Market Rule or Equal Opportunity Rule: An Empirical Analysis Based on Acquisitions of Chinese Listed Companies

Wenting CHEN, Wenxin LIU, Pengyi YU

系统科学与信息学报(英文) ›› 2024, Vol. 12 ›› Issue (2) : 191-211.

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系统科学与信息学报(英文) ›› 2024, Vol. 12 ›› Issue (2) : 191-211. DOI: 10.21078/JSSI-2023-0136

    Wenting CHEN(), Wenxin LIU(), Pengyi YU*()
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Market Rule or Equal Opportunity Rule: An Empirical Analysis Based on Acquisitions of Chinese Listed Companies

    Wenting CHEN(), Wenxin LIU(), Pengyi YU*()
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Abstract

This paper examines the data of A-share listed companies in China from 2002 to 2017, drawing on the theory of equal opportunity and market rules in M&A transactions. This paper investigates the correlation between changes in tender offer policy and M&A tendencies and performance. The findings suggest that following the policy shift and the adoption of market rules, companies that secure an exemption from the mandatory tender offer obligation not only exhibit stronger M&A tendencies but also improved long-term M&A performance. This indicates that market rules are more suitable for China and contribute to enhancing the efficiency of the M&A market. The paper also presents evidence of a moderating effect, demonstrating that exemptions from the mandatory tender offer obligation positively influence the relationship between policy change and M&A performance. Lastly, this paper finds that state-owned and large-scale firms tend to exhibit a higher degree of M&A tendencies.

Key words

takeover regulation / equal opportunity rule / market rule / mandatory tender offer

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Wenting CHEN , Wenxin LIU , Pengyi YU. . 系统科学与信息学报(英文), 2024, 12(2): 191-211 https://doi.org/10.21078/JSSI-2023-0136
Wenting CHEN , Wenxin LIU , Pengyi YU. Market Rule or Equal Opportunity Rule: An Empirical Analysis Based on Acquisitions of Chinese Listed Companies. Journal of Systems Science and Information, 2024, 12(2): 191-211 https://doi.org/10.21078/JSSI-2023-0136

1 Introduction

It is widely acknowledged that the control of large listed companies is typically held by the actual controller[1-5]. A significant issue in the realm of privately negotiated transfer of control, which has garnered considerable attention, is whether non-controlling minority shareholders can participate in the privately negotiated transfer of control and share control premium[6-12]. This issue has been addressed differently in the United States and the European Union. The former implemented "market rules", excluding minority shareholders from the sale of control transactions, while the latter chose "equal opportunity rules", aiming to provide equal benefits to all shareholders, including minority ones. In terms of the acquirer, equal opportunity rules require equal treatment conditions to all shareholders of the acquiree, to protect the interests of minority shareholders. However, this practice usually leads to rising acquisition costs and a reduction in control transaction efficiency[13]. In other words, the rules will prevent transactions with reduced value, and those with increased value as well[14]. In contrast, market rules can better promote the transfer of value-added, but they fail to prevent those with reduced value. As for enterprises, mergers and acquisitions (M&A) play roles in creating and maintaining competitive advantage, while forerunners can gain long-term advantages in the market[15]. Therefore, a question needs to be addressed: under which set of rules can corporate M&A be conducted in order to maximize performance and advantages?
China presents a compelling case study for examining both the equal opportunity and market rules approaches in M&A and tender offers. A significant shift in China's acquisition law occurred in September 2006, transitioning from the British-style mandatory tender offer rules to a more market-oriented approach. Prior to 2006, China's acquisition laws mandated that if an acquirer obtained more than 30% of the issued shares of the acquiree in a control transaction, it would trigger an obligation for an entire offer acquisition. This could only be circumvented by applying for an exemption from the China Securities Regulatory Commission (CSRC), analogous to the United States' Securities and Exchange Commission (SEC). However, the 2006 amendment to China's securities law, promulgated in September of that year, introduced more flexibility for acquirers, allowing them to choose between a full or partial tender offer. In subsequent years, the CSRC eliminated the requirement for early filing and approval of acquisition reports, a move that positively impacted the efficiency of tender offers. Further regulatory adjustments stipulated that in a tender offer acquisition of a listed company's shares, the proportion of shares to be acquired must not be less than 5% of the issued shares of the listed company. This regulation aims to mitigate the risk of protracted negotiations among shareholders with divergent views due to share decentralisation[16].
In the context of acquisitions of Chinese listed companies, this paper specifically explores the decisions and outcomes from the perspective of the acquirer. China provides an intriguing case study due to its fundamental shift in acquisition law in September 2006, transitioning from equal opportunity rules to market rules. Utilizing data on forced tender offer events in China's stock market from 2002 to 2017, this paper investigates the M&A tendencies and performance of China A-share listed companies under both sets of rules, with a particular focus on the acquirer's decision-making and income. The results indicate that the implementation of market rules has led to a stronger inclination towards M&A events due to decreased acquisition costs. Furthermore, companies that are exempted from mandatory obligation demonstrate superior M&A performance. The results show that after the implementation of market rules, companies show a stronger desire for M&A events due to the decrease in acquisition costs. Companies that are exempted from mandatory obligation have better M&A performance than those that are not.
The paper is expected to make the following contributions: 1) While the majority of existing literature on the exemption of tender offer obligation primarily focuses on legal interpretation and institutional consequences, there is a noticeable gap in studies directly discussing the economic consequences of exemption of tender offer obligation. This paper aims to fill this gap by providing a fresh perspective on the exemption of tender offer obligation and its relationship with M&A performance. 2) Through the empirical method, the article also expands on the economic consequences of M&A policy changes in terms of market rules and equal opportunity rules. 3) Furthermore, it provides a reference for China's policy formulation and optimisation regarding tender offers, which paves the way for China to better adapt to marketisation and build a better and healthy capital market.
The rest of this paper is structured as follows. Section 2 describes the evolution of China's acquisition law, especially the fundamental change from equal opportunity rules to market rules since September 2006. Section 3 reviews the related literature and develops the hypotheses. Section 4 introduces the research design. Section 5 presents the empirical results. Section 6 provides additional analyses and the final part concludes the paper.

