Going (More) Public: Ownership Reform among Chinese Firms

Heather A. Haveman University of California, Berkeley, Department of Sociology

410 Barrows Hall Berkeley, CA 94720-1980

email haveman@berkeley.edu tel 510-642-3495

Charles Calomiris Columbia University, Graduate School of Business

601 Uris Hall, 3022 Broadway New York, NY 10027-6902 email cc374@columbia.edu

tel 212-854-8748

Yongxiang Wang Columbia University, Graduate School of Business

Uris Hall, 3022 Broadway New York, NY 10027-6902

email ywang05@gsb.columbia.edu

10 March, 2008

We are grateful to three anonymous reviewers for their insightful comments. We also thank Doug Guthrie for helpful comments, and Zhichao Fang, Feihu Long, Rong Xu, and Kui Zeng for informative discussions about details of the ownership reform plan and for providing some of the data we analyzed here. The third author would also like to thank the Center for International Business Education and Research (CIBER) at the Columbia Business School for financial support.

Going (More) Public: Ownership Reform among Chinese Firms

Abstract

During the past two years, Chinese joint-stock companies have been converting non-tradable stock

held by the state and state-controlled institutions, which constitute almost two-thirds of all stock in

Chinese firms, into stock that can trade on local exchanges. This ownership reform reduces direct

state control over industrial enterprises. It also greatly increases the supply of stock, which threatens

to depress stock prices because there is no corresponding increase in demand. For this reform to

succeed, holders of tradable stock must be compensated for the expected stock-price depreciation.

The most common form of compensation consists of stock grants. Despite huge differences in

stock-price returns, stock-price volatility, and the number of non-tradable shares, most Chinese

firms set compensatory grants at about the same level: three shares for every ten shares of

outstanding tradable stock. Our analysis demonstrates that, net of coercion from state owners, most

of this surprising isomorphism is due to imitation of other firms. Interestingly, we find little direct

evidence of normative isomorphism due to professional advisors.

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Over the past three decades, China has moved gradually from state socialism toward market

capitalism. This transition has involved many different reform events, but all are centered on two

aspects of political economy (Walder, 1995; Naughton, 1995, 2007; Chow, 2007). First, ownership

of productive enterprises has slowly shifted away from central state control toward a combination of

local state and private control, and institutions that create and safeguard property rights have been

developed to foster private ownership. Second, economic transactions have increasingly been

conducted through markets rather than through central planning and redistributive efforts

co-ordinated by national, provincial, and local state offices.

One of the most notable stages in this gradual economic transition involves selling

ownership shares of industrial enterprises that can be traded freely among individual and

institutional investors. By July 2007, over 1,200 formerly state-owned enterprises had conducted

initial public offerings of stock, becoming publicly-held and publicly-traded companies. But until

very recently, these firms were only partially publicly-held and publicly-traded, as most of their stock

was held by the state itself or by state-owned or state-controlled institutions, and this stock traded

only through auctions or negotiations involving other state-owned or state-controlled entities, not

on stock exchanges. On April 29, 2005, the China Securities Regulatory Commission (CSRC) – the

Chinese equivalent to the U.S. Securities and Exchange Commission – announced a plan by which

non-tradable shares could be converted into shares that could be traded on stock exchanges. In

other words, publicly-traded Chinese firms would become more public.

This news was welcome as a concrete step toward a less state-owned and more market-based

economy, which state officials and economic analysts alike hoped would eliminate conflicts of

interest between owners of tradable and non-tradable shares, reduce stock-price volatility and raise

stock prices, and motivate the continued development of effective corporate governance systems

(Inoue, 2005; Wang and Chen, 2006; Chow, 2007). But this news was also greeted with dismay, for

it presented shareholders with a problem: unless managed carefully, a flood of new shares would

depress the prices of tradable shares. Anticipating this problem, the CSRC required that reform be

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done in increments and allowed the owners of tradable shares to be compensated for losses

anticipated to be incurred when stock prices fell. The form and amount of compensation offered to

the owners of tradable shares was left open to negotiation between the two groups of owners.

Our analysis focuses on this most recent step in China’s transition toward market capitalism.

We are interested in solving an empirical puzzle: Why do most Chinese firms offer around the same amount

of compensation to holders of tradable shares? Asset-pricing models from finance predict that the amount

of compensation offered should vary greatly, depending on the number of non-tradable shares

outstanding, the volatility of the focal firm’s stock price, and the correlation between its stock-return

volatility and market return (Kahl, Liu, and Longstaff, 2003; Wu and Wang, 2005). Even though

these three factors varied greatly across firms, the vast majority of Chinese firms compensated

tradable shareholders with grants of about three new shares of stock for every ten shares of tradable

stock held before reform.

In explaining this regularity, we contribute to sociological research on China’s transition

toward a decentralized, market-based, and privately-owned economy. Many observers of China

would expect to see strong coercive pressures emanating from the state because the state has long

controlled political, cultural, and economic familial life in China, and because the state is the largest

owner of many publicly-traded firms (Guthrie, 1997; Green, 2003; Guthrie, Xiao, and Wang, 2007).

But we show that net of state coercion, imitation is the strongest predictor of Chinese firms’

compensation ratios. Our analysis suggests that, at least with respect to some of China’s most

market-focused enterprises, state control over the economy has waned and Chinese firms are

coming to resemble their Western counterparts by attending to the actions of other firms as much

as, if not more than, the demands of the state. These findings dovetail with the argument that the

state’s monitoring and sanctioning capacity has declined due to the shift from a centrally-planned

economy to a market-mediated one (Walder, 1994), and with studies showing that dependence on

the state for guidance and funding has declined as external advisors (such as lawyers and investment

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bankers) and external sources of funding (such as commercial banks, the stock market, and foreign

investors) have developed (Walder, 1994; Keister, 2004).

We also contribute to the study of organizations as economic institutions by bringing issues

of agency into institutional analysis, which responds to longstanding complaints that institutionalist

analyses generally lack a theory of action (Stinchcombe, 1997; see also Perrow, 1985; Abbott, 1992).

We do this by considering the often-conflicting interests of different parties to negotiations over

ownership reform: holders of non-tradable shares (both state and private-sector institutions),

holders of tradable shares, the agents of state and non-state owners, and the managers of publicly-

traded firms. Our analysis is an advance on previous efforts to introduce agency into institutional

analysis because it is based on a well-developed model: economic agency theory. In marrying

institutional and agency ideas, we strive to distinguish between coercive, normative, and mimetic

isomorphic forces (DiMaggio and Powell, 1983), which have often been conflated in previous

research (Mizruchi and Fein, 1999).

We proceed as follows. Since most sociologists are unfamiliar with the Chinese economy, in

particular with how Chinese enterprises are privatized, we begin by describing this process and

detailing the legal institutions that underpin the Chinese political-economic transition. We then map

this evolving empirical terrain onto ideas from sociological theory, and develop hypotheses to

predict how much compensation holders of tradable shares should receive. Next, we describe our

data sources and measures, and explain how we test our hypotheses. After presenting the results of

our empirical analyses, we conclude by considering the implications of our study for sociological

accounts of firm behavior, in particular, explanations of China’s transition toward a market economy

with substantial private ownership of industrial enterprises.

Background: Taking Chinese Enterprises Public

Starting in 1979, the central government of the People’s Republic of China ceded managerial

control of productive enterprises to provincial, municipal, township, and village governments,

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thereby creating myriad state-owned enterprises (SOEs). In addition, the central government

created a “dual-track” system that sent more tax revenues directly to local governments. This kept

SOEs oriented toward the central government’s economic plan, but also gave them incentives to

generate extra income by selling in local markets anything they produced above the plan. Thus,

from 1979 to the mid 1990s, China adopted some aspects of a market economy while continuing to

operate a planned economy (see Naughton [1995, 2007] for more details). By the mid 1990s, the

market component of China’s economy had outstripped the planned component.

This gradual two-dimensional shift – away from central state ownership of productive

enterprises toward local state and private ownership, and away from planned and co-ordinated state

management of the economy toward market-mediated transactions – was bolstered by the aggressive

creation of a rule-of-law infrastructure in the 1980s and 1990s (Guthrie and Wang, 2006; Guthrie et

al., 2007)1. Perhaps the most important regulation is the Company Law, which was passed in 1994

and which codified the process of converting SOEs into corporations. It encouraged enterprises to

standardize governance structures and develop procedures to limit political intervention in

enterprise decision making. This law marked a fundamental shift in the organization of China’s

economy, as it allowed Chinese firms to become legal entities independent of the state, as limited-

liability joint-stock companies [gufen youxian gongsi], whose stocks trade on domestic and foreign stock

exchanges. The Securities Law, which took effect July 1999, further codified the legal basis for the

standardized operation of joint-stock companies.

As a result of these reforms, over 1,200 SOEs floated initial public offerings of stock (IPOs)

and become publicly-traded joint-stock companies. The privatization of SOEs was facilitated by the

opening of the Shanghai and Shenzhen stock exchanges in 1990 and 1991, respectively. The

number of IPOs rose from eight in 1990, the first year data are available, to 1,483 in 2006, while the

number and value of shares issued in IPOs soared from 0.048 billion shares valued at 0.081 billion

1 For a review of legal developments in China, see the special issue of the China Quarterly published September 2007.

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RMB (renminbi, or Chinese yuan) in 1990 to 130.1 billion shares valued at 681.4 billion RMB in 2006

(GTA, 2007).

In the process of going public, entire SOEs may be privatized. Alternatively, single plants or

groups of plants, often the best-performing ones, may be spun out of SOEs. In either case, SOEs

first apply to their local State Assets Administration Bureau for permission to have their assets

appraised. After permission is granted, SOEs choose a certified public assessor or accountant, who

calculates the enterprise’s value. The Bureau conducts further analysis, considering the enterprise’s

health, its industrial sector, and the state’s interests. The final valuation amount is divided into state

shares [guojia gu], which represent investments by the state in the creation, expansion, or upgrading

of the enterprise. State shares are valued at 1 RMB each and held by State-owned Assets

Supervision Administration Commissions or by SOEs that are wholly owned by the state.

New joint-stock companies can raise additional capital by offering three kinds of shares to

three kinds of investors. Institutional shares [faren gu], which are also known as legal-person shares,

are dividend-earning shares offered to domestic institutions such as other joint-stock companies that

have at least one non-state owner and domestic non-bank financial institutions (pension and mutual

funds). Trading in institutional shares is highly restricted; they can be purchased through negotiation

or auction and such trades require the approval of the local government and the exchange on which

the firm is listed (Green, 2003: 119, 144); most are held by state-owned or state-controlled

institutions, although an increasing fraction are held by private-owned or private-controlled firms

(Green, 2003). Individual shares [geren gu], which are also called A shares, are sold to domestic

(mainland Chinese) investors, mostly individuals and a few domestic institutions. These are

dividend-earning and fully negotiable. Foreign shares have been offered since late 1991 to attract

indirect foreign investment; they come in several flavors. B shares are sold to foreign individuals

and institutions, and are traded on the mainland Chinese stock exchanges in a market that is separate

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from the A-share market.2 On the Shanghai Stock Exchange, B shares are denominated in U.S.

dollars; on the Shenzhen Stock Exchange, they are denominated in Hong Kong dollars. H, N, S, J,

and L shares are traded on the Hong Kong, New York, Singapore, Tokyo, and London exchanges,

respectively, and denominated in local currency.

