China’s Non-Tradable Shares Reform: Ownership Regulations

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Updated: Nov 17th, 2023

Abstract

A lot of concerns have been raised concerning the role that change in regulations has on organizational structure and performance. Such concerns have been instigated by the high demand for organizations to appear relevant in their areas of operations, which calls for the need to have a better understanding of the determinants of financial performance in any organization.

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Although the subject of changes in ownership structure and the effect of various regulations have been studied extensively, few researchers and scholars have focused on the effect of regulations and changes in ownership structure on the financial performance of companies. Also, carrying out an analysis of the issue of corporate regulations and changes in ownership structures has proved to have numerous challenges owing to the rapid transformations within the current business environment due to the presence of extensive privatization processes as well as a high number of negative social phenomena.

As such, the effect of regulations and changes in ownership structures on the general performance of any organization is a subject worth investigating. Therefore, this study analyzed the effect of change in regulation on the ownership structure of listed companies in China, with a special focus on the introduction of the Non-Tradable Shares (NTS) reform in 2005. Thus, the primary focus of this study was on the examination of how the adoption of the NTS reform affected the percentage proportion of ownership structures among Chinese listed companies; a subject that was informed by the fact that there is limited literature in this area.

The study used 142 listed companies in China that had fully completed the reform as the sample for the investigation of the changes in ownership before and after the NTS reform. The investigation of the study phenomenon was considered from 2000 to 2014 to have a clear picture of the effect of the NTS reform on the ownership structures of listed companies in China.

Regression analysis and the OLS model was used to analyze the data collected from the study. Even though the primary variables for the study included the introduction of the NTS reform and the percentage change in private ownership, other control variables such as the size of the firm, age and level of innovation, profitability as well as operating performance were used.

The findings from the study indicated that the introduction of the non-tradable reform had a significant effect on the operating performance of Chinese listed companies such as a rise in the Chinese market during the announcement date. Besides, the reform played a significant role in the privatization process as well as in the improvement of corporate governance in China. On the other hand, analysis based on a dummy year showed a negative reaction at the announcement of the reforms.

Within the event window, the percentage or proportion of shares held by state-owned enterprises was high as compared to other types of ownership structures such as public or institutional enterprises. Despite this, the percentage proportion of shareholding structure of non-tradable shares recorded a significant reduction following the announcement of the NTS reform in China. Resultantly, companies experienced a rise in stock prices. These findings imply that there is a significant relationship between regulation and change in ownership structure in any capital market as evident in the case of China’s NTS reform.

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Methodology and Research Design

Methodology

Research can be defined as a systematic investigation of a studied phenomenon in which data is collected, analysed, and interpreted to understand, predict, and describe a phenomenon (Mertens 2005). This description of the research points to the application of systematic processes that are normally referred to as research methodology. Research methodology involves the practical approaches undertaken to obtain data and analyse it (Creswell 2013). This implies that it encompasses the sampling procedures, collection, and the synthesis of data.

These processes are carried out systematically to find out the rationale for the existence of an issue that is being investigated. It is important to note that different steps can be applied to carry out an investigation. The steps are based on various approaches which are influenced by the philosophical foundation of the study. As a result, Silverman (2006) pointed out that the choice of a study method is normally aligned to the epistemological enquiry of the knowledge being sought.

Epistemology is defined as the knowledge which can be found in the theoretical perspective (Leedy & Ormrod 2005). Therefore, concerning the current issue under investigation, i.e., the regulations and ownership structure of firms in China; the selected methodology should be able to lead to the empirical discovery of correlations between the regulations and ownership structure.

In this case, the focus is on the collection of data about the listed companies in China, which forms the rationale for the use of quantitative methods. The methodology is used as the basis for mapping out the entire process of conducting a study. It is worth emphasising that the selection of the methodology in this study is linked to the philosophical approach that outlines the foundations of this study.

Research design and variables

Research designs are the systems used by a researcher to carry out a study. The common research designs are cross-sectional, case studies, explorative research, and longitudinal designs among others (Bronfenbrenner & Evans 2000; Vandenberg 2007). The research design applied for this study is the cross-sectional study design (Denk 2010; Black 2006). The rationale for the design is that it will provide a snapshot of the ownership structures over the stipulated period and hence, draw correlations based on various regulations at the time.

Also, the cross-sectional research design will help in the collection of substantive empirical data over a given time that can be subjected to statistical analysis. This will be important in providing opportunities to understand the ownership structures of the selected firms in China and hence, form the foundation for drawing inferences. The cross-sectional data to be collected will mainly comprise of the share ownership of the organisations, the period (year), and the trade trends.

This study has both the dependent and independent variables. The Y-variable, in this case, is the percentage of private ownership in Chinese listed companies. The primary objective of having this variable is basically to examine the impact of the Non-Tradable Shares reform on the shareholding structure of private ownership among Chinese listed companies. On the other hand, the study has several x-variables with the primary one being the 2006 NTS reform. However, since the study examines the changes in ownership structure before and after the reform, dummy variables 1 and 0 are considered for years before and years after the reform respectively.

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In this case, the range of the years before the NTS reform is considered between 2000 and 2005, while the range of the years of consideration of the impact of adopting the reform is between 2006 and 2014. Such ranges are suitable in that they cover all aspects of the listed firms examined in terms of their sizes, ages, industry sector as well as their level of innovation both before and after the introduction of the Non-Tradable Shares reform.

For this reason, the study evaluates the impact of the reform on the proportionate percentage of private ownership concerning any noticeable changes in the size of firms, price of stocks, performance and the ratio of tangible assets to the intangible assets between 2001 and 2014. However, the size of the firms, measure of innovation (the fraction of a firm’s intangible fixed assets and total assets) are used in this study due to their potential in influencing ownership among the listed companies of China.

Since the NTS reform begun in 2005, the variables used in this study are considered concerning the end of 2004, unless in the case of dummy variables measured either at t-1 or t+1, whereby t is considered to be the date when the first pilot project was initiated. The ownership structure, in this case, is expressed in terms of Dummy State, SOS, Largest, NCB, LPS, H, Dummy, Concentration, Public and Institution.

The public ownership structure is expressed as the ratio of NTS to TS minus one, and such ratio can be explained in terms of proxy for the Chinese market’s corporate governance, or even the inefficiency of the public sector in corporate governance operations. A high level of Public during the initial stages depicts the availability of positive returns after the announcement of the NTS reforms.

Concentration, on the other hand, is a representation of the analysis of the percentage of shareholders of the tradable shares before the establishment of the NTS reform. Such analysis focuses on establishing the ratio of shareholders of tradable to the shareholders of the non-tradable shares.

The H, the variable is considered to be 1 whenever any given firm under investigation has outstanding H shares and otherwise, 0. LPS represents the proportion of legal person shares and is highly relevant when describing the structure of ownership for the sample. NCB represent the total proportion of shareholders second after the largest while SOS represents the proportion of state-owned shares. Institution refers to the proportion of tradable shares in the possession of institutional investors.

Therefore, the study considers the use of a few market-related characteristics such as the liquidity beta (Beta), which is based on how sensitive the stock’s return is based on the aggregate liquidity stocks, the number of sales, and the value of the market, which is expressed as the product of tradable shares and A-shares. Also, the study makes use of the size of the firm (examined through the investigation of the total debt concerning the total assets of the firm) and the return on sales (ROS) to examine the effects of the NTS reforms on the ownership structure among Chinese listed companies.

Data sampling design

Sampling design

Sampling is the process of obtaining the subjects to be included in a study. Sampling plays a very important role in ensuring that the subjects chosen represent the entire population (Sans 2011). As a result, different procedures are used to select a study sample. The sampling procedure to be used for the present study will be simple random sampling. The random sampling will be used to select the listed companies from which data on ownership will be collected and analysed.

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The rationale for using the simple random is based on the fact that allows equal probability for the inclusion of all units in a study (Weber 2010). In the case of this study, all listed companies in China were considered for inclusion in the sample. This is important because it rules out bias that is associated with non-probability sampling procedures (Mackenzie & Knipe 2006). The simple random sampling will lead to a sample size through procedures that uphold the reliability of the sampling process.

Sampling frame

Sample frame entails all the eligible members of the study population/subjects that meet the criteria for being included in the study (Sans 2011). The sampling frame for this study will be composed of all companies that are eligible for the study. This implies that all the listed companies in China will be included in the sampling frame.

