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Resource Seeking, the Role of Government and Value Creation of Chinese Cross-border Mergers and Acquisitions
By
Agyenim Boateng¹, Wei Huang, Min Du Chengqi Wang & Xiuping Hua
¹Agyenim Boateng,
University of Huddersfield Queensgate, Huddersfield,
UK, HD1 3DH E-mail: [email protected]
2
Resource Seeking, the Role of Government and Value Creation of Chinese Cross-Border
Mergers and Acquisitions
Abstract
Two decades of market-oriented reforms and open-door policies have spurred the unprecedented
growth of Chinese multinational corporations abroad. This paper considers the role of
government and institutional influences on value creation through cross-border mergers and
acquisitions by Chinese firms during the period from 1998 to 2008. The findings indicate that
Chinese bidders experience wealth gains ranging from 0.73% - 0.89% over a 3-day event
window. Our cross-sectional analysis indicates that the reforms in the foreign currency approval
system, the deal size and the regional location of the target firms exert significant impact on
shareholder wealth. Another intriguing finding is that Chinese acquirers that conform to the
government resource-seeking policy achieve positive gains; this finding provides support for the
conformity-performance debate under institutional theory.
Keywords: Institutions, Government, Cross-border M&A, Value Creation, China
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Resource Seeking, the Role of Government and Value Creation of Chinese Cross-Border Mergers and Acquisitions
Introduction
After two decades of market and economic reforms, Chinese companies have began to extend
their global reach and consolidate within their industries. As a result, the number of Chinese
firms engaged in cross-border merger and acquisition (CBM&A) activities in recent years is on
the rise. The value of outward mergers and acquisitions, which stood at only 17 million US
dollars in 1988, reached a value of $42 billion in 2008 (see UNCTAD, 2009). The rise in
outward mergers and acquisitions (M&A) activities in China has been attributed to a number of
factors, including resource seeking behaviour of Chinese firms (UNCTAD, 2006; Boateng,
Wang and Yang, 2008), the role of Chinese government and its reform policies, a high volume of
cross-border trade leading to foreign reserves of over 2 trillion U.S. dollars and China’s
continuous growth in GDP at a rate of 10% over the past two decades. In particular, the “go
abroad” strategy initiated by the Chinese government, which actively provides financial and
other support mechanisms to Chinese firms, has been a powerful force behind the surge in
CBM&A activities. Recent studies by Luo, Xue and Han (2010); Peng, Wang and Jiang (2008)
have documented that Chinese government are behind the rise in outward mergers and
acquisitions, but none of these studies gives attention to the effects of the government
involvement on CBM&A outcome. This is a significant omission, given the extent of the
Chinese government’s role in the economy. Hitt et al. (2004) indicate that the Chinese
government’s authority over businesses is pervasive and pronounced. The M&A decisions of
Chinese firms are driven by institutional constraints and incentives. As part of the economic
reforms, the Chinese government has maintained its ability to reward or discipline firms
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depending on their adherence to government directives (Luo, 2000). Deng (2008) echoes similar
views and points out that, due to the prevalence of various institutional constraints in China,
government endorsements are essential for CBM&As to occur. For example, Chinese
government through its “go abroad” policy has created priority sectors in line with national
policy goals of seeking resources which China lacks and all investments complying with these
guidelines in the “go abroad” strategy enjoy favourable financial support, tax holidays, and other
favourable treatment. Basic finance theory suggests that managers are organisationally rational
and implement strategies (which include political and institutional pressures) that they think will
lead to higher performance (Simon, 1976). Some firms therefore see investment in the Chinese
government designated priority sectors as a means of circumventing problems such as the
lending bias of China’s state-dominated banking system at low rate against their firms (Huang,
2003), heavy government regulations and other transaction costs (Guriev, 2004). The above is in
addition to the fact that, government endorsement in China is important and firms are under
pressure to conform to government policy agenda and raise the national flag. It would therefore
be somewhat of a surprise if corporate managers in China did not respond to these pressures. The
government ‘‘helping hand’’ theory of government-business relationship (Che and Qian, 1998)
in shaping international expansion behaviour and the pressures on firms to conform to state-
directed policies have implications for the cost of doing business, impact firms’ confidence and
firm value (Kofele-Kale, 1992, Boddewyn and Brewer, 1994).
Despite this, no study has explicitly examined the link between the role of governments and
value creation by Chinese firms. The few studies in this area examining whether conformity to
government-directed policies has positive effects on firms’ substantive performance and firm
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value include Donaldson (1995); Deephouse (1999); Westphal, Gulati and Shortell (1997) but
have produced mix results. Empirical research suggests that conformity leads to higher
performance because of legitimacy. Positive correlation between conformity and firm value were
reported by Abrahamson and Hegeman (1994) and Miller and Chen (1995). They observed that
conformity reduces risks, enhances opportunities for competitive advantage and hence the firm
value. However, Meyer and Scott (1983); Deephouse (1999); Luo (2001) suggest that conformity
to government-directed policies allows organisations to reap more positive social evaluations,
(i.e. social acceptability). This is because state, as ultimate authority, plays a role by endorsing a
firm’s strategy that falls within its national economic and strategic framework to bolster the
economy and enhance national competitiveness. However, Kennedy and Fiss (2008); and
Donaldson (1995) argued that the choice between conformity and performance-enhancing
templates for organising is a false dichotomy, and managers are unlikely to select templates
merely on account of their social acceptability.
In this paper, we contribute to this sparse literature by examining the effect of cross-border
acquisitions on the market valuation of the acquiring firm and explore the role played by Chinese
government in creating value for Chinese bidders. We argue that the economic rationale behind
acquisitions is based on the belief that gains can accrue via reduction in transaction costs and
acquisition of strategic assets. By conforming to government-directed policies, firms demonstrate
their legitimacy. The basic argument here is that a firm which conforms and avoids legitimacy
challenges tend to obtain higher quality of resources at more favourable terms ((DiMaggio and
Powell, 1983). Both reforms and conformity to government-directed policies reduce costs and
legitimacy improves firm’s value (Deephouse, 1999). Consequently, if stock markets are
efficient in pricing assets then shareholders wealth would be enhanced if Chinese firms’
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investments conform to the government directed priority sectors as such investments would be
perceived as good news. Using the data from the Chinese Stock Market and Accounting
Research Database (CSMAR), this study employs standard event study methodology to capture
the impact of acquisition announcement on firm value around the announcement date and
analyses the impact of government and institutional influences on Chinese CBM&As from 1998
to 2008 under the assumption that Chinese stock markets are semi-strong efficient1.
In terms of contribution, this paper overcomes an overwhelming bias in previous M&A studies,
which have concentrated on advanced market economies and have used traditional economic
factors to explain CBM&A wealth creation. We provide new insights into the implications of the
role of government policies on M&As and highlight the role of government in China’s emerging
economy as a source of value creation. In comparison with previous studies, this research
represents the first relatively large-sample study on CBM&As and value creation carried out in
the Chinese context.
