firm restructuring during an economy-wide shock across institutional environments

FIRM RESTRUCTURING DURING AN ECONOMY-WIDE SHOCK ACROSS

INSTITUTIONAL ENVIRONMENTS

Kulwant Singh

Department of Strategy and Policy National University of Singapore

15 Kent Ridge Drive Singapore 119245

Tel: (65) 6874 3174 Fax: (65) 6779 5059

Email: [email protected]

Ishtiaq P. Mahmood Department of Strategy and Policy National University of Singapore

15 Kent Ridge Drive Singapore 119245

Phone: (65) 6516 6387 Fax: (65) 6779 5059

E-mail: [email protected]

Jinyan Zhu Triumpus capital

15 Scotts Road #08-13 Singapore 228218

Tel: (65) 6874 3075 Fax: (65) 6779 5059

Email: [email protected]

An earlier version of this paper was presented at the Business Policy and Strategy Division, Academy of Management Meetings in August 2003. We thank Abhirup Chakrabarti, Inmoo Lee, Foo Maw Der, Navid Asgari, two anonymous reviewers and Editor Ed Zajac for their valuable comments and suggestions. We also appreciate financial support from the National University of Singapore Research Grant.

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FIRM RESTRUCTURING DURING AN ECONOMY-WIDE SHOCK ACROSS

INSTITUTIONAL ENVIRONMENTS

Abstract

We examine how firms restructure during an economy-wide shock and how the institutional

environment affects restructuring and its outcomes. We draw primarily from institutional

economics and resource-based theory to argue that access to internal and external resources and

the extent of firm embeddedness within the institutional environment are key influences on the

incidence and outcomes of restructuring. Results show that firms may increase or decrease

restructuring during an economy-wide shock depending on their experience with change and

adaptation before the shock, their performance during the shock and their affiliation with

business groups. In most cases, restructuring during the shock improved performance. Results

are consistent with the view that firm characteristics and institutional environments significantly

influence restructuring and its outcomes during an economy-wide shock.

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An economy-wide shock is a sudden, substantial and unanticipated change in the

macroeconomic environment, whose impact spreads beyond specific firms or industries to

disrupt wide sectors of an economy. Economy-wide shocks typically lead to a major and sudden

slowdown in economic activity, with significant declines in business turnover, profitability,

liquidity, investment, employment and optimism. The Great Depression of the 1930s in the US,

currency crises in the 1980s and 1990s in Latin America, the Asian Economic Crisis of 1997 and

the financial crises that struck many countries in 2007 are examples of economy-wide shocks.

Economy-wide shocks, particularly those with financial roots, occur regularly (Mishkin, 2006;

Reinhart and Rogoff, 2009) but attract little attention in strategy research.

Recent economic research (Corsetti, Pesenti and Roubini, 1999; Hahm and Mishkin, 2000;

Reinhart and Rogoff, 2009) has improved understanding of the causes of economy-wide shocks

and their impact on macroeconomic variables such as trade, inflation and growth. Despite recent

interest (e.g., Chakrabarti, 2009; Chang, 2006; Fisher, Lee and Johns 2004; Singh and Yip 2000;

Wan and Yiu, 2009) strategy research has not systematically evaluated microeconomic responses

to sudden, major shocks that affect the broad economic environment, limiting knowledge of the

interface between these shocks and firm strategy (Suarez and Oliva, 2005).

The breadth and severity of economy-wide shocks limit ambiguity about the extent of the

threat and imply that firms have little choice other than to restructure, to adapt to the altered

environment (Chattopadhyay, Glick and Huber, 2001). Restructuring is the deliberate

modification of a firm's structure, resources or operations to improve alignment with a radically

altered external environment. Restructuring differs from other forms of organizational change

and adaptation in that it is primarily driven by sudden, major and adverse changes in the

environment that negatively affect firm performance. However, disruption to internal and

external markets during an economy-wide shock limits resources available to support

restructuring and constrains the adaptation options available to firms. Thus, an economy-wide

shock increases firms' motivation to restructure but reduces their ability to do so. This

conundrum frames the two issues that are the focus of this paper, the occurrence and outcomes of

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firm restructuring during an economy-wide shock, and how institutional environments influence

restructuring and its outcomes.

We propose that the nature and consequences of firm restructuring in response to an

economy-wide shock depend on firm resources and institutional support. We first evaluate the

incidence of restructuring during an economy-wide shock and how a firm's embeddedness in its

institutional environment influences restructuring. We then examine the performance outcomes

of restructuring. By limiting our analysis to the duration of an economy-wide shock across two

emerging economies, we are able to evaluate the effects of a sharp economic shock on the

immediate restructuring firms undertake within stable institutional environments, across

economies with different institutional structures.

It is important for strategy research to focus on economy-wide shocks for two reasons. First,

economy-wide shocks differ from localized industry- or firm-specific shocks in having different

causes, broader effects and more severe consequences (Corsetti et al., 1999; Hahm and Mishkin,

2000; Kawai, 2000; Reinhart and Rogoff, 2009; Singh and Yip, 2000; Suarez and Oliva, 2005).

Hence, insights from localized shocks do not translate well to economy-wide shocks

(Chakrabarti, 2009; Singh and Yip 2000; Suarez and Oliva, 2005). Second, as economy-wide

shocks recur and spread more quickly across borders (Reinhart and Rogoff, 2009) firms’ survival

and success will increasingly depend on their ability to navigate such shocks. In turn, firms'

restructuring will influence how well countries fare in these economy-wide shocks.

We draw primarily from institutional economics (North, 1990) and resource-based theory

(Barney, 1991; Wernerfelt, 1984). Institutions are the set of interrelated rules and norms, and

their enforcement characteristics that govern exchange (North, 1990). The institutional

environment influences restructuring by establishing rules and norms, and providing or limiting

resources that facilitate or constrain firm actions and outcomes. Resources are uncommon

tangible or intangible entities that have the potential to provide competitive advantage (Barney,

1991). Resource-based theory (Barney, 1991; Wernerfelt, 1984) proposes that firm activities and

performance depend on firm-specific availability of resources and capabilities to deploy these

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resources. Resource availability, therefore, has the potential to influence restructuring and its

outcomes. These two theoretical perspectives indicate that firms may differ in restructuring

following an economy-wide shock because of varying access to resources and because the

environment provides different pressures, constraints and support for restructuring.

Empirically, we focus on firm restructuring in South Korea and Singapore following the

major economic crisis that struck these countries in 1997. Major economy-wide shocks permit

first-difference analyses of the effects of major environmental change on firm restructuring and

performance, while substantially controlling for the evolution of institutions. Differences in

institutional structures across South Korea and Singapore (Dent, 2002; Rodan, Hewison and

Robison, 2006) permit evaluation of how institutions affect restructuring. Few studies have

examined the joint impact of economy-wide shocks and institutional influences on restructuring.

We make four main contributions. First, we contribute to the deepening of the organizational

change and restructuring literatures (Bowman and Singh, 1990, 1993; Greenwood and Hinings,

1996; Kraatz and Zajac, 2001; Rajagopalan and Spreitzer, 1997) by advancing understanding of

how firms react to economy-wide shocks and of the outcomes of their actions. In demonstrating

that institutions enable and constrain organizational restructuring and its outcomes, we broaden

the organizational change literature, which has not followed strategy researchers (e.g., Peng,

2003; Makhija, 2004) in paying attention to institutional influences. Second, we contribute to the

institutional perspective as applied to organizations (Peng, 2002; 2003). While this perspective

highlights the external contingencies that affect firms’ restructuring, it underplays inter-firm

variation in restructuring. Our evaluation of the interaction of institutions and organizations in

the context of an economic shock improves understanding of the multi-level mechanisms that

generate restructuring. Third, we contribute to the literature on economic shocks, which focuses

on macroeconomic ramifications of economy-wide shocks but does not adequately consider

micro-economic actions or consequences. We show that evaluating microeconomic adaptation to

macroeconomic shocks improves understanding of firm-level consequences and outcomes of

economy-wide shocks. Finally, we pay attention to issues of endogeneity to account for the

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possibility that heterogeneity in firm-specific motivation may lead to spurious associations

between restructuring and performance. Beck, Brüderl and Woywode (2008) show that most

studies in this field have failed to deal with this issue, producing potentially biased results.

ECONOMY-WIDE SHOCKS, RESTRUCTURING AND EMBEDDEDNESS

Economy-wide shocks

Economy-wide shocks are an extreme form of environmental change, which Suarez and Oliva

(2005) characterize as "avalanche change" because they are high in terms of amplitude, speed

and scope of change but occur infrequently. Firms face significantly different environments

during economy-wide shocks from those during localized shocks, with a key difference being the

availability of resources to support restructuring.

An economy-wide shock affects broad sectors of the economy simultaneously, causing a

decline in economy-wide aggregate demand, which in turn hurts consumer and investor

confidence, exacerbating the demand shock (Dwor-Frecaut, et al., 2000; Mishkin, 2006). Capital

and other resources are typically in short supply and further restricted by the adoption of

conservative policies by banks, industry bodies and regulators, because of increased uncertainty

(Hahm and Mishkin, 2000; Reinhart and Rogoff, 2009). Severe economic conditions may also

encourage these actors to modify norms and regulations, hindering the operations of institutions,

markets and intermediaries (Hahm and Mishkin, 2000; Johnson and Mitton, 2003). Firms face

reduced access to credit and financial markets, disruption of supply and distribution channels,

reduced opportunities for mergers and acquisitions or asset changes, weaker demand, poorer

performance and disrupted strategy (Dwor-Frecaut, et al., 2000; Singh and Yip, 2000).

In contrast, firm- or industry-specific shocks typically result from supply disruptions, sudden

increases in competition, demand changes or technological shocks that adversely affect some

firms or an industry. Capital markets, other economic institutions, foreign trade and the broader

economy are usually relatively unaffected by localized shocks, so that external resources and

institutional support for firm restructuring largely remain available (Kawai, 2000).

The "sub-prime" economy-wide shock of 2007-2008 affected broad sectors of the U.S.

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economy, caused a severe recession, disrupted capital and retail markets, and hurt firm

performance. Many firms faced severe resource shortages which were compounded by reduced

access to external sources of funds. Automobile manufacturers such as GM and Ford, for

example, faced major declines in demand, revenue, profitability and liquidity, but could not raise

funds because the economy-wide shock affected financial markets and other potential sources of

resources. GM and Ford were forced into bankruptcy and were taken over by the government,

which provided resources and support for restructuring.

The major earthquake and Tsunami that struck Japan in 2011 is an example of a major but

localized shock. This caused the Japanese economy to slow significantly and severely disrupted

the operations and sales of many firms. However, most effects were localized geographically or

to particular industries, so that the broader economy was not so severely affected as to prevent

support for firms seeking resources or to restructure. Despite the recession, markets resumed

close-to-normal operations within a short period, allowing firms in distressed industries to access

traditional sources for resources to support restructuring.

Table 1 summarizes key differences between economy-wide and localized shocks. In

summary, economy-wide shocks are more likely to disrupt the operations of the economy,

markets and intermediaries, to increase uncertainty, and to reduce firms' internal resources and

their access to external resources. The severity of economy-wide shocks and the breadth of their

impact increase the need for firms to restructure, while typically limiting firms' restructuring

options to a subset of choices available during localized shocks or non-shock periods.

