State ownership and its impact on financial performance of Chinese acquiring firms

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State ownership and its impact on financial performance of Chinese acquiring

firms

University of Groningen - MSc International Financial Management Faculty of Economics and Business

Student name: Ivaylo Gerasimov Student number: S2498073 Master Thesis Supervisor: Dr. H. Vrolijk

Co-assessor: Dr. J.H. von Eije

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Abstract

Cross-border and national mergers and acquisitions (M&A) by Chinese firms have reached unprecedented levels in recent years. This research seeks to outline the most important trends of the recent M&A activities of Chinese acquirers by focusing on their post-acquisition financial performance while taking into account the effect of Chinese state ownership. After applying a paired t-test, using 708 national and cross-border acquisitions, the results show a decrease of the financial performance of Chinese acquirers in the period of two years following an acquisition deal. Moreover, by regressing the post-acquisition profitability on state ownership, I find that government ownership exerts a positive influence over acquirers’ financial performance. This study is among the first ones to use accounting based measure as a proxy for financial performance instead of the common used market based measurements.

Key words: M&A, cross-border acquisitions, national acquisitions, state ownership, ROA, diversification

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1. Introduction

Mergers and acquisitions (M&A) have received notable attention from developed as well as emerging economies. In the new millennium the global M&A activities have reached new records both in quantity and scale (Chen and Young, 2010). This is a clear sign that M&A activity has turned into an important mean to seek resources and development. However, can M&A be profitable for enterprises? The academic answer to this question has been controversial, so one of the objectives of this study is to identify whether acquirers’ profitability improves or diminishes following M&A.

Among the most important drivers of the burst in M&A activities in the new millennium have been Chinese acquiring firms that are increasingly taking over companies domestically as well as internationally. Increasing competition in the Chinese market (Liu and Wang, 2013) has caused a constant increase in takeovers activities. Hence, in the 5 years period between 2010 and 2014 cross-border and national acquisitions by Chinese acquiring firms have reached 878 deals up from 257 deals between 2002 and 2006. The rise and importance of Chinese M&A have stimulated many academic researches on post-acquisition market valuation of Chinese acquirers (Chen and Young, 2010; Du and Boateng, 2015; Gu and Reed, 2013), but there have been few studies regarding the post-acquisition financial performance of acquirers using accounting based measurements (Edamura, Haneda, Inui et al., 2014; Liu and Wang, 2013). To bridge this gap I analyze the financial performance of Chinese acquiring firms following M&A by applying return on assets (ROA).

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5 academic literature has paid little attention on this topic but more on the government’s role on acquirers’ decisions to expand through M&A (Luo, Xue and Han, 2010; Rui and Yip, 2008; Su, Xu and Phan, 2008; Xiao and Sun, 2005). While these papers conclude that governments play an important role in M&A, they don’t say anything about the casual relationship between profitability and government ownership. Hence, the second objective of this paper is to find out the effect of government’s ownership in the acquiring firm on its post-acquisition financial performance.

This paper makes three primary contributions to the literature. First of all, it creates an overview over the most current M&A activities of Chinese firms and their characteristics, including number of deals, target countries, target industries, financial performance, state ownership etc. This descriptive analysis may be used by other researcher as a starting point for diverse M&A studies. In the second place, it contributes to the M&A literature by examining the profitability of acquiring firms from China by using an accounting based measurement. And third, this paper contributes to literature by showing the beneficial effect of state ownership on acquirers’ financial performance.

The rest of the paper is organized as follows: First I examine the theoretical and empirical literature regarding the financial performance of firms before and after an acquisition and the role of the Chinese government. In the following section, an overview of the acquisition activities of Chinese firms both domestically and internationally1_{in the period between 2002 and 2014 is presented. On} the basis of these sections, I formulate my research questions. Subsequently, the methodology used is elucidated and the sample on which the analysis is based, is further analyzed. Then I represent my empirical findings, discuss them and summarize them. Finally, the last Chapter concludes with the implications for managers and executives while setting limitations, and suggests outlooks for further research.

2. Previous literature

In the academic literature there are many studies regarding M&Aactivities of western companies. Only recently M&Aof emerging economy firms have caught the attention of researchers. I aim to

1_{International acquisitions and cross-border acquisitions are interchangeably used. These are acquisitions where the}

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6 fill this gap by studying cross-border and national acquisitions by Chinese firms, while taking into account the role of the state ownership.

In this section I first take a look at previous studies regarding the financial performance of firms after M&A deal, both nationally and internationally. Considering this the Chinese government’s impact on acquirers’ profitability is described. Based on theoretical arguments and previous findings I formulate my research questions.

2.1 Pre- vs. post-M&A performance

The choice of performance measure is an important factor as it can be based either on accounting or market data. A large part of the papers examining M&A applies short-term market measurements, amongst which the stock’s reaction after an event’s announcement is the most common one. The evidence from these studies shows conflicting results that imply either a value increase or a value decrease in the event window after the announcement. These event studies have nothing to say about the long-term economic gains of M&A. A possible substitute for event study could be Tobin’s Q2_{that can be applied for long-term analyses}3_{. However, the stock market of} China is very complex, for example requiring special permission for trading on the national stock exchanges or even including shares that can’t be traded and are priced by the state. Taking into account also that investors’ expectations and market fluctuations don’t reflect the true impact on acquirers’ profitability, I chose to apply as a measure of corporate performance an accounting based variable that is commonly used in the academic literature – Return on Assets (ROA).

The literature about financial performance (ROA) of firms involved in M&A is very diverse and includes many studies. My research contributes to the current literature by showing evidence for acquirers from an emerging country, while most of the studies so far have been done for developed countries. In addition I also shed light on the role of the state ownership in M&A.