However, parameters for inclusion and exclusion criteria will be provided to ensure that companies selected have the required data for the study. In this case, inclusion criteria will factor companies that have been listed in China’s stock exchange markets. This is in line with the cross-sectional study design for the study, which will cover the period between 2000 and 2014. Therefore, companies that are not within that study bracket will be excluded from the sampling frame. This will provide the rationale for the coming up with the sample size from which data can be extracted.

Sample size

The sample size to be used for the study is anchored on the selected study period. According to the initial inclusion criteria, the selected sample contained 192 firms as showed in table 1, which shows that the sample contained firms from different industries. However, to effectively examine the effects of the NTS reform, it was recommendable to base analysis on one industry. Given that most of the firms were in the industrial sector, the study used a sample size of 142 firms as shown in table 2 in the appendices section.

Methods of Data Collection

The method of data collection used for any study is dictated by the type of data to be gathered, construct that is to be measured and the point of collection (Dhanaraj 2006; Mackenzie & Knipe 2006). This will be done bearing in mind that there are varied methods of data collection that can be used to obtain data. For quantitative research strategies as in the current study, the data collection can either be done through observation technique or data mining from the identified companies.

The observation technique relates to primary sources of data while the data mining is a secondary approach in which already recoded data is analysed to gain insights based on the study objectives (Barroso, Gollop & Sandelowski 2003). In this study, secondary sources of data will be used in which data will be mined from the 142 selected companies.

Data sources

The study is focused on the examination of the correlation between regulation and change in ownership structure in the Chinese context. The validity and reliability of data sources is a very important aspect of any research work (Neumann 2007; Dixon-Woods et al. 2005). For this reason, there was a need to ensure that all the sources used for the collection of data on Chinese NTS reforms were reliable and credible. Obtaining effective and accurate data and information is a vital concern in any study.

Researchers can choose to use either secondary sources of data or the primary ones. The secondary data refers to the information collected by other researchers for purposes that can be different from the primary researcher’s, and such information is available in books, journals, websites and other online databases (Mitchell & Jolly 2010). The primary data, on the other hand, refers to the original data collected by researchers themselves based on the research questions at hand (Foster & Yavorsky 2006). As such, the primary data can be considered to be first-hand information about a given phenomenon under study.

The data used in this research is mainly collected from secondary sources. Credibility and reliability of the collected data were achieved in that all the data used in the study was based on book values disclosed at the end of the fiscal year by Chinese listed companies. Since there are numerous listed companies in China, there was a need for effective refinement to ensure that the right sample size was reached. With the target being the listed companies in China between 2001 and 2014, the study selected 142 companies that qualified the inclusion criteria. For a company to be considered in the study sample, it had to meet the following requirements:

First, the selection of the companies to get information from was based on the hypothesis formulated above. The context of the current study is to develop knowledge about regulations and ownership structure of firms in China. The key focus is listed firms; hence, empirical data on ownership in terms of share capital and trade movements can be obtained.

Furthermore, there are already laid down regulations about the ownership of firms in China by both the locals and foreigners (Wang & Deng 2006; Yeung 2009). As such, the included companies had to be defined in terms of Chinese A-share listed industrial companies in Shanghai stock markets from the CSMAR and China Securities Regulatory Commission website.

Secondly, the listed companies included ought to have complied with the reform issued in 2005 and hence, have the continuity annual reports. On the other hand, the availability of abnormal values was a factor of consideration in this study. As such, to avoid the presence of an abnormal value, companies whose names begun with “*ST”,” ST”,” PT” were excluded from the sample.

The inclusion criteria factored in the significance of the validity of collected data. For this reason, for a company to be included in the sample of the study, its reform project must have been passed.

Validity and Reliability

In any research, reliability and validity are important concepts that are used by researchers to gauge the acceptability of the study. Reliability deals with the quality of measures used in the study, i.e. the ability of the ‘repeatability’ of results in case the same study procedures are applied by another researcher. Thus, it concerns itself with the extent to which consistent results can be obtained from the research if repeated over time (Oladipo, Adenaike & Ojewumi 2010).

Golafshani (2003) pointed out that reliability denotes whether the data obtained meets the set standards for systematic scientific research. In the current quantitative study, reliability is based on the sample size and the type of data that is collected from the listed companies. As a result, data from companies that are not listed will affect the reliability of the data and the entire study.

On the other hand, validity is the appropriateness of the research design (Golafshani 2003). This factors in the application of the right method of data collection, right sources of data so that a study can be termed as being appropriate. For the present study, validity is pegged on the entire study methodology, i.e. research design, sampling design and data collection procedures.

Summary

From the chapter, it has been established that the research philosophy that will use in the study is the positivism paradigm, while the research design to be used will be the cross-sectional study design. The sampling process suitable for the research is a simple random sampling from which a suitable sample size will be selected. Also, the data to be used will be secondary data collected by data mining from the relevant databases. As a result, the chapter provides the basis for the discovery of knowledge concerning the relationship between change in regulation and its effect on the ownership structure in the case of China.

Data analysis, Results and Findings

LR hypothesis contribution

This section of the paper provides the analysis of the collected data, the results and findings from the analysis. The primary objective of this study was to examine the concept of regulation and change in ownership structure concerning the context of China. Thus, the study sought to prove the following hypothesis:

H0: The introduction of the non-tradable share reform is more likely to positively affect the operating performance of listed companies in China.

H1: The prices of the stocks that have a high possibility of benefiting from the NTS reform rise following its announcement.

H2: The introduction of the NTS reform has a diverse impact on the ownership identify of listed firms in China.

Based on the above hypotheses, the study aimed at exploring the effects brought about by the announcement of the NTS reform within the stock market of China. As such, to achieve the objectives of the study, the paper analyzes the performance and the concentration of selected listed firms before and after the reform.

Results

In contemporary times, data is stored in raw form; this implies that information is placed in databases when not synthesised. Therefore, the fact that the secondary data was collected for this study does not signify that it was ready for drawing inferences. It is important to analyse the data to provide answers to the study questions and achieve the study objectives.

Data analysis is defined as the systematic process of synthesising information by the application of techniques to make it possible to make generalities that relate to the objectives of any given study (Creswell 2013). Besides, there are different methods of analysing data collected in a study. In statistical processes, there are tools of data analysis that have been developed to help in the synthesis of data and the subsequent drawing of correlations. Examples of such tools include software such as SPSS, e-views, and advanced spreadsheet applications.

In quantitative studies, these applications are used to test hypotheses by use of mean, standard deviations, t-tests and other factors for drawing correlations. It is important to note that the type of data analysis is normally linked to the research method selected for any given study. In the current quantitative study, the analysis was carried out by the use of regression analysis and MS Excel sheets.

The sample comprised of 142 companies that qualified the inclusion criteria. The analysis of the collected data for this study is done through the use of the OLS model and regression analysis. The analysis focused on the changes expected on the performance of firms following the establishment of the non-tradable shares reforms in 2005. Such changes were assessed through the profitability of the listed firms, leverage changes, output, stock prices and operating efficiency changes.

Change in ownership structure

The study considered the proportion of tradable shares before the NTS reform to compare with tradable shares’ proportion after the introduction of the reform. The table below shows the proportion percentage of tradable shares in China before the NTS reform.

yearTradable Shares (TS)Negotiable A SharesNumber of Negotiable B SharesNumber of Negotiable H SharesOther Overseas Negotiable Shares
200135%25%3%6%0%
200235%26%3%6%0%
200335%27%3%6%0%
200436%28%3%6%0%

The table below shows the descriptive statistics of the percentage proportion of tradable shares ownership in China before the introduction of the NTS reform

yearTradable Shares (TS)Negotiable A SharesNo. of Negotiable B SharesNumber of Negotiable H SharesOther Negotiable Shares
Mean2002.50.35250.2650.030.060
Standard Error0.6454970.00250.006455000
Median2002.50.350.2650.030.060
Mode#N/A0.35#N/A0.030.060
Standard Deviation1.2909940.0050.01291000
Sample Variance1.6666670.0000250.000167000
Kurtosis-1.24-1.2#DIV/0!#DIV/0!#DIV/0!
Skewness020#DIV/0!#DIV/0!#DIV/0!
Range30.010.03000
Minimum20010.350.250.030.060
Maximum20040.360.280.030.060
Sum80101.411.060.120.240
Count444444

On the other hand, the percentage proportion of non-tradable shares in China’s listed companies before the NTS reform was also examined. The findings from the analysis are showed in the table below, which provides a summary of the percentage proportion of non-tradable shares in China between 2000 and 2005.