2 China's Acquisition System

China's acquisition regulatory rules, greatly influenced by British acquisition law, began to be promulgated in 1993, shortly after the revitalisation of China's stock market. Under the initial framework, an independent entity purchasing more than 30% of the total number of shares issued by a listed company was required to purchase all the shares of the company in cash, necessitating an entire tender offer.
In 1998, the Securities Law of the People's Republic of China was enacted, implementing the equal opportunity rules more thoroughly. The acquisition law based on the rule of equal opportunity matured and was implemented until 2002 when the Securities Law came into effect and the CSRC promulgated a series of acquisition measures. This led to the initiation of the entire tender offer in China's securities market. By July 31, 2004, 7 cases of tender offer had taken place in China, such as the NISCO and Doyen International Holdings Ltd. This series of measures is similar to the acquisition laws of the United Kingdom or the European Union in all aspects, showing the opposite characteristics of the market rules. Although most of the tender offer in China is a forced choice, the tender offer has indeed become one of the important means of acquisition of listed companies in China.
In 2006, China's securities regulations underwent a thorough reform, especially the acquisition law. The most notable change was the shift from open hostility to the overall acceptance of market rules. The 2005 securities law, which came into effect in September 2006, replaced the 1998 securities law and cancelled the overall prohibition on previously stipulated partial tender offers. Independent subjects purchasing more than 30% of the shares could choose to make an entire or partial tender offer and to continuously purchase no less than 5% of the shares, marking China's acceptance of market rules.
The transition from equal opportunity rules to market rules in China's acquisition law is unique, as it occurred over a relatively short period. This transition provides a significant research opportunity to explore which of these two rules is better suited to the market economy with Chinese characteristics, particularly in the context of a transition economy with highly concentrated ownership. Generally, the tender offer was required to be an entire one before the reform of the acquisition law in 2006. After the reform, companies that trigger the obligation of a mandatory tender offer can perform a partial one.

3 Literature Review and Hypothesis Development

Legislators and policymakers have expressed concern about the potential adverse impact of partial tender offers, leading to stringent restrictions in the UK and continental Europe. In contrast, US regulations impose fewer restrictions, although partial tender offers are not frequently utilized[17]. Following the 2013 amendment to Delaware law, which reduced the shareholder support threshold for two-step tender offers, Delaware has seen an increase in acquisitions through tender offers compared to other US states[18]. Tender offers have the advantage of substantially faster completion times, and deals in more competitive environments and deals with fewer external impediments on execution are more likely to be structured as tender offers[19]. Several studies on the Chinese capital market have identified political factors as significant influences on M&A tendencies[20]. Some research has also found that specific terms of a tender offer, such as golden parachutes and irrevocable commitments, can contribute to successful M&A events[21-23].
Politics is closely linked with power, systems, and rules. The institutional change in this paper refers to the implementation of the acquisition law in September 2006, which cancelled the mandatory full tender offer and adopted market rules. Enterprises triggering the mandatory tender offer obligation can now choose to make a full or partial tender offer or apply to the CSRC for exemption from the tender offer obligation. This change may reduce acquisition costs, potentially leading to a more pronounced propensity towards M&A activities in Chinese capital market. Based on the above analysis, the following research hypothesis can be proposed:
H1 Enterprises are more likely to initiate M&A after the policy change.
Investor protection may hinder value-increasing takeovers when the equal opportunity rule is in effect[24]. Partial offers may appeal more to shareholders as they mitigate the free-rider problem and increase the anticipated number of shares tendered[17]. Enhanced takeover offers can result in increased acquirer returns and effectively alleviate agency conflicts[25, 26]. The freezeout rule eliminates the well-known free-rider problem in tender offers[14, 15]. However, there are conditions where the freezeout rule does not resolve the free-rider problem. In such an equilibrium, a value-increasing acquirer can profitably take over the target firm, thereby restoring economic efficiency[27]. The process of facilitating the removal of underperforming incumbent boards through a takeover bid mechanism can be time-consuming. However, UK shareholders have managed to overcome the free-rider problem by employing investigation committees on a sufficiently large scale to present a credible threat to board malfeasance[28]. Various factors can influence the performance of enterprises following M&A events. However, the policy change examined in this study is viewed as a positive policy as it allows enterprises to be exempted from the mandatory obligation of a full tender offer. Based on the above analysis, the following research hypothesis can be proposed:
H2 After the reform, the performance of M&A with exemption from obligations improves.

4 Research Design

4.1 Sample Selection and Data Source

This study utilizes data from Shanghai and Shenzhen A-share companies for the period of 2002–2017, with September 2006 serving as the demarcation point to examine M&A tendencies and performance of companies with mandatory tender offers around this period. The data for M&A tendencies were sourced from the China Stock Market and Accounting Research (CSMAR) database. The dataset was refined by excluding: 1) Firms in the financial industry; 2) Reorganisation types such as asset acquisition, asset divestiture, asset replacement, merger absorption, debt restructuring, and shares M&A of buyback; 3) Events with missing data during the sample period. M&A performance data were obtained from the announcements of listed companies on the exemption of tender offer obligations on the CSRC's official website from 2002 to 2017. Additional data were accordingly connected and supplemented from the CNINF Network (CNINF) and were further refined by: 1) Eliminating firms in the financial industry; 2) Excluding data where the proportion of shares after purchase is less than 30%; 3) Categorizing all data into three groups: exemption, entire tender offer, and partial tender offer. Other relevant data were sourced from CSMAR.

