statistics of the labor force and
employed population in this region in the past years
according to Table 1, the variations in age and
employment are shown in Table 2.
1
( , ) ( , )
( , ) ()
i
m
i
E R E q R E q
L E q q
1
1
* (1 )
T
t i t i
t
RCM N x j x j
T
2
1
1
( ) 100 T
i
t
RCM F F T
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Table 2. Working-age population and employed
population in Fujian Province over the past 30
years (in 10,000s, %)
Yea
r
Young-age
Dependenc
y Ratio
Old-age
Dependen
cy Ratio
Employe
d
Populatio
n
Employ
-ment
Rate
199
0
31.47
5.07
1348.38
44.40
199
5
30
6.5
1567.1
48.56
200
0
23
6.68
1794
52.61
200
5
18.3
8.8
1923
54.06
201
0
15.47
7.9
2114
57.24
201
5
16.22
8.45
2768.41
72.11
202
0
10.47
11.12
2206
53.02
According to the statistics shown in Table 1 and
Table 2, it can be seen that the population structure
of this region has shifted in tandem with the
changes in birth rate and death rate. Fujian
Province has embarked on a trajectory of
population ageing since 2000. During the period
covered by this study, in the wake of technological
advances and economic boom, people's life
expectancy continued to edge up, whilst birth rate
kept going down. Total-age dependency ratio was
dominated by old-age dependency ratio, and such a
situation is likely to last long. In the meantime, the
influx of massive working-age population into
cities led to a fundamental shift in the population
structures of both urban and rural areas, which in
turn spurred the gradual change in total-age
dependency ratio and posed daunting challenges on
regional economic growth.
Amid the ascent of total-age dependency ratio,
Fujian's demographic dividend gradually waned,
with employed population and employment rate
also falling year by year. By using the demographic
equation to project the population structure of this
region, it's found that Fujian's demographic
dividend could last until 2030. With the advent of
the "Three-child Policy", both the proportion of
youth population and the birth rate are likely to
increase in Fujian. Although such increase might
push up the young-age dependency ratio in the
foreseeable future, it can also drive up future labor
supply and thus lengthen the period of
demographic dividend. Therefore, Fujian Province
should seize the opportunity and maximum the
benefits of its own population structure.
5.2 Relationship between Regional
Population Structure and Urban/Rural
Economic Growth
1.Construction of Research Model
On the basis of the production function model
described above, variables such as regional
total-age dependency ratio, young-age dependency
ratio and old-age dependency ratio were introduced
to perform multiple linear regressions on labor
input and capital input, in a bid to shed light on
how the shift in population structure would have
impact on economic growth.
On the basis of Equation (6), we first took the
logarithm to eliminate the variances on both sides
of the equation, thereby obtaining the double-log
production function model, [15] : (7)
On the basis of this model, we utilized Equation
(1) to introduce variables to expand the production
function, thereby obtaining the model for
measuring economic growth:
(8)
After constructing Model (7), we extracted the
total-age dependency ratio as an independent
economic growth determinant for analyzing the
direct effects of the shift in population structure on
economic growth. As stated in the theoretical
analysis part of this paper, the decline in total-age
dependency ratio will drive up the labor force
participation rate, thus contributing to economic
growth, [16], [17].Therefore, in this study, we will
use Equation (8) to measure how the shift in
population structure would contribute to economic
growth.
Since only a few model variables were used in
this study, in order to ensure the validity of the
model, we used Eviews 6.0 in combination with the
test model mentioned above to test the calculation
results.
2.Model Calculation Results
Calculation results obtained using the above
models, indicators and variables are shown in Table
3.
1
ln ln lnY O G P
2
2
2
2
ln ln ln
ln ln( ) ln
ln ln( ) ln
ln ln( ) ln
Y O G GDP
Y O G GDP
Y O G GDP
Y O G GDP
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Table 3. Indicators of urban/rural economic growth
in Fujian Province (in 100 millions of RMB)
Year
GDP
Capital Stock
1990
522.28
306.239
1995
2094.9
647.233
2000
3764.54
1276.367
2005
6415.47
2279.981
2010
15002.51
5310.194
2015
26819.46
8617.032
2020
43903.89
12952.468
The analysis was done using Equation (8) and
the data in Table 3 and Table 2. Data analysis and
processing were done using the data analysis
software of SPSS. Linear regressions were
performed using the least squares method. The test
results of the model calculation results are shown
in Table 4.