The People’s Bank decides how many of each kind of shares can be offered. In accordance

with the gradual pace of China’s economic transition, the state has generally required that the

majority of shares in publicly-traded firms be held by institutions that are wholly state-owned. In

this way, the state retained majority ownership and therefore control over most ostensibly public

firms (Chow, 2007; Guthrie et al., 2007).3 As of year-end 2005, non-tradable shares constituted 62%

of shares outstanding in publicly-traded firms; 71% of those were held directly by the state

(Naughton, 2007: 470). In addition, many of the non-tradable legal-person shares (27% of shares

outstanding) were held by state-controlled institutions.4 Notwithstanding this concentration of

shares in the hands of the state, there is great variation across firms in the allocation of shares.

Among the 1,325 firms listed on the Shanghai and Shenzhen Stock Exchanges between 1995 and

2004, state shares ranged from zero to 85% of total shares outstanding (the mean was 39%), legal-

person shares ranged from zero to 80% (mean 21%), tradable A shares ranged from 9% to 91%

(mean 37%), and foreign shares ranged from zero to 62% (mean 4%) (Eun and Huang, 2007: 458).

Initial offering prices for tradable shares are based on the People’s Bank’s estimates of the

company’s future earnings and its assets, and are set to produce price/earnings ratios approximating

international standards. Because of the extraordinary demand for shareholding in China, tradable

2 Until recently, it was illegal for non-mainland Chinese to buy and sell A shares; in December 2002, foreign investors were given limited rights to trade in A shares under the Qualified Foreign Institutional Investor system. And until recently, mainland Chinese could not invest in B shares or trade in international markets; as of March 2001, they could buy and sell B shares, but only by using legal foreign-currency accounts. 3 In addition, former SOEs are still mostly state-run after they go public. The previous enterprise manager and party secretary are typically reappointed as a publicly-traded company’s new chief executive officer and chairman of its board of directors (Chow, 2007). 4 Just how much of this 27% is state-controlled is difficult to estimate, since there are often several layers of ownership. For instance, one state-owned or state-controlled organization may have a controlling interest in an ostensibly non-state-owned organization, which in turn holds shares in a publicly-traded firm.

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share prices rise quickly after IPO. The upshot is that prices of tradable shares may be an order of

magnitude higher than the prices of non-tradable state shares (Hertz, 1998; Green, 2003).

This system of split ownership (part state, part non-state; part tradable, part non-tradable)

was put in place to enable SOEs to raise capital and to allow the government to maintain control of

selected enterprises through majority ownership. But this system created several interrelated

problems (Green, 2003; Wang and Chen, 2006; Feinerman, 2007). Most obviously, there is an

inherent conflict of interest between holders of tradable and non-tradable shares. When the state is

a controlling shareholder, political priorities (maintaining employment levels, providing social

welfare benefits like housing and child care, and controlling sensitive industries) may displace profit-

seeking. Moreover, controlling shareholders, whether state or non-state, can manipulate firms’

accounts by carrying out transactions with affiliated companies to siphon off assets and profits.

Because tradable shareholders are usually in the minority, they have virtually no say in corporate

governance. And because the vast majority of shares are not traded, the stock market is thin and so

vulnerable to fraud and manipulation.

Going More Public: Converting Non-tradable Shares to Tradable Shares

After the domestic stock exchanges were established, Chinese officials struggled with the

issue of how to get non-tradable shares into circulation. Doing so was expected to force publicly-

traded firms to become more efficient and less vulnerable to fraud, and to make it easier to raise

additional capital in the stock market (Chow, 2007). Alas, early reforms failed utterly. In 1992,

when officials suggested that institutional shares be allowed to trade on the domestic stock markets,

prices of tradable shares dropped because supply was expected to swamp demand. The same thing

happened in 1999 when officials announced that state-owned shares of two firms would be made

tradable. On June 12, 2001, the CSRC announced the Tentative Measure for Decreasing State Shareholding,

which was intended to accelerate privatization by requiring the conversion of some non-tradable

shares (10% of total shares outstanding) to tradable status at the tradable-share price. Although only

17 firms participated in this reform, the stock markets plunged 30% in three months. As a result,

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this reform was cancelled four months after it was announced. Due to this aborted reform and to

expectations that other reforms might be in the offing, as well as to the generally poor performance

of listed companies and the discovery of widespread fraud, the stock-market crash continued for

four years. By 2005, market capitalization had declined by over 50%.

The reform on which we focus was unveiled on April 29, 2005, when the CSRC released the

Directive on Problems in Trying to Solve the Split-Share Structure of Listed Companies, which announced that

non-tradable shares would be converted into tradable shares starting in May. Learning from past

mistakes, the CSRC structured the reform to increase the chances that this time reform would

succeed (Wang and Chen, 2006). To begin, reform was to be rolled out in stages. Four firms were

to serve as a pilot project; after their ownership reform was completed, 42 large firms, which

together accounted for 10% of the overall domestic stock-market valuation, were to undertake

reform; only after they finished would other listed firms proceed with reform.5 The reform plan

mandated a one-year lock-up period for holders of formerly non-tradable stock. After the lock-up

period expired, state bureaus and other institutions that held more than 5% of outstanding shares

could sell no more than 5% in the first 12 months and no more than 10% in the first 24 months.

This was intended both to reduce the volume of shares that would enter the market and to signal the

state’s intention to retain sizeable ownership stakes in many firms.

Two features of this reform plan were crucial to its success. First, firms had to obtain

approval from at least two-thirds of non-tradable shareholders and two-thirds of tradable

shareholders. This required a serious negotiation, mediated by the board of directors and

investment banks. Second, the CSRC encouraged non-tradable shareholders to compensate tradable

shareholders for the losses the latter expected to incur. Because tradable share prices would be

diluted when non-tradable shares converted, tradable shareholders needed to be compensated to

5 This is typical of Chinese economic reforms, where the state reveals its policy through the actions of “model” firms, whose experience often prompts adjustments in the reform process before it is applied more generally. In Chinese, this is called mo zhe shi tou guo he, or “crossing the river by feeling the stones.” The phrase was used by Deng Xiaoping to mean that there is no suitable model for reform, so you have to advance step by step and reassess your route after each step.

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persuade them to allow the conversion and to assure investors that their ownership rights would be

upheld.

The CSRC did not specify how firms should compensate tradable shareholders; it left the

details to be negotiated (Inoue, 2005; Wang and Chen, 2006). The Directive of April 29 stated that

“…the companies selected to take part in the experiment decide for themselves how they will sell

their non-tradable shares” (CSRC, 2005a). Guidance notes released by the CSRC on August 23

reiterated this point by declaring the CSRC’s aim was “independent decision-making with respect to

specific share reform scheme to suit circumstances” (CSRC, 2005b). At a press conference held

September 4, when guidelines for the third reform wave were promulgated, the CSRC reinforced

this stance, stating that “the principle approach and operating principle for the Reform” was

“flexible decision-making to suit different circumstances under centralized coordination” (CSRC,

2005c). It is no surprise that legal scholars concluded:

The implemented reform is essentially a privatized bargaining process between the non-tradable and tradable shareholders. The market-based and private bargaining elements of the reform have been repeatedly emphasized in the relevant guidelines and regulations (Wang and Chen, 2006: 341).

Ownership reform begins with a vote by non-tradable shareholders; a two-thirds majority is

required to initiate the reform process. After drawing up and announcing a plan, the board of

directors announces the date of shareholders’ meetings to vote on the plan, and all trading in the

firm’s stock is halted. During negotiations with both tradable and non-tradable shareholders, the

plan may be revised. After the plan is finalized, it is announced to the public and trading is resumed.

Trading is suspended a second time before the shareholders meet and vote on the plan. There are

two separate and independent meetings: one for non-tradable shareholders, the other for tradable

shareholders. For a reform plan to pass, it must be approved by the holders of two-thirds of non-

tradable shares participating in their shareholders’ meeting and by the holders of two-thirds of

tradable shares participating their shareholders’ meeting. If the plan passes in both meetings, the

firm announces the result the next day and the stock begins to trade again.

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This reform effort was hugely successful: 1,250 firms listed on the Shanghai and Shenzhen

Stock Exchanges, a full 84.3% of the total, had undertaken ownership reform by July 18, 2007.

Moreover, starting in late 2005, the domestic stock markets’ capitalization levels surged. The

Shanghai Composite Index increased by 211% over the calendar year 2006, while the Shenzhen

Composite Index rose by 197% over the same period.

The Empirical Puzzle: Isomorphism in Compensation for Owners of Tradable Shares

The first firms to convert non-tradable shares into tradable shares were Sany Heavy Industry

[San Yi Chong Gong], Shanghai Zi Jiang Enterprise [Zi Jiang Qi Yi], and Hebei Jinnui Energy

Resources [Jin Niu Neng Yuan], which announced reform plans in June 2005. (The fourth firm,

Tsinghua Tongfang, failed in its initial attempt at ownership reform because fewer than two-thirds

of the holders of tradable shares approved the plan.) All three successful firms chose to offer extra

equity to tradable shareholders. Their compensation ratios – the number of new shares offered

relative to the number of existing shares – were set at 0.35, 0.25, and 0.30, respectively. The next

month, the second batch of 42 companies announced reforms; their average compensation ratio was

0.33. Of the 1,250 firms that reformed their ownership between May 2005 and July 18, 2007, 87%

(1,086) compensated tradable shareholders through transfers of stock from non-tradable

shareholders. The other 13% used other means of levelling the playing field: offering call or put

warrants to tradable shareholders, guaranteeing stock buy-backs for tradable shareholders at pre-set

prices, or cancelling a fraction of non-tradable shares before conversion. Figure 1, which plots the

cumulative distribution function for compensation ratios among the 1,086 firms that chose this

option, shows that most firms set compensation ratios close to 0.30 (the mean and median are 0.300

and 0.306, respectively) and that the distribution is quite compact (the 25th and 75th percentiles are

0.264 and 0.347, respectively).

[Figure 1 about here]

Such clear isomorphism is surprising because the CSRC did not specify how firms should

compensate tradable shareholders; instead, it merely made general provisions for compensation and

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left the details to be negotiated (Inoue, 2005; CSRC 2005a, 2005b, 2005c; Wang and Chen, 2006).

Moreover, models of asset pricing predict great variation in compensation ratios, depending on the

fraction of shares that are at risk of converting to tradable status, the volatility of the firm’s stock

price, and the correlation between stock-return volatility and market return (Kahl et al., 2003; Wu

and Wang, 2005). Why, then, do most firms set their compensation ratio at about the same level –

three new shares for every ten? Our goal is to explain this remarkable level of similarity in behavior.

