Download Empirical Analysis on the Relationship Between Logistics Industry

Empirical Analysis on the Relationship Between Logistics Industry
and Economic Growth in Xuzhou
LI Aibin1, ZHAO Pianpian1, ZHAO Yuanli1.2
1. School of Management, China University of Mining and Technology, Xuzhou, Jiangsu, P.R.China,
221116
2. Department of Aviation Oil and Material, Xuzhou Air Force College, Xuzhou, Jiangsu, P.R.China,
221000
[email protected]
Abstract: To find out the impact of logistics on economic growth and the relationship between
logistics industry and economic growth, this paper makes quantitative research on the mutual
relationship between the logistics industry and economic growth in Xuzhou based on the GDP and
freight volume data from 2000 to 2009. The results have shown that on the whole the relationship
between Xuzhou economic growth and the logistics industry is an inverted U-quadratic curve; from
2000 to 2007, its economy grows faster than the development of the logistics industry which has pulled
the economic growth effectively; and in 2008-2009, its economy grows slower than the development of
the logistics industry with that logistics industry has less pull effect on the economic growth and even
with a gradually abating tendency. Therefore, local government should make proper policies to
promote the coordinated development between logistics industry and economy growth according to the
characteristics of different development stages.
Keywords: Xuzhou, logistics industry, economic growth, elasticity of economic logistics
1 Introduction
Logistics,called ‘the source of third profit’[1], is considered the artery and elementary industry of
national economic development and has been growing rapidly, which has presented new challenges on
the development of China’s urban logistics and at the same time makes it an important part of the
regional economy development. As a result, many domestic and international cities such as Tokyo,
Hong Kong, Shenzhen take the logistics industry as a pillar industry or elementary industry making it
a new economic growth point in these areas.
Second largest city in Jiangsu Province, Xuzhou is one of the core cities of the three metropolitan
circles and one of the four megapolises under the special construction plan of Jiangsu province.
Furthermore, it is one of the five major urban centers in the Chinese section of the new Eurasian
Continental Bridge as well as the center of Huaihai Economic Zone. It’s easy to see that Xuzhou has a
good basis for the development of the logistics industry for its favorable location and transportation.
However, Xuzhou is located in the north of Jiangsu province with lower level of industry and weaker
economic power. At present the Jiangsu provincial government has proposed a strategic commitment
to ‘revitalizing the old industrial base, Xuzhou’. One of its aims is to develop the business logistics
industry in Xuzhou into one of the four one-billion-dollar industries trying to build Xuzhou into a
logistics center, which provides a golden opportunity for the development of Xuzhou logistics industry
and is of great strategic significance for the development of Xuzhou economy and the overall
rejuvenation of northern Jiangsu.
There are mainly two different views on the relationship between the economic growth and the modern
logistics theoretically. One is the theory of logistics-push, holding the opinion that modern logistics
can contribute to regional economic development; another economic-pull, thinking that the rapid
economic development also pulls the further development of modern logistics[2]. In countries with
developed logistics like the United States, Europe and Japan mainly focus researching on enterprises
with less interest in regional logistics system and its optimization. Ana Maria Sarmiento, Rakesh
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Nagi(1999)[3] gave a comprehensive analysis on the production logistics system; Heijden, Rob E, C, M,
Van Der(2000)[4] studied the evaluation of city logistics; Taniguchietal (2000) using traffic simulation
dynamic model made a quantitative study on the relationship among city’s economic growth, transport
needs, road congestion and environmental pollution; Marc Goetschalckx, Carlos J, Vidal, Koray
Dogan(2002)[5] designed a logistics optimization model from point of view of global logistics. More
domestic researchers focus on the relationship between regional economic development and regional
logistics, some representatives of who are: Tan Qing-mei et al. (2003)[6] who calculated the
contribution rate of logistics capacity to the GDP growth of Jiangsu using regression analysis model;
Wu Zhihui et al. (2008)[7] found out the quantitative relation between regional logistics industry and
regional economic growth using logistic growth model; Liao Ying et al.(2008)[8] using the panel data
of 30 provinces (municipalities) in 1978-2006 came to conclusion that there exists panel cointegration
relationship between regional economic growth and regional logistics growth. Urban logistics research
is an important aspect of the regional logistics study. Wang Hui-ping et al.(2001)[9] made empirical
study testifying the positive effect of the Shanghai logistics industry on economic growth; Guo
Xiangyang et al.(2009)[10] studied the relations between Shenzhen logistics industry and the sustainable
economic growth there.
