Download Research on Influencing Factors of China’s GDP Growth Xing LIANG

Management & Engineering 15 (2014) 1838-5745
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Management & Engineering
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Research on Influencing Factors of China’s GDP Growth
Xing LIANG, Xuanyi YU
School of Economics and Management, Tongji University, 200092, P.R.China
KEYWORDS
GDP,
Three dimensional industries,
Regression analysis,
Industrial structure adjustment
ABSTRACT
Through the empirical research based on the regression analysis about the national GDP in
the early 80s until so far and fixed asset investment in the three dimensional industries, the
consumer price index, government spending, the total net exports and employed population
in this paper we come to the conclusion: the fixed asset investment in the three dimensional
industries, government spending, the total net exports, the increasing of employed population
and consumer price index can all lead to the increasing of the GDP of our country. And the
degree of the influence from strong to weak are the following: fixed asset investment in the
primary industry, consumer price index, total net exports, employed population, fixed asset
investment in the secondary industry, and fixed asset investment in the tertiary industry.
However, nowadays when the central government has changed the idea to pursuit the quality
of GDP and the wellness of the residents, our policies should be forward-looking and
flexible. We should change the idea of development according to the time; adjust the
industrial structure and pursuit technological progress.
© ST. PLUM-BLOSSOM PRESS PTY LTD
1 Introduction
Since the reform and opening up, the Chinese economy has a remarkable achievement. In more than 30 years the average GDP
growth of China is approaching 10%. Facing the changeable global environment in these three decades, the Chinese economy is
always growing with a high speed, and it has even flown against the wind. This phenomenon is regarded as a “Chinese wonder” by
many scholars home and abroad. Identifying the driving factors behind China’s fast economic growth is very important for a clear
understanding of the reasons of our country’s economic growth and for the maintaining of the fast pace of our economy. Many
scholars home and abroad have done long term theoretical and empirical researches on economic growth in depth, and have also
come to many meaningful conclusions.
Generally speaking, scholars home and abroad mainly attribute the factors of the economic growth of our country to the investment
in fixed assets, financial expenditure, the increase in exports, and the improvement in the labor remuneration. Gong Guoyong and
Tan Siyi [1] analyzed the affecting factors of the GDP growth in Shenzhen, and came to the conclusion: In long terms, the added
industrial value, exports and the increase in total sales of social consumer goods led to Shenzhen’s economic growth, while the
increase in imports led to the decrease of Shenzhen’s GDP. Zhu Shan [2] studied the relationship between China’s gross domestic
product (GDP) and economic indicators, and discovered a positive relationship between total imports and exports and the gross

Corresponding author.
E-mail address: [email protected]
English edition copyright © ST. PLUM-BLOSSOM PRESS PTY LTD
DOI:10.5503/J.ME.2014.15.001
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domestic product (GDP) and a positive relationship between total wages and GDP. Hu Rui [3] made a practical analysis based on the
VAR Model about the GDP in Wuhan and total fixed asset investment, per capita consumption expenditure and consumption of urban
residents, educational investment, social engagement and social retail sales of consumer goods in total. He came to the conclusion:
total fixed asset investment, per capita consumption expenditure of urban residents, investment in education and the increase in total
retail sales of social consumer goods led to an increase in GDP of Wuhan City, and the degree of influence is in the following order:
the total retail sales of social consumer goods, total fixed asset investment, per capita consumption and expenditure of urban residents,
expenditure on education. Qi Lili [4]studied the relationship between China’s GDP and the economically active population, urban and
rural savings deposits at the end of the balance of the total fiscal expenditure, the total investment in fixed assets, gross domestic
product (GDP) of the last period, total energy production, taxes, total wages, import and export volume, and came to the conclusion:
ending balance of urban and rural savings deposits, fixed assets investment, gross domestic product (GDP) of the last period, total
wages, import and export volume increase all have an promoting role for the GDP growth in our country.
Lin Yifu and others [5] corrected the GDP accounting method with multiplier analysis, and consider that the growth of exports not
only directly promotes economic growth, but also influences the consumption, investment and government spending, and therefor e
indirectly stimulate economic growth. Wei Xinghua and Hou Weimin [6] think that China is still in the investment-driven stage of
economic growth. Capital-intensive industries is the dominant industry, economic growth is still based on capital investment as the
main drivers. Economic efficiency is still low. We should use scientific and technological innovation to improve efficiency, promote
the optimization of economic structure and energy savings, thus contributing to economic growth. Krugman [7] pointed out in his
famous article “the Myth of Asia’s Miracle” that in most East Asian countries and regions, economic growth is mainly due to the
increase in factor inputs, technological progress does not play a significant role. This is an unsustainable pattern of growt h. Wu
Jinglian [8] believes that China's economic growth is mainly dependent on the factors of production, particularly capital investment,
and it maintains economic growth through resource consumption. Therefore it is an extensive mode of economic growth. Overview
of the literature can be seen, investment in fixed assets, consumption, exports, the increase of the labor factor plays a positive role in
China’s economic growth. But analysis of the impact of the investment in fixed assets on China’s GDP in the past was not according
to three dimensional subsections, this article will divide fixed assets investment into three dimensions to study its impact on China’s
GDP.