Year200020012002200320042005
Non-Tradable SharesState-owned38.91%46.2%47.3%47.4%46.9%45.0%
Sponsor’s16.94%12.7%11.3%10.9%10.6%7.2%
Foreign-owned1.23%0.90%0.91%0.92%0.97%2.96%
Privately- owned5.64%4.6%5.0%4.81%4.82%3.98%
Employee0.63%0.45%0.28%0.18%0.12%0.05%
Others0.93%0.32%0.56%0.54%0.66%3.77%
Total64.28%65.17%65.35%64.45%63.95%62.91%

The shareholding structure of Chinese listed companies before NTS reform (2000-2005)

According to the table above, it is evident that the percentage shareholding structure of Chinese listed companies changed significantly concerning various shares and years before the introduction of the NTS reform. For example, the percentage number of state-owned enterprises showed an increasing trend from 2000 towards 2005. However, the percentage proportion of state-owned shares decreased from 46.9% in 2004 to 45.0% in 2005. The table below shows the descriptive statistics of the non-tradable shares in China before the NTS reform.

state-ownedsponsoredForeign-ownedPrivately- ownedEmployee
Mean0.1071333330.10861670.1089166670.1079166670.106783333
Standard Error0.0618299530.0732610.0748204450.0750803140.074216631
Median0.034350.02750.029550.028650.02895
Mode­-
Standard Deviation0.1514518360.17945190.1832719120.183908460.181792876
Sample Variance0.0229376590.0322030.0335885940.0338223220.03304865
Kurtosis2.5557439334.51623834.87072844.9514634264.990947184
Skewness1.7024572732.10779922.1815816582.1999095972.208279053
Range0.38280.45880.47020.47220.4678
Minimum0.00630.00320.00280.00180.0012
Maximum0.38910.4620.4730.4740.469
Sum0.64280.65170.65350.64750.6407

The study analyzed the changes in ownership structure by examining the transition between 2005 and 2006 following the introduction of the NTS reform. According to the analysis, the study found out that the total number of shares changed significantly between 2005 and 2006, as various listed firms struggled to adhere to the requirements of the reform. As evident from the descriptive statistics’ table below, the total number of shares for all the listed companies examined was high in 2006 as compared to the case in 2005. Also, a significant decrease in the number of non-tradable shares was evident in 2006 concerning the case in 2005.

yearmeanMaxminStd. Dev
Total Number of Shares20056.43E+081.75E+10650000001.89E+09
20067.27E+081.75E+10755000001.95E+09
number of non-tradable shares20053.96E+081.28E+10325000001.37E+09
20064.23E+081.28E+10289087501.41E+09
state-owned shares20053.18E+081.28E+1001.38E+09
20063.54E+081.28E+1001.43E+09
legal person shares2005638915056.61E+08094524949
2006542178425.32E+08079664809
tradable shares20052.47E+084.73E+09312000005.31E+08
20063.04E+084.74E+09395323755.62E+08
% OF PS20050.2309420.81192600.257166
20060.2174380.81184300.247411
% OF PL20050.2378150.67068900.226388
20060.1899830.76978900.20733
% OF TS20050.4575510.8779510.1880740.114402
20060.5263260.8779510.1881570.136429
% OF NTS20050.5424490.8119260.1220490.114402
20060.4736740.8118430.1220490.136429

Descriptive Statistics of ownership structure in 2005 and 2006

The study examined the size (FIRMSIZE), a measure of innovation (INFA/FA) and the age of the firms based on the year of incorporation and the current year under examination, 2014. The table below shows the descriptive statistics on Age, INFA/FA and size of the firm. According to the study sample used, most of the firms had 13 years of operation since their incorporation, as shown in the table of descriptive statistics on Age, INFA/FA and size of the firm below.

AGEINFA/FAFIRMSIZE
Mean16.464790.26168921.81523
Median160.10043121.70455
Mode13n/an/a
Standard Deviation3.295521.8074531.236141
Sample Variance10.86045n/an/a
Kurtosis1.063498596.91123.819311
Skewness1.05729823.697960.590397
Minimum120.00000017.91741
Maximum2952.0120326.75123
Sum2338640.353453381.87
Count142142142

The descriptive statistics of the tradable shares, non-tradable shares, PS and PL are shown below.

__OF_NTS__OF_PL__OF_PS__OF_TS
Mean0.3314480.1337550.1610470.668552
Median0.3269340.0000000.0000000.673066
Maximum0.8874150.8560790.8499841.000000
Minimum0.0000000.0000000.0000000.112585
Std. Dev.0.2731110.2084720.2452120.273111
Skewness0.0790931.4807251.203426-0.079093
Kurtosis1.5284593.9660542.9302601.528459
Sum816.0258329.3055396.49771645.974
Sum Sq. Dev.183.5648106.9563147.9768183.5648
Observations2462246224622462

Correlation, OLS and regression analysis

Empirical evidence indicates that the adoption of the NTS reform had a significant influence on the performance of firms in China and subsequently on their structure (Hung, Chen & Fang 2015; Petit-Konczyk 2010). As such, this study was entirely focused on the examination of the control variables such as the operating efficiency of listed firms in China, as well as their level of output and profit margins following the announcement of the NTS reform and established that there was a significant improvement in these aspects of the listed firms. Therefore, for the reliability of such findings, the study used the selected firms to confirm whether or not there was any significant impact of the NTS reform on ownership structure and performance by examining various profitability ratios after NTS reform.

The following model was used to examine the impact of reform on Non-Tradable Shares in Chinese listed companies’ structure as well as their productivity.

PPit = αit + β1DummYrit + β2SIZEit + β3LEVEit + εit,

Whereby, PP stands for the measures of performance such as the EBITS and ROS; DummYr is the dummy variable which is considered at either zero or one; the SIZE takes care of the cumulative assets; LEVE refers to the leverage expressed as a fraction of the debit total and the total assets. The descriptive statistics from the regression analysis are shown below.

ROSEBITS
DummYr0.090240.0916
SIZE0.04830.0616
LEVE-0.2554-0.3390
R20.12090.1604

According to the table above, it was evident that the coefficients of DummYr for ROS and EBITS are significantly positive. The control variables used in this case, such as the size of the firms indicate a significant and positive impact on the performance ratios, although the LEVE variable highlights a negative impact on the performance ratios. On the other hand, the study controls for the age, firm size and the level of innovation, using the following model:

Yi=C + ai (dummy) + bi (AGE) + ci (FIRMSIZE) + di (INFA/FA)

The model was varied using i, whereby i=1, 2, 3 and 4 to have Y1 as the percentage of non-tradable share in total shares; Y2, the percentage of state-owned share in total shares; Y3 as the percentage of legal person shares in the total shares, and Y4 as the percentage of tradable shares in total shares. The table below shows the results of the analysis.

__OF_NTS__OF_PL__OF_PS__OF_TSDummy_Reform_Firm sizeAgeINFA_FA
__OF_NTS1.000.500.61-1.00-0.73-0.29-0.580.00
__OF_PL0.501.00-0.29-0.50-0.42-0.35-0.27-0.03
__OF_PS0.61-0.291.00-0.61-0.430.04-0.340.01
__OF_TS-1.00-0.50-0.611.000.730.290.580.00
Dummy_ReForm_-0.73-0.42-0.430.731.000.380.580.01
Firm size-0.29-0.350.040.290.381.000.350.02
Age-0.58-0.27-0.340.580.580.351.000.05
INFA_FA0.00-0.030.010.000.010.020.051.00

The analysis shows that changing the structure of ownership of listed firms in China positively affected the legal person shares’ EBITS as well as the Return on Sales. On the other hand, the study noted that the NTS reform which brought a change in the ownership concentration negatively affected the EBITS of the listed firms. On the other hand, the EBITS and the Return on Sales have a negative correlation concerning the tradable A-shares. The implication is that the reform on the non-tradable shares in China led to rapid growth in the control of tradable share, which led to a decrease in the profit margins of listed firms in China.

Discussions of Findings

Introduction

The primary objective of this study was to examine the state of regulation and the change of ownership structure in the context of Chinese listed companies. As such, a lot of emphases was given on the examination of the impacts of the Non-Tradable Shares reform that was initiated in 2005.

According to the scope and the objectives of the study, there is a need for valuable data from credible sources. As noted earlier, to examine the subject of regulation and change in ownership structure in China, the study used secondary sources of data that are credible such as Chinese databases on the corporate market.

