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Ownership structure, corporate governance and productive efficiency in China

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Abstract

This paper investigates whether and to what extent ownership structure and corporate governance affect productive efficiency in a sample of 744 publicly listed manufacturing firms in China between 1999 and 2006. The paper finds that firm efficiency, as estimated using stochastic frontier analysis and data envelopment analysis, is negatively related to state ownership while positively related to public and employee share ownership. In addition, the relationship between ownership concentration and firm efficiency is U-shaped, indicating that the largest shareholder may engage in tunneling activities. As the identity of the largest shareholder changes from government, government-controlled legal entity to other types of legal entity, firm efficiency significantly improves. These results provide strong evidence that political interferences have reduced firm efficiency. Moreover, firms with more independent board are more efficient, supporting the argument that board of directors can be an effective internal governance mechanism. Furthermore, provincial market development, a proxy for the strength of external governance mechanism, is positively related to firm efficiency. Overall, the findings illustrate that restructuring state-owned enterprises via improvements in corporate governance has enhanced firm efficiency, but partial privatization without transfer of ownership and control from the state to the public remains a major source of inefficiency in corporate China.

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Notes

  1. State shares are retained by the State Assets Management Bureau (SAMB) of the central or local government and are not allowed to be publicly traded. Legal entity shares are held by domestic institutional investors including banks, securities companies, insurance companies, mutual funds and other SOEs. Similar to state shares, legal entity shares are not tradable and most of them are ultimately controlled by the state through its control over the legal entities, although the government has initiated reforms to float state and legal entity shares in 2005. Public shares are held by the investment public and tradable on the two securities exchanges. Employee shares are offered to workers and managers of a listed firm, typically at substantial discounts, at the time of initial public offerings (IPOs).

  2. For detailed information on the construction of the provincial marketization index, see Fan and Wang (2008).

  3. An important assumption underlying market-based performance measures, such as Tobin’s q or market-to-book equity ratio, is that the stock market is sufficiently efficient so that share prices reflect the fundamental value of the listed firms. However, share prices of China’s listed firms are often driven by purely speculative activities and bear little information about the fundamental value. In addition, accounting-based measures, such as return on assets or return on equity, may not be good proxies for firm performance because earnings management behavior is quite prevalent in corporate China (Lin 2004). As a result, this paper avoids using purely market-based or accounting-based performance measures and chooses productive efficiency to measure firm performance.

  4. Aigner et al. (1977) and Meeusen and van den Broeck (1977) first developed the SFA model with a composite error term that sums a two-sided random error and a one-sided half-normal error term measuring technical inefficiency. Stevenson (1980), Pitt and Lee (1981), Kumbhakar (1987), Battese and Coelli (1988) and Greene (1990) provide several variations of the original SFA model allowing for different distributions of error terms, such as truncated distributions, exponential distributions and two-parameters gamma distributions. Park and Sima (1994), Fan et al. (1996) and Park et al. (1998) propose several specifications of semi-parametric panel SFA models. Kumbhakar et al. (2007) develops a new approach to handle non-parametric SFA models based on local maximum likelihood techniques. SFA models have been widely used in business, economics and management research. See Kumbhakar and Lovell (2000) and Fried et al. (2008) for reviews of the basic models, theoretical extensions and recent development of SFA; Shiu (2002) and Fu et al. (2008) for applications of SFA and DEA methodologies in studies of the productive efficiency of Chinese SOEs; and Li et al. (2008) for the special issue in Journal of Productivity Analysis on the productivity and efficiency analysis of transition economies.

  5. Charnes et al. (1978) first formulated the DEA methodology, which determines a piecewise linear efficiency frontier from the most efficient DMUs and derives efficiency measures for all other DMUs relative to that frontier. Since then, DEA has been widely used in business, economics and management research. See Cooper et al. (2000, 2004) for reviews of the basic models, theoretical extensions and major developments in DEA methods. Simar and Wilson (1998) first introduces the bootstrap method to obtain statistical properties of the DEA efficiency scores. Simar and Wilson (2007) extends their approach to account for the impact of environmental variables on efficiency. Simar (2007) and Simar and Zelenyuk (2011) develop stochastic DEA models that synthesize the best features of the DEA and SFA methods by introducing statistical noise in nonparametric frontier models.

  6. Simar and Wilson (2007) finds that efficiency scores generated by DEA are dependent on each other. Estimating regression (10) or (11) by OLS is not appropriate because \( \varepsilon {}_{i,t} \) and \( {\mathbf{Z}}{}_{i,t} \) are correlated.

  7. This paper uses FEAR (Frontier Efficiency Analysis with R) Version 1.13, a software package developed by Wilson (2008), to compute bootstrapped DEA estimates.

  8. This paper also estimates the half-normal and exponential SFA models and finds that they yield very similar empirical results with the conditional mean truncated normal SFA model. For brevity, estimation results from the half-normal and exponential SFA models are not reported in the paper.

  9. For example, the government may use the listed firms for personal gains or political nepotism. Because many senior managers are appointed by the controlling shareholders for their political loyalty and seniority in the political system, they no doubt have little incentives in improving firm performance.

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Acknowledgments

We thank seminar participants at University of Otago, Monash University, Jinan University, Zhongshan University, the 2007 NTU International Conference of Economics, Finance and Accounting held in Taiwan, the 15th Annual Conference on Pacific Basic Finance, Economics, Accounting and Management (PBFEAM) held in Ho Chi Minh City, and the 2009 China International Conference in Finance held in Guangzhou for their valuable comments and suggestions. Su also acknowledges financial supports from the National Natural Science Foundation of China (Grant No. 71173090), China Ministry of Education (Grant No. 09YJA790084 and the Program for New Century Excellent Talents in University NCET-08-0614), the Guangdong Pearl River Scholar Fund, the Fundamental Research Funds for the Central Universities (21609204), the Guangdong Natural Science Foundation (Grant No. S2011010004257) and the Guangdong Social Science Foundation (Grant No. 09E-16).

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  1. Department of Finance, Jinan University, Guangzhou, 510632, China

    Dongwei Su & Xingxing He

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  1. Dongwei Su
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Correspondence to Dongwei Su.

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Su, D., He, X. Ownership structure, corporate governance and productive efficiency in China. J Prod Anal 38, 303–318 (2012). https://doi.org/10.1007/s11123-011-0257-8

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