The main findings of this study indicate that Chinese acquirers in the international market for
corporate control experience significant wealth gains around the announcement date of
acquisition. Cross-sectional regression results show that conformity to the government-directed
policy to invest in priority sectors and reforms in the foreign currency approval process influence
the wealth gains of Chinese acquirers.
1 Semi-strong efficiency is the ability of stock prices to adjust to the release of new information to market under efficient market hypothesis (EMH). EMH posits that stock prices will react or adjust instantaneously to reflect the release information such as announcement of major investment,
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The rest of the paper is structured as follows: Section 2 reviews the previous theoretical and
empirical studies. Section 3 presents the sample selection and method used in this study.
Following that is the analysis of the wealth effects and the factors that influence the wealth gains
from the M&As of Chinese acquirers. The final section concludes the paper and discusses the
implications of the study.
Relevant Literature: Government, Institutions, Wealth Effects and M&As
A number of theoretical perspectives have been used to explain how firms enter foreign markets,
including transaction cost theory (Hennart, 1989; Buckley and Casson, 1976), ownership,
location and internalisation (OLI) paradigm (Dunning, 1993) and institutional theory (Brouthers,
2002, Delios and Beamish, 1999). Overall, the predominant theoretical view of FDI is premised
on the asset-exploitation perspective. With this perspective, firms make the most of their rent-
yielding proprietary resources and knowledge-based capabilities by internalising resources
within the firm when expanding into overseas markets (Buckley and Casson, 1976; Hymer,
1976). The above perspectives were developed largely in the context of the advanced market
economies of North America and Western Europe, researchers such as Lall (1983) and Wells
(1983) describe their limited applicability in the context of firms from one developing country
entering into other developing countries. It is argued that firms from developing countries
expand mostly into similar or less developed countries using proprietary advantages such as low
input costs, inexpensive labour, managerial skills and advantages associated with conglomerate
ownership (Gubbi et al., 2010). While prior studies have used the above theoretical perspectives
to examine a firm’s choice of international entry mode in developed and developing market
economies, recent studies suggest that institutional theory appears to be the most applicable
8
theory when explaining enterprise behaviour in emerging markets (Child and Rodrigues, 2005,
Buckley et al., 2007, Hoskinsson et. al., 2000). Institutional theory’s explanatory power is
attributed to the fact that government and societal influences are stronger in emerging economies
than in developed countries (Hoskisson et al., 2000). Moreover, institutions defined as “the rules
of the game” help shape the strategies, structures, and competitiveness of firms (North, 1990).
Researchers argue that a firm’s strategic choices are driven by the institutional framework in
which the firm is embedded (Porter, 1990, Scott, 2002). The role an institution within an
economy is to reduce both transaction and information costs through reducing uncertainty, thus
establishing a stable structure that facilitates interaction and allows enterprises to move beyond
institutional barriers (see Oliver, 1991). Despite the above reasons, Luo, Xue and Han (2010;
p.68) suggest that “the specific policies enacted by home country governments has yet to be
systematically examined in the literature, hence the role of home governments in promoting
outward foreign direct investment (OFDI) and nurturing the growth of emerging market
enterprises” is not well understood. In this section, we review the existing literature on the role of
government and home country institutions.
The Role of Government
Political economists have long observed the pivotal role played by governments and home
country institutions in shaping international expansion behaviour and the trajectory of
multinational enterprises (see Boddewyn, 1988; Kofele-Kale, 1992, Moran, 1985; Boddewyn
and Brewer, 1994). Leone (1986: 6) aptly points out that “the acts of government create
individual winners and losers in the marketplace”. It is readily acknowledged that it is the
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government that creates legislation to regulate the economy and that establishes both the
regulatory and competitive environments in which businesses operate; however, the
government’s relationship with businesses in enhancing their growth and success is
complementary and complex (Boddewyn, 1988; Boddewyn and Brewer, 1994).
Most governments of emerging economies that support local firms decisions to ‘go abroad’ do so
with the assumption that these firms will bring in advanced technology, natural resources and
managerial know-how that home countries lack and that they will help bolster the national
economy and enhance national competitiveness (Luo, 2001). Luo, Xue and Han (2010) echo
these views and suggest that the Chinese “go abroad” policy has political dimensions and is
based on national interest (to acquire scarce resources such as natural resources, technology,
finance, managerial capabilities and other intangible assets) and the need to improve the
efficiency of Chinese firms and the Chinese economy. It is important to point out that the tacit
nature of some types of proprietary and intangible know-how, resources and capabilities makes
them difficult to purchase through market transactions (Coff, 1999, Gupta and Govindarajan,
2000). However, Capron, Dussauge, and Mitchell (1998) have noted that the market for firms
may be more efficient than the market for some resources, thus making acquisitions the popular
choice for gaining and reconfiguring new resources and capabilities. In short, CBM&As give
firms in emerging economies access to key strategic resources that may not be available at home,
thereby enhancing their capacity to be competitive. Therefore, it is not surprising that China has
taken a number of steps to encourage local firms to expand internationally, including i) creating
policy banks for credit support at lower lending rates and other incentives for firms venturing
abroad; ii) streamlining administrative procedures and decentralising them to local levels of
government; iii) easing capital control; iv) providing information and guidance on investment
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opportunities abroad; and v) reducing political and investment risks through bilateral and
multilateral agreements with countries and international institutions.
Government, Institutions and Value of Firms
Stretching the above point further, Boddewyn (1975pp. 194) argues that “government relations
are … largely unavoidable, and they are particularly important for multinational firms whose
legitimacy and loyalty are frequently questioned by government at home and abroad”. The
underlying concern is that company managers will ignore, to their immense detriment, the
importance of governments in their business strategy. This line of thinking is consistent with the
views of Wooten and Hoffman (2008), Scott (2001) and Zucker (1987) who strenuously argue
that organisations should adapt their decisions to external forces such as governments to gain
legitimacy and ensure their survival. Explaining this point clearly, DiMaggio and Powell (1983;
1991) Oliver (1997), Tsui et al., (2004), and Peng (2003); and Scott (1987) point out that,
organisations may make decisions voluntarily in response to pressures to conform to the strategic
direction and policies of the government or involuntarily in response to coercion by powerful
institutional forces that control critical resources or have legislative powers, i.e., coercive
isomorphism. Yet prior studies have been confined to traditional economic factors and wealth
creation (See Morck and Yeung, 1992; Kang, 1993; Markides and Ittner, 1994) and ignored the
role of institutions. Among the few studies investigating the wealth gains of CBM&As in the
context of emerging economies is a study by Boateng et al. (2008) that found significant positive
wealth gains for Chinese acquirers without analysing the factors on which the wealth was created.