***Table 1 about here***

Restructuring

Restructuring and other forms of organizational change incorporate a broad range of actions that

can lead to firm expansion or contraction, financial restructuring, changes in the scope of

activities, or changes to employment and internal structures. The key distinction between

restructuring and other forms of organizational change lies in the motivation for restructuring – a

sudden, major and unforeseen shock to the external environment that threatens firm performance

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and causes firms to undertake adaptation actions – rather than in the specific types of actions that

firms take.1 For example, a firm may raise additional capital, sell a business or modify the

structure of its divisions in reaction to a major external economic shock or because of a change

in strategy; the former motivation indicates restructuring, while the latter represents other forms

of change. How firms adapt to major external shocks has been studied from the perspective of

general environmental change (e.g., Greenwood and Hinings, 1996; Kraatz and Zajac, 2001),

major institutional change (e.g., Newman, 2000; Peng, 2003), de-regulation or privatization (e.g.,

Audia, Locke and Smith, 2000; Makhija, 2004) and technological change (e.g., Haveman, 1992;

Mitchell and Singh, 1996). However, few studies have examined the impact of a major economic

shock on restructuring (Suarez and Oliva, 2005).

Firms that restructure typically aim for rapid improvements as major, adverse changes in the

external environment threaten their performance and survival. This may require increased action

to alter the firm's structure, resources or operations, or alternatively, reduced activity to preserve

the firm's assets or operations, or to conserve resources. Restructuring therefore represents a

discontinuity in a firm's pattern or momentum of regular change (Beck et al., 2008).

Restructuring is costly, requiring firms to invest resources in undertaking transactions that

alter the financial, operational and organizational structure of the firm or its base of assets and

activities (Chakrabarti, 2009; Bowman and Singh, 1990, 1993; Mitchell and Singh, 1996). Even

efforts to reduce the asset or cost structure of a firm may incur costs for disposing assets, laying-

off employees, writing-off facilities, transferring resources and executing transactions.

Restructuring is also difficult, requiring firms to have the managerial capabilities to undertake

major changes while minimizing disruption to assets, operations, structures and people. The

availability and need for resources is therefore an important influence on how firms restructure.

How firms use and adapt their resources to changing environments is central to resource-

1A range of overlapping and imprecisely distinguished constructs relate to restructuring (Suarez and Oliva, 2005). These include adaptation, change, downsizing, reconfiguration, reorganization, transformation and turnaround. Transformation (Newman, 2000) and turnaround (Chakrabarti, 2009) relate most closely to our concept of restructuring as externally-induced change, but imply and focus on successful outcomes (Newman, 2000). In contrast, our conceptualization focuses on firms' actions and accommodates successful and failed outcomes. We refer to firms' adaptation to causes other than major external shocks as "change and adaptation."

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based theory (Barney, 1991; Wernerfelt, 1984). Firms are more likely to achieve strong

performance through the stable deployment of resources, supported by capabilities that commit

firms to consistent strategies (Barney, 1991). Rapid or radical restructuring that disrupts the

deployment of resources, capabilities and routines may harm firm performance (Kraatz and

Zajac, 2001; Newman 2000). More broadly, the strategic change literature warns that

organizational and managerial disruption following restructuring may offset the benefits of

improved resource alignment with the environment (Haveman, 1992; Rajagopalan and Spreitzer,

1997). Restructuring thus poses a dilemma: firms that do not restructure in response to major

environmental change risk poorer performance from misalignment, while firms that restructure

bear the costs of disruption following major internal change.

Three broad conclusions from the organizational change and restructuring literature are: (1)

Restructuring is difficult and costly. (2) Complex combinations of organizational resources and

external factors create heterogeneity in firms' ability and willingness to restructure, and in the

outcomes of restructuring. (3) Little research has examined the joint impact of economy-wide

shocks and the institutional environment on restructuring; most studies examine firms within

single countries, removing institutional variation.

Institutional Environments and Embeddedness

Institutional economics (North, 1990; Peng, 2002; 2003) explains that the institutional

environment shapes firms' options, choices, behavior and performance. A key insight is that the

institutional structure significantly influences how firms organize and perform by specifying the

rules, constraints and incentives for doing business. The sociological tradition of institutional

theory (Pfeffer and Salancik, 1978) offers a complementary prediction, that as firms depend on

the environment within which they are embedded for resources, firm choices are enabled or

constrained by the environment. Firms that align with the institutional environment are rewarded

with improved performance.

The institutional environment can affect restructuring in three ways. First, institutional

structures establish the normative contexts that define acceptable economic behavior and

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performance, and determine the general incentive structures and constraints within an economy

(North, 1990; Peng, 2003; Whitley, 1999). More developed institutional environments,

particularly markets for corporate control, impose greater pressures for performance by offering

stronger incentives, prescribing clearer rules and norms, and providing more reliable valuation of

firms' performance and prospects (Chakrabarti, Vidal and Mitchell, 2011; Mishkin, 2006).

Institutional ambiguity, which often characterizes less developed institutional environments,

creates uncertainty about firms' status, prospects and options, and raises the transactions costs of

restructuring activities, hindering restructuring.

Second, component institutions and intermediaries of the institutional structure will affect the

resources and support that facilitate or hinder restructuring and its outcomes (Chakrabarti et al.,

2011; Makhija, 2004). Developed institutions and intermediaries are more effective at mobilizing

resources and channelling them to firms, and at providing the support firms need to restructure.

Support for restructuring includes, for example, rules and regulations to indicate available

options; intermediaries to guide firms in selecting and undertaking these actions; access to

markets for the sale or purchase of assets and the raising of financial and other resources; and

guidelines and systems for managing human resource and other organizational changes. These

mechanisms and intermediaries are more available and effective in more developed institutional

environments (Khanna and Rivkin, 2001; Makhija, 2004; Peng 2003)

Third, a firm’s embeddedness within specific institutions can influence its restructuring by

nesting it within a socio-economic context that can facilitate or constrain access to resources

(Aoki, 2001; Newman, 2000) and buffer it from the need to restructure. A buffer is an

intervening factor that protects an organization from environmental pressures (Aldrich, 1979).

Institutional embeddedness refers to the extent to which a firm’s decisions are constrained by its

relationship with external constituents (Carney, 2004; Feenstra and Hamilton, 2006; Greenwood

and Hinings, 1996), such as business groups, banks, politicians, and governments. These

relationships may provide privileged access to information, financial loans and transfers, licenses,

business contracts, protection from competition and other favors that buffer firms from market

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and environmental pressures (Chang, 2003; Feenstra and Hamilton, 2006; Mishkin, 2006;

Whitley, 1999) and allow them to avoid or limit restructuring.

Collectively, these institutional influences will determine how the effects of an economy-

wide shock are felt by firms, firms' propensity to restructure, the type of restructuring they

undertake, and restructuring outcomes. The large and complex literatures on firm change and

restructuring have paid limited attention to the impact of institutional structures on firm

restructuring and its outcomes, particularly in the context of economy-wide shocks.

HYPOTHESES

Our examination of restructuring across institutional structures during an economy-wide

shock relies on four theoretical building blocks: (1) Firms will restructure if the need to

restructure exceeds their ability to withstand such pressures. (2) Relative to localized shocks,

economy-wide shocks exert greater pressures on firms to restructure and reduce more greatly the

resources that may buffer firms from external pressure to restructure. (3) Institutional

environments influence restructuring, as more developed institutional structures exert greater

pressures to restructure, provide greater resources and support for restructuring, and limit

opportunities for buffering. (4) Institutional embeddedness moderates restructuring by providing

resources that may buffer restructuring pressures.

Hypotheses 1a and 1b: Incidence of restructuring

An economy-wide shock radically alters economic and business environments, and leads to two

key firm outcomes, weaker performance and reduced access to resources. While a decline in

performance is likely to increase the incentive to restructure, access to internal and external

resources may reduce the need to restructure. Firms are compelled to restructure only when both

outcomes – the incentive to restructure as well as the loss of resource buffers – occur at the same

time. These outcomes are more likely following an economy-wide shock than at other times

(Reinhart and Rogoff, 2009; Singh and Yip, 2000).

The severity of an economy-wide shock substantially restricts management’s options and

reduces ambiguity on the need to restructure (Audia et al., 2000; Chattopadhyay et al., 2001).

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Severe economic conditions lead to actual or prospective performance decline, reduce the

availability of internal resources and access to external resources, undermine strategy and

operations, and increase the likelihood that firms will act to preserve or improve performance.

An economy-wide shock also moderates the embeddedness that may allow firms to avoid

restructuring by weakening ties to connected organizations and the resources they can provide.

Hence, efficiency-maximizing considerations designed to improve performance are likely to

drive firms to restructure during an economy-wide shock.

However, restructuring will be constrained by the uncertainty accompanying a major shock,

which may cause firms to resist change or to act conservatively in restructuring (Audia et al.,

2000; Karim and Carroll, 2008; Staw, Sandelands and Dutton, 1981). Restructuring costs,

resource constraints and high transactions costs in the midst of a major crisis will further hinder

restructuring. Firms with high rates of change and adaptation prior to the shock may chose not to

increase restructuring during the economy-wide shock but may reduce restructuring instead. The

restructuring literature has focused on actions firms take during or after an economy-wide shock

(e.g., Fisher et al., 2004; Suarez and Oliva, 2005) without adequately considering how prior

change and adaptation may affect restructuring during it (Beck et al., 2008).

Therefore, firms may increase or decrease their restructuring during an economy-wide shock

depending on their need to restructure, their ability to overcome constraints on restructuring, and

pre-shock levels of adaptation and change. As it is uncertain which effect will dominate, we

make the baseline prediction that restructuring during an economy-wide shock will depart from

prior rate of adaptation and change. Hypothesis 1a: Firm restructuring during an economy-wide shock will change significantly from change and adaptation prior to the shock.

The institutional environment will influence how firms restructure during an economy-wide

shock through the pressures imposed on firms to restructure, the resources and support firms can

access to restructure, and the availability of buffers that may allow firms to avoid restructuring.

Developed institutional structures have relatively elaborate formal rules and norms, more

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effective enforcement and more sophisticated actors and intermediaries, all of which will

transmit the effects of economy-wide shocks more directly to firms and impose greater pressures

for restructuring. Markets and intermediaries will signal and transmit the adverse economic

conditions more efficiently so that firms will face reduced demand, more constrained and costly

borrowing, market-based and risk-adjusted valuations, and greater pressures from owners to

restore performance (Mishkin, 2006). Firms will face greater normative pressures to install

structures and undertake actions that conform to adverse economic conditions. More developed

institutional structures can also potentially provide greater access to resources and support for

restructuring (Chakrabarti et al., 2011). Institutions and intermediaries associated with more

developed structures are likely to be less supportive of efforts to avoid restructuring and less

likely to provide buffers to enable such efforts (Mishkin, 2006).

In contrast, less developed institutional structures will impose fewer pressures to restructure,

provide fewer resources and less support for restructuring, and will be less effective at

preventing firms from using buffers to avoid restructuring. Inadequate rules and regulations and

their poor enforcement, inadequate or missing intermediaries, information asymmetry and other

institutional weaknesses also hinder restructuring in less developed institutional environments

(Chakrabarti et al., 2011; Makhija 2004; Mishkin, 2006). These arguments suggest that firms in

more developed institutional environments are more likely to increase restructuring during an

economy-wide shock relative to firms in less developed institutional environments.

However, these differences in institutional environments will also influence change and

adaptation in non-shock periods. Hence, firms in more developed institutional environments are

likely to undertake greater change and adaptation prior to the shock, and through this experience,

improve routines and capabilities that will facilitate restructuring during an economy-wide shock.

Firms in less developed institutional environments will undertake less adaptation and change in

non-shock periods, and thus have less experience and weaker restructuring capabilities.

