Download Management & Engineering Technology Progress to Economic Growth in China

Management & Engineering 10 (2013) 1838-5745
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Management & Engineering
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An Empirical Analysis on the Contribution Rate of Science &
Technology Progress to Economic Growth in China
Yefeng ZHANG , Wenyin WANG
School of Economic & Management, North University of China, 610036, P.R.China
KEYWORDS
ABSTRACT
Science & technology progress,
Production function,
Contribution rate,
Economic growth
Based on the statistical data from 1980 to 2009 in China, building broad C-D production
function model, the paper has analyzed the contribution of scientific and technological
investment, labor inputs and science & technology progress to economic growth in China.
The results show that capital investment and science & technology progress in China become
a major factor in economic growth, and some advice that the future economic growth in
China still needs to strengthen science & technology progress is put forward.
© ST. PLUM-BLOSSOM PRESS PTY LTD
1 Introduction
In the Fifth Plenum of the17th CPC Central Committee has also pointed out the Twelfth Five-year Program period is the key period
to build comprehensive well-off society and is crucial period to deepen reform and opening up and speed up the transformation of
economic development mode.[1] Chinese economic growth pattern of transformation is mainly changing from extensive growth
pattern relying on labor and capital to intensive growth pattern relying on scientific and technological progress, from the
investment-driven type to the technological progress; from technology introduction type to Independent Innovation Technology
Introduction Technology Introduction type. In addition, we are currently "Second Five Year Plan" the first year, peace, development
and cooperation are still the trend of the times in today's world. The world multi-polarization and economic globalization has been
future developed. The world economic and political patterns have taken on the new change. The future of human beings and the
prosperity of the country are more than ever depending on the development of science and technology. Scientific and Technological
progress has become the major driver of each nation economic growth. Therefore, it has important practical significance that this
paper uses broad C-D production function model to study the contribution of science & technology progress to economic growth in
China.
2 The Model Introduction
In1928, economics professor Douglas and mathematicians Cobb in the university of Chicago has studied and analyzed the historical

Corresponding author.
E-mail address: [email protected]
English edition copyright © ST. PLUM-BLOSSOM PRESS PTY LTD
DOI:10.5503/J.ME.2013.10.001
3
data on made in USA between 1899 and 1922, and pointed out that the main factors of the inputs in the production is to labor and
capital, but the contribution of the rest of the production factors to the output is negligible. Then they brought up the well known
Cobb-Douglas production function in the econometrics [2] [3]: Y  f ( K , L)  AK  L
Where, K and L are respectively capital and labor inputs in the production process, Y is likely to be the maximum output.
elastic coefficient of capital inputs,


is
is elastic coefficient of labor inputs. If the sample is time series data, then C-D function will
be written as the generalized production function: Y  A0 e t K  L
Where,
A0
is the technical level in the base period, t is the time variable.
A0 e t reflects the influence of technological progress to output, and A0 , 

is the average annual growth rate for the technology.
are the parameters for to be estimated.
3 Model Building, Estimation and Parameters Test
Most countries or regions still use GDP index at the present [4]. So this paper selects GDP as measuring the index of our country
economic outputs, written as GDP. According to the related calculating method, it fits the actual situation to put all the social fixed
assets investment each year as capital inputs [5] So this paper selects all the social fixed assets investment as capital inputs index,
written for K. The statistical classification of our country to labor category is referenced to statistical classification of each market
economic countries and to establish labor market statistical system which adapts to the situation of our country's labor market
development. Currently our country’s Labor market scope is constantly changing. [6] Therefore, this paper selects total number of
employed persons at the end of year employment as labor inputs index, written as L. The sample data of this paper is the annual data
in 1980-2009, a total of 30.