2_{Tobin’s Q is defined as “the market value of the firm divided by the replacement value of its assets” (Morck and}

Yeung, 1991, pp. 171; Tobin, 1969)

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7 Most of the studies about post-acquisition acquirers’ financial performance include domestic target companies. Mueller (1980) examines 247 transactions during the period between 1962 and 1972 by measuring the ROA three years after the deal, and finds a decline after an acquisition. Peer (1980) concludes similar results for Netherlands as Ryden and Edberg (1980) for Sweden for the same time period. In studying M&A in United States, Ravenscraft and Scherer (1987) find out that profitability of acquiring firms decreases in the post-acquisition period. Their sample includes 2732 US M&A deals in the manufacturing sector for the period between 1957 and 1977. The largest study of M&A in United Kingdom (Meeks, 1977) come to the same conclusion as Ravenscraft and Scherer (1987) that takeovers reduce profitability of acquiring firms. But other studies for UK have concluded an increased profitability after M&A (Cosh, Hughes and Singh, 1980). In tune with Cosh, by examining 134 German M&A during the same time frame, Cable, Palfrey and Runge (1980) find also an increase in ROA. Gugler, Mueller, Yurtoglu et al. (2003) come to the same conclusion as Cable and Cosh, that ROA increases in the post-acquisition period. Bruner (2002) made a review paper, consisting of 15 studies, for the acquiring firms’ financial performance after M&A. Four of the studies report out significantly negative performance, three studies significantly positive performance and eight of the studies don’t report any significant difference between pre- and post-acquisition. Furthermore some researchers claim that M&A may benefit operating synergies, which improve acquirers’ accounting variables such as revenues and costs, and ultimately ROA (Clemente and Greenspan, 1998). However, Gmelich (2011) disproves the operating synergy effect of M&A by finding that ROA of the majority of acquirers decreases in the period of 1 to 5 years after M&A.

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8 conduct a meta-analysis and find that on average the ROA of cross-border acquiring firms “doesn’t positively change as a function of their acquisition activity, and is negatively affected to a modest extent “ (p.187).

When studying M&A, it is important to differentiate between vertical and horizontal acquisitions4_. The majority of paper, studying diversification5 through M&A use market based measures as a proxy for firms’ performance and report out that diversification decision destroys firms’ value because of the high agency costs for these firms (Berger and Ofek, 1995; Servaes, 1996; Yermack, 1996). Other researchers associate diversified M&A with self-manager’s interests such as managers pursue goals that are contrary to profit maximization (Jensen and Meckling, 1976). E.g. managers could transfer resources from large divisions with good investment opportunities to small divisions with poor ones making the internal resource allocation inefficient (Doukas and Kan, 2008; Rajan and Zingales, 2000), which ultimately damages firms‘ performance. Information asymmetry between the acquiring firms’ managers and target firms’ managers is greater within diversified companies, which may lead to higher operating costs that would damage firm performance (Aggarwal and Samwick, 2003; Stein and Scharfstein, 2000). Loughran and Vijh (1997) and Morck, Shleifer and Vishny (1988) find also that unrelated transactions benefit less from M&A than related M&A. Therefore I expect that diversified deals will result in lower profitability compared to undiversified M&A.

Based on the discussed literature, I come to the first research question of this study: the financial performance of Chinese acquiring firms after M&A deal. This question seeks to identify whether there is a difference in ROA between pre- and post-acquisition.

i. What is the ROA of Chinese acquiring firms in the period after the acquisition compared to the period before the acquisition?

4_{Horizontal acquisition - Two companies that are in direct competition and share the same product lines and markets.}

Vertical acquisition – Two companies that are on different stages of the value chain – e.g. a supplier and manufacturer.

5_{A takeover is considered as a diversification if the two companies have different Standard Industrial Classification}

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2.2 State ownership

Privatization and liberalization of the Chinese market are ongoing, however the role of the state remains significant. The Chinese economic model could be considered as a state capitalism economy, that is based on the dominance of the state-owned companies and an open-market economy. Since I am studying the post-acquisition performance of Chinese acquiring firms, I need to account for the role of the Chinese government.

The literature gives two interpretations for the effects of state ownership on firm value. One of the view is that state ownership has an adverse effect on corporate value and performance because government intervention will slow down a firm’s corporate decision-making process in an increasingly competitive environment (Du and Boateng, 2015). Further arguments for the detrimental role of the government are that investors may have little confidence in M&A due to the lack of managerial competence (Xiaoyue and Xiaodong, 2001). In this regard Hemerling, Michael and Michaelis (2006) find out that most of the Chinese state-owned acquirers lack world-class M&A capabilities, that impediments the execution of large-scale cross-border mergers and acquisitions and ultimately damages firm’s performance. Political motivations may also shape the relationship between private investors and the State Council. According to Su et al. (2008) political decisions create divergence of interests between the majority owner, the Chinese government, and the minority shareholder, individuals and foreign institutions (principal-principal conflicts)6. From major decisions such as the appointment of top managers to day-to-day business operations, the Chinese government is driven by political considerations (Walter and Howie, 2003) that often contradict with profit maximization interests of all other shareholders. This reflects the fact that the objective of the Chinese communist party (CCP), which has a full control over the state, is to maintain a “harmonious society” and not to enhance profit. Other studies (Boycko, Shleifer and Vishny, 1996; Dewenter and Malatesta, 2001; Megginson, Nash and Van Randenborgh, 1994) also support the negative effect of the government’s role over the firm’s financial performance. For instance to reduce social pressures government may reduce unemployment instead of maximize profit (Du and Boateng, 2015), or to work towards regional development or income redistribution. Achieving these social objectives sometimes requires redundant workers, pricing

6_{Publicly-traded firms experience principal-principal conflicts when the majority owner has interests that deviate}

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10 goods and services below market and even below costs, locating plants in uneconomic areas, or keeping uneconomic facilities open (Musacchio and Lazzarini, 2012).

The contrary view of the effect of the state ownership on firm’s profitability argues that state-owned companies are more likely to receive preferential treatment from the government, thereby improving their financial performance (Blanchard and Shleifer, 2000). For example there is a sufficient evidence that Chinese firms involved in M&A have benefited from government support through value-added tax breaks and favorable financing (Xiao and Sun, 2005). In other studies (Bai, Lu and Tao, 2006; Guariglia, Liu and Song, 2011; Poncet, Steingress and Vandenbussche, 2010) it is also argued that emerging market governments might induce soft budget constraints and provide some support for state-owned firms driven by socio-economic and political objectives. Another example comes from Luo et al. (2010) and Peng, Wang and Jiang (2008), who have documented that through its ownership of firms the Chinese government provides tax rebates and foreign exchange assistance. Firms with state ownership also face fewer financial constraints compared to privately owned firms (Lin and Bo, 2012; Zhou, Guo, Hua et al., 2012), which are often credit-rationed by state banks and face much higher interest rates (Allen, Qian and Qian, 2005). Government support through lower lending rates and other incentives for state-owned firms may influence positively the company’s profitability (Lubatkin and Shrieves, 1986).

