Does State Ownership Have an Influence on the Length of M&A Deal?

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Does State Ownership Have an Influence on the

Length of M&A Deal?

Evidence analysis from China

University of Groningen

Faculty of Economics and Business

Master Thesis International Economics and Business

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Abstract

This research studies the influence of state ownership on the length of merger and

acquisition deals in China, using data from China of a 15-year period from 2001 to

2015. The main conclusion are whether the acquirer is a SOE or a POE does not have

a significant influence on the length of M&A deal; however, the M&A process takes

significant longer length when the target is a SOE than a POE, holding other conditions

constant. Additional robustness check presents a consistent result.

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1. Introduction

Increasing competition pressure is one of the most significant factors results in Merger

and Acquisition (M&A) activities of most of the companies. Globalization, fast

economic growth and maturation of emerging markets increase company’s competitive

pressure (Caiazza and Volpe, 2015). In order to remain competitive in the market, many

companies have merged with each other with motivations of expend to new markets,

incorporate new technologies and enhance revenue (Haspeslagh and Jemison, 1991;

Vazirani, 2015). According to Sarch et al. (2016), global M&A activity in 2015

increased 43% compared to 2014, with a total deal value of US$ 4.8trn (up from

US$ 3.3trn). Specially, there is significant regional M&A boom in Asia Pacific. The

report of the same authors (Sarch et al., 2016) indicate that this M&A boom in Asia

Pacific is largely driven by the demand of regional expansion of Chinese companies

and a result of increased regional investment by Japanese companies.

Many factors play important role and influence the process when M&A occurs, such as

i) the complete and clear objectives, goals and scope of the M&A project, ii) Project manager’s competence, iii) communication and information sharing, iv) M&A advisory firm’s resource and ability, v) financing scheme and vi) the legal and institutional environments, among which the type of ownership structure of involved companies

may be one of the most important ones (Wong and O’Sullivan, 2001; Feito-Ruiza et al.,

2014). China has recently experienced significant institutional change in terms of

ownership structures (Ralston et al., 2006), having evolved from the domination of

SOEs in the communist era to the development of local Chinese POEs (Liao, 2015). SOEs and POEs are simultaneously existing in China’s market, however, those SOEs and POEs in China are subject to different social codes, as well as differentiated social

identities (Liao, 2015). Some of the SOEs are clustered, and it indicates that

governmental and social institutions offer normative guidelines for companies,

designed to improve social welfare and employment, while imposing regulatory

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5 indicates the development of free market mechanisms aimed at increasing the efficiency

of market transactions, along with the presence of norms associated with the

encouragement of entrepreneurship (Park et al., 2006).

National development plan and government intervention in economic activities is a significant character in China’s economy, and this has a strong influence in M&A process. The forces of China’s M&A activity are twofold. The first force is

endogenously from the company per se. Chinese companies desire to access technology

(e.g. Shanghai Electric acquiring Ansaldo Energia1), infrastructure (e.g. China General

Nuclear Power Corporation is interested in Hinkley Point nuclear plant2), as well as real

estate (e.g. Chinese real estate developer ABP and Royal Albert Docks3). Another force

is exogenously from the perspective of government’s policy. One Belt One Road

(OBOR) is a new strategic development initiative that is focusing on the ideas of a “silk road economic belt” which connects China with Europe through Central and Western Asia, and a “maritime silk road” which connects China with Southeast Asian countries, Africa and Europe (Willers et al., 2015). The OBOR strategy is increasing enthusiasm

for M&As among Chinese companies, driving players in a variety of sectors to

proactively look for M&A targets in overseas markets, including energy and resources,

industry, agriculture, and financial services (Willers et al., 2015; Sarch et al., 2016).

The motivation of this research originates from the fact that state ownership in China

was dominant from during the communist period before the reform (1978), and is still

the majority form of ownership in key economic sectors. Therefore the analysis on

governmental influence, represented by SOEs during the M&A activities would

1_{Shanghai Electric to buy Ansaldo Energia stake. [Online] Available at:}

http://www.ft.com/cms/s/0/4e8e4cc4-d6ba-11e3-b251-00144feabdc0.html#axzz49xr6mMl0

2_{China may take over Hinkley Point nuclear project, claims Lord Howell. [Online] Available at:}

http://www.theguardian.com/uk-news/2016/may/12/china-may-take-over-hinkley-point-nuclear-project-claims-lord-howell

3_{Little China rising in the east: London's new docklands business district to become Asian hub. [Online]}

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6 contribute to the further understanding of SOE’s behaviour in China’s dynamic

economy. Previous study indicates that China’s SOEs may have governmental support

to help them acquire target companies in industries under tight government control, and

SOEs may enjoy favourable financial support such as government subsidies and

privileged bank loans (Zhou et al., 2015). The dominant owner of SOEs is very often

the government, and thus SOEs are considered to have more political connections than

POEs. Fan et al. (2007) indicate that the decisions on M&As of SOEs are ultimately

approved by the government. The uniqueness of the Chinese economy is that corporate

investment and financing decisions are significantly influenced by government

intervention (Firth et al., 2008). Therefore, state ownership is expected to have

significant impact on the M&A activities.

