Study on the Adjustment of Industry Structure Model of Sustainable Development in Western China

Study on the Adjustment of Industry Structure Model of Sustainable Development in Western China Haiyan WEI, Jinle Zhang, Shiyu ZHANG Division of Human Resources, Northwestern Polytechnical University, Xi’an710072 , China School of Humanities, Economics and Law, Northwestern Polytechnical University, Xi’an710072, China School of Management, Northwestern Polytechnical University, Xi’an710072 , China xjrs1212@163.com; zhangjinle@nwpu.edu.cn; zhangshiyu@nwpu.edu.cn Abstract The economic development of the Chinese western region is relatively backward. One of the important reasons is unreasonable industrial structure. Based on the study of the industrial structure of Western China as the main line, the reason of China western industrial structure and sustainable development contradictions and problems is analyzed. On this basis, empirical research constructs the industrial structure in Chinese western region dynamic control model by using the grey system theory and through the analysis and research of the data puts forward the countermeasures and strategies Western China Industrial Structure adjustment.

Keywords Sustainable Development; Western China; Industrial Structure; Adjustment

Problems of China's Western Industrial Structure Based on Standard of the Sustainable Development The Western Industrial Structure Disproportion And High Levels Of Sustainable Development Resources Contradict The Requirements.

The proportion of the first industry GDP of the chinaʹs western region is higher than the national average level and industrial development of eastern regions in varying degrees, but the first industry is lagging behind, resulting in a large number of green resources being wasted.

Also, the second industry development lags behind for the weakness of industrial foundation and in most of the provinces; the second industry proportion of GDP is lower than the national average level, existing a big gap with the eastern region.

Compared with Chinese average level and the eastern region, the proportion of the tertiary in the western china is lower significantly. The western industrial structure presents the structural shortage and low level. If it is not adjusted timely, the goal of sustainable development is difficult to achieve.

The Western Industrial Structure System Is Not Perfect and Is Not Compatible With the Overall Effect on the System of Sustainable Development in the First Place Since the resource allocation is centralized, such as the concentrate financial resources, material resources and manpower, builds a number of large‐scale production and plays an important role in the national industrial base, thus constructing the regional economic growth system. New industries in the western region have not yet formed and redundant constructions are serious. Because many cities in the following industries with independent intellectual property rights and patent industry, new materials, automobile, pharmaceutical, fine chemical, mechanical and electrical integration have become the focus of city development. Industry excessive assimilation restricts the formation of industry scale, caused by the irrational industrial structure. In addition, the low level of industrial technology and innovation ability is not strong, also weakened the competitiveness of industries in 36 International Journal of Sociology Study, Vol. 3 No. 1‐June 2015 2328‐1685/15/01 036‐05, © 2015 DEStech Publications, Inc. doi: 10.12783/ijss.2015.03.007

Study on the Adjustment of Industry Structure Model of Sustainable Development in Western China 37

Western regions.

Compare with the Private Economy, the State‐Owned Economy Has High Proportion From the quantitative perspective, state‐owned enterprises are numerous, but because most of the traditional enterprises’ technology is relatively backward, lack of vitality, the loss is severe. While the Western private economy is of less quantity and small scale, it is difficult to play the lead role in Western economy. The proportion of state‐owned economy is high and the proportion of private economy is low, which often makes the slow adjustment of industrial structure in the west. It is difficult to keep up with the world and the pace of industrial structure adjustment.

Establishment of Industrial Structure Dynamic Control Model in China's Western Region The adjustment of industrial structure is a dynamic process. The industrial structure information with partly known and partly unknown has the characteristics of dynamics and uncertainty. Therefore, this research by the method of grey system theory, constructs the dynamic model of industrial structure in chinaʹs western region.

Grey model (GM model), refers to the time series X (m) continuous curve in the data plane or curve approximation and time axis of the area, based on the differential fitting and built model.

The total energy consumption index X, the amount of investment increase K, technical level of Q and labor input L act as control variables in each industry. Due to technical level are difficult to determine and unable to statistics, in this paper, infrastructure investment, the three industrial investments, the proportion of employees act as variables, instead of increasing the amount of K investment, technical level of Q and labor input L. In order to establish GM model.Let

X   X (1)

X   X (0)

(1)

(0)



(1), X (0) (2),... X (0) (n)



be the original data, can generate series for X (1) , so k

(1), X (1) (2),... X (1) (n) . If X (1) (k )   X (0) (m), (1  k  n) , so we called



m 1



X  (1)

the accumulated

generating sequence for X (0) .