The both sides of generalized C-D production function take logarithm:
LNGDP  LNA0   t   LNK   LNL  1.....(1)
According to the data the annual data in 1980-2009, we use Eviews6.0 software to take least squares estimate with (1) type:
ˆ
LOG(GDP)
 5.012370  0.036276  t  0.536745  LNK  0.901683  LNL+µ
1
(t value)
(-1.826494)
(1.922392)
(3.520970)
(5.324453)
R2 =0.996404 R 2 =0.995989 F=2401.533 S.E=0.086714 D.W=0.453043
When model goodness of fittest ( R ) is high, F value is high, and variance Var (  j ) of each regression parameter estimation is
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very large (ie, t value is very low), this shows there may exist the multicollinearity in explanatory variables. [7] The estimation above
meet the case, and T test of C value and T value didn't pass, so explanatory variables LNL and explanatory variables LNK may exist
multicollinearity. We found the correlation coefficient between explanatory variables LNL and LNK reached 0.946029, and can
judge exists serious multicollinearity. This may be one reason that test of C value and T value didn't pass. So model needs to be
amended to eliminate multicollinearity.
4 Model Modification
We can use per capita GDP (GDP/L) and per capita (K/L) to eliminate multicollinearity in the state of constant returns to scale
(     1 ). Whether the specific problem of investigation can exert constraint conditions or whether the constraint model directly
exert regression, we will also carry out the corresponding test. In Eviews software, Wald test is usually used.
[8]
Wald test is to
determine whether fitting results meets the constraint condition of the coefficient, that is, whether meets - 1 + C (3) + C (4) = 0.
The following is to use Wald test for logarithmic constrain test. The null hypothesis of the test is C (3) + C (4) = 1 (see table 2)
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Table 2 Wald test output results
Wald Test:
Equation: EQ04
Test Statistic
Value
df
Probability
F-statistic
2.773277
(1, 26)
0.1079
Chi-square
2.773277
1
0.0958
Normalized Restriction (= 0)
Value
Std. Err.
-1 + C(3) + C(4)
0.438429
0.263271
Null Hypothesis Summary:
Restrictions are linear in coefficients.
P value of the test from the table3 is 0.1079 and greater than the one in a = 0.05 significant level, so to accept the original hypothesis,
namely to meet coefficient constraint condition. The constraint regression model can be thought to have the same explanatory as the
original model under the constraint of - 1 + C (3) + C (4) = 0. Thus to eliminate multicollinearity and establish the model as follows:
LN  GDP / L   LNA0    t    LN  K / L   µ2 ...............  2 
Use Eviews6.0 software to make least-square estimation can get the following estimation equation:
ˆ / L)  0.490726  0.052756  t  0.492809  LOG( K / L)  
LOG(GDP
2
(t value)
(–1.193250)
(3.180783)
(4.906596)
R2 =0.994662 R 2 =0.994266 F=2515.423 S.E=0.089517 D.W=0.354553
F test passes in a = 0.05 significant levels and it shows that model is overall significantly established.
R2 =
0.994266, and it
indicates that the model = goodness of fittest is better, but T test of C value and T value didn't pass, DW value is low and only
0.354553 low value. Therefore, we can judge that it may exist sequence autocorrelation and need to re-correct model to eliminate
sequence correctional.
5 The Revised Model Again
The first order and second order autocorrelation of the model are respectively tested, and found that model exists first order and
second
order
autocorrelation
according
to
accompanying
probability.
So
build
the
following
correction
model:
LN (GDP / L)  LNA0    t    LN ( K / L)  AR(1)  AR(2)  3.........(3)
So use Eviews6.0 software and generalized differential estimation model to estimate the model and result is as follows:
LOG(GDPˆ / L)  1.130482  0.077569  t  0.336173 LOG( K / L)  1.287617  AR(1)  0.525327  AR(2)  3
(t value)
（–2.422156） （4.022471） （3.012227）
（6.523756）
(–2.812903)
R2 =0.998446 R 2 =0.998176 F=3694.738 S.E=0.047741 D.W=1.721212
The model has not exist first order and second order autocorrelation based on LM multiplier test judgment. T test of C value,T value
and LOG(K/L) has passed in a=0.05 significant level.
