Abstract:

This study explores the impact of state ownership on the performance of Chinese listed firms.  This study uses annual data of 143, state-owned 1,235, private enterprises for a period of 2011 to 2015. We use Ordinary Least Square method to find whether firm profitability and ownership are associated with each other or not. The results of whole sample indicate that over all firm performance and state ownership are negatively associated in China. However, the negative connection between state ownership and financial performance changes as we run the regression across different sectors.

Key Words:

Capital Structure, Firm Performance, State-Owned Enterprises, China.

Introduction

The literature provides extensive research work on the connection between state control and profitability of the companies. Smith, (1877) first proposed the concept that ownership and financial performance of corporations are linked to one another.  The division of ownership and control in modern corporate environment is very important to ensure that management behaves in the interest of shareholders. Specifically, introducing large shareholders in state owned enterprises can reduce entrenchment of the owner (state) and the managers. Since major shareholders have both incentives and resources for controlling management and protecting wealth of minority shareholders. The two prominent theoretical thoughts, Property right theory (Villalonga, 2000) and residual claimant theory (Rowthorn and Chang, 1993) underline that non-SOE’s are better than SOE’s in both profitability and efficiency. The property right theory claims that right of the shareholders are much clear and more protected in non-SOEs than SOEs. Such inequalities in shareholders right, leads to effective monitoring and better management performance in private enterprises (Alchain, 1965; McCormick and Meiners, 1988).

The connection between SOE and firm profitability is empirically investigated by many researchers around the world. Dewenter and Malatesta (2001) empirically investigates the impact of state control on firm profitability, they found that government enterprises are less profitable than private enterprises. Boardman and Vining (1989) examine the firm performance and efficiency of state and private enterprises in Canada. There results indicate that private firms outperform public firms in both productivity and competitiveness. Pryke, (1982) analyses and compares the firms’ profitability of private and state controlled enterprises in across different sectors. His results showed that non-SOE in these three industries were better in both efficiency and profitability, than state controlled enterprises. Ahuja and Majumdar, (1998) analysed the performance of government owned firms in India, over the period of 1987 to 1991. Their result shows that state owned enterprises are poor in firm performance.  Bashir, Riaz, Butt and Parveen, (2013) examine the impact of ownership on the performance of firms in Pakistan for the period of 2007 to 2011. Their result shows that private companies are better in firm performance than the government owned companies. Davis, (1971) examines the private and state owned companies in airlines industry of Australia. Their result shows no significant differences in the firm performance of private and state owned enterprises. Kole and Mulherin, (1997) analyse and compare firm profitability of private and SOEs in US. Their findings indicate that private sector performance was not substantially different from that of state-owned enterprises. Ahmed and Hadi, (2017) analyse the connection between ownership and profitability of firms in MENA region. Their finding indicates that managerial ownership is negatively linked to profitability, while large shareholders and government ownership is positively connected to the firms’ profitability.

The system of corporate ownership is distributed in developed as well as new developing countries. However, due to well-established legal framework and managerial labour market, the right of minority shareholders in developed countries is strongly secured as compared to emerging and developing countries (Claessens and Fan, (2002)). China is an important emerging country that is transforming toward a market economy. Due to weak law enforcement and poor legal infrastructure, Chinese companies have concentrated ownership, poor protection for investor’s rights and limited disclosure. Chinese publically listed company’s main shareholders include private, state or institutional shareholders. During the early economic reform the Chinese government has privatized many small and medium state owned enterprises but still many Chinese companies have concentrated state ownership. 

Several empirical studies have looked into the phenomena of the connection between state ownership and firm profitability in China. However, finding from existing studies on the connection between state control and profitability are not clear. Xu and Wang, (1999) empirically examined the effect of ownership on firm profitability for the period of 1993 to 1995. The study result indicates a negative relationship between state control and business profitability. Kang and Kim, (2002) investigated the association between ownership and firm performance in China. Their result shows that enterprises owned by state are poor in performance partially privatized enterprises. Sun and Tong (2003) examined the connection between state control and profitability of Chinese companies. Their result shows that firms controlled by state are poor in performance than private companies. Similarly Qi et al., (2000) examine a sub set of the listed Chinese companies and found that state control and firm profitability were adversely related. The effect of state control on fir profitability was analysed by Sun et al,.( 2002) using data of Chinese listed. Their study reveals different result from the above mentioned. They claim that state ownership is positively linked with profitability. Yu, (2013) empirically investigates the connection between state control and profitability of firms for a period of 2003 to 2010. The result shows that coefficient of state dummy have a positive effect on the performance of the firm.