However, previous studies have either only analysed state ownership in China, or

focused on the M&As in China. The analysis of this investigation differs from previous

work by linking state ownership of Chinese companies to their M&A activities. Given

the importance of the emerging Chinese financial markets in the global economy, the

accompanying importance of the privatization of SOEs in general (Francis et al., 2009),

as well as the desire of companies to conduct the M&A activities, it is important to have

an understanding of the influence of state ownership in the M&A process.

More specifically, this research investigates the impact of state ownership on the length

of M&A deal. Since the government plays a role and helps with SOEs to acquiring the

targets by different means (Zhou et al., 2015; Shleifer and Vishny, 1994), it is expected

to take a shorter length of M&A deal when the acquirer is a SOE than a POE. In contrast,

it is expected to take a longer length of M&A deal when the target is a SOE than a POE.

The fact is that when a SOE privatizes, it seldom sells all of its stakes or controlling

shares, this may due to the legal structure of China (Bortolotti et al., 2002).

In order to figure out the above assumptions, this paper addresses the question of

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2. Theory and Hypotheses

2.1 Mergers and Acquisitions

A merger is the joining or integration of two previously discrete entities, it occurs when

two companies integrate to form a new company with shared resources and corporate

objectives (Ghobadian et al., 1999; Horwitz et al., 2002). Acquisition is widely known

as a business takeover which is a process of buying out another business (Daniel and

Metcalf, 2001), and it occurs when one organization acquires sufficient shares to gain

control or ownership of another organisation (Horwitz et al., 2002). Mergers and

Acquisitions are often used interchangeably since the result is the same that one

company takes control over another (Halperin and Bell, 1992). In this paper, M&A

refers to the cases of either mergers or/and acquisitions.

There are various motives for M&As. A primary motive is market expansion.

Acquisition of another organisation with complementary product of geographic spread

can access the resources of place, people, and regulatory approval in a short time, which

enables expanding into new product categories of geographical territories (Aurora et al.,

2011). Another important motive is diversification. Acquiring a different line of

business reduces the instability of earnings, and diversification is undertaken to shift from the acquirer’s core product lines into those that have higher growth prospects (Amihud and Lev, 1981). The motive to create synergy is also often observed in M&As,

and it is based on the notion that the merger of two companies can create greater

shareholder value than if they are operated separately (Vazirani, 2015). When Glaxo

Welcom and Smithkline Becham merged, they not only gained market share, but also

eliminated competition between each other (Aurora et al., 2011), and thus enable them

to create the world's largest drug company4. Inefficient management, agency problems,

4_{Glaxo Wellcome-SmithKline Beecham merger creates world's largest drug company. [Online] Available at:}

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8 and tax considerations are some other common motives of M&As (Jensen and Ruback,

1983; Machiraju, 2003; Vazirani, 2015).

The process and performance of M&A have been evaluated in many perspectives.

According to Vazirani (2015), there are four different schools of thoughts in M&A

theories: the capital market, the strategic management, the organization behaviour, and

the process perspective. The capital markets school studies the impact of M&As on

value creation at a societal level (Caves, 1987). The strategic management school has

the objective to relate the performance of the acquirer and target (Vazirani, 2015). The

organizational behaviour research focuses on two questions: how people respond to

M&A situations and what is the impact of M&A on the organization (Marks and Mirvis,

1985). Finally, the process perspective is focussed on the actions taken by the

management to guide the post-acquisition integration process (Vazirani, 2015). The

benefits and the synergies are depending on the management’s efforts to manage the

post-acquisition process in an effective manner (Shrivastava, 1986).

2.2 The M&A Process

The process of M&A normally starts from the forming of motives but the completion

point variates depending on individual cases. Caiazza and Volpe (2015) conduct a

structured literature review and divide M&A process in three phases based on previous

studies (Brocke and Sinnl, 2011; Soni and Kodali, 2011; Gogan et al., 2013). The first

phase is multilevel due diligence, which is based on multiple levels of analysis for

identifying risks and opportunities of the markets, industry characteristics and strength of the target’s competitive positioning (Caiazza and Volpe, 2015). The multilevel due diligence helps the acquirer to understand the financial statements of the target business,

assess the working capital needs, identify cash trapped in subsidiaries, reconcile

accounting differences, and facilitate combination of human resources (Schweiger et

al., 1993; Morosini, 1998; Ranft and Lord, 2002; Schuler et al., 2004). The second

phase is integration, which requires a large number of activities to create a new entity

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9 2015). Integration is an evolutionary phase which involves decisions regarding the level of integration, organizational cultures’ combination, and human capital management (Haspeslagh and Jemison, 1991; Morosini, 1998; Cartwright and Cooper, 1990). The

final phase is assessment and performance. According to Caiazza and Volpe (2015),

the operation of M&A between two companies is very complex that its success depends

on the ability to manage each phase of the process, thus the process of assessment and

performance has to be implemented at all the hierarchical levels and need a common

vision well diffused in both companies. This division of M&A process has simplified

the complicated strategic considerations of an M&A into structural phases. However,

this division is not an optimal one for the empirical analysis of this study.

