Journal of accounting, auditing finance tập 26, số 02, 2011 4

Auditing & Finance 264 623–640Ó The Authors 2011 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0148558X11409147 http://jaaf.sagepub.com Accounting Properties

Auditing & Finance 26(4) 623–640

Ó The Author(s) 2011 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0148558X11409147

http://jaaf.sagepub.com

Accounting Properties of

Chinese Family Firms

Abstract

We posit that family firms in China exhibit accounting properties consistent with the lence of Type II agency problems In contrast to the owners of non-family firms, theowners of family firms have more incentives to seek private benefits of control at theexpense of minority shareholders and provide lower-quality earnings for self-interested pur-poses The empirical evidence presented in this study suggests that the accounting earnings

preva-of listed Chinese family firms are less informative, and family firms employ less conservativeaccounting practices than their non-family counterparts We also find that Chinese familyfirms have higher discretionary accruals compared to non-family firms, which is consistentwith the view that family firms engage in more opportunistic reporting behavior Overall,our study suggests that family ownership in China is associated with lower earnings quality,which is in sharp contrast to the findings of prior studies that examine such ownership inthe U.S

Keyword

agency problems, accounting properties, family firms, China

This study examines the accounting properties of family firms in China The majority ofthe world’s firms can be classified as family firms to some extent (Claessens, Djankov, &Lang, 2000; La Porta, Lopez-de-Silanes, & Shleifer, 1999), and such firms thus play a criti-cal role in modern economies Recent studies examining the accounting properties offamily firms primarily focus on the United States and offer interesting results Wang(2006), for example, finds that founding family ownership is associated with more informa-tive earnings, more conservative reporting, and lower discretionary accruals Ali, Chen, andRadhakrishnan (2007) analyze the typical agency problems faced by family firms and find

Baozhi Qu, Skolkovo Institute for Emerging Market Studies, Unit 1608, North Star Times Tower, No 8

Beichendong Road, Chaoyang District, Beijing, China, 100101

Email: baozhi_qu@skolkovo.ru

that these firms report higher quality earnings These important articles shed light on howfamily ownership affects accounting properties and disclosure when Type I agency prob-lems, which arise from the separation of ownership and management and thus can be miti-gated by family ownership, dominate Type II agency problems, which stem from conflictsbetween controlling and noncontrolling shareholders.

Fan and Wong (2002) find listed firms in East Asia to be characterized by less tive accounting earnings This lack of high-quality information disclosure has been said to

informa-be responsible, at least in part, for the 1997 Asian financial crisis (Ho & Wong, 2001) Fanand Wong (2002) examine seven East Asian jurisdictions but exclude China However, webelieve that examining the interactions among institutional arrangements, family ownership,and accounting properties in China would offer important incremental insights The coun-try’s weak legal system makes it easier for controlling shareholders to expropriate minorityshareholders (the Type II agency problem), thus providing us with a good opportunity toinvestigate whether family firms tend to have different disclosure incentives and hence,exhibit different accounting properties, in an environment in which the Type II agencyproblem is more pervasive than it is in developed markets such as the United States

It is well recognized in the literature that Type II agency problems can lead to themanipulation of accounting earnings by family firms For example, Ali et al (2007) suggestthat a variety of incentives arising from these agency problems may lead family firms tomanipulate accounting earnings to facilitate private benefit-seeking behavior For instance,these firms may be motivated to manipulate earnings to ‘‘hide the adverse effect of arelated party transaction’’ (p 243) Ali et al further point out that family owners usuallyhave a high level of influence over the firm’s board and top management, which is cer-tainly the case in China Hence, they are able to manipulate earnings more easily shouldthey choose to do so Although legal institutions that are designed to protect the rights ofminority shareholders may help to mitigate the differences in Type II agency problemsbetween family and nonfamily firms, given that such institutions are either nonexistent orineffective in China (Allen, Qian, & Qian, 2005), family firms are expected to be subject

to more severe Type II agency problems and, accordingly, to have poorer earnings quality.Using a sample of all listed nonstate firms in China from 2003 to 2006, we first examinethe informativeness of accounting earnings and find the reported earnings of family firms

dependence model to test the relationship between family firms and the persistence of thetransitory loss components in earnings, which measures accounting conservatism Thefamily firms in our sample are found to use less conservative accounting practices thantheir nonfamily counterparts Finally, we examine the relationship between discretionaryaccruals and family firms and find these firms to have a higher level of such accruals Ourresults remain robust across different model specifications and to the inclusion of differentcontrol variables

The findings of this study make several contributions to the literature First, we ment the importance of Type II agency problems to financial reporting The effect ofagency conflicts on disclosure has been extensively investigated (see Healy & Palepu,

docu-2001, for a review), and recent studies have examined the impact of family ownership oncorporate disclosure (e.g., Ali et al., 2007; Chen, Chen, & Cheng, 2008; Wang, 2006).However, the aforementioned studies focus on the U.S market, which is characterized byType I agency problems (e.g., Ali et al., 2007) Our focus on Chinese family firms offers

us an opportunity to isolate a setting in which Type II agency problems dominate Ourinvestigation of the accounting properties of these firms thus provides insights that are

complementary to those of previous studies (e.g., Ali et al., 2007; Wang, 2006) examiningthe way in which agency conflicts affect accounting properties.

Second, an examination of family firms in China, where privatization took place onlyrecently and the founders of family firms still run their firms directly, enables us to sharpenour tests of the impact of family ownership on financial reporting and disclosure In con-trast to Chinese family firms, the majority of those in the United States are entrepreneurialfirms The founders of U.S family firms often hire professional managers When thesefounders retire, their families usually hold only ‘‘marginal ownership’’ (Burkart, Panunzi,

& Shleifer, 2003, p 2168) Prior studies that use samples of U.S family firms use eitherthe S&P 500 (e.g., Ali et al., 2007; Wang, 2006) or the S&P 1500 (e.g., Chen et al., 2008),which may raise concerns about the sample (Hutton, 2007) Recent studies have shown thatfindings involving family firms are ‘‘indeed sensitive’’ to the sample used (Miller, Breton-Miller, Lester, & Cannella, 2007, p 831); these authors have discovered that findingsbased on Fortune 1000 firm data simply cannot be replicated in randomly drawn samples

of smaller public companies By no means do we suggest that our study uses a noise-freesetting, but the early stages of both Chinese family firms and the Chinese stock marketmay offer a more powerful context for our tests

This study also differs from prior studies that examine ownership concentration inEast Asia (e.g., Fan & Wong, 2002) and earnings quality in China (e.g., Firth, Fung, &Rui, 2007), none of which investigates the difference between family and nonfamilyfirms Furthermore, Fan and Wong (2002) did not include China in their sample, and Firth

et al (2007) compare earnings quality between the country’s state- and nonstate-ownedfirms Our study focuses on the impact of family ownership on corporate disclosure andthus adds to this literature