Gubbi et al. (2010), examined 425 acquisitions by Indian firms and reported positive and
11
significant cumulative abnormal returns of 2.58% around the announcement date. On the other
hand, Aybar and Ficci (2009) studied 433 CBM&As announcements associated with 58 bidding
emerging markets multinationals and reported negative and significant cumulative abnormal
returns of 0.09% and 0.12% over two- and three-day event windows. In summary, the literature
offers conflicting evidence about the wealth effects of CBM&As by acquirers from emerging
markets, and none of these studies attempt to shed light on the link between the institutions and
the value of the emerging market firms. This study aims to fill the void in the literature by
providing evidence on wealth gains to Chinese bidders and the factors influencing such gains
from CBM&A activities. More specifically, this study focuses on the role of the Chinese
government’s reforms policy in respect of currency approval process and conformity to state-
directed policies to explain the wealth gains that can accrue to Chinese bidders.
Hypotheses Development
North (1990) suggests that any attempt to examine a firm’s strategic choice requires an
understanding of the institutional framework in which the firm is embedded. Scott (2001), and
Buckley et al., (2007), concur and argue that the institutional and regulatory framework of an
emerging economy can shape the domestic firms’ strategy and determine their ability to invest
abroad. Since the 1980s, the Chinese government has created and used several institutions such
as the Ministry of Commerce (MOC), the People’s Bank of China (PBC), the State
Administration of Foreign Exchange (SAFE), the State Owned Asset Supervision and
Administration Commission (SASAC) and the State Development and Reform Commission to
guide and manage overseas FDI. These institutions have been at the forefront of reforming,
12
providing support and developing the regulatory environment in which Chinese businesses
operate. As a result, we have seen a phenomenal rise of Chinese OFDI to a total of over 118
billion dollars, with M&As accounting for over 90 percent of this amount in the first half of 2008
alone. Below, we develop a set of hypotheses involving the two main factors of interest that this
study attempts to explore:
Conformity to Government Policy Direction and Value Creation (CGOPD)
The Chinese government, through its “go abroad” policy, has classified some sectors as
strategic2; these sectors receive more active support, and firms that conform to the direction of
government policies can more readily access inputs, such as cheaper sources of funds, and other
incentives. Zhang, Zhou and Ebbers (2010) point out that because of the China’s booming
economy, securing natural resources abroad has become the state imperative. Acquiring
advanced technology, management expertise and energy resources abroad is perceived as an
important means to strengthen firm’s international competitiveness. In line with the “go abroad
strategy”, government supports the firms’ overseas acquisitions through value-added taxes and
favourable financing (UNCTAD, 2005; Xiao & Sun, 2005). For example, the Chinese National
Development and Reform Commission (NDRC) and China EXIM Bank jointly issued ‘‘Notice
concerning the policy on providing credit and loan support for overseas projects encouraged by
the State’’ indicating that a low-rate loan will be provided if the FDI projects fulfil at least one of
the following requirements: exploring the a natural resource that China lacks (including energy; 2 In recent years, an expressed goal of state-directed Chinese overseas direct investment has been to access advanced proprietary technology; natural resources and other immobile strategic assets and other capabilities (Deng, 2003; Cai, 1999; Wu and Sia, 2002). The Chinese government provides support in the form of information on obstacles and problems encountered by OFDI firms, lower lending rate credit funds for companies engaged in acquisitions for the following: i) energy; natural resources in mining, gas and oil, promotion of textiles exports. The priority sector in this study include: minerals, petroleum, textiles; research and development (R &D).
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natural resources in mining, gas and oil); promoting textiles export; and R&D activity using
advanced international technology. Deng (2008) documents that Chinese firms increasingly use
cross-border acquisitions to acquire natural resources and advanced technology because they are
under pressure to conform to the state investment policy direction and bring in the resources that
China lacks. Although a number of researchers such as Donaldson (1995); Deephouse (1999);
Meyers and Rowan (1977); DiMaggio and Powell (1983) have investigated the link between
conformity and firm value, but the results appear inconclusive. Given the unique environment in
China and the fact that government endorsement does not only confers legitimacy but viewed as
firms devoted to national course and therefore are supported with favourable financial incentives,
conformity to national policy agenda may lead to value creation. We argue that conformity leads
to legitimacy and acquisition of financial resources at more favourable terms in China. Moreover,
analysts in financial markets recognise that technological resources acquired by the Chinese
firms from abroad can be taken back to home country, internalised and generate spillovers in
China (see Ranamurti, 2012). Therefore, conformity may provide a positive signal to the stock
markets about the prospects for firm whose strategic goal is to maximise shareholder wealth - the
only direct measure of shareholder value (Lubatkin and Shrieves, 1986; (McGee, Thomas and
Wilson, 2005). Accordingly, the following hypothesis addresses the impact of the role of the
Chinese government on the acquiring firms’ value.
H1: Chinese acquiring firms that conform to the government investment policy direction by
investing in the designated priority sectors will lead to a positive impact on shareholder value.
14
Government Reforms Policy (GOVREF)
Buckley et al. (2007, p.503) argue that “the institutional environment is likely to have a far-
reaching and profound effect on the internationalisation decisions of Chinese firms”. We argue
that liberalisation, institutional reform and outward investment procedures reduce bureaucracy
and generate positive wealth effect when acquisitions are announced due to potential reduction in
the costs of doing business. It is expected that the ensuing efficiencies associated with the
reforms may lead to value for Chinese acquirers on assumption that the stock markets in China
are efficient. We delineate below the key phases of the liberalisation of the foreign currency
approval system for overseas investment – the single reform policy that has undergone a
complete decentralisation from the State Council to the Provincial level.
1998-2006: Centralised Approval System for foreign currency
A standardised approach with greater scrutiny and monitoring procedures put in place
to approve outward investments. State Council involved in the approval process.
Currency approval required from the State Administration of Foreign Exchange
(SAFE). Entry into the World Trade Organisation (WTO). Policies to encourage
outward investment activities in textiles, energy, natural resources and R&D activities.
The “go-abroad” strategy or zou chu qu directive adopted by 17th Congress in 2002. In
2002, limited decentralisation from the central agency to selected local authorities for
projects of US 1 million or less, with overall investment capital of US$ 200 million.
Further decentralisation in 2005, with a local limit of US 10 million and the quota later
expanded to US 5 billion (Cai, 1999; Wu and Sia, 2002)
15
2006- present: Fully Decentralised Currency Approval System
Both SOEs and private enterprises are actively encouraged to invest overseas,
particularly in sectors considered strategic to China, with active state support.
Guidelines, establishment of specialised funds to help firms go abroad. In June 2006,
the overall investment quota for foreign currency is abolished. The quota for
purchasing foreign exchange for overseas investments was revoked and the necessary
foreign exchange for domestic investors to invest abroad was extended to self-owned
foreign exchange, the foreign exchange purchased by RMB, or the domestic and
overseas foreign exchange loans. We argue that easing the control of foreign exchange
required to undertake acquisitions abroad reduces cost and increase firm flexibility and
value. We therefore test the following hypothesis:
H2: Chinese acquirers engaged in CBM&A will create more wealth after the foreign exchange
approval reforms compared to the pre-reforms period.