As such, various data sources were visited such as the sites containing Chinese stock market details like listed companies, data on ownership structures in China, as well as the available regulations and factors that influence ownership structure in the country. However, this section of the dissertation provides an in-depth discussion of the results and findings of the study

Basic information analysis about China stock market

China has a complex capital structure (Alves & Mendes 2004; Bhagat & Bolton 2010). Despite this, various changes such as the NTS reform have seemed to bring some order into the capital market structure as well as the shareholding structure in the country (Apostolov 2010; Blair & Hite 2005). Initially, China had a very small number of shares as well as the total equity (He, Zhang & Han 2009; Eun-Young 2008).

Nevertheless, the stock market of China has experienced rapid development between 1997 and 2014 (Barontini & Bozzi 2009; Boccia 2013). This can be inferred from the growth in the number of listed companies in China between 1997 and 2014. For example, the Chinese stock market had more than 2656 listed companies and total equity of more than CNY 4400 billion (Blajer-Gołębiewska 2010).

Important characteristics

To ascertain the impact of the NTS reform, this study examined the effects brought about in China in terms of volume and prices following the announcement of the Non-Tradable Shares reforms. Such examination focuses on explaining the rate of abnormal returns experienced during the period based on the measured characteristics before the stated period. Therefore, there is a need to examine the market data from the stock exchange of Shenzhen and Shanghai to understand the shareholding structure and governance according to the CSMAR database.

There were four companies at the start of the NTS reform in 2005 and these included the Sany Heavy Industry, Shanghai Zi Jiang Enterprise Group, Hebei Jinniu Energy Resources and the Tsinghua Tongfang (Chen et al. 2013; Chen, Démurger & Fournier 2005). More than 1300 companies had joined the NTS reforms by 2007, of which 98% were listed (Lakshmi 2010). As pointed out earlier, working with such a large sample can be cumbersome and even lead to a lot of errors. For this reason, the study applied the inclusion and exclusion criteria as well as the convenient sampling technique to reach a sample size of 142 companies.

Findings

The study examined the percentage proportion of tradable and non-tradable shares among the listed companies in China between 2001 and 2014. Such analysis was aimed at finding whether or not there was any change in the number of shares following the introduction of the Non-Tradable Shares reform in 2006.

As evident from above, the number of non-tradable shares in China shows a decreasing trend from 2000 towards 2005 for the cases of the sponsor’s companies, and the employees. Such a decrease is also noticed when examining the trend in total non-tradable shares from 2000 to 2014. The data shows an increase in the percentage proportion of non-tradable shares between 2000 and 2001 (6.28% to 65.17%), before a decrease within the following years.

Based on the data on the table showing the proportion of capital stock structure for tradable shares of listed companies in China, it is evident that the ownership structure in Chinese listed companies is complicated and the negotiability is bad. Such findings align with China’s capital market history (Chidambaran, Palia & Zheng 2011; Cuomo, Zattoni & Valentini 2012; Deakin 2010).

The ownership structure for the listed companies in China has remained to show complex trends since 1997 (Ding 2010; Guo & Keown 2009). The ownership property is divided into state shares, legal person’s shares and individual shares, the state shares and the legal person’s shares could not be tradable (Gatti 2009; Fracassi & Tate 2012).

If the ownership structure can be considered in terms of negotiability, it would be tradable shares and non-tradable shares. The non-tradable include state shares, the legal person’s shares (Domestic Promoter’s Legal Person Shares, Foreign Promoter’s Legal Person Shares, and Raised Legal Person Shares) and employee Shares. The tradable include Negotiable A-shares, number of negotiable B shares, number of negotiable H shares, and other overseas negotiable shares.

As evident from the above, the proportion of state shares and the legal person’s shares in China is quite high. Additionally, these two types of shares are non-tradable. The implication from such a situation is that the majority of companies’ control rights belong to the large shareholders (Gorga 2013; Ishikawa, Sugita & Zhao 2009). For this reason, according to Haque (2010) and Lee (2015), the floating stockholders do not affect the corporate governance, as usual, implying that the stock market cannot reflect the corporate performance. This situation was very instrumental in the emergence of the non-tradable reform.

Additionally, Kohlbacher and Gruenwald (2011) noted that the ownership structure in China is highly centralized. For example, before the establishment of the non-tradable shares reform, there were nearly more than 1000 companies whose control right belonged to the state, accounting for about 65% of the total percentage of listed companies in China (Kumar & Zattoni 2015; Tan 2011).

On the other hand, an examination of the shareholding structure of the non-tradable shares in China reveals that the proportion of non-tradable shares in China was high before 2006 with most of the shareholding coming from the state (Liu 2008; Liu & Magnan 2011). For this reason, it suffices that the majority of the listed companies in China are owned by the state.

A review of the changes in the percentage proportion of the non-tradable shares in China shows an inclining trend from 2001 towards 2006 (Lejenas & Rodhe 2007). However, the proportion shareholding structure shows a decrease starting 2004 onwards, which can be attributed to the introduction of the NTS reform in 2005 (Magdaléna 2008).

As evident from the analysis, the proportion of the tradable shares is 53% in 2006 which is higher than in the case of 2005. On the other hand, the proportion of the state-owned shares is 21.7%, a value that is lower than during 2005. However, an examination of the maximum and minimum value reveals a maximum value of 81% and a minimum of 0%. Such a scenario presents a large standard deviation implying that during the reform period, there was a large difference in the proportion of state shareholding structure.

Using the regression equation, the study analyzed the relationship between the ownership structure and the non-tradable reform, firm size, firm age, and intangible fixed assets divided fixed assets. It is hypothesized that the construction model is as follows:

Yi=C + ai (dummy) + bi (AGE) + ci (FIRMSIZE) + di (INFA/FA), Where i represents the percentage of non-tradable share in total shares, percentage of state-own share in total shares, percentage of legal person shares in the total shares and percentage of tradable shares in total shares.

On the other hand, the impact of the reform process was also examined through an analysis of the prices of shares. The study examined prices around the announcement date (to) and dummy variables (before and announcement). The initial pilot projects were complete by the end of August 2005.

The completion of the trial projects was followed by the expression of the Chinese government regarding the extension of the NTS reforms to feature other stock markets and companies. A change in the price of stocks affects dividends of the affected company in the future. Such a change results in a robust reaction towards improving the necessary fundamentals. Therefore, a small difference is noticed when the price changes at date t1 as compared to the change at date t0-1.

However, according to the review of literature, the Chinese context of price discovery is quite different from numerous other cases as it does not guarantee a linear process at all the time. Nakhla (2015) observed that there was a decline in SSE’s composite index in 2005 notably from 1,169 to 1,013, which was attributable to the government’s announcement of the NTS reform extension.

Even though at the announcement date of the reform, a negative reaction was experienced, a 3% rise was reported a few weeks following a session of fallen stock prices. Despite this, there was a loss of 10% in the market according to market reports featuring transactions in June and July (Mallin 2012; Tan & Yu 2011). Nonetheless, a 1.5 per cent increase in the market was reported on the last day of the pilot project of the non-tradable share reform before it could be extended to include other companies in China (Tan 2011).

Such findings explain the uncertainty of the price discovery process in China, which aligns with the findings from the analysis of the percentage proportion of shareholding structure in Chinese listed companies. According to the analysis above, the percentage of state-owned shareholders in China was very high between 2001 and 2005, before the establishment of the NTS reform as compared in the case from 2006 onwards (Nathan 2011).

Similarly, the analysis of the cumulative abnormal returns for the selected sample can be used to show the effects of the change in ownership structure following the NTS reform. The analysis features the cumulative abnormal returns before and after the announcement of the reform. The results of this analysis revealed 1% CAR based on analysis one day before the announcement date. According to the review of the literature, such findings are suggestive of leakages in information regarding the announcement of the NTS reform (Nietsch 2005; Pindado 2011).

Analysis that featured a day after the announcement of the reform found out that stakeholders experienced CAR of 2.6%, and increased as days progressed. However, the examination of the cumulative abnormal returns taking into consideration the shareholders’ date of the meeting and the issuance of bonus shares revealed a significant drop in the average prices.

It is evident in this case that the increase in the prices is temporarily not affected by movements in the market or even compensation of tradable shareholders by the non-tradable shareholders in terms of bonus shares (Salleh, Ahmad & Kumar 2009). If assessed 10 days later, the analysis would reveal a significant drop in the prices.