The rest of the article proceeds as follows The next section discusses China’s tional background Section titled ‘‘Relevant Literature and Hypothesis Development’’reviews the relevant literature and develops our hypothesis Section titled ‘‘Sample andEmpirical Analysis’’ discusses our sample and empirical tests, and the last section con-cludes the article

institu-Institutional Background of China

China had a centrally planned economy for the three decades following the birth of thePeople’s Republic of China in 1949 The country’s economic reforms and opening-uppolicy began in 1978 and initially focused on rural areas In the 1980s, these reforms,which blended central-planning elements with market-based practices, were extendedbeyond the agricultural sector to state-owned enterprises (SOEs) It was not until 1992 thatthe Chinese Communist Party formally announced, at its 14th National Congress, thatChina was adopting a socialist market-based system A significant chapter in the country’stransition to this economic system was the establishment of the Shanghai and ShenzhenStock Exchanges in the early 1990s, and its capital markets have experienced unprece-dented growth since then

The majority of listed firms on the country’s stock market are the result of the zation of SOEs Typically, an operational unit of a large SOE was carved out, with its netassets converted to nontradable shares at a certain rate The remaining shares were thenissued to the public and can be traded As in other countries in which the governmentkeeps a controlling stake in listed (and partially privatized) SOEs, the Chinese central andlocal governments remain, either directly or indirectly, the controlling shareholders of these

firms (Chen, Firth, Gao, & Rui, 2006) According to Chen et al (2006), 30% of the shares

in a typical listed SOE are owned by the government or government-related agencies, andanother 30% are held by legal entities that are usually controlled by the state The remain-ing 40% are owned by individuals (including management and employees), private institu-tions, and foreign investors In non-SOE listed firms, the controlling shareholder may be afamily (discussed below) or some other type of nonstate entity (such as a foreign investor,the firm’s employees, etc.)

Hence, the Chinese stock market presents two unique ownership features First, althoughall shareholders have the same rights, there are six types of shares: state, legal entity, for-eign, management, employees, and other individuals (Firth, Fung, & Rui, 2007) The sharesheld by state and legal entities cannot be traded on the market, whereas those owned byindividuals are actively traded Second, ownership is highly concentrated The state, and/or

a legal entity shareholder, often controls the listed company, and, typically, there are noother block holders (Chen et al., 2006) Of the aforementioned six types of shares, thoseheld by management, employees, and foreign investors usually account for less than 3%(Firth et al., 2007)

Relative to SOEs, private companies, including family firms, are a recent product of thecountry’s economic reforms and opening-up policy The first group of entrepreneurs gener-ally comprised farmers and workers who had been laid off as a result of the SOE reforms

It is estimated that around 140,000 such entrepreneurs started up family businesses in theearly 1980s The expansion of economic reform has led to the rapid growth of these familyfirms, which have had a presence in China’s capital market since its inception In the first

10 years of this market’s establishment, the number of listed family firms increased ally by 83.8% (Zhang & Zhang, 2004) In all, 36% of these firms went public throughInitial Public Offerings (IPOs), 3% were listed through management buyouts, and theremainder obtained listing status by acquiring existing listed companies (Zhang & Zhang,2004) Although Chinese family firms have clearly become increasingly significant, sur-prisingly, to the best of our knowledge, no one in the literature has studied the impact offamily ownership on the accounting properties among the nonstate firms in China

annu-Relevant Literature and Hypothesis Development

Agency Problems and Family Firms

Firms face two types of agency problems, both of which have significant implications forthe accounting properties of family firms (e.g., Ali et al., 2007; Wang, 2006) The firsttype, known as Type I agency problems, results from the separation of ownership and con-trol, and may lead managers to act in their own best interests rather than those of the share-holders (Jensen & Meckling, 1976) Type I agency problems are typical in countries inwhich ownership is diffuse, such as the United States The second type of agency problem,known as Type II, stems from the conflict between controlling and noncontrolling share-holders (Ali et al., 2007), and is common in regions in which the ownership of listed firms

is usually concentrated in the hands of a single shareholder, as is generally the case in EastAsia (Fan & Wong, 2002) Both types of agency problems result in incentives and disin-centives for accounting transparency and corporate disclosure

Compared with their nonfamily counterparts, family firms usually exhibit different terns in both types of agency problems Several factors influence the Type I agency prob-lems in these firms First, family members usually hold positions among top management

pat-or serve on the board of directpat-ors and are sometimes directly involved in the firm’s tions As a result, they usually have better knowledge of the daily operations of the firm,which enables them to monitor managers more effectively and reduce opportunistic beha-vior on the part of the latter (Anderson & Reeb, 2003) Second, family firms are long-termoriented, and thus, the managers of these firms are less likely to seek short-term benefits bymanipulating accounting earnings (e.g., Chen et al., 2008) Third, family firms are moresensitive to negative market events, such as litigation (Chen et al., 2008) For all ofthese reasons, family firms may be less subject to the severe agency problems that oftenarise from the separation of ownership and control and more likely to disclose higher qual-ity earnings.

opera-However, Type II agency problems may lead the controlling owners of these firms toengage in opportunistic activities Family owners may use their controlling positions in thefirm to expropriate outside shareholders through various channels, such as related-partytransactions (Anderson & Reeb, 2003) and freezing out minority shareholders (Gilson &Gordon, 2003), and they may pursue their own interests at the expense of those of noncon-trolling shareholders (Ali et al., 2007) Correspondingly, the controlling shareholders offamily firms have more incentives to hide relevant information by disclosing lower qualityearnings, as such opacity helps them to expropriate outside shareholders

The severity of one type of agency problem over the other determines the quality of theinformation that firms disclose For example, the U.S market is characterized by diffuseownership, and Type II agency problems are significantly alleviated due to the well-established investor protection mechanisms in that country As a result, Type I agencyproblems tend to dominate Type II in the United States, which means that the family firmsthere are more likely to disclose higher quality earnings, as family ownership mitigatesType I problems Ali et al (2007) and Wang (2006) provide evidence to support this argu-ment Our study, in contrast, examines a setting in which Type II agency problems arelikely to be dominant, thus enriching our understanding of the impact of such agency prob-lems on accounting properties

Hypothesis Development

Both types of agency problems exist in China, although, as noted, Type II problems arepredominant for several reasons First, the existence of dominant shareholders is a typicalfeature of listed firms in China Second, the country’s investor protection mechanisms areweak, despite the rapid development of its macro-legal environment The Chinese legalsystem has been heavily influenced by the civil law tradition La Porta, Lopez-de-Silanes,Shleifer, and Vishny (1998) argue that legal protection for shareholders is weakest in coun-tries with a civil law legal origin Furthermore, Allen et al (2005) provide evidence toshow that creditor and shareholder protection in China is even worse than that in othermajor emerging markets The existence of dominant shareholders, in conjunction withweak protection for investors, renders Type II agency problems more salient, which helps

to explain why the China Securities Regulatory Commission, the country’s stock marketregulator, has repeatedly asserted that its top priority is strengthening minority shareholderprotection