Such divergent result from the existing studies may be resulted because of different model specification, sample selection techniques or because of ignoring the sect oral differences. All of the above mentioned studies have not accounted for the sect-oral level difference, which is, running regression across different sectors. It is therefore very important to investigate the link between state ownership and profitability of the firms across different sectors.

In the following study we use a dummy variable, state-ownership, to explore the connection between state control and profitability of listed companies in China. The impact of state ownership on firm profitability is also considered for the difference in the sector where a particular firm belong. This research employs an approximation of the Ordinary Least Square to investigate the relation described above.

Rest of the paper is organized as follows. Section two presents data, empirical model and variables used in the study. Section three discusses empirical results and section four presents conclusion.  

Data and Empirical Model Data

This study includes seven different sectors’ data (construction (BVD 10), chemical, rubber, plastic and non-metallic products (BVD 06), machinery and other equipment (BVD 08), metals and metal products (BVD 07), primary sector (BVD 01), services sector (BVD 17), and Transport (BVD 13)) . This study uses Annual data of 143, public and 1,235, private listed firms for a period of 2011 to 2015. All the financial and instructional data is extracted from Orbis. This study sample does not include any financial enterprises because their debt levels are driven by regulation. As a consequence, these firms' debt-like liabilities are not comparable with non-financial firms' debt  (Zhengwei, 2013). 

Empirical Model

The model used in this study assumes that financial performance (FP) is determined by Leverage (L), tangibility (T_icsy), size (?lnTA?_icsy), and Tobin’s Q (?TQ?_icsy) of firm I sector s in year y. To investigate the connection between state control and profitability, dummy variable is created. Therefore ?SOE?_ics, is a dummy variable equivalent to one if a company is owned by the state. Firm profitability is the ratio between earnings before interest and taxes and total assets, leverage is calculated as total debts over total assets, tangibility is equal to net tangible assets over total assets, Size is the natural log of total assets measured in billion US$ and growth is the fraction of market capitalization and total assets.

The empirical model is given below:

?FP?_isy=?_isy ? + ??_1 L_isy+?_2 T_isy+?_3 ?lnTA?_isy+?_4 ?TQ?_isy+?_5 ?SO?_is+?_y+?_s+?_isy 1)

Equation 1 ?_1 to ?_5 shows the estimated coefficient of all variables, ?_y and ?_s represents Year specific and sector fixed effect and ?_isy shows the error term. The statistical significance of ?_5show the effect of state ownership on firm performance in Chinese listed companies. To further investigate the effect of ownership on firm profitability at different sectors, firm specific fixed effects ?_s is eliminated from equation 1.

Empirical Outcome Table 1. Correlation result

> > > > >

Variables width="84" nowrap=""> ROA width="90" nowrap=""> Leverage width="96" nowrap=""> Tangibility width="90" nowrap=""> Size width="84" nowrap=""> Tobin's Q

ROA width="84" nowrap=""> 1 width="90" nowrap=""> width="96" nowrap=""> width="90" nowrap=""> width="84" nowrap="">

Leverage width="84" nowrap=""> -0.230*** width="90" nowrap=""> 1 width="96" nowrap=""> width="90" nowrap=""> width="84" nowrap="">

Tangibility width="84" nowrap=""> 0.050*** width="90" nowrap=""> -0.037*** width="96" nowrap=""> 1 width="90" nowrap=""> width="84" nowrap="">

Size width="84" nowrap=""> 0.119*** width="90" nowrap=""> 0.282*** width="96" nowrap=""> -0.186*** width="90" nowrap=""> 1 width="84" nowrap="">

Tobin's Q width="84" nowrap=""> 0.133*** width="90" nowrap=""> -0.201*** width="96" nowrap=""> -0.033*** width="90" nowrap=""> -0.066*** width="84" nowrap=""> 1

*** show significance 1 percent levels

 

Table 1 present the correlation between dependent and independent variables. The result shows that firm performance and other firm variable are significantly correlated. Leverage is significantly negatively correlated, while tangibility, size and Tobin’s Q are significantly positively correlated with firm performance.