To sum up the role of the government could be either detrimental or beneficial. Therefore my second research question seeks to identify what is the effect of state ownership on post-acquisition ROA of Chinese acquiring companies both domestically and internationally.

ii. What is the effect of state ownership on ROA of Chinese acquiring firms?

3. Chinese M&A: trends and patterns

The acquisition of foreign assets by Chinese companies has seen rapidly development since 2002. To develop a clearer understanding of that process and its characteristics, both globally and domestically, I examine all cross-border and national acquisitions initiated by Chinese firms from 2002 to 2014. Hence, I present a descriptive analysis on various aspects of the Chinese takeover’s7

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11 activities. Researchers may find this analysis as very useful as they can use it as a basis for numerous studies regarding the explanatory nature of the presented data. The analysis may also benefit investors as it triggers their attention to the new opportunities for investments.

In the descriptive section I use data for the period between 2002 and 2014, that includes number of national and cross-border acquisitions, target countries, target industries, state ownership in Chinese acquirers and financial performance of Chinese acquiring firms.

An explosion of M&A

Chinese companies have expanded abroad slower than many others in the global business community had expected (Luedi, 2008). Up to 2002 the Chinese “outbound” M&A remained relatively small even compared to other developing countries such as India and South Africa (Hemerling et al., 2006). However, the launch of the Go Global Policy in 1999 and especially the admission of China in the World Trade Organization in 2001 caused a sharp increase in the acquisition deals initiated by Chinese firms.

Figure I shows the number of cross-border acquisitions by Chinese firms between 2002 and 2014. The increase of number of deals has been steady with spikes in 2011 and 2014, when 17 deals were completed in each of the years. The trend shows that Chinese outbound M&A are rising. Moreover according to some researchers (Hemerling et al., 2006; Luedi, 2008) the recent M&A activities by Chinese firms are only the beginning of a long-term trend.

Figure I - Overseas acquisitions of Chinese acquirers by number of deals

Source: Bureau van Dijk’s Zephyr database

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12 National acquisitions have been growing at a fast pace as well (Figure II), reaching their peak in 2010. The peak in deal volume of Chinese M&A transactions that followed until 2010 did not extend to 2011. Because of its large interconnections with global finance, China’s economy started to slow down. Along with the unstable global economy, China was hit by several other circumstances, such as the outflow of capital, changeable inflation, rising cost of wages, a still-unclear regulatory approval system and collapsing black market loans (Baxter et al., 2013). All of these factors might have caused a slowdown in the M&A activities of Chinese firms.

Figure II- National acquisitions of Chinese acquirers by number of deals

Source: Bureau van Dijk’s Zephyr database Where are the targets?

In the past Chinese M&A have been focused primarily on Asia due to the geographic proximity and cultural similarities (Luedi, 2008). However, since the beginning of 2000s the Chinese companies have started pursuing asset’s acquisition across all geographies. Between 2002 and 2014 Chinese companies acquired assets through acquisitions in 32 different countries. This geographical shift started after the introduction of the “Go Global Policy” and the new attempts of the Chinese government towards market liberalization and privatization.

I present in Table I all target countries for Chinese acquirers. Notable is that among the top ten target countries, there aren’t any developing markets. Why there are so little acquisitions in emerging markets? The answer to this question is that the preferred method for entering developing

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13 markets are green field investments (Giovannetti and Sanfilippo, 2009; Kaplinsky and Morris, 2008). Thus M&A as a mean for FDI are less common in developing markets.

Table I – Cross-border acquisitions of Chinese acquirers by target country (2002-2014)

Country Number of acquisitions Country Number of acquisitions

Hong Kong8 ₂₄ _Austria ₁

Germany 19 Belarus 1

USA 9 Columbia 1

Canada 7 Czech republic 1

Australia 6 Spain 1 France 6 Hungary 1 Italy 5 Israel 1 UK 4 Japan 1 Netherlands 4 Kyrgyzstan 1 Denmark 3 Korea 1

Virgin islands (British)9 ₃ _{Cayman islands}9 ₁

Brazil 2 Norway 1

Indonesia 2 Russia 1

Macau8 2 Sweden 1

Singapore 2 Thailand 1

Argentina 1 Taiwan 1

At what sectors are the deals aimed?

Most of the deals for both national and cross-border takeovers in the period between 2002 and 2014 fall in “Manufacturing” (Figure III), 46% and 51%, respectively. This shows the dominant position of the Manufacturing in the acquisition activities of Chinese firms. The Manufacturing sector also reflects the rapid growth of the Chinese economy in the last decades (Hemerling et al., 2006).

Another major industry is “Finance, Insurance and Real Estate”10_{, which is 14% from the national} acquisitions and 22% from the cross-border ones. If we consider absolute numbers, the deals’ volume on national level is way bigger than on international level (219 domestic deals vs. 26 overseas). The large acquisitions’ activity in the financial sector by Chinese firms, especially

8_{Hong Kong and Macau are considered as developed markets by the World Bank. They are also included as}

cross-border markets due to their recent colonial status and high degree of autonomy from the State council.

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14 abroad, follows the massive market capitalization spike of Chinese banks11 and their strong, profitable growth, allowing them to possess a plenty of capital and foreign currency reserves (Lung, Michaelis, and Tang, 2008).

Another interesting feature is the relatively small amount of deals which fall under “Mining”. It is well known that Chinese companies are extensively investing in sectors that exploit natural resources and raw materials (Thorborg, 2011). However, these are green field investments, mostly in developing countries, that are not captured by the data.

Figure III- Acquisitions by target industries12 (2002-2014)

In Figure IV I have plotted the target industries distribution by state-owned and privately owned acquirers. Again the “Manufacturing” is the dominant sector, with 41% and 49% for state-owned and non state-owned acquiring firms, respectively. In comparison to Figure III (cross-border vs. national) the financial sector is equally distributed between the two samples, with 14% of all deals.