2 Model Structure
According to the analysis of literature theory, this article selects China’s GDP from 1982 to 2010 (Y), the consumer price index of
CPI (X1), the first industry investment in fixed assets (X2), the secondary industry investment in fixed assets (X3), the tertiary industry
investment in fixed assets (X4), financial expenditure (X5), net exports (X6) and the employed population (X7), a total of eight
economic indicators to build the regression model. Thus, we build the following model:
Y=β0+β1 X1+β2 X2+β3 X3+β4 X4+β5 X5+β6 X6+β7 X7+ε.
In which β0 is the constant term, ε is the random error, and β is the coefficient of each variable. The statistics are from 1982 to 2010
for each index. The data is cited from “China Statistical Yearbook”.
3 Model Test and Improvement
3.1 Model parameter estimation
Estimate the parameters with OLS along with theoretical model, and use the R software to run the data. The result is shown in
Table 1:
Table 1 Parameter estimates of OLS regression equation
(Intercept)
X1
X2
X3
X4
X5
X6
X7
Estimate
Std. Error
t-value
9 270.917
10 049.2 052
0.923
22.589 1
2.320 7
9.734
-10.059 5
2.808 6
-3.582
0.722 4
0.274 7
2.63
0.313 4
0.278 4
1.126
1.384 7
0.300 7
4.606
0.558 4
0.287 3
1.944
-0.266 9
0.212 2
-1.258
Residual standard error: 2017 on 21 degrees of freedom
Multiple R-squared: 0.999 7,
Adjusted R-squared: 0.999 7
F-statistic: 1.196e+04 on 7 and 21 DF, p-value: < 2.2e-16
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Pr(>|t|)
0.366 719
0.000 000***
0.001 758**
0.015 641*
0.273 023
0.000 153***
0.065 441
0.222 328
3.2 Inspection and improvement of the model
Following conclusions can be obtained according to the parameter estimates of the regression equation in Table 1:
(1) Though the model fit of the data is very good and the F=1,196, significantly with the probabilistic P <0.001, which explains that
under the condition of significance level 0.001 the regression equation passes the F-test, the coefficients of fixed assets investment in
the primary industry and of employment population economic variables are negative, which does not match with the actual situation.
If we take the high correlation between economic variables in practice into account, it may lead to mistake. Therefore, in order to
avoid the multi collinearity problems of the customer data brings, I have to give up the classic regression method, and switch to
principal component regression. The principal component regression should first identify the main component of the independent
variable set, and then create the main component for the first few variables unrelated regression equation, and finally restore the
original independent variable regression equation—principal component regression equation. The principal component regression is
frequently used in dealing with economic data and the results are good. First of all, we make a principal component analysis about
the economic variables in this article the results are shown in Table 2:
Table 2 Principal component analysis
Comp.1
Comp.2
Comp.3
Comp.4
Comp.5
Comp.6
Comp.7
Standard deviation
2.498 695
0.711 08
0.488 66
0.077 40
0.057 08
0.045 17
0.028 507
Proportion of variance
0.891 925
0.072 23
0.034 11
0.000 86
0.000 47
0.000 29
0.000 116
Cumulative proportion
0.891 925
0.964 16
0.998 27
0.999 13
0.999 60
0.999 88
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From the principal component analysis of the eigenvalue we can determine the variables with multicollinearity in Table 2. The
cumulative contribution rate of the first two principal components has reached more than 96 percent, so we select these two principal
components to make a regression against dependent variable GDP. Coefficients of the regression equation are shown in Table 3:
Table 3 Principal component regression
(Intercept)
a1
a2
Estimate
Std. Error
t value
102 273.2
854.7
119.661
43 338.4
342.1
126.701
2 591.6
1 202
2.156
Residual standard error: 4 603 on 26 degrees of freedom
Multiple R-squared: 0.998 4,
Adjusted R-squared: 0.998 3
F-statistic: 8 029 on 2 and 26 DF, p-value: < 2.2e-16
Pr(>|t|)
<2e-16
<2e-16
0.0 405
According to the parameter estimates of the regression equation in Table 3, we can come to the following conclusions:
(1) Square test. It can be obtained from the results that the coefficient of determination R 2=0.998 4, adjusted R2=0.998 3, indicating
that about 99.83 percent of GDP deviation can be explained with this model, which means this model fit well with the data.
(2) The regression equation significance test. The F=8 029, significantly with the probabilistic P <0.001 explains that under the
condition where the significance level is 0.001, the regression equation can pass the F-test, and the regression equation is of notable
significance. The multivariate regression model which uses all variables to predict the gross national product relatively fit well with
the data.
(3) Significant test of each regression coefficient. P-value of the intercept, the first principal component, and the second principal
component are less than 0.05, indicating that at a significant level of 0.05, each regression coefficient can pass the significance test.