The governance mechanisms and incentive structure of family firms differ from those ofnonfamily firms in several important aspects, all of which have significant implications forType II agency problems The key difference lies in their different ultimate controllers.Unlike family firms, which are controlled by an individual person and his or her family,

nonfamily firms are controlled by a group of legal entities, employees, or private investors,including institutional investors The benefits of expropriation for these controlling share-holders, which are typically institutions, organizations, or a group of private investors thatare independent of one another, are thus diluted As a result, the large shareholders of non-family firms have fewer incentives to expropriate minority shareholders (Villalonga &Amit, 2006) Family owners in China, in contrast, usually have absolute control over theirfirm’s board and management and are less constrained by its corporate governance system.Such a control structure makes it less costly for them to expropriate minority shareholders.Furthermore, the private benefits of control are not diluted, as they all go to the familyowners Family owners thus have stronger incentives to seek private benefits at the expense

of minority shareholders and may have more significant Type II agency problems pared with nonfamily firms Consequently, their disclosures tend to be more opaque forself-interested purposes For example, their accounting may be less informative, and theirearnings may be managed to bury the wealth effects (transfers) of their expropriationactivities

com-Type I agency problems, in contrast, which arise from the separation of ownership andmanagement, are similar for family and nonfamily firms in China because, on average,both have a concentrated ownership structure Large shareholders are likely to monitormanagement effectively and are sometimes directly involved in management For example,chairman of the board is an executive position in China This chairman, who is presumed

to represent the interests of the controlling shareholder(s), is often directly involved inoperations (Chen et al., 2006) In addition, chief executive officers (CEOs) and other topmanagers are usually appointed by the controlling shareholders (or, in some cases, are actu-ally the founders or their family members)

In summary, compared with their counterparts in the United States, Chinese family firmsconstitute a unique sample that is characterized by a higher degree of Type II agency prob-lems Consequently, we posit that Chinese family firms have different disclosure incentivesthan such firms in the United States, and we thus put forward the following hypothesis.Hypothesis: Family firms in China report lower quality accounting earnings thantheir nonfamily counterparts

Sample and Empirical Analysis

This section presents our empirical analyses Our sample covers all non-state listed nies in China from 2003 to 2006 We exclude finance firms, although their inclusion has

compa-no quantitative effect on our results General accounting data and data on family firms areobtained from the Guotaian (GTA) databases, which are widely used in accounting andfinance research using Chinese data (e.g., Haw, Qi, Wu, & Wu, 2005; Sun & Tong, 2003;Wei, Xie, & Zhang, 2005) In this study, a family firm is defined as a firm that is con-trolled by a private person and his or her family through direct stock ownership or through

a pyramid structure In addition, for a firm to be considered a family firm, the ownershipstake of the controlling family owner (the largest shareholder) must be greater than orequal to 10% Given the short history of the Chinese stock market and the rarity of mergersand acquisitions among the country’s listed companies, most, if not all, listed Chinesefamily firms are still controlled by their founders and their families The nonfamily firms

in our data set primarily include the following types of companies: dispersedly held nies with no controlling owner (or family), companies that are controlled by a group of

compa-investors (who are not from the same family), companies that are controlled by a group oflegal entities (such as not-for-profit organizations, township and village organizations, etc.),companies whose shares are held by employees or their unions, foreign-invested compa-nies, and other nonstate firms that are not family controlled.

Table 1 presents the descriptive statistics of our sample On average, the family firmsare smaller and have a higher level of abnormal returns, lower leverage ratios, greater cashflows from operations, greater profitability, and a higher level of return volatility than thenonfamily firms These characteristics suggest that family firms’ Type I agency problemsare at least not as severe as that of nonfamily firms even though both groups of firms havesimilar level of ownership concentration, a result that is consistent with prior studies (e.g.,

are thus likely to be driven by Type II agency problems Finally, at the bottom of Table 1,

we can see that both groups of firms have a similar degree of market capitalization.Table 2 presents the sample distribution for family and nonfamily firms by year andindustry The total number of both types of firms increased steadily from 2003 to 2006 Ofthe 1,542 observations, approximately 59.8% are family firms, about two thirds of which

Table 1 Descriptive Statistics

Family firm Nonfamily firm

n M Median n M MedianRET 917 0.006 20.062 613 20.048*** 20.091**EARNINGS 829 0.007 0.001 606 0.007 0.001DNI 870 0.009 0.001 566 0.010 0.001ABS_ACC 782 0.112 0.067 579 0.101 0.068SIZE 922 20.764 20.729 619 20.814 20.850BETA 841 1.117 1.110 592 1.091 1.100

MB 922 2.924 2.239 619 2.854 2.090LEVERAGE 922 0.585 0.535 619 0.647*** 0.554**LOSS 922 0.180 0.000 619 0.216* 0.000*SEO 922 0.018 0.000 619 0.019 0.000CFO 869 0.056 0.049 589 0.046** 0.044*ROA 923 20.012 0.022 619 20.028** 0.018**RETVOL 912 0.438 0.396 619 0.391*** 0.355***MVE 922 1,553.690 1,016.750 619 1,498.132 1,084.356

Note: RET = cumulative market-adjusted returns over the 12-month period from 8 months before the fiscal year-end

to 4 months after it (that is, from May 1 of year t to April 30 of year t 1 1); EARNINGS = the annual change in net income, deflated by the market value of equity at the beginning of the year; DNI the change in net income, calculated

as the net income of year t minus that of year t 2 1, scaled by the book value of equity at the beginning of year t; ABS_ACC = the absolute value of discretionary accruals (performance-matched discretionary accruals calculated follow- ing Ali, Chen, & Radhakrishnan, 2007); SIZE = the natural logarithm of the year-end book value of total assets; BETA = the stock beta at year t; MB = the market-to-book ratio, calculated as the year-end share price divided by the book value of equity per share; LEVERAGE = the leverage ratio of the firm at the end of the year, calculated as the year-end book value of total liability divided by total assets; LOSS = a dummy variable that equals one if net income \ 0 and zero otherwise; SEO = a dummy variable that equals one if the company has seasoned equity offerings and zero other- wise; CFO = cash flow from operations scaled by beginning-of-year total assets; ROA = return on assets, measured by net income divided by average total assets; RETVOL = annual stock volatility calculated using monthly stock returns over the year; and MVE = the market value of equity, in millions of Chinese yuan.

*** indicates that the mean (or median) value of the variable for family firms is significantly different from that for nonfamily firms at the 1% level; ** indicates a significance level of 5%; and * indicates a significance level of 10%.

are industrial firms In the overall sample, the firms are from five different industries, withthe majority industrial firms (67.8% for family firms and 61.1% for nonfamily firms).

