Download The Countermeasure Research of Suqian Industrial Structure Adjustment and Economic Development

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The Countermeasure Research of Suqian Industrial Structure
Adjustment and Economic Development
QIN Yitian
School of Economics and Management, Beijing Jiaotong University, China, 100044
[email protected]
Abstract: Industrial structure adjustment is an important subject of economic development all over the
world, and to establish a reasonable industrial structure. Suqian as a less developed city in Jiangsu
province, its industrial structure and industrial structure inside still need to be adjust. In this paper, we
use Granger causality test proves that the correlation of three times industrial structure and economic
development in Suqian. Finally, Suqian industrial restructuring put forward some suggestions and
countermeasures.
Keywords: Regional industrial structure, Industrial structure adjustment, Economic development
1 Introduction
1.1 Background and significance
Suqian, located in the northern part of Jiangsu Province. As a city with smallest economic aggregate in
Jiangsu, China. Suqian has seized the opportunity with rapid economic development in sixteen years
since its establishment.
Industrial structure and economic growth has been the focus of economists’ study at home and abroad.
Economic growth refers to the increasing total amount of goods and services or income growth of a
country or region within certain time. The economic aggregate of Suqian has been less with irrational
industrial structure in sixteen years. Therefore, the industrial structure adjustment has great significance
on economic development and industrial restructuring countermeasures of Suqian.
1.2 Research methods
(l) Combined method of theory and demonstration was used in the work. Theory played an important
role in guiding empirical analysis. Industrial Structure Theory was the main theory of the work.
(2) Qualitative research method, as a traditional approach of regional economics, was the premise of
quantitative methods. Qualitative methods, including description and observation, were firstly used in
any kinds of social phenomenon and economic phenomenon, followed by quantitative mathematical
analysis methods. So do the methods in the work.
(3) Finally, recommendations were proposed for industrial structure adjustment of Suqian at this stage,
including suggestions on three-industrial internal structure adjustment.
2 Current Situation of Suqian’s Industrial Structure
Up to 2012, the gross regional product of Suqian had reached 150.67 billion RMB; public budget
revenue was 15.81 billion RMB with an increase of 30.7%, becoming one of top 70 prefecture-level
cities in China. The actual foreign investment on the account exceeded $500 million with an increase of
166%; fixed asset investment and loan balance both reached over one hundred billion RMB, increasing
by 26.3% and 31.9%, respectively. The increase amplitude of 8 major economic indicators took the top
place in the province.
2.1 Development status of Suqian’s industry structure
We use the data was based on “Statistical Yearbook of Jiangsu Province” during 2002-2013.We can find
the three industrial output value of Suqian was in steady growth during 12 years from 2002 to 2013. The
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primary industry increased by 15.262 billion RMB in 2013 compared to that in 2002, with the increase
of 200.58%; the output value of secondary industry increased by 64.234 billion RMB than that in 2000,
with the increase of 906.74%; the tertiary industry had a growth of 521.16 RMB than that in 2000, with
the increase of 970.14%. Various industries had acquired rapid development, especially in the secondary
and tertiary industries.
Figure 3-1 showed the proportion of primary industry in Suqian had been rapidly decreasing in 13 years,
presenting a steady growth in output value of the secondary and tertiary industry. The industrial
structure of Suqian was transformed from the past “primary-secondary-tertiary” to “secondary-tertiaryprimary”, gradually optimizing the industrial structure. However, without playing the role of pillar
industries yet, the tertiary industry of Suqian could not replace the secondary industry as a leading
industry. Therefore, it indicated that the industrial structure of Suqian was still in continuous adjustment
and optimization.
Figure 3-1 Changing trend of the proportion of three industries in Suqian
3 Relationships Between Industrial Structure Adjustment and Economic
Development
The industrial structure of Suqian has been in constant adjustment with the continual economic
development—it is the inevitable process of economic development. Based on analysis above, Suqian’s
industrial structure has been toward rational adjustment since its establishment. Research on relationship
between industrial structure adjustment and economic development has an important practical
significance to Suqian as an underdeveloped city, especially for the achievement of rapid economic
development and realization of a middle-developed city.