A clearly defined M&A process is important for research that interested in the length

of M&A deal, while the length of M&A deal might range from different periods under

different definitions. Boone and Mulherin (2007) provide an empirical analysis of the

acquisition process, and they divide the process into two general phases: the private

takeover process and the public takeover process. Figure 1 illustrates the two phases:

the private takeover process is the period from the private initiation to the first public

announcement of the takeover; and the public takeover process is the period from the

first public announcement of the takeover to the resolution of the takeover (Boone and

Mulherin, 2007). The study of this paper focuses on the second phase, that is, the public

takeover process. Therefore, the length of an M&A deal in this paper is counted from

the date of announcement to the date of completion (resolution).

Figure 1: Timeline of the Acquisition Process

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2.3 M&As in China

M&As in China surged by 55% in terms of both volume and value in 2014, with 6,899

transactions totalling $407 billion were completed (Brown and Chan, 2015). While still

not quite yet in the same league as the U.S., China is catching up fast (Perkowski, 2015).

In addition to the numbers, the nature of M&A activity in China is also changing:

transactions in the technology, consumer-related, and financial industry sectors are

becoming more important, reflecting the development of a broader based Chinese

economy (Perkowski, 2015). As market entry thresholds come down and more capital

become available in local markets, many multinationals are now able to channel their

foreign direct investment towards Chinese acquisition targets (Pang and Cainey, 2009).

As a result, M&A deals in China become progressively larger, spread across a much

wider range of industries ranging from energy to manufacturing and services, target at

both distressed companies and industry frontrunner, and increasingly focus on the

ownership structures of acquired companies (Pang and Cainey, 2009)

Despite the booming M&A activities in China, Yang et al. (2015) point out that

successful M&A in China is by no means easy: every step of the process, beginning

with due diligence, presents a unique set of challenges, and the most critical step is the

regulatory approval. The industry, location of the target, and whether the target is a SOE

all affect the nature and complexity of the M&A process (Yang et al., 2015). The

Ministry of Commerce (MOFCOM), whose purview ranges from antitrust, foreign

investor approval, to national security, is at the centre of the process (Yang et al., 2015).

Yang et al. (2015) further indicate that if the target is a listed company, the China

Securities Regulatory Commission (CSRC) will be involved, and the acquisition of

SOEs have to be reviewed by the State-owned Assets Supervision and Administration

Commission of the State Council (SASAC). A specific description of the three key

regulatory authorities for M&As in China is presented in Appendix I.

There have been both successes and failures of M&A activities in China. Swiss food

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11 Group in 2011 (Tong, 2011). The reason behind the success, according to Yang et al.

(2015), is that the acquirer understands the importance of prioritizing the authorities of

which they need to communicate with, and both of the acquirer and target are able to

speak from the same script about the business logic and the social impact of the deal.

Within ten days of signing the acquisition agreement, the president of Yinlu prepared a

report on the transaction to the local government, explaining the deal and seeking to

ease any concerns over the potential disappearance of Chinese national brands, and providing the estimates of future revenue as well as the combined company’s contribution to the national and local economy, including the taxes to be paid (Yang et

al., 2015). Yinlu together with Nestlé’s efforts helped them in the approval process.

However, not all of the M&A cases are successful, for example, the high-profile bid by

Coca-Cola for juice maker Huiyuan, a public listed Group, came to a failure following

long and costly negotiations (Pang and Cainey, 2009). In the year of 2009, China

rejected a $2.4 billion Coca-Cola deal that would have been the country’s biggest

foreign takeover, the Ministry of Commerce (MOFCOM) ruled against Coke’s

proposed acquisition of Huiyuan Juice on competition grounds, saying the move would

hurt smaller domestic companies and limit consumer choice (Tucker et al., 2009).

2.4 SOEs and the Reforms in China

Different types of companies play important roles in a dynamic economy such as China.

In the past decades , the Chinese economy have been fundamentally changed through

several reforms characterized with a serial of institution changes concerning the market,

enterprises and the government in the novel form of “transitional institutions” (Chen

and Werle, 2014). SOEs were the backbone of the Chinese economy before the

beginning of the reforms in 1979 (Fei, 2004). Since then, a dynamic private sector

emerged, and behind China’s surge in economic development lies the emergence of a

non-state sector includes private owned companies, joint ventures, collective-owned

enterprises and other forms of private enterprises (Fei, 2004). Nevertheless, SOEs are

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12 The SOE reform is a major concern in China’s overall economic reform (Ralston et al., 2006). The economic reform saw incremental liberalisation of agriculture and the

non-state sector (McKinnon, 1994; Fishman, 2005) and the gradual establishment of the

necessary institutions to facilitate “marketization” (White and Liu, 2001; Cooke, 2008). Central to this process has been the “marketization” of SOEs (Hassard et al., 2010). SOEs have been characterized as possessing a lack of managerial ﬂare, little concern for proﬁt, low employee motivation, with a tendency to maximize corporate size and as being ready for dismembering (Meyer et al., 2002). Some views even argue that the

less open and less transparent SOEs pose a problem for the further development of the

market-based practice in the economy (Woetzel, 2008).