Table 2 shows descriptive statistics of all the variables in our model across different sectors. The average mean value of firm performance (ROA) is significantly lower for state owned enterprises in the following sectors; Chemical, rubber, plastic and non-metallic products, Machinery & other equipment and Metals & metal products, while firm performance of state enterprises is significantly higher in services, primary and transport sector.  Among the entire sectors, average mean value of size is significantly higher, whereas the average mean value of growth is significantly lower for SOE. Leverage is significantly lower for private enterprises among all sectors except for the transport sector.

Table 2: Descriptive Statistics

> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >

Chemical, Rubber, Plastic and Non-Metallic Products

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 130 width="55" nowrap=""> 0.035 width="74" nowrap=""> 0.034 width="55" nowrap=""> 0.086 width="75" nowrap="" rowspan="2"> -1.797*

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 1675 width="55" nowrap=""> 0.047 width="74" nowrap=""> 0.041 width="55" nowrap=""> 0.077

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 130 width="55" nowrap=""> 0.560 width="74" nowrap=""> 0.575 width="55" nowrap=""> 0.208 width="75" nowrap="" rowspan="2"> 5.619***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 1675 width="55" nowrap=""> 0.447 width="74" nowrap=""> 0.444 width="55" nowrap=""> 0.222

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 130 width="55" nowrap=""> 0.927 width="74" nowrap=""> 0.956 width="55" nowrap=""> 0.106 width="75" nowrap="" rowspan="2"> -0.289

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 1675 width="55" nowrap=""> 0.929 width="74" nowrap=""> 0.951 width="55" nowrap=""> 0.079

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 130 width="55" nowrap=""> 13.932 width="74" nowrap=""> 13.879 width="55" nowrap=""> 1.050 width="75" nowrap="" rowspan="2"> 7.476***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 1675 width="55" nowrap=""> 13.150 width="74" nowrap=""> 13.068 width="55" nowrap=""> 1.156

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 130 width="55" nowrap=""> 0.978 width="74" nowrap=""> 0.684 width="55" nowrap=""> 0.988 width="75" nowrap="" rowspan="2"> -3.636***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 1675 width="55" nowrap=""> 1.650 width="74" nowrap=""> 1.040 width="55" nowrap=""> 2.089

Construction

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of observation width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 45 width="55" nowrap=""> 0.035 width="74" nowrap=""> 0.027 width="55" nowrap=""> 0.033 width="75" nowrap="" rowspan="2"> 0.421

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 175 width="55" nowrap=""> 0.032 width="74" nowrap=""> 0.031 width="55" nowrap=""> 0.045

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 45 width="55" nowrap=""> 0.759 width="74" nowrap=""> 0.814 width="55" nowrap=""> 0.157 width="75" nowrap="" rowspan="2"> 4.458***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 175 width="55" nowrap=""> 0.622 width="74" nowrap=""> 0.640 width="55" nowrap=""> 0.191

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 45 width="55" nowrap=""> 0.871 width="74" nowrap=""> 0.939 width="55" nowrap=""> 0.190 width="75" nowrap="" rowspan="2"> -0.804

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 175 width="55" nowrap=""> 0.898 width="74" nowrap=""> 0.993 width="55" nowrap=""> 0.204

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 45 width="55" nowrap=""> 17.106 width="74" nowrap=""> 17.791 width="55" nowrap=""> 1.582 width="75" nowrap="" rowspan="2"> 14.007***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 175 width="55" nowrap=""> 14.177 width="74" nowrap=""> 14.288 width="55" nowrap=""> 1.152

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 45 width="55" nowrap=""> 0.148 width="74" nowrap=""> 0.062 width="55" nowrap=""> 0.165 width="75" nowrap="" rowspan="2"> -3.250**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 175 width="55" nowrap=""> 0.702 width="74" nowrap=""> 0.393 width="55" nowrap=""> 1.134

Machinery and Other Equipment

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 210 width="55" nowrap=""> 0.021 width="74" nowrap=""> 0.021 width="55" nowrap=""> 0.078 width="75" nowrap="" rowspan="2"> -4.689***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 2500 width="55" nowrap=""> 0.045 width="74" nowrap=""> 0.039 width="55" nowrap=""> 0.071

