Xinjiang Production and Construction Corps of Industrial Structure Adjustment - An Empirical Analysis of Grey Correlation Model

[Abstract] proved that industrial restructuring is the key to the Xinjiang Production and Construction (hereinafter referred to as the Corps) Regiment of economic development. In this paper, 2003--2009 years of statistical data based on gray correlation analysis model Corps industrial structure empirical analysis. Studies have shown that: agriculture remains the dominant industries Corps, the second and tertiary industries in the industrial structure are weaknesses Corps, the Corps indicated that the industrial structure is still in the primary level. Based on these conclusions, the paper put forward relevant suggestions Corps of industrial restructuring.
Paper Keywords: industrial restructuring, gray correlation analysis model, empirical analysis, the Xinjiang Production and Construction Corps industry is the cornerstone of a country's economy, the modern economic development in the final analysis is an industrial structure adjustment and optimization of the process. Xinjiang Production and Construction Corps (hereinafter referred to as 'Corps') was in the 1980s and 1990s were a number of industrial restructuring, and effectively promoted the economic development of the Corps. However, due to historical reasons, compared with the domestic and foreign countries and regions, the Corps of industrial structure is still in a relatively irrational state, limiting the further development of the Corps economy, therefore, drawing on domestic industrial structure adjustment on the basis of research results Research Corps of industrial structure, its industrial restructuring have important inspiration and guidance.
First, data sources and model (a) research in economics indicators and data sources commonly used GDP, industrial production and gross internal three times the GDP of the industrial sector to measure the industrial structure of each situation in a country and region. Therefore, this article will select the GDP Index of the Corps as an analysis of the industrial structure, all data are derived from the 'Statistical Yearbook of the Xinjiang Production and Construction Corps' (2004 Year - 2009). As the 'Statistical Yearbook of the Xinjiang Production and Construction Corps,' the integrity of the time is not very good, so the sample data collected in large quantities is very difficult, therefore we chose gray correlation model analysis, factors associated with the Corps to quantify the industrial structure.
Theoretical basis (b) Introduction 1. Grey relational analysis model called relational analysis model, is to analyze the factors of the system. Factor analysis, mainly statistical methods, such as single regression, non-linear regression. But statistical analysis of the factors are mostly small, linear, linear regression, multivariate regression is very difficult. The multi-factor, very difficult nonlinear regression analysis (Luo Qingcheng, Xu Guoxin, 1989).
In 1982, a famous scholar Professor Deng Julong first proposed the theory of gray system, gray correlation analysis emerged. Gray correlation analysis between the factors is the case among comparator or quantitative description of the system or systems, in the development process and the relative change over time, that is the analysis of time series of geometric shapes, etc. with their varying size, direction and magnitude closeness to measure the size of the correlation between them. This is a measure between systems or factors that change over time correlation magnitude scale, known as associate degrees. According to this theory the mathematical basis of space, according to the normative, even symmetry, integrity and proximity of these four principles, gray system theory to establish a correlation coefficient of main action sequences and related sequences, do average processing, have relevance degree (Sun Jing Kou Hua Qiu, 2003).
Step 2. Grey Relational Analysis (1) to determine the reference sequence. The so-called reference sequence is used as a comparison 'mother sequence', expressed as:
{X0 (k)} = {X0 (1), X0 (2), ......, X0 (n)}, (k = 1,2, ......, n)
Correlation Analysis for the reference sequence to compare the degree of association 'child series' called comparative sequence, denoted by X1, X2, ..., XN.
(2) dimensionless. Due to various factors, different measurement system, so quantitative data is also inconsistent, different dimensions, different order of magnitude is not easy to compare, or difficult to obtain a correct conclusion. Therefore, when gray analysis, are generally required to be non-dimensional data processing. Original series dimensionless method, there is the initial value of the mean of, the values, public values, and so the relative value of the interval. Commonly used methods are mainly the first two. Initialization method, in general quiet conditions to adapt to the social and economic system of dimensionless, so choose Initialization. Initialization refers to all data on the same number of columns, are divided by the first data to obtain a new series. As for the initial value of the reference sequence obtained after treatment:
{X0 (k)} = { , , ..., }, (K = 1,2 ... n)
(3) Find the correlation coefficient. The degree of association is essentially the difference between the curve geometry. Therefore, the size difference between the curves can be used as a measure of the degree of association. Association analysis under normal circumstances, for a reference sequence X0, there are several comparative sequence X1, X2, ... Xn. The difference between the comparison of sequences (ie comparison curve) to the reference sequence (ie each point of the curve), and by the following relationship:
(4) Find the correlation degree. Because the correlation coefficient is relatively curve and reference curve relative difference in the k-time, so it's more than one value, the information is too scattered and not easy to compare a whole. Therefore, it is necessary to focus the correlation coefficient each time to a value that is seeking its average value, expressed as the number of associate degrees.
Correlation denoted Its expression is:
=, (I = 1,2, ..., n)
(5) The row incidence order. When comparing sequences. Months, the relative degree of association also has m, according to the value of the size of the line up is related order. Relational comparison of sequences directly reflects various advantages and disadvantages related to the reference sequence. Relatively large correlation value sequence, indicating a greater its impact on the reference sequence, and vice versa, the less impact on the reference sequence.
Second, the gray correlation Empirical Analysis of Industrial Structure associated Corps (a) First Corps three industries in accordance with the 2009 'Group Statistical Yearbook,' get 2003-2008 Corps of GDP, primary industry GDP, the first secondary industry GDP, the tertiary industry GDP, gross domestic product selected as a reference sequence, first, second and tertiary industries GDP compared sequences, the first to get the original data, as shown in Table 1:
Table 1 2003 - 2008 three industries sequence original series (Unit: 100 million)

