Download Economic Growth Effect Analysis on Large-scale Infrastructure Construction

Economic Growth Effect Analysis on Large-scale Infrastructure
Construction
——Taking Nanjing South Station as an Example
WANG Baoqian, DING Minglei
Hohai University Business School, Department of Economics, Nanjing, 210098; &
Office of School-run Enterprises Management, Hohai University, Nanjing, 210098
[email protected] & [email protected]
Abstract: The construction of Nanjing South Station has brought unprecedented development
opportunity to Nanjing city. The article analyzes economic growth effect by cointegration analysis,
concluding that the direct construction investment of Nanjing South Station will draw GDP in Nanjing
approximately 1.49% every year over the next four years. The indirectly driven investment by Nanjing
South Station is more enormous, so the driving function of economic growth will be more remarkable.
The Granger causal relation examination indicates that economic growth will promote investment,
sustained increase of economy has vital significance to the construction and function exertion of
Nanjing south station as well as attached matching facilities.
Keywords: Nanjing South Station, Economic Growth, Cointegration Analysis
1.
Introduction
Western economists Paul Rosenstein-Rodan, Hirschman, Walt Whitman Rostow and others have
researched more in infrastructure, pointed out that infrastructure plays an important role in economic
development[1]; Helmut Seitz and George • Wright have shown that urban infrastructure can reduce costs
significantly, stimulate investments in machinery, equipment as well as land and buildings[2].Jin Fengjun
pointed out that infrastructure development and economic growth are accompanied , infrastructure is not
only the conditions for regional development, but also results of regional development[3].
In the early 1980s, Granger proposed cointegeration analysis method [4], the basic thought is: if two or
more than two variables are non-stationary, but their some kind of linear combination displays the
stability, then these variables exist long-term balanced relations, namely cointegrating. Zhang Xiao-tong
[5]
, Yue Jin-gui[6], Li Qing-mei[7], Cui Liang[8], Sun Yan-ping[9]and others have done some research and
application on cointegeration method.
This paper attempts to establish error correction model, using cointegration analysis to study the
relationship between Nanjing South Station-related investment(including direct investment, as well as
the investment led by South Station Area Development) and economic growth in Nanjing respectively
from the perspective of long-term and short-term.
2.
The scale of investment in Nanjing South Station
2.1 Overview of Nanjing South Station
Nanjing South Station is one of the five departure stations along Beijing-Shanghai high-speed railway,
which is about 10.5 kilometers from Nanjing Center, including Beijing-Shanghai Railway,
Shanghai-Wuhan-Chengdu line, Nanjing-Hangzhou line, Nanjing -Anqing line etc. According to the
forecast, in 2030, Nanjing South Station will send away railway passengers 58.22 million, highway
travelers 11 millionevery year[10].After completion, Nanjing South Station will replace Nanjing Station
to become transportation gateway of Nanjing city, whose scale will have 6 times of Nanjing Station,
more than 70% of the passengers will be diverted at Nanjing South Station, and it will become the fourth
largest integrated rail transport hub designed by China regional passenger transport center in East
-China [11-12].
According to the plan, a first-level highway passenger-transport south station is equipped near by
，
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Nanjing South Station; subway of south-extended line 1, line 3 and line 6 cross underground; bus station
is also designed, providing more than 700 taxi berths, 2000 social vehicle berths; a light rail will be
constructed between Nanjing South Station and Lukou airport, achieving seamless transfer of five kind
of transportation patterns.
2.2 Scale of investment
The Nanjing railway hinge is the biggest junction station that Beijing-Shanghai high-speed railway in
Jiangsu, whose investment will amount to 136 hundred million Yuan, including three bulk projects of
Nanjing South Station, Dashengguan Yangtse River Bridge and more than 20 kilometer railway line[12].
According to the "Controlling Detail Plan of Nanjing South Station Area" established by Nanjing
Planning Bureau, taking Nanjing South Station as the center in a rectangle area of 6 square kilometers, it
will form a entire distribution structure including public servicing facilities area, business district,
entertainment area, inhabitation community, mixed construction area etc.
At present, Nanjing city is planning a “southern new town” occupying 48 square kilometers, taking
Nanjing South Station and Honghua-airport area as the core, Ningnan science and technology plate and
Dongshan area as two wings. "Chinese Real Estate Newspaper" reported that dean Qiu Xiangyang of
Jiangsu urban development research institute considered that with Nanjing “Hexi new town” drew by
Olympic center project similarly, “the South new town” leaded by large-scale railway investment, which
is equal to build again a “Hexi new town”, and estimated: “the government investment as well as the
private investment drew would achieve nearly 1,000 hundred million Yuan at south area in the future
several years [13]. Nanjing Daily reported that Nanjing Development and Planning Commission proposed
that it would invest 1,000 hundred million Yuan to develop Nanjing South Station area from now on,
making it to become with Xinjiekou, Hexi “the tripod standing” urban vice-center [14].