Also, the examination of the returns based on variables such as turnover, ROS, leverage, volatility and spread reveals that a negative correlation in the case of ROS, turnover, sales and institution (Shafiqul-Huque 2011; Sliwka 2009; Valadares & Leal 2008). On the other hand, the leverage, volatility and spread depict a positive correlation. While such correlations can be used to explain the impact of the NTS reform on ownership structure, it is important to consider that they can be influenced by other variables such as the type of ownership and the size of the firm (Snopko 2012; Wang 2009).

As evident in the case of time-series analysis, the negative reaction following the announcement of the NTS reform was attributable to concerns regarding the credibility of public firms (Tan & Yu 2011; Rakowska, Valdes-Conca & de Juana-Espinosa 2015). Besides, a lot of concerns were raised over leakages of information on the announcement of the reform.

The introduction of the non-tradable shares reform had various impacts on the capital market of China in terms of change in ownership structure and regulation (Teimoury, Fesharaki & Bazyar 2011). For example, according to the analysis of the effects of the reforms on prices of stocks, the study found out that the NTS reform was instrumental for changes in the ownership structure in the future though it did not instantly affect the firms’ ownership structure (Wei 2007).

This is attributable to the fact that the reform set up conditions for improved profitability of firms by providing grounds for a change in corporate governance, liquidity and ownership of the firms (Weiss & Nikitin 2010). In any market that is forward-looking in terms of stocks, it is expected that there would be immediate changes in the market fundamentals (Welch 2008; Wen 2011; Witzky 2010). As evident from the findings, the reaction of the Chinese investors to the announcement of the NTS reforms was based on consideration of the future. However, the reaction was specific for various event windows.

Conclusion and Recommendations

Conclusion

The capital market of China has been very instrumental in the growth and development of the economy of China. Empirical results show that the corporate governance of any country is founded on the ownership structure (Ye 2012). For this reason, various corporate organizations are based on the difference in ownership structures and thus, the ownership structure is very instrumental in the behaviour and performance of various corporations.

The introduction of the regulatory authority in China has helped organizations to define their limits; a move that has contributed immensely to the growth of China’s capital market and economy (Yu 2012). However, this has been possible following several reforms in the country including the Non-Tradable Share (NTS) reform.

Secondary data entails the use of secondary sources to gather relevant information. This implies that data being sought is already collected and stored. Secondary data is easy to use due to the fact many companies have data stores. Therefore, in the current study, authorisation was sought from the relevant personnel from the selected companies to give access to their databases for data on Chinese listed companies.

It is from the databases that data that is relevant for the research was mined. The relevance of the data was based on the time frame for the study and specific information that was being sought. The secondary data was paramount in providing the basis for drawing comparisons concerning the ownership structure of the firms listed in China and the regulations that relate to the ownership.

The secondary data on ownership structure was collected from the databases of the selected 142 companies. The data collected entailed the share ownership, the years, and the trading trends, and was then compared and contrasted with the existing regulations at the time. It is important to note that listed companies’ data can be obtained from the various stock markets databases. This made it easy to obtain the data as it is not confined as a private asset.

The use of the right sources of data is very important in achieving the reliability and validity of any information used in a study. This assertion explains why it is often very important to use appropriate methods of data collection in any study. In the case of the current study, there were several problems encountered during the collection of the required information.

First, China has numerous companies listed in the stock exchange of Hong Kong, Shenzhen or Shanghai (Cheng, Fung & Leung 2009). For this reason, it was hard to decide which companies and types of data to use in the study. However, this challenge was tackled through the adoption of inclusion and exclusion criteria. Secondly, the specific data required in this study was scarce since there are limited studies in China that have sought to explain the correlation between the NTS reform and the ownership structure.

The findings from the review of the literature have revealed that there was a high level of dominance of state-owned enterprises in China in the eighties. However, such a situation changed following the establishment of the main stock exchanges in China in the early nineties. Despite this, the state was responsible for the control of China’s capital market structure since most of the firms in China had a strange structure. For this reason, almost 67% of the stock market of China in 2005 was majorly filled by non-tradable shares.

From the foregoing analysis, it can be concluded that the establishment of the non-tradable reform within the Chinese capital market significantly affected the operating performance of many companies when assessed over a long-term. According to the analysis, it was evident that the reforms led to a rise in the Chinese stock market prices during the announcement date. Consequently, other factors that are closely related to the market portfolio such as the size of the firms, the governance structure and liquidity were equally affected and coherently responded.

Secondly, the initial project on the non-tradable shares, which is considered to have set up the pathway towards privatization as well as led to an improvement in the corporate governance, has been very instrumental in the explanation of the reaction of the reforms in terms of stock returns for various companies.

The study found out that there was a negative reaction at the announcement of the reforms, which was largely attributed to a lack of clarity in the directionality of the NTS reforms. The negative reaction was justified as many investors needed to understand the effects that the change in the non-tradable shares would have in the long run on the performance of companies.

Thirdly, the study discovered that within the event window the percentage of the shareholding structure was adversely affected by the announcement of the reform. The analysis showed that before the reform was announced the percentage proportion of shares held by state-owned enterprises was high as compared to other types of ownership structures such as public or institutional enterprises.

However, the percentage proportion of shareholding structure of non-tradable shares significantly reduced after the announcement of the NTS reform. On the other hand, the changes in the stock prices explained the transition of most companies in line with the provisions of the NTS reform. Such a scenario can be explained further by the reduction in the composite index of the SSE in 2005.

The review of literature on the price discovery in China indicated that the process is quite complex and it does not show linearity (Inoue 2009). Analysis of the operational performance of companies showed that the NTS reforms had a significant impact on Chinese listed companies. Such conclusion stems from the fact that based on long-term assessment, stakeholders experienced significantly positive cumulative abnormal returns (Cai, Li & Zhang 2010).

Therefore, considering the hypothesis of the study, it was evident that the introduction of the non-tradable share reform led to a decrease in the component of non-tradable shares, while at the same time, the prices of the stocks had a high possibility of benefiting from the NTS reform following its announcement. As such, all the hypotheses were proved and thus, there is a significant relationship between regulation and change in ownership structure in any capital market as evident in the case of China’s NTS reform.

Recommendations

The study on the impacts of the non-tradable shares reform has opened avenues for the need for more studies that can explain the subject further. For example, there is a need for future studies to focus on the aftermath of the reforms as far as the governance of corporations is concerned. The review of literature has indicated that the availability of related party transactions is very important concerning corporate governance (Allen & Qian 2006).

This is based on the fact that the open market sale of stocks especially by individuals holding non-tradable shares can probably lead to considerable change in the ownership structure within the market thereby, affecting the culture of corporate governance. As such, this study recommends more studies on the activism of shareholders, as well as the effect that such activism has on the operational performance of companies. Such studies can adequately provide insights regarding the aspect of dynamic change in internal mechanisms in the case of corporate governance to protect the interests of investors.

On the other hand, based on the objectives and the findings of the study, the success and growth of China’s capital market is tied up to continuous reforms in the regulation and ownership structure. For this reason, this study recommends more amendments to the stock market of China that are aimed at ensuring that there are avenues for equity financing to the majority of the companies in the country based on a wider range. Also, more reforms towards decreasing the intervention of the government on the general performance of firms would lead to strong asset pricing in the country.

Additionally, the examination of the effects of the compensation of the non-tradable shares among companies forms an important aspect for future research. This is based on the fact that the announcement of the NTS reform resulted in actions aimed at compensating firms that were affected by the reform through bonus shares. While empirical literature shows that there was no major role played by such compensation as far as the explanation of the changes in abnormal returns of the companies is concerned, exploration of this element in the future is more likely to offer clear insights into the significance of such compensation.

Lastly, the study recommends the use of a large sample size other than the one used in this study. This is attributable to the fact that a large sample size would give a clear picture of the state of affairs in the Chinese corporate market as far as the effects of the non-tradable shares reforms are concerned. Moreover, a large sample size is effective in achieving the precision and accuracy of information used in a study (Kothari 2005; Denzin & Lincoln 2008).

For more effective results and findings, future studies ought to consider a precise event window, perhaps the examination of the state of affairs in China’s capital market ten years before the establishment of the NTS reform and ten years after. Such a length of time would depict clear effects of the change in regulation and ownership structure.

References

Allen, F & Qian, M 2006, ‘Comparing China’s Financial System’, China Journal of Finance, vol. 1, no. 1, pp. 1-28

Alves, C & Mendes, V 2004, ‘Corporate Governance Policy and Company Performance: the Portuguese case’, Corporate Governance, vol. 12, no. 3, pp. 290-301.