Data and Methodology
Sample Selection and Characteristics
Panel A of Table 1 provides data on the sample selection of Chinese bidders. The sample
analysed in this study consists of mainland Chinese listed companies engaged in CBM&As
during the period 1998 - 2008. The announcement and completion dates as well as the parties
involved were identified from the GTA database from Hong Kong. The initial requirements for
inclusion in the study were as follows: i) the acquirer had to be publicly listed in the Shanghai
and Shenzhen Stock Exchanges under A Share, which provides data on cross-border M&As in
16
China; ii) neither the targets nor the acquirers could be a trust or financial firm. The resulting
sample included 445 bidders. The next requirement for inclusion was the availability of share
price data from the Chinese Stock Market and Accounting Database (CSMAR). To properly
separate the effects of each acquisition, the bidder could not be involved in multiple
acquisitions within three months. The acquiring firm must have its shares traded in Shanghai
and Shenzhen. In addition, we required that there must be at least 280 days of continuous data
around the announcement date. The event window was defined as a period of 260 days prior to
and 20 days following the announcement. Finally, there could not be a contaminating
announcement within ten business days before or after the announcement. It is important to
point out that the data from CSMAR database was compared with Thomson SDC Platinum
M&A database and Datastream. CSMAR database appears to provide relatively more up-to-
date information in terms of number of acquisitions and stock returns with fewer missing values.
The final, usable sample consisted of 148 cross-border acquisitions by Chinese bidders. It is
pertinent to point out that, lack of stock price data was the most important reason for the
exclusion from the final sample. In most of these cases, the listing occurred after the event. The
final sample compared favourably with a recent and similar study in Chinese context with a
sample of 68 drawn from SDC Platinum M&As Database for 1991-2008 period by Bhagat,
Malhotra and Zhu (2011). Panels B, C, D, E and F of Table 2 highlight locations of the targets,
priority/non-priority dichotomy by industry type, number of deals from 1998 through
September 2008 and sectoral distribution. It is apparent from Table 1 that most of the
acquisitions occurred in Asia (54.1%), with the rest taking place in advanced Western countries
(the U.S. and Western Europe). In terms of priority and non-priority industry classification,
over 40 percent of the acquisitions were in sectors designated by the government as priority
17
sectors, while the rest were in non-priority sectors. In terms of frequency by year, the highest
number of deals occurred in 2004 and 2005, followed by 2006 and 2008; the lowest number
were in 1998. The sectoral distribution is categorised into seven sectors, with manufacturing
having the highest number of acquisitions (30.4%), followed by general trade (20.3%), then R
& D (16.2%). The remaining sectors are transport and communication (10.8%), natural
resources & energy (10.1%), building & construction (6.8%) and textiles & apparel (5.4%).
Regarding the investment values of the acquisition, firms with investment value from 10-100
million dollar account for 60.8 percent while 39.4 percent have over 100 million dollars.
(Insert Table 1 here)
Methodology
To measure shareholder wealth changes, standard event study methodology (Brown and Warner,
1985) is employed to measure the wealth effects of M&A announcements on participating firms.
The event study approach allows researchers to conclude whether an event had a positive or a
negative effect on shareholder wealth. To derive the cumulative abnormal returns (CARs),
expected returns are based on a 260-day return prior to the announcement of the foreign
acquisition. We considered the following event widows: (-1, 0), (-1,+1), (-5,+5). The following
standard market model equation was used to calculate the normal return of the sample firms’
common stock:
Rjt = αj + βjRmt + εjt (1)
where,
t = day measured relative to event,
18
Rjt = return on security j on day t,
Rmt = Shanghai and Shenzhen Composite Index (a proxy for the market
portfolio of risky assets),
αj = estimated period intercept of firm j,
βj = OLS estimates of firm j’s market model parameters,
εjt = the error term of security j on the sample event day t.
The abnormal returns (AR) for each sample event j on day t are obtained as follows:
ARjt = Rjt – (αj + βj Rmt) (2)
where,
t = day measured relative to event,
ARjt = excess return to security j for day t,
Rjt = return on security j during day t,
Rmt = Shanghai and Shenzhen Composite Index (a proxy for the market
portfolio of risky assets),
αj = estimated period intercept of firm j,
βj = OLS estimates of firm j’s market model parameters.
Daily abnormal excess returns are calculated for each sample event in the study over the event
window. For a sample of N sample events, the daily average abnormal return for each day t is
estimated as:
ARt = 1
/N
jAR jt N
=∑ . (3)
19
The cumulative abnormal return (CAR) for each security j, CARj, is calculated by summing
average abnormal returns over the event period as follows:
∑=
=L
KtjtLKJ ARCAR ,, (4)
where the LKJCAR ,, is for the period from t = day K until t = day L.
The cumulative average abnormal returns (CAARs) over the event time period from day K to
day L are calculated as:
∑=
=N
JLKJLK CAR
NCAAR
1,,,
1 (5)
To correct for serial correlation of daily event period abnormal returns for the same firm, Coutts,
Mills and Roberts (1995) recommend using standardising cumulative abnormal returns for
longer event windows. Accordingly, each firm’s cumulative abnormal return is standardised by
dividing the CARs by respective standard errors. To calculate the statistical significance of the
tests, standardised abnormal returns and standardised cumulative abnormal returns are used to
calculate a Z statistic.
Using the Z-statistic, p-values were calculated for standardised abnormal returns and cumulative
abnormal returns over the event window. Under the null hypothesis of no stock price effect, this
statistic will have, approximately, a standard normal distribution. We report the standardised
CARs for the following event windows: (-5,+5; -1,+1; 0,+1). The CARs are utilised as dependent
variables in the cross-sectional analysis, and the tests of differences are all standardised.
20
Cross-Sectional Analysis of Cumulative Abnormal Returns (CARs)
Control Variables
Based on extant studies, a number of control variables are taken into account, including: home
country gross domestic product (LGDP) (Kiymaz, 2004); deal size (Uddin and Boateng, 2009);
exchange Rate (EXRATE) (Kish and Vasconcellos, 1993); Kiymaz, 2004). Regional location of
the Target (REGION); Kiymaz (2004); Control (CONTR) (Kiymaz, 2004). We take into account
the profitable of the acquiring firms in that highly profitable firms may drive performance. We
measure profitability using the ratio of operating profit to sales (PROFIT). The sample includes
firms from seven industry classifications. We control the sectors in line with previous studies, for
example, Doukas and Travlos (1988), who reported wealth gains across different sectors. Earlier
studies suggest that having full control of the target would give the acquiring firm the flexibility
of imposing the management style and expertise of the bidder thereby leading to more value
creation for the bidder. Chari, Ouimet and Tesar (2004) find evidence that acquiring firm’s value
is associated with controlling stake.