Or, to put it another way, we seek to explain what causes firms to deviate from this standard. We

begin by focusing on how political coercion operated through the actions of the Chinese state. We

conclude with an assessment of norm-guided behavior and imitation.

Theory: Setting Compensation Ratios

As communities of organizations evolve, a variety of forces, such as interorganizational

power relations, the state and professions, and competition, promote organizational isomorphism –

similarity in structure or behavior (DiMaggio and Powell, 1983). Being isomorphic with prevailing

notions of structure or behavior brings organizations legitimacy, which in turn improves access to

resources and acceptance, and thus contributes to organizational survival (Meyer and Rowan, 1977).

Organizations become isomorphic in three ways (DiMaggio and Powell, 1983). Coercion works

through organizations on which the focal organization is dependent and through cultural

expectations of the societies in which organizations operate. State institutions like the laws and

administrative guidelines that constitute the basic rules governing transactions are exemplary agents

of coercive isomorphic pressures. Norms works through “expert” sources of information about the

nature of fields, values (what is important and good), and expectations (how things should be done).

Professions and collective actors like industry associations are major sources of normative

isomorphic pressures. Imitation works through observation of others and stems from responses to

uncertainty. Copying others, in particular similar others that are perceived to be more successful and

legitimate, is an efficient solution to ambiguous causes and unclear solutions: when in doubt, do

what highly successful (and therefore highly legitimate) organizations do.

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This model has typically been used to explain the behavior of organizations in Western

capitalist economies. But it offers great promise to explain the behavior of organizations in other

settings, including Asian societies undergoing economic and political transitions, as a few examples

make clear. Westney’s (1987) analysis of the transfer of Western organizational structures in Meiji-

era Japan revealed coercive, normative, and mimetic effects, tempered by the fact that the

organizations she studied adapted Western structures to fit their own culture. More germane to our

study is Guthrie’s (1997) analysis of Shanghai firms in the mid 1990s. Their creation of Western-

style bureaucratic structures – written rules and job descriptions, formal grievance procedures and

mediation committees, and formal hiring procedures and promotion tests – was driven by all three

of the isomorphic processes identified by DiMaggio and Powell (1983): state mandates, normative

pressures from foreign investors, and economic uncertainty, which prompted imitation of other,

“market-savvy” Chinese firms. Similar to Westney, Guthrie found that Chinese managers did not

blindly imitate Western firms; instead, they tailored the logics underpinning Western structures to

their own political and economic situation.

Many scholars have complained that institutionalist accounts of organizations, including

DiMaggio and Powell’s (1983) model of isomorphism, ignore the “guts” of institutions: the people

whose interests are at stake when institutions diffuses across fields (Stinchcombe, 1997; see also

Perrow, 1985; Abbott, 1992). There have been some attempts to incorporate a theory of action into

this model of isomorphism (e.g., Dobbin, et al., 1993; Fligstein, 1996), but those attempts are limited

because their thinking about action and agency is limited to the particular phenomena under study

(e.g., the roles played by personnel managers in developing affirmative-action policies for employing

organizations or the interests of corporate managers in market stability). To infuse this very general

institutional model with a general theory of action, we draw on the highly coherent theory of agency

derived primarily from economics (Jensen and Meckling, 1976; Fama, 1980).

Briefly, agency theory focuses on relationships between principals and agents (for an

engaging review, see Shapiro [2005]). Principals hire agents to perform services and delegate

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decision-making authority to those agents; for instance, owners shareholders hire executives to run

corporations, and corporate executives hire professional investment banks to advise them on

financial transaction. There are often conflicts between principals and agents, for two reasons.

First, agents’ interests are often not identical to those of principals; for example, principals want

executives to maximize their firm’s share price, both in the short run and in the long run, while

executives want to maximize their compensation, which may depend only on short-run share-price

performance. Second, principals and agents have different information; in particular, principals

cannot know precisely how hard agents are working, or even whether agents are working at the right

tasks. The upshot is that agents are often prone to doing things that principals don’t want them to

do. To prevent this, principals try to set up reward and monitoring systems so as to align agents’

interests more closely with those of principals, or to make it harder for agents to do the wrong thing

or do too little of the right thing.

Like the model of institutional isomorphism, the model of principal/agent conflict is a

general one. But it, too, has great power to explain the behavior of organizations in China and other

countries that are undergoing economic and political transitions. For example, Lin, Cai, and Li

(1998) argued that the separation of ownership and control causes Chinese industrial enterprises to

suffer from the same agency problems as those of Western corporations. Similarly, Walder (1995)

demonstrated that the varying ability of state institutions to monitor the enterprises they own

(strongest at the local level and weakest at the central state level) accounts for differences in

enterprise performance.

Because of its evident importance in Chinese society, our analysis begins by discussing the

state’s coercive power. We then consider normative and mimetic factors in succession. For all three

isomorphic processes, we first conduct a traditional, agency-free institutional analysis, and then

renalyze the situation considering the interests, motivations, and abilities of all relevant actors.

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The Coercive Power of the Chinese State

The most obvious explanation for similarity of behavior among Chinese firms – or any other

collection of Chinese actors, for that matter – is state coercion. The state strictly governs all aspects

of political, cultural, and economic life in China. Indeed, China has since 1978 earned a Polity IV

score of -7 on a scale ranging from +10, which denotes full democracy, to -10, which denotes full

autocracy (http://www.cidcm.umd.edu/polity/country_reports/Chn1.htm). State policy can be

changed at any time with little or no input from the public. Sudden policy shifts are excellent

natural-experimental stimuli, since seldom can anyone predict what policies will be announced. This

contrasts sharply with most Western countries, where government action is generally preceded by

public debate and so can be easily anticipated.

Coercion by the state as regulator. For publicly-traded Chinese firms, the CSRC is a powerful

coercive actor. Publicly-traded firms must get approval from the CSRC for any significant financial

decisions, such as equity offerings and mergers, while private firms must get approval from the

CSRC to be listed on domestic or foreign stock exchanges and so become publicly-traded. It is clear

that publicly-traded firms were coerced into reforming their ownership by the CSRC. On May 30,

2005, the CSRC and the central State-owned Assets Supervision Administration Commission jointly

issued a statement stressing how important the ownership reform program was and stating that all

those involved should give it their support. In addition, the CSRC offered companies that reformed

their ownership structures priority when they sought to raise new capital by borrowing from state-

controlled banks or floating new equity issues. The coercive actions of the CSRC can explain why

almost all publicly-traded companies in China have launched ownership reforms, but not why they

settled on such similar compensation ratios. The law of 2005 explicitly requires that each firm

determine on its own how it would compensate holders of tradable shares. Not only does the CSRC

place no restriction on the amount or form of compensation, it actively encourages firms to design

compensation schemes appropriate for their particular situations (Inoue, 2005; CSRC, 2005a, 2005b,

2005c). This flexibility was built into the reform to avoid past mistakes. An article published in the

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China Securities Journal (Wang, 2003), the most influential business paper in China, concluded that the

failed reform of 2001, “…teaches us a big lesson, that is, government and regulatory agencies cannot

simply set a uniform plan for thousands of public firms to solve this [non-tradable shares] issue.”

Interviews with Chinese investment bankers indicate that this sentiment is widespread. Therefore,

the great isomorphism that we see in compensation ratios was clearly not due to general coercion by

the CSRC. To explain this, we must look to how state coercion plays out within firms, specifically,

through the state’s presence as an owner.

Coercion by the state as owner. Unlike firms in the U.S., the state has a large presence in publicly-

traded Chinese firms: most shares are held by state-owned agencies, and all of these shares are non-

tradable. Thus, the state enters directly into the negotiation between the non-tradable and tradable

shareholders over the compensation the former should offer the latter. The interests of the two

groups are opposed: all non-tradable shareholders, including the state, prefer to offer little or no

compensation to tradable shareholders, while tradable shareholders prefer to be offered a lot of

compensation. A super-majority of both groups must be satisfied if the reform is to proceed.

The tug of war that ownership reform unleashes is a game played in a fog. This reform is

highly uncertain because, as explained above, earlier ownership reforms failed. Moreover, the

property rights of tradable shareholders are recent social inventions, and so not well understood,

much less accepted as permanent (Putterman, 1995; Oi and Walder, 1999). The situation is

exacerbated by the fact that this reform involves complex financial-economic calculations. To

determine the appropriate level of compensation, one must calculate how much non-tradable shares

would increase in value and how much tradable shares would drop in value if the ownership reform

were to pass. Although the windfall gains accruing to non-tradable shareholders can be calculated

using a method developed by Wu and Wang (2005), which is a variant of Kahl et al.’s (2003) asset-

pricing model, the losses accruing to tradable shareholders cannot be calculated because no asset-

pricing model has been developed.

16

In sum, because of the great uncertainty surrounding this reform, no-one knows what

compensation is optimal or fair. This makes compensation schemes observable but not easily verifiable:

observable because they are divulged, not verifiable because their truth-claims cannot be checked

without a great deal of time and effort (Bolton and Dewatripont, 2005). The inability to verify

compensation schemes arises from the fact that there is no clear and precise benchmark. The only

outcome owners can verify is whether or not reform passes. The upshot is that the negotiation

between the two ownership groups offers many opportunities for manipulation.

The question of which ownership group wins the tug of war depends, in large part, on a

third party: the executives of publicly-traded firms. Executives prefer to offer more compensation

than non-tradable shareholders because it is in executives’ interests for this reform to succeed. If it

does, executives and their firms will be viewed favourably by the CSRC, and their firms will be

eligible for preferential terms on loans and future equity offerings. The probability of reform

succeeding, which hinges on a two-thirds majority vote by tradable shareholders, increases with the

amount of compensation offered. The tendency of managers to offer high levels of compensation

to ensure success is accentuated by the fact that managers, like owners, do not know how much

compensation is optimal or fair; managers know only that more compensation makes acceptance by

tradable shareholders more likely. Agents can be held accountable by principals only for verifiable

outcomes, not for unverifiable outcomes (Bolton and Dewatripont, 2005); this means that managers

can be held accountable only for the success or failure of reform attempts, not for the compensation

schemes they suggest to owners.

One of the strongest players in this three-way tug of war is the controlling shareholder.

Some firms are controlled by the state, while others are controlled by non-state institutions, such as

other pension funds, mutual funds, joint-stock companies, and foreign firms. With respect to the

compensation offered to holders of tradable shares, private-sector holders of non-tradable shares

have the same preference as the state, but less power to coerce executives. When the state is the

controlling shareholder, the state will be more successful at pushing executives to offer less

17

compensation than would a private-sector controlling shareholder, because the state is a stronger

coercive force. Accordingly, we propose that when the state is the controlling shareholder, the state

has the leverage to win the tug of war:

Hypothesis 1a: Firms controlled by state owners will set lower compensation ratios than firms controlled by private-sector institutions.