Although presently research has achieved a lot in the relationship between economic growth and
logistics industry, yet most of the research is aimed at the logistics in developed regions and
quantitative analysis on the relationship between economic growth and urban logistics industry in
underdeveloped cities is lacking. Combining quantitative and qualitative methods, the goal of this
paper is to establishe a mathematical model of the relationship between logistics industry and economic
development in Xuzhou to reveal the mutual relationship between logistics industry and economic
growth and makes evaluation on it hoping to provide some reference for decision-making in
ascertaining the role of logistics in the economic development of Xuzhou as well as for making policies
and planning development for logistics in Xuzhou.
2 Research Methodology
2.1 Selection of index
Development ability of the logistics industry refers to the logistics supplier’s capability to provide
logistics services, the index of which is rather sophisticated and in theory there is yet no universally
acknowledged index to comprehensively reflect the logistics capability of a city. As far as city is
concerned, index to measure the logistics capability should include the carrying capacity of urban
logistics facilities, the network performance of logistics communication, the reasonability of space
layout in logistics center, the adaptability of economic and management system of logistics, turnover
rate of freight and freight volume, etc. In order to facilitate data collection, this paper according to the
related literature review refers to Zhang Hongbo[11] and other scholars’ practice, selects the freight
volume (expressed as x) as the comprehensive index to measure the development capabilities of
logistics in Xuzhou City.
Economic growth could be reflected in ‘content’, namely the continuous increase of gross national
production, and also consideration of improvement of ‘quality’ is also feasible. The improvement of
‘quality’ includes not only the speed of economic growth, but also the overall progress in the average
life quality of a nation or a region, the whole economic structure and social structure. In this paper, we
just measures the economic development from ‘quantity’ perspective, so it selects the gross national
production(GDP, expressed as y) to measure the economic growth in Xuzhou.
2.2 Construction of model
2.2.1 Mathematical model of the effect of logistics on urban economic growth
To study and the interaction between urban economic growth and the logistics industry, a regression
model for the urban GDP and logistics capacity can be expressed as follows:
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（ 1）
y = f ( x) + ε
where the urban GDP y refers to explained variables, logistic capacity x refers to explanatory variables,
ε is random error term.
2.2.2 Elasticity of economic logistics
To study the quantitative relationship between urban economic growth and the logistics industry, the
elasticity of economic logistics (E) is introduced. E is given as the ratio of economic growth rate and
the growth rate of urban logistics ability, that is:
E=
∆y
∆x
×
x
(2)
y
Value of E describes the interaction relationship between urban economic growth and the logistics
industry indicating the pull economic growth rate when the urban logistics capability increases 1%.
E>1 shows that city’s economy grows faster than the development of urban logistics ability with that
the pull effect is more obvious than the push effect and the logistics demand is greater than the supply;
whereas E<1 tells us that city’s economy grows slower than the development of urban logistics ability
with that the pull effect is less obvious than the push effect and the logistics demand is less than the
supply; and if E=1, it indicates th`at the economy grows with the logistics ability at the same speed and
the pull effect equals to the push effect, which shows the supply and demand is balanced, and is the
ideal state of the interaction between the economic growth and logistics industry and the goals of urban
logistics development.
3 Empirical Analysis on the Relationship Between Economic Growth and
Logistics Industry
3.1 Construction of the regression model for economic growth and the logistics industry
This paper makes an empirical analysis about the relationship between the economic growth and the
logistics industry in Xuzhou City from 2000 to 2009, of which the data for 2000-2008 is from
Statistical Yearbook of Xuzhou City, the data for 2009 is collected from the Bulletin of Xuzhou
Statistics Bureau. The specific data is showed in Table 1.
Table 1: Freight volume and GDP in Xuzhou
Freight volume
GDP
Year
(10,000 tons
billion Yuan
）
（
2000
9669
616.30
2001
9785
681.49
2002
9907
749.34
2003
10066
852.26
2004
11348
1031.12
2005
14022
1212.15
2006
16459
1428.80
2007
18480
1679.56
2008
23852
2007.36
2009
23517
2390.16
）
Firstly, descriptive statistics is made according to the data obtained by taking the freight volume(x) as
the abscissa and GDP (y) as the vertical axis to get the plot of the relationship between the two (figure
1). It can be seen from figure 1 that GDP and freight volume appears apparently the positive
110
correlation which will be analyzed quantitatively with SPSS17.0 as a result that the positive correlation
can not be quantified.
3000.00
2500.00
）
n
a 2000.00
u
Y
n
o
i 1500.00
l
l
i
b
（1000.00
P
D
G
500.00
0.00
0
5000
10000 15000 20000 25000 30000
freight volume（10,000 tons）
Figure 1: Plot of freight volume and GDP
As the plot can not determine which type of model is closer to the sample, curve estimation model is
constucted (Figure 2). As can be seen from Figure 2, the quadratic polynomial regression curve is of
the highest goodness of fit with the observation value of the sample. Through the above analysis and
comparison, the quadratic function is chosen to make a regression analysis on the relationship between
GDP (y) and freight volume(x). The specific equation is:
(3)
y = −1.136 × 10 −6 x 2 + 0.143x − 554.326
Figure 2: Curve estimation of GDP and freight volume
Through the analysis, the correlation coefficient of the regression equation R = 0.981, coefficient of
determination R2=0.963, adjusted coefficient of determination R 2 =0.952. All this indicates a strong
representation of the sample regression equation.