To avoid unprepared failure, the SOE reform was very experimental in the beginning.

The dual-track approach was applied to the ownership reform in China: one track

represents market-oriented institutions that have emerged in a parallel economy, and

this economy comprises non-state enterprises with diverse forms of ownership such as

POEs; the other track is made up of the retained SOEs, and reforms were restricted to

conservative policy measures on the fringe of the economy on this second track through

minor improvements to enhance productivity (Opper, 2001; Sachs and Woo, 1997).

After two and a half decades of the reforms, SOEs no longer totally dominate China’s

economy (Ralston et al., 2006). However, SOEs’ signiﬁcance to the country is not

undermined, and it has been China’s ambition to build the national teams in several key

industries such as automotive, pharmaceutical, electronics, and petrochemical, in which

SOEs have a dominant presence (Nolan, 2001). As stated by Ralston et al. (2006), today’s SOEs in China have substantially transformed to approximate a conﬁguration desired by the Chinese government when it began the SOE transformation, in order to

make them competitive in a global perspective. In addition, while the SOEs continue to

focus on overseas acquisitions in the energy and natural resource fields, the POEs are

more interested in acquiring technologies and brands that they can bring back to China

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2.5 State Ownership and M&As

China’s government has continued to encourage M&As to create large and competitive

local conglomerates that can compete with large foreign enterprises for decades, this

has created a massive drive for thousands of SOEs and POEs to be merged and acquired

(Chia et al., 2011). Previous studies have done some work to examine the role of state

ownership in M&A activities. Zhou et al. (2015) find that SOE acquirers outperform

POE acquirers in the M&A activities. The government in China continues to play a

decisive role in the economy. The uniqueness of the Chinese economy is that the

corporate investment and financial decisions are significantly affected by government

intervention, and a large proportion of companies are owned or controlled by central or

local government agencies (Chen et al., 2008). As a direct means of resource

reallocation and ownership transfer, M&As are therefore influenced by the government

to achieve political and economic goals (Zhou et al., 2015). But how and to what degree

Chinese government is influencing the economy is very hard to be mapped out.

Therefore, if the question is focused on whether the SOE is performing differently

compared to POE in M&A process, it may be a step towards a solid answer to the

question. The first hypothesis is then formulated as:

Hypothesis 1: The M&A process takes shorter length if the acquirer is a SOE than a POE, holding other conditions the same.

According to Yang et al. (2015), as mentioned in previous text, the acquisitions of SOEs

need to be reviewed by the State-owned Assets Supervision and Administration

Commission of the State Council (SASAC), and normally this process takes two to

three months. The aim of this process is to sell state-owned assets at a fair price and in

a transparent process, at the same time try to avoid public outcry (Yang et al., 2015).

The second hypothesis for this study is thus formulated as:

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3. Methodology

3.1 Data and Sample

The data used by this research is from Orbis, which provides a database of company

information and business intelligence for individual countries, regions and the world,

combining information from more than 140 sources and covers over 200 million

companies; and from Zephyr, which contains information on M&A, IPO, private equity

and venture capital deals and rumours. Both of Orbis and Zephyr are the products

provided by Bureau van Dijk5 which possess databases of company information and

business intelligence for individual countries, regions and the world.

To ensure a sufficient sample size, a 15-year period data from 2001 to 2015 are used.

This period is chosen for the reason that China has entered into WTO in 2001, and the

termination of discriminatory measures of the private sector has been leading to a rapid growth in Chinese companies’ participation in the global competition by engaging in overseas M&As (Chen and Werle, 2014).

The final sample consists of 523 completed M&A transactions that were announced

between 1 January 2001 and 31 December 2015 in China. The information of each

transaction includes: i) from Zephyr - announced date, completed date, deal value, deal

method of payment, acquirer country code, target country code, acquirer name, target

name, acquirer BvD ID number and target BvD ID number6; ii) from Orbis – number

of employees, NACE industry code (4 digits), and ultimate owner. The threshold7 used

to define the ultimate owner (UO) in this study is 50.01%. Table 1 illustrates the

detailed sample selection process, starts with the exporting of data from Zephyr and

Orbis, to the procedure of combine the data from this two sources.

5_{More information is available at the website of Bureau van Dijk: http://www.bvdinfo.com/en-gb/home} 6_{The BvD ID number (exported from Zephyr) is used as a search criterion for corresponding company}

information in Orbis.