Therefore, firms in more developed institutional environments will likely have stronger

capabilities and support from the institutional environment for restructuring, while firms in less

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developed institutional environments will have weaker capabilities and support for restructuring.

However, firms in less developed institutional environments will suffer greater loss of

buffers during an economy-wide shock because of disruption of non-market relationships.

Though non-market relationships may be disrupted in all markets, firms in less developed

environments are more reliant on non-market relationships for resources. Firms in less developed

institutional environments also have greater scope to increase restructuring during an economy-

wide shock because of relatively low levels of pre-shock change and adaptation. On balance, we

predict that firms in less developed institutional environments are more likely to increase

restructuring when an economy-wide shock strikes.

Hypothesis 1b: The less developed the institutional environment, the greater the likelihood that firms will increase restructuring from pre-shock change and adaptation when an economy-wide shock strikes.

We expect firms to undertake a broad range of restructuring actions, contingent on the

interaction of firm and institutional characteristics. Bowman and Singh (1990, 1993) propose a

strategic conceptualization that classifies restructuring actions into three categories. Financial

restructuring refers to significant changes to a firm’s capital structure, such as the infusion of

debt, leveraged buyouts, stock repurchases or injection of funds. Portfolio restructuring involves

significant change to the mix of assets a firm owns or to its scope of business. Organizational

restructuring consists of significant structural changes such as realignment of processes,

structures and operations, or changes in ownership, management and employment.

In Table 2 we explore how key components of the institutional structure may constrain or

enable financial, portfolio and organizational restructuring, demonstrating the value of

examining the impact of institutional components on firm restructuring. This analysis shows that

the institutional structure may constrain restructuring through multiple mechanisms, many of

which follow from increased risk and uncertainty, weaker economic conditions and markets, and

reduced resource availability. However, institutional structures and adverse conditions may also

motivate and facilitate some types of restructuring. In light of this ambiguity, we do not

hypothesize on the specific types of restructuring firms undertake but evaluate these empirically.

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Who will restructure more?

Hypotheses 2a and 2b: Business group affiliation

We reinforce our focus on institutional differences by evaluating the embeddedness of firms into

stable institutions within each country, identifying business group membership as a key

characteristic. Business groups are a network form of organization comprising legally

independent firms with strong financial and administrative ties (Chang, 2006; Khanna and

Rivkin, 2001). Business group affiliation is associated with central coordination, internal trading

and sharing of resources, potentially greater access to external resources, greater embeddedness

and restricted firm flexibility (Chang, 2003; Feenstra and Hamilton, 2006; Whitley, 1999). The

business groups literature has not investigated how group affiliation influences restructuring,

except in broad terms (Chang, 2003; 2006).

Group affiliation can reduce restructuring in two ways. First, group affiliated firms have

greater access to group-wide resources, which may allow them to avoid restructuring. Intra-

group buyer-supplier relationships, interlocking directors, mutual debt guarantees, direct transfer

of resources and cross-shareholdings are some of the mechanisms that allow resource sharing

within a group (Chang, 2003; Feenstra and Hamilton, 2006; Khanna and Rivkin, 2001).

Chakrabarti et al. (2007) found that group-affiliated firms gained from resource transfers,

particularly in less developed economies. Ahmadjian and Robbins (2005) found that firms more

integrated into the Japanese business system through higher levels of shareholdings by financial

institutions had better access to financing and lenders of last resort, making them less susceptible

to restructuring pressures from foreign shareholders. Carney (2004) argues that business groups

resist change to avoid upsetting their internal and external ties and relationships.

Second, group-affiliated firms are more institutionally-embedded than non-group firms,

suggesting that group-affiliated firms may have less incentive to restructure. Institutional and

market weaknesses in emerging or transitional economies allow business groups and their

leaders to develop relationships with dominant institutions that provide access to resources and

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buffers (Chang, 2003; Feenstra and Hamilton, 2006; Johnson and Mitton, 2003; Mishkin, 2006;

Peng, 2003). Business groups' economic importance in less developed institutional environments

reinforces their privileged access to resources (Feenstra and Hamilton, 2006; Khanna and Rivkin,

2001; Tsui-Auch, 2006) particularly in environments where connections to politicians and

bureaucrats can facilitate resource access (Chang, 2006; Dent, 2002; Whitley, 1999). Johnson

and Mitton (2003) found that politically connected firms received additional resources following

an economy-wide shock, enabling them to limit restructuring. Baek, Kang and Park (2004) and

Mishkin (2006) report that business groups in South Korea enjoyed favored access to resources

during an economic crisis.

However, an economy-wide shock will weaken external ties and the buffering these ties

provide business groups. An economy-wide shock will affect institutions, markets,

intermediaries and other actors, and disrupt the resources and support that they can provide to

connected business groups (Mishkin, 2006). In turn, the disruption suffered by groups will limit

the current or future resources they can reciprocate to these intermediaries and actors, which will

weaken ties and resource transfers. This suggests that an economy-wide shock will weaken the

buffers that may shield group affiliates from restructuring.

Though an economy-wide shock will weaken buffers, business groups are likely to have

greater access to resources relative to non-group firms because of internal transfers and because

they are more embedded, as discussed above. In addition, business groups may enjoy greater

resource support during an economy-wide shock because they have disproportionately important

economic impact. Chang (2003) and Mishkin (2006) report that business groups in South Korea

were perceived to be "too big to fail" and received disproportionate support during an economy-

wide shock, while Tsui-Auch (2006) indicates that government-linked groups in Singapore also

gained from their association with the government. Therefore, group affiliates may be less

inclined to restructure than non-group firms because they are more embedded within networks of

internal and external relationships that buffer them from pressures to restructure.

Hypothesis 2a: Group affiliated firms will restructure less than non-group firms during an

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economy-wide shock.

The extent to which group affiliation may buffer firm restructuring depends on the

development of the institutional structure. Developed institutional structures, particularly well

developed markets for corporate control, may make it more difficult for groups to cushion poor

performing affiliates (Kawai, 2000; Mishkin, 2006). These institutional structures will impose

greater pressures on groups to restructure and will be less compliant in providing resources that

may defer restructuring (Chakrabarti, 2009; Makhija, 2004), thereby reducing the inertial effects

of resource sharing and institutional embeddedness on group-affiliated firms' restructuring. For

example, group-affiliated firms are more likely to lose their privileged access to external

resources following an economy-wide shock when capital markets are more developed. Stock

markets are more likely to rate poorly, group affiliates that fail to restructure appropriately.

Banks may be less willing to provide new loans to group-affiliated firms or may impose stringent

conditions on such loans to limit resource diversion to more distressed firms within the group.

These effects will be weaker in less developed institutional environments. For example, Chang

(2003: 196) illustrates how business groups in South Korea avoided financial restructuring by

artificially re-valuing their assets and by issuing equity to affiliated firms. Developed capital

markets are less likely to accommodate such efforts to buffer (Mishkin, 2006).

Following the arguments of Hypothesis 1b, group affiliates in less developed institutional

environments will suffer greater loss of buffers during economy-wide shocks than groups in

more developed institutional environments, while being more reliant on these buffers. These

firms will have greater scope for restructuring, because of lower levels pre-shock change and

adaptation. We therefore expect group affiliates to have greater pressures, resources and support

for restructuring in more developed institutional environments, and those in less developed

institutional environment to have greater need for restructuring because of the loss of buffers and

greater scope for increasing restructuring. As the loss of buffers may be critical, we predict that

group affiliates will increase restructuring more relative to non-group firms in less developed

environments, than group affiliates will relative to non-group firms in more developed

17

institutional environments.2 Therefore, we expect that the moderating effects of group-affiliation

on restructuring to be weaker in less developed institutional environments. Hypothesis 2b: The less developed the institutional environment, the weaker the negative impact of group affiliation on restructuring during an economy-wide shock.

In developing Hypothesis 1b, we argued that firms in more developed institutional

environments would have developed greater restructuring capabilities from restructuring more in

the non-shock period. This argument also applies to Hypothesis 2b. We therefore control for

firms' propensity to restructure in our empirical analysis.

Hypotheses 3a and 3b: Prior Performance

Poor performance is an important motivator of restructuring (Bowman and Singh, 1990). Poor

performance reduces the stock and flow of resources within an organization, prompts managers

to recognize their firm's condition, and induces restructuring to conserve and raise additional

resources. Kraatz and Zajac (2001) show that firms with greater resources are less likely to

restructure because resources can protect firms from environmental pressures. Cheng and Kesner

(1997) find that resource availability in the form of slack may make organizations more or less

likely to respond to environmental change. However, poor performance may reduce the stock of

internal resources to support restructuring, and may restrict access to external resources and

support, which will hinder restructuring. On balance, the severity of economy-wide shocks will

limit the options for poorly performing firms to defer restructuring. Therefore, we expect poor

performance to lead to increased restructuring. Hypothesis 3a: Firms will restructure more during an economy-wide shock, the poorer their performance.

Poor performance will pose fewer constraints if a firm has access to external resources that

may buffer external pressures and allow restructuring to be avoided or delayed (Ahmadjian and

Robbins 2005; Johnson and Mitten, 2003; Mishkin, 2006). Several studies discuss inertia from

organizational constraints such as firm age but few have evaluated inertia driven by a firm’s ties,

2 This is compatible with the view (Chang, 2003; Carney, 2004) that business groups resist change and restructuring, as our arguments are relative to non-group firms within institutional environments, not in absolute terms.

18

particularly in less developed institutional environments. Groups often value relationships and

stable performance over superior financial returns (Lincoln, Gerlach and Ahmadjian, 1996;

Whitley, 1999) and resist change that may upset their network of internal and external ties

(Carney, 2004). As hypothesis 2 predicts, firms affiliated with business groups enjoy greater

access to internal and external resources, which may buffer them from the pressures of poor

performance relative to non-group firms. At the same time, more developed institutional

environments will be less tolerant of under-performance and will impose greater pressures for

improvement. Therefore, we expect group affiliation to weaken the effects of poor performance

on restructuring, but that this moderation will be weaker with institutional development. Hypothesis 3b: The less developed the institutional environment, the weaker the negative association between performance and restructuring among group affiliates during an economy-wide shock.

Hypotheses 4a, 4b and 4c: Outcomes of restructuring

The central argument of the organizational change and restructuring literatures is that improving

alignment with altered environments improves firm performance (e.g. Bruton, Ahlstrom and

Wan, 2003; Haveman, 1992; Kraatz and Zajac, 2001; Suarez and Oliva, 2005). Several studies

report that restructuring following a major economic crisis improves firm performance, though

not consistently or for all firms (Chakrabarti, 2009; Claessens et al., 1998; Fisher et al., 2004).

Institutional structures influence the outcomes of restructuring during an economy-wide shock

through pressures to restore performance, providing resources either for restructuring or for

buffering against it, and by providing varying degrees of support for restructuring. More

developed institutional environments will provide relatively greater pressures, resources and

support for restructuring. In economies where markets for corporate control are effective and

access to low-cost or non-market sources of funds is limited, firms will have fewer opportunities

for engaging in restructuring that is not performance oriented, so restructuring is more likely to

improve performance (Fisher et al., 2004; Makhija, 2004). Therefore, while we expect

restructuring to improve performance in general, the combination of greater pressures, greater

resources and support and weaker buffers in more developed environments will lead to more

19

positive restructuring outcomes than in less developed institutional environments. Hypothesis 4a: Restructuring during an economy wide shock is positively associated with firm performance. Hypothesis 4b: The less developed the institutional environment, the weaker the impact of restructuring on firm performance during an economy wide shock.