Variables Measurement
Cumulative Abnormal Returns (CARs)
We employ stock market reaction to the announcement, as reflected in the firm’s share price
movement around the announcement of the M&A event. We chose shareholder wealth creation
for the following reasons: i) it is widely accepted in finance literature that the goal of a firm is to
maximise the wealth of its shareholders, which is measured by stock prices, and prior studies in
finance and strategic management have extensively used market reaction in M&A studies (see
Delong, 2001; Sudarsanam and Mahate, 2003; McGee, Thomas and Wilson, 2005); ii) Haleblian,
21
Kim and Rajagopalan (2006) and Kale, Dyer and Singh (2002), point out that share price
movement has a better predictive validity than other objective measures such as profitability, in
that it is an ex-ante performance measure that has been found to correlate with ex-post
performance; and iii) share price movement is relatively unbiased compared to other measures
and invariant to differences in accounting policies across nations (Cording, Christmann and King,
2008). Following Kiymaz (2004), we measure the M&A short-term performance of Chinese
acquirers using the cumulative abnormal returns (CARs) for the event window 0, 1 period.
Independent and Control Variables
The manner in which the independent variables are measured is shown in Table 2.
(Insert Table 2 here)
Empirical Results
Short-run wealth effects
Wealth gains to Chinese bidder firms during the 21 day period surrounding the merger
announcement are shown in Table 3. The average abnormal returns (ARRs) for Chinese bidders
are 0.73% and 0.89% on days 0 and +1 and are statistically significant. The significant daily
return that occurs on day -1 (0.36%) may be due to information leak prior to the announcement.
However, the positive AAR on day +10 appears to be due to factors other than the announcement.
Panel B of Table 4 reports four different cumulative abnormal returns (CARs) for the Chinese
acquiring firms. For the (-1, 0) and (-1, +1) windows, our results indicate that, on average,
announcements of international acquisitions by Chinese bidders are associated with positive
22
abnormal returns. Positive market returns for the two- and three-day event windows range from
0.01% to 0.02% respectively. However, the CAR for window (-5, +5) is not statistically
significant3. Overall, the dominance of positive reactions suggest that investors perceive Chinese
CBM&As as value-creating strategic initiatives. These results are consistent with the findings of
Morck and Yeung (1992), and a similar study by Boateng, Wang and Wang (2008), who find
that CBM&As by Chinese firms increase the wealth of the acquirers. However, the results are at
variance with the conclusions drawn by Click and Harrison (2000); Hitt et al. (2001) and Aybar
and Ficici (2009). Our results confirm that Chinese stock markets are efficient and that all
publicly announced information is reflected in stock prices. In the next section, we discuss the
factors that may account for the positive reactions of investors.
Insert Table 3 here
Panels A and B of Table 4 report the t-test results of CARs for Chinese bidders in two different
windows in respect to state-backed priority/non-state-backed dichotomy type by industry and the
role of government-based foreign currency reforms. Chinese bidders making acquisitions both in
the state-backed sectors and after currency approval reforms enjoyed positive abnormal returns
for the two event windows. The results suggest that a state-backed sector has higher mean scores
compared to non-state backed sectors, with one of the event windows (0,+1) being significant at
1%. This finding suggests that the state-backed sectors tend to create more value compared to
non-state-backed sectors. Regarding the foreign currency reforms for undertaking outward
investments, the results indicate that the mean scores for the post-reforms period are statistically
3 No consensus has emerged among researchers with regard to the proper length of event window for calculating CARs (see Mc Williams, Siegel and Teoch, 1999 for review)
23
significantly higher than the period prior to the reforms for the two event windows, suggesting
that reforms lead to positive investor reactions. Panel C shows a test of differences between high
growth firms and low growth firms based on the profitability of the acquiring firms. T-test results
indicate that the differences between the high growth firms and low growth firms are statistically
insignificant.
(Insert Table 4 here)
Table 5 shows summary statistics for the dependent and independent variables. The table reports
the mean, standard deviation and minimum and maximum values for the variables used in the
regression analysis. The mean value for Asia appears to be higher than for the U.S. and Europe.
(Insert Table 5 here)
Cross-sectional Regression Results
The regression results for Chinese bidders are reported in Table 6. This table shows that the F-
values for all the seven regression models are statistically highly significant. The adjusted 2R
range from 16.9% to 18.6%, suggesting that, the regression procedure explains the variation in
the change in wealth gains of Chinese bidders. The total amount of variation explained by the
models appear reasonable and compare favourably to other CBM&A studies, such as Kiymaz
(2004), who obtained an overall Adjusted R square of 4% and 12% for his studies of a target
firm’s performance for CBM&As. The impact of the role of the Chinese government on the
wealth gains of Chinese bidders is evident in Table 6. The coefficient of the two variables,
CGOPD and GOVREF in models 1 to 7 are significantly positive, indicating that the Chinese
24
government plays a significant role in the wealth creation of Chinese acquirers. The results
provide support for hypotheses 1 and 2. Models 1 - 6 incorporate the main variables conformity,
foreign exchange reform and control variables including the acquirer characteristics,
macroeconomic variables with sectors entered in successive. The positive coefficient of the state-
backed sectors variable indicates a positive and significant relationship between the state-backed
sectors and wealth gains. This finding is interesting suggesting that, Chinese government through
its investment policy framework relentlessly pursue certain long-term objectives to help Chinese
firms acquire the resources they lack and thereby create wealth for these acquirers. The result is
consistent with the point made by Rui and Yip (2008) who argue that, Chinese firms strategically
use CBM&As to achieve specific goals, such as acquiring strategic resources and capabilities to
offset their competitive weaknesses through the use of government support and other incentives
and minimisation of institutional constraints. It is important to point out that, Chinese firms
engage in CBM&As in the government designated priority sectors enjoy privileged access to
low-cost capital and other incentives provided by the Chinese government. Conforming to the
state-directed policy to acquire strategic assets therefore helps these firms to gain legitimacy,
social support and prestige in the market place, which, in turn, leads to maximisation of
shareholder wealth creation as reflected in share prices. The results of this study indicate that
conforming to the government-directed policy tend to help emerging Chinese firms to offset
ownership and location disadvantages consistent to the conclusion made by Aggarwal and
Agmon (1990) in their study on the role government of developing countries. The results
therefore render some support for the conformity-performance debate under the institutional
theory. The results also indicate that specific policies enacted by emerging country governments
create value for acquiring firms and this appears to support the conclusion drawn by Boddewyn
25
and Brewer (1994) and Leone (1986) that the acts of government can create winners in the
marketplace by improving firm’s competitive advantage.
Another important finding is related to the impact of the liberalisation of the foreign currency
approval system on the wealth effects of Chinese acquirers. The results suggest that
decentralising the currency approval system on outward investment is beneficial to Chinese firms
engaged in international acquisitions. The results support the notion that liberalising the foreign
currency approval procedures reduces bureaucracy and the costs of doing business, thereby
generating positive wealth effects when acquisitions are announced.
