iBusiness, 2010, 2, 395-400
doi:10.4236/ib.2010.24052 Published Online December 2010 (http://www.scirp.org/journal/ib)
Copyright © 2010 SciRes. iB
Research of Logistics and Regional Economic
Ana Wang
Dongbei University of Finance and Economics, Dalian, China.
E-mail: wangana@dufe.edu.cn
Received August 11th, 2010; revised October 6th, 2010; accepted November 19th, 2010.
This paper used Granger causality test method to analyze regional GDP growth in the domestic and regional freight
turnover. And this paper used logistic model to analyze the reasons that regional logistics promote Anhui economic
growth. Through the analysis that find Anhui economic growth on the leading role of regional logistics is not obvious.
This showed that the role of regional logistics in promoting economic growth in Anhui Province has not been fully
played out, which was not showing a good momentum of development co-ordination. So logistics will play an active
role in the economy of Anhui province in the future.
Keywords: Logistics, Economic Growth, Granger Causality Test, Logistic Model
1. Introduction
With economic globalization and the deepening of social
division labor, logistics as a sophisticated organization
and management technology, which showed more and
more important strategic position in the region economic
development, and gradually cause for concern. Thus the
interaction between regional logistics and regional eco-
nomic growth has also thus become a hot research spot.
Foreign theoretical studies on the relationship of regional
logistics and regional economic growth started from We-
ber’s Industrial location theory. Danuta. Kisperka-Moron
[1] studied the relationship between economy and logis-
tics in the period of economic transformation. He pointed
out that the logistics problem is important issues of
economy in the economic transition. Different economic
period’s inventory reflects the changes of logistics. Keith
G. Debbage (1999) and Kenneth Button, Samantha Tay-
lor [2] studied the relationship between the air transport
and regional economic development. Keith G. Debbage
[3] thought that the air transport and regional economic
development have an important link. Kenneth Button
established a relational model of a new economic system
of the United States and inter-regional air transport.
Wei-Bin Zhang [4] studied the conditions of transport on
economic growth and the impact of the economic zone.
Taking into account transport is the most important part
of logistics, and the research of the relationship between
transportation and regional economic can reflect its in-
trinsic role at a certain extent. In addition, Hunsoo Lee
and Han Mo Yang [5] studied the development strategy
of South Korea Incheon International Airport. The re-
search identified its development potential as the logistics
center of Northeast Asia.
Domestic studies on the relationship between re-
gional economic and regional logistics started in the 20th
century. Some studies are fully aware of the dynamic
role of regional logistics in economic development.
These research results further deepen the internal rela-
tionship between regional logistics and regional eco-
nomic. And it provides some new ideas and methods for
studying the relationship from many facts.
Zhang Wenjie [6] used regional economy and trade
theory to demonstrate the relationship between regional
logistics and regional economic and pointed out that
China’s economic development promoted the develop-
ment of modern logistics. As the same time modern lo-
gistics development also changed the regional economic
growth ways and promoted the formation of new indus-
tries and optimizes the regional industrial structure.
Zhonggang [7] defined the exact meanings of regional
logistics and regional economic growth. He selected
three variables (freight, freight turnover, logistics net-
work) as indicators to describe logistics from different
aspects and also took every region’s GDP as its descrip-
tion indicators of economic growth. He had established
Research of Logistics and Regional Economic Growth
Copyright © 2010 SciRes. iB
two single-equation regression models about the effects
of regional logistics impacted on the regional economic
With the policy of expanding domestic demand and
the gradual implementation of the strategy of china cen-
tral, further promote the division of labor in the Pan-
Yangtze River Delta, Hefei, Wuhu mussels innovation
comprehensive reform pilot area to speed up the con-
struction, in particular the industrial transfer demonstra-
tion region of the city-cluster along the Yangtze River in
Anhui ,which makes the development of Anhui's econ-
omy is facing a new height, but also bring an important
opportunity for regional logistics development to Anhui
Province. Logistics as an important part of Anhui’s
economy, which has a great significance to Anhui eco-
nomic growth, the interaction between the two studies
for the promotion of regional logistics development in
Anhui Province, and to promote regional logistics and
Anhui economy coordinated development.