4.2 Variable Definition and Measurement

4.2.1 Dependent Variables

The dependent variables of this paper are M&A tendencies (M&AT) and M&A performance (M&AP). Specifically, M&AT is quantified by the completion ratios of M&A (M&AC) and M&A amount (M&AA), while M&AP is divided into short-term and long-term performance, including cumulative abnormal return(CAR), buy-and-hold abnormal return (BHAR), and market-to-book ratio (MBR). CAR and BHAR serve as short-term and long-term absolute market performance indicators, respectively, while MBR is a relative market performance indicator.

4.2.2 Independent Variables

The independent variables are T1, T2 and T1T2. T1 represents whether a company's mandatory tender offer obligation has been exempted by CSRC. If the company obtains the exemption, T1 is 1, otherwise, it is 0. T2 refers to the first announcement date before and after September 2006. If the date is before September 2006, T2 is 0, otherwise, it is 1. T1T2 is the interaction of T1 and T2.

4.2.3 Control Variables

This study incorporates a set of control variables based on corporate governance and corporate finance. The definition of these variables is provided in Table 1.
Table 1 Definitions of variables
Variable type Variable symbol Variable meaning
Dependent variables M&AC Samples of M&A of the company in that year / Samples of all first announcements of the company in the same year
M&AT M&AA Make a sum of all M&A payments of the company in the year and then take its natural logarithm.
M&AP CAR Using CAPM model to calculate car value. The date of M&A is the date of occurrence of the event. Estimated window is [150,6] and event window is [1,1] and [5,5]
BHAR Abnormal returns in 3 years after M&A.
MBR Market-to-Book Ratio=total assets / market value
Independent variables Exemption or not (T1) If the company obtains the exemption, T1 is 1, otherwise it is 0.
Policy change (T2) If the first announcement date is before September 2006, T2 is 0, otherwise it is 1. After triggering the mandatory tender offer obligation in September 2006, enterprises can not only choose to make a full or partial tender offer, but also apply to the CSRC for exemption from the obligation of tender offer.
T1T2 T1T2 is the interaction of T1 and T2.
Control variables Corporate governance Board characteristics INDR The proportion of the number of independent directors in the board of directors in the year before M&A.
Bsize Number of board of directors in the year before M&A.
CEO chara cteristics edu The education background of CEO in the year of M&A, 1 for master degree or above, 0 for others.
tenure The tenure of CEO in the year of M&A.
CEOpower CEO compensation of the year before M&A / remuneration of directors and supervisors of the year before M&A
CEOoverconfidence The salary of CEO in the year before M&A plus 1 and then take the natural logarithm.
Pconnection In the year of M&A, if the CEO held the post in relevant government agencies, take it as 1, otherwise it is 0.
Executives characteristics magshare The proportion of shares held by board of directors and supervisors in the year before M&A.
magsalary The total remuneration of directors and supervisors in the year before M&A plus 1 and then take the natural logarithm.
Ownership characteristics TOP1 The shareholding ratio of the largest shareholder in the year before M&A.
Corporate finance lnasset Add 1 to the total assets at the end of the year before M&A and then take the natural logarithm.
Lev Asset liability ratio of the company in the year before M&A.
OCF The ratio of operating cash flow to total assets in the year before M&A.
FirmGrowth Growth rate of business income in the year before M&A.
Age Duration of the company.
Listyear Listing time of the company.
Others YEAR Annual virtual variable.
IND Industry dummy variable.

4.3 Model Settings

M&ATijt=+β1T2i+γX+μj+μt+εijt,
(1)
M&APijt=+β1T1i+β2T2i+β3T1iT2i+γX+μj+μt+εijt.
(2)
In order to investigate the impact of acquisition policy changes on M&A tendencies and activities, this paper constructs the regression model above. Specifically, i represents the company, j represents the industry, and t represents the year. X represents control variables. The last three symbols, namely μj, μt and εijt, correspond to industry fixed effect, year fixed effect, and error item respectively.

5 Analysis of Inspection Results

5.1 Descriptive Statistics and Univariate Analysis

5.1.1 Descriptive Results

Table 2 provides the descriptive statistics of the complete sample. The mean values of T1 and T2 are 0.007 and 0.864, respectively, indicating a higher proportion of samples with exemptions and policy changes. Regarding M&A tendencies, the mean M&AC is 0.986, suggesting a high degree of completion for the M&A events post-announcements. The average M&AA is 18.603, with a maximum value of 23.165, which reduces to the original amount of about RMB 105 million and RMB 9.846 billion, respectively. In terms of M&A performance, the mean values of BHAR and MBR are 0.232 and 3.562 respectively, and CAR is 0.001, suggesting that corporate-initiated M&A events do not yield significant benefits to shareholders. The control variables show relatively large differences in tenure, age, and Listyear, while others exhibit smaller variations. Generally, there is no standard deviation that is much larger than the mean.
Table 2 Descriptive statistics
Variables N Mean SD Min Max
M&AC 10879 0.986 0.076 0.5 1
M&AA 10382 18.603 2.048 13.122 23.165
CAR 186 0.001 0.065 0.183 0.188
BHAR 142 0.232 1.345 2.833 7.024
MBR 135 3.562 1.779 1.218 12.074
T1 25719 0.007 0.081 0 1
T2 25521 0.864 0.343 0 1
T1T2 25521 0.005 0.072 0 1
INDR 31629 0.348 0.082 0 0.56
Bsize 31629 9.01 1.83 5 15
edu 24603 0.478 0.5 0 1
tenure 31322 7.379 4.576 1 17
CEOpower 31264 0.155 0.063 0.028 0.405
CEOoverconfidence 31347 12.302 2.17 0 14.88
Pconnection 31322 0.053 0.224 0 1
magshare 30464 0.097 0.175 0 0.679
magsalary 31629 14.646 0.928 12.136 16.808
TOP1 31636 0.371 0.154 0.091 0.757
lnasset 31635 21.656 1.221 19.008 25.511
Lev 28250 0.463 0.203 0.07 0.972
OCF 28250 0.044 0.077 0.204 0.263
FirmGrowth 28249 0.178 0.346 0.535 1.873
Age 31730 14.271 5.709 3 29
Listyear 30344 9.413 6.042 1 24
The limited number of observations for performance indicators can be attributed to the following factors: 1) Between 2002 and 2017, the instances of M&A events where the acquisition of more than 30% of shares triggered a mandatory tender offer obligation were relatively few, with only 1, 093 occurrences according to CSRC statistics and CNINF comparison data. 2) A significant proportion of M&A events in this category involve an unlisted parent company acquiring a listed subsidiary. Given the focus of this study on the acquirer's perspective, it is necessary to exclude M&A events where the acquirer is an unlisted parent company due to data availability constraints.