Thus it can be seen that the construction will pull cities investment in fixed assets real estate investment
enormously especially in Nanjing South Station area, commerce and trade, logistics, catering, real estate
will obtain fast development, promoting economic growth of Nanjing.
，
3. Cointegration analysis
As one of the three carriages driving economic growth, investment not only pulls demand, but also
affects demand structure, providing necessary material and technical support for long-term economic
growth.
3.1 Data selection
This paper uses Nanjing GDP, entire social fixed assets investment (excluding countryside non-peasant
household investment), commodity retail price index as original data of the model, which originate from
Nanjing Statistics Bureau provided" Nanjing Statistical Yearbook "and statistical analysis. By using
Nanjing GDP to reflect economic growth, this article selects retail price index and takes 1990 as the base
period to eliminate price influence on Nanjing GDP and entire social fixed assets investment. This
article also makes natural logarithm processing on the data to eliminate different variance influence.
Construction investment related to Nanjing South Station (including direct investment and the driven
development investment) involves the urban fixed-asset investment and real estate development
investment, but does not include the investment in rural non-farm households, thus the entire social
fixed assets investment excludes the investment in rural non-farm households; due to the adjustment of
statistical system, this article makes corresponding data processing to eliminate the impact of investment
in rural non-farm households.
This article uses statistical software EViews5.0 version to carry on the related statistical test and the
regression analysis, Y and X represent separately Nanjing GDP and entire social fixed assets investment
rejected countryside non-peasant household investment (eliminating price influence), LNY and LNX
represent the data that carried on natural logarithm processing.
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List of part economic statistical data on Nanjing
Unit: Hundred million Yuan
The entire
The entire social fixed
Commodity
social fixed assets
GDP
retail price X
Y
LNX
LNY
Year
assets
investment
index
investment
1
1990 42.65
37.26
176.52
100
37.26
176.52
3.618 5.173
1991 49.71
43.87
202.37
105.3
41.66
192.18
3.729 5.258
1992 82.22
63.39
263.67
99.8
60.32
250.90
4.100 5.525
1993 126.46
98.39
355.25
116
80.71
291.42
4.391 5.675
1994 154.36
122.11
472.17
121.3
82.58
319.32
4.414 5.766
1995 233.86
197.06
584.59
111.2
119.84
355.52
4.786 5.874
1996 317.95
271.48
682.78
106.1
155.61
391.37
5.047 5.970
1997 351.66
299.62
773.78
97.6
175.96
454.43
5.170 6.119
1998 376.60
322.65
850.24
98.2
192.96
508.49
5.263 6.231
1999 373.01
314.39
937.89
97.1
193.64
577.66
5.266 6.359
2000 412.20
345.37
1073.54
99.2
214.43
666.54
5.368 6.502
2001 464.91
391.42
1218.51
98.8
245.98
765.74
5.505 6.641
2002 602.95
509.78
1385.14
96.3
332.67
903.90
5.807 6.807
2003 954.05
804.22
1690.77
98.1
534.97
1124.71 6.282 7.025
2004 1201.88
984.17
2067.18
98.1
667.36
1401.74 6.503 7.245
2005 1402.72
1123.04
2411.11
96.7
787.51
1690.75 6.669 7.433
2006 1613.55
1263.13
2773.78
98.9
895.60
1966.70 6.797 7.584
2007 1867.96
1487.92
3283.73
99.9
1056.04 2330.60 6.962 7.754
2008 2154.17
1734.33
3775
106.2
1159.06 2522.86 7.055 7.833
Note: The entire social fixed assets investment (1) is rejected rural non-farm households invest; commodity retail
price index takes the price of last year as 100, the price index in 1991, 1992, 1993 come from urban fair trade price
index, the price index in 2008 is consumer price index.
Table 1-1
（）
8.0
7.5
7.0
6.5
6.0
5.5
5.0
4.5
4.0
3.5
3.0
0
9
9
1
1
9
9
1
2
9
9
1
3
9
9
1
4
9
9
1
5
9
9
1
6
9
9
1
7
9
9
1
9
9
9
1
8
9
9
1
LNX
Figure 1-1
0
0
0
2
1
0
0
2
2
0
0
2
3
0
0
2
4
0
0
2
5
0
0
2
6
0
0
2
7
0
0
2
8
0
0 Year
2
LNY
Tendency chart
Figure 1-1 shows that the trend and changing direction of the time series are unceasingly growing and
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basically coincident; the correlation coefficient i reaches as high as 0.9929, which indicates a strong
correlation relationship between LNX and LNY.
