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中国景区类上市公司资本化率及其影响因素研究 被引量:2

Capitalization Rates and Their Influences on Chinese Listed Tourism Companies Involved in Scenic Spots
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摘要 文章根据加权平均资本成本和资本资产定价模型,通过计算8家中国景区类上市公司2004~2011年的权益资本成本和债务资本成本,得出景区类上市公司历年资本化率数值,并分析其变动趋势,为应用收益还原法评估景区经营权价值提供了较为科学的资本化率数值。并利用非平衡面板随机/固定效应模型,考察了控制权结构、董事会独立性、债权人治理因素对中国景区类上市公司资本化率的公司治理效应。研究结果发现,控制权结构与资本化率之间存在着倒"U"形的非线性关系,而董事会独立性对资本化率的影响不显著,若适当增加负债融资比例,可以加强对管理者的约束,降低资本化率。 Properly evaluating the management franchise values of scenic spots can scientifically curb opportunism behaviors, and can reduce business disputes related to the transfer process of management franchises in cooperative ventures between the government and enterprises. However, it is difficult for academics in China to scientifically and quantitatively evaluate capitalization rate values used in the income capitalization approach. To approach this problem, this paper conducts a review of the literature on quantitative estimates of capitalization rates, analyzes share prices and data on corporate debt for Chinese listed tourism companies involved in scenic spots from 2004 to 2011, and reveals that the weighted average cost of capital, which comprises equity capital cost and debt capital cost, can be taken as a reasonable and objective estimate of capitalization rate. Additionally, this paper analyzes the trend of change in the capitalization rate from the perspective of diversified business modes. Moreover, based on the random / fixed effects econometrics model of unbalanced panel data, we discuss the factors of control ownership structure, board independence and creditor governance, and measure their corporate governance effects on capitalization rates of the studied companies under the conditions in which company level factors are controlled. The research conclusions of this paper are as follows: first, the studied companies have higher cost of equity capital than of debt capital. Capitalization rates are generally moderate, but differ considerably among the studied companies. The mean curve of the capitalization rates approximates the shape of the letter "W" in the annual period, and this shape changes to approximate an " inverted U" as the company' s degree of diversification increases. Second, there exists a non-linear "inverted U" relationship between control ownership structure and capitalization rate, but board independence has no significant effect on the capitalization rate. In addition, an appropriate proportional increase in debt financing can strengthen constraints on managers, reduce the capitalization rate, and exert a positive effect on corporate governance. Third, there is a significant positive correlation between the profitability, solvency and capitalization rate of the companies. Moreover, enhancing the growth ability of the companies can reduce their capitalization rate. Company size has no significant effect on the capitalization rate. The policy implications of the research findings are as follows: first, according to the first and second conclusions, companies should make full use of debt financing to reduce their capitalization rates. Second, the average capitalization rate of 14.66% identified in this study can be used as a scientific capitalization rate value when the income capitalization approach is applied to assess the economic values of scenic spots. Third, according to the first conclusion, companies should increase their diversification to reduce the capitalization rate. Finally, improving corporate governance structure is the simplest measure that companies can implement to reduce the capitalization rate. Companies should avoid a highly concentrated ownership structure to reduce " tunneling" behavior. They should also increase the proportion of outside directors so as to increase the independence of the board of directors. In addition, they should make full use of mandatory debt interest payments to strengthen constraints on the top management team.
出处 《旅游学刊》 CSSCI 2013年第9期34-42,共9页 Tourism Tribune
关键词 景区类上市公司 资本化率 变动趋势 影响因素 非平衡面板回归模型 listed companies involved in scenic spots capitalization rate changing trend influencing factors regression model of unbalanced panel data
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