5.1.2 Sub-Sample Statistics

Table 3 presents the sub-sample statistics for M&A tendencies and performance. The sample is divided into two sub-samples: The pre-policy sample (2002–2006) and the post-policy sample (2007–2017). The results suggest that: 1) In terms of corporate governance, indicators including INDR, CEOpower, and CEOoverconfidence have improved after the policy change. 2) In terms of corporate finance, policy changes have led to significant improvements of indicators such as lnasset and Lev. 3) In terms of M&A tendencies, M&AC as well as M&AA in the post-policy sample is higher than the other. 4) In terms of M&A performance, CAR has witnessed a minor drop since 2007, while both BHAR and MBR have significantly increased. In general, enterprises are more inclined to issue M&A after the policy change, preliminarily verifying hypothesis H1. However, whether enterprises perform better after the policy change requires further exploration.
Table 3 Group tests
All pre-policy sample post-policy sample
Variables Mean Mean Mean t-value
Panel A: Corporate governance
INDR 0.348 0.251 0.366 106.314***
Bsize 9.01 9.675 8.881 28.590***
edu 0.478 0.357 0.501 16.380***
tenure 7.379 3.271 8.171 74.903***
CEOpower 0.155 0.143 0.157 14.467***
CEOoverconfidence 12.302 11.079 12.529 43.715***
Pconnection 0.053 0 0.063 18.286***
magshare 0.097 0.009 0.11 33.786***
magsalary 14.646 13.679 14.835 91.010***
TOP1 0.371 0.431 0.359 31.051***
Panel B: Corporate finance
lnasset 21.656 21.104 21.763 35.778***
Lev 0.463 0.471 0.461 3.332***
OCF 0.044 0.046 0.043 2.205**
FirmGrowth 0.178 0.221 0.17 9.503***
Age 14.271 9.293 15.241 73.387***
Listyear 9.413 6.554 9.973 36.967***
Panel C: M&A tendencies
M&AC 0.986 0.984 0.998 6.639***
M&AA 18.603 17.686 18.749 15.720***
Panel D: M&A performance
CAR 0.001 0.003 0.002 0.071
BHAR 0.232 6.348 2.788 8.548***
MBR 3.562 2.778 3.815 2.998***
Note: ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.

5.1.3 Typical Facts

To gain a more comprehensive understanding of the M&A landscape in China's A-share market from 2002 to 2017, this study, based on the CSMAR database, presents several key facts using graphical representations. Specifically, the ratio of A-share listed companies that have undergone M&A events to the number of companies trading normally is used as a measure of M&A tendencies. As depicted in Figure 1, M&A tendencies surged from 58% to 72% in 2007, decelerated in 2010, and then resumed an upward trajectory. The trend generally hovers around 70% in most years, suggesting a robust M&A tendency in the A-share market.
Figure 1 A-share listed companies' M&A tendencies during 2002–2017

Full size|PPT slide

Additionally, this study examines the distribution of M&A transactions exceeding RMB 105.0 million annually from 2002 to 2017 (Table 2 shows the average M&A transaction converted to RMB 105.0 million, which this study classifies as large deal M&A events). Figure 2 reveals that the number of large deal M&A events reached a peak in 2007, with a significant increase in 2014–2015, followed by a slowdown in 2016–2017. This trend aligns closely with the introduction of M&A policies, underscoring the substantial influence of China's policies on the market.
Figure 2 Number of M&A during 2002–2017

Full size|PPT slide

The policy change discussed in this paper pertains to the takeover law that abolished the entire mandatory offer obligation, implemented in September 2006. Specifically, acquirers whose shares reach 30% of the issued shares of the company can apply to the CSRC for an exemption from the entire mandatory offer obligation under certain conditions. Those without an exemption must issue a full or partial mandatory offer to shareholders. Compared to the previous
law, this amendment introduces an additional option to apply for an exemption, signifying a shift in regulatory rules for corporate control transactions from equal opportunity rules to market rules. This change is beneficial for corporate takeovers as it significantly reduces takeover costs and diversifies payment methods1.
1The Takeover Code of 1993 requires that the triggering of a mandatory tender offer obligation must be followed using cash to acquire the shares of all shareholders.