11_{In 2007 three of the four largest listed banks in the world were Chinese (Leung, Michaelis and Tang, 2008).} 12_{Standard Industrial Classification (SIC)}

0% 1% 22% 51% 8% 1% 2% 6% 5% 6% 1% 2% 14% 46% 5% 0% 2% 11% 12% 6% 0% 10% 20% 30% 40% 50% 60%

Agriculture, Forestry and Fishing Construction Finance, Insurance and Real Estate Manufacturing Mining Public Administration Retail Trade Services Transportation, Communications, Electric, Gas…

Wholesale Trade

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Figure IV- Acquisitions by target industries (2002-2014)

How big is the government’s ownership in acquiring firms?

The first attempts for privatization of Chinese state-owned enterprises happened in the early 90s, when due to a severe debt crisis many state-owned companies and even some cities itself were in danger of bankrupting. Sequentially concerns about the state banking system arose and the Chinese government decided that its relationship with its enterprises should change. Thus in 1995 the State Council, led by the former prime - minister of China Zhu Rongji, endorsed a policy to retain the large state-owned enterprises and to release the small ones. In order to expedite the privatization a huge shift of ownership from the central government to municipalities was initiated. That allowed the municipal, provincial and national governments to be engaged individually or to operate as joint ventures with private companies (Antkiewicz and Whalley, 2007). The result of the privatization’s policy was that between 1995 and 2001 the number of state-owned enterprises fell from 1,200,000 to 468,000, which impacted mostly small firms that were not listed. Lau, Fan, Young et al., (2007) calculated that in 2001, 80% of the controlling shareholders13_{of all Chinese} listed companies were either local or central government and only 12.8 % were identified as private investors14. Later in 2005 Morck, Yeung and Zhao (2008) reported that 65.9 % of all outstanding shares of the 1,381 listed companies on China’s two mainland exchanges (Hong Kong and Shanghai) have been owned by the various Chinese government organs. In this study the data

13_{Controlling shareholders are identified as} _{stockholders who own more than half of the shares or majority of the}

outstanding shares in a company.

14_{The rest of the controlling shareholders was identified as unknown.}

1% 2% 14% 49% 4% 0% 2% 12% 10% 5% 1% 2% 14% 41% 9% 0% 3% 8% 17% 7% 0% 10% 20% 30% 40% 50% 60%

Agriculture, Forestry and Fishing Construction Finance, Insurance and Real Estate Manufacturing Mining Public Administration Retail Trade Services Transportation, Communications, Electric, Gas…

Wholesale Trade

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16 comprise solely of Chinese acquiring firms, and their controlling shareholders represented either by the Chinese government or by private companies.

Figure V shows the percentage of state-owned acquirers15 from all acquirers involved in acquisition deals between 2002 and 2014. The blue line depicts the cross-border takeovers while the orange line represents the national deals. The trend shows that the role of the Chinese government as a controlling shareholder in the acquiring companies gradually decreases over the years reaching its lowest level in the end of the observed period. It is also noticeable that in 2002, all of the acquirers, involved in both national and international takeovers, were governmentally controlled. However, the total amount of acquisitions that took place in 2002 was only 5.

Further on in Figure V I present the difference between national and cross-border acquisitions in terms of the involvement of the government as a controlling shareholder. The Chinese government clearly engages more as a controlling shareholder in cross-border acquisitions than national ones. This may be driven by political motivations, where the state takes over companies abroad in order to gain direct access to resources and technology

Figure V - Percentage of all Chinese cross-border and national acquirers with the government as a controlling shareholder (2002-2014)

15_{A state-owned acquirer is considered as an acquirer, whose controlling shareholder is the Chinese government.}

0% 20% 40% 60% 80% 100% 120% 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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17 Another interesting feature regarding state’s ownership is the size of both national and cross-border acquiring firms, in terms of total assets value, in which the Chinese government acts a controlling shareholder. In order to present this data I divided the firms into four categories, each of it representing exactly 25% of the total sample (cross-border & national takeovers). On Figure VI you can see that Chinese government ownership rises with increase of the firm’s size. For example 16% of the firms that have total assets above € 0.17 but lower than € 0.40 billion have a controlling shareholder represented by the State Council, while almost three times more or 45% of the companies having total assets greater than € 1.33 billion are controlled by the Chinese government.

Figure VI – Percentage of all Chinese acquirers (cross-border and national) where the government is a controlling shareholder – firms are divided in 4 categories according to their total assets (2002-2014)

Source: Bureau van Dijk’s Zephyr & Orbis database

Figure VII shows to what extent the Chinese government acts as a controlling shareholder in the different industries of the acquirers. E.g. 34% of the acquirers within “Retail Trade” are government owned, while 66% are not. Earlier in the study I noted that the “Manufacturing” sector is the largest target industry in terms of deal numbers for both national and cross-border takeovers. The importance of this sector is confirmed also in Figure VII, where we can see that 25% of the acquirers within “Manufacturing” are state-owned. However, at the top of figure VII we can see that 46% of the acquiring firms in “Mining” and 45% in “Transportation, Communications, Electric, Gas and Sanitary service” have the state as a controlling shareholder (for absolute numbers please refer to Appendix B – Table IV). These findings show that “Mining” as well as “Transportation, Communications, Electric, Gas and Sanitary service” are the industries with highest state ownership.

45% 34% 16% _15% 0% 10% 20% 30% 40% 50% 60%

Firms > € 1.33 billion total assets

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Figure VII – Percentage of all Chinese acquirers (cross-border and national) where the government is a controlling shareholder – by industry sector (2002-2014)

Source: Bureau van Dijk’s Zephyr & Orbis database

To sum up the role of the Chinese government in acquisition deals remains significant during the whole observed period even though its magnitude has been decreasing over the last decade. This clearly establishes the commanding position of the Chinese government in the M&A decision-making process. Therefore, its impact on acquisition deals' outcomes is of a big importance for investors and policy makers.

Acquirers’ and targets’ performance?

