AN EMPIRICAL ANALYSIS OF THE RELATIONSHIP BETWEEN

SOCIAL CONSUMPTION DEMAND FACTORS AND THE

CULTURAL INDUSTRY IN CHINA

Li Cui, Haoxiong Yang and Hao Zhang

School of Business, Beijing Technology and Business University, 33 Fucheng Road, Beijing, P.R. China

Keywords: Industry structure, Cultural industry, Social consumption demand, Influence relationship, Regression

analysis.

Abstract: The relationship between social consumption demand factors and the development of Chinese culture

industry is analyzed based on the theory of industrial structure. The result indicates that average disposable

income of urban residents and Engel coefficient of rural households are related to culture industry very

significantly and that the contribution of culture industry to GDP needs to be improved. Three

countermeasures are proposed to promote the development of culture industry from two angles, including

improving average disposable income of urban residents to increase their consumption ability, reducing

Engel coefficient of rural households to improve the quality of life and promoting the construction of public

cultural service system.

1 INTRODUCTION

International competition enters into culture industry

and culture domain under the background of

economic globalization. Therefore, the strength of

culture industry becomes an indicator of national

culture competitiveness. The statistical data of

Chinese culture and relevant industries

accomplished by China National Bureau of Statistics

shows that Chinese culture industry increases

powerfully and the increasing speed came to be

higher than that of gross domestic production for the

first time in 2006. It was also faster than the tertiary

industry in the corresponding period. China is a

developing country whose culture industry started

later and the level of industrialization, scale and

intensification is lower than developed countries.

Chinese culture industry is in the process of growth

and the value added increased from 394.1 billons

RMB in 2004 to 760 billons RMB in 2008. But the

proportion accounting for GDP only increased with

a small rate from 2.15 percent to 2.53 percent

As the income of urban and rural Chinese

residents is being enhanced remarkably and the

quality of life improves further, new concepts of

culture consumption gradually grows up and the

consumption demand space becomes larger and

larger. On the other hand, the State Council made

Culture Industry Promotion Planning in July 2009

which proposed explicitly the guiding ideology,

fundamental principles and planning goals. The

planning goals included that culture industry scale

must constantly enlarge and the industry function

and role of motivating economic and social

development be played better. A depth study on the

influence of social consumption demand factors on

the development of Chinese culture industry can

help provide important basis for making national

culture industry policies.

We conducted empirical analysis on culture

industry and the relevant influential factors with

Eviews, a statistical software. The results show that

average disposable income of urban residents and

the Engel coefficient of rural households influence

Chinese culture industry most notably and that the

contribution of Chinese culture industry to GDP

needs to be enhanced. According to the empirical

analysis results, we put forward some

countermeasures and proposals to facilitate the

development of culture industry.

Be advised that papers in a technically unsuitable

form will be returned for retyping. After returned the

manuscript must be appropriately modified.

606

Cui L., Yang H. and Zhang H..

AN EMPIRICAL ANALYSIS OF THE RELATIONSHIP BETWEEN SOCIAL CONSUMPTION DEMAND FACTORS AND THE CULTURAL INDUSTRY IN

CHINA.

DOI: 10.5220/0003597406060610

In Proceedings of the 13th International Conference on Enterprise Information Systems (PMSS-2011), pages 606-610

ISBN: 978-989-8425-56-0

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

2 CULTURE INDUSTRY AND

SOCIAL CONSUMPTION

DEMAND FACTORS

Consumption demand plays a role of guiding and

pulling tremendously to the development of society

and economy. Economy development and income

growth always push the demand of culture go up at

some stages in the process of industrialization and

urbanization. China is in the intermediate period of

industrialization and urbanization where the speed of

economy development and income growth is fast

and the demand of culture is being awakened. But

the system of resource allocation by market has not

been built. Therefore, the demand of spirit and

culture products lacks of effective interaction and

links with the suppliers. On the one hand the huge

potential demand cannot be realized. On the other

hand a large quantity of products supply is invalid

and more enormous culture resources cannot be

industrialized.

Consumption demand has become the source of

industry formation and development since demand

determines production in the modern economy.