We examine three attributes of accounting earnings in Chinese family firms: earningsinformativeness; the persistence of transitory loss components in earnings, which is a mea-sure of conservatism; and discretionary accruals These three attributes have also beenexamined in studies of the earnings quality of U.S family firms (e.g., Ali et al., 2007;

Informativeness of Accounting Earnings

We follow the common practice in the literature to measure the informativeness of ing earnings (e.g., Ali et al., 2007; Collins & Kothari, 1989) and examine whether those ofthe family firms in our sample are less informative The primary estimation model is given

account-by the following:

ð1Þwhere RET represents cumulative market-adjusted returns over the 12-month period from

8 months before the fiscal year-end to 4 months after it (from May 1 of year t to April 30 ofyear t 1 1), which includes the earnings announcement period; EARNINGS is the annual

and FAMILY is a dummy variable that equals one if the firm is a family firm and zero wise Following the prior literature (e.g., Ali et al., 2007; Collins & Kothari, 1989), weinclude the following control variables in our regression models: firm size (SIZE, which is

other-Table 2 Sample Distribution by Year and Industry

Number of firmsYear Family firm Nonfamily firm Total

4: Conglomerates 100 96 1965: Industrials 625 379 1,004

Total observations 922 620 1,542

the natural logarithm of the year-end book value of total assets); stock beta (BETA); growthpotential (MB, which is the market-to-book ratio, calculated as the year-end share pricedivided by the book value of equity per share); risk of bankruptcy (LEVERAGE, which is theleverage ratio of the firm at the end of the year, calculated as the year-end book value oftotal liability divided by total assets); and return volatility (RETVOL, which represents annualstock volatility and is calculated using monthly stock returns over the year) Finally,INDUSTRY EFFECTS and YEAR EFFECTS are dummy variables that are included to controlfor industry and time-fixed effects, respectively To mitigate the undue influence of outliers,

Simple correlation analysis (see Table 3) reveals that cumulative market-adjusted returnsand earnings are more positively correlated for nonfamily firms than they are for familyfirms (both correlation coefficients are significant at the 5% level), which is consistent withthe supposition that family firms are characterized by less informative earnings

Table 4 presents our estimation results Robust standard errors adjusted for clusteringand heteroscedasticity are reported in parentheses for all of the coefficient estimates(Petersen, 2009) Regression (1) in Table 4 is conducted to determine whether firm

Table 3 Correlations Among Variables

RET EARNINGS SIZE BETA MB LEVERAGE LOSS SEO RETVOLFamily firms

year-at the end of the year, calculyear-ated as the year-end book value of total liability divided by total assets; LOSS = a dummy variable that equals one if net income \ 0 and zero otherwise; SEO = a dummy variable that equals one if the company has seasoned equity offerings and zero otherwise; RETVOL = annual stock volatility calculated using monthly stock returns over the year.

* indicates that the correlation is significant at the 5% level or better.

earnings are generally informative, with a positive sign expected for b1 The estimationresult generally confirms this expectation, with the coefficient being positive and highly sig-nificant The sign of this coefficient estimate also remains positive in Regression Model (2).

In Regressions (2) and (3) in Table 4, the main coefficient of interest is that ofEARNINGS 3 FAMILY If it is positive, then family firms’ earnings are more informativethan those of their nonfamily counterparts A negative coefficient would indicate the oppo-site Family firms are found to disclose less informative earnings, as the coefficient estimateshave a negative sign in both of these regression models and are significant at the 5% level.Our results remain robust across different model specifications and after controlling forvariables that are commonly used in the literature (e.g., Ali et al., 2007; Collins & Kothari,1989; Wang, 2006), including firm size, stock beta, leverage, the effects of growth (MB),stock price characteristics, and the like The coefficients on the control variables, when sig-nificant, have the expected signs (except for that on EARNINGS 3 BETA) For example,firms with better growth potential tend to report more informative earnings, and those with

a greater degree of leverage less informative earnings In addition, because firms that issueboth A shares in the mainland Chinese stock markets and H shares in the Hong Kong stockmarket are likely to be subject to more stringent monitoring and accounting quality regula-tions, we run a sensitivity test by excluding firms with dual A and H shares (column 4 ofTable 4) Our main results hold in this test Finally, column 5 presents the estimationresults with real estate firms excluded from the sample Our main results are unchanged,but the coefficient estimate becomes only marginally significant Our estimates may thus

be sensitive to the exclusion of certain industries such as property and real estate in thesense that the significance level of our estimation results is somehow reduced by theirexclusions

Persistence of Transitory Loss Components in Earnings

Researchers have long argued that the transitory loss components in earnings are less sistent than positive earnings changes, possibly as a result of the conservative nature ofaccounting earnings (Basu, 1997) In this section, we use a piecewise serial dependencemodel (Ball & Shivakumar, 2005; Basu, 1997; Wang, 2006) to test the relationship

primary estimation model is given by

INDUSTRY EFFECTS1YEAR EFFECTS1error;

ð2Þ

defined The coefficient of interest on DNIt13DDNIt13FAMILYt captures the mental difference in accounting conservatism between family firms and nonfamily firms

conserva-tive in accounting (lower earnings quality) than the latter and vice versa

Table 5 reports the estimation results Similar to those reported in the previous section,the robust standard errors adjusted for clustering and heteroscedasticity are reported in par-

Regression Models (1) and (2), and are significant at the 1% level, which means thatfamily firms use less conservative accounting than do nonfamily firms Following the argu-ments in the prior literature (Ball & Shivakumar, 2005; Wang, 2006), this finding providesevidence to indicate that Chinese family firms issue lower quality financial reports than dononfamily firms

Another interesting result from Model 2 of Table 5 is that the coefficient estimate on

that larger firms are more conservative, which is consistent with the notion thatsuch firms may provide higher quality financial reports In general, the overall regression

Table 6 Discretionary Accruals and Family Firms

Regression ModelsDependent variable: ABS_ACC (1) (2) (3)CONSTANT 0.135*** (0.016) 0.394** (0.160) 0.394** (0.164)FAMILY 0.014* (0.009) 0.016* (0.008) 0.016* (0.008)SIZE — 20.015* (0.009) 20.015* (0.009)LEVERAGE — 0.046 (0.029) 0.046 (0.029)

MB — 0.005 (0.005) 0.005 (0.005)LOSS — 20.042*** (0.012) 20.043*** (0.012)CFO — 20.050 (0.076) 20.050 (0.077)ROA — 20.112 (0.111) 20.116 (0.114)SEO — 20.004 (0.017) 20.005 (0.017)INDUSTRY EFFECTS Yes Yes Yes

YEAR EFFECTS Yes Yes Yes

Adjusted R2 019 053 052

No of observations 1,283 1,283 1,276

Note: The dependent variable is ABS_ACC, which is the absolute value of discretionary accruals matched discretionary accruals calculated following Ali et al., 2007); FAMILY = a family dummy that equals one if the firm is a family firm and zero otherwise; SIZE = the natural logarithm of the year-end book value of total assets; MB = the market to book ratio, calculated as the year-end share price divided by the book value of equity per share; LEVERAGE = the leverage ratio of the firm at the end of the year, calculated as the year-end book value

(performance-of total liability divided by total assets; LOSS = a dummy variable that equals one if net income \ 0 and zero wise; SEO = a dummy variable that equals one if the company has seasoned equity offerings and zero otherwise; CFO = cash flow from operations scaled by beginning-of-year total assets; ROA = return on assets, measured by net income divided by average total assets; INDUSTRY EFFECTS = dummy variables that control for industry fixed effects; and YEAR EFFECTS = dummy variables that control for calendar year fixed effects Real estate firms are excluded from the regressions In Regression (3), firms that issue both A shares (in the mainland Chinese stock markets) and H shares (in the Hong Kong stock market) are excluded from the sample Continuous variables are winsorized (1% in each tail) Standard errors (in parentheses) are robust standard errors adjusted for clustering and heteroscedasticity Values are bold to highlight rows of our focal interest.

other-*** indicates a significance level of 1%, ** indicates a significance level of 5%, and * indicates a significance level of 10%, all two-tailed.

models are highly significant Industry and year dummies are again included tocontrol for fixed industry and time effects, and, similar to the previous section, we runsensitivity tests by excluding A and H dual share firms (Regression 3 in Table 5) and realestate firms (Regression 4 in Table 5) from the sample, but the main results remainunchanged.