In the last part of the descriptive analysis I present panel data for the performance and size of target companies as well as acquiring. Government-owned acquiring enterprises are on average 7.5 times bigger than privately owned companies in terms of total assets (Table II). Moreover state-owned acquirers have higher ROA compared to private takeover companies, 9.09% and 7.86% respectively. The better financial performance of government-owned acquirers may be due to the preferential treatment, which these firms receive (Blanchard and Shleifer, 2000). Further Table II clearly shows that on average state-owned acquirers take over larger companies in terms of total assets compared to privately owned acquirers. This is not surprising given the fact that government-owned companies are bigger, which allows them to acquire large companies. However, state-owned acquiring firms target companies with lower ROA compared to private acquirers. This might be explained with the fact that private companies work towards profit and

0% 14% 16% 18% 18% 25% 30% 34% 45% 46% 0% 10% 20% 30% 40% 50% 60% Public Administration Services Construction Agriculture Wholesale Trade Manufacturing Finance, Insurance and Real Estate Retail Trade Transportation, Communications, Electric, Gas and…

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19 value maximization, while state-owned companies have other incentives such as unemployment reduction (Du and Boateng, 2015). For further descriptive statistics of ROA please refer to Appendix A.

Table II–Average total assets and ROA of target and acquiring firms for the period between 2006 and 2012

Variable Average total assets Average ROA

Target firms of state-owned acquirers € 316,802,931.51 6.26% Target firms of non state-owned acquirers € 98,970,490.18 8.51%

State-owned acquirers € 6,785,510,623.05 9.09%

Non state-owned acquirers € 899,689,263.34 7.86%

Source: Bureau van Dijk’s Orbis database

In the next chapter of this paper I make a statistical comparison between pre- and post-acquisition period to see whether I can find any significant difference between the two periods. Moreover I try to explain the relationship between ROA and the government ownership using a set of control variables.

4. Data and Methodology

4.1 Data source and sample selection

For this study I gathered data on all completed national and cross-border acquisitions by publicly traded Chinese firms over the period from January 2002 to December 2014. Deals and their characteristics, such as number of completed deals, deals’ value, target country, target industry, government ownership etc., are gathered from Bureau van Dijk’s Zephyr Database. After that I insert the acquirers’ identification numbers into Bureau van Dijk’s Orbis Database to obtain firms’ accounting and financial information that is needed for the empirical analysis (a full overview of the used variables can be seen in Appendix B, Table V). The initial sample consists of 2604 M&A deals. For inclusion in the final sample, I impose the following restrictions on the acquiring and target firms:

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20 b) Due to the fact that Orbis database provides information from 2005 onwards the years

over which the statistical analysis is possible are 2006-201216.

c) Mergers are taken out, because there is no distinction between acquirer and target. d) Neither the acquirer nor the target should be a financial firm. Thus all the firms that

belong to the financial sectors, banks, insurance companies and investment firms are excluded from the empirical analysis. The reason behind it is that financial firms have different nature of assets and liabilities, different financial reporting systems and unique regulations that might cause a bias.

e) The takeover company must acquire more than 10% of the target because acquiring a stake less than 10% is classified as a portfolio investment rather than acquisition. The final share of the acquirers must be at least 50% of the target company, thereby gaining a majority share.17

f) The financial and accounting data of the acquirer must be available in Orbis database.

After I impose these restrictions I come to the final usable sample of 708 deals from which I create four sub samples (Table III).

Table III – Sample distribution (2006 to 2012)

Type of Acquisition Number of Deals

Main sample 708 --- Subsample cross-border 40 Subsample national 668 --- Subsample state-owned 187

Subsample non state-owned 521

16_{Deals in 2005 are excluded as I need data a year prior the deal, while deals in 2013 and 2014 are also excluded}

because the post-acquisition period is 2 years.

17_{If company A acquirers 10% of company B and company A has already 40% stake in B, than the deal will be}

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4.2 Methodology

4.2.1 Dependent variable

ROA is used as a proxy for financial performance of firms. The variable is an accounting-based measure of financial returns that can be applied for a long-term analysis. It illustrates how profitable the firms’ assets are in generating revenue. In the empirical analysis I use two types of return on assets: ROA prior acquisition denoted as ROA before (used as a control variable), and ROA after acquisition denoted as ROA after (used as a dependent variable). The higher the return, the more efficiently management uses its asset base. ROA after of the acquirer is calculated two years after the takeover as a percentage in the following way:

(1) 𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑛 𝐴𝑠𝑠𝑒𝑡𝑠 =𝑃𝑟𝑜𝑓𝑖𝑡 𝑜𝑟 𝐿𝑜𝑠𝑠 𝑏𝑒𝑓𝑜𝑟𝑒 𝑡𝑎𝑥𝑒𝑠

𝑇𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠 𝑥 100

Table IV shows that ROA after during the financial crisis in 2008 is lower than the average for the entire period, 5.41% and 5.93% respectively. The ratio then strongly recovers in 2009, when it reaches its peak for the given period. Noteworthy is that the 25th percentile increases much stronger than the 75th_{after the crisis, which indicates that underperforming companies have} recovered very fast. However, the lowest values of ROA after for the entire period are recorded in 2012 and 2013, when they reach 4.88% and 4.12%, respectively. To sum up the descriptive statistics for ROA after doesn’t show a clear trend of the development of ROA after over the years. There aren’t also any indications for severe outliers (descriptive statistics for subsamples national and cross-border acquisitions can be seen in Appendix B, Table II and Table III respectively).

Table IV – Descriptive statistics of ROA after for the full sample of 708 deals

Year Mean Min Q1 Median Q3 Max Std

2008 5.41 -25.1 2.35 5.12 11.49 27.26 8.95 2009 9.01 -8.15 5.26 8.02 13.24 23.67 6.23 2010 6.66 -45.6 2.58 5.64 10.6 46.68 8.64 2011 6.21 -21.67 2.6 5.07 8.74 29.29 6.76 2012 4.88 -11.73 1.61 3.81 7.16 23.43 5.59 2013 4.12 -26.81 1.54 4.23 7.25 19.07 6.36 2014 7.37 -2.02 2.84 6.25 10.96 24.44 5.5 2008-2014 5.93 -45.6 2.31 5.08 9.08 46.68 6.92

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4.2.2 Independent variable

The independent variable is state ownership. Lin and Bo (2012) and Xu and Zhang (2008) measure state ownership as a percentage of equity ownership by all levels of the Chinese government held in the acquiring firm to total equity. Due to data limitation regarding the exact state ownership stake in the takeover company, I apply a dummy variable to show whether or not the Chinese government is a controlling shareholder in the acquiring firm. The dummy variable takes one, when the government is a controlling shareholder and zero otherwise. As already mentioned controlling shareholder is identified as a stockholder who owns more than half of the shares of the outstanding shares in a company or is the largest shareholder.