Years

2003

2004

2005

2006

2007

2008

Total production value

257.7

281.2074

217.6585

358.9042

399.1845

437.989

A production output value

109

112.074

126.2825

135.7345

147.1156

152.58054

Secondary industry GDP

63.9

69.03602

80.6429

94.880513

115.2677

139.02155

Tertiary industry GDP

84.8

100.0973

113.2288

128.28914

136.8012

146.38693


Source: 'Statistical Yearbook Corps' to 2003 prices.
Use Table 1 of the original data series, as the initial value of the process, the use of the aforementioned method, calculated correlation analysis table is as follows:
Table-2 corps of three related industries analysis table

Project

Total production value

A production output value

Secondary industry GDP

Tertiary industry GDP

Correlation

1

0.664503

0.668828

0.764059063


As can be seen from the table, the tertiary industry total production value associated with the highest degree of 0.76405903, followed by the secondary industry, the first industry association is minimum.
(Ii) the internal structure of the three industries associated Corps analysis 1, the internal analysis Firstly, the first industry association in accordance with the 2009 'Group Statistical Yearbook,' get 2003-2008 Corps gross agricultural production, farming, forestry, animal husbandry, fisheries, agriculture gross production data service, select the total value of agricultural production as a reference sequence, farming, forestry, animal husbandry, fisheries, agriculture gross production services compared sequences, the first to get the original data table, as shown in Table 2 show:
Table-3 2003 - 2008 Internal Corps first industrial original series (Unit: million)

Years

Gross agricultural production

Planting

Forestry

Livestock

Fisheries

Agricultural services

2003

2187989

1775231

43331

207217

10305

151905

2004

2255106.1

1783759.5

32359.299

239,276.53

11549.172

188,161.64

2005

2558181.3

2071573

31273.781

246,790.48

13668.681

194,875.4

2006

2847057.7

2320964.3

29397.685

259,905.78

14788.569

222,001.3

2007

3089950.5

2486961.1

30287.175

332,686.63

16501.195

223,514.37

2008

3225800.5

2495472

29895.073

439,657.11

18937.397

241,838.91


Source: 'Statistical Yearbook Corps' to 2003 prices.
The original time table 3 the number of columns to do the initial value of the process, according to previously described methods and procedures to calculate the correlation degree of the table, as shown in Table 4:
Correlation table inside -4 primary industry analysis table

Project

Agriculture

Planting

Forestry

Livestock

Fisheries

Agricultural services

Correlation

1

0.961208

0.522328

0.778062

0.747742

0.799749


Table 4 shows, the Corps of agriculture all relevant factors of the main factors related to: Farming> Agricultural Services> Livestock> Fisheries> Forestry, indicating that the focus of development followed by the Corps of agriculture is farming, agricultural services, animal husbandry, fisheries, forestry, farming plays an important role in the Corps of agriculture. Agricultural development and stability Corps planted under the premise of industry, should arrange agricultural services, the proportion of animal husbandry, strengthen agricultural diversification.
Secondly, according to the 2009 'Group Statistical Yearbook' data collation get 2003-2008 farming internal corps relevant data, as shown in Table 5:
Table -52,003 - A 2008 internal corps farming original series (Unit: million)

Years

Gross planting industry

Cereals

Cotton

Oil-bearing

Vegetable gardening

2003

1756414

131,731.05

1271643.7

47423.178

107,141.25

2004

1758594

167,066.43

1190568.1

40447.661

138,928.92

2005

2035104.8

203,510.48

1404222.3

28491.467

126,176.5

2006

2272498.1

215,887.32

1524846.2

24997.479

170,437.35

2007

2487006.4

174,090.45

1758313.5

39792.102

149,220.38

2008

2495471.9

209,619.64

1579633.7

62386.798

242,060.78


Source: 'Statistical Yearbook Corps' to 2003 prices.
Use Table 5 of the original data, the relevance of the Corps planted inside each sector, such as shown in Table 6:
Correlation Table -6 planting internal analysis table