3.1 Research methods and data description
Time series of economic phenomena in econometrics were required to be stationary. Cointegration
theory proposed by Engle and Granger, two British economists, described that a long-term stable
equilibrium relationship existed among the linear combination of non-stationary economic variable with
the same order in time series analysis, namely cointegration relationship. Cointegration test included
two main methods: least square method and maximum likelihood method. In order to study the
contribution of the industrial structure adjustment to economic development of Suqian, the work
adopted the GDP data of Suqian from 2002 to 2013 in “Jiangsu Province Statistical Yearbook”. The
total GDP of Suqian was taken as independent variable with the primary industry as GDP1 and the
secondary industry as GDP2; the tertiary industry GDP3 was the dependent variable. The independent
variable and dependent variable used the price in 2002 as the cardinal number, with data base of actual
GDP, thus ensuring the validity of data model. Data were mainly processed through EVIEWS7.0.
3.2 Casual relationship between industrial structure and economic growth
3.2.1 Principle of Granger causality
Granger causality test, developed by the British quantitative economists Granger, was “a method testing
one-way or two-way causal relationship between variables”. The logic of Granger test was as follows:
when including past information of both variable X and Y, the predictive effect on variable Y was better
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than that including Y with past information, indicating that variable X contributed to explaining the
future changes of variable Y, then variable X was considered as Granger cause causing variable Y. But
Granger causality test was the casual relationship in statistical significance rather than a real causal
relationship. Regression analysis on Y used Granger causality test as follows:
m
m
i =1
j =1
Yt =  aiXt − i +  bjYt − j + u1t
s
s
i =1
j =1
Xt =  ciXt − i +  d jYt − j + u 2t
3.2.2 Data preparation and processing of Granger test
GDP and X1, X2, X3 were converted with the base period of prices in 1990, taking real gross domestic
product as the model data. The data after conversion was taken natural logarithm, thus eliminating the
heteroskedasticity of economic time series, as well as improving linear trend among the variables. The
causal relationship among variables was not changed, recording the variables as lnGDP, lnGDP1,
lnGDP2 and lnGDP3, respectively. An important prerequisite for Granger test was the stability of time
series of the test. The series stability was determined by unit root, using ADF method for verification by
EVIEWS7.0 (See table below).
Null Hypothesis: D(lnGDP,2) has a unit root
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=2)
t-Statistic
Augmented Dickey-Fuller test statistic
-3.978608
Test critical values:
1% level
-4.200056
5% level
-3.175352
10% level
-2.728985
Prob.*
0.0141
Null Hypothesis: D(lnGDP1,2) has a unit root
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=2)
t-Statistic
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level
-4.279472
-4.200056
-3.175352
-2.728985
Prob.*
0.0089
Null Hypothesis: D(lnGDP2,2) has a unit root
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=2)
Augmented Dickey-Fuller test statistic
Test critical values:
t-Statistic
Prob.*
-4.268688
0.0104
1% level
-4.297073
5% level
-3.212696
10% level
-2.747676
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Null Hypothesis: D(GDP3,2) has a unit root
Exogenous: Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=2)
t-Statistic
Augmented Dickey-Fuller test statistic
-4.965103
Test critical values:
1% level
-4.200056
5% level
-3.175352
10% level
-2.728985
Prob.*
0.0032
The above table showed that the P values of four variables were less than 5%; lnGDP, lnGDP1, lnGDP2
and lnGDP3 at the 5% significance level presented stability in the same order after second difference.
Then co-integration test was conducted as follows.
3.2.3 Cointegration test
Johansen test was used for cointegration test of lnGDP and lnGDP1, lnGDP and lnGDP2, lnGDP and
lnGDP3, respectively, with the results as follows:
Cointegration test of lnGDP and lnGDP1
Unrestricted Cointegration Rank Test (Trace)
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *
0.890251
27.64654
15.49471
0.0005
At most 1
0.090004
1.131778
3.841466
0.2874
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
Cointegration test of lnGDP and lnGDP2
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None
0.583263
10.81015
15.49471
0.2234
At most 1
0.025223
0.306562
3.841466
0.5798
Trace test indicates no cointegration at the 0.05 level
Cointegration test of lnGDP and lnGDP3:9
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *
0.711907
15.65198
15.49471
0.0474
At most 1
0.058103
0.718311
3.841466
0.3967
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
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The results showed that cointegration existed between lnGDP and lnGDP1, lnGDP and lnGDP3; there
was no cointegration between lnGDP and lnGDP2.
3.2.4 Results analysis of Granger test
EVIEWS7 was used for Granger test (Granger test could not be applied in lnGDP and lnGDP2 due to
lack of cointegration relationship) with the following results.