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 210 width="55" nowrap=""> 0.621 width="74" nowrap=""> 0.647 width="55" nowrap=""> 0.194 width="75" nowrap="" rowspan="2"> 12.667***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 2500 width="55" nowrap=""> 0.430 width="74" nowrap=""> 0.431 width="55" nowrap=""> 0.211

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 210 width="55" nowrap=""> 0.969 width="74" nowrap=""> 0.972 width="55" nowrap=""> 0.021 width="75" nowrap="" rowspan="2"> 6.240***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 2500 width="55" nowrap=""> 0.939 width="74" nowrap=""> 0.959 width="55" nowrap=""> 0.069

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 210 width="55" nowrap=""> 14.532 width="74" nowrap=""> 14.451 width="55" nowrap=""> 1.385 width="75" nowrap="" rowspan="2"> 17.811***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 2500 width="55" nowrap=""> 13.043 width="74" nowrap=""> 12.972 width="55" nowrap=""> 1.143

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 210 width="55" nowrap=""> 0.784 width="74" nowrap=""> 0.452 width="55" nowrap=""> 0.936 width="75" nowrap="" rowspan="2"> -5.903***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 2500 width="55" nowrap=""> 1.500 width="74" nowrap=""> 1.005 width="55" nowrap=""> 1.738

Metals and Metal Products

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 100 width="55" nowrap=""> -0.002 width="74" nowrap=""> 0.006 width="55" nowrap=""> 0.066 width="75" nowrap="" rowspan="2"> -4.613***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 557 width="55" nowrap=""> 0.028 width="74" nowrap=""> 0.026 width="55" nowrap=""> 0.059

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 100 width="55" nowrap=""> 0.621 width="74" nowrap=""> 0.670 width="55" nowrap=""> 0.179 width="75" nowrap="" rowspan="2"> 5.128***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 557 width="55" nowrap=""> 0.506 width="74" nowrap=""> 0.536 width="55" nowrap=""> 0.211

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 100 width="55" nowrap=""> 0.950 width="74" nowrap=""> 0.983 width="55" nowrap=""> 0.083 width="75" nowrap="" rowspan="2"> 1.985*

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 557 width="55" nowrap=""> 0.933 width="74" nowrap=""> 0.957 width="55" nowrap=""> 0.082

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 100 width="55" nowrap=""> 15.297 width="74" nowrap=""> 15.164 width="55" nowrap=""> 1.086 width="75" nowrap="" rowspan="2"> 12.421***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 557 width="55" nowrap=""> 13.530 width="74" nowrap=""> 13.291 width="55" nowrap=""> 1.346

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 100 width="55" nowrap=""> 0.569 width="74" nowrap=""> 0.369 width="55" nowrap=""> 0.627 width="75" nowrap="" rowspan="2"> -3.812***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 557 width="55" nowrap=""> 1.337 width="74" nowrap=""> 0.785 width="55" nowrap=""> 1.994

Services Sector

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 80 width="55" nowrap=""> 0.073 width="74" nowrap=""> 0.065 width="55" nowrap=""> 0.046 width="75" nowrap="" rowspan="2"> 2.865**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 770 width="55" nowrap=""> 0.049 width="74" nowrap=""> 0.041 width="55" nowrap=""> 0.075

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 80 width="55" nowrap=""> 0.527 width="74" nowrap=""> 0.566 width="55" nowrap=""> 0.203 width="75" nowrap="" rowspan="2"> 2.059**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 770 width="55" nowrap=""> 0.470 width="74" nowrap=""> 0.478 width="55" nowrap=""> 0.240

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 80 width="55" nowrap=""> 0.965 width="74" nowrap=""> 0.991 width="55" nowrap=""> 0.046 width="75" nowrap="" rowspan="2"> 2.861**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 770 width="55" nowrap=""> 0.927 width="74" nowrap=""> 0.972 width="55" nowrap=""> 0.117

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 80 width="55" nowrap=""> 14.374 width="74" nowrap=""> 14.166 width="55" nowrap=""> 1.356 width="75" nowrap="" rowspan="2"> 7.164***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 770 width="55" nowrap=""> 13.123 width="74" nowrap=""> 12.881 width="55" nowrap=""> 1.498

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 80 width="55" nowrap=""> 0.985 width="74" nowrap=""> 0.689 width="55" nowrap=""> 0.941 width="75" nowrap="" rowspan="2"> -2.516**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 770 width="55" nowrap=""> 1.851 width="74" nowrap=""> 0.943 width="55" nowrap=""> 3.063