5.2 Empirical Results

In this study, standard errors are clustered by stock symbols and robust regression is employed to adjust for heteroskedasticity and control for within-group correlation. Year-fixed effects and industry-fixed effects are incorporated to control for potential exogenous events and inter-industry heterogeneity during the sample period. Table 4 presents the regression results of the model.
Table 4 OLS regression results
(1) (2) (3) (4) (5)
Variables M&AC M&AA CAR BHAR MBR
T1T2 0.446** 5.679** 0.842*
(0.012) (0.049) (0.089)
T1 0.791*** 5.707* 0.957
(0.004) (0.061) (0.545)
T2 1.349** 0.713*** 0.776 0 0.875
(0.016) (0.000) (0.389) (.) (0.611)
INDR 0.632 0.308 1.519 2.451 3.954
(0.508) (0.560) (0.661) (0.661) (0.127)
Bsize 0.0274 0.0206 0.0952 0.158 0.086
(0.508) (0.239) (0.192) (0.539) (0.481)
edu 0.0498 0.130** 0.273 0.355 0.204
(0.608) (0.017) (0.501) (0.643) (0.351)
tenure 0.0780** 0.00237 0.0111 0.0408 0.001
(0.028) (0.913) (0.931) (0.824) (0.990)
CEOpower 1.517** 1.907*** 0.92 0.564 0.583
(0.039) (0.000) (0.474) (0.852) (0.747)
CEOoverconfidence 0.00474 0.0529** 0.115* 0.199 0.017
(0.733) (0.013) (0.081) (0.108) (0.569)
Pconnection 0.142 0.117 4.608*** 2.459 0.755
(0.423) (0.292) (0.001) (0.383) (0.458)
magshare 0.492** 0.111 7.838 2.755 4.623
(0.049) (0.546) (0.351) (0.742) (0.531)
magsalary 0.0273 0.0907* 0.12 0.053 0.182
(0.729) (0.066) (0.606) (0.887) (0.329)
TOP1 0.846** 0.554*** 0.464 1.139 1.021
(0.015) (0.007) (0.574) (0.641) (0.377)
lnasset 0.105* 0.318*** 0.293* 0.274 0.523**
(0.057) (0.000) (0.096) (0.411) (0.012)
Lev 0.0312 0.239 0.00697 0.175 5.685***
(0.896) (0.191) (0.997) (0.929) (0.000)
OCF 0.153 0.0564*** 2.24 1.798 6.724**
(0.772) (0.000) (0.427) (0.631) (0.014)
FirmGrowth 0.00807 0.0157 0.289 0.528 0.345
(0.942) (0.817) (0.680) (0.116) (0.481)
Age 0.0193* 0.00209 0.0478 0.0406 0.072
(0.093) (0.785) (0.775) (0.603) (0.302)
Listyear 0.0722*** 0.0123 0.033 0.0581 0.001
(0.007) (0.413) (0.754) (0.680) (0.988)
_cons 2.678** 11.33*** 7.144** 1.009 5.083
(0.020) (0.000) (0.027) (0.856) (0.203)
Industry Yes Yes Yes Yes Yes
Year Yes Yes Yes Yes Yes
N 225 6942 52 79 79
adj. R2 0.183 0.138 0.589 0.315 0.553
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.
Columns (1) and (2) display the impact of policy changes (T2) on M&A tendencies. Regardless of whether the dependent variable is M&AC or M&AA, the coefficient of T2 is significantly positive, indicating that policy changes stimulate firms to initiate M&A behaviors, providing preliminary support for Hypothesis H1.
Columns (3), (4), and (5) present the impact of mandatory tender offer obligation exemption (T1), policy changes (T2), and their interaction (T1T2) on M&A performance. The results suggest that: 1) In terms of the short-term performance indicator CAR, companies obtaining exemptions perform better in the short term, while policy changes have a negative impact. However, the interaction term T1T2 is significantly positive at the 5% level, suggesting that firms with exemptions after the policy change demonstrate superior M&A performance. 2) In terms of the long-term performance indicator BHAR, firms exempted from the mandatory tender offer obligation exhibit poorer M&A long-term performance, while the interaction term T1T2 is significantly positive at the 5% level, indicating that firms that are successfully exempted from obligation after policy reform exhibit exceptional long-term performance. 3) In terms of the market performance indicator MBR, the interaction term T1T2 is significantly positive at a 10% level, suggesting that firms that obtain exemptions from the mandatory tender offer obligation following the revised policy achieve notable success in M&A events. These results provide general support for Hypothesis H2.