3.2 Stable examination
ADF test method is carried out on the unit root test of the sequence of LNX and LNY. C, T, K in the test
form (C, T, K) express intercept term, trend term and lag orders, N expresses that there is no intercept
term or trend term, lag orders are determined according to the criteria of Akaike (AIC). D expresses
difference operator.
Table 1-2 shows that the time sequence of LNX and LNY is unstable, but ADF statistic of the first-order
difference sequence of D (LNX) and D (LNY) at the 5% significance level are less than its
corresponding critical value. Therefore, the first-order difference sequence of D (LNX) and D (LNY) at
the 5% significance level is stable, that is, D (LNX) and D (LNY) are both I (1) (first-order
single-whole) , the variables of LNX and LNY may exist cointegration relationship.
Table 1-2 Stable test result of the sequence of LNX and LNY
Critical value
Test
form
Statistic ADF
C,T,K
1%
5%
10%
（ ）
LNX
（C,N,0)
LNY
（C,N,1)
D(LNX） （C,N,0)
D(LNY） （C,N,0)
Variable
Conclusion
-0.7083
-3.8574
-3.0404
-2.6606
Unstable
-0.1187
-3.8868
-3.0522
-2.6666
Unstable
-3.2022
-3.8868
-3.0522
-2.6666
Stable
-3.3514
-3.8868
-3.0522
-2.6666
Stable
3.3 Cointegration test
Since LNX and LNY are both first-order sequences of a single whole, so we use two-step method of
"Engle-Granger" to check whether there is a long-term stable relationship between them. First, this
article adopts OLS method (ordinary least squares method) on the sequences of LNX and LNY to make
cointegration regression, and obtains a long-term equilibrium equation.
ln Y
）
i
= 2.303 + 0.769ln
X （1.1）
i
(18.75 (34.5)
R-squared=0.9859, F=1190.57, DW=0.6528
Goodness of fit is higher, R-squared= 0.9859; F = 1190.57, significance level is 0, so the equation passes
test F; test t values of the two coefficients are 18.75 and 34.5, significance level is 0, passing test t; DW
= 0.6528, so residual sequences may exit positive correlation. If the sequences of LNX and LNY exist
cointegration relationship, then the residual sequence E of equation (1.1) should be stable, so the article
make unit root test, result of ADF test is as follows:
Table 1-3
（
）
variable
Test form C,T,K
Residual E
（N,N,1)
ADF test result of the residual sequence E
Critical value
Statistic ADF
1%
5%
10%
-2.6308
-2.7081
-1.9628
-1.6061
Conclusion
Stable
The ADF statistic of residual sequence E at the 5% significance level is less than its corresponding
critical value, the residual sequence E at the 5% significance level is stable, and thus concluding that the
residual sequence of E is 0-order single-whole sequence, so we can prove that there is cointegration
relationship between the sequence of LNX and LNY.
As the statistic DW = 0.6528, residual consequence exists a positive- correlation issue, this shows that
economic growth is not only affected by the investment in fixed assets, but also by other factors, so a
first-order autoregressive AR ( 1) is added in the regression equation for amendment, and getting the
following regression results:
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ln Y
i
= 2.341 + 0.762ln
X
i
+0.6788AR (1)
（1.2）
(6.66) (13.02)
(3.41)
R-squared=0.991 F=835.269 DW=1.413
Goodness of fit of the Equation (1.2) is very high, all passing the test without sequence autocorrelation.
It can be considered that LNX and LNY exist positive long-run equilibrium relationship, and the
cointegration coefficient is 0.762, that is, investment in fixed assets for every 1% increase in a long term
will bring a corresponding 0.762% increase in GDP, while economic growth in Nanjing is also affected
by other factors.
，
，
3.4 Error correction model
As said above, cointegration test showed that there is a positive long-run equilibrium relationship
between fixed-asset investment (the exclusion of investment in rural non-farm households) and GDP in
Nanjing, but needing to make further validation in the short-term fluctuations relationship between two
variables. According to the residual sequences of E and D (LNX) and D (LNY), using OLS method to
estimate error correction model as follows:
D(ln Y ) = 0.1 + 0.245* D(ln X
i
i
) − 0.0912* E i −1
(1.3)
(4.943)(2.73)
(-0.781)
R-squared=0.3334 F=3.751 DW=1.492
，
，
F = 3.751, significance level is 0.048, passing F test; t-test values of three coefficients are 4.943,2.73,
-0.781 respectively, corresponding significance level is 0,0.016,0.447, only the regression coefficient of
the error correction item doesn’t pass the t test; DW = 1.492, there is no self-correlation issue, passing
the test; R-squared = 0.3334, goodness of fit is comparatively low.