Primary Sector

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 85 width="55" nowrap=""> 0.025 width="74" nowrap=""> 0.025 width="55" nowrap=""> 0.078 width="75" nowrap="" rowspan="2"> 2.988**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 260 width="55" nowrap=""> 0.025 width="74" nowrap=""> 0.025 width="55" nowrap=""> 0.078

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 85 width="55" nowrap=""> 0.555 width="74" nowrap=""> 0.560 width="55" nowrap=""> 0.148 width="75" nowrap="" rowspan="2"> 2.470**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 260 width="55" nowrap=""> 0.494 width="74" nowrap=""> 0.515 width="55" nowrap=""> 0.211

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 85 width="55" nowrap=""> 0.913 width="74" nowrap=""> 0.951 width="55" nowrap=""> 0.085 width="75" nowrap="" rowspan="2"> 0.217

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 260 width="55" nowrap=""> 0.911 width="74" nowrap=""> 0.942 width="55" nowrap=""> 0.101

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 85 width="55" nowrap=""> 15.764 width="74" nowrap=""> 15.304 width="55" nowrap=""> 1.723 width="75" nowrap="" rowspan="2"> 13.238***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 260 width="55" nowrap=""> 13.380 width="74" nowrap=""> 13.224 width="55" nowrap=""> 1.336

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 85 width="55" nowrap=""> 0.544 width="74" nowrap=""> 0.441 width="55" nowrap=""> 0.435 width="75" nowrap="" rowspan="2"> -4.452***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 260 width="55" nowrap=""> 1.504 width="74" nowrap=""> 0.932 width="55" nowrap=""> 1.971

Transport Sector

Variables width="88" nowrap=""> Ownership width="97" nowrap=""> Number of Observations width="55" nowrap=""> Mean width="74" nowrap=""> Median width="55" nowrap=""> SD width="75" nowrap=""> T-stat

ROA width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 65 width="55" nowrap=""> 0.068 width="74" nowrap=""> 0.068 width="55" nowrap=""> 0.050 width="75" nowrap="" rowspan="2"> 2.852**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 245 width="55" nowrap=""> 0.049 width="74" nowrap=""> 0.044 width="55" nowrap=""> 0.046

Leverage width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 65 width="55" nowrap=""> 0.398 width="74" nowrap=""> 0.376 width="55" nowrap=""> 0.190 width="75" nowrap="" rowspan="2"> -3.380***

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 245 width="55" nowrap=""> 0.495 width="74" nowrap=""> 0.496 width="55" nowrap=""> 0.209

Tangibility width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 65 width="55" nowrap=""> 0.956 width="74" nowrap=""> 0.983 width="55" nowrap=""> 0.069 width="75" nowrap="" rowspan="2"> 2.119**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 245 width="55" nowrap=""> 0.920 width="74" nowrap=""> 0.962 width="55" nowrap=""> 0.130

Size width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 65 width="55" nowrap=""> 14.601 width="74" nowrap=""> 14.832 width="55" nowrap=""> 1.449 width="75" nowrap="" rowspan="2"> 2.213**

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 245 width="55" nowrap=""> 14.166 width="74" nowrap=""> 13.939 width="55" nowrap=""> 1.398

Tobin's Q width="88" nowrap="" valign="top"> SOE width="97" nowrap=""> 65 width="55" nowrap=""> 0.850 width="74" nowrap=""> 0.706 width="55" nowrap=""> 0.783 width="75" nowrap="" rowspan="2"> 0.232

width="88" nowrap="" valign="top"> NSOE width="97" nowrap=""> 245 width="55" nowrap=""> 0.889 width="74" nowrap=""> 0.489 width="55" nowrap=""> 1.288

*, ** and *** show significance at 10, 5 and 1 percent levels, respectively.

 

This study employed the estimation technique of Ordinary Least Square (OLS) to investigate the connection between the state control and the firm profitability in listed Chinese firms. All the estimated models in table 2 and 3 are statistically significant with considerable R-squared. The result of F-statistics is statistically significant in the entire models (base model- model 7) and shows that the explanatory variables do determine frim performance. The base model in table 3 shows the result of the full sample. Among the explanatory variables the effect of leverage on firm’s profitability is adverse, whereas in Chinese listed firms, the impact of size and tangibility on the profitability of the company is positive. The effect of state ownership on firm performance is negative and statistically significant. The parameter of state ownership (-0.012), reflects the average impact of state dummy on financial profitability of all the companies operating in different sectors. These results indicate that the overall effect of state ownership on firm performance is negative in China. The results of full sample are in line with the previous findings (Qi et al., 2000; Sun et al., 2002).

