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Factors Influencing the capital structure of the listed companies of China's iron and steel industry

Author: SunYan””WangZuo From: www.yourpaper.net Posted: 2009-10-30 00:31:10 Read:
Abstract: The company's capital structure is reasonable directly affect the company's operating results and long-term development, the use of multivariate statistical analysis, the empirical analysis of the impact factor of the capital structure of listed companies in China's iron and steel industry, the results show that: iron and steel industry, the profitability of listed companies, firm size, liquidity, cash flow and asset-liability ratio is negatively correlated; positively related to the value of asset-backed, corporate growth, corporate operating capacity, asset-liability ratio.
Keywords: iron and steel industry; listed companies; capital structure; Factor Analysis
First, the study design

(A) variable defined
The capital structure of listed companies in this article impact factors index system (see Table 1).

For the above-mentioned variables, using the method of factor analysis to identify independent factors set, then regression analysis of these factors on capital structure.
(B) sample selection
The paper selects listed companies of December 31, 2007 in Shenzhen and Shanghai-listed steel industry as the research sample, selected in the 2007 Annual Report data, data from Wind Financial Database. Second, the empirical analysis

(A) factor analysis
1 correlation test. Factor analysis aims to simplify data or to find out the basic data structures, a prerequisite for the use of factor analysis is that there should be a strong correlation between the observed variables after Bartlett test show: Bartlett's accompanied by a probability of 0.0000, less than significant level of 0.01. Observed variables of this article KMO value of 0.624, according to statisticians Kasier given criteria, factor analysis can be done.
Extract the common factor. Using factor analysis method to extract the common factor variance analysis table, seven common factor variance contribution rate of more than 7%, the highest of 17.55% cumulative variance contribution rate has reached 85.29 percent, and be able to explain most of the information, According to the cumulative variance contribution rate is greater than or equal to 85% of the principle to select the front seven factor analysis (see Exhibit 2).
3. Factor named. In order to facilitate the interpretation and analysis of practical problems need to be rotated in order to the factor loadings matrix represented the load on each factor influencing factors, which can reflect the meaning of the different factors represent variance maximize implementation of the factor loading matrix is cross rotated and after the results (see Table 3).
The significant load variable factor F1 return on equity, return on assets, the main business profit margins, earnings per share, profitability named. The factor F2 on the significant load variable total assets, the main business income, can be named enterprise scale. Significant load factor F3 variable ratio of fixed assets, inventory ratio of fixed assets, tax levels, operating expenses than income, can be named as the value of asset-backed. The factor F4 significant variable load current ratio, quick ratio, asset liquidity named. Of factor F5 load variable is the growth rate of total assets, main business revenue growth, net profit growth rate can be named corporate growth. Of factor F6 has a significant load variable for inventory turnover, asset turnover, fixed asset turnover, can be named for enterprises operating capacity. Significant variable load factor F7 on the per share net operating cash flow per share in net cash flows, can be named as the level of corporate cash flow.

(B) regression analysis
Regression analysis using the extracted factor on the asset-liability ratio DW test value of 2.373, close to 2, indicating that there is no clear correlation between the residuals. R = 0.796, the best fit model. F value equal to 5.683, Sig = 0.001, Regression strong, and through hypothesis testing. Are shown in Table 4 and Table 5.
The regression results can be expressed as follows:
Y = 58.858-2.123F1-0.544F2 0.665 F3-8.335F4 2.080 F5 0.028 F6-0.64F7
Regression analysis showed that: the negative correlation between profitability and asset-liability ratio, strong corporate profitability, it is able to retain more of the surplus on a smaller demand for bond financing. Negative correlation between the size of the business and the asset-liability ratio, indicating that the greater the size of the business, the smaller the required liability. The value of asset-backed and asset-liability ratio is positively correlated, the higher the value of the security, to have more assets to secured liabilities.

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