R 2 = 0.998176, it shows regression equation to the sample data fitting is
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better, explanatory variables and the dependent variables are highly linear correlation. F test has significantly passed and improved.
White test (table5) test shows its P values is greater than 0.05, then accept there is no assumptions of heteroskedasticity assumptions,
think model does not exist heteroskedasticity. Therefore, we can say model is through the econometrics test.
Table 5 White test results
Heteroskedasticity Test: White
F-statistic
1.562003
Prob. F(14,13)
0.2143
Obs*R-squared
17.56064
Prob. Chi-Square(14)
0.2275
Scaled explained SS
22.56666
Prob. Chi-Square(14)
0.0677
The above results show that,   0.336173 ,   0.663827 ,   0.077569 . Therefore, the standards of the model is:
GDP  0.322878e0.077569t K 0.336173 L0.663827
Among them,   0.336173 , it indicates when capital inputs grow 1% and it can lead to its GDP grows
0.336173%.   0.663827 , it shows labor inputs increase by 1%, and it can lead to its GDP grows
0.663827%.   0.077569 , it reflects the annual growth rate of the technological progress in China is 7.7569%.
6 Calculation and Analysis of Each Element
The contribution rate of capital inputs, labor inputs and technological progress is respectively:
K
L
,
, E ( A)  1  E ( K )  E ( L)
K
E(K )  
 100% E ( L )   L  100%
Y
Y
Y
Y
The results of the contribution rate of each element are seeing figure1 as follows:
Figure 1 The figure of the contribution rate of each element
As can be seen from Figure1, capital inputs, labor inputs and technological progress become the major factor of Chinese economic
growth one after another. There is little change in the contribution of labor inputs. The world economy is in a recession by the 2007
U.S. subprime mortgage crisis affect, each country rescue the market. The plan is to inject in china and stimulate domestic demand
by capital. Chinese capital inputs have increased dramatically from 2007 to 2009, which caused the contribution rate of science and
technology progress dropped sharply negative. The contribution rate of labor inputs decreased slightly in recent years, employment
increased slowly, the number of employment in recent years significantly declined. It reflects a large number of workers are laid off
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because of technological progress in keeping the economic growth in China, the laid-off is mostly because of the economic recession
in the last three years.
7 Conclusions and Recommendations
From 2007 to 2009 Chinese economic growth recession and contribution rate of the progress of science and technology had such a
large fall, which fully explains our future economic growth must still continue to accelerate the progress of science and technology.
According to this, put forward the following suggestions: (1) Chinese R﹠D funds is 5802.1 billion Yuan, accounting for 1.7% of
GDP. While developed countries accounting for 3% ~ 5% of its gross domestic product. Therefore, China should continue to increase
R﹠D inputs, on one hand, we should continue to increase the government's inputs in science and technology. On the other hand, we
should encourage and guide the enterprises to increase investment in science and technology and strengthen scientific research
cooperation of enterprises, scientific research institutions and universities to make their full advantages. (2) To improve education
level, pay great attention to the human capital accumulation and play the role of human capital. The decisive factor of long-term
economic growth in national of is knowledge and human capital accumulation such as some endogenous factors. China is the country
which has the most abundant human resources in the world, but human resources must combine with the education to improve the
laborer quality. China should actively introduce high-tech talents, this makes Chinese population become human resources of
Chinese economic growth. (3) The digestion and absorption of technology, and strengthen the ability of independent R﹠D and
innovation. China has been known as a manufacturing power and production workshop in the long term, which fully testifies Chinese
imitation ability is too strong, but the innovation ability is relatively backward. The successful experience in Japan and South Korea
is the technological introduction and digestion and absorption as soon as possible, this is basically they also increase the input of
digestion and absorption at the same time. (4) Perfect market economic system to promote enthusiasm and initiative of science and
technology innovation. (5) Perfect intellectual property protection and increase personnel's reward of science and technology
innovation
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