Report On The Clothing Industry Prosperity Index In The Three Quarter Of 2011
Chinese Classics clothing Industrial prosperity index report shows that the three quarter of 2011, China classics clothing industry The prosperity index was 99.5 points, a slight increase of 0.1 points over the previous quarter, and the warning index of the clothing industry in China was 103.3 points, down 16.7 points from the previous quarter. Function The early-warning lights of the garment industry in China are changed from "yellow" to "green". Judging from the production and operation of garment manufacturing industry, the three quarter, clothing production, product sales revenue, export volume, gross profit, total tax and other indicators reverses the decline in the previous quarter, except for clothing production, the latter four indicators are better than expected; the total amount of fixed assets investment in garment manufacturing has dropped rapidly compared with the same period last year, but it is still a hot state. However, we should also see that clothing manufacturing industry still has some unfavorable factors such as the cold production of clothing, the further decline of the profit level of the industry, the sharp increase in the total deficit of the deficit companies, and the high inventory level. In the fourth quarter, under the background of tight domestic industrial structure adjustment, unclear external demand and higher cost of enterprise capital, the development of garment manufacturing industry is still hidden. In order to ensure the healthy operation and good development of the garment manufacturing industry, it is suggested that the government departments formulate and implement preferential policies to support the development of small and medium-sized enterprises, broaden the financing channels for SMEs, improve the cotton control system, and keep cotton prices basically stable. The early warning lamp number is the state of some important indicators that describe the development of the industry by means of traffic lights. The red light is too fast (overheating), the yellow light is fast (partial heat), the green light is normal and stable, the light blue light is slow (partial cold), the blue light is too slow (too cold), the different index is given to the single indicator lamp, and the comprehensive warning index aggregated by it is also shown by 5 light areas, meaning the same as above. Brief introduction of China economic prosperity index The "China economic prosperity index" was compiled and published jointly by the Economic Daily News Center and the national economic monitoring center of the State Statistical Bureau. The "China economic prosperity index" relies on the authoritative perspective of economic daily and National Statistical Bureau respectively in the authoritative perspective of China's economic field to track and monitor the operation of key economic sectors in the national economy, and timely excavate new situations and new problems in the field of industry reporting, and strive to build a high-level platform for continuous monitoring and information release of the industry's prosperity and development trend, so as to create an influential data product brand that accurately predicts the development trend of the industry, with a view to provide scientific decision-making basis for the central government, industry authorities and the vast number of industrial and commercial enterprises. What needs to be explained is that the "China economic prosperity index" is not a single index, but an index system. Each industry index will include the prosperity index (the main economic indicators such as industry production, sales, profits, employment, investment, etc.). The early-warning index is composed of the leading indicators of 10 industries to reflect the development trend of the industry. And the industry early-warning lamp is directly described by the red, yellow, green, light blue and blue lights. The "hyperbola" is used in the calculation of the prosperity index: the red curve is calculated by excluding seasonal factors and retaining random factors, while the blue curve further eliminates the random factors after eliminating seasonal factors. Through the comparison of the two curves, we can see clearly the influence and function of policy measures and other random factors on industrial development, and then we can better judge and grasp the development trend of the industry.
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