Project

Planting

Cereals

Cotton

Oil-bearing

Vegetable gardening

Correlation

1

0.725375

0.897365

0.644254

0.760632


Table 6 shows the internal corps farming all relevant factors of the main factors related to: cotton> vegetable gardening> Cereal> oilseeds, which shows the development of the Corps order of planting cotton, vegetable gardening, grains, oilseeds, the Corps is still farming presented 'a single flower' situation, while vegetable gardening and grains have a higher degree of relevance. Corps planting can be in the context of the development of cotton, an appropriate increase in the proportion of vegetables and cereals like gardening.
2. The internal analysis was first associated with the second industry 2003-2008 farming internal corps relevant data based on the 2009 'Group Statistical Yearbook' data collation, as shown in Table 7:
Table -72,003 - A 2008 internal industry Corps second original series (Unit: million)

2003

2004

2005

2006

2007

2008

Secondary industry GDP

638721

690,448.88

805,928.12

948,992.22

1153112.1

1390115

Industrial Gross

409605

443,860.76

546,286.99

661,966.26

824,217.1

1005611.2

Gross Construction

229116

246,588.12

259,641.13

287,025.96

328,894.74

384,503.8


Source: 'Statistical Yearbook Corps' to 2003 prices.
On the basis of Table 7, the calculated internal correlation of the second industry.
Correlation table inside -8 second industry analysis table

Project

Secondary industry

Industry

Building industry

Correlation

1

0.746132

0.654027


As can be seen from Table 8, the impact of industry on the second corps is greater than the construction industry.
Secondly, and then select industrial output as the reference sequence, select light and heavy industries as compared sequences, original data column in Table 9, calculate correlation, the results in Table 10.
Table -92,003 - The 2008 corps within the industry original series (Unit: million)

2003

2004

2005

2006

2007

2008

Industry

1218342

1406806.2

1698362.7

2076174.6

2612177.7

3182600.8

Light industry

758540

823,250.24

898,542.72

1034767.4

1349939.5

1573128

Heavy industry

459802

583,555.99

799,819.96

1041407.2

1262238.3

1609472.8


Source: 'Statistical Yearbook Corps' to 2003 prices.
Table -10 corps within the industry association analysis table

Project

Industry

Light industry

Heavy industry

Correlation

1

0.766386

0.659532


As it can be seen from Table 10, the impact on the industry's heavy light corps, corps and other mineral resources for further development.
3, the internal analysis since the corps of tertiary industry association statistics on the tertiary industry data classification more messy, so just select transportation, storage and postal industry as a comparative sequence wholesale and retail trade, in order to increase the value of the output value of the study, see the original sequence Table 11, the associated computational analysis shown in table 12.
Table -112,003 - A 2008 internal corps of tertiary industry original series (Unit: million)

2003

2004

2005

2006

2007

2008

The added value of the tertiary industry

888869

1045512.2

1132584.1

1283091.9

1367860.2

1463810.7

Transportation warehousing gross postal industry

113317

112,210.32

111,279.47

128,334.96

142,689.46

145,837.87

Wholesale and retail trade worth

198364

206,550.15

190,334.65

224,651.09

251,070.05

277,656.41


Source: 'Statistical Yearbook Corps' to 2003 prices.
Correlation table inside table -12 Tertiary Industry