According to the Engel’s law and Maslow’s

hierarchy of needs theory, when the economy

develops to certain level income improvement and

the change of income structure will make demand

structure go upstream and the proportion of spirit

and culture consumption continuously rise at a faster

speed than that of material consumption demand. As

the culture consumption ability increases, the scale

of culture consumption will be constantly expanded

so as to pull the growth of culture industry. The

culture consumption demand of a country is the

basis of the development of its culture industry and

the motive power of enhancing competitive

advantage of culture industry. So grasping the

culture consumption demand is capturing the master

key of developing culture industry. The key point of

expanding domestic demand is exploiting new

hotspots with the rapid development of national

economy and the expansion of civil culture

consumption demand space while culture

consumption is a new pattern of pulling economy

development through consumption. International

experience also testifies that culture consumption

expenditures are positively relevant with GDP.

According to the industrial structure theory of

Chenery, an American economist, some kind of

linear correlation exists among certain GDP

development level, certain Engel coefficient and

certain culture consumption expenditures. When the

average GDP is between 2000 dollars to 4000

dollars, the resident culture consumption demand

will emerge evidently and the culture consumption

will reach 4 to 5 percent of GDP. Chinese average

GDP was larger than 2500 dollars while the culture

consumption accounted only 2.5 percent for GDP.

This indicator is 5.47 percent in the same rank

countries. That is to say, the culture consumption

level of Chinese residents is only half of the level of

other countries in the same class.

At the present stage in China, the condition of

insufficient proportion and lower amount of culture

consumption stands out. Therefore, Chinese culture

consumption has a great improvement space

compared with western developed countries. Inferior

culture consumption demand is the direct factor that

restricts the development of the culture industry in

China.

3 THE EMPIRICAL ANALYSIS

3.1 Indicator Selection

The contribution of culture industry to a country’s

economy can be measured by the proportion of the

added value of culture industry accounting for GDP

on the basis of existing research. So we selected the

added value of culture industry as the dependent

variable i.e. explained variable of the linear

regression equation. According to Chenery’s

theory of industrial structure, we selected GDP,

average income level and Engel coefficient as

independent variables i.e. explanatory variables.

It is necessary to point out that average income

level and Engel coefficient reflect social

consumption ability from amount and structure

respectively although they are strongly correlative.

These two indicators are complementary since

average income level emphasizes on the resident

consumption ability as the foundation and guarantee

of consumption ability while Engel coefficient

emphasizes on the living behavior.

In order to study the influence of urban and rural

culture consumption demand further, the average

income level is split into average disposable income

of urban residents and average net income of rural

residents and Engel coefficient is split into Engel

coefficient of urban households and Engel

coefficient of rural households to make pointed

references for resolving the problems of the

development of urban and rural culture industry.

In conclusion, we selected the added value of

culture industry, GDP, average disposable income of

urban residents, average net income of rural

AN EMPIRICAL ANALYSIS OF THE RELATIONSHIP BETWEEN SOCIAL CONSUMPTION DEMAND FACTORS

AND THE CULTURAL INDUSTRY IN CHINA

607

residents, Engel coefficient of urban households and

Engel coefficient of rural households as the indictors

of linear regression model. The data of the six

indicators are from the year of 1998 to 2009. The

symbols and meanings of the dependent variable and

independent variables in the model are demonstrated

in Table 1.

In the empirical analysis, we should not only find

out the factors which influence the economic

contribution of Chinese culture industry but also

determine the significance of each factor and

whether auto correlativity exists among these

factors. These goals bring forward high requirements

for the comprehensive function of software. The

strong function of Eviews can just satisfy these

requirements with great practical value.

Table 1: Relevant Variables.

Type of Variables Symbols Variables

Dependent variables Y Added value of culture industry

Independent variables

GDP

Average disposable income of urban

residents

Average net income of rural residents

Engel coefficient of urban households

Engel coefficient of rural households

3.2 Related Data

The data used in the regression model is time series

data derived from China Statistical Yearbook (1999-

2010) and the website of China National Bureau of

Statistics. The sample data are shown in Table 2.

Table 2: Related data.