Robust Check
To check the robustness of this finding, we carried out the Chow test for differences that may be
due to the structural changes which may cause differences in the intercept or the slope coefficient
or both. We divided 1998-2008 into two as follow: 1998- June 2006 and July 2006-2008 where
complete foreign exchange reforms occurred. We compute the F-value as follows:
)2/(][
/)]([
2121
21
knnRSSRSS
kRSSRSSRSSF
nn
nnN
−++
+−= (6)
where
=NRSS Restricted residual sum of squares with knndf −+= 21 ,
K= number of parameters estimated,
=+ 21 nn RSSRSS Unrestricted residual sum of squares.
26
Under the null hypothesis 0H that the parameters are stable, we accept the null hypothesis and
conclude that there is no significant change in the parameters between the two periods4.
The results for the control variables suggest that the variables LDSIZE and ASIA impact the
wealth gains accruing to Chinese bidders. However, the EXRATE dummy, LGDP, PROFIT,
EUROPE and the sector-level dummies appear not to have significant effects on the wealth gains
of Chinese acquirers. The lack of effect of the EXRATE rate may be due to virtually fixed nature
of Chinese currency (Renminbi), which is allowed to float within limited margins. The
coefficient for the GDP has a negative sign and the results are not statistically significant. The
LDSIZE has a positive coefficient, indicating that deal size impacts the wealth gain accruing to
Chinese bidders, which is surprising. The expectation that large deals will have the potential to
reduce free cash flows that can be spent in the future, or lead to merger integration problems
thereby conveying a negative signal to the stock market that limited funds are available for future
investment opportunities. However, this appears not to be the case, and the findings support the
conclusions drawn by Asquith et al., (1983), Jarrell and Poulsen, (1989), and Houston and
Ryngaert (1994) whose studies find that average wealth gains to the bidders are associated with
large target size.
Following the work of Kiymaz (2004), we use regional location as control variables. To avoid a
dummy trap 5, the U.S. variable is chosen as a benchmark and other regional dummies are
defined relative to the U.S. The findings in respect to other regional groups are interpreted
4 Our calculated value is 3.34 and at 0.05 critical value of ( =)125,1F 3.92; the test statistics for calculated F<3.92 5 We include two dummy variables for three regions to avoid a “dummy variable trap” and perfect multicollinearity, as recommended by Gujarati (2003), before running the regression.
27
relative to the U.S. The coefficient for the EUROPE variable is positive but statistically
insignificant suggesting that Chinese bidders do experience wealth gains with European
acquisitions, but the gains are statistically insignificant relative to U.S. acquisitions. With regard
to Asia, our results suggest that acquisitions in Asia tend to be value-decreasing compared to
their counterparts in the U.S. and Europe. The coefficient for Asia is negative and statistically
significant. This finding may be explained by the fact that Asia contains diverse countries with
idiosyncratic institutions and legal environments compared to the U.S. For example, the single
market in Europe has created the opportunity for less costly operation across national borders
due to the presence of a common legal environment; this is also true for the U.S. The reduced
operating cost may generate a positive reaction from investors leading to wealth gains for bidders.
Another plausible explanation may be the strategic asset-seeking nature of Chinese acquisitions
in Western Europe and the U.S.; most investments are in motor and communication equipment
manufacturing and technology-related firms that are normally available these countries. Given
that Chinese firms lack these resources, the markets may see acquisition announcements in U.S.
and EUROPE as an opportunity to acquire strategic assets and are therefore more likely to react
positively to such announcements and, consequently, create wealth for the bidders.
We also found home LGDP to be negative and statistically insignificant and with a sign opposite
to that predicted by the model. PROFIT has positive coefficient but the results are not
statistically significant indicating that level of profits of acquiring firms do not create value for
Chinese acquirers. All the sector dummy variables appear to have statistically insignificant
impact on wealth creation for the acquirers. Regarding the impact of level of economic
development of target firm, our results indicate a negative and insignificant effect on wealth
28
gains of Chinese acquirers contrary to our expectation. The CONTR variable has positive but
statistically insignificant impact on wealth gains of acquirers.
Sectoral Analysis
Table 7 reports the effects of various sectors on value creation by the Chinese acquirers. The
results indicate that two sectors, namely, energy and natural resources and transport and
communication have significant impact on wealth creation. The results are in line with the
Chinese government resource seeking policy. It is worth pointing out that, studies such as
Boateng et al., (2008); Rui and Yip (2008); Deng (2007; 2009) have provided an unequivocal
support for resource-seeking behaviour of Chinese firms within the government investment
policy framework. For example, the need to acquire resources in energy, natural resources and
technology in motor and communication equipment industry have led to some high profile
acquisitions in the oil sector, communication equipment and motor car industry such as the
takeover of TCL acquisition of Thomson’s TV (France); Lenovo’s acquisition of IBM’S pc unit
in 2005; Volvo of Netherlands; Rover in the UK; and the acquisition of Canada-based PetroKaz
by China National Petroleum Corporation with massive government support. The significant
impact of reforms in the currency approval system on wealth gains in the energy and resources;
textile and apparel; transport and communication sectors suggest that these priority sectors have
benefited from the reforms in currency approval system. The results confirm the important role
played by Chinese government and indicate that the M&A decisions of Chinese firms are driven
by institutional constraints and incentives put in place by the government rendering support for
institutional theory.
29
The results for the control variables suggest that the variables LDSIZE, level of control,
EXRATE and ASIA appear to negative and significant impact the wealth creation of Chinese
bidders on a number of sectors including energy, manufacturing, general trade, service, and
transport and communication. However, the EXRATE and LGDP appear to have significant
effects on the wealth gains in energy & natural resources and transport and communication
sectors.
(Insert Table 7 here)
Summary and Conclusion
This study has investigated the wealth creation and factors that impact on the wealth effects of
CBM&As by Chinese bidders. Using a sample of 148 acquisitions announcements by Chinese
firms in the U.S., Europe and Asia, this paper makes some significant contributions on two fronts.
First, much of the academic research on M&As over the past three decades have centred on one
crucial question: do M&As create value? This question is of crucial importance to researchers
and practicing managers and the quest to answer it is important, yet existing studies, which have
been based in advanced market economies, have produced mixed and inconclusive results (see
Morck and Yeung, 1991; Markides and Ittner, 1994; Moeller and Schlingemann, 2005; Eun,
Kolodny, & Scheraga, 1996). This study is one of the rare attempts to examine whether
international acquisitions by firms from China, the biggest emerging economy and one that has
seen unprecedented reforms over the past two decades, creates value for the acquiring firms.
Second, we make contribution to the institutional theory by test whether conforming to the
30
Chinese government-directed policies and reforms in the currency approval system lead to
wealth creation for Chinese bidders in the global market for corporate control.