Group affiliates enjoy the advantage of access to within-group resources, and greater access

to external resources than non-group firms. However, these internal and external sources and

their ties to business groups will weaken during an economy-wide shock, potentially limiting

their resource advantage over non-group firms. Evidence from the Asian crisis of 1997 indicates

that the drying up of bank credit was a critical factor that hindered operations and influenced

restructuring for many business groups (Chang, 2003; Mishkin, 2006). Business groups have

more complex structures and operations, and stronger integration processes and links (Feenstra

and Hamilton, 2006; Whitley, 1999), which may make restructuring more costly and its

outcomes less positive (Greenwood and Hinings, 1996). Chakrabarti et al. (2007) found that

business groups suffered greater performance reversals when economic conditions changed

significantly. We therefore expect that group affiliates will achieve poorer outcomes from

restructuring than non-group firms.

Following our previous arguments, we expect that greater pressures, resources and support

make it more likely that group affiliates in more developed institutional environments will

achieve positive outcomes from restructuring. Group affiliates in less developed institutional

environments, facing weaker pressures for performance, weaker access to resources and support,

and greater loss of buffers, are less likely to achieve positive outcomes from restructuring.

Therefore, we expect group affiliation to weaken the positive impact of restructuring on

performance, particularly in less developed institutional environments. Hypothesis 4c: The less developed the institutional environment, the weaker the association between restructuring and performance among group affiliates during an economy-wide shock.

In summary, we hypothesize that firms will change their restructuring pattern when an economy-

wide shock strikes (H1a) with greater likelihood that they will increase restructuring in less

20

developed institutional environments (H1b). We then predict that during the economy-wide

shock, group affiliates will restructure less than non-group firms (H2a) though the negative effect

of group affiliation will be weaker in less developed institutional environments (H2b). We expect

poor performance to increase restructuring during the shock (H3a) but that group affiliation will

weaken this relationship particularly in less developed environments (H3b). Finally, we predict

that restructuring improves firm performance (H4a) but that this effect will be weaker in less

developed institutional environments (H4b) and that group affiliation will also weaken this

relationship, particularly in less developed institutional environments (H4c).

DATA, VARIABLES AND METHODS

We locate our study in Singapore and South Korea between 1995 and 1999. The Asian

Economic Crisis struck these economies in late-1997, causing both economies to suffer their

deepest recessions for decades (Corsetti et al., 1999; Dwor-Frecaut et al., 2000; Kawai, 2000).

Appendix 1 provides economic data that demonstrates the impact of the crisis. The severity of

the shock imposed immediate pressures on firms to respond to the crisis and on governments to

restore economic growth. However, the institutional structures in South Korea and Singapore did

not change during the shock and despite pressures for reform, evolved gradually in following

years (Carney, 2004; Whitley, 1999).

As we evaluate restructuring during an economy-wide shock, we focus our analysis on the

period immediately before and during the shock, to eliminate substantial institutional change.

Reinhart and Rogoff (2009: 236) view the crisis in South Korea as lasting two years, which also

applies to Singapore, as its economy had made a strong recovery by 2000 (Rodan et al., 2006).

Therefore, we treat 1996 and 1997 as pre-shock years, and 1998 and 1999 as shock years.

Institutional Structures: South Korea and Singapore

A series of studies (e.g., Chang, 2006; Dent, 2002; Feenstra and Hamilton, 2006; Huff, 1995;

Rodan et al., 2006, Whitley, 1999) substantiate the view that Singapore and South Korea had

substantially different institutional structures during our study period, with several (e.g. Aron,

2000; La Porta et al., 1998; Chakrabarti et al., 2011) regarding Singapore as more institutionally

21

developed. Appendix 1 shows that these countries had substantially different economic structures,

while Appendix 2 evaluates their key institutional components. We conclude that Singapore is

more developed than South Korea in terms of the business-oriented institutional environment.

A major source of the differences between South Korea and Singapore was the openness of

the economies. Singapore's economy was open and highly integrated with the global economy,

and had few constraints on flows of capital, goods, firms and people. Foreign trade represented

more than 300% of Singapore’s GDP, among the highest levels globally, and many times South

Korea's levels. UNCTAD (2000: 25) rated Singapore second (with a score of 36.2) and Korea

last (score: <5) on its Transnationality Index of 30 developing countries. MNCs had a very large

presence in Singapore, with more than 24,000 affiliates present in the country in 1997

(UNCTAD, 2000), many times the number in South Korea. The Singapore government’s active

management of the economy created a relatively sophisticated banking and finance sector, and

relatively developed business-related institutions. In contrast, South Korea had a relatively

closed domestic economy, a history of resisting foreign influences, and limited foreign capital,

goods, firms and people.

High levels of global integration can cause domestic institutions to adopt characteristics of

and become partly embedded in global institutions (Whitley, 1999). Singapore's small and open

economy imported or adopted many global and Western business systems and institutions, so

that its institutional structure resembled those of developed nations in many respects (Dent, 2002:

121-123). Singapore's long history as an English colony and its immaturity as a nation-state

reinforced the isomorphic tendencies of its institutions. South Korea's institutions were more

idiosyncratic, and less aligned with and embedded in global business systems and institutions

(Dent, 2002; Feenstra and Hamilton, 2006; Whitley, 1999). South Korea's government and

institutions did not adapt effectively to the economy's progress and increasing globalization, so

that the institutional structure in the 1980s and 1990s lagged behind the development of the

economy (Chang, 2003: 35-37).

We draw two conclusions from this overview. First, Singapore and South Korea had

22

significantly different institutional structures, allowing evaluation of the impact of institutional

differences. Second, Singapore had a more developed business-related institutional structure

embedded in global institutions, allowing evaluation of the impact of institutional development.

Data

Our sample comprised all manufacturing firms listed on the Singapore and South Korea

exchanges in 1995, as reported in the Worldscope Database (November 2000 edition). We

excluded inactive firms and those whose principle business was outside manufacturing, which

resulted in samples of 125 firms in South Korea and 73 in Singapore. From these, 114 South

Korea and 66 Singapore firms existed in 1999, and formed our final sample.3 We obtained firm

data from the Worldscope Database. The Corporate Handbook for Singapore, The Korea Firm

Yearbook and company websites provided additional data.

Variables

Restructuring. Our dependent variable for Hypotheses 1 to 3 is the count of restructuring actions

undertaken by each firm. We incorporated the quadratic term for restructuring, as gains from

improved alignment may be offset by the costs of disruption at high levels of restructuring. There

is no ready source of data on restructuring as databases and reporting services do not capture

such complex non-financial information. We therefore followed Kang and Shivdasani (1997) and

Nixon et al. (2004) and relied on articles published in newspapers for restructuring information.

The search centered on each firm in our sample and was conducted on the Dow Jones Interactive

database.4 This method of data collection assumes that media sources report business news

systematically. This is reasonable as restructuring by listed firms attracts media attention.

3We investigated all delistings between 1995 and 1999 to examine if any resulted from failed restructuring. Six delistings in South Korea were due to M&As within business groups and two to acquisitions by unrelated firms, while two were not M&A-related. We could not confirm the reasons for one delisting. For Singapore, four cases were within-corporation M&As, one firm was acquired in an unrelated M&A, and one delisting occurred for unknown reasons. Though some delistings may have been related to corporate changes, none appeared to result from firm-level restructuring. Further, as delistings are not a large part of our sample, we believe that survivor bias is not a significant problem for our study. Our procedure is consistent with Fisher et al. (2004). 4For South Korea, this collection used reports from Korea Herald and Korea Times, the two leading English newspapers in the country. This search produced 2,664 articles of which 105 were repeat articles and 1,132 were unrelated to restructuring. We used a similar procedure for Singapore data, which utilized The Straits Times and Business Times, the only two English newspapers published in the country. The 2,505 articles on our sample were reduced to 1,027 by eliminating 118 repeat articles and 1,360 articles unrelated to restructuring.

23

Consistency in reporting across sources within each country also suggested reliability of

reporting. Finally, no other method allowed our “grounded, large-sample, multi-year, detailed

firm-level restructuring” research design; this approach is useful but underutilized because of its

difficulty (Van de Ven and Huber, 1990). Following Bowman and Singh (1990; 1993) we

classified restructuring activities into portfolio, financial and organizational restructuring.5 Table

3 summarizes our restructuring data.


Performance. Measuring firm performance is a considerable challenge in rapidly changing

environments. Accounting measures such as return on assets (ROA) suffer from significant lag

effects because they rely on historical values that may not reflect current valuation in rapidly

changing environments. Hence, ROA and related measures may not reliably reflect the outcomes

of restructuring during an economy-wide shock. Market measures such as Tobin's q offer a more

current assessment of performance. However, Tobin's q is a market-based assessment of

performance that may provide a relatively pessimistic estimate of performance and restructuring

outcomes during an economy-wide shock because it encompasses systematic risk (Bentsen,

1985). Concerns about market efficiency arise in under-developed institutional environments,

though these concerns also apply to accounting standards and measures. As restructuring

primarily aims to improve firm performance in the short-term to overcome the threat of a major

external change, we believe the advantage of a current estimation recommends the use of Tobin's

q as a measure of performance. Other studies of restructuring during an economy-wide shock

also adopt Tobin's q (e.g. Baek et al., 2004).

We employ a modified version of Tobin’s q as the dependent variable for the tests of

Hypotheses 4a, 4b and 4c. We measure Tobin’s q as the ratio of firm value (total market value of

equity and debt) to replacement value of assets. As replacement value of assets and market value

of debt were not available, we divided market value of equity and book value of liabilities by

5We tested the reliability of our classification by having four coders assign a sample of 40 restructuring actions into the three categories of restructuring. The four coders agreed perfectly with our classification of 34 of 40 items and three coders agreed on a further five items, suggesting substantial reliability.

24

book value of assets as an approximation of Tobin’s q. The value of equity was based on closing

prices on the last trading day of each year.

Hypotheses 3a and 3b require a measure of performance to evaluate if poor performance

influences restructuring. We used ROA for this purpose. ROA's lagged measure of performance is

an advantage in this regard, as realized poor performance is more likely to drive restructuring.

We include ROA's quadratic term to detect the impact of extremes in performance, as might

occur during an economy-wide shock.

Group affiliation. An important difference between Singapore and South Korea was the nature

of business groups. In South Korea, large family-owned business groups (chaebols) dominated

the economy (Chang, 2003; Feenstra and Hamilton, 2006; Whitley, 1999). In Singapore,

government linked corporations (GLCs) were the dominant business group form (Chakrabarti et

al., 2007; Singh and Ang, 1999; Tsui-Auch, 2006), though there were some family-owned

groups. We established group affiliation by referring to stock exchange handbooks and to self-

reported associations on company websites. We confirmed these affiliations by referring to data

on Singapore and South Korea groups provided by authors of published studies. An indicator

variable noted group affiliated firms.

Control variables. We used the logarithm of total assets to measure firm size. We used assets as

this is reasonable measure for manufacturing firms and because restructuring often relates to

asset changes. We used the current ratio (current assets/total assets) to measure liquidity and

debt ratio (debts/total assets) to measure leverage. These three controls measure resource

availability, which influences restructuring (Kraatz and Zajac, 2001). Foreign sales ratio

(foreign sales/total sales) accounted for possible mitigating effects of foreign operations during

the shock. Firm age may affect ability to change (Kelly and Amburgey, 1991; Tan and See,

2004), which we measured in years from time of formation. As our sample comprises only

manufacturing firms, we used technology intensity indicators (OECD, 1999) to classify firms as

high, medium-high, medium-low and low in technology intensity. All variables other than firm

age and indicators were lagged one year. Table 4 provides summary statistics.