2. Data Collection, Analysis Methods and
Model Selection
2.1. Analysis Index
2.1.1. Regional Logistics Index Determination
Logistics is a complex economic phenomenon and so far
our country has not established a unified logistics index
system. Improving the cargo turnover of logistics, accel-
erating the turnover rate of goods and flow rate of occu-
pancy funds, which play an important role for improving
the national economy and the development of logistics
industry. While cargo turnover is a real indicator, it is not
impacted by the price level index fluctuations. Therefore,
cargo turnover represents the level of development of
Anhui regional logistics is more appropriate (Table 1).
2.1.2. Regional Economic Growth Indicators
In this article, economic growth measured economic devel-
opment from the perspective of quantity. Taking into ac-
count the availability and effectiveness of data, then select
the gross domestic product (GDP) as a measure of indica-
tors of economic growth in Anhui Province (Table 2).
2.2. Granger Causality Test
2.2.1. Stationarity Test
Analysis of the time series data by the method of tradi-
tional regression analysis are implicitly assumed the time
series is stationary. And Standard method is the unit root
test. This paper used the method of ADF (Augmented
Dickey-Fuller Test) test.
2.2.2. Cointegration Test
Cointegration is used to describe the long-term stable
Table 1. Cargo turnover of anhui province in recent twenty
Total cargo
(Million tons)
Total cargo
(Million tons)
Total cargo
(Million tons)
1990662.3 1997 908.6 2004 1456.3
1991691.5 1998 917.9 2005 1566.5
1992777.8 1999 977.5 2006 1703
1993876.2 20001077.7 2007 1989
19941001.3 20011066 2008 5843
1995906.8 20021249.8 2009 6273.3
1996942 20031355.8
Source: “Statistical Yearbook of Anhui province in 2008” and “National
Economic and Social Development of Anhui Province Statistical Bulletin in
Table 2. Gross domestic product of Anhui province in re-
cent twenty years.
Year GDP
(BillionYear GDP
(Billion Year GDP
1990658 19972347.3 2004 4759.3
1991 663.5 19982543 2005 5375.1
1992801.2 19992712.3 2006 6131.1
19931069.8 20002902.1 2007 7364.2
19941488.5 20013246.7 2008 8874.2
1995 1810.7 2002 3519.7 2009 10052.9
1996 2093.3 2003 3923.1
Source: “Statistical Yearbook of Anhui province in 2008” and “National Eco-
nomic and Social Development of Anhui Province Statistical Bulletin in 2009”.
relationship of the level value of some economic vari-
ables. This paper selected method of Johansen cointegra-
tion test.
2.2.3. Granger Causality Test
The two variables y and x, Granger causality test requires
the following regression is estimated:
iti it
aax u
 
 (1)
 (2)
y represents Gross national product. x represents the
cargo turnover. In general, if the x impacted y, that x is a
Granger cause of y, and the changes of x must before the
changes of y. Therefore, when do the regression analysis
of y impacted on the on the other variables, if the past or
lagged values of x were encompassed can significantly
enhance the explanatory power of regression, which can
be considered x is the Granger reason of y. It also set up
in turn.
2.3. Logistics Model
2.3.1. Logistic Function Model
Logistic function model also was known as growth curve
function model. It is widely used in biological growth
process and a description of the process of industrial
Research of Logistics and Regional Economic Growth
Copyright © 2010 SciRes. iB
growth. The function expression is:
where, y as the dependent variable, x as independent
variable, k, a, b for the unknown constants, k > 0, a > 0,
0 < b < 1.
Logistic curve describing phenomena characterized by:
With the growth of x, the initial values of y slowly grow,
and then gradually speed up to access to accelerated
growth stage; when it reached Inflection point (x*, y*),
with the increasing saturation,
The rate of growth from the “incremental” into the
“decline”; finally entered a stable stage, the growth rate
gradually converge to zero, close to a horizontal line.
The contribution of regional Logistics for regional eco-
nomic growth also has a maximum, and then stabilized.
Therefore, by the growth curve function of logistic to
analyze the impact of freight on the role of GDP had a
high similarity and feasibility.