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Table 1: Sample Selection Process

Step Condition Observations

Left

Zephyr

1) Restrict the time period: on and after 01/01/2001; up to and including 31/12/2015 (announced deals)

1,186,776

2) Restrict to current deal status: completed 1,095,357 3) Restrict to specific country: China ( including acquirer or target ) 52,490 4) Methods of payment: cash, cash assumed, converted debt, debt assumed,

deferred payment, earn-out, loan notes, shares, other

34,107

5) Deal value: all deals with known value 31,194 6) Restrict to transactions that both of the acquirer and the target have a

country code

18,515

7) Restrict to transactions that both of the acquirer and the target have a BvD ID number

10,296

8) Exclude the transactions of which the announced date and the completed date are in the same day

4,445

Orbis

9) Search for the corresponding company information in Orbis (acquirer and target) by using the BvD ID numbers exported from Zephyr

6,120

10) Number of employees: all companies with a known value 2,293 11) NACE Code: All companies with a known code 2,209 Combine data from Zephyr and Orbis8

12) Restrict to transactions of which the number of employees information are available for the target

1,801

13) Restrict to transactions of which the NACE 4 digits industry code are available for both acquirer and target

523

3.2 Variables

The dependent variable of this study is the length of the M&A process, and it is counted

as the difference in days between the announcement date and the completion date.

The independent variables are the ownership types of the acquirer and the target. The

acquirer can be a SOE or a POE, so does the target. This research first answer the

question of whether SOE acquirers face a shorter length in the M&A process than the

8_{The BvD ID numbers are available from both Zephyer and Orbis, and thus are used as the intermediary to}

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16 POE acquirers, and then figure out the question of whether it takes longer length to

acquire a SOE target than a POE target.

The M&A activity is determined by various factors: the value of deal, the size of target,

the method of payment, whether the M&A is cross-border, and whether the acquirer

and the target are in the same industry (O'Sullivan and Wong, 1999; Weitzel and McCarthy, 2011; Alexandridis et al., 2012; Wong and O’Sullivan, 2001; Yang et al., 2015). Those influencing factors are included in this study as control variables.

The first control variable is the value of deal which is considered to have an impact on

the M&A deal length. According to O'Sullivan and Wong (1999), deals of larger value

are more attractive and are thus organized more carefully in order to minimize the

probability of failure. Thus the larger the value of deal, the longer length of M&A is

expected.

The second control variable is the size of target. Weitzel and McCarthy (2011) provide

evidence that larger companies perform less well in M&As. It is reasonable since when

a company has larger number of employment, it is harder for them to make a change or

a finish a transition. Additional support is from Alexandridis et al. (2012) who indicate

that the complexity associated with large targets makes it more difficult for acquirers.

Thus, it is expected that the larger the target, the longer the length of M&A deal.

The third control variable is the method of payment. According to Wong and O’Sullivan

(2001), if a bid is financed by cash, the precise value of the bid to target shareholders

is known and consequently shareholders possess better information when deciding

whether to accept or reject the bid, while bids financed by other forms of payment have

a higher degree of uncertainty for shareholders. Sudarsanam (1995) finds that the

influence of method of payment is significant: on the one hand, when pure equity or

equity plus cash is offered, the defence is more successful; on the other hand, when

cash is involved as the payment, it improves the chances of a successful bid. In addition,

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17 to be completed. Therefore, it is expected to take shorter length of an M&A deal when

cash is involved as the payment method.

Then, whether the M&A is cross-border is included in this model as another control

variable. Yang et al. (2015) point out that in the regulatory approval process of M&A,

westerners often misinterpret the impact of the Chinese cultural phenomenon of

“guanxi”, which they misconstrue as a murky system of “connections” or

“relationships”. However, “guanxi” is actually rooted in the empathy that concern for someone else’s interests when taking an action of one’s own (Yang et al., 2015). As a foreign company, they need to prepare for this regulatory approval process thoroughly,

and it takes time for them to build up this so called “guanxi”, that is, mapping out the various stakeholders’ interests and concerns. Thus, cross-border M&A deals are expected to face a longer length of the M&A process.

Another factor which may have an impact on the M&A deal length is whether the

acquirer and the target are in the same industry, since the antitrust approval is specially

required when the acquirer and the target are in the same industry (Yang et al., 2015).

Among all the regulatory authorities for M&As in China, the antitrust review process

is the most complex, they consider a wide variety of factors, including the views of the

public, competitors, and industry groups (Yang et al., 2015). Thus, the M&A length is

expected to be longer if the acquirer and the target are in the same industry.

3.3 The Econometric Model

The least squares (LS) method is applied in this study, and the basic econometric

estimation equation takes the following form:

Length = α + β1OWN_Acq + β2OWN_Tar + β3Value + β4Size_Tar + β5Payment+ β6Border + β7Industry + e

where α is the constant parameter and e is the error term. β1 to β7 are the coefficients of

each variable, which represent the estimated marginal effect of the explanatory variable

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18 In order to interpret the coefficients (marginal effect) of the dummy variables in the

Log-linear Model where the dependent variable is in the form of natural logarithm and

the independent variable is a dummy, a calculation is needed. For example, to interpret the coefficient β1 of the acquirer ownership,9 based on the calculation by Hill et al. (2011), the length difference between SOE and POE is:

ln(length)SOE – ln(length)POE = ln(lengthSOE/lengthPOE) = β1

by using the property of logarithms that ln(x) – ln (y) = ln(x/y). These are natural

logarithms and the anti-log is the exponential function:

lengthSOE/lengthPOE = eβ1

Subtract 1 from each side to obtain:

lengthSOE/lengthPOE – lengthPOE/lengthPOE

= (lengthSOE –lengthPOE)/lengthPOE

=eβ1 – 1

Therefore, the percentage difference between M&A deal lengths of SOE and POE is

100(eβ1 – 1)%. The same procedures are applied for interpreting the coefficients of other

dummy variables from the estimation equation.