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Table 2: Regression test-analysis of variance
Soruces
variation
Quadratic sum
Degree
freedom
Regression
3148657.247
Residual
Total
：
of
of
Mean square
F
Sig.
2
1574328.623
90.204
.000
122170.905
7
17452.986
3270828.152
9
Remark independent variable is the freight volume
As can be seen from Table 2, F = 90.204, Sig.is less than 0.05 indicating that there truly exists a
regression relationship between GDP y and freight volume x.
3.2 Analysis of economic logistics elasticity
From equation (3) can be drawn, the relationship between GDP of Xuzhou and freight volume appears
as an inverted U quadratic curve. According to the calculation, when the freight volume x<62940.14,
GDP and freight volume changes in the same trend, that is when the logistics industry is in miniature,
the pull effect of logistics industry on the GDP growth increases with its own expansion of scale; and
when x> 62940.14, the two showed the reverse trend which means that when the logistics industry is
large-scale, the pull effect of logistics industry on the GDP growth decreases with its own expansion of
scale. However, this can not reflect the change proportion of the GDP relative to the logistics industry.
Therefore, the value of economic logistics elasticity is solved according to equation (2) as follows:
dy x
E=
×
dx y
(4)
− 2.272 × 10 −6 x 2 + 0.143x
− 1.136 × 10 −6 x 2 + 0.143x − 554.326
Substituting the data in Table 1 into the equation (4), we can get the elasticity coefficient of economic
logistics of 2000-2009, as shown in Table 3.
=
Table 3: Elasticity coefficient of economic logistics
Year
Freight volume
tons
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
9669
9785
9907
10066
11348
14022
16459
18480
23852
23517
）
（ 10,000
Elasticity of
logistics(E)
economic
1.62
1.61
1.59
1.57
1.44
1.27
1.17
1.10
0.96
0.97
As can be seen from Table 3, in recent years, Xuzhou Economic Logistics elasticity coefficient E shows
an overall downward trend. Before 2008, E>1, indicating that economy grows faster than the logistics
development and the relationship between economic growth and logistic ability mainly appears as the
logistics pull effect on the economic growth, economy’s push effect on the logistics development is less
strong enough. From 2008 to 2009, E<1, showing that the relationship between economic growth and
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logistic ability mainly appears as the economy’s push effect on the logistics development, logistics’ pull
effect on the economic growth is not so obvious. Specifically, as the logistics industry increases 1%, the
correspondent GDP growth of Xuzhou is respectively 0.96% in 2008 and 0.97% in 2009. The analysis
is indeed based on model (4), in which only one index---freight volume is considered for the growth of
the GDP, that is, only one push factor for GDP growth is dealt with without other factors involved,
which may credit the pull effect of other factors to that of logistics industry. This is a limitation of the
model.
4 Conclusion
This paper pinpoints the stage characteristics of logistics industry development and its contribution
effect to the economic growth of a city through quantifying the mutual relationship between the
economic growth and the logistics industry development in Xuzhou from 2000 to 2009. Generally
speaking, the relationship between Xuzhou economic growth and the logistics industry appears as an
inverted U-quadratic curve. Before 2008, the development of Xuzhou logistics industry has effectively
pulled the economic growth, yet since 2008, the logistics industry’s pull effect on the economy is not so
obvious, and even gradually abating.
To keep the supply and demand balance of logistics in Xuzhou and to ensure the favorable interaction
between economic growth and logistics industry, Xuzhou should seize the golden opportunity brought
about by national adjustment on the logistics industry and the plan of rejuvenation, and correctly grasp
the market demand of logistics according to the economic development status and true productivity
level, and furthermore develop right and reasonable policies for the logistics industry aimed at the
characteristics of different stages. By doing this, the logistics development can be planned synthetically
with the improvement of the logistics infrastructure and equipment as well as the speeding-up
establishment of logistics information platform so that the further integration of logistics resources and
optimalization of the structure of logistics ability can be achieved to accomplish the scientific
development of logistics industry.
Acknowledgements:
We are grateful for the financial support from the key discipline development project ‘Coal industry
strategy and security management’ of ‘the Third 211 Project’ of China University of Mining &
Technology(CUMT), science and technology foundation of CUMT (NO. 2007B026), 2008 scientific
research innovation project for graduates of Jiangsu provincial universities (NO. CX08B-042R) and
2008 opening research foundation for the State Key Laboratory of Coal Resources and Mine Safety of
CUMT NO. 08KF05 .
（
）
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