Year

Y (Hundred

Million RMB)

((Hundred

Million RMB))

(RMB) X

(%)X

(%)

1998

1823.9

84402 5425 2162 44.5 53.4

1999

2098

89677 5854 2210 41.9 52.6

2000

2391.2

99215 6280 2253 39.2 49.1

2001

2768.7

109655 6860 2366 38.2 47.7

2002

3090.5

120333 7703 2476 37.7 46.2

2003

3415.1

135823 8472 2622 37.1 45.6

2004

3940.8

159878 9422 2936 37.7 47.2

2005

4454.8

183217 10439 3255 36.7 45.5

2006

5123

211924 11759 3587 35.8 43.0

2007

6559.9

249530 13786 4140 36.3 43.1

2008 7600 300670 15781 4761 37.9 43.7

2009 8400 340507 17175 5153 36.5 43.0

Data source: China Statistical Yearbook, 1999-2010.

3.3 Regression Analysis

It is supposed that linear correlativity exists between

the added value of culture industry and GDP,

average disposable income of urban residents,

average net income of rural residents, Engel

coefficient of urban households and Engel

coefficient of rural households. A linear equation is

built as following

Y=C

(1)

The result of a linear regression analysis of the data

in Table 2 is shown in Table 3.

Table 3: Results of linear regression analysis.

Variable Coefficient Std.Error t-Statistic Prob.

-0.0315 0.0186 -1.6957 0.1409

0.6387 0.2238 2.8542 0.029

0.0741 0.2282 0.3248 0.7563

-42.8431 19.0012 -2.2348 0.065

-54.7905 13.8829 -3.9466 0.0076

C 5472.92 599.3474 9.1315 0.0001

R-squared 0.998 F-statistic 631.5

The number of variables is 5 and the sample size

is 12. Adjusted R Square is 0.998 and F-statistic is

631.5. So the degree of fitting reaches up to 0.998.

The regression of forecasting dependent variables

within the sample is very successful.

In the result of Prob. the p value of X1 is 0.1409,

which indicates that the influence of X1to Y is not

significant. The t statistic values of X2 and X3 are

both positive, indicating that these variables are

positively correlated with Y. It means that the added

value of culture industry will increase as the average

income of urban and rural resident increases.

Meanwhile, the t statistic values of X4 and X5 are

both negative, indicating that these variables are

negatively correlated with Y. It means that the added

value of culture industry will increase as the Engel

coefficients decrease.

Then the most significant indicators were

analyzed by linear regression. In the results of Prob.,

the larger the p value, the less significance it shows.

The significance is the largest when the p value is

zero while the significance degree is zero when the p

value is 0.15. From Table 3 it is known that the p

value of

is 0.7563, which indicates it is

insignificant. The p values of

and X

are 0.1409

and 0.065 respectively, which indicates their

significance degrees are small. Therefore, these

three groups of data can be eliminated. Then we

made regression analysis of

and X

. The output

results are shown in Table 4.

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608

Table 4: Results of linear regression of X

and X

Variable Coefficient Std.Error t-Statistic Prob.

0.270 0.020 13.395 0.000

-82.354 9.780 -8.421 0.000

C 4782.960 613.670 7.794 0.000

R-squared 0.994 F-statistic 754.04

Durbin-

Watson stat

1.781

Prob

(F-statistic)

0.000

The number of variables is 2 and the sample size

is 12. Adjusted R Square is 0.994 and F-statistic is

754.04. The fitting degree of the regression equation

is high, reaching up to 0.994. The regression of

forecasting dependent variables within the sample is

very successful.

From the output results of Prob., the significance

degrees of X2 and X5 reach to the largest level.

These two factors are the determining factors of this

regression equation.

In the end, we tested the correlativity of the most

significant indicators. After building the linear

regression model, we can obtain the figure of

residual distribution. It shows that there is

heteroscedasticity if the distribution dots are not

closely around a horizontal line and their distribution

area becomes broader or narrower or irregular

complex variation appears. Auto correlativity does

not exist from direct viewing.

Firstly, we got the figure of residual distribution

as seen in Figure 1 to verify if heteroscedasticity

exists between X2 and X5. From the figure we can

draw the conclusion that heteroscedasticity exists

between X2 and X5 and auto correlativity does not

exist from direct viewing.

残差图

-100

-50

100

150

1996 1998 2000 2002 2004 2006 2008

Resid

Figure 1: Residual distribution.

Then we used Durbin-Watson statistic to test if

there is auto correlativity between X2 and X5. From

Table 4, the DW statistic is 1.781. For the situation

where k is 2 and n is 12, the lower threshold dL is

0.812 and the upper threshold is 1.579. Since DW is

in the range of dU→2, we can judge that there is no

sequence correlativity between X2 and X5.