It must be stated here that the usual caveat applies when interpreting these findings

As Ball and Shivakumar (2005) and Wang (2006) point out, the serial dependence model(Basu, 1997) is limited by its potential inability to distinguish the transitory components

in earnings from random accruals errors and from some types of earnings management

In addition, this model may be unable to determine whether the recognition of the tory loss components in earnings is timely or untimely (Ball & Shivakumar, 2005)

transi-Discretionary Accruals

Following the literature (e.g., Ali et al., 2007; Ashbaugh, LaFond, & Mayhew, 2003), weestimate the following model to examine the relationship between discretionary accrualsand family firms:

1YEAR EFFECTS1error:

ð3Þ

The dependent variable ABS_ACC is the absolute value of discretionary accruals, whichare performance-matched discretionary accruals calculated as in Ali et al (2007) Morespecifically, we match firms by return on assets (ROA) within their industry, that is, utili-ties, conglomerates, industrials, and commerce, with the property and real estate industry

et al., 2007; Wang, 2006) Specifically, we control for the risk of bankruptcy(LEVERAGE), firm size (SIZE), and growth potential (MB) Firms may manage their earn-ings to meet the regulatory standards for stock rights offerings, and we thus control for thiseffect by including a SEO dummy that equals one if the firm had a seasoned equity offeringand zero otherwise CFO is defined as cash flows from operations scaled by total assets atthe beginning of the year, and ROA is the current year’s return on assets LOSS is a dummyvariable that equals one if net income \ 0 and zero otherwise All of the other variablesare as previously defined Finally, we include industry and year dummies to control fortime and industry effects A positive coefficient on the family dummy would indicate thatfamily firms are associated with a higher level of discretionary accruals

The descriptive statistics reported in Table 1 suggest that the mean value of ABS_ACCfor family firms is higher than that for nonfamily firms, although the difference is statisti-cally insignificant Table 6 reports the multiple regression results with the robust standarderrors adjusted for clustering and heteroscedasticity in parentheses The coefficient esti-mates of the family dummy in Models 1 and 2 are significantly positive at the 10% level,thus indicating that the level of discretionary accruals is higher for family firms than fortheir nonfamily counterparts and that greater opportunistic reporting behavior exists amongthe former If a higher level of discretionary accruals proxies for lower quality earnings,then this result is consistent with those on earnings informativeness and conservatism

These findings are robust to the inclusion of the various control variables commonlyused in the literature, and the signs of the coefficients on these variables are also generallyconsistent with the prior literature For example, the coefficient on SIZE is negative andsignificant at the 10% level, which suggests that large firms have a lower level of discre-tionary accruals The coefficient on LOSS has a negative sign, which may reflect thegreater degree of monitoring by the government and the market that loss firms receive in

previously stated, if a firm issues both A shares on the Shanghai or Shenzhen stockexchange and H shares on the Hong Kong exchange, then it may be subject to greater regu-latory scrutiny and therefore less likely to manage earnings As a sensitivity test, weexclude dual A and H share firms from our sample (column 3 of Table 6), but our mainresults hold However, caution must be exercised in interpreting our discretionary accrualsresults, as the FAMILY coefficient is only marginally significant across all of the regres-sions in Table 6

In summary, using a portfolio of earnings quality measures, including earnings tiveness, conservatism, and discretionary accruals, we find evidence that is consistent withthe notion that family firms in China exhibit certain accounting properties that stem fromType II agency problems

informa-Conclusion

Family firms have become an increasingly important area of research (e.g., Bennedsen,Nielsen, Perez-Gonzalez, & Wolfenzon, 2007) Previous accounting studies using U.S.family firm data provide evidence on the degree of transparency and disclosure in thesefirms when Type I agency problems dominate However, compared with U.S family firms,which are usually managed and controlled by professional managers, those in Asian econo-mies, including China, are more pervasive and diverge more from their nonfamily counter-parts Because of the weak investor protection mechanisms and less-advanced marketdevelopment in these economies, Type II agency problems are likely to play a larger role.The use of Chinese data thus helps to alleviate some of the data problems seen in U.S.studies and to isolate Type II agency problems, which has sharpened our tests of the inter-actions among institutional development, incentives, ownership structure, and accountingproperties Different from the findings reported by Ali et al (2007) and Wang (2006) onU.S family firms, we find that such firms in China disclose less informative earnings, areless conservative in their financial reporting, and are more likely to engage in the manipu-lation of discretionary accruals These findings are consistent with our argument thatChinese family firms have greater Type II agency problems than their nonfamilycounterparts

Several limitations must be acknowledged This study does not examine the effect ofChina’s convergence to International Financial Reporting Standards (IFRS), a process thatbegan in 1993 Following the country’s new generally accepted accounting principles(GAAP), which became effective in 2007, it is clear that the Chinese authorities believe theconvergence between Chinese GAAP and IFRS to be nearly complete (Ding & Su, 2008,

p 478) The findings of the current study suggest that incentives and institutions, perhaps

in combination with accounting standards and education, may have an impact on corporatetransparency Our sample period ended before the new standards were implemented in

2007 A possible direction for future research would be to examine whether China’s stagedapproach to IFRS convergence has any impact on the results reported here The

profitability requirement and valuation of IPOs have been dramatically changed over the

examine the effect of these changes on our results In addition, some of our results (such asthose of our discretionary accruals analysis) are marginally significant, and caution shouldthus be exercised in their interpretation

Authors’ Note

The authors are grateful for the helpful comments from the anonymous referee, Charles Chen, YuanDing, Gordon Richardson, and seminar participants at the Peking University, Shanghai JiaotongUniversity, and the 2009 Shanghai Winter Finance Conference of China They also thank QingboYuan for his excellent research assistance The usual disclaimer applies

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/

or publication of this article

3 Fan and Wong (2002) use only earnings informativeness, not the other two attributes

4 The authors also run regressions using operating income rather than net income, and the resultsare similar

5 Speculative trading is an important factor that may affect the value of RET for firms in China It

is well known that speculative trading, which tends to create outliers with exceptionally high- orlow-RET values, is rife in the Chinese stock markets We tackle this problem by winsorizingRET at the 10th and 90th percentiles