25

*** Table 4 about here***

Methods

The count of restructuring actions in total or within each category is the dependent variable for

the tests of Hypotheses 1 to 3. Poisson regression and negative binomial regression, a variant of

the former that accounts for heteroscedasticity, are standard models for count-based data.

However, standard Poisson or negative binomial models that handle zero and non-zero outcomes

in one model cannot adequately describe data when there is a preponderance of zeros, as is the

case for our study because many firms did not restructure. Consequently, we adopted the zero-

inflated Poisson (ZIP) regression model, which is effective at handling the preponderance of

non-events in the dependent variable (Wooldridge, 1999). This model offers the additional

advantage of evaluating unobserved heterogeneity by distinguishing firms that restructure from

those that do not. As too few events prevented convergence of some ZIP models of restructuring

within categories, we primarily report negative binomial regression results. Comparisons with

ZIP models that converged suggest broadly similar results. For the test of Hypothesis 4 on the

outcomes of restructuring, we used generalized estimating equations (GEE). GEE accounts for

firm heterogeneity and autocorrelation due to repeated measurements of the same firms by

estimating the correlation structure of error terms.

Firm-specific heterogeneity, such as in resource availability or restructuring capabilities, may

make some firms more willing to restructure and may affect restructuring outcomes. The

restructuring literature has not systematically evaluated the impact of such endogeneity (Beck et

al., 2008). Hypotheses 2 and 3 evaluate the likelihood of restructuring during the economy-wide

shock, which may be influenced by firms' propensity to restructure. For Hypothesis 4, it is

possible that restructuring affects performance while sub-optimal performance induces firms to

restructure (as predicted by Hypothesis 3), making it difficult to distinguish cause and effect. To

control for factors that may cause firms to restructure and that may also affect performance, we

employed a two-stage estimation procedure for the evaluation of Hypotheses 2, 3 and 4. In the

first stage, we used probit regression to estimate the likelihood of restructuring (restructuring

26

predictor) with the following variables: firm sales (log value, lagged one year); market

capitalization (log value, measured at the start of the year); foreign sales (lagged one year);

ownership concentration of the largest owner (%, lagged one year); two indicator variables to

note when the largest owner was a bank or family; and an indicator to distinguish Singapore and

South Korea firms. Sales, market capitalization and foreign sales controlled for performance and

resources. Concentration and ownership variables controlled for owners' influence on resource

access and restructuring (Baek et al., 2004; Makhija, 2004). Though these variables do not

include all influences on restructuring, they broadly control for resource availability, which is

likely to influence propensity to restructure. We estimated separate models for financial,

portfolio, organizational and total restructuring. The second stage used negative binomial to

evaluate restructuring (Hypotheses 2 and 3) and GEE models to evaluate the impact of

restructuring on performance (Hypothesis 4).

RESULTS

Restructuring: A shock effect?

Table 5 presents results of the test of Hypothesis 1a, which show that total restructuring did not

change during the shock (Model 1, b = -0.099, n.s.). However, financial restructuring increased

(b = 1.346, p < 0.001), particularly for Singapore firms (b=1.870, p < 0.01).


Table 6 expands the test of Hypothesis 1a by evaluating restructuring within country samples.

Results show a striking difference in restructuring across countries. Singapore firms significantly

decreased total restructuring (b = -0.352, p < 0.01) driven by the reduction in portfolio

restructuring (b = -0.495, p < 0.001), while South Korea firms increased all forms of

restructuring from pre-shock levels. These significant changes in restructuring support

Hypothesis 1a. The significant increase in restructuring in South Korea and decrease in

Singapore support Hypothesis 1b, which predicted greater likelihood of increased restructuring

in less developed institutional environments. Table 3 shows that South Korea firms had

significantly lower levels of pre-shock change and adaptation than Singapore firms (p < 0.001),

27

and also lower levels of restructuring during the shock (p < 0.05).


These results show that an economy-wide shock significantly impacts restructuring, but that

firms may increase or decrease restructuring relative to pre-shock levels of change and adaption.

The contrast in restructuring across the two economies indicates the importance of country

factors, consistent with our emphasis on institutional differences, and the hazards of pooling

country samples. We therefore conduct separate evaluations for all subsequent analyses.

Who restructures more?

Hypothesis 2a predicts that group affiliates will restructure less than non-group firms during an

economy-wide shock. Table 7 evaluates restructuring for the shock period only, and shows that

group affiliates in Singapore did not differ in restructuring from non-group firms. In contrast,

group affiliates in South Korea restructured more than non-group firms across all categories of

restructuring. These results do not support Hypothesis 2a but are consistent with Hypothesis 2b's

prediction that group affiliation in less developed environments will restrict restructuring less

than in more developed environments. Hypothesis 2a relies partly on the argument that group

affiliates restructure less because of greater support from being "too big to fail." We repeated our

analysis for the largest 25% of firms by assets, sales and market capitalization, for whom the

"too big to fail" effect would be strongest. Singapore results were unchanged but the positive

association between group affiliation and restructuring in South Korea was lost for all three

measures, indicating large group affiliates restructured less. This is consistent with buffering

helping large group affiliates avoid restructuring in less developed institutional environments.


Table 7 also reports results of the tests of Hypothesis 3a, which predicts that poor

performance will increase restructuring. ROA was negatively related to restructuring for

Singapore firms, except for organizational restructuring, but was not associated with

restructuring for South Korea firms. This result shows that poor performance drives restructuring

during an economy-wide shock in Singapore, supporting Hypothesis 3a. ROA2 was positively

28

associated with total and financial restructuring in Singapore, indicating that strong firms

restructure more during shocks, possibly to exploit opportunities.

Hypothesis 3b predicts a weaker relationship between poor performance and restructuring

among group affiliates in less developed environments during the shock. Results in Table 7 show

non-significant Group*ROA for Singapore firms, indicating that group affiliates did not differ

from non-group firms. Group*ROA was negative for South Korea firms except for portfolio

restructuring, showing that poor performance drove restructuring among group affiliates more

than for non-group firms in South Korea. The positive Group*ROA2 coefficients for South Korea

indicates that very strongly performing group affiliates were more likely to restructure. These

results do not consistently support Hypothesis 3b.

Results in Table 7 indicate that Singapore firms restructure primarily to correct performance,

but that group affiliation drives restructuring in South Korea; among these South Korea group

affiliates, both poor performance and very strong performance increases restructuring.

Outcomes of restructuring

Table 8 presents results of the tests of Hypotheses 4a, 4b and 4c, on the impact of restructuring

on performance. Financial restructuring was associated with improved Tobin's q for Singapore

firms, as were high levels (Restructuring2) of total and portfolio restructuring. Restructuring was

positively associated with Tobin's q in South Korea, except for portfolio restructuring. These

results are consistent with the view that restructuring improves performance, though greater

restructuring may be required to improve performance in more developed institutional

environments. These results support Hypothesis 4a. Meanwhile, high levels of total restructuring

in South Korea and of financial restructuring in both economies hurt performance. Intensive

financial restructuring in the midst of an economy-wide shock or intensive restructuring in less

developed institutional environments, where resources and support for restructuring are

inadequate, may cause too much disruption and hurt performance.

Hypothesis 4b predicted weaker outcomes from restructuring in less developed institutional

environments. Results only support this prediction for high levels of restructuring. It is possible

29

lower levels of pre-shock change provides greater scope for improvement in less developed

institutional environments, but that these environments do not provide adequate resources and

support to allow positive outcomes when restructuring is intensive. Hypothesis 4c predicted

weaker outcomes from restructuring for group affiliates in less developed institutional

environments. Results indicate that group affiliates gain less than non-group firms from

organizational restructuring in Singapore and from financial restructuring in South Korea, but

otherwise achieved similar outcomes. These results do not support Hypothesis 4c.


The restructuring predictor was significant for Singapore but not for South Korea in Table 8,

indicating that common factors predicted the propensity to restructure and the outcomes of

restructuring in Singapore. Two possible factors are that Singapore firms had greater capabilities

that facilitate restructuring and improve firm performance, and that Singapore's more developed

institutional environment influenced restructuring and its outcomes. Both factors are consistent

with our focus on firm and institutional resources as key drivers of restructuring and its outcomes.

We repeated our analysis without the restructuring predictor variable and found results to be

broadly consistent but with stronger coefficients. This indicates that failing to control for

endogeneity may result in over-estimation of the benefits of restructuring.

Control variables did not consistently influence restructuring or its outcomes, though we find

some consistencies within countries. The absence of consistent effects among control variables

suggests that restructuring and its outcomes during an economy-wide shock are contingent on

firm-specific factors.

In summary, we find that Singapore firms undertook greater restructuring during the

economy-wide shock than South Korea firms but reduced restructuring during the shock, while

South Korea firms increased restructuring during the shock. Poor performance drove

restructuring during the shock for Singapore firms ahead of other characteristics such as group

affiliation. In contrast, group affiliation was the key determinant of restructuring before and

during the shock in South Korea, with performance only driving restructuring for group affiliates.

30

These results indicate that institutional structures and embeddedness within these structures

influence firm restructuring during an economy-wide shock. Finally, we find that restructuring

improved performance across institutional environments, though more intensive restructuring

was required in more developed institutional environments. These results are consistent with the

complexity of the construct of restructuring and with the challenges and uncertainty faced by

firms during economy-wide shocks. More generally, results indicate the importance of firm-

specific and institutional influences on restructuring. Though results do not consistently support

hypotheses, they provide interesting insights into restructuring and its outcomes.

Robustness tests

We conducted several tests to evaluate the sensitivity of results. First, we evaluated alternate

measures of key variables, using return on invested capital instead of ROA, sales instead of

assets, and the quick ratio instead of the current ratio. Results were largely unchanged, though

with some changes in significance levels. Second, we re-tested Hypotheses 1a and 1b using

various combinations of one and two-year durations for the pre and shock periods, but found

results to be stable. Third, we replaced Tobin's q with year-end market capitalization to measure

firm performance for the test of Hypothesis 4. As our version of Tobin's q utilizes book values of

assets and liabilities, it is a less sensitive measure of performance than market capitalization. We

found that all forms of restructuring in Singapore were positively related to market capitalization

but that none were in South Korea. These findings are consistent with Hypothesis 4b's prediction

of more positive outcomes from restructuring in more developed environments.

DISCUSSION AND CONCLUSIONS

We investigate firm restructuring and its consequences following an economy-wide shock,

focusing in particular on embeddedness within institutional environments and institutional

differences across economies. A general conclusion is that firms change their pattern of

restructuring during an economy-wide shock, rather than necessarily increasing restructuring,

and that under severe economic conditions, restructuring does not offer a direct path to

performance improvement. Firms in a more developed institutional environments reduced

31

restructuring during the shock and improved their performance, while firms in a less developed

institutional environment increased restructuring and also improved performance. Institutional

environments also influenced whether poor performance or group affiliation affected

restructuring. Our results contribute to three research streams.

First, we contribute to the restructuring literature, extending it to two understudied contexts,

economy-wide shocks and varying institutional environments. Investigating the joint effects of

an economy-wide shock and institutional environments provides insights that may help resolve

basic disagreements on firm restructuring. In showing that the interaction of firm and

institutional characteristics affects restructuring and its outcomes, we demonstrate that current

explanations of restructuring that focus largely on firm heterogeneity will benefit from

incorporating the influences of institutional heterogeneity. The failure to evaluate the

institutional environment and the extent of firms' embeddedness may partly explain existing

contradictory results. For example, a study that only evaluated Singapore firms would have

concluded that restructuring is disruptive, so that reducing it during a shock can improve

performance, and that business groups do not matter. A similar study in South Korea would

conclude that firms can significantly increase restructuring during a shock and improve their

performance in the process, but that group affiliation is the key influence. By evaluating the

impact of internal and external resources on restructuring, we help to integrate resource-based

and institutional economics perspectives on the issue of firm restructuring.