Apostolov, M 2010, ‘Ownership and Control Structures: A Case Study’, Economics Research Journal, vol.1, no. 1, pp. 8-71.

Barontini, R & Bozzi, S 2009, ‘Executive Compensation and Ownership Structure: Empirical Evidence for Italian Listed Companies’, SSRN Electronic Journal.

Barroso, J, Gollop, C & Sandelowski, M 2003, ‘The challenges of searching for and retrieving qualitative studies’, Western Journal of Nursing Research, vol. 25, no. 2, pp. 153-178.

Bhagat, S & Bolton, B 2010, ‘Corporate Governance and Company Performance. SSRN Electronic Journal, vol. 1, no. 1, pp. 109-143.

Black, I 2006, ‘The presentation of interpretivist research’, Qualitative Market Research: An International Journal, vol. 9, no. 4, pp. 319-324.

Blair, B & Hite, D 2005, ‘The Impact of Environmental Regulations on the Industry Structure of Landfills’, Growth And Change, vol. 36, no. 4, pp. 529-550.

Blajer-Gołębiewska, A 2010, ‘The Ownership Structure and the Performance of the Polish Stock Listed Companies’, JOIS, vol. 3, no. 1, pp. 18-27.

Boccia, M 2013, ‘Social Business by Design: Transformative Social Media Strategies for the Connected Company’, Performance Improvement, vol. 52, no. 4, pp. 53-55.

Bronfenbrenner, U and Evans, G. 2000, ‘Developmental science in the 21st Century: Emerging questions, theoretical models, research designs and empirical findings’, Social Development, vol. 9, no. 1, pp.115-125.

Cai, J, Li, Y & Zhang, S 2010, ‘What Will Privatization Bring: The Non-Tradable Share Issue Reform in China’, SSRN Electronic Journal.

Chen, L, Wei, L, Qiao, Z & He, Y 2013, ‘Research on Relationship between Control Transfer, Ownership Structure and Company’s Performance: Evidence from Domestic Listed Companies’, IBR, vol. 6, no. 6, pp. 1-66.

Chen, Y, Démurger, S & Fournier, M 2005, ‘Earnings Differentials and Ownership Structure in Chinese Enterprises’, Economic Development and Cultural Change, vol. 53, no. 4, pp.933-958.

Cheng, L, Fung, H & Leung, T 2009, ‘Dividend preference of tradable-share and non-tradable-shareholders in Mainland China’, Accounting & Finance, vol. 49, no. 2, pp. 291-316.

Chidambaran, N, Palia, D & Zheng, Y 2011, ‘Corporate Governance and Firm Performance: Evidence from Large Governance Changes’, The Economic Journal, vol. 3, no. 1, pp. 23-34.

Creswell, J W 2013, Research design: Qualitative, quantitative, and mixed methods approaches, SAGE Publications, Thousand Oaks, CA.

Cuomo, F, Zattoni, A & Valentini, G 2012, ‘The Effects of legal reforms on the ownership structure of listed companies’, Industrial and Corporate Change, vol. 22, no. 2, pp.427-458.

Deakin, S 2010, ‘Reflexive Governance and European Company Law’, SSRN Electronic Journal.

Denk, T 2010, ‘Comparative multilevel analysis: proposal for a methodology’, International Journal of Social Research Methodology, vol.13, no.1, pp. 29-39.

Denzin, N & Lincoln, Y 2008, Colllecting and interpreting qualitative materials, Malden, MA: Blackwell.

Dhanaraj, C 2006, ‘Research Methodology in Strategy and Management/Research Methodology in Strategy and Management’, Academy of Management Review, vol. 31, no. 2, pp.497-500.

Ding, M 2010, ‘Corporate Ownership Structure, Types of Block Ownership and Firm Liquidity’, Journal of economic studies, vol. 3, no 1, pp. 25-50.

Dixon-Woods, M, Agarwal, S, Jones, D, Young, B & Sutton, A 2005, ‘Synthesising qualitative and quantitative evidence: a review of possible methods’, Journal of Health Services Research and Policy, vol. 10, no. 1, pp. 45-53.

Eun-Young, L 2008, ‘The Study on the Executive Compensation and Governance Structure in Chinese Listed Companies’, China Studies, vol. 43, no. 2, pp.669-687.

Foster, J & Yavorsky, C 2006, Understanding and Using advanced statistics, Thousand Oaks, CA: Sage.

Fracassi, C & Tate, G 2012, ‘External Networking and Internal Firm Governance’, The Journal of Finance, vol. 67, no. 1, pp.153-194.

Gatti, D 2009, ‘Macroeconomic effects of ownership structure in OECD countries’, Industrial And Corporate Change, vol.18, no. 5, pp. 901-928.

Golafshani, N 2003, Understanding reliability and validity in qualitative research, The Qualitative Report, vol. 8, no. 4, pp. 597-606.

Gorga, R 2013, ‘Corporate Control and Governance after a Decade from ‘Novo Mercado’: Changes in Ownership Structures and Shareholder Power in Brazil’, IBER, vol.11, no. 8, pp.12-14.

Guo, E & Keown, A 2009, ‘Privatization and non-tradable stock reform in China’, Global Finance Journal, vol. 20, no. 2, pp.191-208.

Haque, F 2010, ‘The Impact of Ownership and Regulations on Bank Risk-Taking: Evidence from the Middle East and North Africa (MENA) Region’, SSRN Electronic Journal.

He, D, Zhang, W & Han, G 2009, ‘Productivity Growth of the Non-Tradable Sectors in China’, SSRN Electronic Journal.

Hung, C, Chen, Q & Fang, V 2015, ‘Non-Tradable Share Reform, Liquidity, and Stock Returns in China’, International Review of Finance, vol. 15, no. 1, pp.27-54.

Inoue, T 2009, ‘Reform of China’s Split-Share Structure Takes Shape’, Capital Market Review, vol. 8, no. 3, pp. 42-59.

Ishikawa, J, Sugita, Y & Zhao, L 2009, ‘Corporate Control, Foreign Ownership Regulations and Technology Transfer’, Economic Record, vol. 85, no. 269, pp.197-209.

Kohlbacher, M & Gruenwald, S 2011, ‘Process ownership, process performance measurement and firm performance’, International Journal of Productivity & Performance Management, vol. 60, no. 7, pp. 709-720.

Kothari, C 2005, Research Methodology-Methods and Techniques, New Delhi: Wiley Eastern Limited.

Kumar, P & Zattoni, A 2015, ‘Ownership Structure, Corporate Governance and Firm Performance’, Corporate Governance: An International Review, vol. 23, no. 6, pp. 469-471.

Lakshmi, K 2010, ‘Ownership Structure and Capital Structure: Evidence from Indian Firms’, Corporate Governance, vol. 1, no. 3, pp. 44-113.

Lee, S 2015, ‘Ownership Structure and Capital Structure Decision’, Modern Applied Science, vol. 9, no. 4. pp. 264-265

Leedy, P & Ormrod, J 2005, A handbook for teacher research from design to implementation, Pearson Education, New Jersey.

Lejenas, H & Rodhe, H 2007, ‘Change in the ownership of Tellus’, TELLUSA vol. 1, no. 2, pp. 1-2.

Liu, M & Magnan, M 2011, ‘Self-dealing Regulations, Ownership Wedge, and Corporate Valuation: International Evidence’, Corporate Governance: An International Review, vol. 19, no. 2, pp. 99-115.

Liu, Y 2008, ‘Company Performance and Ownership Structure Empirical Evidence for China’, SSRN Electronic Journal, vol. 2, no. 4, pp. 45-231.

Mackenzie, N & Knipe, S 2006, ‘Research dilemmas: Paradigms, methods and methodology’, Issues in Educational Research, vol. 16, no. 1, pp. 1-6.

Magdaléna, M 2008, ‘Divided Co-Ownership and Matrimonial Property in Legal Regulations of Slovak Republic’, Contemporary Economics, vol. 2, no. 3, pp. 1-4.

Mallin, C 2012, ‘The Relationship between Corporate Governance, Transparency and Financial Disclosure’, Corporate Governance, vol. 10, no. 4, pp. 253-255.

Mertens, D 2005, Research methods in education and psychology: Integrating diversity with quantitative and qualitative approaches, Sage, Thousand Oaks.

Mitchell, M & Jolly, J 2010, Research design explained, Belmont, CA: Wadsworth.