Table 2 summarizes the types and measures of each variable. Length is measured by

the natural logarithm of the deal length. OWN_Acq is a dummy variable represents

whether the acquirer is a SOE, while OWN_Tar represents whether the target is a SOE.

Value is measured by the natural logarithm of the deal value in million Euro. Size_Tar

refers to the size of target and is measured by the natural logarithm of number of

employees for target. Payment is a dummy variable that refers to the method of

payment, the transaction can be financed by cash or by other kinds of payment such as

converted debt, debt assumed, deferred payment, earn-out, loan notes, and shares

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19 (Zephyr). Border is a dummy variable which refers to whether the M&A is cross-border.

The last variable Industry is also a dummy variable, it represents whether the acquirer

and the target are in the same industry.

Table 2: Variable Specification

Variable Type Measure

Length of Deal Dependent Natural logarithm of the deal length Ownership of Acquirer

(Dummy)

Independent - Equals to 1 when the acquirer is state-owned - Equals to 0 when the acquirer is not state-owned Ownership of Target

(Dummy)

Independent - Equals to 1 when the target is state-owned - Equals to 0 when the target is non state-owned Value of Deal Control Natural logarithm of the deal value

Size of Target Control Natural logarithm of number of employees for target Method of Payment

(Dummy)

Control - Equals to 1 if the transaction is financed by cash - Equals to 0 if the transaction is financed by other

kinds of payment Cross-Border

(Dummy)

Control - Equals to 1 if the M&A is cross-border - Equals to 0 if the M&A is domestic Industry

(Dummy)

Control - Equals to 1 when the acquirer and the target are in the same industry

- Equals to 0 when the acquirer and the target are in different industry

The multiple regression model requires several preconditions on the explanatory

variables and the random error (residuals) e. According to Hill et al. (2011): i) any one

of the explanatory variables should not be an exact linear function of the others; ii) the

residuals need to have a normal probability distribution; iii) the random errors need to

be homoscedastic. In this study, the VIF (Variance Inflation Factor) value is used to test

for multicollinearity, the Shapiro-Wilk W test is produced for testing normality of

residuals, and the Breusch-Pagan test is performed to test Homoscedasticity.10

10_{“Stata Web Books, Regression with Stata, Chapter 2 - Regression Diagnostics”, available at:}

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20

4. Empirical Results

4.1 Descriptive Analysis

Table 3 provides the basic descriptive statistics of the variables in the regression

model.11 The observations for each variable are 523. The length of M&A deal ranges

from 1 to 812 days with a mean of 138 days. 21.9% of the acquirers are SOE, and 78.1%

of the acquirers are POE. Besides, only 7.6% of the targets are SOE while 92.4% of

them are POE. The deal value ranges from 0.18 to 28,030.48 million Euro, with a mean

of 313.5 million Euro. The number of employees ranges from 5 to 493,583, with a mean

of 9,313. In addition, cash is involved in 81.5% of the transactions. 21.4% of the

transactions are cross-border while 78.6% of them are domestic. 34.4 % of the M&As

are those that the acquirer and the target are in the same industry.

Table 3: Descriptive Statistics

Variable Observation Mean Std. Dev. Min Max

Deal Length 523 137.9 130.64 1 812 Acquirer Ownership 523 0.219 0.4145 0 1 Target Ownership 523 0.076 0.2660 0 1 Deal Value 523 313.5 1472.9 0.18 28030.48 Target Size 523 9312.8 33993.3 5 493583 Payment Method 523 0.815 0.3890 0 1 Cross-border 523 0.214 0.4106 0 1 Industry 523 0.344 0.4755 0 1

Table 4 presents the correlation matrix of the variables. The correlation between

acquirer ownership and the length of M&A deal is positive but not strong (0.05). The

correlation between target ownership and the length of M&A deal is 0.13, suggesting a

positive relationship. It should also be mentioned that the deal value is positively related

to deal length (0.38), which means the larger the deal value, the longer the M&A deal

length. However, the payment method shows a negative correlation with the length,

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21 suggesting it takes shorter time when the transaction is financed by cash. Additionally,

influence test is not suggestive of multicollinearity, the mean VIF scores is 1.15 and it

is well below the suggested threshold (Appendix III: Checking for Multicollinearity).