6 The authors also tried Basu’s (1997) reverse regression approach However, the relationshipbetween family ownership and timely loss recognition is nonsignificant even though the coeffi-cient estimate has the expected sign As Gigler and Hemmer (2001) argue, Basu’s approach maygenerate biased results because it does not control for the potential effect of voluntary disclosures

on stock prices

7 Including these firms in the analysis does not change our main results

8 In China, a listed firm with losses may be designated as Special Treatment (ST) or ParticularTreatment (PT) firms by the regulatory body ST/PT firms are usually subject to greater regula-tory and market scrutiny

9 The authors thank the anonymous referee for raising this point In China, firms were required toachieve an annual profitability level of at least 10% for three consecutive years to be qualifiedfor an IPO, but the criteria were changed later to 10%, on average, for three consecutive years.Furthermore, the Chinese Corporate Law was enacted in 1993 and was amended 3 times in

1999, 2004, and 2005 It is believed that these amendments have led to significant ments The latest Corporate Law, for instance, has codified independent directorship and

improve-addressed serious constraints facing supervisory boards, which are part of the dual-board ture in Chinese listed companies.

Burkart, M., Panunzi, F., & Shleifer, A (2003) Family firms Journal of Finance, 58, 2167-2201.Chen, G., Firth, M., Gao, D., & Rui, O (2006) Ownership structure, corporate governance, andfraud: Evidence from China Journal of Corporate Finance, 12, 424-448

Chen, S P., Chen, X., & Cheng, Q (2008) Do family firms provide more or less voluntary sure? Journal of Accounting Research, 46, 499-536

disclo-Claessens, S., Djankov, S., & Lang, L H (2000) The separation of ownership and control in EastAsian Corporations Journal of Financial Economics, 58, 81-112

Collins, D., & Kothari, S P (1989) An analysis of inter-temporal and cross-sectional determinants ofearnings response coefficients Journal of Accounting and Economics, 11, 143-181

Ding, Y., & Su, X (2008) Implementation of IFRS in a regulated market Journal of Accounting andPublic Policy, 27, 474-479

Fan, J., & Wong, T J (2002) Corporate ownership structure and the informativeness of accountingearnings in East Asia Journal of Accounting and Economics, 33, 401-425

Firth, M., Fung, P., & Rui, O (2007) Ownership, two-tier board structure, and the informativeness ofearnings—Evidence from China Journal of Accounting and Public Policy, 26, 463-496

Gigler, F B., & Hemmer, T (2001) Conservatism, optimal disclosure policy and the timeliness offinancial reports Accounting Review, 76, 473-493

Gilson, R J., & Gordon, J (2003) Controlling controlling shareholders (Working Paper No 228).New York, NY: Columbia Law School, The Center for Law and Economic Studies

Haw, I., Qi, D., Wu, D., & Wu, W (2005) Market consequences of earnings management in response

to security regulations in China Contemporary Accounting Research, 22, 95-140

Healy, P., & Palepu, K (2001) Information asymmetry, corporate disclosure, and the capital markets:

A review of the empirical disclosure literature Journal of Accounting and Economics, 31, 440

405-Ho, S., & Wong, K (2001) A study of the relationship between corporate governance structures andthe extent of voluntary disclosure Journal of International Accounting, Auditing and Taxation, 10,139-156

Hutton, A (2007) A discussion of ‘‘corporate disclosure by family firms.’’ Journal of Accountingand Economics, 44, 287-297

Jensen, M., & Meckling, W (1976) Theory of the firm: Managerial behavior, agency costs and ership structure Journal of Financial Economics, 3, 305-360

own-La Porta, R., Lopez-de-Silanes, F., & Shleifer, A (1999) Corporate ownership around the world.Journal of Finance, 54, 471-517

La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R (1998) Law and finance Journal ofPolitical Economy, 106, 1113-1155.

Miller, D., Breton-Miller, I., Lester, R H., & Cannella, Jr., A (2007) Are family firms really ior performers? Journal of Corporate Finance, 13, 829-858

super-Petersen, M (2009) Estimating standard errors in finance panel data sets: Comparing approaches.Review of Financial Studies, 22, 435-480

Sun, Q., & Tong, W (2003) China share issue privatization: The extent of its success Journal ofFinancial Economics, 70, 183-222

Villalonga, B., & Amit, R (2006) How do family ownership, control and management affect firmvalue? Journal of Financial Economics, 80, 385-417

Wang, D (2006) Founding family ownership and earnings quality Journal of Accounting Research,

Auditing & Finance 26(4) 641–658

Ó The Author(s) 2011 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0148558X11409160

http://jaaf.sagepub.com

Does Enterprise Risk

Management Increase Firm

enterprise risk management (ERM), traditional risk management (TRM), S&P ERM rating,insurance firms, firm value

The crisis that started in 2007 with U.S financial institutions caused a panic that rippledacross global markets and practically froze credit markets in 2008 Some have blamed thecrisis on a ‘‘failure of conventional risk management in financial institutions’’ (Fraser &Simkins, 2010, p 27) Others have extended the blame to include enterprise risk manage-ment (ERM), a new paradigm that had started to supplant conventional risk management,especially within the large financial institutions at the heart of the crisis (Hampton, 2009,

p 66)

The crisis has once again brought risk management to the forefront, not just among topexecutives within firms but also among members of Congress and government regulators.However, this concern about risk management had been gaining steam for several years.For instance, Section 404 of the Sarbanes-Oxley Act of 2002 requires a top-down riskassessment, which includes the identification of material risks on financial statements In

2004, the New York Stock Exchange (NYSE) implemented new corporate governancerules requiring audit committees of listed firms to be more involved in risk oversight The

new rules have motivated many boards to require the review and approval of riskmanagement processes and top risk exposures by their audit committee.

In response to the financial crisis, in October 2008, Congress enacted the EmergencyEconomic Stabilization Act, which created the Troubled Asset Relief Program (TARP), tohelp troubled financial institutions TARP stipulates that participating firms must certifythat executive compensation programs do not encourage excessive risk taking In May

2009, Senators Schumer and Cantwell proposed legislation, the Shareholder Bill of Rights,which requires public companies to create stand-alone risk committees comprised entirely

of independent directors who are responsible for the establishment and evaluation of riskmanagement practices In October 2009, the Federal Reserve proposed guidance that placesresponsibility on the board of directors for establishing appropriate incentive compensationarrangements and effectively monitoring risk exposures created by incentive compensationarrangements New rules from the Securities and Exchange Commission effective February

28, 2010, require enhanced risk-related disclosures in proxy and annual statements.Disclosure is required indicating the relationship of a company’s compensation policies andpractices to risk management and the board of directors’ leadership structure and role inrisk oversight