We find evidence of positive abnormal returns for Chinese acquirers and identify the contextual
factors under which CBM&As create value. Our findings indicate that the average abnormal
returns for Chinese bidders range from 0.73%-0.89% over the 3-day event window, suggesting
that acquisition announcements of Chinese firms, on average, are perceived by investors to
create wealth for shareholders. The results appear to support the findings of Morck and Yeung
(1992), and a similar study by Boateng, Wang and Wang (2008), who find that CBM&As by
Chinese firms increase the wealth of the acquirers.
The cross-sectional results obtained indicate that government-backed priority sectors and the
reforms in the foreign currency approval system have positively influenced the wealth gains of
Chinese acquirers. We conclude that Chinese firms backed by the state and seeking strategic
assets tend to increase firm value and therefore provide support for the institutional theory. The
underlying cause of the wealth improvement is that Chinese firms conform to government-
directed policy and acquire strategic assets not available at home to bolster national
competitiveness. In return, the state provides support such as low interest loans and other
incentives to these firms, thereby eliciting a positive reaction from investors regarding the future
prospects of the firms and their values. We therefore conclude that conformity to government
strategic policy direction has a positive effect on shareholder wealth creation and render support
to studies such as Deephouse (1999); Westphal, Gulati and Shortell, 1997); DiMaggio and
Powell (1983). Another important conclusion is that specific reforms, such as easing restrictions
31
on currency for outward investments, improve firm value. We therefore suggest that the
government should take additional steps to further reduce other restrictions on outward
investments.
Regarding control variables, we find that the size of the deal is associated with value creation.
However, our results indicate that Asian targets have a negative and significant impact on
shareholder wealth. This suggests that international expansion to Asia by Chinese bidders is
associated with value destruction, as opposed to the U.S. and Europe acquisitions.
The policy implication of the above results is that home country policies and institutions do not
only shape international expansion strategies of firms but also provide opportunities for
significant value-creating activities, which correlate positively with market expectations. The
findings appear to support the conclusion drawn by Gubbi et al., (2010), who point out that
international acquisitions provide an opportunity to acquire resources and reconfigure
capabilities, which facilitates strategic and organisational transformation of firms from emerging
markets.
Although this study has elucidated the wealth effects of Chinese acquirers and the factors
influencing value creation, these findings should be considered preliminary; first, given that the
study concentrated on only home country variables. Second, despite a number of steps taken to
ensure the robustness of our results, the study used two measures for conformity to government-
directed policy and reforms in foreign currency approval system variables. We suggest that
future studies should examine both home and host country variables and consider additional
measures for conformity and reforms to currency approval systems.
32
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Table 1: Sample Selection and Sample Characteristics of Chinese Bidders Panel A: Sample Selection Number Percentage CBM&A after Initial Restrictions 445 100 Less: No data/News/missing values 287 8.1 Less Multiple Acquisitions 10 5.8 Net Sample 148 86.1 Panel B: Frequency by Region Asia/Pacific North America European Union Total
80 28 40 148
54.1 18.9 27.0 100
Panel C: Industry Classification Strategic Asset seeking (Priority) 63 42.6 Non-priority (No government support) 85 57.4 Total 148 100 Panel D: Frequency by Year 1998 5 3.3 1999 6 4.1 2000 8 5.4 2001 9 6.2 2002 11 7.4 2003 13 8.8 2004 20 13.5 2005 20 13.5 2006 19 12.8 2007 18 12.2 2008 19 12.8 Panel E: Sectoral Distribution Energy & Natural resources 15 10.1 Manufacturing 45 30.4 General Trade 30 20.3 Textile and Apparel 8 5.4 R & D 24 16.2 Building & Construction 10 6.8 Transport & Communication 16 10.8
Panel F: Deal Value $10 -100 million 90 60.8 Over $100 million 58 39.4
Total 148 100
Table 2: Measurement of Independent Variables Variables Measurement Government Priority Sector (CGOPD)
The sample was classified into two sectors: the top-priority sector, backed by the state, and the non-priority sector. A dummy variable representing state-backed sectors (strategic assets seeking) was constructed. Strategic assets seeking companies backed by the Chinese government are equal to 1, otherwise the value is zero.
Government Reforms Policy (GOVREF)
We measure the role of government reforms with a dummy variable: 0= 1998-June, 2006; 1 = July, 2006 – 2008, when the foreign currency approval system for outward investment was abolished.
Home country Gross Domestic Product (LGDP)
The GDP variable is measured as log of GDP during the study period.
Regional Location of the Target (REGION)
Following the work of Kiymaz (2004), a set of regional dummy variables were created based on the target firms geographical location. The Asia dummy variable is equal to one if the acquisition takes place in Asia, and zero otherwise. The U.S. and EUROPE variables are constructed similarly to the Asian dummies.
Exchange Rate (EXRATE)
A dummy for the period when the Chinese currency was fixed (0 = fixed rate; 1 = variable within limited margins).
Deal size (SIZE)
We measured the deal size by the natural log of the amount paid for the target firm
Sector A dummy variable for each sector: 1=Energy & natural resources; 0 =otherwise; 1= Manufacturing; 0 =otherwise; 1= General trade; 0 = otherwise; 1= Textiles & Apparel; 0= otherwise; 1=Service; 0=otherwise 1= Building & Construction; 0=otherwise; 1= Transport & Communication; 0 =otherwise
Control (CONTR) A dummy variable: 1=acquisition gives the acquirer control of the firm; 0=otherwise
Level of economic development (DEVLOP)
Based on IMF’s classification, target countries are classified into two groups: developed and developing economy. A dummy variable: 1= acquisition takes place in a developing country; 0 =otherwise
Notes: For the purpose of this study, priority sectors include: minerals, petroleum, fishery, agriculture products, textiles; motor, communication equipment manufacturing (Cai, 1999; Wu and Sia, 2002).
Table 3: Abnormal returns to Chinese acquirers surrounding the announcement of CBM&As Event Days AAR (%) t-statistics Panel A: Average Daily Abnormal Returns -10 0.0016 0.9636 -9 0.0013 0.4881 -8 - 0.0021 0.3009 -7 0.0013 1.2279 -6 0.0012 0.8967 -5 0.0011 0.2069 -4 0.0032 1.5847 -3 0.0002 -0.2746 -2 -0.0001 0.1707 -1 0.0036 1.7136* 0 0.0073 3.8227*** +1 0.0089 3.7935*** +2 0.0035 1.2583 +3 0.0017 0.8219 +4 0.0007 -0.0530 +5 -0.0011 -0.5609 +6 0.0030 1.3299 +7 0.0019 -0.7557 +8 -0.0018 -0.5587 +9 0.0015 0.7790 +10 0.0024 2.3613** Panel B: Cumulative Abnormal Returns (CAR)
Windows CARs (%) t-statistics CARs (-1,0) 0.0109 2.8655*** CARs (-1,1) 0.0197 3.2916*** CARs(-5,5) 0.0286 1.0879
Note: The null hypothesis is that the average abnormal returns are not statistically different from zero. ***, **, and * indicate statistical significance at the 1%, 5% and 10% levels, respectively.