A second contribution comes from showing that failing to control for endogenous influences

exaggerates the incidence and outcomes of restructuring, supporting the view (Beck et al., 2008)

that previous studies may have reported biased results. Third, we contribute to the application of

institutional economics to the study of organizations by demonstrating how variation in

institutional environments can affect firm processes and performance. Detailed evaluation of

components of the institutional structure and of their influence on firm phenomena will improve

understanding of how the institutional environment can facilitate or hinder restructuring and its

outcomes. Many strategy studies view institutions primarily as constraints and do not adequately

32

recognize their role in supporting and enhancing firm actions and performance. Relatively

limited empirical strategy research has gone beyond broad conceptualization of institutional

influences to evaluate specific impact. Greater development of middle range theory on

institutional influences on strategic phenomena is required.

Finally, we help to integrate research on economy-wide shocks and firm restructuring. The

suddenness and severity of these shocks control for many factors that buffer change, permitting

better isolation of externally induced restructuring and of its performance consequences.

Economy-wide shocks are unusual in providing a context that imposes severe pressures on firms

to restructure, while constraining firms' access to resources that may buffer such pressures. They

are therefore particularly useful contexts for evaluating the impact of firm resources and dynamic

capabilities. These shocks are also inherently interesting, offering the radical environmental

change that strategy theory must address. The impact of economy-wide shocks on firms and the

opportunity to study firms during such shocks is under-recognized in strategy research. Our

study shows how micro-level restructuring affects firm performance, which collectively

determines how economies adjust to macroeconomic shocks. This indicates the value of linking

firm restructuring and economic recovery in future research and of the potential for theory

explicitly linking intra-organization change with macroeconomic phenomena (Newman, 2000).

As firm adaptation to economy-wide shocks influences the microeconomic resilience of

economies, these findings offer important lessons for managers and policy makers.

Several issues we do not address in this study suggest opportunities for future research. First,

our contrast of institutional environments in two emerging economies controls differences across

several dimensions. It would be interesting to contrast restructuring in an advanced institutional

environment. It would also be useful to evaluate restructuring across economy-wide shocks to

examine the impact of variation in these shocks along with variation in institutional

environments. Examining sequential economy-wide shocks will allow evaluation of firm and

institutional learning across shocks and identification of restructuring's longer-term outcomes.

33

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Table 1. Impact of economy-wide and local shocks on the business and economic environment

Institution Economy-wide shock Local shocks Capital markets

There are substantial adverse movements in exchange rates, trade balances, debt, liquidity, investments and FDI, leading to reduced turnover and declining capital markets. New fund raising and refinancing severely reduced.

Capital markets and availability of resources generally not substantially altered, outside of the affected industry.

Labor markets

Greater firm insolvency and failures reduce hiring, increase layoffs and create union-employer conflict. Industrial action may increase substantially. Increased management layoffs and board turnover may follow poorer firm performance.

Layoffs and union-employer conflict usually limited to affected industry and closely related industries. Board and management turnover may or may not increase.

Product markets

Declines in economic activity and confidence lead to substantially reduced demand and business activity across broad sectors of the economy. Firms suffer reduced turnover and profitability. There are increased levels of firm exit and failures, and reduced levels of product introductions and innovation. Risk and uncertainty increase.

Localized slowdowns affect single or closely related industries but do not substantially affect the overall economy. Firms in the affected industry suffer significant slowdowns in activity, profitability and investments, leading to layoffs and firm failures.

Legal and regulatory systems

May be substantially affected, with changes to regulations relating to capital and financial markets, investments, employment, taxation and other business aspects. Some changes will aim to lower costs of doing business and increase flexibility for firms; others will protect key organizations and employees through increased regulation and greater constraints on firms and employers.

Shocks to particular industries or sectors usually do not affect legal or regulatory systems and typically do not lead to broad or major changes in the regulatory environment. Some changes may take place if the industry is viewed as being important for the economy or other industries.

State structure and political environment

The shock may be attributed to weaknesses in the state’s political and economic policies, and institutional structure. This may lead to significant changes to scope of government and business operations, foreign participation in the economy, structure of markets, legal institutions, and capital and financial market rules and regulations. Some of these changes may be imposed by international agencies. Substantial changes in the political environment may also lead to changes in leadership, political structures, authority of agents, and the structure of government finances. In extreme cases, governments and their agencies may intervene in businesses and industries for political or economic reasons.

In most cases, there is no substantial impact on the political environment. Political intervention may occur only for selected industries viewed as having significant national security, political or economic impact.

Trust and authority relationships

Major economic and other disruption may alter perspectives of appropriate government and external management of the economy, extent of market competition and regulation, openness to foreign firms and trade, power of unions and related issues. Trust in various actors and the status of businesses may be severely affected.

In most cases, there are no substantial changes to the broader social-cultural environment.

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Table 2. Impact of the institutional structure on constraining or facilitating restructuring during an economy-wide shock Financial Restructuring Portfolio Restructuring Organizational Restructuring Capital markets

Constrain Restructuring - Uncertainty and risk reduce availability of funds and increase costs of funds - Shocks attributed to capital markets and related actors, constraining their role in restructuring Facilitate Restructuring - Macroeconomic easing increases funds for firms - Low market activity may create low cost opportunities

Constrain Restructuring - Poorer market and economic conditions discourage buyers and reduce M&As - Difficulty and cost of fund raising may discourage costly restructuring and new investments Facilitate Restructuring - Lower activity reduces costs and increases bargain hunting - Distressed sellers are more willing to negotiate

Constrain Restructuring - Difficulty and cost of fund raising may discourage costly layoffs and other organizational changes Facilitate Restructuring - Difficult market conditions encourage consolidation within firms and industries - Poor market conditions may force senior leadership to make difficult leadership and HR changes

Labor markets

Constrain Restructuring - Risk of industrial action hinders fund raising Facilitate Restructuring - Negative conditions may allow bundling of actions and major cleaning up of books - Union cooperation may allow non-traditional financial actions

Constrain Restructuring - Substantial layoffs, plant closures and firm failures increase union resistance and discourages restructuring Facilitate Restructuring - Negative conditions may encourage union-employer cooperation

Constrain Restructuring - Actual or potential industrial action restricts labor-related changes Facilitate Restructuring - Severe conditions may encourage collective negotiations and arbitration that allow major restructuring

Product markets

Constrain Restructuring - Lower valuations of firms and assets reduce the attractiveness of potential financial transactions Facilitate Restructuring - Lower prices and valuations may attract new funds and potential buyers

Constrain Restructuring - Decline in activity and disruption of supply and distribution chains hinder operations, reduce valuations and buyers - Poor conditions limit new investments and potential buyers or partners Facilitate Restructuring - Poor market conditions may lower prices and encourage buyers of plants and assets

Constrain Restructuring - Regulations introduced to protect workers may limit options for restructuring Facilitate Restructuring - Poor market conditions may motivate firms to increase restructuring

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Legal systems

Constrain Restructuring - M&A and disclosure rules are difficult to comply with during a shock, limiting transactions - Efforts to correct perceived causes of crises often create new financial and capital constraints Facilitate Restructuring - Some regulations may be suspended or relaxed during the shock, to increase liquidity or limit firm failures

Constrain Restructuring - Regulations and systems designed for non-shock periods may be inappropriate and constraining during shocks - Potential changes to regulations and legal challenges from government or private parties may increase uncertainty and discourage transactions Facilitate Restructuring - Enforcement may be relaxed and new facilitating rules fast tracked, facilitating restructuring

Constrain Restructuring - Collective agreements with unions or government bodies may prevent actions that may affect HR or employment changes Facilitate Restructuring - Relaxation of some rules and regulations may facilitate restructuring

State structure and political regime

Constrain Restructuring - Additional constraints on capital markets and financial instruments may be introduced - Government restructuring of financial sector may hinder financial transactions Facilitate Restructuring - Financial restructuring may be encouraged as part of stabilisation or to increase liquidity in economy - Constraints to transactions with foreign parties may be reduced

Constrain Restructuring - Macroeconomic stabilization efforts may hinder micro-economic adjustments - Industrial and political policies designed to stabilize or boost economic activity may limit restructuring options Facilitate Restructuring - Economic conditions or pressures from global institutions may encourage flexible regulations that facilitate restructuring - Governments may introduce schemes to promote and fund consolidation among firms

Constrain Restructuring - Political considerations may limit actions that result in increased layoffs Facilitate Restructuring - Governments may provide support for restructuring that increases employment or investments or restructures ownership and management - Initiatives to maintain employment may allow some forms of restructuring

Trust and authority structures

Constrain Restructuring - Key institutions and actors are blamed for shocks, limiting their ability to support restructuring - Lack of trust in capital markets and intermediaries hinder financial transactions Facilitate Restructuring - Crisis environment may encourage support for institutions to take bold actions in support of restructuring

Constrain Restructuring - Disruption and uncertainty reduce trust in firms and public organizations, limiting firms' options - Governments may constrain restructuring to limit possible exploitative acts by firms Facilitate Restructuring - Government and public organizations may coordinate and guide restructuring as part of stabilization actions

Constrain Restructuring - Reduced trust in formal and informal institutions and actors increases the difficulty of labor and employment changes Facilitate Restructuring - Organizations that weather the shock may be perceived as more reliable and attract opportunities - Widespread action legitimizes firms' restructuring efforts

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Table 3. Incidence of restructuring (1996-1999)

Count of Restructuring:

Total Singapore1 South Korea1

1996 1997 1998 1999 Total 1996 1997 1998 1999 Total 1996* 1997 1998 1999 Total Financial restructuring2

30 27 47 64 168 28 23 32 40 123 2 4 15 24 45

5.4% 5.9% 11.0% 13.6% 8.8% 9.0% 7.8% 15.2% 16.8% 11.7% 0.8% 2.4% 6.8% 10.3% 5.2% Portfolio restructuring3

288 229 182 203 902 210 178 113 115 616 78 51 69 88 286

52.1% 49.9% 42.4% 43.1% 47.2% 67.7% 60.3% 53.8% 48.3% 58.5% 32.1% 31.1% 31.5% 37.8% 33.3% Organizational restructuring4

235 203 200 204 842 72 94 65 83 314 163 109 135 121 528

42.5% 44.2% 46.6% 43.3% 44.0% 23.2% 31.9% 31.0% 34.9% 29.8% 67.1% 66.5% 61.6% 51.9% 61.5% Total 553 459 429 471 1912 310 295 210 238 1053 243 164 219 233 859 Average per firm 3.07 2.55 2.38 2.62 10.62 4.70 4.47 3.18 3.61 15.95 2.13 1.44 1.92 2.04 7.54

Note: 1. N=66 for Singapore, and 114 for South Korea 2. Financial restructuring includes issue of stocks and bonds, loans, attracting new investments, share and debt repurchase and swaps, reduction in debt payments, extension of debt maturity and other debt restructuring 3. Portfolio restructuring includes sell-offs, spin-offs, plant closures, withdrawals from businesses, divestment, acquisition, merger, establishing of new businesses, major investments, and setting up of joint ventures and alliances. 4. Organizational restructuring includes substantial expansion or reduction of internal operations, change of senior leadership and members of the board, changes in ownership among largest owners, major management and structural changes, early retirements and layoff programs, new hiring efforts and adjustments to employment and compensation terms. 5. Percentages are computed within columns, as the percentage of total restructuring actions for each year.