Table 4. Model regression estimates and test results
Model
Variabl
e
Unstandar
di-zed
Coefficient
Standard
Deviatio
n
Standardize
d
Coefficient
Signif
i-canc
e
lnY
0.504
0.009
0.640
0.000
lnG
1.298
0.007
0.204
0.000
GDP
-0.734
0.142
-0.071
0.025
lnY
0.470
0.014
0.184
0.000
LnY-χ
1.104
0.064
0.539
0.000
lnY
0.454
0.014
0.504
0.000
LnY-α
1.105
0.068
0.404
0.000
lnY
0.571
0.011
0.614
0.000
LnY-β
1.405
0.085
0.204
0.000
Figures shown in the above table are the results
exported by SPSS. According to Table 4, the
proposed model can produce relatively stable
calculation results, and the significance of the
calculated results of each variable is greater than the
critical value. The calculation results exhibit a certain
extent of stability, and can be tested to confirm the
existence of a long-term dynamic relationship.
According to Equation (5), the stationarity of
calculation results must be tested through unit root
test. In order to enhance the robustness of the
calculation results of Equation (5), the unit root test
must be done using two different methods. If the two
methods produce consistent test results, the results
can be exported directly; if the two methods produce
inconsistent test results, adjustments would be
necessary. After using the test model to make
necessary adjustments, the significance of variables
improved greatly, confirming the existence of a
long-term dynamic relationship between the
calculation results and the variables. Finally, by
analyzing the model calculation results, the impact of
regional demographic outcomes on urban and rural
economic growth can be discerned.
According to the calculation results of the model,
China's market economy was still in its infancy in
the 1990s. With the influx of capital into the market,
the industrial structure gradually shifted from a
labor-intensive one to an asset-intensive one, and
Fujian also closely followed the footsteps of the
market economy. During this period, capital
contributed greatly to economic growth, and the
total-age dependency ratio was negatively
correlated with economic growth — that is, when
the total-age dependency ratio came down,
economic output would climb up. Our calculation
results well accord with the economic growth
characteristics in this period as described in other
studies. After 2005, due to the impact of economic
crisis, the market saw another round of massive
capital inflow, and market economy posed
increasingly higher requirements on human capital.
During this period, the total-age dependency ratio
was positively correlated with economic growth.
The sweeping inflow of rural population into the
cities led to rapid industrial development and
boosted the market economy. However, the
increasing proportion of elderly people and children
in the total population in rural areas has brought
agricultural development to a standstill. While
population ageing, which is gradually stepping up
its pace, is stalling economic growth, the early
economic dividends still remain.
By analyzing the standardized coefficients of
labor input in the calculation results of the proposed
model, it can be seen that the impact of labor input
on economic growth remains around 0.350 when
the impact of total-age dependency ratio on labor
output is not taken into account. When the total-age
dependency ratio is taken into consideration, the
economic growth would be greatly affected by
labor input. Meanwhile, a systematic analysis of the
calculation results can confirm that the shift in
population structure would lead to a shortage of
labor resources, which would in turn hold back
economic growth. Comprehensive analysis of the
above results confirms that the shift in regional
population structure and the continued increase in
the total-age dependency ratio would drive down
labor output and compromise economic growth,
thereby reducing the contribution of the shift in
population structure to economic growth.
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6 Summary
After an empirical analysis of the impact of
regional population structure on urban and rural
economic growth, we have obtained the following
results:
1.During the period covered by this study, there
existed long-term dynamic relationships between
total-age dependency ratio, population structure
and economic growth in the subject region, and
there was a negative correlation between
dependency ratio and economic growth. In the
years to come, the subject region is expected to
heighten its utilization of demographic dividend.
2.In analyzing the impact of regional population
structure on urban and rural economic growth, it's
found that the contribution rate of population
structure to economic growth, as estimated in this
study, basically accords with the findings of
existing studies, suggesting that the analysis model
used herein is valid and can be used for subsequent
research.
3.To push up economic growth rate and plug the
yawning gap in economic growth between urban
and rural areas, it's necessary to enhance the quality
of population, tap the huge potential of the elderly,
optimize the current labor force structure, and
effectively mitigate the employment pressure.
4.Current demographic outcomes are not
conducive to economic growth. The total-age
dependency ratio has been edging up due to the
plunge in birth rate. Whilst the shift in population
structure has long been a driver of economic
growth, population ageing is apparently hindering
economic growth. If population quality remains
unimproved, urban and rural economic growth will
surely be compromised.
7 Conclusion
Whilst population structure has long been a crucial
determinant of China's economic development, the
ongoing shift in population structure is having a
seismic impact on China’s urban and rural
economy, with certain regions even undergoing
negative economic growth. Through thorough
empirical analysis, this study attempts to shed light
on the relationship between the regional population
structure and urban and rural economic growth, in
the hopes that its findings would inform future
policies and provide theoretical basis for future
economic development.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Tzu-kuang Hsu conceived idea; Chien-hsien Wu
performed the data analysis and wrote the paper.
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This article is published under the terms of the
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.156
Chien-Hsien Wu, Tzu-Kuang Hsu
E-ISSN: 2224-2899
1730
Volume 19, 2022