5.3 Robustness Tests

This study employs four robustness test methods to ensure the reliability of the regression results.
1) Replacement of the dependent variable: This study substitutes the dependent variable M&AT with the dummy variable M&A Directions (M&AD) for testing, while keeping other variables consistent. The regression results, shown in Table 5, align with the findings in Table 4. Additionally, the window period of CAR is expanded to (5,+5), with other conditions remaining unchanged. The regression results, shown in Column (2) of Table 5, indicate a short-lived improvement in CAR for firms receiving exemptions after policy change, suggesting a rapid increase in short-term stock price followed by a return to a rational level. This phenomenon is consistent with the conclusions of the existing literature[29].
Table 5 Replacement of dependent variables
(1) (2) (1) (2)
Variables M&AD CAR Variables M&AD CAR
T1T2 0.174*** magsalary 0.00608 0.0631**
(0.009) (0.309) (0.012)
T1 0.183 TOP1 0.0357 0.203**
(0.106) (0.213) (0.047)
T2 0.127*** 0 lnasset 0.00262 0.0400**
(0.000) (.) (0.576) (0.035)
INDR 0.0642 0.0637 Lev 0.0682*** 0.0866
(0.389) (0.825) (0.002) (0.368)
Bsize 0.00678*** 0.00865 OCF 0.00806*** 0.409
(0.008) (0.438) (0.000) (0.183)
edu 0.0151* 0.0860* FirmGrowth 0.0475*** 0.0479
(0.063) (0.060) (0.000) (0.152)
tenure 0.000204 0.0209** Age 0.000694 0.00555
(0.946) (0.014) (0.571) (0.444)
CEOpower 0.0644 0.308 Listyear 0.00422** 0.0185***
(0.289) (0.281) (0.047) (0.002)
CEOoverconfidence 0.0018 0.000209 _cons 0.215** 0.405
(0.395) (0.961) (0.027) (0.207)
Pconnection 0.0374** 0.143 Industry Yes Yes
(0.030) (0.126) Year Yes Yes
magshare 0.121*** 0.159 N 19938 73
(0.000) (0.865) adj. R2 0.029 0.486
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.
2) Shortening of the time window: To mitigate the impact of other policies, the sample range is shortened to 2004–2015 for regression, with other conditions remaining stable. The regression results, shown in Table 6, further verify the robustness of hypotheses H1 and H2.
Table 6 Shortened time window
(1) (2) (3) (4) (5)
Variables M&AC M&AA CAR BHAR MBR
T1T2 0.490** 6.387* 0.853*
(0.012) (0.052) (0.082)
T1 0.888*** 6.486* 0.96
(0.005) (0.061) (0.549)
T2 0.993* 0.293* 0.159 2.508 0
(0.067) (0.085) (0.773) (0.515) (.)
INDR 0.509 0.467 2.803 5.538 3.844
(0.702) (0.412) (0.489) (0.324) (0.199)
Bsize 0.00201 0.0238 0.136 0.232 0.0764
(0.969) (0.220) (0.217) (0.371) (0.557)
edu 0.0318 0.143** 0.301 0.711 0.209
(0.782) (0.015) (0.475) (0.373) (0.375)
tenure 0.0981** 0.0116 0.0158 0.0328 0.0437
(0.025) (0.627) (0.906) (0.857) (0.735)
CEOpower 1.818** 1.932*** 0.634 0.433 0.503
(0.032) (0.000) (0.683) (0.888) (0.787)
CEOoverconfidence 0.00607 0.0512** 0.116* 0.406 0.003
(0.640) (0.031) (0.065) (0.175) (0.925)
Pconnection 0.0342 0.0775 4.669*** 2.571 0.705
(0.880) (0.495) (0.001) (0.375) (0.501)
magshare 0.560* 0.25 8.69 0.83 2.169
(0.093) (0.216) (0.324) (0.922) (0.807)
magsalary 0.0199 0.0964* 0.0931 0.114 0.188
(0.837) (0.080) (0.702) (0.782) (0.345)
TOP1 0.683* 0.467** 0.0668 0.0517 0.793
(0.064) (0.038) (0.965) (0.983) (0.560)
lnasset 0.105* 0.312*** 0.266 0.415 0.526**
(0.082) (0.000) (0.157) (0.157) (0.012)
Lev 0.115 0.0758 0.529 0.188 5.546***
(0.718) (0.706) (0.818) (0.920) (0.000)
OCF 0.115 0.0562*** 2.131 1.662 6.803**
(0.868) 0.000 (0.448) (0.678) (0.023)
FirmGrowth 0.0293 0.0989 0.141 0.552* 0.307
(0.867) (0.179) (0.860) (0.091) (0.543)
Age 0.0183 0.00288 0.0817 0.0572 0.0818
(0.150) (0.736) (0.638) (0.407) (0.281)
Listyear 0.0762*** 0.0116 0.016 0.0124 0.00699
(0.010) (0.471) (0.878) (0.931) (0.912)
_cons 2.867** 11.94*** 6.958* 2.393 4.749
(0.045) (0.000) (0.093) (0.644) (0.242)
Industry Yes Yes Yes Yes Yes
Year Yes Yes Yes Yes Yes
N 167 5765 50 74 75
adj. R2 0.012 0.134 0.581 0.246 0.54
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.
3) Heckman's two-stage method: A treatment effect model is used to address potential sample self-selection bias. The first stage involves selecting whether to choose tender offer as the form of M&A (Tenderornot) as the exclusion constraint variable, followed by probit regression of all samples to obtain the inverse Mills ratio (IMR). The second stage involves OLS estimation using M&AA as the explanatory variable, with the addition of the obtained IMR. The results, shown in Table 7, indicate a significant positive relationship between Tenderornot, T2, and the IMR, further verifying hypothesis H1.
Table 7 Heckman's two-stage results
(1) (2) (1) (2)
Variables First Second Variables First Second
main magshare 4.752*** 0.346**
T2 0.349*** (0.001) (0.036)
(0.000) Bsize 0.0462* 0.0252
Tenderornot 6.776*** (0.073) (0.129)
(0.001) INDR 1.041 0.315
IMR 2.284*** (0.250) (0.527)
(0.006) OCF 0.590** 0.0661*
CEOoverconfidence 0.00205 0.0615*** (0.041) (0.056)
(0.917) (0.000) edu 0.11 0.140***
magsalary 0.0408 0.062 (0.312) (0.008)
(0.549) (0.144) tenure 0.0662** 0.0966***
TOP1 0.341 0.573*** (0.024) (0.000)
(0.345) (0.002) lnasset 0.192*** 0.312***
Lev 0.218 0.0409 (0.000) (0.000)
(0.527) (0.777) CEOpower 1.995*** 1.635***
FirmGrowth 0.0269 0.0522 (0.002) (0.000)
(0.878) (0.443) Pconnection 0.257 0.118
Age 0.0235 0.0341*** (0.493) (0.250)
(0.173) (0.000) _cons 6.958*** 9.989***
Listyear 0.0453** 0.0401*** (0.000) (0.000)
(0.018) (0.001) N 6942 6942
adj. R2 0.091
Pseudo R2 0.144
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.
4) Coarsened exact matching (CEM): Referring to the existing literature, this paper uses the CEM model to re-estimate the promotional effect and performance consequences derived from M&A policy changes[30, 31]. The CEM model matches regressions based on the theoretical distribution of each variable, assigning a certain weight to data in the treatment group and control group. The weights generated by CEM are re-estimated using WLS regression, and the results show that the sign of the estimated coefficients of the core independent variables remains unchanged for both M&AT and M&AP. Overall, the core hypotheses H1 and H2 of the study remain robust.