Table 3: Estimating the Effect of State Ownership on Financial Performance

> > > > > > > > > > > > > > > > > >

Variables width="96" nowrap=""> Base Model width="124" nowrap=""> Chemical Industry width="106" nowrap=""> Construction width="98" nowrap=""> Machinery Industry

Leverage width="96" nowrap=""> -0.138*** width="124" nowrap=""> -0.178*** width="106" nowrap=""> -0.092*** width="98" nowrap=""> -0.120***

width="96" nowrap=""> (-28.380) width="124" nowrap=""> (-18.580) width="106" nowrap=""> (-4.720) width="98" nowrap=""> (-15.510)

Tangibility width="96" nowrap=""> -0.003 width="124" nowrap=""> 0.023 width="106" nowrap=""> -0.036*** width="98" nowrap=""> 0.002

width="96" nowrap=""> (-0.440) width="124" nowrap=""> (-1.040) width="106" nowrap=""> (-3.470) width="98" nowrap=""> (0.120)

Size width="96" nowrap=""> 0.015*** width="124" nowrap=""> 0.026*** width="106" nowrap=""> 0.005* width="98" nowrap=""> 0.016***

width="96" nowrap=""> (17.190) width="124" nowrap=""> (11.220) width="106" nowrap=""> (2.030) width="98" nowrap=""> (9.100)

Tobin's Q width="96" nowrap=""> 0.002** width="124" nowrap=""> 0.007* width="106" nowrap=""> -0.010*** width="98" nowrap=""> 0.004**

width="96" nowrap=""> (-2.910) width="124" nowrap=""> (2.570) width="106" nowrap=""> (-3.340) width="98" nowrap=""> (2.860)

SOE width="96" nowrap=""> -0.012*** width="124" nowrap=""> -0.008 width="106" nowrap=""> -0.007 width="98" nowrap=""> -0.021***

width="96" nowrap=""> (-4.790) width="124" nowrap=""> (-1.410) width="106" nowrap=""> (-1.140) width="98" nowrap=""> (-4.110)

Fixed Effect

Sector width="96" nowrap=""> 16.320*** width="124" nowrap=""> - width="106" nowrap=""> - width="98" nowrap=""> -

Year width="96" nowrap=""> 61.550*** width="124" nowrap=""> 20.670*** width="106" nowrap=""> 1.980* width="98" nowrap=""> 18.940***

Number of obs. width="96" nowrap=""> 6890 width="124" nowrap=""> 1800 width="106" nowrap=""> 220 width="98" nowrap=""> 2710

F-statistic width="96" nowrap=""> 80.010*** width="124" nowrap=""> 51.160*** width="106" nowrap=""> 10.520*** width="98" nowrap=""> 35.370***

R-squared width="96" nowrap=""> 0.183 width="124" nowrap=""> 0.268 width="106" nowrap=""> 0.32 width="98" nowrap=""> 0.138

Ad. R-squared width="96" nowrap=""> 0.181 width="124" nowrap=""> 0.264 width="106" nowrap=""> 0.291 width="98" nowrap=""> 0.135

RMSE width="96" nowrap=""> 0.064 width="124" nowrap=""> 0.066 width="106" nowrap=""> 0.035 width="98" nowrap=""> 0.066

Table 4. Estimating the Effect of State Ownership on Financial Performance

> > > > > > > > > > > > > > > > > >

Variables width="100" nowrap=""> Metal Products width="100" nowrap=""> Primary Sector width="100" nowrap=""> Services Sector width="100" nowrap=""> Transport

Leverage width="100" nowrap=""> -0.111*** width="100" nowrap=""> -0.129*** width="100" nowrap=""> -0.134*** width="100" nowrap=""> -0.126***

width="100" nowrap=""> (-8.280) width="100" nowrap=""> (-7.870) width="100" nowrap=""> (-6.800) width="100" nowrap=""> (-11.130)