Let X i (t ), K i (t ), Qi (t ), Li (t ) represent the index of total energy consumption of industrial, investment increase, the level of technology and labor inputs of phase, we got the GM model: dX 1(1) (t )  a11(1) X 1(1) (t )  a1(1) K1(1) (t )  b1(1) Q1(1) (t )  c1(1) L1(1) (t ) (1) dt dX 2(1) (t )  a22(1) X 2(1) (t )  a2(1) K 2(1) (t )  b2(1) Q2(1) (t )  c2(1) L2(1) (t ) (2) dt dX 3(1) (t )  a33(1) X 3(1) (t )  a3(1) K 3(1) (t )  b3(1) Q3(1) (t )  c3(1) L3(1) (t ) (3) dt 

a  ( a ii(1) a i(1) b i(1) c i(1))T  ( B Ti B i ) 1 B Ti Y i

In the model, we have following equation:

Yi   X i (0) (2)

X i (0) (3) ... X i (0) (n) 

T

 1  (1) (1) K i (1) (2) Qi (1) (2) Li (1) (2)    2 ( X i (2)  X i (1))   (1) (1) (1)   1 ( X (1) (3)  X (1) (2))  K Q L (3) (3) (3) i i i i  B 2 i   ... ... ... ...    1  (1) (1) (1) (1) (1)   ( X i (n)  X i (n  1)) K i (n) Qi (n) Li (n)   2  (i  1, 2,3; n  2)

dX i (1) (t )  A(1) X (1) (t )  B (1)U (1) (t ) (4) dt

38 HAIYAN WEI, JINLE ZHANG, SHIYU ZHANG

And

X

 a1(1)  B 0   0

(1)

(t ) 

 X1(1) (t ) 

(1)

X 2 (t )

X 3 (t )  (1)

T

b1(1)

c1(1)

0

0

0

0

0

0

0

a2 (1)

b2 (1)

c2 (1)

0

0

0

0

0

0

0

a3

(1)

(1)

A

(1)

0   0   a33(1) 

0 a22

(1)

0

 K1(1) (t ) K 2 (1) (t ) K 3(1) (t )    U (1) (t )   Q1(1) (t ) Q2(1) (t ) Q3(1) (t )   (1)  (1) (1)  L1 (t ) L2 (t ) L3 (t ) 

0   0   c3(1) 

b3(1)

 a11(1)   0   0

(1)

Discrete the equation (4), we got: X (1) ( K  1)  e A X (1) (k )  A(1) (e A  I ) B (1)U (1) (k ) 1

Take e A  A , A(1) (e A  I ) B (1)  B , we got: X (1) (k  1)  AX (1) (k )  BU (1) (k ) and: (1)

(1)

X (k  1)  AX (k )  BU (k ) (5)

In equation (5):

 a11 A   0  0

0   a1 b1 c1  0  B   0 0 0  0 0 0 a33 

0 a22 0

(1) 11

a11  ea a1  a2  a3 

a1(1) a11(1) a2(1) a22

(1)

a3(1) a33

(1)

(1) 11

(e a

(e a

(1)

(e a

(1)

22

33

 1)

b1 

b1(1)

b3 

a22

b3(1) a33

(1)

(e a

(1)

22

(1)

0

a2 0

b2 0

c2 0

0 0 a3 b3

(e a

33

(1)

(1)

0 0  c3 

0

0

 1)

(e a

b2(1)

0

33

(1) 11

a11(1)

0

 0, a33  ea

22

 1) b2   1)

(1)

 0, a22  ea

0

c1 

c1(1)

 1) c2 

 1) c3 

(1) 11

(e a

a11(1)

c2(1) a22

(1)

c3(1) a33

(1)

(e a

22

(e a

33

(1)

 1)

(1)

 1)

 1)

a1 , a2 , a3 represents the growth elasticity of three industries for each additional unit of investment on the total

energy consumption index growth rate, b1 , b2 , b3 says three industries increase for each growth elasticity level units to the total energy consumption index growth rate respectively, c1 , c2 , c3 represents each increase of three times industry growth elastic unit labor force to the total energy consumption index growth rate. Equation (5) is the industrial structure dynamic control model.

According to the industrial structure model given above, and the data in Table 4 ‐ 1, we got following equation:

dX 1(1) (t )  1.9500 X 1(1) (t )  0.0033K1(1) (t )  0.0100Q1(1) (t )  0.0250 L1(1) (t ) dt dX 2 (1) (t )  2.2837 X 2 (1) (t )  0.0012 K 2(1) (t )  0.0011Q2 (1) (t )  0.1200 L2(1) (t ) (6) dt dX 3(1) (t )  1.5455 X 3(1) (t )  0.00001K 3(1) (t )  0.0006Q3(1) (t )  0.0795 L3(1) (t ) dt After the discretization and reduction treatment of equation (6), we got (7):

X 1 (k  1)  0.1423X 1 (k )  0.0015K1 (k )  0.0044Q1 (k )  0.0101L1 (k ) X 2 (k  1)  0.1020X 2 ( k )  0.0005K 2 (k )  0.0004Q2 ( k )  0.0472L2 ( k ) (7) X 3 (k  1)  0.2132X 3 (k )  0.00005 K 3 (k )  0.0003Q3 (k )  0.0404L3 (k )