6 Additional Analysis

6.1 Mechanism Tests

Since the full implementation of the market system in China in September 2006, firms purchasing more than 30% of the equity can choose between an entire and a partial tender offer, indicating a shift from equal opportunity rules to market rules. In order to explore whether and how the exemption of mandatory tender offer obligation affects the relationship between the policy change and firms' M&A performance, this paper takes the exemption of the mandatory tender offer obligation as a mechanism variable and draws on the methodology of the existing literature to construct the following moderated model regression[32, 33]. Subsequently, this paper explores the existence of moderating effects based on regression results and measures the size of the moderating effects. The definitions of the model variables are consistent with the previous studies.
M&APijt=bT1i+(a+cT1i)×T2i+γX+εijt.
(3)
The regression results, shown in Table 8, indicate that the model with the interaction term has better explanatory strength. The coefficients of the interaction terms of CAR, BHAR and MBR are significant, suggesting a positive moderating effect of the exemption from the mandatory offer obligation on the relationship between policy change and M&A performance. In addition, in order to explore the effect of mandatory tender offer obligation exemption on M&A performance more clearly, this paper adopts a graphical method based on the regression results.
Table 8 Moderating effect test results
(1) (2) (3) (4) (5) (6)
Variables CAR1 CAR2 BHAR1 BHAR2 MBR1 MBR2
T1 0.0891*** 0.181*** 0.465 5.122*** 0.671 1.789
(0.009) (0.000) (0.674) (0.001) (0.528) (0.382)
T2 0.00443 0.0139 4.656*** 0 0.884 0
(0.780) (0.317) (0.000) (.) (0.302) (.)
T1T2 0.240*** 4.656*** 0.953*
(0.000) (0.000) (0.069)
INDR 0.0441 0.0445 2.201 2.201 9.143* 7.213
(0.605) (0.526) (0.654) (0.654) (0.056) (0.124)
Bsize 0.00223 0.00165 0.0068 0.0068 0.279* 0.256
(0.467) (0.512) (0.966) (0.966) (0.072) (0.149)
edu 0.0112 0.0227* 0.709 0.709 0.414 0.226
(0.407) (0.054) (0.259) (0.259) (0.490) (0.630)
tenure 0.00443 0.00025 0.108 0.108 0.0528 0.0753
(0.247) (0.940) (0.498) (0.498) (0.730) (0.542)
CEOpower 0.0499 0.0643 1.04 1.04 0.855 0.927
(0.405) (0.197) (0.681) (0.681) (0.724) (0.605)
CEOoverconfidence 0.00268 0.00203 0.0506 0.0506 0.0302 0.00604
(0.199) (0.238) (0.704) (0.704) (0.813) (0.901)
Pconnection 0.142*** 0.238*** 2.722* 2.722* 0.819 0.824
(0.000) (0.000) (0.086) (0.086) (0.585) (0.517)
magshare 0.207 0.0332 2.611 2.611 15.8 13.9
(0.238) (0.825) (0.806) (0.806) (0.124) (0.281)
magsalary 0.00821 0.0068 0.276 0.276 0.00687 0.0153
(0.262) (0.261) (0.531) (0.531) (0.987) (0.958)
TOP1 0.0407 0.00619 1.32 1.32 2.267 2.309
(0.386) (0.877) (0.586) (0.586) (0.331) (0.275)
lnasset 0.000109 0.0016 0.267 0.267 0.743*** 0.707**
(0.982) (0.680) (0.285) (0.285) (0.003) (0.026)
Lev 0.00297 0.0221 0.374 0.374 8.793*** 8.276***
(0.942) (0.517) (0.819) (0.819) (0.000) (0.000)
OCF 0.0679 0.00599 3.435 3.435 0.0633 1.45
(0.339) (0.920) (0.416) (0.416) (0.987) (0.561)
FirmGrowth 0.0177 0.0289 0.187 0.187 0.41 0.352
(0.415) (0.116) (0.754) (0.754) (0.475) (0.406)
Age 0.000812 0.00136 0.02 0.02 0.193** 0.194
(0.654) (0.367) (0.824) (0.824) (0.028) (0.175)
Listyear 0.00248 0.00035 0.0965 0.0965 0.0838 0.111
(0.331) (0.872) (0.429) (0.429) (0.474) (0.216)
_cons 0.0157 0.115 7.636 2.98 7.062 8.057*
(0.891) (0.252) (0.113) (0.546) (0.126) (0.082)
N 52 52 79 79 79 79
adj. R2 0.314 0.535 0.341 0.341 0.526 0.574
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.
As shown in Figure 3, the positive relationship between T2 and CAR among firms that have received exemptions from the tender offer obligation is stronger than those without exemptions; as shown in Figure 4, compared to firms without exemptions, T2 exhibits a stronger relationship with BHAR among firms that have received exemptions; and according to, there exists a more obvious positive relationship between T2 and MBR.
Figure 3 Moderating effect graph-CAR