Driven by this intense flurry of government and stock exchange activities related to riskmanagement within corporations, trade and business publications directed at top manage-ment are full of articles related to ERM, yet academic research in the area is still rare Webelieve that one main roadblock to this research is the difficulty in developing a valid andreliable measure for the ERM construct Beasley, Pagach, and Warr (2008) and Hoyt andLiebenberg (2011) use the appointment of a chief risk officer (CRO) as a proxy for ERMimplementation, whereas Gordon, Loeb, and Tseng (2009) develop their own ERM index.Results on the relationship between ERM and various measures of firm value have beenmixed Beasley et al (2008) investigate equity market reactions to senior managementappointments to oversee a firm’s ERM processes Their results suggest firm-specific bene-fits of ERM For nonfinancial firms, they find that market reactions to appointmentannouncements are positively related to firm size and volatility of previous earnings butnegatively related to leverage and the ratio of cash to liabilities They cannot make thesame claim for financial firms and argue that these firms may be more driven by otherdemands for risk management, such as from regulators Hoyt and Liebenberg (2011) found

a positive relationship between firm value and the appointment of a CRO Gordon et al.(2009) found that the relationship between ERM and firm performance depended on howwell ERM implementation was matched with firm-specific factors

We use a newly available measure to investigate the relationship between the extent ofrisk management implementation and firm performance Since 2007, Standard and Poor’s(S&P) has included a risk management rating as a component in its overall rating of insur-ance companies The rating is a sophisticated and comprehensive index that assesses therisk management culture, systems, processes, and practice within the insurer

S&P assigns risk management ‘‘ERM ratings’’ over five categories, which we interpret

as indicating increasing levels of risk management sophistication ranging over three tional risk management (TRM) levels and two ERM levels Our study offers a unique set-ting to investigate the relationship between risk management and firm value for tworeasons First, insurance firms are arguably leaders in implementing sophisticated riskmanagement programs; second, the year 2008 was characterized by extreme uncertainty inwhich a superior risk management program should provide an advantage Overall, ourresults indicate a positive relationship between ‘‘ERM rating’’ and firm value as the rating

tradi-increases over the first three categories—the first three categories are indicative of ing levels of TRM—but no additional increase in firm value as the rating moves beyondTRM into what we consider the ERM realm.

increas-The article is organized as follows First, in our literature review, we cover the evolution

of risk management research from ‘‘irrelevance’’ to ERM, focusing on the distinctionbetween TRM and ERM Next, we motivate the variables we use in the study, including adescription of S&P’s new risk management rating for insurance companies In our researchdesign section, we describe the data and model After detailing the results, we concludewith suggestions for future research

Literature Review

Risk management has been a widely debated topic from the early days of finance research,where it was considered irrelevant (Modigliani & Miller, 1958) under perfect market condi-

finance academics begin to investigate their effectiveness The following discussion coversthe evolution of this topic and distinguishes between what we call ‘‘TRM’’ and ‘‘ERM.’’

TRM

Some finance scholars responded to Modigliani and Miller’s (1958) ‘‘risk managementirrelevance principle’’ by citing capital market imperfections and proposing theories thatexplain why risk management can increase firm value In TRM research, scholars proposethat the existence of these imperfections allows risks to impose real costs on firms and thatrisk management can increase firm value by reducing total risk, typically measured assome type of volatility Researchers have identified various value-increasing benefits ofrisk management that can generally be classified as reduction in expected costs related tothe following: tax payments, financial distress, underinvestment, asymmetric information,

Such studies help in understanding the reasons that firms decide to hedge risk and vide a theoretical justification for the link between risk management and firm value.Allayannis and Weston (2001) directly investigate the relationship between risk manage-ment and firm value Among their sample of large nonfinancial firms with foreign currencyexposures, Allayannis and Weston find that firms using foreign currency derivativeshad, on average, almost a 5% higher firm value than nonusers More studies (see, for exam-ple, Bartram, Brown, & Conrad, 2009; Carter, Rogers, & Simkins, 2006; Graham &Rogers, 2002; Nelson, Moffitt, & Affleck-Graves, 2005) followed showing a positive rela-

However, Guay and Kothari (2003) question the results of these studies after findingthat derivatives positions of most nonfinancial companies are too small to significantlyaffect firm value They surmise that derivatives usage is likely a fine-tuning mechanism for

a firm’s much larger overall risk management program, which includes other activities,such as operational hedges In support of this view, Jin and Jorion (2006) investigate oiland gas firms and find no evidence that firms using derivatives to hedge their oil and gasrisk increase firm value relative to firms that do not hedge

The studies mentioned up to now investigate risk management using derivatives tohedge risk as a proxy for risk management activities Other studies investigate the relation-ship between financial and operational hedging and, typically, proxy financial hedging by

derivative usage and operational hedging by geographic and segment diversification.Chowdhry and Howe (1999) argue that derivatives are used to mitigate short-term currencyexposures, whereas operational hedges are better suited for handling long-run currencyexposures Later studies examine whether financial and operational hedging are substitutes

or complements, and most find evidence of a complementary relationship (see, for ple, Allayannis, Ihrig, & Weston, 2001; Kim, Mathur, & Nam, 2006; Pantzalis, Simkins, &Laux, 2001)

exam-Another strand of the finance literature argues that firms should not engage in any effort

to manage idiosyncratic risk In the 1960s, building on Markowitz’s (1952) work on sification and portfolio theory, various researchers (Lintner, 1965; Mossin, 1966; Sharpe,1964; Treynor, 1961, 1962) developed the capital asset pricing model (CAPM) In thismodel, investors are compensated only for bearing systematic (nondiversifiable) risk butnot for bearing idiosyncratic (diversifiable) risk In other words, a firm’s cost of capital(required rate of return) should depend only on the firm’s systemic risk, not the total risk

diver-of the firm, because investors can eliminate the diversifiable risks diver-of individual firms byholding a well-diversified portfolio The systemic risk of a firm is also called ‘‘marketrisk’’ because this risk (and the firm’s cost of capital) depends on the covariance of thefirm’s security returns with the returns of the broad market, not on the firm’s overall volati-lity (variance) The systemic risk of the firm is represented by the familiar b in the CAPM

An implication of CAPM is that firms should not use risk management to reduce

diversification

However, several researchers countered with asset pricing models in which idiosyncraticrisk does matter, for example, because investors may hold undiversified portfolios (see, forexample, Goyal & Santa-Clara 2003; Green & Rydquist, 1997; Levy, 1978; Merton, 1987).Froot and Stein (1998) develop a capital allocation/structure model for financial institu-

builds on this model to include customer aversion to insolvency risk, which is an importantconsideration for financial institutions because their customers typically have a greater con-cern about solvency risk than do investors Overall, an implication is that in decidingwhether to allocate capital for an investment, the decision should reflect the covariation ofthe investment’s risk with the firm’s existing portfolio of risks

ERM

Traditionally, risk management has been compartmentalized and uncoordinated within a

whereas the treasury department used derivatives to reduce financial risks, such as interestrate, credit, market, and foreign exchange risk ERM attempts to deal with additional riskssuch as operational or strategic risks The goal of ERM is the coordinated management ofall risks faced by a firm, whether it is risk related to corporate governance, auditing, supplychains, distribution systems, IT, or human resources Unlike TRM’s silo-based risk man-agement, the purpose of ERM is to gain a systematic understanding of the interdependen-cies and correlations among risks A fundamental concept of ERM is the aggregating ofrisks into portfolios, then hedging the residual risk, which is more efficient and value maxi-mizing than dealing with each risk independently Applying concepts of portfolio theory,ERM can increase firm value because the risk of an aggregate portfolio should be less than

the sum of the individual risks if the risks are not 100% correlated, especially if naturalhedges exist.6