Table 4: Correlations (1) (2) (3) (4) (5) (6) (7) (8) (1) Deal Length / (2) Acquirer Ownership 0.05 / (3) Target Ownership 0.13 0.11 / (4) Deal Value 0.38 0.18 0.07 / (5) Target Size 0.04 0.17 0.11 0.24 / (6) Payment Method - 0.23 0.04 0.08 - 0.31 0.05 / (7) Cross-border 0.04 0.11 - 0.06 0.27 0.03 0.09 / (8) Industry - 0.01 0.05 - 0.03 - 0.02 0.15 - 0.11 - 0.06 /

4.2 Results

Table 5 below provides the multivariate regression results. Columns (1) consists of the

base model of controls: the M&A deal value, target size, payment method, whether the

M&A is cross-border, and whether the acquirer and the target are in the same industry.

Among those controls, only the coefficients of deal value and payment method are

significant. The coefficient of Deal Value is positive (0.2389), indicating a positive

effect on the length of M&A that the larger the value of the M&A deal, the longer the

length of M&A process. This result is supported by O'Sullivan and Wong (1999). And

a 1% increase in the deal value is estimated to increase the length of M&A deal by

0.24%. However, the coefficient of Payment Method is negative (- 0.3627), suggesting

a negative effect if the transaction is financed by cash. This is consistent with the opinions of Wong and O’Sullivan (2001), Sudarsanam (1995), and Muehlfeld et al. (2007). The percentage difference in the days of completing the M&A deal between

financing by cash and by other payments is - 30.4%.12

12_{Based on the calculations in section 3.3, the percentage difference in M&A length is: 100(e}-0.3627_{– 1)% =}

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22 The dependent variables - acquirer ownership and target ownership - are included in

column (2) of Table 5, and the minimum percentage to characterize the path from a

subject company up to its ultimate owner (UO), in this situation, is 50.01%. The

significance levels and signs of coefficients for the control variables all keep the same

as in the first model, and the magnitude change is very small.

Table 5: Regression results

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

The main result of the interest for this study is the coefficients of acquirer ownership

and target ownership. The coefficient of Acquirer Ownership is insignificant, and it can

be concluded that whether the acquirer is a SOE or POE does not have an impact on

the length of M&A deal, holding others constant. The coefficient of Target Ownership,

however, is positive and significant (0.5710). It can be concluded that companies face

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23 longer time to complete the M&A deal if the target is a SOE than a POE, holding others

constant. The percentage difference in the days of completing the M&A deal is 77.0%.13

In column (3) of Table 5, a different threshold is used to define the SOE: the minimum

percentage to characterize the path from a subject company up to its ultimate owner

(UO), in this situation, is 25.01%. The significance levels and signs of coefficients for

all the variables all keep the same compared to the first and second models, suggesting

a consistent conclusion. In addition, in this case, the coefficient of Target Ownership is

still positive and significant, only the magnitude is slightly lower (0.3440). Thus, the

same conclusion can be drawn that companies face longer time to complete the M&A

deal if the target is a SOE than a POE and the percentage difference in the days of

completing the M&A deal is 41.1%.14

4.3 Robust Results

The result of Shapiro-Wilk W test15 indicates that the residuals are not normally

distributed, and the result of Breusch-Pagan test16 shows that the variance of the

residuals is heteroscedastic (non-constant). The existence of heteroscedasticity means

the least squares assumption (precondition) is violated, thus the standard errors

computed for the least squares estimator are incorrect and the results may be misleading

(Hill et al., 2011). Some additional robustness checks have been conducted through

performing the regression by using the heteroscedasticity robust standard errors. The

robust results are presented in Table 6.

13_{Based on the calculations in section 3.3, the percentage difference in M&A length is: 100(e}0.5710_{– 1)% =}

100(1.7700 – 1)% = 77.00%.

14_{Based on the calculations in section 3.3, the percentage difference in M&A length is: 100(e}0.3440_{– 1)% =}

100(1.4106 – 1)% = 41.06%.

15_{The Shapiro-Wilk W test is a test for checking normality of residuals. The p-value is based on the assumption}

that the distribution is normal. See Appendix IV: Checking Normality of Residuals.

16_{The Breusch-Pagan test is a test for checking homoscedasticity of residuals. The null hypothesis that the}

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24

Table 6: Robust Result

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Overall, the robust results are consistent with previous conclusions: i) whether the

acquirer is a SOE or POE does not have an impact on the length of M&A deal, holding

others constant; ii) companies face longer time to complete the M&A deal if the target

is a SOE than a POE, holding others constant.

However, there are three small differences. Firstly, in column (2) of Table 6, the

coefficient of Acquirer Ownership is less significant (p<0.05) than the counterpart

(p<0.01) in Table 5. Secondly, the coefficients of Payment Method are more significant

(p<0.01) than the counterpart (p<0.05) in Table 5. Thirdly, the adjusted R2 are generally

slightly higher than those in Table 5.

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25

5. Conclusion

The main conclusion of this study is SOE and POE does perform differently in M&A

process, demonstrated by the result: the M&A process takes significant longer length

when the target is a SOE than a POE. However, SOE acquirer and POE acquirer do not

perform differently measured by the length in M&A process. The first hypothesis is not

supported by the results of this study, but the second hypothesis is supported by the

finding.

