Download An Empirical Analysis of Relationship Between Science & Technology

An Empirical Analysis of Relationship Between Science & Technology
Inputs and Economic Growth of Shandong Province
NIU Yongping
School of Economics, Shandong Institute of Business and Technology, Yantai, P.R.China, 264005
[email protected]
Abstract: There is close relationship between science & technology inputs and economic growth. Based
on the data of science & technology input and economic growth of Shandong province, firstly the paper
makes the gray correlation analysis on the economic growth and science & technology inputs of
Shandong province and then builds econometric models for further study. The paper analyzes and
compares the contribution rate of science & technology inputs to economic growth of Shandong
province and China. Of that, there is the closest relationship between economic growth and science &
technology activities, followed by economic growth and science & technology activities expenditures,
again, is R&D expenditures. Finally the paper calculates the contribution rate of science & technology
inputs to economic growth of Shandong province.
Keywords: Science and technology inputs, Economic development, Grey correlation analysis
1.
Introduction
Since the reform and opening up, there has been rapid economic growth in Shandong province and
Shandong economy plays an important role in China. Therefore it is necessary to study the relationship
between science & technology (hereinafter referred to as S&T) inputs and economic growth of the
province. This paper is divided into the following sections: first is to sort out the relevant literature;
second is to collect the basic data of S&T inputs and economic growth of Shandong; third to make grey
relational analysis of S&T inputs and economic growth of Shandong; fourth to establish econometric
model to analyze the relationship between S&T inputs and economic growth to make comparison with
gray correlation analysis; finally to draw conclusions.
About the relationship between economic growth and S&T inputs, domestic studies on this area mainly
focus on three fields: provincial research, regional research and research on the whole society. An Ning
and Luo Shan (2008), Xu Qijuan et al. (2009) and Guo Ruidong(2009) study the relationship between
S&T inputs and economic growth of Guangdong, Zhejiang and Hebei provinces[1] [2] [3]. Liu Huiling and
Yan Hong (2007) study the relationship between S&T inputs and economic growth of western China [4].
Li Xiaojian (2009) studies the relationship between S&T inputs and economic growth of China between
1999 and 2006, and believes that R & D inputs are important to economic growth [5].
About the research methods, the majority of scholars use the grey correlation analysis method or
econometric model analysis, and some scholars use the DEA (DEA) method. Grey correlation analysis
method has the advantage of giving the difference of importance or weight of various variables of
science & technology inputs, econometric model approach has the advantage of giving the clear factor
of explanatory variables and DEA method can clearly describe the efficiency of science & technological
inputs, but DEA method can not give the contribution rate of various factors. This paper will intend grey
correlation analysis method and econometric model analysis method, and make comparison with each
other.
2.
Data
This paper uses the value of GDP to represent economic growth, and to eliminate the price effect, this
paper use price index (base 1994) to divide the nominal GDP to get real GDP. This paper use personnel
engaged in S&T activities, internal expenditures on S&T activities and expenditure on R&D to represent
S&T inputs. Similarly, internal expenditures on S&T activities and expenditure on R&D are the real
ones. All data are collected from China Statistical Yearbooks and Shandong Statistical Yearbooks of
713
each year. As shown in Table 1.
Year
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Table 1 Economic Growth and S&T Inputs of Shandong Province
Real
GDP(100 Personnel engaged in
Internal expenditures
million Yuan)
S&T activities
on S&T activities
(100 million Yuan)
(10 thousand persons)
3844.50
12.76
49.43
4345.04
13.50
52.89
4862.65
14.28
60.80
5314.69
15.11
72.97
5755.21
15.99
89.75
6193.26
16.91
110.41
6778.43
17.89
132.50
7356.03
16.89
143.21
8155.16
15.88
153.99
9362.91
17.04
175.53
10807.08
16.46
215.22
12948.86
18.84
250.51
14817.02
20.43
296.48
17195.97
24.51
405.38
20308.54
27.35
498.01
Expenditure on
R&D
(100 million Yuan)
10.28
11.80
14.58
18.79
24.81
32.77
42.24
48.74
69.97
80.50
101.30
135.52
157.13
206.83
284.44
This paper uses RGDP to represent the growth rate of real GDP, RSP to represent the growth rate of
personnel engaged in S&T activities, RSE to represent the growth rate of internal expenditures on S&T
activities and RRD to represent the growth rate of expenditure on R&D. According to figure 1, it can be
found that there exists certain relationship between RGDP and RSP, RSE and RRD.