2.4. The Model of Interaction between Regional
Logistics and Regional Economic Growth
2.4.1. Marginal
In economics, marginal describes the amount of an
economic variable changes when other variables change
1%. In this paper, the “marginal” expressed the con-
structions of regional logistics about the role of regional
economic growth. That is the amount of economic
growth that was caused by a unit Logistic growth. Spe-
cific formula is:
dy b
dx kab
 (4)
2.4.2. Elastic
In economics, Flexibility is described the percentage of
an economic variable changes with other economic vari-
ables changed 1%. In this paper, the concept of “flexibil-
ity” means the rate of regional economic growth was
pulled by every 1% increase in regional logistics. Spe-
cific formula is:
dy xxb
dx ykab
 (5)
2.4.3. Inflexion Point
The leading role of regional logistics on regional eco-
nomic growth changed at inflection point (x*, y*). At this
time the growth rate is from the increased into the de-
creased. Inflection point is that the second derivative of
the function equal to zero. The value of inflection point
ln 0
xx x
dy bab
dxk abk abkab
3. Empirical Analyses
3.1. The Qualitative Analysis of Regional
Logistics and Economic Growth in
Anhui Province
1) The rapid and healthy development of logistics in
Anhui Province is not only the protection of economic
growth, or the power to promote further economic
growth. Regional transport network is continuously im-
provement in road, rail and water transport and other
aspects. It has basically formed a more reasonable logis-
tics network system. The economy of Anhui province
has been able to fast-growing must thanks to the devel-
opment of regional logistics. Because it promoted social
division of labor deepening. So that the specialized mar-
ket of Anhui province continuously improve.
2) The unique nature of economic growth of Anhui
province determined the development of regional logis-
tics. Regional characteristics industries relatively con-
centration in the region and the relevance of industries
created important practical conditions for the construc-
tion of the regional logistics. The development of re-
gional characteristics industries required a large devel-
opment of regional logistics objectively.
Market-oriented, play all over the resources positively,
nurturing a distinctive regional economic, which pro-
moted the rise and development of regional logistics.
3) Mutual promotion and coordinated development of
Logistics and economic growth in Anhui Province. Anhui
province’s rapid economic growth generated huge demand
for logistics, which is the power that regional logistics
network continue to improve. While the development of
regional Logistics also promoted the social division of la-
bor, specialized production and foreign trade, and further
promote the rapid economic growth in Anhui Province.
3.2. Quantitative Analysis of Regional Logistics
and Economic Growth in Anhui Province
3.2.1. Time Series Stationarity Test
Because of the logarithmic function does not change the
monotonicity of the function, can eliminate heterosce-
dasticity, smooth data and reduce the volatility series. So
this paper carried out the Logarithmic based on the
original data. This article used the corresponding letter
variables to represent the indicators of regional logistics
development and regional economic growth. The corre-
sponding relationships between the variables and their
indicators are as Table 3 shows.
The paper uses the Eviews software to test the regional
Research of Logistics and Regional Economic Growth
Copyright © 2010 SciRes. iB
logistics indicators (cargo turnover) and economic grow-
th indicators (GDP) and the stationarity of time series.
Select the ADF test in this paper, test results are as fol-
lows (Table 4):
As can be seen from the above table, ADF statistics of
logarithm of the time series and the ADF statistic of
first-order difference are both greater than the critical
value of the difference sequence. This shows that each
time series are non-stationary series and the first order
non-stationary series. However, the ADF statistic of
second-order difference of the time series are less than
the critical value of the difference sequence, which indi-
cate that the time series between economic growth and
logistics are second-order stationary sequence in Anhui
3.2.2. Cointegration Test
Cointegration test between regional logistics and re-
gional economic growth is actually a test of a long-term
stable relationship between these two variables. This
paper chooses the method of Johansen cointegration test.
The paper obtained the following results by using
Eviews econometric analysis software (Table 5).
As can be seen from the above table, there is a cointe-
gration between regional logistics and Economic Growth
of Anhui province at the 5% significance level. It shows
that a long-term stable relationship exists between the two.
3.2.3. Granger Causality Test
According to the principle of Granger causality test, two
Table 3. Corresponding relationships between indicators
and variables.
Indicator GDP Cargo turnover
Variable GDP HZL
Logarithmic form
of variable LGDP LHZL
First-order difference DLGDP DLHZL
Second-order difference D2LGDP D2LHZL
Note: The letter variables are the abbreviation of the first letter of the indi-
Table 4. Stability test of year sequence.
Variable Test form
LGDP (C,T,2) 2.15 3.58 3.71 4.62 non-stationary
DLGDP (C,T,2) 2.31 2.30 3.37 4.67 non-stationary
D2LGDP (0,0,1) 2.16 3.85 1.96 2.73 Stationary
LHZL (C,T,2) 2.06 0.64 3.71 4.62 non-stationary
DLHZL (C,T,2) 2.09 0.70 3.73 4.67 non-stationary
D2LHZL (0,0,1) 2.00 2.82 1.96 2.73 stationary
Note: test forms (C, T, K) denoted unit root test equation with the intercept,
with time trend and lagged order, D as the difference operator.