There is reason, however, to believe that this hypothesis is wrong, due to the different

capacities of state and non-state owners to monitor executives, and to agency problems within the

state itself. Starting in 2003, the state’s ownership interests have been handled by central and local

State-owned Assets Supervision Administration Commissions (SASACs), which monitor the

operations of the firms owned by the state, appoint directors, approve major operating decisions,

and report on performance and revenues to government bureaus. SASACs were created to separate

the government’s functions as owner of state assets from its function as public manager of society as

a whole and to reduce the diversion of assets from publicly-traded firms into the hands of managers

and their cronies (Naughton, 2007: 316). SASACs are fiduciaries of the state bureaus that own

SOEs, township and village enterprises (TVEs), and former SOEs and TVEs that have been

transformed into corporations. The central SASAC represents the State Council’s interests; local

SASACs represent provincial, municipal, township, and village governments. SASACs also control

state-owned asset management companies (Naughton, 2007).

SASACs are analogous to institutional investors like pension or mutual funds, as each is set

up to manage a portfolio of assets (Guthrie et al., 2007). Because each SASAC represents the state’s

ownership interests in many firms (for example, the central SASAC originally oversaw 196 firms),

SASACs have limited ability to monitor any single firm (Sun and Tong, 2003). The central SASAC’s

control of the firms it monitors is particularly limited because multiple layers of holding companies

own stakes in publicly-traded firms; it is the highest level of holding companies, rather than the

central SASAC, that actually controls firms (Naughton, 2007: 317-318). In contrast, the typical non-

state owner is a large shareholder in only a few firms, so non-state owners of legal-person shares are

18

both more able and more motivated to monitor and coerce enterprise management than are

SASACs (Xu and Wang, 1999).

Non-state owners are also generally more competent to monitor enterprise management

than are SASACs. Non-state owners have more expertise than SASACs because many legal-person

shareholders have close business ties to publicly-traded firms: many firms were carved out of non-

state legal-person shareholders, and many legal-person ownership stakes were created through debt-

equity swaps (Qi, Wu, and Zhang, 2000). Such close business ties facilitate monitoring managers.

Moreover, all SASACs are beset by internal agency problems (Wang and Chen, 2006; Chow,

2007). SASAC employees generally hold short-term appointments (a few years at most) and their

performance is evaluated annually or at the end of their appointment. Therefore, SASAC employees

are motivated to pursue short-term goals at the expense of the long-term health of the firms they

oversee. SASAC employees have been told repeatedly that ownership reform is important, and that

high-ranking state officials want it to succeed. Therefore, SASAC employees may be tempted to

jump on the reform bandwagon and accept high levels of compensation to ensure that tradable

shareholders vote for reform, even though such actions run counter to the interests of the state

owners they are supposed to safeguard. The tendency of SASAC employees to offer more

compensation than state owners prefer is enhanced by the fact that SASAC employees do not

personally foot the bill – the state owners do.

Given these three facts – (i) SASAC employees’ attention is scattered across many firms

while the attention of non-state owners is concentrated on one or a few firms, (i) non-state owners

are more competent to monitor the firms they own than state owners, and (iii) the interests of

SASAC employees are not aligned with those of the state – the coercive power of the state may be

less than that of non-state owners. If so, firms controlled by the state should offer more

compensation to tradable shareholders than firms controlled by non-state owners. This logic yields

the following hypothesis, which is directly opposite to hypothesis 1a:

Hypothesis 1b: Firms controlled by state owners will set higher compensation ratios than firms controlled by private-sector institutions.

19

Conflict or co-operation between non-tradable shareholders? As the owner of publicly-traded firms,

the Chinese state is not a monolithic entity; instead, it is hydra-headed (cf. Adams, 1996; Kiser, 1999).

The policy of decentralization carried out since 1978 drove decision making about most industrial

enterprises down to the provincial and local levels. Subsequent corporatization and privatization

efforts led to a situation in which most state ownership stakes are in the hands of provincial and

local governments (Putterman, 1995). Because the state consists of many different entities, we must

consider not just the overall coercive power of the state, but also whether the many state owners of

a publicly-traded firm act in concert or clash. There is great variation across firms in the extent to

which state ownership is concentrated in the hands of a few parties, and therefore there is great

variation in the extent to which the state is a cohesive, much less monolithic, coercive force.

The issue of owner cohesion extends beyond state owners to all non-tradable shareholders.

As explained above, these owners must negotiate among themselves and agree on a compensation

scheme to offer tradable shareholders.6 Concentrated ownership of non-tradable shares can have

two opposing effects on the compensation scheme they negotiate. On the one hand, the more

concentrated ownership of non-tradable shares is, the stronger is non-traadable shareholders’

bargaining power vis-à-vis tradable shareholders. This happens because greater ownership

concentration means fewer owners have a say in setting the compensation ratio, which reduces free-

rider problems (Darley and Latané, 1968; Jensen and Meckling, 1976). The smaller the free-rider

problem among non-tradable shareholders, the more likely the outcome of the negotiation is to

reflect the preferences of non-tradable shareholders rather than those of tradable shareholders, and

the lower the compensation the two groups will agree on. Therefore, we propose:

6 The non-state owners of non-tradable shares are often closely tied to the state in two ways. First, legal-person shares are often transferred from the state to the private sector through negotiations to which only firms with close state ties have access (Calomiris, Fisman, and Wang, 2008). Second, some shares labelled non-state legal-person shares are actually state-owned due to inconsistencies in the Chinese stock-ownership classification system (Green, 2003: 15). For example, when a state-controlled firm establishes a subsidiary that purchases non-tradable shares through negotiation with a state owner, those shares are usually labelled legal-person shares. But they are still owned by a state-controlled firm, albeit indirectly. Thus, even when many non-tradable shares are held by non-state owners, the state has great oercive power.

20

Hypothesis 2a: The more concentrated ownership of non-tradable shares is, the lower the compensation ratio.

But the effect of concentrated ownership of non-tradable shares may run in the opposite

direction because the interests of non-tradable shareholders are not identical. Large non-tradable

shareholders have a particularly strong incentive to reform their firm’s ownership because they have

the most, in absolute terms, to gain from increases in the value in their share holdings due to

removing trading restrictions.7 The more concentrated ownership of non-tradable shares is, the

more controlling non-tradable shareholders can dominate the decision-making process, and the

easier it is for them to offer a high level of compensation to ensure approval by the holders of

tradable shares. This leads us to predict:

Hypothesis 2b: The more concentrated ownership of non-tradable shares is, the higher the compensation ratio.

Owners of tradable shares. Publicly-traded Chinese firms face a second source of coercive

pressure when they contemplate reforming their ownership structures: tradable shareholders must

agree to the reform proposal, or it will fail. When non-tradable shareholders negotiate among each

other to determine how much to offer tradable shareholders, they are likely to take into account

tradable shareholders’ expectations about compensation. The lower those expectations are, the less

compensation they will offer. The distribution of ownership among tradable shareholders

determines how much compensation they can demand. The more widely distributed shareholding

is, the more free-rider problems limit tradables shareholders’ ability to agree on and demand a high

level of compensation (Darley and Latané, 1968; Jensen and Meckling, 1976). Conversely, the more

concentrated shareholding is, the easier it is for tradable shareholders to band together and demand

a high level of compensation. Thus we predict:

Hypothesis 3a: The more concentrated ownership among tradable shareholders is, the higher the compensation ratio.

Ownership among tradable shares is often highly concentrated when mutual funds own large

stakes. This introduces a new player to our tug of war, mutual-fund managers. These agents may

7 We thank Mr. Kui Zeng of CITIC Securities, a leading securities firm in China, for pointing out this factor.

21

have different interests from their principals, mutual-fund investors. Specifically, non-tradable

shareholders can make side-payments to mutual-fund managers to persuade them to accept, on

behalf of their investors, less compensation than they would otherwise demand. Such bribery is

likely because compensation schemes are not verifiable outcomes, which means that investors

cannot hold mutual-fund managers accountable for whatever compensation is finally offered.

Discussions with managers at two leading investment banks in China, Mr. Zhichao Fang of CITIC

Securities and Mr. Feihu Long of Guosen Securities, confirmed that such side-payments do occur.

Therefore, if ownership concentration among tradable shares is due to mutual funds holding large

blocks of shares, then high concentration may result in low compensation ratios, since it is quite easy

for mutual-fund managers to be bribed by non-tradable shareholders. Accordingly, we predict:

Hypothesis 3b: The more concentrated ownership among tradable shareholders is, the lower the compensation ratio.

Normative Isomorphism

For publicly-traded firms in China, as in many other countries, one of the most salient

sources of professional norms is investment banks, which counsel corporations about offerings of

equity and debt, mergers and acquisitions, joint ventures, etc., and which manage complex financial

transactions. Investment banks are likely to exert strong pressure on Chinese firms because

investment bankers have more experience with market economies than do Chinese managers. For

their part, investment bankers look to their own past experience to determine what works well.

Therefore, investment banks are likely to advise Chinese firms to set compensation ratios close to

the values set by their previous clients, and Chinese firms are likely to accept this advice.

Accordingly, we predict:

Hypothesis 4a: The higher the mean compensation ratio set by other firms that used the same investment bank, the higher the compensation ratio set by the focal firm.

Any relationship we find between the focal firm’s compensation ratio and the compensation

ratios set by the other clients of its investment bank might be due to spurious causation (Haunschild,

22

1994). Some unobserved factor may influence all investment banks or all Chinese firms; for

instance, there may be some generalized understanding of appropriate behavior that is shared by all

Chinese firms, including those served by other investment banks. Such a generalized norm may be

due to the fact that in addition to looking at its own past experience, each investment bank looks at

the actions other investment banks, especially the most prestigious. Interviews with investment

bankers in China confirmed this tendency: they stated that they usually read reports from top

investment banks, such as the China International Capital Corporation (CICC), a joint venture

between the China Construction Bank and Morgan Stanley, and from some foreign investment

banks, but they rarely paid attention to what the smaller and less-prestigious investment banks did.

The actions of other investment banks are likely to be salient normative forces because most

of the investment banks advising Chinese firms on ownership reform are small. Some prestigious

investment banks advised only a handful of firms; for example, CICC advised four firms. Interviews

with Chinese investment bankers revealed that income from this activity is quite small, especially in

later stages of this reform, when many small investment banks obtained permission from the CSRC

to participate in this reform. One person we interviewed, who wished to remain anonymous, said:

In the very beginning, when only a handful of investment banks were allowed to advise the firms on setting a proper compensation plan, typically an investment bank would earn 4,000,000 RMB. But when more securities firms got licenses to participate in this reform, consulting frees dropped sharply, in some cases to 400,000 RMB, which barely covers banks’ consulting costs. Faced with this situation, many top investment banks withdrew from this market, leaving a lot of unknown securities firms… Some prestigious investment banks, like _______, participated not for the current small profit; instead, they did so because they wanted to maintain their relationships with publicly-traded firms.