3.4 Analysis Results

The analysis results of this multiple regression

model are as follows.

(1) After analyzing all the indicators by linear

regression, we knew from the output results of t-

statistic that the added value of culture industry will

increase if the average income of urban and rural

households increases. Meanwhile, the added value

of culture industry will increase if the Engel

coefficients of urban and rural households decrease.

In the output result of [Prob.], the p-value of X

is 0.1409, indicating that the influence of X

to Y is

not significant. The reason is that there is little direct

relation between the growth of GDP and that of

culture industry. The contribution of culture industry

to GDP is not very evident.

(2) After analyzing all the indicators by linear

regression, we knew from the output results of

[Prob.] that the influence of X

to Y is not

significant and the significance of X

and X

is little.

So we eliminated these three factors and made

regression analysis of X

and X

. From the output

results, the significance of X

and X

reaches to the

largest level. Therefore, among the five variables

average disposable income of urban residents and

Engel coefficient of rural households are the

determinant factors. The reason is that urban

residents spend the added income more on culture

consumption after the subsistence problem has been

resolved. But the life quality of rural residents is not

as high as that of urban residents. So the rural people

spend the added income more on material

consumption.

(3) After confirming that X

and X

are the

determinant factors of this linear model, we made D-

W test for X

and X

. We found that there is no auto

correlativity. It means that although average

disposable income of urban residents and Engel

coefficient of rural households are important factors

influencing the added value of culture industry there

is no certain relation between them.

4 CONCLUSIONS

Through the empirical analysis of the consumption

demand factors that influence the development of

culture industry, we drew the conclusion that

average disposable income of urban residents and

Engel coefficient of rural households are

determinant factors influencing the economic

distribution of Chinese culture industry. The average

AN EMPIRICAL ANALYSIS OF THE RELATIONSHIP BETWEEN SOCIAL CONSUMPTION DEMAND FACTORS

AND THE CULTURAL INDUSTRY IN CHINA

609

income level of residents and household Engel

coefficient are two factors that reflect domestic

culture consumption demand comprehensively. So

we testified that the culture consumption demand of

a country is the basis of the development of its

culture industry and the motive power of enhancing

competitive advantage of culture industry. So

grasping the culture consumption demand is

capturing the master key of developing culture

industry. In order to facilitate the development of

Chinese culture industry, it is necessary to expand

the culture consumption demand from two aspects,

one of which is to enhance the average disposable

income of urban residents with still more forces so

that the consumption ability can be increased, the

other of which is to lower the Engel coefficient of

rural household and improve their life quality.

The following countermeasures were put forward

according to this empirical analysis.

 Enhancing the resident income level. The

consumption ability of residents is decided by their

income level. So enhancing the income of residents

especially the rural residents and the urban low-

income residents is the prerequisite to strengthen the

resident consumption ability and provide a solid

economic foundation for the development of culture

industry. For this purpose, it is necessary to increase

the proportion of resident income in the national

income distribution, enhance the subsistence

allowances of urban low-income residents, increase

transfer payment to the distressed areas and reduce

the residents income gap. It is need to enlarge the

scale of the medium-income group and enhance the

income of rural residents through various measures.

 Releasing the rural consumption demand. From

the model, the added value of culture industry will

increase as the Engel coefficient decreases.

Therefore, it is necessary to improve the lift quality

of the rural residents. Although the activities of

sending culture to the countryside have been carried

out in many regions, there are many problems such

as little quantity and low quality because of lack of

corresponding motivation system. It is a problem

that needs to be solved as soon as possible to

improve the rural culture consumption situation and

release the rural consumption demand. For this

purpose, it is necessary to building more rural

culture facilities to satisfy the hardware

requirements of culture consumption and invest on

training culture talents and supporting culture

projects to provide solid and sustainable guarantee

for booming rural culture.

 Promoting public culture service systems. For

the people in backward areas and lacking

consumption ability, establishing and completing

public culture service systems is necessary to satisfy

the requirements of culture consumption demand.

Opening public culture products and service market

can turn the potential culture demand into actual

culture demand so as to develop culture

productivity. The key point is to reform the

management system of public culture. The

government should exit from the position of

monopoly provider and produce various structure

condition, policy condition and social condition.

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