Study on the Adjustment of Industry Structure Model of Sustainable Development in Western China 39

And

0 0  0 0 0 0 0 0  0.1423 0.0015 0.0044 0.0101    A 0 0.1020 0 B   0 0 0 0.0005 0.0004 0.0472 0 0 0   0  0 0 0.2132  0 0 0 0 0 0.00005 0.0003 0.0404  The Dynamic Control Model Accuracy Analysis Taking the equation (7) as a predictive model with the data in Table 1, prediction obtained three industrial energy consumption index values (2000 ~ 2003), respectively (1.0206, 1.0033, 1.0011, 1.0706), (0.93612, 0.98883, 0.97743, 0.99918), (1.0894, 1.1551, 1.178, 1.2299), which means deviation is 3.80%, respectively, 3.40%, 3.18%, agrees well with the actual values. The system deviation can be regarded as external influence of random factors. So the following this model based on the economic analysis is effective. And the model (7) stability and controllability are obvious.

TABLE 1

Primary industry

Second industry

Tertiary industry

Year The total energy consumption index Investment in capital construction Investment for renovation and transformation The proportion of employees The total energy consumption index Investment in capital construction Investment for renovation and transformation The proportion of employees The total energy consumption index Investment in capital construction Investment for renovation and transformation The proportion of employees

1999 1.00 92.34 11.95 62.9 1.0 890.40 472.01 13.1 1.0 1635.85 338.80 24.0

2000 1.01 107.43 8.63 60.4 0.96 997.23 582.58 14.3 1.1 1890.12 362.50 25.3

2001 1.00 110.52 8.67 60.0 0.96 1106.14 707.43 14.0 1.16 2230.00 431.76 26.0

2002 1.08 170.26 8.33 58.6 0.98 1332.20 977.43 14.7 1.22 2752.18 379.29 26.7

2003 1.13 194.13 12.58 57.6 1.08 1910.61 1359.90 14.4 1.3 3537.28 386.07 28.3

Data source: Chinese peopleʹs Republic of China National Bureau of Statistics, http://www.stats.gov.cn/

Analysis and Conclusion By comparison of (6) and (7), we can see that a1  a2  a3 .The first and second industry have major effect on energy consumption index, the tertiary industry has little effect on energy consumption index. The infrastructure investment of the first and second industry to the total energy consumption index is far greater than that of the tertiary industry, respectively 10 times and 30 times. So the first and second industry should strengthen infrastructure construction, improve agricultural production environment, control energy consumption, reduce the damage to the environment. This is consistent with the lack of infrastructure construction in Western China in reality. b1  b2  b3 Illustrates the influence of growth elasticity, technical level, two industry first on the total energy

consumption per unit of exponential growth rate, respectively 11 times and 14.7 times of the tertiary industry. So it should accelerate the technological transformation of the first industry and the second industry. The proportion of the second industry practitioners is higher than the rate of growth elasticity ratio of energy consumption index.

Practitioners accounted for the proportion of exponential growth effect is respectively 4.67 times and 1.12 times to the first industry and the tertiary industry.

From the internal factors of each industry, the first industry who’s every factor ratio is a1 : b1 : c1  1: 3.03 : 7.57 , indicating lack of infrastructure construction of the western region, need to strengthen the investment in infrastructure construction, improve the technical level of agriculture. While the first industry jobholders’ proportion is very high, the agricultural surplus labor forces flow. In the second industry, a2 : b2 : c2  1: 0.8 : 94.4 , shows western second industrial technology content has a great potential to absorb labor force. The tertiary industry in the western region still needs a lot of labor input to create employment opportunities for the laid‐off workers and rural surplus labor. The development of the tertiary industry in the western industrial structure adjustment should be the rapid.

40 HAIYAN WEI, JINLE ZHANG, SHIYU ZHANG

ACKNOWLEDGMENT

This work is supported by the National Social Science Fund (No.14XJL009) Soft Science Research Project of Shaanxi Province, (No.2014KRM42) NPU Policy Research Foundation (No. ZYY201403).

REFERENCE

[1]

Davis,S. H. ,1993, Traditional Knowledge and Sustainable Development, World Bank,pp. 2‐29.

[2]

Masahisa Fujita and Da Peng Hu, 2004, Regional disparity in China 1985‐1994: The effects of globalization and economic liberalization, The Annals of Regional Science, Vol. 35, No.1, pp.3‐37.

[3]

Ewald Nowotny, 2004, Evolution of structures of European economic policy, Journal of Evolutionary Economics, vol. 14, No.2, pp. 211‐215.

[4]

Guang‐zhen Sun and Yew‐K Wang Ng, 2000, The measurement of structural differences between economics: An axiomatic characterization, Economic Theory, vol.16, No.2, pp.313‐321.