4.2.3 Control variables

To deal with the possibility that a variety of factors can jointly affect corporate’s financial performance and thus induce a spurious correlation between them multivariate analyses are performed with controlling for a set of factors:

a) Leverage

An important firm characteristic is company’s capital structure. Titman and Wessels (1988) and Rajan and Zingales (1995) report out that leverage is correlated to ROA. I calculate the leverage as total liabilities over total assets (Tian, 2001).

b) Size

Large-sized firms may benefit from scale economies and better access to bank credits that ultimately could improve corporate profitability (Chhibber and Majumdar, 1999). Margolis, Elfenbein and Walsh (2007) find firm size to be positively associated with financial performance, because bigger firms have better resources available than smaller firms. Following Tian (2001) as a proxy for size I use the natural logarithm of total assets.

c) Firm age

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23 d) Diversification effect

I consider an acquisition deal to be diversified when the acquirer takes over a firm in a new unrelated line of the core business, while an undiversified acquisition is the other way around (Feito-Ruiz and Menéndez-Requejo, 2012). According to Berger and Ofek (1996) and Campa and Kedia (2002) if the first two digits of SIC of acquirer and target differ, the deal is regarded as a diversification, otherwise as non diversification. The final sample consists of 340 unrelated and 368 related acquisition deals. To capture the diversification effect I apply a dummy variable that takes one, when the firm is diversified and zero otherwise.

e) ROA before

The inclusion of ROA before in the regression models improves the estimate of the regression coefficients and gives also higher values of adj. R2. It is calculated one year prior the M&A in the same way as ROA after (profit or loss before taxes over total assets multiplied by 100, equation (1)).

Table V reports the descriptive statistics for all of the control variables. Noteworthy is that acquiring firms are very large in terms of total assets. Compared to the total assets reported in the paper of Tian (2001) the mean of my sample is twice as high. In absolute numbers the average size of the acquiring firms is € 0.5 billion, while by looking at the 75th_{percentile we can see that 75%} of the acquirers have total assets below € 1.2 billion. The largest company included in the sample is PETROCHINA CO., LTD, that had € 125.5 billion of total assets in 2012.

The mean of ROA before is 7.28 (Table V), which is higher than the reported mean of ROA after (Table IV), which is 5.93. Hence, the preliminary analysis already indicates that post-acquisition financial performance of acquiring firms diminishes.

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Table V – Descriptive statistics for all of the control variables for the whole sample (2006 to 2012)

Variables Mean Min Q1 Median Q3 Max Std

Leverage 0.52 0.02 0.37 0.54 0.70 1.43 0.22

SIZE (ln) 20.03 16.23 18.93 19.76 20.92 25.56 1.53

Age 12.25 1.00 9.00 12.00 16.00 40.00 4.74

ROA before 7.28 -55.14 3.29 6.32 10.82 60.88 9.88

The table represents the summary descriptive statistics (mean, minimum, 25th percentile, median, 75th percentile and standard deviation), whereas leverage is calculated by total liabilities over total assets, size is the natural logarithm of total assets and age is the difference in years between the deals’ year and the year of acquirers’ incorporation. All of the control variables are calculated in the year of the deal.

4.2.4 Multicollinearity

Table VI shows the Pearson correlation coefficients between all the regression variables. The highest correlation is between the dummy for state ownership and the size of the acquiring firm, which indicates that on average state-owned acquirers are associated with higher size. State ownership is also positively correlated with ROA after, which gives the first indication for the relationship between state ownership and financial performance. Diversification on the other hand shows negative correlation with ROA after. I don’t find any high correlations between the explanatory variables such as multicollinearity can be seen as a problem in the regressions.

Table VI – Pearson correlation coefficients between all the regression variables

4.2.5 Econometric analysis

The econometric investigation starts with comparison analyses, whereas paired t-tests are used to examine the differences between two sample means. The results of this univariate test are displayed in the section empirical results.

Further on the analysis focuses on regressions, where ROA will be regressed using OLS on the state ownership dummy variable and the control variables that are discussed below. The

Variables ROA after Leverage Size Age Dummy state-ownership Dummy diversification ROA before

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25 relationship can be modeled as: Return on Assets = ʄ (state ownership, age, size, leverage, diversification, ROA before). The functional relationship can be transformed into the following models:

(M1) ROA after = α0 + β1Dgovernment ownership it + β2Ageit + β3SIZEit + β4LEVit + β5Ddiversification it +

β5ROAbefore it + ε

for national acquisitions, and

(M2) ROA after = α0 + β1Dgovernment ownership it + β2Ageit + β3SIZEit + β4LEVit +β5Ddiversification it +

β5ROAafter it + ε

for cross-border acquisitions.

Where ROA after it is calculated two years after deal it and ROA before it one year prior deal it, Age is the number of years between firm’s incorporation and deal’s year, Size is the natural logarithm of total assets, Lev is total debt over total assets, D government ownership is a dummy that takes 1 if a companies is state-owned and zero otherwise and D diversification is a dummy that takes one if a company is diversified and zero otherwise.

5. Empirical Results

5.1 ROA before and after takeover (univariate model)

Here I analyze the differences between the results of ROA for the period before and after the acquisition and hence I give an answer to my first research question. In order to do that I use a paired T-test to examine whether the ROA differs between the pre- and post-acquisition period. First I match up deals based on their pre- and post-acquisition profitability. Then I use the following simple equation to calculate the difference:

(2) ROA difference it = ROA after it – ROA before it,

Where ROA after it is calculated two years after deal it and ROA before it one year prior deal it.

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26 paired differences in the population will be either greater or lower than zero. First I perform this test for national and cross-border acquisitions (Table VII).