Table 5. Cointegration test between anhui gdp and cargo
Eigenvalue Likelihood
5% Critical
1% Critical
No. of CE(s)
0.621771 19.8828112.53 16.31 None**
0.123963 2.3822363.84 6.51 At most 1
assumptions that the cargo turnover lead to economic
growth or economic growth lead to the improvement of
cargo turnover can be tested by the method of Granger
causality test. This paper tested the above variables, test
results are as follows (Table 6).
The value of P indicates the probability of accepting
the null hypothesis in the above form. The number is
lower that the ability that the independent variables cause
the dependent variable is stronger. From the above test
results, you can see the cargo turnover and GDP of An-
hui Province had a relatively strong correlation. At sig-
nificance level of 10% that GDP can not cause cargo
turnover, while at the same significance level of 10%
that cargo turnover can cause GDP.
3.2.4. Determine the Logistic model
Granger causality test model shows that regional logis-
tics has become an important factor in regional economic
growth. So we can select the appropriate mathematical
model to describe the relationship between the regional
logistics and regional economic growth. According to the
analysis between the regional logistics and regional eco-
nomic growth, the paper thinks that the Logistic growth
model can truly reflect the dependent relationship the
logistics and economic growth in Anhui Province.
1) Determine the value of k
Known from the theoretical model, 0 < b < 1when
x→∞, y1/k, that 1/k is the saturation value of y. How-
ever, y as the GDP, it can’t be the saturation value in fact.
And x (cargo turnover) can not tend to infinity in the real
economic life. The model is mainly used for analysis of
the relationship between cargo turnover and economic
growth. So that x does not have to be extrapolated to
infinity. Based on this, according to GDP’ growth rate of
10% to project that Anhui’s GDP is about 2.6075 trillion
Yuan in 2020. Set 1/k = 26075.
2) Estimate Model Parameters
In the use of OLS method, we obtain the following
results (Table 7):
That can be seen from the results: P = 0.0004 < 0.05,
the explanatory variables had significant impacts on the
dependent variable at 5% significant level. DW = 1.482,
At this point the sample size n = 20, in a condition of one
explanatory variable and given significance level a = 0.05,
searched the DW table l = 1.20, dU = 1.41, then dU < DW
= 1.482 < 4 d
U = 2.59, so known from the decision
Research of Logistics and Regional Economic Growth
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Table 6. Grand test result between Anhui GDP and cargo
Null Hypothesis Obs F-statistic Probability
LNHYC does not
Granger cause LNGDP 18 2.88611 0.09179
LNGDP does not Granger
cause LNHYC 18 0.32406 0.72889
Table 7. Estimated results of ols.
Variable Coefficient Std. Error t-Statistic Prob.
X -0.000430 9.94E-05 -4.323811 0.0004
C -7.371275 0.220203 -33.47488 0.0000
R-squared 0.909475 Mean dependent var -8.063802
R-squared 0.982223 S.D. dependent var 0.939198
S.E. of regression 0.675816 Akaike info criterion 2.148848
Sum squared resid 8.221090 Schwarz criterion 2.248421
Log likelihood -19.48848 F-statistic 180.69534
stat 1.481885 Prob(F-statistic) 0.000409
Dependent Variable: Y; Method: Least Squares; Date: 08/01/10, Time:
14:23; Sample: 1990 2009; Included observations: 20.
region of DW that the region error sequence of Anhui
does not exist first-order error autocorrelation, thus it
doesn’t need to correct it .Then the determined model is
the model that the logistic model had been linear proc-
essed. If we want to analyze the role of logistics to the
economic growth in Anhui province that need to derive
logistic model from this linear model. The reduction of
the model, the following results:
3.2.5. Marginal Analysis
In the formula, because 0 < b < 1, Lnb < 0, and x
b> 0,
)( x
abk > 0, so this shows that GDP growth with the
growth of cargo turnover. According to the statistics of
cargo turnover of Anhui Province in 2009.that x = 6273.3,
and put it into the following formula
)( 2
 ,
then get the following results
)( billion
That GDP increased 2.217 units (billion) when added
each unit of cargo turnover (billion ton-km).