Nakhla, M 2015, ‘Innovative regulations, incomplete contracts and ownership structure in the water utilities’, Eur J Law Econ, vol. 1, no. 1, pp. 23-45.

Nathan, E 2011, ‘Critical success factors: How one multinational company develops global e-learning’, Performance Improvement Quarterly, vol. 24, no. 1, pp. 7-30.

Neumann, W 2007, Social Research Methods: Qualitative and Quantitative Approaches, Allyn & Bacon, London.

Nietsch, M 2005, ‘Corporate Governance and Company Law Reform: a German perspective’, Corporate Governance: An International Review, vol. 13, no. 3, pp. 368-376.

Oladipo, S, Adenaike, F and Ojewumi, A 2010, ‘Establishing the reliability and validity scale’, IFE Psychologia, vol.18, no. 2, pp. 1-23.

Petit-Konczyk, M 2010, ‘Big Changes in Ownership Structures – Multiple Voting Shares in Interwar in France’, Journal of finance, vol.1, no. 4, pp. 35-56.

Pindado, J 2011, ‘Capital Structure: New Evidence from the Ownership Structure’, International Review Of Finance, vol. 11, no. 2, pp. 213-226.

Rakowska, A, Valdes-Conca, J & de Juana-Espinosa, S 2015, ‘Affecting Factors of Public Employees’ Organizational Commitment, International Journal Of Synergy And Research, vol. 3, no. 5, pp. 3-5.

Salleh, A, Ahmad, A & Kumar, N 2009, ‘Human governance: A neglected mantra for continuous performance improvement’, Performance Improvement, vol. 48, no. 9, pp.26-30.

Sans, W 2011, ‘Sampling methods and market surveillance’, Economic Quality Control, vol. 26, no. 2, pp. 2-11.

Shafiqul-Huque, A 2011, ‘Accountability and governance: strengthening extra‐bureaucratic mechanisms in Bangladesh’, Int J Productivity & Perf Mgmt, vol. 60, no. 1, pp.59-74.

Silverman, D 2006, Interpreting qualitative data: methods for analysing talk text and interaction, SAGE, London.

Sliwka, D 2009, ‘Organizational structure and innovative activity’, Economics Of Governance, vol. 4, no. 3, pp. 187-214.

Snopko, J 2012, ‘Analysis of changes in the organizational structure of municipal offices’, Management, vol. 16, no. 2, pp. 10-24.

Tan, D 2011, ‘Ownership Structure and Corporate Governance – A Empirical Study of Chinese Listed Companies’, AMR, vol. 2, no. 3, pp. 225-226.

Tan, D & Yu, S 2011, ‘Ownership Structure and Corporate Governance – A Empirical Study of Chinese Listed Companies’, AMR, vol. 2, no.5, pp.1314-1317.

Teimoury, E, Fesharaki, M & Bazyar, A 2011, ‘The relationship between governance and NPD performance and the mediating role of tie strength’, International Journal f Productivity & Perfect Management, vol. 60, no. 6, pp. 622-641.

Valadares, S & Leal, R 2008, ‘Ownership and Control Structure of Chinese Companies’, Journal of Management & Governance, vol. 8, no. 2, pp. 129-148.

Vandenberg, R 2007, ‘Organizational Research Methods Yearly Update’, Organizational Research Methods, vol. 12, no. 1, pp.3-5.

Wang, L 2009, ‘Ownership, size, and the formal structure of organizations: evidence from US public and private firms, 1992-2002’, Industrial And Corporate Change, vol. 18, no. 4, pp. 595-636.

Wang, Z & Deng, X 2006, ‘Corporate Governance and Financial Distress: Evidence from Chinese Listed Companies’, Chinese Economy, vol. 39, no. 5, pp.5-27.

Weber, R 2010, ‘The Rhetoric of Positivism versus Interpretivism: A Personal View’, MIS Quarterly, vol. 28, no. 1, pp. 3-12.

Wei, G 2007, ‘Ownership Structure, Corporate Governance and Company Performance in China’, Asia Pacific Business Review, vol. 13, no. 4, pp.519-545.

Weiss, A & Nikitin, G 2010, ‘Performance of Czech Companies by Ownership Structure’, Journal of Management & Governance, vol. 8, no. 2, pp. 29-48.

Welch, E 2008, ‘The Relationship between Ownership Structure and Performance in Listed Australian Companies’, Australian Journal Of Management, vol. 28, no. 3, pp. 287-305.

Wen, W 2011, ‘Ownership Structure and Bank Performance in China: Does Ownership Concentration Matter?’ IJBA, vol. 3, no. 1, pp. 1-24.

Witzky, M 2010, ‘Enforcement of Accounting Standards and Changes in Corporate Governance’, IBER, vol.11, no. 3, pp. 1-87

Ye, H 2012, ‘Learning Ownership Regulations in China through Networks: A Framework on Its Role in Flexibility and Post-entry Mode Change’, IJBA, vol. 3, no. 1, pp. 23-47.

Yeung, H 2009, ‘Non-Tradable Share Reform in China: Marching Towards the Berle and Means Corporation’, SSRN Electronic Journal.

Yu, H 2012, ‘MNC Flexibility And Post-Entry Mode Change: The Role Of Learning Ownership Regulations Through Network Embeddedness’, International Business & Economics Research Journal (IBER), vol.11, no. 8, p.871.

Appendices

Table 1: Distribution of sample

Panel A: Industry

IndustryNumber of firmsPercentage of total
Industrials14274.0
Real estate94.7
Commercials63.1
Public Utility2211.5
Conglomerates136.7
Total number of firms192100

Table 2: Stock code, industry and name of listed companies used in the study sample