Table 4: The Role of Government and Value Creation:
Event Window Variable Mean
SD t-value
Panel A Event Window
Priority v. non-priority
CAR (0,1) State-backed sector 0.0268 0.0219 Non-state backed -0.0178 0.1466 2.325** CAR (-1,+1) State-backed sector 0.0409 0.1730 Non-state backed 0.0170 0.1364 1.538
Panel B
CAR (0, 1) July 2006 -2008 0.0438 0.0866 1998 – June, 2006 0.0081 0.1291 -2.652*** CAR (-1, +1) July 2006 -2008 0.0642 0.2174 1998 – June, 2006 0.0079 0.1324 -1.812*
Panel C CAR (0,1) High Growth 0.007 0.0727 Low Growth 0.347 0.0575 0.395
Notes: *p<0.1; **p<0.05; ***p<0.01; Number of cases=148
Table 5: Summary Statistics
Variables Mean Standard Dev Minimum Maximum
CGOPD 0.21 0.408 0.00 1.00 GOVREF 0.28 0.452 0.00 1.00 CAR (0, +1) 0.015 0.687 -0.1747 0.3342 LGDP 11.258 1.305 8.858 12.264 CONTR 3.135 1.623 10.00 100.00
Energy 0.1014 0.30282 0.00 1.00 Manufacturing 0.3041 0.46157 0.00 1.00 General Trade 0.2027 0.30282 0.00 1.00
Textile 0.0541 0.22689 0.00 1.00 R&D 0.1622 0.36985 0.00 1.00
Building & Const 0.676 0.25185 0.00 1.00 Transport & Com 0.1081 0.31157 0.00 1.00 EXRATE 0.36 0.483 0.00 1.00 USA 0.24 0.420 0.00 1.00 EUROPE 0.16 0.364 0.00 1.00
ASIA 0.61 0.488 0.00 1.00 LDSIZE 4.11 1.754 2.30 10.79
Table 6: Cross-Sectional Regression Results for Chinese bidders Variables Model 1 Model 2
Model 3 Mode1 4 Model 5 Model 6 Model 7
Constant CAR
0.116** (2.171)
0.132* (1.759)
0.129* (1.698)
0.118** (2.177)
0.124* (1.642)
0.127* (1.702)
0.121 (1.600)
CGOPD 0.305** (2.121)
0.321*** (3.482)
0.320*** (3.446)
0.307** (2.121)
0.299** (2.055)
0.314*** (3.409)
0.316*** (3.409)
GOVREF
0.192** (2.313)
0.185** (2.241)
0.188** (2.266)
0.189** (2.274)
0.179** (2.211)
0.183** (2.213)
0.189*** (2.275)
Control variables
LDSIZE 0.167* (1.794)
0.164 * (1.830)
0.177* (1.903)
0.165* (1.748))
0.176* (1.860)
0.168* (1.876)
0.163* (1.789)
CONTR 0.062 (0.725)-
0.078 (0.922) -
0.066 (0.767)
0.071 (0.839)
0.066 (0.782)-
0.062 (0.732)
0.069 (0.814)
EUROPE - - - -
0.060 (0.467)
PROFIT -
0.053 (0.200)
-
-
0.035 (0.556)
0.052 (0.657)
-
ASIA -0.272*** (-2.798)
-0.37 (-0.816)
-0.309 -(0.675)
-0.274*** (-2.796)
0.269*** (-2.751)
-0.312 (-0.685)
-0.312 (-0.680)
LGDP -0.062 -0.713
-0.042 -0.475
-0.071 -0.822
-0.073 (-0.841)
-0.059 (-0.655)
-0.088 (-1.019)
-0.073 (-0.844)
EXRATE 0.015 - - 0.010 0.023 - -
(0.103) (0.064) (0.152)
GTRADE 0.065 (0.769)
MANUF
-0.105 (-1.232)
ENERGY
-0.041 (-0.471)
TEXTILE
-0.016 (-0.186)
R&D
0.058 (0.653)
BUILD
-0.098 (-1.184)
TRNSP
0.018 (0.217)
F-statistic 3.891 *** 4.025 *** 3.838 *** 3.811 *** 3.868*** 4.008*** 3.813*** R2 0.233 0.24 0.231 0.230 0.232 0.239 0.230 Adj. R2 0.173 0.18 0.171 0.169 0.172 0.186 0.170
1. Following the work of Kiymaz (2004), we used standardised cumulative Abnormal Returns (CAR) for the (0, 1) period as a dependent variable. 2. Beta denotes standardised coefficient; *p<0.1; **p<0.05; ***p<0.01; Number of cases=148
Table 7: Cross-Sectional Regression Results for Chinese bidders by Sector
Variables in model
Sector 1 Sector 2 Sector 3 Sector 4 Sector 5 Sector 6 Sector 7
Constant CAR
0.911*
(2.616)
0.068*
(0.781)
0.168
(1.616)
2.238
(1.342)
0.165***
(2.952)
0.050***
(5.430)
0.159*
(1.714)
CGOPD
1.474**
(2.775)
0.240
(0.942)
0.330
(0.829) -
0.056
(0.689) -
0.980***
(3.673)
GOVREF 2.495**
(2.887)
0.176
(0.644)
0.243
(0.580)
0.792**
(2.760)
-0.026
(-0.339) -
0.980***
(2.861)
EXRATE -
0.091
(0.538)
-0.209
(-1.129)
-2.238
(-1.470)
-0.269
(1.267) -
0.453*
(1.818)
LGDP 2.586*
(2.508)
-0.148
(-0.754)
-0207
(-1.126) - - -
0.725*
(1.977)
Ownership - -
0.149
(0.804) -
-0.358*
(-1.735)
-1.319***(
6.751) -
ASIA -2.898**
(-3.052)
-0.271
(-1.555)
-0.535**
(-2.732)
2.644
(1.328)
0.449**
(-2.150)
-41.361**
(-5.549
-0.651*
(-1.943)
LDSIZE -0.018
(-0.605)
-0.339*
(-1.956) -
-0.735*
(-2.486) -
-40.391**
(-5.465) -
R2 0.896 0.138 0.560 0.800 0.295 0.913 0.762
Adjusted R2 0.740 0.023 0.400 0.532 0.177 0.861 0.584
F-statistic 5.743* 0.855 3.473*** 2.991** 2.508* 17.517*** 4.278***
Notes: Sector 1= Energy & Natural Resources; Sector 2= Manufacturing; Sector 3=General Trade Sector 4 =Textile & Apparel; Sector 5= R&D; Sector 6 = Building & Construction;
Sector 7 = Transport & Communication