3.2.6. Elastic Analysis
Because 0 < b< 1, Lnb< 0, x > 0, a > 0, x
b > 0, so
the elasticity
> 0 that showed that the GDP growth and
cargo turnover growth maintain the same growth direction.
Making 0)(
 b
and then 0 kkxLnbabx.The equation is a tran-
scendental equation. The solution was obtained by nu-
merical methods. x = 2501
At this point,
= 10.9 for the maximum, and when x
= 2501, the growth size of cargo turnover is 10%, and the
maximum of GDP growth is 10.9%. Specifically, cargo
turnover of Anhui increased 1% based on the scale of
2009 than could pull 10.9% GDP growth.
3.2.7. Inflection Point Analysis
Although the marginal effect that logistics industry im-
pacted on the GDP is always greater than zero. But ac-
cording to 0
d get that x = 8390.75. When x <
8390.75, xd
>0; When x > 8390.75, xd
This means that the marginal effect that the cargo turn-
over impacted on the GDP can be divided into two
phases: when x < 8390.75, the increase of GDP that was
generated by each additional unit of cargo turnover in-
creased with their increase size; when x > 8390.75, the
increase of GDP that was generated by each additional
unit of cargo turnover decreased with the increase of
their size. Its marginal effect on GDP is not very clear
when the cargo turnover reached a considerable scale.
When x = 8390.75, the marginal effect of cargo turnover
on the GDP is the largest. Anhui’s cargo turnover in
2009 was 627.33 billion tons km. while in the vicinity of
x = 8390.75, the marginal effect close to its maximum.
So development of the cargo turnover timely and appro-
priate can has a most significant role to GDP growth of
4. Conclusions
The paper conducted in-depth study and discussion about
the interaction between regional Logistics of Anhui
province and economic growth by Granger causality tests
and Logistic model. Get the following conclusions:
4.1. The Relationship between Regional Logistics
and Economic Growth is Not a Simple
Relationship. But It is Two-Way Feedback
Relationship of the Coordinated Development
The rapid growth of economic will inevitably bring
about the huge demand of logistics. The increase of
logistics demand will inevitably lead to the increase of
Research of Logistics and Regional Economic Growth
Copyright © 2010 SciRes. iB
logistics investment demand, thereby increasing re-
gional logistics supply capacity. The improvement of
Logistics supply capabilities created conditions for fur-
ther economic development and finally to promote fur-
ther economic growth. From the qualitative analysis
between the development of the regional logistics and
economic growth in Anhui province can be seen that it
really is not a simple one-way promote relations, but
the relationship of coordination and common develop-
4.2. Granger Causality Test Method is an
Effective Method to Analyze the Interaction
between the Regional Logistics and
Economic Growth
In previous studies, often the direct use of regression
analysis of regional logistics and analysis of the rela-
tionship of economic growth. However, if used the time-
series in the data collection, which is prone to cause
“false return” phenomenon. This paper made a corre-
sponding analysis of the interaction between them by
using the data of regional logistics and economic growth
in Anhui Province. Then the results show that Granger
causality test is an effective research method that ana-
lyzed the relationship between regional logistics and
economic growth.
4.3. The Results of Granger Causality Test
Granger causality test shows that GDP does not cause the
changes of the goods turnover at the 10% significance
level, while the cargo turnover can lead to the changes of
GDP at the same significance level. Granger causality
analysis shows that the regional logistics and regional
economic growth in Anhui Province did not show a two-
way feedback.
4.4. Logistic Models Show That Regional
Logistics Has a Significant Role in
Promoting Regional Economic Growth of
Anhui Province
Marginal analysis shows that each additional unit of
cargo turnover (billion ton-km), GDP corresponding in-
crease 2.217 units (billion). Elastic analysis shows that
cargo turnover of Anhui province grows 1% base on the
scale of 2009 that can pull GDP to grow 10.9%. Inflec-
tion point analysis shows that timely and appropriate
development of cargo turnover has a most significant
role in the growth of Anhui’ GDP.
In short, according to this study that promotes the
healthy development of regional logistics and the coor-
dinated development of economic growth and regional
logistics is till to be the direction of Anhui in the next
period of time. The logistics of Anhui province wants to
become a new economic growth point that also needs
efforts of considerable period time. Must increase in-
vestment in regional logistics and make public know that
the importance of the need of the development of re-
gional logistics. From the government to Logistics enter-
prises to work together to jointly promote the healthy
development of logistics in Anhui Province.
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