Small investment banks, who have shallower pools of talent and less experience than large

investment banks, face great uncertainty about what compensation is appropriate. This uncertainty

prompts them to imitate what other investment banks do to avoid an awkward situation: they don’t

know how to help their clients. For this reason, we propose:

Hypothesis 4b: The higher the mean compensation ratio set by set by other investment banks for their client firms, the higher the compensation ratio set by the focal firm.

23

When we consider agency problems that may crop up with investment banks, our

expectations change dramatically. Investment banks often act as the agents of managers, not as

agents of owners, because it is managers, not owners, who are responsible for hiring them. As

explained above, many Chinese investment banks are quite small – indeed, much smaller than the

firms they are hired to advise, especially in the third reform wave. This reduces the likelihood that

investment banks exert much normative influence on executives. Instead, executives may exert

considerable influence on investment banks, pushing banks to suggest compensation schemes that

match executives’ preferences. In other words, investment banks may not be normative influences:

they may be “beards” for CEO preferences. This possibility is supported by a banker in a small

Chinese investment bank, who wishes to remain anonymous:

Ours is not a big investment bank, as you may know. Our main task is to communicate between the firm (the CEO) and the non-tradable shareholders. When we actually made a presentation about what compensation ratio the firm should set, it turned out we were shadows of the firm. You must know “Shuanghuang” show? 8 Then you see what I mean, right? Those CEOs really think that they can manage everything by themselves and that they are the real controllers of their firms who can decide on everything… Why do they hire us? Oh, do you think the tradable shareholders would believe that compensation ratio is fair and acceptable if they are told that the CEO sets it? After all, we’re called financial intermediaries.

This indicates that investment banks may play limited roles in determining compensation schemes,

other than by facilitating communication between the two ownership groups. We expect that

agency problems may eliminate any normative influence of investment banks. Thus we propose:

Hypothesis 4c: Net of the effect of ownership structure, there will be no effect of investment banks on the focal firm’s compensation ratio.

Mimetic Isomorphism

Indiscriminant imitation: everyone is a target. For publicly-traded Chinese firms, ownership

reform was a very uncertain proposition because, as explained above, several earlier reforms failed

8 Shuanghuang is a traditional Chinese show in which one player stands before the audience on the stage and another player hides behind the stage. The audience perceives that the first player is “talking,” but actually the second player is. The first player is just moving his mouth to make audience think he is doing the talking.

24

and the rights of tradable shareholders were recent social inventions. Faced with great uncertainty,

firms contemplating ownership reform will look for clues about what to do in the actions of other

firms that have gone through this reform (DiMaggio and Powell, 1983). Thus we propose:

Hypothesis 5a: The higher the mean compensation ratio set by other firms that previously reformed their ownership, the higher the compensation ratio set by the focal firm.

Targeted imitation of role-equivalent and cohesive firms. A careful reading of DiMaggio and Powell

(1983: 148) reveals that imitation in the face of uncertainty is not indiscriminant; instead, it will be

seen primarily within sets of organizations that play similar roles or that are tied directly to each

other. We consider both imitation targets in turn. Firms attend to the actions of other firms in their

industry because they are role equivalents, which means that firms in the same industry are involved

in similar types of exchange relations, although not necessarily with the exact same exchange

partners (Winship and Mandel, 1983; Winship, 1988). Strategic decisionmaking uses cognitive

categories that executives construct as they label and make sense of the competitive environment

(Daft and Weick, 1984; Porac and Thomas, 1990). Executives attend to the actions of organizations

in their own industry more than other industries because the segregating mechanisms (Hannan and

Freeman, 1989: 45-65) that create and maintain industry boundaries also serve to focus their

attention. Moreover, organizations in the same category as the focal organization, such as those in

the same industry, will be viewed as more important competitors than organizations outside this

category; therefore, firms in the same industry will be monitored more closely than firms in other

industries (Porac and Thomas, 1990: 232-234). Thus, competitive boundaries and competitive

scanning are narrowly focused by industry. For these reasons we predict:

Hypothesis 5b: The higher the mean compensation ratio set by firms in the same industry that previously reformed their ownership, the higher the compensation ratio set by the focal firm.

Industry is not the only boundary salient to decision-making attention; location also matters.

Executives can more easily observe the actions of nearby organizations than those of far-away

organizations. Region is especially relevant when we study firms in China, which covers a vast

25

terrain – a landmass that is 2% larger than the U.S., with mountains that fence regions off from one

another. This rugged terrain has long engendered strong regional cultures and hampered the

creation of a national culture. To the extent that executives’ cognitive strategic maps are congruent

with regional boundaries, they will tend to downplay, even ignore, the actions of organizations in

other regions, and will tend to focus only on the actions of organizations in the same region. For

this reason, we expect:

Hypothesis 5c: The higher the mean compensation ratio set by firms in the same province that previously reformed their ownership, the higher the compensation ratio set by the focal firm.

Now consider imitation of organizations that are directly connected to the focal firm.

Director interlocks are important sources of information for Chinese firms, just as they are for

western ones (Useem, 1984; Haunschild, 1994). Expensive decisions like what compensation to

offer ordinary shareholders during ownership reform are discussed at board meetings. According to

CSRC guidelines, non-tradable shareholders entrust boards of directors to oversee reform, for

instance by hiring investment banks as professional advisors. Board of directors typically discuss all

issues related to ownership reform, including what compensation ratio should be offered tradable

shareholders. Conversations with directors of other firms that have succeeded at this complex and

uncertain reform will offer directors vivid examples that are likely to influence their own decisions

and actions. Indeed, such vivid, case-based information is more influential than pallid, abstract

statistics (Nisbett and Ross, 1980). Therefore, we predict that the compensation ratios previously

set by firms with which the focal firm is interlocked will influence decision makers in the focal firm:

Hypothesis 5d: The higher the mean compensation ratio set by firms with which the focal firm is interlocked, the higher the compensation ratio set by the focal firm.

The influence of peer-group organizations and interlock partners may be more intense in

situations of great uncertainty (DiMaggio and Powell, 1983; Haunschild, 1994). When faced with

uncertainty, organizations economize on search costs (Cyert and March, 1963 [1992]) and imitate the

actions of other organizations, substituting institutional rules for technical ones (Meyer, Scott, and

Deal, 1983). When there is uncertainty about what to do, decision makers should be more likely to

26

attend to information gained from salient others, such as other firms in the same industry, the same

region, and those with which they are interlocked. Accordingly, we propose:

Hypothesis 5e: The impact of imitation targets will be stronger when uncertainty is greater.

Considering agency issues does not change any of our predictions about mimetic

isomorphism. Instead, it merely changes our interpretation of any findings of mimetic isomorphism.

Specifically, incorporating ideas about agency problems leads us to presume that executives, non-

tradable shareholders, and tradable shareholders alike all justify their preferences for low or high

levels of compensation by using salient role models.

Research Design

To test the hypotheses developed above, we gathered and analyzed data on all conversion

plans developed by publicly-traded Chinese firms between June 12, 2005, when the first successful

conversion plan was announced, and July 18, 2007. Our unit of analysis is the firm.

Data and Measures

Our main sources of data are the Guo Tai An Information Technology Company (GTA,

also called CSMAR) and Wind Information Corporation. GTA is a for-profit enterprise based in

Hong Kong that has developed databases on the Chinese banking industry, stock market, and

economy for international academic and industry researchers. Wind is a Shanghai-based provider of

financial data used by most investment banks in China. Because these two companies provide

similar information about publicly-traded firms in China, we were able to cross-check their databases

for consistency and completeness, which is always a concern when dealing with data on China. The

GTA Ownership Restructuring database covers the period up to the end of 2006, while the WIND

database covers the period up to July 18, 2007. Our reading of detailed ownership reform plans of

over 400 firms indicates that Wind provides a more precise record of compensation ratios than

GTA. Also, GTA records only those non-tradable shareholders who own 5% or more of a firm’s

27

stock, while Wind provides data on all non-tradable shareholders. Accordingly, we gathered data on

compensation ratios, details of reform plans, the reform’s completion date (if successful), director

names, investment bank names, ownership of all non-tradable shareholders, province, and industry

from Wind; we gathered data on assets, financial performance, beta, and the ownership stakes of the

ten largest tradable shareholders from GTA.

Measuring the dependent variable. Our dependent variable is the compensation ratio, the ratio of

shares granted to shares held before ownership reform. For instance, if an investor held ten shares

of tradable stock and received three shares of tradable stock, the compensation ratio would be 3:10,

or 0.30. A few plans (5% of the 87%) also included grants of cash; for these, we translated cash into

shares using the closing stock price the day before the reform plan was announced.

Measuring independent variables. We created a binary indicator to measure coercion due to state

ownership, specifically, whether the firm under study is controlled by the state or the private sector.

This variable was set equal to one when the controlling shareholder listed in the firm’s annual

shareholders’ report was a government entity and zero otherwise. Starting in 2004, each listed firm

is required to disclosure its ultimate controlling shareholder in its annual report. We downloaded

annual reports filed the year before each firm undertook ownership reform from the Shanghai and

Shenzhen Stock Exchange websites (www.sse.com.cn and www.szse.com.cn).

Dummy variables are rather crude indicators of differences between firms. To compensate

for this limitation, we created a second, more nuanced, measure of state control: the percentage of

non-tradable shares that are owned by the state, either as state shares [guojia gu] or as state-owned

legal-person shares [faren gu].

Next, we assessed cohesion among non-tradable shareholders. We measured the concentration of

ownership of non-tradable shares using the Hirschman-Herfindahl index:

( )∑=

=n

iimm yNT ionConcentrat

1

2 ,

28

where yim is the fraction of the non-tradable shares in firm m owned by the ith holder of non-tradable

shares. When this index is high, ownership of non-tradable shares is concentrated; when this index

is low, ownership of non-tradable shares is dispersed.

For coercive pressure due to the bargaining power of tradable shareholders, we again used the

Hirschman-Herfindahl index, this time to measure concentration among the top ten tradable

shareholders:

( )∑=

=n

iimm yT ionConcentrat

1

2 ,

where yim now represents the fraction of the tradable shares in firm m held by the ith tradable

shareholder. As before, when this index is high, ownership is concentrated; when it is low,

ownership is dispersed.

To measure normative isomorphic pressures from investment banks we used the mean

compensation ratio set by other Chinese firms that were advised by the same investment bank and the

mean compensation ratio set the by clients of other investment banks. Note that the only client firms

whose compensation ratios were included in these measures were those that finished reforming their

ownership structures before the focal firm began to reform its own. To be sensitive to the fact that

the actions of top-ranked investment banks matter more than the actions of other investment banks,

we weighted data for investment banks ranked higher than the focal firm at 0.7 and weighted data

for lower-ranked banks at 0.3. We took investment-bank rankings from the Securities Association

of China (www.sac.net.cn). We used the 2006 rankings, which were based on net profits per worker,

and which captures investment banks’ operating efficiency and creative ability. Because rankings do

not change much from year to year, a static measure for 2006 is reasonably accurate.