There are several limitations of this study and suggestions for further research:

 The reliability of data based on Chinese market could be a concern because there is a lack of independent data research companies in Chinese market. Further studies

could generate data from different independent sources.

 This study investigates the difference in M&A process between SOE and POE using length as a measurement of dependent variable. However, there are several

other options such as company performance, post-M&A stock price, etc. The

reason of this study using only one specific variable is due to the limitation to

access other variables in good quality in a short time.

 A large number of Chinese enterprises have been experienced the transition from state owned to private owned. When a SOE privatizes, it seldom sells all of its

stakes or controlling shares (Bortolotti et al., 2002). In this paper, although some

enterprises are coded as private owned, they keep the old state-owned enterprises’

concept and mode of operation. It may have an influence on the M&A procedure,

thus bias may occur due to this reason. The suggestion for further study is to

investigate the M&A activities of those enterprises which are newly experienced

the transition.

 This study introduces industry as a control variable, with industry refers to whether the acquirer and the target are in the same industry, since the antitrust approval is

specially required when the acquirer and the target are in the same industry (Yang

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26 the length of M&A. The limitation is that only large companies are involved in the

antitrust approval process, this regulatory is not applied to small enterprises.

Further research may focus on the large companies and study the effect of antitrust

regulatory on the length of M&A deal.

 In the sectors of China’s national strategic interest such as energy, transportation, telecommunication, etc., the M&A process would be much longer because the

political considerations are influenced by central governments. For further study,

an optimization could be realized by including data correlated with different

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27

Acknowledgement

This article has been written as part of the MSc International Economics and Business

study at the University of Groningen, and has been written in the year of 2016.

My personal interest as an economist lies in the dynamic Asian Economy, including the

developed economies like South Korea and Japan, as well as the developing economies

such as China and India. South Korea was one of the poorest countries in the world

after the Korean War in 1950s. Now South Korea has become one of the leading

industrial economies in the world. The economy of China and India have been catching

up during the last decades, however, through different paths: government strategy and

policies for economic growth, challenges for sustainable growth, and the side effects of

rapid economic growth are all different. This study mainly focuses on the effect of state

ownership in the Chinese market, and I want to figure out whether state ownership plays

a significant different role in the M&A process.

Above all, I would like to thank Dr. Padma RAO Sahib for her kindness and patients,

and for the hours she spent on providing the valuable feedbacks.

I am also grateful to Prof. dr. Ning Qu for providing me an internship as a project

assistant in his foundation at UMCG, and his time spent on proofread of this paper.

Last but not least, a thank to my mother for being in Groningen and for cooking nice

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28

Appendices

Appendix I: Key Regulatory Authorities for M&As in China

Figure 2: Key Regulatory Authorities for M&As in China

(Source: “M&As in China, Getting Deals Done, Making Them Work”, by Yang, et al., 2015)

Appendix II: Description of Variables

Table 7: Variables description

Variable name Storage

type

Display format

Value label

ln(Deal Length) float %9.0g Log value of days of a M&A process Acquirer Ownership byte %10.0g = 1 when acquirer is SOE; = 0 otherwise Target Ownership byte %10.0g = 1 when target is SOE; = 0 otherwise ln(Deal Value) float %9.0g Log value of M&A deal in million Euro ln(Target Size) float %9.0g Log value of number of employment of target Payment Method byte %10.0g = 1 if financed by cash; = 0 otherwise Cross-border byte %10.0g =1 if cross-border; = 0 if domestic

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29

Table 8: Descriptive Statistics

Variable Observation Mean Std. Dev. Min Max

ln(Deal Length) 523 4.32 1.32 0 6.69 Acquirer Ownership 523 0.219 0.4145 0 1 Target Ownership 523 0.076 0.2660 0 1 ln(Deal Value) 523 3.54 2.04 -1.73 10.24 ln(Target Size) 523 7.51 1.89 1.61 13.11 Payment Method 523 0.815 0.3890 0 1 Cross-border 523 0.214 0.4106 0 1 Industry 523 0.344 0.4755 0 1

(Note: the variables deal length, deal value and target size are in natural logarithm.)

Appendix III: Checking for Multicollinearity

Table 9: VIF Value

Variable VIF 1/VIF

Acquirer Ownership 1.07 0.933041 Target Ownership 1.04 0.959105 ln(Deal Value) 1.37 0.728401 ln(Target Size) 1.14 0.876119 Payment Method 1.22 0.820886 Cross-border 1.14 0.877620 Industry 1.06 0.947652 Mean VIF 1.15

Appendix IV: Checking Normality of Residuals

Table 10: Shapiro-Wilk W test for normal data

Variable Obs W V z Prob>z

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30

Appendix V: Checking Homoscedasticity

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance

Variables: fitted values of llength

chi2(1) = 8.92 Prob > chi2 = 0.0028

Figure 3: Residuals Plots

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31

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Does State Ownership Have an Influence on the Length of M&A Deal?