Tangibility width="100" nowrap=""> -0.063* width="100" nowrap=""> 0.003 width="100" nowrap=""> -0.0265 width="100" nowrap=""> -0.01

width="100" nowrap=""> (-2.290) width="100" nowrap=""> (0.220) width="100" nowrap=""> (-0.830) width="100" nowrap=""> (-0.680)

Size width="100" nowrap=""> 0.006** width="100" nowrap=""> 0.014*** width="100" nowrap=""> 0.012*** width="100" nowrap=""> 0.002

width="100" nowrap=""> (2.700) width="100" nowrap=""> (5.470) width="100" nowrap=""> (5.710) width="100" nowrap=""> (1.090)

Tobin's Q width="100" nowrap=""> -0.003 width="100" nowrap=""> 0.003 width="100" nowrap=""> 0.003 width="100" nowrap=""> -0.002

width="100" nowrap=""> (-1.890) width="100" nowrap=""> (0.290) width="100" nowrap=""> (1.570) width="100" nowrap=""> (-0.850)

SOE width="100" nowrap=""> -0.030*** width="100" nowrap=""> 0.013* width="100" nowrap=""> 0.009 width="100" nowrap=""> 0.005

width="100" nowrap=""> (-4.260) width="100" nowrap=""> (2.510) width="100" nowrap=""> (1.200) width="100" nowrap=""> (0.990)

Fixed Effect

Sector width="100" nowrap=""> - width="100" nowrap=""> - width="100" nowrap=""> - width="100" nowrap=""> -

Year width="100" nowrap=""> 8.310*** width="100" nowrap=""> 6.010*** width="100" nowrap=""> 13.790*** width="100" nowrap=""> 1.680

Number of obs. width="100" nowrap=""> 655 width="100" nowrap=""> 850 width="100" nowrap=""> 345 width="100" nowrap=""> 310

F-statistic width="100" nowrap=""> 18.670*** width="100" nowrap=""> 12.470*** width="100" nowrap=""> 13.850*** width="100" nowrap=""> 16.160***

R-squared width="100" nowrap=""> 0.219 width="100" nowrap=""> 0.138 width="100" nowrap=""> 0.288 width="100" nowrap=""> 0.303

Ad. R-squared width="100" nowrap=""> 0.209 width="100" nowrap=""> 0.129 width="100" nowrap=""> 0.269 width="100" nowrap=""> 0.282

RMSE width="100" nowrap=""> 0.054 width="100" nowrap=""> 0.068 width="100" nowrap=""> 0.063 width="100" nowrap=""> 0.04

*, ** and *** show significance at 10, 5 and 1 percent levels, respectively.

 

Model 1-7 shows the effect of state ownership on financial performance of firms across the different sectors in China. The results in table 3 and 4 shows that the effect of leverage on profitability is significantly negative for all selected sectors. These findings suggest that leverage is an important determinant of firm profitability. The effect of tangibility on firm performance is significantly negative in construction and metal product industries. The effect of size on firm performance is positive and significant in all the selected sectors except for transport industry. Growth has a significant and positive effect on firm performance in chemical product and machinery equipment sectors, whereas, in construction sector growth and financial performance are negatively associated. The association between state dummy and firm profitability changes as we run the regression across different sectors. The result shows that coefficient of state dummy has a negative and significant effect on the profitability of the firms in the following sectors; machinery and other equipment and Metals and metal products, while positive in service sector. Whereas there is no significant link between state dummy and company profitability among other sectors. These results indicate that the impact of state control on firm financial performances do vary across companies operating in various sectors.

Conclusion

In this study the effect of ownership on the firm profitability is examined for Chinese listed firms.  This study uses annual data of 143, public and 1,235, private owned enterprises for a period of 2011 to 2015. This study employed the estimation technique of Ordinary Least Square (OLS) to investigate the relationship between state control and firm profitability in listed Chinese firms. The results of whole sample indicate that over all firm performance and state ownership are negatively associated in China. However, the negative connection between state ownership and financial performance changes as we run the regression across different sectors. The result shows that coefficient of state dummy have a significant and negative effect on the performance of the firms in the following sectors; machinery and other equipment and Metals and metal products, while positive in service sector. Whereas among other sector no significant connection between the state’s dummy and firms performance exist. These findings show that the impact of state dummy on financial performance differs across firms operating in different sectors. 

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