Most previous studies of mimetic isomorphism have focused on the diffusion of particular types

of practices or structures; for instance, the spread of civil-service reform among American cities

(Tolbert and Zucker, 1983) or the adoption of the multidivisional structure by large American

corporations (Fligstein, 1985). Because the outcomes under study were binary (0,1) variables,

previous studies have counted the number of organizations within some reference group that

29

previously adopted the practice or structure in question. But our dependent variable, the ratio of

new share grants to outstanding shares, is continuous. A firm contemplating ownership reform can

set its compensation ratio at an infinite number of levels: 0.301, 0.3011, 0.30111, etc. Given the

nature of our dependent variable, we took a different approach and measured the mean

compensation ratio set by firms in a reference group. The mean of any distribution captures its

central tendency, what the “typical” firm in the reference group did.

We considered four different reference groups. First, we assessed untargeted mimesis by

including in the reference group all firms that had previously set compensation ratios. Second, we

restricted the reference group to firms in the same industry as the focal firm, and then to firms

headquartered in the same province as the focal firm, thereby capturing mimesis through role

equivalence. Finally, we restricted the reference group to the set of firms with which the focal firm

is interlocked, thereby capturing mimesis through cohesion. The first firm in each reference group to

undertake ownership reform – or the first group of firms, if multiple firms announced ownership

reform on the same day – has no reference group. Those pioneering firms drop out of our analysis

when we include the reference-group variables. Because some firms have no director interlocks,

they drop out of the analysis when we include the director-interlock reference-group variable.

Measuring the moderator: uncertainty. Recall that we expect uncertainty to accentuate the effect

of several independent variables. Uncertainty derives from the actions of other firms whose actions

are relevant to the firm under study, so we used the standard deviation of the compensation ratio

within the four reference groups, which measures within-group disagreement. The greater the

standard deviation, the greater the disagreement, and therefore the greater the uncertainty around

what is “right” or “normal” with regard to ownership reform.9 These measures are specific to each

9 Another potential measure of uncertainty is a time clock. As time passes and more firms reform their ownership structures, uncertainty diminishes because firms learn from each other’s successes and failures. But this measure is unsuitable because the timing of ownership reform was correlated with the complexity of ownership structure (firms that issued B or H or N shares, as well as A shares, reformed ownership later than firms that issued only A shares) and financial performance (troubled firms were the laggards in the reform process).

30

firm: all reference groups were based on firms that had already reformed their ownership structures,

which depended on the timing of the focal firm’s ownership reform, its industry, and its location.

We created interaction terms by multiplying uncertainty and the reference-group average.

Such interaction terms are often highly correlated with their components. High correlations

between variables in regression models cause multicollinearity, which can cause computational errors

when using standard statistical software (Jaccard, Turrisi, and Wan, 1990). Moreover, coefficients

on collinear variables are poorly estimated, so small measurement or sampling errors can have large

effects on coefficients. To avoid these problems, we subtracted both factors in an interaction from

their sample means before multiplying them together to create a mean-centered interaction (see

Cohen, 1978; Cronbach, 1987).

Measuring control variables. Our statistical models include for several factors that are not of

central interest to us, but that nonetheless might influence compensation ratios. First, we controlled

for firm size, in terms of market value, measured just before reform began. The shares of large firms

are more likely to trade often and in large quantities in the domestic exchanges than the shares of

small firms. Therefore, tradable shareholders in large firms will be less affected by the sale of

formerly non-tradable shares on the domestic exchanges than will tradable shareholders in small

firms (cf. Field and Hanka, 2001; Brav and Gompers, 2003). Therefore, tradable shareholders in

large firms are likely to demand less compensation for ownership reform than tradable shareholders

in small firms.

We also controlled for the focal firm’s overall stock-price performance, using the mean return

on the stock over the twelve months before ownership reform began. The higher the stock return,

the more tradable shareholders have already benefitted from the run-up in the stock price and the

less potential there is for future increases in stock price. So the higher the stock return, the less

incentive non-tradable shareholders have to initiate ownership reform, and the less compensation

they are likely to offer to tradable shareholders. We gathered data on stock returns from Sinofin, a

database created by the Center for China Economy Research at Peking University, which offered a

31

more convenient way to gather daily stock-return data than GTA. This widely used financial-market

database is devised to conform to the standards of the well-known database from the University of

Chicago’s Center for Research in Securities Prices.

We controlled for three variables that finance theory (Kahl et al., 2003; Wu and Wang, 2005)

predicts will affect compensation ratios. First, we controlled for stock-price volatility using the standard

deviation of the focal firm’s stock prices over the twelve-month period before that firm’s

ownership-reform process began.10 For this measure, the year under study was idiosyncratic to each

firm and was determined by the date on which the firm undertook ownership reform. The more

volatile stock returns are, the lower the implied value of non-tradable shares is (controlling, of

course, for the level of past stock returns) and the more removing trading restrictions increases their

value. The more volatile stock returns are and the larger potential windfalls for non-tradable

shareholders are, the more compensation they are willing to offer tradable shareholders. Our

second financial control is the beta of the asset-pricing model. We measured beta over the twelve

months before the focal firm’s ownership-reform process began. By a similar logic to that used

above, the higher beta is, the higher the implied value of non-tradable shares is, and the less their

holders benefit from lifting trading restrictions; therefore, the less they will compensate tradable

shareholders. Our third financial control is the ratio of non-tradable to tradable shares, which was

measured on the day before the focal firm’s ownership-reform process began. The higher the ratio

of non-tradable to tradable shares, the more removing trading restrictions will flood the market and

the more tradable shareholders can expect to suffer losses. The higher the ratio of non-tradable to

tradable shares, therefore, the more non-tradable shareholders must compensate tradable

shareholders to get the latter group to agree to the proposed reform.

10 Some firms in our analysis were recently listed and so lacked a full year’s track record; others were long-established but illiquid in that their stocks did not trade at all in the year before they undertook ownership reform. For both categories of firms, we lack the data needed to calculate stock-price volatility and beta. These firms dropped out of the analysis whenever we included these variables as regressors.

32

Methods of Analysis

Our data are cross-sectional and our dependent variable is continuous, so we estimate linear

regression models. These firms vary greatly in size and financial performance, so we correct for

heteroskedasticity.

Results

Table 1 presents descriptive statistics on all variables used in our analysis.

[Table 1 about here]

Table 2 presents the results of our multivariate analysis. Models are built step-wise, by

adding one variable at a time to a baseline model that contains control variables. This table is split

into two parts: Table 2a contains Models 1 to 7; Table 2b, models 8 to 12.

[Tables 2a and 2b about here]

Control variables. Model 1 shows that three control variables have the expected effects. Firms

with larger market capitalization levels and firms with better financial performance (as measured by

returns to stock price) set lower compensation ratios than smaller and poorer-performing firms,

while firms with higher ratios of non-tradable to tradable shares set higher compensation ratios.

The two other controls do not behave as predicted by finance theory. Stock-price volatility has the

expected positive effect, but this effect is generally non-significant. The effect beta is unexpectedly

positive, but generally not statistically significant. These results indicate that finance theory doesn’t

do a very good job of explaining the behavior of Chinese publicly-traded firms. This is not entirely

surprising, as it is much more difficult for tradable shareholders to understand and act on complex

asset-pricing models than it is for investors in Western economies. Western investors have a well-

developed appreciation of investment banks’ expertise and economic models of supply and demand,

but Chinese investors do not. The directors of Chinese firms cannot simply write letters to their

tradable shareholders and suggest that the compensation ratios they are being offered are “fair”

because they are based on the advice of investment banks that rigorously used asset-pricing models.

33

Model 2 adds the dummy variable indicating whether the firm is ultimately controlled by the

state. The coefficient is positive and statistically significant, which supports hypothesis 1b and fails

to support hypothesis 1a. Model 3 substitutes the more-nuanced measure of state control, the

percentage of shares owned by state shareholders. Again, we see a positive and statistically

significant effect, which again supports hypothesis 1b and fails to support hypothesis 1a. Together,

these results indicate that problems within the organizations that act as agents for state owners – the

central and local SASACs – attenuate the ability of state owners to coerce the managers of publicly-

traded firms to act in the state’s interests and against the interests of tradable shareholders. Model 4

includes both state-coercion proxies together. These variables are highly correlated (r=.60), so it is

not surprising that the effect of the dummy (the coarser measure) is rendered non-significant.

Model 5 drops the now-non-significant state-control dummy and adds ownership

concentration among non-tradable shares. The coefficient on this variable is negative and

statistically significant. This result supports hypothesis 2a and fails to support hypothesis 2b. It

indicates that the more ownership is concentrated among a few state agencies, the more bargaining

power state owners have vis-à-vis tradable shareholders.

Model 6 adds ownership concentration among tradable shares, to assess the coercive power

of that ownership group. We see a negative and statistically significant effect, which supports

hypothesis 3b and fails to support hypothesis 3a. This indicates severe agency problems among

tradable shareholders, most likely due to mutual-fund managers. Recall that ownership

concentration among tradable shares is often due to the fact that mutual funds own large stakes. If

so, then high concentration results in low compensation ratios because mutual-fund managers are

offered side payments (bribes) by non-tradable shareholders to do their bidding, rather than the

bidding of mutual-fund investors.

Model 7 tests for normative isomorphic pressures from investment banks by adding the

mean compensation ratio set by other firms advised by the same investment bank as the focal firm,

and the mean compensation ratio set by firms advised by other investment banks. The effects of

34

both variables are positive and statistically significant. These results support hypotheses 4a and 4b,

and fail to support hypothesis 4c. Taken together, these results suggest that when investment banks

advise Chinese firms, they look at both their own prior practices and at the practices of other

investment banks, especially more prestigious ones. (Recall that we gave banks ranked higher than

the focal firm a weight of 0.7 and banks ranked lower than the focal firm a weight of 0.3.) This

result is not surprising, given that many investment banks advising Chinese firms are small and

inexperienced.

Models 8 through 12, which are shown in Table 2b, add variables to capture the effects of

reference groups that might serve as bases for imitation: all firms that have previously undergone

ownership reform, firms in the same industry as the focal firm, firms in the same province as the

focal firm, and firms interlocked with the focal firm. In Model 8, the parameter estimates on three

groups (all firms, firms in the same industry, and firms in the same province) are statistically

significant (using one-tailed t tests, which is appropriate for directional hypotheses). The estimate

on the fourth group (interlocked firms) is non-significant. These results support hypotheses 5a

through 5c and fail to support hypothesis 5d. We conclude that Chinese firms attend to the actions

of all firms, as well as the actions of firms in their industry and region; however, after taking into

account these imitation targets, Chinese firms do not attend to the actions of interlock partners. In

other words, untargeted imitation and imitation of role-equivalent organizations trump imitation of

directly tied organizations. Note that the coefficient on the reference group encompassing all firms

is much larger than the coefficients on the more-restricted reference groups: eight times as large as

the same-industry effect and five times as large as the same-province effect.