RRD
RSP
RES
RRD
1.2
1
0.8
0.6
0.4
0.2
0
59
91
69
91
79
91
89
91
99
91
00
02
10
02
20
02
30
02
40
02
50
02
60
02
70
02
80
02
Figure 1 Relationship between the Growth Rate of Real GDP and the Growth Rate of S&T Inputs of
Shandong Province
3.
The Grey Correlation Analysis on the Relationship between Economic
Growth and S&T Inputs of Shandong Province
3.1 The grey correlation analysis method
Set reference and comparison series. Reference series is Y0 ( k ) = { x0 (1), x0 (2),..., x0 ( n)} , where n is
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the
length
indicator
of
the
series
(for
example,
，
year).
The
comparison
series
are Yi ( k ) = { xi (1), xi (2),..., xi ( n)} , i=1, 2… m k=1, 2… n., where m is the number of comparison
series.
The formula of gray correlation coefficients between Y0(k) and Yi(k) is:
ξi (k ) =
min min x0 (k ) − xi (k ) + ρ max max x0 (k ) − xi (k )
i
k
i
（ 1）
k
x0 (k ) − xi (k ) + ρ max max x0 (k ) − xi (k )
i
k
≤≤
Where, ρ is the resolution factor, generally taken 0.5 ρ 1.
Finally, the relative correlation degree between Y0 and Yi is :
δi =
（2）
1 n
∑ ξi (k )
n k =1
3.2 The process of grey correlation analysis
Set reference and comparison series. Y0 (k) is reference series on behalf of economic growth, where
x0 is the value of annual real GDP. Yi (k) are comparison series on behalf of S&T inputs, where x1 is the
number of annual personnel engaged in S&T activities, x2 for the value of annual internal expenditures
on S&T activities and x3 for the annual expenditure on R&D.
Dimensionless original data. There are initial value method and mean method and so on. This paper
takes initial value method.
According to formula(1) ,the grey correlation coefficients between Y0 (k) and Yi (k) can be
calculated, where ρ = 0.5.
According to formula (2) , the relative correlation degree δi between Y0 and Yi can be calculated.
According to above data and methods, the grey correlation coefficients between Y0 (k) and Yi (k) can be
calculated, as shown in table 2.
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②
③
④
Table 2 Grey correlation coefficients between Economic Growth and S&T Inputs of Shandong Province
Year
Y0 ~Y1
Y0 ~Y2
Y0 ~Y3
Year
Y0 ~Y1
Y0 ~Y2
Y0 ~Y3
1994
1.00
1.00
1.00
2002
0.93
0.92
0.70
1995
0.99
0.99
1.00
2003
0.91
0.91
0.67
1996
0.99
1.00
0.99
2004
0.88
0.88
0.61
1997
0.98
0.99
0.96
2005
0.86
0.87
0.53
1998
0.98
0.97
0.92
2006
0.83
0.84
0.49
1999
0.98
0.95
0.88
2007
0.81
0.75
0.42
2000
0.97
0.92
0.83
2008
0.78
0.70
0.33
2001
0.95
0.92
0.80
Mean
0.92
0.91
0.74
According to table 2, the value of δ1, δ2 and δ3 are respectively 0.92, 0.91and 0.74. First, there is the
closest relationship between GDP and personnel engaged in S&T activities with the relative correlation
degree being 0.92; second is the relationship between GDP and internal expenditures on S&T activities
with the relative correlation degree being 0.92; finally is the relationship between GDP and expenditure
on R&D with the relative correlation degree being 0.74. These results prove that labor is still the most
important factor in S&T activities in Shandong Province, also meet the basic conditions in Shandong
Province as well in the country that labor-intensive enterprises are in the dominant position.
4.
The Econometric Model Analysis on the Relationship between Economic
Growth and S&T Inputs of Shandong Province
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This paper sets real GDP as dependant variable and the elements of S&T inputs as independent variables.