Full size|PPT slide

Figure 4 Moderating effect graph-BHAR

Full size|PPT slide

Figure 5 Moderating effect graph-MBR

Full size|PPT slide

6.2 Heterogeneity Analysis

The issue of differences in property rights of M&A has received considerable critical attention. The influence of different property rights of enterprises on M&A largely stems from the government. State-owned enterprises, under unprecedented reorganisation policy pressure, tend to expand through M&A events in order to avoid losing independence. Large-scale enterprises, with solid economic foundations and anti-risk abilities, are usually more capable and willing to launch investment activities including M&A[34]. This study further explores the impact of policy changes and M&A tendencies by considering the heterogeneity of property rights and enterprise scale. Property rights are grouped according to state-owned (SOE=1) versus non-state-owned enterprises (SOE=0), while enterprise scale is grouped according to the median of the main business income (large-scale and small-scale).
The results, shown in Table 9, suggest that the impact of policy changes on M&A tendencies is more significant for state-owned and large-scale enterprises, both in terms of coefficients and significance. The impact of policy changes mainly originates from state-owned enterprises as well as large-scale enterprise samples, which leads to differences in M&A tendencies between state-owned and non-state-owned enterprises, as well as between large-scale and small-scale enterprises.
Table 9 Heterogeneity analysis results
Variables M&AC M&AA M&AC M&AA
SOE=1 SOE=0 SOE=1 SOE=0 large-scale small-scale large-scale small-scale
T2 0.610** 0.0046 1.051*** 0.102 1.303*** 0.0522 1.184*** 0.317
(0.030) (0.823) (0.000) (0.648) (0.000) (0.857) (0.000) (0.197)
INDR 1.348 0.0114 0.142 0.091 1.728 0.298 0.698 1.139
(0.285) (0.339) (0.860) (0.904) (0.198) (0.831) (0.350) (0.164)
Bsize 0.08 0.00088 0.003 0.037 0.0251 0.0883 0.0214 0.0248
(0.211) (0.170) (0.889) (0.205) (0.732) (0.106) (0.356) (0.384)
edu 0.0303 0.001 0.222** 0.025 0.228 0.00123 0.141* 0.102
(0.780) (0.777) (0.011) (0.726) (0.125) (0.991) (0.063) (0.195)
tenure 0.00433 0.00021 0.033 0.035 0.0906* 0.0259 0.0245 0.0211
(0.911) (0.913) (0.323) (0.253) (0.061) (0.543) (0.371) (0.518)
CEOpower 1.566** 0.0914 0.971 2.191*** 3.251*** 0.901 1.812*** 1.971***
(0.028) (0.145) (0.249) (0.000) (0.005) (0.389) (0.002) (0.002)
CEOoverconfidence 0.00112 0.0011* 0.051*** 0.033 0.0242 0.0032 0.046** 0.0581*
(0.941) (0.074) (0.009) (0.447) (0.490) (0.857) (0.047) (0.086)
Pconnection 0.141 0.00522 0.039 0.123 1.080*** 0.0513 0.222 0.0408
(0.420) (0.654) (0.890) (0.310) (0.001) (0.807) (0.171) (0.776)
magshare 0.405 0.014 0.157 0.114 0.426 0.692* 0.382 0.00716
(0.144) (0.612) (0.875) (0.561) (0.427) (0.060) (0.195) (0.975)
magsalary 0.0539 0.00037 0.054 0.119* 0.328** 0.012 0.137* 0.0223
(0.577) (0.735) (0.462) (0.096) (0.044) (0.909) (0.059) (0.767)
TOP1 0.864** 0.0035 0.710** 0.447 0.38 0.584 0.625** 0.259
(0.023) (0.428) (0.045) (0.101) (0.548) (0.166) (0.028) (0.386)
lnasset 0.136** 0.0026 0.446*** 0.141*** 0.346*** 0.208** 0.356*** 0.122**
(0.047) (0.162) (0.000) (0.010) (0.007) (0.030) (0.000) (0.034)
Lev 0.202 0.012 0.334 0.239 1.090*** 0.625** 0.126 0.410*
(0.504) (0.402) (0.259) (0.311) (0.006) (0.034) (0.661) (0.089)
OCF 0.171 0.0031 0.696 0.042*** 0.386 0.717 0.626 0.502
(0.815) (0.512) (0.112) (0.001) (0.657) (0.273) (0.124) (0.213)
FirmGrowth 0.04 0.00163 0.067 0.004 0.497 0.0295 0.0966 0.0726
(0.691) (0.407) (0.573) (0.961) (0.144) (0.782) (0.311) (0.483)
Age 0.0163 0.0011 0.015 0.001 0.056*** 0.0158 0.0093 0.0131
(0.216) (0.499) (0.318) (0.884) (0.005) (0.351) (0.418) (0.189)
Listyear 0.0168 0.00061 0.022 0.012 0.091** 0.0143 0.0328 0.0098
(0.574) (0.743) (0.329) (0.594) (0.012) (0.648) (0.103) (0.665)
_cons 1.4 0.0407 9.036*** 15.52*** 4.732* 2.387 11.06*** 15.68***
(0.458) (0.275) (0.000) (0.000) (0.085) (0.287) (0.000) (0.000)
Industry Yes Yes Yes Yes Yes Yes Yes Yes
Year Yes Yes Yes Yes Yes Yes Yes Yes
N 166 3018 2765 4177 97 122 3470 3455
adj. R2 0.062 0.024 0.18 0.12 0.153 0.084 0.168 0.113
Note: Standard errors of regression coefficients are in parentheses. ***, **, and * represent coefficients that are significant at the 1%, 5%, and 10% levels, respectively.

7 Conclusions

This study examines the M&A tendencies and performance of Chinese Shanghai and Shenzhen A-share companies from 2002 to 2017, using the implementation time of September 2006 as the dividing line. The findings of this paper are as follows: First, Chinese A-share listed companies exhibit stronger M&A tendencies after policy change. Second, while the performance of the acquirer initially drops after a short period of upswing, it rises continuously in the long run. These conclusions remain robust after a series of tests. Specifically, M&A performance increases significantly around the announcement, followed by a gradual decline in the cumulative abnormal returns; however, as the effects of market rules gradually take hold, the performance three years after the M&A and the market performance show a continuous rebound. This indicates that in the long run, policy changes are conducive to improving Chinese firms' M&A performance and market efficiency. This paper also finds that policy change has a more significant impact on M&A tendencies in state-owned and large-scale samples, and that exemption from the mandatory tender offer obligation positively moderates the relationship between policy change and firms' M&A performance. Overall, the implementation of market rules appears to be more adaptive and efficient in the long run in China, relative to equal opportunity rules. This paper contributes to the research on the economic consequences of M&A in the tender offer system and offers insights for China to optimise acquisition policies and promote the high-quality development of its capital market.
This study incorporates the application of market rules into the analytical framework, examines the impact on firms' M&A tendencies and performance after the policy change, and explores the effects. However, future research should further investigate the internal mechanism of the role of market rule implementation on firms' M&A tendencies and performance.

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