The coefficients on the variables capturing the normative influence of investment banks

become close to zero and non-significant. This suggests that for Chinese firms, the power of role

models trumped any normative power that investment banks may have had. This conclusion is

bolstered by interviews with Chinese investment bankers, who told us that when they present

research in the course of advising Chinese managers about ownership reform, the most common

35

index of “reasonable” behavior they use is the average compensation ratio set by other firms that

have undergone ownership reform. For example, an internal consulting report written by the

prominent investment bank CICC highlights the average compensation ratio set by other firms.

Model 9 drops the normative variables and the interlock reference group. In this model, the

effect of the unrestricted reference group, of firms in the same industry, and of firms in the same

province are all significant using two-tailed tests, while the effect of interlock partners remains non-

significant.

Models 10 through 12 test for the moderating effect of uncertainty, using the three reference

groups that had significant main effects in Models 8 and 9. In all three models, the main effects of

the reference groups remain positive and statistically significant, the main effect of uncertainty

(which is measured relative to each reference group) is negative and statistically significant, and the

interaction effects are positive and statistically significant. These results support hypothesis 5e. In

results not shown here to save space, we estimated a similar model for the interlock reference group

and found a non-significant interaction, which fails to support hypothesis 5e. In other results not

shown here to save space, we included all three interaction effects in one model. Alas, high

correlations rendered many coefficients non-significant.

Robustness checks. We conducted several ancillary analyses to assess the robustness of these

results. First, we used an alternative measure of financial performance – earnings per share instead

of the stock return. Second, we used the natural logarithm of size. Third, we measured size using

assets instead of market capitalization. In all three alternative analyses, the results were very similar

to those shown here. Fourth, we experimented with other weights for high- and low-ranked

investment banks, which we originally weighted at 0.70 and 0.30, respectively. Our results are robust

to weights of 0.8:0.2 and 0.6:0.4. Fifth, we checked whether our results were driven by a few

extreme observations by deleting observations on firms whose compensation ratio was outside the

[5%, 95%] interval. Our results are robust to this trimming of the sample, which is to be expected,

as deleting a few extreme observations only makes the compensation ratios more similar than before.

36

A total of 75 firms (7%) have only one non-tradable shareholder, which means their non-

tradable share concentration index was 1.0. When we dropped these unusual firms from the sample,

all variables, including the concentration of non-tradable shares, had the effects of approximately the

same magnitude with approximately the same level of statistical significance.

One of our control variables – the ratio of non-tradable to tradable shares – is highly

skewed, with a mean of 2.17 and a small number of very, very large values (maximum 27.5). We

investigated the sensitivity of our results to outliers by dropping all 59 firms where this variable was

one standard deviation above the mean (4.23). In this subset of observations, all variables had

effects in the same direction and with the similar values and significance levels. The effect of the

ratio of non-tradable to tradable shares was much larger than in the results shown here, which

demonstrates that including the outliers obscured the true power of this factor.

The impact of other firms’ behavior: Coercion, norms, or mimesis? So far, we have assumed that

coercive pressure comes from owners, normative pressure comes from professional advisors, and

mimetic influences are instantiated in reference groups. But Mizruchi and Fein (1999) argued that

coercive and normative pressures can also come from reference groups. As they explained, research

that uses a binary dependent variable, which includes almost all research on mimesis, cannot

distinguish among imitation of, coercion from, or norms from reference groups. Because we have a

continuous dependent variable, we can draw this distinction. If Chinese firms were coerced by their

peers or if they viewed the behavior of their peers as a culturally valued norm, we would expect

them to set compensation ratios at least as high as, if not higher than, their peers’ average. After all,

if a firm tried to set its compensation ratio lower than its peers’ average and if the holders of

tradable shares noticed, they might refuse the proposed offer, which could be interpreted as coercive

or normative. In the aggregate, if Chinese firms are coerced by their peers’ behavior or if they

valorize that behavior, the distribution of compensation ratios should be centered on some point

above the average of the salient reference group. But if Chinese firms simply imitated the behavior

of other firms because they didn’t know what else to do, if they didn’t valorize that behavior and

37

didn’t feel pressure to conform to it, we would expect them to set compensation ratios neither

consistently higher nor lower than their peers’ average, but rather about the same. Such behavior

would, in the aggregate, yield a distribution centered on the average of the salient reference group.

To test predictions about coercion by or imitation of reference groups, we performed

Wilcoxon rank tests on a simple statistic: the compensation ratio set by the focal firm minus the

mean compensation ratio of its reference group. We focused on the three reference groups that had

significant effects on compensation ratios in Model 13 of Table 2b. Table 3 shows the results of this

analysis. For all three reference groups, the compensation ratio set by the focal firm is more likely to

be lower than the group mean that it is to be higher than the group mean. These results fail to

support the interpretation of similarity of behavior as being coerced or normative. Based on this

analysis, we conclude that firms are not coerced by their peers, nor do they interpret their peers’

behavior as instantiating cultural values; instead, they imitate them as a way out of great uncertainty.

[Table 3 about here]

To continue probing the issue of coercion or norms vs. imitation, we conducted a

multivariate analysis of the variable analyzed in Table 3, the difference between the focal firm’s

compensation ratio and its reference group’s average compensation ratio, to investigate how the

bargaining power of different shareholders affects whether the focal firm’s compensation ratio is

above or below its reference-group mean. We are specifically concerned with testing two

predictions that were supported in our original analysis, shown in Table 2a. Extending the logic

behind hypothesis 1b, we expect that because the agents of state owners (SASAC employees)

monitor many firms while non-state owners concentrate on one or a few firms, because non-state

owners are more competent to monitor the firms they own than state owners, and because the

interests of SASAC employees are not aligned with those of the state, firms controlled by state

owners should set higher compensation ratios, relative to their peers, than firms controlled by non-

state owners. Extending the logic of hypothesis 3b, we expect that because concentration of

ownership of tradable shares is often due to mutual funds owning large stakes, and because non-

38

tradable shareholders can make side-payments to mutual-fund managers to persuade them to accept

less compensation than they would otherwise demand, then the more concentrated ownership is, the

more likely it is that firms set compensation ratios lower than their peer groups.

The results of this ancillary analysis are shown in Table 4, which examines the three peer

groups that had significant effect on compensation ratios in Model 14 of Table 2b. The results are

consistent across the three specifications. Better-performing firms (those with larger market

capitalization and stock-price returns) set lower compensation ratios than their peers in all three

groups, which suggests that better-performing firms can resist peer pressure. In addition, firms with

higher fractions of non-tradable shares, which are more likely to see demand for tradable shares

swamped by excess supply if reform passes, set higher compensation ratios than their peers. Firms

with more state ownership set compensation ratios higher than their peers, which supports the

extension of hypothesis 1b. Concentrated ownership tradable shares reduces compensation ratios

relative to peers, which supports the extension of hypothesis 3b.

[Table 4 about here]

Discussion and Conclusion

In this paper, we explained a curious empirical regularity: publicly-traded Chinese firms

undergoing ownership reform tended to compensate their tradable shareholders in the same way

(with new grants of shares) and at about the same level (three new shares for every ten existing

shares). As expected, we found that the state is a powerful coercive force. But we also discovered

that the behavior of other firms – role models – have strong effects. Moreover, we found that

predictions based on analysis that ignored issues of agency were incorrect; only when we took the

interests of principals (both kinds of owners, state and non-state) and many different agents

(employees of the SASACs that oversee publicly-traded firms, managers of the publicly-traded firms

themselves, employees of the non-state holders of non-tradable shares, and managers of the mutual

funds that hold many tradable shares) were we able to explain Chinese firms’ compensation ratios.

39

Finally, because our analysis focused on a continuous (rather than discrete) outcome, we were able

to clearly separate mimetic effects from coercive and normative ones (cf. Mizruchi and Fein, 1999).

Coercive effects. Although the Chinese state (specifically, the CSRC) coerced firms into

undertaking ownership reform, it did not force them to compensate tradable shareholders for their

expected losses, and did it not force them to set compensation at any particular level. Instead, the

CSRC pushed each firm to determine, by negotiation between non-tradable and tradable

shareholders, an outcome that was appropriate for its own circumstances. Coercion by the state did

operate through an internal, firm-specific channel: through state ownership of non-tradable shares,

which constituted over two-thirds of shares in publicly-traded Chinese firms. But this coercion took

an unexpected turn, due to agency problems within state owners. Specifically, when the state owned

a large fraction of shares, compensation ratios were high, which indicates that state owners of non-

tradable shares are less able than non-state owners to monitor managers to make sure they act in the

interests of non-tradable shareholders.

One concern is that coercion may work through channels other than state ownership; for

example, through pressure on investment banks to advise their clients to act in ways that conform to

state preferences. But we showed that the effects of investment banks disappeared after we took into

account the impact of imitation targets, possibly due to agency problems with investment banks

(they are beholden to the executives who hire them rather than to shareholders). So even if

investment banks are a channel of state coercion, our results indicate this channel is not powerful.

Finally, state officials on corporate boards may be an alternative channel of coercive

influence, one that is not taken into consideration in our analysis. State officials sit on corporate

boards in China for two main reasons: either the central, provincial, or local government controls a

firm, usually by being its largest shareholder, or a firm controlled by individuals or non-state

corporations brings state officials onto its board in order to form a political connection, as insurance

against unexpected political shocks or other state intervention (Calomiris, Fisman, and Wang, 2008).

To the extent that state ownership is highly correlated with the appearance of state officials on the

40

board, our measure of state ownership captures this channel of state influence. Alternatively, the

presence of state officials on corporate boards may not reflect pressure from the state, but rather

firms’ attempts to manage their dependence on unpredictable state action by co-opting state officials

(Pfeffer, 1972).

Normative effects. We demonstrated that mimetic isomorphic effects overshadowed normative

ones. Evidence that Chinese firms followed the path taken by other firms advised by the same

investment bank was wiped out when we controlled for the actions of imitation targets. We also

described, with the limited information available to us, the evolution of the role played by

investment banks, which shows how actors, actions, and meanings changed over time.

Mimetic effects. We found evidence of three distinct imitation targets – all firms, firms in the

same industry as the focal firm, and firms in the same region as the focal firm. These findings

suggest that great uncertainty drove firms to imitate the actions of others, rather than to follow the

advice of investment banks. We found that imitation of all reference groups was more pronounced

when uncertainty was great.