Table 3-4 Granger test of lnGDP, lnGDP1 and lnGDP, lnGDP3
Null Hypothesis:
lnGDP1 does not Granger Cause lnGDP
Obs
F-Statistic
Prob.
13
5.154 40
0.046 5
0.444 52
0.520 0
25.409 5
0.000 5
21.029 9
0.001 0
lnGDP does not Granger Cause lnGDP1
lnGDP3 does not Granger Cause lnGDP
lnGDP does not Granger Cause lnGDP3
13
The above table showed that the null hypothesis (the primary industry GDP was not the cause of total
GDP) was rejected because the P value was less than 5%. The null hypothesis that the total GDP was not
the cause of primary industry GDP could not be rejected as the P value was greater than 5%. Two P
values between the tertiary industry GDP and total GDP were less than 5%, both rejecting the null
hypothesis.
The demonstration proved that the relationship between industrial structure and economic growth of
Suqian was more complex rather than one-way causal relationship. The primary industry and tertiary
industry played a significant role in promoting economic growth of Suqian. Meanwhile, the economy
stimulated the development of tertiary industry in Suqian. However, adjustments of the primary industry
and secondary industry were less affected by economic growth of Suqian.
4 Suggestions and Measures on Industrial Structure Adjustment of Suqian
The correlation between industrial structure adjustment and economic development has been proved
through the above empirical analysis, thus it is necessary to optimize the industrial structure.
4.1 Optimizing industrial structure to promote industrial upgrading
Agriculture is the basis of national economy. As a traditional major city of agriculture, Suqian has been
related to national security. The adjustment of industrial structure has an extremely important role in
further increase of agricultural productivity and improvement of agricultural output, thus consolidating
the basic position of agriculture. Agriculture should be stably developed with effective solution for the
“Three Agricultural Problems”. Suqian’s industry is relatively backward in Jiangsu Province, while the
secondary industry becomes the dominant force of Suqian’s industry. The key to economic development
of Suqian is the acceleration of optimization and adjustment of industrial structure. Suqian should take
advantage of its rich natural and human resources, with its comparative advantage. Suqian economy
should be integrated with Yangtze River Delta economy, promoting industrial structure optimization
with constant improvement of industrial scale and production quality. The tertiary industry, as an
important indicator of the socio-economic development level, is the main driving force for national
economic development. With the continuous improvement of people’s living standards, the demand of
the tertiary industry is continually increasing, especially for service industry. Therefore, clear
preferential policy should be formulated by government to promote the development of tertiary industry
of Suqian.
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4.2 Optimizing industrial distribution with formation of industrial clusters
Suqian should accelerate the cultivation of characteristic industry and brands, with constant
improvement of industrial concentration, thus promoting optimization and upgrading of industrial
structure. With characteristics of centralization, profession and scale, industry cluster is an important
way for the optimization of regional economic structure, promotion of enterprises innovation, and
maintenance of continued growth of regional economy.
4.3 Intensifying development of technological innovation of enterprises
Technological progress is an important factor of economic growth as well as the power for optimizing
the industrial structure. Reasonable adjustment of local industrial structure should be promoted relying
on technological innovation in Suqian, driving the rapid development of regional economy.
The construction of technological innovation system should be accelerated, establishing a shared
platform for innovation resources based on local universities, research institutions and enterprises with
innovative strength.
5 Conclusions and Prospects
The industrial structure of Suqian is developing toward the optimized pattern of “secondary-tertiaryprimary” while presenting a low level. Through the above quantitative and qualitative analysis, the
general direction of industrial structure adjustment of Suqian is as follows: the secondary industry
should be developed as a pillar industry, focusing on the improvement of the proportion of tertiary
industry; the basic position of primary industry should be consolidated, improving production efficiency
of agriculture.
Acknowledgements:
We thank the financial supports from the National Nature Science Foundation of China (71072028).
References
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Zhengzhou City, D, Zhengzhou University. 2011 (in Chinese)
[2]. Zheng Dongpo. Research on Qintangcang regional industrial structure optimization, D, Hebei
University. 2011 (in Chinese)
[3]. Gao Xin. Research on the Development of Industry Structure of the Less-developed Areas in
Southeast China, AMOY University. 2011 (in Chinese)
[4]. Nie Tao. The Countermeasure Research of Zhongshan Industrial Structure Adjustment, Tongji
University. 2012 (in Chinese)
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