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Table 4a. Descriptive statistics for Singapore Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Restructuring(#) 3.99 5.22 2. Financial restructuring(#) 0.47 1.27 0.43* 3. Portfolio restructuring(#) 2.33 3.3 0.84* 0.21* 4. Organizational Restructuring(#) 1.19 2.63 0.73* 0.11 0.31* 5. Group affiliated 0.2 0.4 0.27* 0.06 0.24* 0.21* 6. ROA 0.03 0.09 0.06 -0.02 0.14* -0.04 0.03 7. Assets (US$Bn) 4.79 1.32 0.35* 0.06 0.37* 0.20* 0.36* 0.32* 8. Foreign sales ratio 0.35 0.17 0.03 0.01 -0.05 0.11 0.21* -0.03 0.10 9. Age (years) 26.08 21.27 0.10 0.00 0.10 0.08 0.28* -0.05 0.48* 0.23* 10. Debt assets ratio 27.08 18.21 0.00 0.10 -0.07 0.04 0.01 -0.31* 0.10 -0.01 0.08 11. Current ratio 1.7 0.99 0.03 -0.08 0.06 0.02 0.05 0.21* 0.03 0.05 -0.10 -0.51* 12. High-tech 0.23 0.42 0.07 0.20 0.10 -0.07 0.10 -0.03 -0.05 0.06 -0.10 -0.04 0.06 13. Medium-high tech 0.21 0.41 -0.08 -0.04 -0.09 -0.01 -0.07 0.01 -0.11 -0.05 -0.14* 0.09 -0.08 -0.28* 14. Medium-low tech 0.26 0.44 -0.07 -0.11 -0.09 0.01 0.06 -0.05 -0.09 -0.08 -0.05 -0.08 0.08 -0.32* -0.31* 15. Low tech 0.3 0.46 0.07 -0.04 0.08 0.06 -0.08 0.07 0.23* 0.06 0.26* 0.03 -0.06 -0.31 -0.34* -0.39* Note: n=66, *p<.05 Table 4b. Descriptive statistics for South Korea

Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 13 1. Restructuring(#) 1.88 5.86 2. Financial restructuring(#) 0.1 0.58 0.36* 3. Portfolio restructuring(#) 0.63 1.93 0.80* 0.22* 4. Organizational Restructuring(#) 1.16 4.27 0.96* 0.26* 0.62*

5. Group affiliated 0.44 0.50 0.25* 0.12* 0.21* 0.23* 6. ROA 0.04 0.09 0.10* -0.04 0.11* 0.09 0.09* 7. Assets (US$Bn) 6.36 1.49 0.39* 0.11* 0.29* 0.39* 0.35* 0.14* 8. Foreign sales ratio 0.35 0.39 -0.07 -0.05 -0.07 -0.05 -0.09* 0.03 -0.06 9. Age (years) 3.46 0.40 0.02 0.05 0.02 0.02 0.11* -0.01 0.07 -0.06 10. Debt assets ratio 46.73 26.74 0.10* 0.09 0.09 0.09 0.08 -0.29* 0.17* -0.05 -0.02 11. Current ratio 1.25 1.19 -0.05 -0.02 -0.05 -0.04 -0.13* 0.08 -0.34* 0.06 -0.04 -0.25* 12. High-tech 0.15 0.36 0.22* 0.04 0.13* 0.24* -0.02 0.07 0.05 0.01 -0.16* 0.06 0.11* 13. Medium-high tech 0.23 0.42 0.09* 0.08 0.08 0.08 0.11* 0.01 -0.09* -0.02 0.07 -0.09* 0.16* -0.23* 14. Medium-low tech 0.19 0.40 -0.11* -0.05 -0.09 0.10* 0.06 0.03 0.14* -0.02 -0.01 -0.04 -0.05 -0.21* -0.27* 15. Low tech 0.43 0.50 -0.15* -0.05 -0.09 -0.16* -0.12* -0.08 -0.06 0.03 0.07 0.07 -0.18* -0.36* -0.47* -0.43* Note: n=114, *p<.05

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Table 5. Restructuring before and during the economy-wide shock (1996-1999) Count of Restructuring: Total Financial Portfolio Organizational Model 1 Model 2 Model 3 Model 4 Shock period -0.099 1.346*** -0.168 -0.226 (H1a) (0.113) (0.312) (0.158) (0.186) Group affiliated 0.457* -0.507 0.493** 0.557* (0.179) (0.335) (0.183) (0.253) ROA -1.257 -4.905 2.989 0.213 (2.783) (5.216) (2.664) (4.793) ROA2 7.199 27.609+ 0.424 -0.706 (12.320) (15.132) (9.576) (22.219) Size 0.277+ 0.310* 0.183 0.299* (0.157) (0.137) (0.168) (0.150) Foreign sales ratio -0.395 -2.510** -0.517 0.224 (0.319) (0.955) (0.471) (0.474) Age -0.003 0.015* -0.003 -0.000 (0.005) (0.007) (0.004) (0.006) Debt assets ratio 0.002 -0.006 0.005 0.004 (0.006) (0.011) (0.006) (0.009) Current ratio 0.146 -0.202 0.082 0.142 (0.125) (0.248) (0.098) (0.146) High tech 0.387 0.455 0.003 0.589 (0.260) (0.344) (0.254) (0.402) Med-high tech 0.316 0.077 -0.029 0.562 (0.298) (0.428) (0.277) (0.402) Med-low tech -0.303 -0.530 -0.263 -0.139 (0.328) (0.579) (0.285) (0.451) Singapore 0.612 1.870** 1.197 0.433 (0.543) (0.611) (0.762) (0.523) Constant -0.634 -2.471+ -1.078 -1.644 (1.550) (1.482) (1.864) (1.687) Log Likelihood -1619 -300.0 -953.3 -899.0 Wald Chi-sq (13 df) 34.95*** 76.11*** 31.85** 49.67*** N=647; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1 Zero-inflated Poisson Regression; robust standard errors adjusted for clustering by firms in parentheses

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Table 6. Restructuring before and during an economy-wide shock for Singapore and South Korea (1996-1999) Singapore: Count of Restructuring South Korea: Count of Restructuring Total Financial Portfolio Organizational Total Financial Portfolio Organizational Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8Shock period -0.352** 0.282 -0.498*** -0.303 0.739*** 1.930*** 0.577* 0.823** (H1a, H1b) (0.124) (0.371) (0.134) (0.198) (0.197) (0.493) (0.253) (0.265) Group affiliated 0.657** 0.289 0.650** 1.109** 1.050** 0.885+ 1.034** 0.986* (0.247) (0.403) (0.222) (0.367) (0.380) (0.535) (0.358) (0.414) ROA -1.404 -2.211 -2.160 -1.467 11.281** 5.858 14.168** 9.885* (2.270) (4.678) (2.568) (3.241) (3.522) (4.045) (4.769) (3.912) ROA2 -3.006 5.379 5.838 -7.112 -9.629** -4.105 -11.890** -8.653* (8.401) (17.621) (8.567) (13.226) (3.697) (4.243) (4.611) (4.057) Size 0.334** 0.124 0.357*** 0.404** 0.185 0.258 0.111 0.232 (0.114) (0.182) (0.106) (0.152) (0.156) (0.281) (0.160) (0.187) Foreign sales ratio 0.175 -0.478 -0.596 1.415 -1.513* -2.421* -2.289** -0.501 (0.461) (0.907) (0.479) (0.972) (0.697) (1.152) (0.860) (0.494) Age -0.009 -0.006 -0.006 -0.014 -0.004 0.004 0.004 -0.004 (0.005) (0.011) (0.005) (0.010) (0.014) (0.020) (0.013) (0.016) Debt assets ratio -0.003 -0.003 -0.009 0.003 0.016+ 0.019+ 0.019* 0.013 (0.006) (0.011) (0.006) (0.009) (0.009) (0.010) (0.009) (0.011) Current ratio -0.095 -0.253 -0.082 -0.056 -0.079 0.397 -0.126 -0.085 (0.146) (0.213) (0.130) (0.198) (0.154) (0.356) (0.167) (0.184) High tech -0.069 0.738 -0.038 -0.499 0.453 -0.925 0.094 1.015+ (0.305) (0.518) (0.280) (0.525) (0.601) (0.898) (0.549) (0.575) Med-high tech -0.099 -0.026 -0.199 0.136 0.417 -0.352 0.252 0.814 (0.319) (0.434) (0.292) (0.569) (0.518) (0.763) (0.469) (0.530) Med-low tech -0.362 -0.506 -0.376 -0.486 -0.972* -1.873* -1.171* -0.766 (0.315) (0.442) (0.283) (0.491) (0.491) (0.873) (0.539) (0.541) Constant 0.253 -0.855 -0.005 -1.946* -2.611 -6.693* -3.198+ -3.870* (0.640) (0.878) (0.638) (0.976) (1.646) (2.783) (1.663) (1.631) Log Likelihood -616.8 -206.1 -489.7 -337.4 -483.5 -91.17 -310.2 -355.2 Wald chi-sq (12 df) 55.65*** 20.56+ 107.4*** 34.60*** 111.7*** 40.42*** 117.8*** 101.7*** N=260 for Singapore and 387 for South Korea; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1 Negative Binomial Regression; robust standard errors adjusted for clustering by firms in parentheses

43

Table 7. Restructuring during the shock for Singapore and South Korea (1998 & 1999) Singapore: Count of Restructuring South Korea: Count of Restructuring Total Financial Portfolio Organizational Total Financial Portfolio Organizational Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8Group affiliated 0.477 -0.502 0.613 0.531 2.047*** 2.170* 1.711*** 2.316** (H2a, H2b) (0.393) (0.776) (0.380) (0.503) (0.579) (0.926) (0.498) (0.792) ROA -5.992+ -11.487* -6.453+ -0.098 4.358 8.280 7.232 -0.041 (H3a) (3.271) (5.785) (3.553) (4.236) (5.675) (8.066) (7.198) (6.452) ROA2 21.200+ 46.716* 18.023 9.103 22.326 58.397 -0.462 48.466 (12.824) (19.435) (13.345) (17.013) (31.270) (36.163) (16.927) (39.919) Group*ROA 0.306 3.648 0.642 -2.825 -12.998+ -28.274** -5.655 -19.286+ (H3b) (2.830) (7.184) (2.355) (4.420) (7.723) (10.006) (5.017) (9.961) Group*ROA2 0.168 -1.134+ 0.004 0.668 0.593* 0.601+ 0.587* 0.609* (0.342) (0.663) (0.353) (0.411) (0.263) (0.312) (0.287) (0.287) Size 0.187 0.170 0.241+ 0.125 -0.118 0.014 -0.129 -0.176 (0.124) (0.283) (0.137) (0.178) (0.174) (0.272) (0.194) (0.190) Foreign sales ratio 0.216 2.409 -0.608 1.422 -1.120+ -2.320+ -1.122 -0.813 (0.735) (1.617) (0.986) (0.995) (0.581) (1.332) (0.718) (0.718) Age -0.001 0.001 -0.001 -0.007 -0.011 -0.011 -0.000 -0.027 (0.005) (0.014) (0.006) (0.008) (0.014) (0.026) (0.019) (0.018) Debt assets ratio 0.007 0.013 -0.008 0.031** 0.012 0.029* 0.009 0.009 (0.009) (0.019) (0.010) (0.011) (0.010) (0.012) (0.009) (0.009) Current ratio 0.035 -0.025 -0.033 0.176 0.258 0.332 0.099 0.374+ (0.204) (0.467) (0.180) (0.222) (0.188) (0.302) (0.192) (0.197) High tech 0.508 2.521*** 0.204 0.102 0.283 -0.599 -0.242 0.084 (0.353) (0.763) (0.370) (0.434) (0.787) (1.037) (0.913) (0.740) Med-high tech 0.190 1.316+ -0.130 0.254 -0.597 -0.377 -0.602 -0.418 (0.346) (0.737) (0.394) (0.511) (0.449) (0.771) (0.474) (0.532) Med-low tech -0.119 0.671 -0.396 0.125 -1.415** -0.738 -2.142*** -1.035+ (0.432) (0.741) (0.440) (0.534) (0.433) (0.755) (0.603) (0.530) Restructuring 1.896* 11.553* 1.830* 2.924 3.168*** 4.408 3.003* 5.412** predictor (0.892) (4.503) (0.769) (1.992) (0.900) (3.674) (1.192) (1.899) Constant -1.417+ -6.387** -1.076 -3.722*** -1.281 -4.490* -1.752 -1.157 (0.804) (1.961) (0.834) (1.088) (1.374) (2.047) (1.865) (1.450) Log Likelihood -276.5 -88.94 -209.3 -152.0 -239.0 -62.35 -155.0 -168.0 Wald chi-sq (14 df) 49.86*** 33.91** 44.75*** 49.20*** 59.82*** 37.07*** 40.42*** 37.83*** N=129 for Singapore and 197 for South Korea; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1 Negative Binomial Regression; robust standard errors adjusted for clustering by firms in parentheses