Table VII – Paired T-test for ROA (subsamples – national & cross-border takeovers)

Paired t-test National Cross-border

Observations 669 39

Hypothesized Mean Difference 0 0

Degrees of freedom 668 38 --- Sample Mean -1.31 -1.56 Sample Std. Dev. 10.18 5.2 --- Method T-statistic 3.33 1.87 Probability 0.00* 0.03* Critical value 1.96 1.69

The table shows the mean-comparison test between the pre- and post-acquisition ROA of both samples – national and cross-border. The two sample consist of 708 deals between 2006 and 2012.* the significance level is at 5%.

The t-value from the table has to be compared to a critical value of t-distribution with n-1 degrees of freedom at a significance level of 5% for a two sided test. The t-statistic for national and cross-border acquisitions fall outside of the range of the critical value, which allows me to reject the null hypothesis. Thus based on the evidence, shown in Table VII, I can conclude that there is a significant difference between the pre-and post-acquisition period. Moreover the outcome is negative, which implies that on average acquirers have a lower ROA in the period after the takeover compared to the period before not matter whether the takeover takes place domestically or internationally.

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Table VIII – Paired T-test for ROA (subsamples – state-owned & non state-owned)

Paired t-test State-owned Non state-owned

Observations 187 521

Hypothesized Mean Difference 0 0

Degrees of freedom 186 520 --- Sample Mean 0.11 -1.84 Sample Std. Dev. 8.38 10.44 --- Method T-statistic -0.18 4.02 Probability 0.86* 0.00* Critical value 1.97 1.96

The table shows the mean-comparison test between the pre- and post-acquisition ROA of both samples – state-owned and non state-owned. The two samples consist of 708 deals between 2006 and 2012.* the significance level is at 5%.

5.2 Relationship between government ownership and ROA (multivariate model)

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Table IX – Multivariate model

Independent variables M1 (national) M2 (cross-border)

Intercept 8.54* 0.89

(2.34) (0.09)

Dummy government ownership 2.15* 1.35

(3.51) (0.73) Leverage -0.91** 3.65 (-1.76) (0.69) Size -0.16 -0.06 (-0.90) (-0.11) Age -0.07 -0.09 (-1.40) (-0.43) ROA before 0.19* 0.51* (7.31) (2.94)

Dummy diversification effect -0.16 1.89

(-0.33) (1.08)

N 669 39

Adj. R2 _0.11 _0.14

Table IX shows the results of the multivariate analysis. The model regresses the ROA after of national (M1) and cross-border (M2) acquirers from China on government ownership, leverage, firms’ size, firms’ age, ROA before and diversification. ROA after is calculated as profit/loss before taxes over total assets multiplied by 100 and it is taken two years after the deals’ completion. The value between the parentheses reports the t-value. *Significant at 5% level, ** Significant at 10% level

6. Discussion

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29 is that state ownership in Chinese acquiring firms gradually decreases over the years for national as well as for cross-border acquirers. This indicates the decreasing effect of the Chinese state on M&A and it is also in tune with the trends pinpointed by Hemerling et al. (2006) and Luedi (2008). The findings in the descriptive analysis can be used as a basis for various explanatory researches.

Secondly, I analyzed whether there is a difference in acquirers’ ROA before and after M&A (first research question). My findings demonstrate that post-acquisition profitability of Chinese acquiring companies on average decreases following a takeover deal, for national as well for cross-border acquirers. This conclusion is derived from both descriptive and empirical analyses. The lower performance of cross-border acquirers is consistent with the findings of Chatterjee and Banerjee (2013) and Bertrand and Betschinger (2012) for cross-border M&A, although they use a longer time span to measure ROA before and after the deal. For national takeovers the decreased profitability is in tune with the findings of most of the papers in this area such as Mueller (1980), Ravenscraft and Scherer (1987), Gmelich (2011) etc. These findings show that M&A decisions are not always driven by profitability or synergy goals, since performance diminishes, but by other motives that are not in the scope of this paper.

Further on I continued the analysis with comparison between pre- and post-acquisition ROA of state-owned acquirers. Using paired t-test I didn’t find any significant difference between pre-and post-takeover ROA. The descriptive analysis, however, has shown that 52% percent of the state-owned acquirers experience decrease in their profitability following M&A. These descriptive results demonstrate that even government-owned companies don’t improve their financial performance following M&A. This may be explained with the findings of Walter and Howie (2003) and Du and Boateng (2015) that the Chinese government is often driven by political and social considerations, which contradict to the profit maximization interests of all other shareholders.

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30 a private owner as a controlling shareholder. This shows the beneficial role of the government (Blanchard and Shleifer, 2000), which may be explained with the lower lending rates and other incentives for state-owned firms in China (Lubatkin and Shrieves, 1986). It however contradicts with the results of Tian (2001) who finds that private acquirers have on average higher ROA compared to state-owned acquirers. For cross-border takeovers I don’t find any significant relationship between financial performance and state ownership. The cause for this might be the small sample size18_{or data bias. The lack of papers on this topic presents also an impediment for} discussing the relationship between post-acquisition performance of cross-border acquirers and state ownership in the acquiring firm. Therefore I recommend a further research including larger sample.

Further, I examined a few commonly applied control variables. When I control for diversified M&A I don’t find any significant relationship between diversification and ROA. This conclusion fails to support my expectation that acquirers, that engage in unrelated M&A, perform worse than companies taking over related businesses. These findings show that agency problems, which according to the common literature occur often within diversified M&A, don’t have an impact on firms’ financial performance. This is contrary to the conclusions of Stein and Scharfstein (2000) and Aggarwal and Samwick (2003). The determinants of the diversification effect in national and cross-border M&A could be elaborated in future researches.

Controlling for leverage shows that leverage decreases ROA of acquirers. This supports the findings of Booth, Aivazian, Demirguc-Kunt et al. (2001) and Rajan and Zingales (1995). Size and Age don’t impact firms’ financial performance, while companies, which have higher pre-acquisition ROA have also higher post-pre-acquisition ROA.

7. Conclusion and Limitations

This thesis studies the M&A characteristics of Chinese companies while it focuses on their post-acquisition financial performance and the effect of state ownership on it. The study finds that inbound and outbound acquisitions by Chinese firms are increasing at a fast pace across all

18_{From 120 cross-border deals, completed between 2002 and 2014 I have financial information for only 40 deals that}

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31 industries and geographies, whereas state ownership in acquiring firms is decreasing owing to the ongoing efforts of the Chinese state for liberalization and privatization. However, large assets companies are still often owned by the government.