According to the loading matrix and the principal component regression equation, we can get:
Y=6.341*X1+8.047*X2+0.542*X3+0.440*X4+0.72*X5+2.518*X6+1.530*X7-74281.45
4 The Economic Significance of the Model
4.1 The relationship between GDP and consumer price index
By the model, we found that there is a positive relationship between CPI and GDP, but that does not have any practical significance.
What we have to consider is the real GDP growth not accounting the inflation factors.
4.2 The relationship between GDP and fixed asset investment
Studies of GDP and fixed assets in the past show that the increase of the fixed assets investment can produce a significant impact on
the GDP growth, but there was no research according to different industries. According to our model results can be seen that the fixed
assets investment in three industries all have positive relationships with China’s GDP each additional 100 million yuan for the fixed
assets investment in the primary industry can boost GDP growth to 804.7 million yuan, each additional 100 million yuan for fixed
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assets investment in the secondary industry can boost GDP growth to 54.2 million yuan, each additional 100 million yuan for fixed
assets investment in the tertiary industry can boost GDP growth to 44 million yuan. The impact of fixed assets investment in the
primary industry on the GDP growth was significantly stronger than that in the secondary and tertiary industries. It can be interpreted
as a spillover effect. The products of primary industry are brought to the deep processing for the secondary and tertiary industries;
thereby the increased gross national product (GDP) is the contribution by the primary industry investment in fixed assets.
4.3 The relationship between GDP and financial expenditure
The financial expenditure is the financial disbursement of funds by the government for the provision of public goods and services to
meet community needs under market economy conditions, and it is an important means for the government to maintain social justice
and ensure stable economic growth. According to the model results, the government expenditure for each additional one hundred
million Yuan will be able to boost GDP growth to 72 million yuan.
4.4 The relationship between GDP and net exports
Exports are one of the troikas of economic growth, its importance is self-evident. According to the model results, we can
quantitatively see that each additional 100 million yuan of net exports can boost GDP growth to 251.8 million yuan.
4.5 Direct relationship between GDP and employment
Employment directly determines the labor element of labor input in the production. In the economic boom of our country over the
past ten years, the transfer of rural labor has made its enormous contribution. It can also be seen from the model, that each additional
10,000 employed population will be able to boost GDP growth to 153 million yuan.
5 Conclusion and Policy Recommendations
(1) Pursuit the real GDP growth, and control prices to benefit people’s livelihood. At this stage, China’s economic downside risks still
exist, many people asked the government to loose monetary policy to stimulate the economy. But inflationary pressures in China are
still huge, the government cannot pursuit GDP growth rate blindly, it should also take the feelings of the people into account, and
should therefore continue to implement a prudent monetary policy.
(2) Increase investment in fixed assets, and adjust the industrial structure. According to our model can be seen, since the reform and
opening up investment in fixed assets have significant contribution to China’s GDP, therefore, China should increase investment in
fixed assets. But at the same time the growth rate of investment in fixed assets of China's tertiary industry in recent years is very low
which means China’s efforts on investment in the development of tertiary industries were not enough, the trend of economic
development is to increase the proportion of secondary and tertiary industries in the national economy. As it is mentioned above,
although investment in fixed assets in secondary and tertiary industries does not influence GDP that much as fixed assets investment
in first industry, but we must adjust the industrial structure and give priority to the development of tertiary industry, on the one hand,
this can promote economic growth pattern to enable enterprises to shift from extensive economic growth mode to intensive mode of
production, and to get the best value for money; on the other hand, because the tertiary industry has the largest employment elasticity,
we can increase employment and stimulate economic growth by spillovers.
(3) Continue to implement a proactive fiscal policy. Since the 2008 financial crisis, our government has implemented a proactive
fiscal policy to response to financial crisis impact, which has made China quickly get out of the world financial crisis and has got
remarkable achievements. Now there are still risks about economic downside, and according to Keynesian thought, the government
needs to play the role of the invisible hand to influence the operation of socio-economic. Therefore we should increase fiscal
spending, expand domestic demand and maintain steady and rapid economic growth.
(4) Promote exports and optimize the export structure. On one hand, the increase in net exports has very significant impact on GDP
growth. The government should introduce and strengthen appropriate policies and measures, continue to encourage and strengthen
exports, such as the expansion of the export tax rebate income range. On the other hand, the export also has a spillover effect, the
increase in exports can promote enterprise to expand production, while solving the employment problem, which is conducive to
social stability. While maintaining steady growth of the export scale, we should also optimize export structure, strive to improve the
quality and efficiency of export growth, and focus on improving the quality and efficiency of the export growth, including the
strengthening of the competitiveness of enterprises, the support high value-added labor-intensive exports, guiding the transformation
and upgrading of the labor-intensive industries, including improvement of the export structure cost and increase of workers' income,
especially migrant workers income.
(5) Promote the employment. Our country should vigorously develop the tertiary industry, because tertiary industry is labor-intensive
industry, and his development can absorb more labor. In addition, the literature at this stage also proved that the tertiary industry has
the largest employment elasticity. To promote employment growth is essential not only for the growth of our national economy, it can
also ensure social stability and prosperity. Therefore, the government should introduce policies to promote employment vigorously.
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