44

Table 8. Effects of restructuring on performance during the shock for Singapore and South Korea (1998 & 1999) Singapore: Tobin's q South Korea: Tobin's q

Total Financial Portfolio Organiz-ational Total Financial Portfolio Organiz-

atonal Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

Restructuring 0.030 0.549*** -0.059 0.237 0.087* 0.706* 0.061 0.092+ (H4a) (0.029) (0.152) (0.065) (0.152) (0.040) (0.335) (0.050) (0.056) Restructuring2 0.003** -0.038** 0.014* -0.008 -0.004* -0.167+ -0.006 -0.007 (0.001) (0.013) (0.006) (0.014) (0.002) (0.101) (0.005) (0.005) Group affiliated 0.048 -0.004 -0.040 0.036 0.001 0.014 -0.015 -0.002 (0.167) (0.112) (0.180) (0.142) (0.052) (0.050) (0.050) (0.049) Group* -0.030 -0.557 0.016 -0.297+ -0.067 -0.632+ -0.032 -0.073 restructuring (H4b) (0.040) (0.396) (0.084) (0.170) (0.045) (0.351) (0.065) (0.059) Group* -0.002 0.059 -0.008 0.017 0.003+ 0.161 0.005 0.007 restructuring2 (0.001) (0.080) (0.009) (0.015) (0.002) (0.102) (0.007) (0.005) ROA 0.523 1.632 -0.105 0.027 -0.830+ -0.821+ -0.947* -0.837* (1.367) (1.493) (1.694) (1.365) (0.426) (0.434) (0.391) (0.420) ROA2 -8.864** -12.645** -7.155+ -8.772** -0.235 -0.135 -0.271 -0.316 (3.439) (4.344) (3.684) (3.336) (0.394) (0.400) (0.370) (0.390) Size -0.322*** -0.094 -0.282** -0.300** -0.016 0.008 -0.011 -0.014 (0.089) (0.064) (0.100) (0.105) (0.016) (0.019) (0.015) (0.016) Foreign sales ratio -0.110 -0.047 0.049 -0.409 0.005 0.010 -0.005 -0.002 (0.281) (0.305) (0.312) (0.280) (0.020) (0.020) (0.021) (0.020) Age 0.003 -0.000 0.001 0.003 -0.005** -0.005** -0.005** -0.005** (0.003) (0.003) (0.004) (0.003) (0.002) (0.002) (0.002) (0.002) Debt assets ratio -0.004 -0.004 -0.000 -0.004 0.005*** 0.004*** 0.005*** 0.005*** (0.004) (0.004) (0.004) (0.004) (0.001) (0.001) (0.001) (0.001) Current ratio -0.098+ -0.002 -0.082 -0.034 0.035 0.034 0.037 0.034 (0.057) (0.069) (0.070) (0.063) (0.023) (0.024) (0.026) (0.025) High tech -0.110 -0.331+ -0.004 -0.099 0.178* 0.238** 0.196* 0.188* (0.150) (0.173) (0.169) (0.172) (0.084) (0.084) (0.080) (0.081) Med-high tech 0.116 -0.058 0.122 0.045 -0.044 -0.009 -0.037 -0.043 (0.157) (0.157) (0.180) (0.172) (0.066) (0.068) (0.061) (0.064) Med-low tech -0.089 -0.202 -0.111 -0.154 -0.071 -0.083+ -0.077+ -0.080+ (0.161) (0.136) (0.169) (0.165) (0.047) (0.048) (0.046) (0.047) Restructuring 1.461** 4.059** 1.468* 2.439** -0.030 -0.002 0.062 0.045 predictor (0.528) (1.553) (0.597) (0.940) (0.132) (0.439) (0.118) (0.201) Constant 2.056*** 1.014* 2.021*** 2.077*** 0.926*** 0.817*** 0.873*** 0.896*** (0.360) (0.487) (0.440) (0.417) (0.158) (0.187) (0.147) (0.153) Wald chi-sq (16 df) 515.8*** 138.8*** 49.09*** 75.31*** 783.1*** 508.5*** 872.5*** 974.0*** N=129 for Singapore and 197 for South Korea; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1 GEE population-averaged model with exchangeable correlations; robust standard errors adjusted for clustering by firms in parentheses

45

Appendix 1. Economic Data and Impact of Crisis

Singapore South Korea

1995 1996 1997 1998 1999 2000 1995 1996 1997 1998 1999 2000 GDP (constant 2000 US$billion)1 68.23 73.55 79.68 78.58 84.24 92.72 430.55 460.68 482.12 449.06 491.66 533.38

GDP growth (%) 9.17 7.00 4.65 -6.85 9.49 8.49 8.15 7.79 8.34 -1.38 7.20 10.06

GDP per capita (constant 2000 US$)

19,359 20,036 20,990 20,010 21,280 23,019 9,548 10,119 10,491 9,702 10,547 11,347

Inflation (%) 1.72 1.38 2.00 -0.27 0.02 1.36 4.48 4.92 4.45 7.51 0.81 2.26

Unemployment (%) 2.06 2.05 2.61 6.96 6.34 4.42 2.69 2.99 2.05 2.73 4.90 5.96

Foreign trade in services (% of GDP)

57.58 55.60 53.03 53.62 62.47 63.24 9.40 9.50 10.81 14.51 12.06 11.98

Foreign trade in merchandise (% of GDP)

288.02 276.98 268.52 256.83 273.26 293.74 50.31 50.22 54.38 65.31 59.15 62.38

FDI net outflows (% of GDP)

8.05 8.59 11.37 2.63 9.69 6.38 0.69 0.82 0.85 1.37 0.94 0.94

FDI, net inflows (% of GDP)

13.69 10.46 14.35 8.88 20.07 17.78 0.34 0.42 0.55 1.57 2.10 1.74

Exchange rate (local units per US$, year average)

1.42 1.41 1.48 1.67 1.69 1.72 771.27 804.45 951.29 1401.44 1188.82 1130.96

Population (millions) 3.52 3.67 3.80 3.93 3.96 4.03 45.09 45.53 45.95 46.29 46.62 47.01 Foreign banking entities in country3,4 128 131 140 142 133 132 49 48 50 45 43 40

Foreign affiliates in country5 18154 24114 3878 6486

Note:1. GDP: Gross domestic product; FDI: foreign direct investment. 2. All data is from World Development Indicators (www.data.worldbank.org/data-catalog/world-development-indicators) unless indicated. 3. Source for Singapore: Monetary Authority of Singapore, www.mas.gov.sg/about_us/annual_reports/annual_reports.html. 4. Source for South Korea: Jeon Y, Miller SM, Yi I. 2007. Performance comparisons and the role of restructuring for foreign and domestic banks, SSRN: http://ssrn.com/abstract=1006310. 5. Source: UNCTAD (2000)

46

Appendix 2. Institutional Environments in Singapore and South Korea (1990s) Singapore South Korea Capital markets

- Open, but with restrictions in selected areas, and with relatively well-developed regulations and governance frameworks. - Stock exchange competed to attract foreign listings and investments; restrictions on foreign ownership exist in limited areas. - Very large presence of foreign financial institutions and capital, though with restrictions in retail banking and finance. - Few restrictions on foreign acquisitions of domestic firms and almost no restrictions on FDI. - Domestic firms had ready access to local capital markets and foreign sources of capital.

- Relatively closed markets, with under-developed and poorly enforces regulatory and governance frameworks. - Stock exchanges and financial markets restricted foreign listings and investments, and foreign ownership of local firms. - Strong constraints on foreign financial institutions establishing operations in Korea. - Strong formal and informal restrictions on foreign acquisitions of domestic firms, with constraints on FDI in many areas. - Most domestic firms faced constraints in accessing foreign capital markets.

Labour markets

- Relatively flexible, with few restrictions on inward or cross border movement. - Regulations aimed primarily to support economic growth and limit disruption to firms. - Orderly tripartite employer-union-government system coordinated negotiations, arbitrated disputes and eliminated major industrial conflict.

- Relatively rigid, with strong informal and formal restrictions on internal or cross border movement of managers and employees. - Employment and labour regulations aimed primarily at supporting large businesses. - Disruptive employer-union relations, with ritualized and confrontational industrial action.

Product markets

- Developed and largely free markets with almost no barriers on imports or foreign participation. - Among the most open and globalized of economies. Highly integrated with global markets.

- Well developed, but with strong formal and informal barriers on imports and MNC participation. - Technologically advanced but relatively isolated from external markets and trends.

Legal systems

- Derived from English common law.- Regulations focused on supporting economic growth and imposed relatively limited constraints on business except in selected areas. - Major MNCs presence resulted in most rules and regulations conforming to Western systems.

- Civil law, derived from German system.- Economic regulations designed to support governments' industrial policies and business groups. - Limited influence of foreign institutions, resulting in local and idiosyncratic systems.

State structure and political regime

- Developmental global-city state based on single party political dominance and a pragmatic ideology prioritising economic development, political stability and a non-confrontational approach to most issues.

- Developmental state based on multiple political parties driven by strong sense of economic nationalism. State maintained strong links with business elites and prioritised development centred on business groups.

Trust and authority structures

- Economic exchange based on strong trust in formal institutions, which had substantial authority based on government links and strong economic growth. Informal institutions had relatively little impact on economic exchange.

- Formal institutions related to business were not fully developed or trusted. - Economic exchange importantly influenced by informal institutions.

Dominant business groups

- GLCs were the dominant domestic group, though some family business groups were prominent. - Government was very active in business through economic and industrial policies and operations of its statutory boards; direct participation occurred through GLCs.

- Family-based business groups were dominant, accounting for very large share of the economy and exports. - Government intervened heavily in business with policies designed to channel resources to business groups, as the key drivers of economic growth.

Source: Authors, Dent (2002), Feenstra and Hamilton (2006), Huff (1995), Rodan et al. (2006) and Whitley (1999).

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