Project

Tertiary Industry

Transportation warehousing postal industry

Wholesale and retail trade

Correlation

1

0.739575

0.78507


As can be seen from Table 12, the impact of the Third Corps of the wholesale and retail industry, more than transportation, warehousing and postal industries.
Third, the conclusions and measures (a) The conclusion 1. Agriculture is the Corps of competitive industries, its dominant position in the stable at the same time, adjust the agricultural structure should be reasonable, strengthen agricultural diversification.
2. The second and tertiary industries in the industrial structure are weaknesses Corps, the Corps indicated that the industrial structure is still in the primary level. In the second industry, is still based on traditional, low value-added agricultural products processing industries, the proportion of high-tech industries, high value-added industries is very low, the level of industrial development is a key constraint Corps uncoordinated industrial development. In the tertiary industry, the impact of wholesale and retail trade industry, although more than a third transportation, warehousing postal industry, but between the two are very similar, indicating that the Corps develop new industries need to be further accelerated, therefore, an urgent need to upgrade the industrial structure of the Corps tertiary industry also need further expansion.
As can be seen, the Corps of industrial structure is the key factor behind the economic development corps, therefore, adjusting the industrial structure is the Corps economic imperative.
Policy (b) to promote industrial restructuring Corps Recommendation 1. The development of modern agriculture, accelerate agricultural industrialization process of agriculture is the foundation of the Corps economy, but also the Corps of competitive industries. Key growing corps of agriculture should be based on the quality and efficiency of continuous improvement achieved by the number of growth-oriented transformation of the quality of growth-oriented, and this change is to develop the Corps of modern agriculture, the core is accelerating the Corps of agricultural industrialization process (Li Yuxin , Li Xiaoju, 2007). Should increase investment in agriculture, the adjustment of agricultural layout, solve forestry, animal husbandry, industry, short-legged two issues, protecting the environment, developing national-needed cotton, grain, pond feed, fruits, wool sheep and green food production base and export base. We have established the Tianshan Mountains cotton, sugar, grain crop belt, northwestern pastoral areas of grain and oil crops, Tianshan Mountains cotton, grain, sugar crop belt, and actively promote the southwestern cotton, grain, fruit area development.
To this end, it is necessary to follow the agricultural modernization 'high five' (land output rate, high labor productivity, high value-added processing, high environmental quality, high quality of life) and 'seven' of (science and technology of modern, mechanized, structure rationalization, layout regionalization, business integration, knowledge of farmers, rural urbanization) standards, improve the efficiency of agricultural production; second is to rely on the advantages of the Corps of agricultural resources, and gradually build a national export cotton and high-quality grain, livestock products, specialty fruits production base; third is to the industrialization of agriculture in the Corps, '6221' project for the development goals, market-oriented, high technology as a means of efficiency as the center, based on Farms, and actively promote the industrialization process of agriculture corps.
2. Accelerate the development of the secondary industry, and vigorously promote the industrialization process is a strategic choice to promote the industrialization process of objective laws of economic development, but also the economic development of the Corps. The development of industry in the industrial structure play an important role, and the current corps slow development of industry, a direct impact on the further development of the Corps of the total national economy and further improve the economy, so vigorously promote the industrialization process of industrial restructuring is to focus on the Corps of One.
First Corps of the industrial structure adjustment should follow the requirements of new industrialization, market-oriented, rely on scientific and technological progress, the depth of processing, excellent, specialty foods, to extend the textile industry chain, the development of agricultural machinery, equipment and other water-saving agro-industries, the development of quality cement, stone and other new building materials industry and actively develop bio-pharmaceutical products, research the use of cottonseed protein, wind energy, solar energy and protein, bentonite and other advantages of resources, the establishment of high-tech industry is dominated by traditional industries based on new industrial framework, thereby the XPCC industry gradually moving to high-class. Secondly, the priority development of Shihezi Economic Zone Tianshan Mountains, wujiaqu and southern economic zone of Alar, Tumushuke four cities and Kuitun Tianshan District, Hami big barracks town and a number of distinctive industrial park, Promoting point line to line with the surface, and gradually form a reasonable division of labor, the cooperation, highlight the advantages of the industrial layout; and finally to actively take advantage of preferential policies for developing the western region and other countries, relying on its agricultural, mineral and other resources, and actively undertake domestic industry transfer.
3. To develop the market, to promote the rapid development of the tertiary industry to deepen the reform of state-owned commercial enterprises, actively cultivate and develop, 'the company ten Farm' and other new forms of modern distribution organization relations and marketing chain, delivery operations, the establishment of efficient operation of commodity circulation and market information network, speed up the flow of modernization and internationalization. Relying towns, roads, inland goods distribution center and windows, and actively nurture and strengthen the market system and a comprehensive service system construction, planning and specialty products market, small commodity wholesale market, libraries, and storage of fresh fruits and grain, cotton, agricultural repository, forming a large market and achieve large circulation. Optimize the export commodity structure, foster export base, expand the depth of the neighboring countries, Europe and Southeast Asia, efforts to expand in Africa, the Middle East and Eastern Europe. Actively promoting the international chain to join the network. We must focus mainly white cotton series, sue tomato-based red series, with fruits, beans, peanuts and other characteristics mainly green series commodity export bases. While scientific and rational organization of the traditional development of tertiary industry, and strive to expand the information industry, characteristic tourism, finance and insurance and technology services and other emerging industries, promote the diversification of the tertiary industry.

References]
[1] Xinjiang Production and Construction Corps Corps Statistical Yearbook [Z] Beijing: China Statistics Press, 2004-2009.
[2] Luo Qingcheng, Xu new relational analysis and application [M]. Jiangsu Science and Technology Publishing House, 1989.
. [3] Sun Jing, Qiu Hua Kou Beijing Tourism Industry Development Strategy [J] Systems Engineering Theory and Practice, 2003, (6): 116-122.
[4] Li Yuxin, Li Xiaoju Xinjiang Corps Regional Economic Differences and Coordinated Development [M]. Xinjiang Production and Construction Corps Press, 2007.

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