Taking into account that independent variables include the index of personnel engaged in S&T activities
whose dimension is inconsistent with dependant variable, which can affect economic significance of the
model, this paper use growth rate to replace real value. This paper uses RGDP to represent the growth
rate of real GDP, RSP to represent the growth rate of personnel engaged in S&T activities, RSE to
represent the growth rate of internal expenditures on S&T activities and RRD to represent the growth
rate of expenditure on R&D. By examining the relevant literatures and taking into account that
expenditure on R&D is a part of internal expenditures on S&T activities, this paper designs econometric
models as follows:
Model 1 RGDP=C0+C1*RSP+C2*RSE+ε1
3
Model 2 RGDP=C3+C4*RSP+C5*RRD+ε2
4
Where, model 1 measures the relationship between the growth rate of real GDP and the growth rate of
personnel engaged in S&T activities and the growth rate of internal expenditures on S&T activities,
model 2 measures the relationship between the growth rate of real GDP and the growth rate of personnel
engaged in S&T activities and the growth rate of expenditure on R&D, C0 and C3 for the constant, C1,
C2, C4 and C5 for the coefficients, ε1, ε2 for residuals.
According to the data of table 1, this paper calculates the growth rate of each variable and then makes
OSL regression analysis using SPSS13.0 statistical software .the results are shown in table 3.
：
：
（）
（）
Coefficients
Model 1
Model 2
C0
C1
C2
C3
C4
C5
0.128
0.683
0.264
0.109
0.514
0.010
Table 3 Results of OSL regression
t-test
D-W
F
R
value
4.495
1.664
25.212 0.953
3.193
3.092
5.417
1.606
20.761 0.904
4.220
3.221
Adjusted R2
Residuals
0.849
0.062
0.877
0.073
According to Table 3, F test value, D-W test value, R2 test value and the residuals meet the basic
requirements; there is no collinearity among the variables, so the equation itself has significance. The
significance probability of each variable is less than 0.05.
Model 1
RGDP=0.128+0.683*RSP+0.264*RSE
5
Model 2
RGDP=0.109+0.514*RSP+0.010*RSE
6
According to equation (5) and (6), there is significant correlation between the growth rate of real GDP
and the growth rate of personnel engaged in S&T activities of Shandong Province, followed is the
relationship between the growth rate of real GDP and the growth rate of internal expenditures on S&T
activities and the relationship between the rate of real GDP and the growth rate of expenditure on R&D
is the weakest. These are consistent to the results of the previous grey correlation analysis. After
averaging all the coefficients of model 1 and model 2 and standardization, this paper gets the
contribution rate of the growth rate of S&T inputs to the growth rate of real GDP of Shandong is 0.29.
The economic significance is that if the growth rate of S&T inputs changes 1 percentage, the growth rate
of real GDP changes 0.29 percentage.
：
：
5.
（）
（）
Conclusion
According to the above analysis, this paper gets following conclusions:
According to the grey correlation analysis, there is the closest relationship between real GDP and
①
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personnel engaged in S&T activities in Shandong province, the second is the relationship between real
GDP and internal expenditures on S&T activities and the third is the relationship between real GDP
and expenditure on R&D .
According to the econometric model, there is significant correlation between the growth rate of real
GDP and the growth rate of personnel engaged in S&T activities of Shandong Province , followed is the
relationship between the growth rate of real GDP and the growth rate of internal expenditures on S&T
activities and the relationship between the rate of real GDP and the growth rate of expenditure on R&D
is the weakest.
The contribution rate of the growth rate of S&T inputs to the growth rate of real GDP of Shandong is
0.29.
②
③
References
[1]. An Ning, Luo Shan.An Empirical Analysis of Relationship between Economic Growth and Science
& Technology Inputs of Guangdong Province. Science and Technology Management Research,
Science and Technology Management Research ,2008(12),190-193(in Chinese)
[2]. Xu Qijuan, Ye Shanwen, Zhu qijuan. An Empirical Analysis of Relationship between Economic
Growth and Science & Technology Inputs of Zhejiang Province. Statistics and Decision,
2009(16):86-87(in Chinese)
[3]. Guo Ruidong. An Empirical Study on the Dynamic Equilibrium between Local Government
Financial Investment in Science and Technology and Economic Growth in Hebei Province. Journal
of Hebei University of Science and Technology (Social Sciences), 2009(1):7-11(in Chinese).
[4]. Liu Huiling, Yan Hong. An Empirical Analysis of Relationship between Economic Growth and
Science & Technology Inputs of Western China. Special Zone Economy, 2007(6):194-195(in
Chinese).
[5]. Li Xiaojian. The Grey Correlation Analysis on the Relationship between Economic Growth and
S&T Inputs of China. Theory Monthly, 2009(8): 78-81(in Chinese).
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