The above error correction model shows that in a short-term, fixed-asset investment changes 1% will
lead GDP to change in the same direction a about 0.245%; E is a error correction item, error correction
coefficient is -0.0912, which is consistent with the contrary-correction mechanism, reflecting a
mechanism that the error correction model itself can amend deviated balance-error, that is The
non-equilibrium error of previous year amends reversely the error between real GDP of this year and its
long-run equilibrium value at 0.0912%, once the short-term fluctuations deviate from the long-run
equilibrium relationship, the error correction mechanism can correct the deviations, error correction
coefficient is only -0.0912, which indicates non-equilibrium errors have a weak capacity of the
amendment on the long-run equilibrium relationship , also shows that GDP growth in Nanjing is not
only affected by the impact of investment in fixed assets, but also by other factors. As regression
coefficients of the error correction item doesn’t pass t test, so the explanatory power of error correction
coefficient is not very strong.
3.5 Granger causality test
Granger causality tests priority and information content, rather than some sort of causal relationship in a
general sense. If the delayed item of LNX joined helps to predict LNY, or regression coefficient of
lagged variable of LNX shows statistical significance, then that LNX is Granger cause of LNY.
The lagged periods are collected from one, two, three respectively, Granger causality test results
between LNX and LNY are shown in Table 1-4. When the lagged periods are chosen 2, and 3, LNY is
the the Granger cause of LNX at 10% significance level, LNX is not Granger cause of LNY, meaning
that change in GDP is the Granger cause of leading the change of the investment in fixed assets,
previous GDP has ability to explain and predict currently actual capacity of investment in fixed assets,
while investment in fixed assets is not the Granger cause that affects GDP.
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Table 1-4 Granger causality test between LNX and LNY
Conclusion
Null hypothesis
Lag phase Statistics F
5%
LNX is not Granger cause of LNY
0.031
Accept
1
LNY is not Granger cause of LNX
2.126
Accept
Conclusion
10%
Accept
LNX is not Granger cause of LNY
（ ）
LNY is not Granger cause of LNX
LNX is not Granger cause of LNY
LNY is not Granger cause of LNX
4.
2
3
（ ）
Accept
0.294
Accept
Accept
2.964
Accept
Refuse
0.314
Accept
Accept
3.312
Accept
Refuse
Conclusions and recommendations
，
Based on the above analysis we can draw the following conclusions:
(1)There is long-term stable equilibrium relationship between LNY and LNX. Judging from long term,
fixed-asset investment increases by 1% , GDP in Nanjing will increase by 0.762% accordingly; in
short-term, fixed-asset investment increases by 1% , GDP in Nanjing will increase by 0.245% in the
same direction, indicating that fixed assets investment not only promotes the current economic growth,
but also play greater role in promoting sustained economic growth in long-term.
(2) Error correction coefficient shows that the amendment ability of non-equilibrium error on the
long-run equilibrium relationship is not strong, GDP growth in Nanjing is not only affected by the
fixed assets investment but also by other factors, the mode of economic growth in Nanjing is changing,
beginning to shift from investment to consumption and foreign trade.
(3) Granger causality test shows that at 10% significance level, when the lag periods are 2 and 3, three is
one-way causal relationship between LNY and LNX, GDP growth in Nanjing triggers corresponding
increase in fixed assets investment, while fixed assets investment is not Granger cause that affects GDP
in Nanjing to change.
(4) Assuming 13.6 billion investment of Nanjing railway hub is divided into four-year investing period,
annual investment is about 3.4 billion, taking the fixed assets investment in 2008 (excluding investment
in rural non-farm households) and GDP as base number, we can see from above analysis, belong to
direct capital investment of Nanjing railway hub, in the next few years it will provide annual 1.49%
growth in GDP, namely, Nanjing City will increase in GDP 5.626 billion Yuan per year. Thus, in the next
few years, the direct construction investment of Nanjing South Station railway hub is up to 13.6 billion
Yuan, as well as 100 billion Yuan investment led by Nanjing South Station will greatly promote
economic growth in Nanjing. After completing construction, the formed economic stock will have more
sustainable role in promoting economic growth in future.
(5)Sustained and steady economic growth in Nanjing is necessary to ensure the development and
construction investment of the South Station area, but also necessary to play the function of Nanjing
South Station sufficiently, so scientific forecast in future economic growth in Nanjing is essential to
rationally determine the investment scale.
Author introduction:
Wang Baoqian (1964 - ), Regional Economics Ph.D., Associate Professor, Economics Department head
of Hohai University Business School. Main research direction: regionally economic development
strategy and management, privatization of infrastructure and public utilities and so on.
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