I also find that post-acquisition profitability of Chinese acquirers decreases for both national and cross-border M&A. This conclusion is of great interest to shareholders, who may reconsider investing in companies that engage in M&A due to the decreased financial performance.

For the set of national acquisitions my findings show that government owned companies experience higher ROA compared to private firms. These results confirm the beneficial role of the Chinese state on national M&A. For cross-border takeovers I don’t find any significant relationship between ROA of acquirers and state ownership in acquiring firms. Since the literature suggests that Chinese government has indeed an impact on outbound M&A, I recommend a further research, which uses a larger sample.

Where previous studies have focused on market valuation, this study seeks to report implications on accounting-level, and thus avoiding the imperfections of the Chinese stock exchanges. Private investors and policy makers should take notice of the outcomes since they could benefit from the current development of Chinese M&A.

One should bear in mind that there are some important limitations that might have an impact of the interpretation of the results. For measuring the ROA of acquiring firms I use the period one year prior acquisition and two years after it. This might not be long enough time to capture the effects of M&A over the firms’ financial performance. Moreover, Orbis database has data availability from 2005 onwards, which makes the analysis possible only from 2006. Future researchers could stretch the time before and after the deal.

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stock-32 exchanges databases to calculate the precise state ownership, which will give more refined results regarding the government’s impact on profitability.

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33

Acknowledgements

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Appendix A

Acquirer’s performance?

Here I take a look at the acquirers’ performance in terms of ROA19_{. In Figure I I’ve plotted the} average ROA for all international and national deals in the year before the deal and in the second year after the deal. For example cross-border deals that took place in 2006 have a ROA in 2008 that is higher than the ROA in 2005. Except for acquisitions in 2008 and 2009 the ROA in the pre-acquisition period is higher than the ROA in the post-pre-acquisition period for cross-border takeovers. For national takeovers I also conclude that post-acquisition ROA is lower than pre-acquisition ROA for most of the years with the exception of 2007 and 2008.

Figure I - Average ROA in the year before and 2 years after the acquisition for cross-border and national takeovers

Moreover if I look up at a firm level, then I find that 54% and 59% of the acquirers have experienced a decrease in ROA ratios over the three years span from pre- to post-acquisition for cross-border and national takeovers respectively (Table I).

19_{Financial sector is excluded.}

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Table I - Percentage of national, cross-border, state-owned and non state-owned acquirers that have lower ROA in the period after the acquisition deal for the period between 2006 and 2012

Paired t-test ROA after < ROA before

National 59%

Cross-border 54%

State-owned 52%

Non state-owned 61%

Further on I present the ROA of owned and non owned acquirers (Figure II). For owned companies I find that post-ROA decreases in 4 of the 7 given years, while for non state-owned firms ROA decreases for almost the entire period except 2006 and 2007. Besides I find that 52% and 61% of the acquirers have lower post-ROA for state-owned and privately owned takeovers respectively (Table I).

Figure II- Average ROA in the year before and 2 years after the acquisition for cross-border and national takeovers

0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 2006 2007 2008 2009 2010 2011 2012 Before After 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 2006 2007 2008 2009 2010 2011 2012 Before After

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Appendix B

Table II – Descriptive statistics of ROA after for national acquisitions – 668 deals in the period between

2008 and 2014

2006 5.47 -25.10 2.20 5.19 11.51 27.26 9.05 2007 9.53 -8.15 5.26 8.52 13.86 23.67 6.09 2008 6.58 -45.60 2.58 5.60 10.11 46.68 8.88 2009 6.13 -21.67 2.76 5.05 8.68 29.29 6.75 2010 4.90 -11.73 1.60 3.82 7.16 23.43 5.61 2011 3.95 -26.81 1.53 4.18 7.05 19.07 6.60 2012 7.44 -2.02 2.81 6.34 11.06 24.44 5.53 2006-2012 5.93 -45.60 2.38 5.04 9.08 46.68 7.01

Table IV represents the summary descriptive statistics (mean, minimum, 25th percentile, median, 75th percentile and standard deviation) of ROA after of the acquirer in the period after the acquisition, which is calculated as profit/loss before taxes divided by total assets.

Table III – Descriptive statistics of ROA after for cross-border acquisitions – 40 deals in the period between

2008 and 2014

2006 3.17 3.17 3.17 3.17 3.17 3.17 NA* 2007 4.98 -4.77 3.19 6.69 8.49 11.75 6.26 2008 7.72 1.09 4.31 8.72 10.85 14.15 4.68 2009 8.66 1.06 3.04 7.91 11.47 21.04 7.40 2010 2.02 2.02 2.02 2.02 2.02 2.02 NA* 2011 5.46 1.13 1.92 5.76 7.92 14.19 3.83 2012 3.73 3.73 3.73 3.73 3.73 3.73 NA* 2006-2012 6.14 -4.77 2.02 5.97 9.32 21.04 5.13

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Table IV Number of all Chinese acquirers (cross-border and national) where the government is a controlling shareholder – by industry sector (2002-2014)

Sector Non state-owned State-owned

Manufacturing 738 246

Transportation, Communications,

Electric, Gas and Sanitary service 89 73

Finance, Insurance and Real Estate 133 57

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Table V - Definitions of all variables, used in the empirical analysis for the whole sample between 2006 and 2012

Dependent variable Definitions

ROA after A proxy of corporate accounting profitability. It is calculated as the

net profit/loss before taxes over total assets two years following the deal.

Independent variable

D government ownership A dummy variable of state ownership. If the government is the

controlling shareholder of the acquiring firm it takes one, otherwise zero.

Controlling variables

Age Firm age. It is calculated by taking the difference between the

current year 2015 and the year of incorporation of the firm

LEV Leverage. It is calculated by dividing total liabilities over total assets.

D diversification A dummy variable of diversification. If the first two digits of the

acquirer's SIC differ from the target's SIC the dummy variable takes one, otherwise zero.

SIZE Corporate size. It is calculated by taking the natural logarithm of the total assets.

ROA before A proxy of corporate accounting profitability. It is calculated as the

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