Stknme_enName of a listed firmStk. CodeIndustry
DSDCShenzhen Desay Battery Technology Co., Ltd.000049Industrial
HJGFNorth Huajin Chemical Industries Co., Ltd000059Industrial
ZJLNShenzhen Zhongjin Lingnan Nonfemet000060Industrial
XJDQXJ Electric Co., Ltd.000400Industrial
GZLQLonkey Industrial Co.Ltd., Guangzhou.000523Industrial
HNHYHainan Haiyao Co., Ltd.000566Industrial
LZLJLuzhou Lao Jiao Co., Ltd.000568Industrial
QDSXQingdao Doublestar Co., Ltd.000599Industrial
JTNYJionto Energy Investment Co., Ltd. Hebei.000600Industrial
HMKGZhejiang Huamei Holding CO., LTD.000607Industrial
JLADJilin Aodong Pharmaceutical Group Co., Ltd.000623Industrial
YLTNingxia Younglight Chemicals Co., Ltd.000635Industrial
ZHZFZhuhai ZhonGFu Enterprise Co., Ltd.000659Industrial
HXFZHuaxun Fangzhou Co., Ltd.000687Industrial
BXNYGuangdong Baolihua New Energy Stock Co., Ltd.000690Industrial
BHNYTianjin Binhai Energy and Development Co., Ltd.000695Industrial
HGGFHESTEEL COMPANY LIMITED000709Industrial
SNHQSuning Universal Co., Ltd.000718Industrial
ZZDLShanxi Zhangze Electric Power Co., Ltd.000767Industrial
XXZGXinxing Ductile Iron Pipes Co., Ltd.000778Industrial
MLZYMCC Meili Paper Industrial Co., Ltd.000815Industrial
JSQJHubei J.S.Machine Co., Ltd.000821Industrial
LXHGLuxi Chemical Group Co., Ltd.000830Industrial
FXGFHubei Fuxing Science and Technology Co., Ltd.000926Industrial
ZLSHCOFCO Biochemical (Anhui) Co., Ltd.000930Industrial
HXGFJiangsu Huaxicun Co., Ltd.000936Industrial
JZNYJizhong Energy Resources Co., Ltd.000937Industrial
SGGFBeijing Shougang Co., Ltd.000959Industrial
ATKJAdvanced Technology and Materials Co., Ltd.000969Industrial
GSKGGOSUN HOLDING CO., LTD.000971Industrial
HGKJHuagong Tech Company Limited000988Industrial
XHCZhejiang NHU Co., Ltd.002001Industrial
HDXYHongda Xingye Co., Ltd.002002Industrial
WXGFZhejiang Weixing Industrial Development Co., Ltd.002003Industrial
HBJKHUAPONT LIFE SCIENCES CO., LTD002004Industrial
DHRDElec-tech International Co., Ltd.002005Industrial
JGKJZhejiang Jinggong Science and Technology Co., Ltd.002006Industrial
HLSWHualan Biological Engineering, Inc.002007Industrial
DZJGHan’s Laser Technology Industrial Group Co., Ltd.002008Industrial
TQGFMiracle Automation Engineering Co., Ltd002009Industrial
CHGFZhejiang Transfar Co., Ltd.002010Industrial
DAHJZhejiang Dun’an Artificial Environment Co., Ltd.002011Industrial
KEGFZhejiang Kan Specialities Material Co., Ltd.002012Industrial
ZHJDAVIC Electromechanical Systems Co., Ltd.002013Industrial
YXGFHuangshan Novel Co., Ltd.002014Industrial
XKHBXiake Color Spinning Co., Ltd.002015Industrial
SRZYGuangdong Shirongzhaoye Co., Ltd.002016Industrial
DXHPEastcompeace Technology Co., Ltd.002017Industrial
HXGJCefc Anhui International Holding Co., Ltd.002018Industrial
YFXFYIFAN XINFU PHARMACEUTICAL CO., LTD002019Industrial
JXYYZhejiang Jingxin Pharmaceutical Co., Ltd.002020Industrial
ZJZYZOJE RESOURCES INVESTMENT CO., LTD.002021Industrial
KHSWShanghai Kehua Bioengineering Co., Ltd.002022Industrial
HTDQGuizhou Space Appliance Co., Ltd.002025Industrial
SDWDShandong Weida Machinery Co., Ltd.002026Industrial
FZCMFocus Media Information Technology Co., Ltd.002027Industrial
SYDQSiyuan Electric Co., Ltd.002028Industrial
QPLFujian Septwolves Industrial Co., Ltd.002029Industrial
JLZNGreatoo Intelligent Equipment Inc.002031Industrial
SBEZhejiang Supor Co., Ltd.002032Industrial
MXDZhejiang Mizuda Printing and Dyeing Group Co., Ltd.002034Industrial
HDGFVATTI CORPORATION LIMITED002035Industrial
LCDZLianChuang Electronic Technology Co., Ltd002036Industrial
JLFZGuizhou Jiulian Industrial Explosive Materials Development Co., Ltd.002037Industrial
QYDLGuizhou Qianyuan Power Co., Ltd.002039Industrial
HFSFHuafu Top Dyed Melange Yarn Co., Ltd.002042Industrial
TBBDehua TB New Decoration Material Co., Ltd.002043Industrial
MNJKMeinian Onehealth Healthcare Holdings Co., Ltd.002044Industrial
GGDQGuoguang Electric Company Limited002045Industrial
ZYKJLuoyang Bearing Science and Technology Co., Ltd.002046Industrial
BYGFShen Zhen Globe Union Industrial Corp.002047Industrial
NBHXNingbo Huaxiang Electronic Co., Ltd.002048Industrial
ZGGXUnigroup Guoxin Co., Ltd.002049Industrial
SHGFZhejiang Sanhua Co., Ltd.002050Industrial
WGGFWuhan Iron and Steel Co., Ltd.600005Industrial
BGGFBaoshan Iron and Steel Co., Ltd.600019Industrial
SHDLShanghai Electric Power Co., Ltd.600021Industrial
SYZGSany Heavy Industrial Co., Ltd.600031Industrial
YGTZHenan Yinge Industrial Investment Co., Ltd.600069Industrial
SHMLShanghai Maling Aquarius Co., Ltd.600073Industrial
GZFZGuangzhou Development Group Incorporated600098Industrial
SQJTSAIC Motor Corporation Limited600104Industrial
YDGFJiang Su Etern Co.Ltd.600105Industrial
ZZMDZhengzhou Coal Industrial and Electric Power Co., Ltd.600121Industrial
JFKJKingFa Sci. and Tech. Co., Ltd.600143Industrial
ZGCBChina CSSC Holdings Limited600150Industrial
HHXFHenan Huanghe Whirlwind Co., Ltd.600172Industrial
ZJQYShanghai Zijiang Enterprise Group Co., Ltd.600210Industrial
DYCSDalian Dayang Trands Co., Ltd.600233Industrial
TFDZAnhui TongFeng Electronic Company Limited600237Industrial
KLKJKaile Science and Technology Co., Ltd. Hubei600260Industrial
YGZMZhejiang Yankon Group Co., Ltd.600261Industrial
JHNYZhejiang Jiahua Energy Chemical Industrial Co., Ltd.600273Industrial
SGGFLiaoning SG Automotive Group Co., Ltd.600303Industrial
HTGFShandong Huatai Paper Co., Ltd.600308Industrial
HDGFSichuan Hongda Co., Ltd.600331Industrial
AKMAucma Company Limited600336Industrial
YQMYYang Quan Coal Industrial (Group) Co., Ltd.600348Industrial
ZJLSZhejiang Longsheng Group Co., Ltd.600352Industrial
HFZYMudanjiang HengFeng Paper Co., Ltd.600356Industrial
NBYSNingbo Yunsheng Co., Ltd.600366Industrial
HXFZGuizhou Redstar Developing Co., Ltd.600367Industrial
JSGFShenyang Jinshan Energy Co., Ltd.600396Industrial
HLZJHeilan Home Co., Ltd.600398Industrial
HRGFHareon Solar Technology Co., Ltd.600401Industrial
ATJTShanxi Antai Group Co., Ltd.600408Industrial
SYHGTangshan Sanyou Chemical Industries Co., Ltd.600409Industrial
XDGFXiangtan Electric Manufacturing Co., Ltd.600416Industrial
JHQCAnhui Jianghuai Automobile Co., Ltd.600418Industrial
LHGFLiuzhou Chemical Industrial Co., Ltd.600423Industrial
RBKHenan Rebecca Hair Products Co., Ltd.600439Industrial
BTGFBaoji Titanium Industrial Co., Ltd.600456Industrial
SLWHangzhou Silan Microelectronics Co., Ltd.600460Industrial
BLDQTianjin Benefo Tejing Electric Co., Ltd.600468Industrial
FSGFAeolus Tyre Co., Ltd.600469Industrial
HTGDHengtong Optic-electric Co., Ltd.600487Industrial
TYGFTianjin Tianyao Pharmaceuticals Co., Ltd.600488Industrial
JXCZJinxi Axle Co., Ltd.600495Industrial
JGGGChangjiang Jinggong Steel Building (Group) Co., Ltd.600496Industrial
FDTGFangda Special Steel Technology Co., Ltd.600507Industrial
KMYYKangmei Pharmaceutical Co., Ltd.600518Industrial
HHYYZhejiang Huahai Pharmaceutical Co., Ltd.600521Industrial
CYJTChangyuan Group Ltd.600525Industrial
JNGXJiangsu Jiangnan High Polymer Fiber Co., Ltd.600527Industrial
YGJQHenan Yuguang Gold and Lead Co., Ltd.600531Industrial
TSLTasly Pharmaceutical Group Co., Ltd.600535Industrial
YJGDEGing Photovoltaic Technology Co., Ltd.600537Industrial
KYYYJiangsu Kanion Pharmaceutical Co., Ltd.600557Industrial
KEBZhejiang Conba Pharmaceutical Co., Ltd.600572Industrial
WLDQWolong Electric Group Co., Ltd.600580Industrial
CDKJJiangsu Changjiang Electronics Technology Co., Ltd.600584Industrial
GDRTGuangdong Rongtai Industrial Co., Ltd.600589Industrial
THKJTellhow Sci-tech Co., Ltd.600590Industrial
YBZYGuizhou Yibai Pharmaceutical Co., Ltd.600594Industrial
SNGFShenergy Company Limited600642Industrial
JYGFShanghai Jiao Yun Group Co., Ltd.600676Industrial
SSFZShanghai Industrial Development Co., Ltd.600748Industrial
TBNYTop Energy Company Ltd.Shanxi600780Industrial
GTDLSDIC Power Holdings CO., LTD.600886Industrial
ZYJTZhuzhou Smelter Group Co., Ltd.600961Industrial
BHZYShandong Bohui Paper Industrial Co., Ltd.600966Industrial
YHSHYihua Lifestyle Technology Co., Ltd.600978Industrial
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IvyPanda. 2023. "China's Non-Tradable Shares Reform: Ownership Regulations." November 17, 2023. https://ivypanda.com/essays/chinas-non-tradable-shares-reform-ownership-regulations/.

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IvyPanda. "China's Non-Tradable Shares Reform: Ownership Regulations." November 17, 2023. https://ivypanda.com/essays/chinas-non-tradable-shares-reform-ownership-regulations/.

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