While our integrated theoretical framework gives us a new angle to examine the social life

using augmented new institutional theory, and while our empirical results offers some useful hints

about how institutional isomorphism plays out among publicly-traded Chinese firms, we are also left

with several new puzzles and problems. Theoretically, we have a lot of work to do to fully integrate

agency theory into institutional analysis. Empirically, the complex ownership structure of Chinese

firms – cross-shareholding and multiple-layer business groups – make it difficult to precisely

measure the influence of different interest groups: the state, non-state institutions, and individual

investors (Guthrie, et al., 2007). Untangling interests is a formidable task since detailed information

on holders of non-tradable shares of Chinese firms is simply not available.

41

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Figure 1: The Distribution of Compensation Ratios Set by Chinese Firms, May 2005 – July 2007

di

Note: This figure summarizes data from Wind Information on all 1,086 publicly-traded Chinese firms that reformed their ownership structure and compensated the holders of tradable shares with grants of new tradable shares between May 1, 2005 and July 18, 2007. This group constituted 87% of firms undertaking ownership reform. For plans that included cash compensation (5% of the 1,086), we translated cash into an equivalent number of shares using the closing stock price the day before the reform plan was announced. Each point represents one firm’s compensation ratio. For instance, the arrow points to the modal firm, whose compensation ratio was 0.306, meaning that holder of tradable shares were granted 3.06 shares for every 10 shares they held before reform.

47 Table 1: Descriptive Statistics

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Mean .300 .713 34.6 .600 .006 .317 .314 .318 .316 .315 .311 .069 2.85 -.0015 .022 1.03 2.18 Standard deviation .079 .453 26.8 .274 .030 .031 .030 .012 .032 .027 .049 .007 12.1 .0022 .048 .204 2.06 Minimum .020 0 0 .049 .000 .100 0 .300 .100 .200 .100 0 .272 -.06 .0075 .075 .268 Maximum .700 1 85.0 1.00 .786 .500 .375 .364 .474 .500 .594 .089 370 .011 .053 1.57 27.3 # observations 1086 1086 1086 1086 1086 1017 1086 1085 1014 1055 821 1086 1077 1077 1076 1086 10851 Compensation ratio 2 Controlling shareholder dummy .215 3 % State-owned shares .303 .642 4 Concentration[NT shares] .028 .028 .431 5 Concentration[T shares] -.105 .028 .026 .029 6 Mean CR[same IB] .055 -.022 .024 .133 .041 7 Mean CR[other IBs] .076 -.025 -.018 .035 .013 .083 8 Mean CR[all firms] .165 -.050 -.008 .121 -.022 .382 .417 9 Mean CR[same industry] .152 -.010 .007 .005 -.009 .135 .043 .304 10 Mean CR[same province] .152 -.022 -.031 .043 -.033 .171 .225 .398 .154 11 Mean CR[interlocked firms] .064 .027 .025 .057 -.041 .070 .110 .192 .142 .166 12 Uncertainty: Std Dev(CR[all firms]) -.175 -.043 -.087 -.178 .028 -.276 -.329 -.771 -.234 -.313 -.184 13 Market capitalization/109 -.007 .062 .105 .075 -.002 -.042 .018 -.009 -.090 .031 -.001 -.003 14 Mean stock-price return -.171 .040 .074 .095 .078 .105 .065 .193 -.055 .059 .060 -.201 .064 15 Stock price volatility .148 -.028 -.057 -.093 .066 -.055 -.028 -.060 .098 -.033 .030 .108 -.107 -.353 16 Beta .166 -.018 .016 -.042 -.047 .021 -.019 .038 .156 .037 .036 .012 .018 -.407 .575 17 # NT shares/# T shares .324 .110 .183 .056 -.023 .049 .019 .032 .005 .081 -.005 -.051 .432 .024 -.001 -.012

Note: This table is based on 1,086 observations on ownership reform plans by publicly-traded Chinese firms between June 2005, when the first plan was announced, and July 18, 2007. All of these plans offered compensation in the form of stock or stock plus cash. We converted cash grants into stock equivalents. Mean CR[ ] refers to the mean compensation ratio set by the reference group named in the square brackets. NT and T stand for non-tradable and tradable shares, respectively. To save space, we show only uncertainty based on all firms.

48

Table 2a: Linear Regression Analysis of Compensation Ratios

(1) (2) (3) (4) (5) (6) (7) Market capitalization/1012 -1.07*** -1.09*** -1.09*** -1.09*** -1.07*** -1.06*** -1.01*** (-5.26) (-4.97) (-4.83) (-4.84) (-4.7) (-4.72) (-4.64) Mean stock-price return -5.39** -5.45** -6.01*** -6.05*** -5.94*** -5.45** -8.12*** (-2.88) (-2.88) (-3.24) (-3.27) (-3.21) (-2.95) (-4.40) Stock price volatility .746 .932 1.23* 1.23* 1.13 1.35* .839 (1.24) (1.52) (2.03) (2.04) (1.89) (2.25) (1.46) Beta .031* .030* .022 .023 .021 .017 .022 (2.06) (1.96) (1.48) (1.45) (1.5) (1.19) (1.47) #NT shares/# T shares .015*** .014*** .013*** .013*** .013*** .013*** .013*** (6.06) (5.93) (5.69) (5.67) (5.66) (5.65) (5.51) Controlling shareholder dummy .023*** -.004 (4.20) (-.049) % State-owned shares/103 .637*** .679*** .741*** .745*** .847*** (7.35) (5.84) (7.30) (7.34) (8.05) Concentration[NT shares] -.021* -.021* -.026** (-2.40) (-2.36) (-2.88) Concentration[T shares] -.244*** -.237*** (-5.89) (-5.67) Mean CR[same IB] .218*** (3.25) Mean CR[other IBs] .412*** (3.38) # Observations 1075 1075 1075 1075 1075 1075 1008 R2 0.15 0.16 0.19 0.19 0.19 0.20 0.24

Notes: This table presents ordinary-least-squares regressions. Robust t-statistics are in parentheses below parameter estimates. * indicates p<.05, ** p<.01 and ***p<.001, two-tailed t tests. Coefficients on the constant are omitted to save space.

49 Table 2b: Linear Regression Analysis of Compensation Ratios

(8) (9) (10) (11) (12)Market capitalization/1012 -.911*** -.916*** -.997*** -1.04*** -1.04***

(-3.31) (-3.82) (-3.65) (-4.46) (-4.56)Mean stock-price return -10.82*** -10.47*** -9.67*** -6.86*** -7.27***

(-4.98) (-4.98) (-5.10) (-3.61) (-3.89)Stock price volatility 1.22 1.03 1.40* 1.30* 1.12*

(1.82) (1.59) (2.37) (2.14) (1.96)Beta .015 .010 .007 .011 .019

(0.86) (1.11) (0.49) (0.70) (1.27)#NT shares/# T shares .012*** .012*** .013*** .012*** .013***

(4.90) (4.96) (5.40) (5.44) (5.44)% State-owned shares/103 1.08*** .961*** .789*** .818*** .813***

(8.84) (6.48) (6.83) (6.16) (6.26)Concentration[NT shares] -.037*** -.037*** -.032*** -.026** -.026**

(-3.53) (-3.58) (-3.67) (-2.74) (-2.84)Concentration[T shares] -.206*** -.204*** -.216*** -.232*** -.218***

(-.564) (-5.85) (-5.27) (-6.58) (-5.42)Mean CR[same investment bank] -.061

(-0.52)Mean CR[other investment banks] .049

(0.28)Mean CR[all firms] 1.59*** 1.50*** 1.27***

(3.64) (4.83) (5.83)Mean CR[same industry] .185 .186* .382***

(1.92) (2.07) (4.71)Mean CR[same province] .308** .293* .465***

(2.60) (2.54) (5.26)Mean CR[interlocked firms] .028 .042

(0.57) (0.88) Uncertainty[reference group] -1.03* -.232** -.114

(-2.56) (-2.70) (-1.31)Mean CR[reference group]*Uncertainty[reference group] 71.5*** 4.80* 4.47*

(3.76) (2.19) (2.17)# Observations 764 789 1074 1005 1044R2 0.31 0.31 0.27 0.25 0.24

Notes: This table presents ordinary-least-squares regressions. Robust t-statistics are in parentheses below parameter estimates. * indicates p<.05, ** p<.01 and ***p<.001, two-tailed t tests. Coefficients on the constant are omitted to save space.

50

Table 3: Testing For Coercion:

The Difference Between the Focal Firm’s Compensation Ratio

and the Peer Group’s Average Compensation Ratio

(1) (2) (3)

Peer Group All Firms Firms in the Same Industry Firms in the Same Province

# Observations # Observations # Observations

Difference Positive 471 (43%) 451 (44%) 465 (44%)

Difference Negative 614 (57%) 559 (55%) 590 (56%)

Difference = 0 0 4 0

Total Sample Size 1,085 1,014 1,055

Wilcoxon Test

median difference = 0

vs.

median difference > 0

Pr(#positive ≥ 471) =

Binomial(n = 1085, x ≥ 471, p = 0.5) =

1.0000

Pr(#positive ≥ 451) =

Binomial(n = 1,014, x ≥ 451, p = 0.5) =

0.9997

Pr(#positive ≥ 465) =

Binomial(n = 1,055, x ≥ 465, p = 0.5) =

0.9999

Wilcoxon Test

median difference = 0

vs.

median difference < 0

Pr(#negative ≥ 614) =

Binomial(n = 1,085, x ≥ 614, p = 0.5) =

0.0000

Pr(#negative ≥ 559) =

Binomial(n = 1,010, x ≥ 559, p = 0.5) =

0.0004

Pr(#negative ≥ 590) =

Binomial(n = 1,055, x ≥ 590, p = 0.5) =

0.0001

Conclusion Focal-firm CR < Mean CR[all firms] Focal-firm CR < Mean CR[same industry] Focal-firm CR < Mean CR[same province]

51

Table 4: Linear Regression Analysis of the Difference

Between the Focal Firm’s Compensation Ratio and its Reference-Group Average Compensation Ratio

(1) (2) (3) All Firms Firms in the Same Industry Firms in the Same Province

Market capitalization/1012 -1.03*** -.789*** -.997*** (-4.25) (-3.29) (-4.45)

Mean stock-price return -7.73*** -6.91*** -8.34*** (-4.22) (-3.45) (-4.29)

Stock price volatility 1.27* 1.20 1.16* (2.17) (1.85) (2.02)

Beta .014 -.003 .017 (1.00) (-0.20) (1.14)

#NT shares/# T shares .013*** .012*** .012*** (5.56) (5.12) (5.26)

% State-owned shares/103 7.97*** .866*** .859*** (8.12) (8.03) (8.35)

Concentration[NT shares] -.027** -.026** -.030*** (-3.10) (-2.74) (3.34)

Concentration[T shares] -.230*** -.236*** -.216*** (-5.56) (-7.05) (-4.89)

# Observations 1074 1005 1044 R2 0.22 0.19 0.21

Notes: This table presents ordinary-least-squares regressions. Robust t-statistics are in parentheses below parameter estimates. * indicates p<.05, ** p<.01 and ***p<.001, two-tailed t tests. Coefficients on the constant are omitted to save space.