In a call for risk management research that focuses on the coordination and strategicallocation of risk, Stulz (1996) proposes that academic theory expand beyond consideringthat the goal of risk management is ‘‘variance minimization.’’ In other words, the goal ofrisk management should not be to reduce total risk but to allocate risks to play on a firm’sstrengths A basic concept of ERM is that a firm should reduce exposure to risk in areaswhere it has no comparative information advantage and exploit risks in areas where it has

an advantage, meaning that total risk can possibly increase under ERM risk allocation.Schrand and Unal (1998) posit that corporate managers should coordinate risk-management activities by hedging exposure to activities in which they are likely to earnzero economic rents (homogeneous risks), such as investments in efficient markets, whileincreasing exposure to core-business activities (Barney, 1991) in which they enjoy com-parative information advantages Such a coordinated approach can generate a decreasing,neutral, or increasing effect on total firm risk Since Schrand and Unal (1998), there hasbeen very little work related to coordinated risk management in the finance literature.Recently, Zhang, Cox, and McShane (2011) use insurance industry data to investigate thecoordination of risks across completely different functions of the enterprise while control-ling for other factors that affect hedging decisions They consider investments to be ahomogeneous risk for insurers and underwriting to be a core-business risk, and find evi-dence that insurers are coordinating risk management by hedging investment risk to take

on more underwriting risk

A few articles have indirectly investigated the determinants of ERM implementationamong firms Liebenberg and Hoyt (2003) investigate the determinants of ERM adoption,using the appointment of a CRO as a proxy for ERM implementation Their main finding

is that more leveraged firms are more likely to appoint a CRO In a similar study, Pagachand Warr (2011) find that firms with more leverage, higher earnings volatility, poorer stockperformance, and a CEO whose compensation increases with stock volatility are morelikely to have a CRO Using survey data, Beasley, Clune, and Hermanson (2005) findERM implementation in their sample of firms to be positively related to factors such as thepresence of a CRO, firm size, and whether the firm is in the insurance or banking industry.Two studies indirectly investigate the relationship between ERM implementation andfirm value Hoyt and Liebenberg (2011) find a positive relationship between firm value andthe appointment of a CRO In an event study of the market reaction to the appointment ofsenior executives to oversee a firm’s ERM process, Beasley et al (2008) find firm-specificbenefits of ERM for nonfinancial firms, but not for financial firms Gordon et al (2009)develop their own ERM index and find that the relationship between ERM and firm perfor-mance is conditional on the match between ERM implementation and firm-specific factors.Beasley et al (2008) indicate that a limitation of using the CRO variable is that it doesnot capture the extent of ERM program implementation In the next section, we describethe measure used in this study, which we believe comprehensively captures the complexity

of ERM and reflects the extent of its implementation

Variable Motivation

Our risk management variable is novel, but the other variables are motivated by the ous risk management literature

Dependent Variable (Firm Value)

Our dependent variable is firm value, which we proxy for using Tobin’s Q, the most monly used measure of firm value in empirical risk management studies (Smithson &Simkins, 2005) We calculate Tobin’s Q as the market value of equity plus the book value

com-of liabilities divided by the book value com-of assets This version com-of Tobin’s Q is suitable forinsurance companies because the book value of an insurer’s assets is a good approximation

of replacement costs (Cummins, Lewis, & Wei, 2006; Hoyt & Liebenberg, 2011)

Independent Variable of Interest (ERM Rating)7

Financial rating firms, such as S&P, rate the ability of a firm to pay back creditors A firmwith a higher rating will have lower borrowing costs, which should translate to higher firmvalue, all else equal This effect will be intensified for insurers because the policyholder is

a contingent debtholder In essence, policyholders are both customers and main creditors ofinsurance companies As described in McShane, Cox, and Butler (2010), insurers withhigher ratings command higher premiums because they are perceived as safer by policy-holders Premiums are the main revenue source for an insurance firm, implying that ahigher credit rating leads to higher returns, and supporting empirical evidence has beenfound (see, for example, Cummins & Nini, 2002)

We use the new risk management rating from S&P as a proxy for degree to which an

insurers based on eight components and gradually started to add the newest component,

rating’’ for each insurer: risk management culture, risk control processes, emerging risksmanagement, risk and economic capital models, and strategic risk management At the base

of the ERM program is the firm’s risk management culture A major S&P consideration inthis area is the importance of the risk management process to C-suite executives becauseERM only works if the ‘‘tone is set at the top.’’ The governance structure should reflectthe influence of risk and risk management considerations on corporate-wide decisionmaking, including the transparency with which the risk management philosophy is commu-nicated across the organization and the extent to which risk management influences man-agement compensation and budgeting

Next are the three pillars of the ERM program: (a) the ability of the insurer’s risk trol processes in identifying, analyzing, and keeping losses within defined risk tolerances;(b) the capability of the insurer to scan the environment to anticipate and prepare for emer-ging risks; and (c) the effectiveness of the insurer’s risk and economic capital models torealistically provide insight into possible risks facing the insurer and support to other ERMprocesses

con-A strong risk management culture at the base and the three well-designed pillars areessential to support the firm in achieving effective strategic risk management for which akey consideration is the extent to which the insurer has integrated risk management withcore strategic planning processes Firms with a higher ERM rating should have an advan-tage in anticipating and dealing with the next big risk, lower volatility of earnings, andgreater ability to allocate capital to attain higher risk-adjusted returns

S&P places each insurer into one of five ‘‘ERM rating’’ categories A weak ERM gram lacks reliable loss control systems for one or more major risks An adequate ERMprogram has reliable loss control systems but may still be managing risks in silos instead of

pro-coordinating risks across the firm The ERM program is rated adequate with a positivetrend if it exhibits strong/excellent risk control systems but still lacks a well-developed pro-cess for making coordinated risk/reward decisions that are necessary for effective strategicrisk management A strong ERM program has progressed beyond silo risk management todeal with risks in a coordinated approach, the capability to envision and handle emergingrisks, and well-developed risk-control processes and a focus on optimizing risk-adjustedreturns that are necessary for effective strategic risk management An excellent ERM pro-gram has the same characteristics as a strong ERM program but is even further into the

S&P expects that insurers ‘‘with an adequate ERM program should not experience proportionate losses in a normally adverse environment,’’ whereas ‘‘strong/excellentinsurers are expected to exhibit lower losses in difficult times and especially in extremelyadverse times.’’ The S&P ERM rating is from April 2008, and other data we use are from

dis-2008, which we consider to be an extremely adverse year for financial institutions, cially the latter half Thus, the 2008 downturn offers an excellent setting to investigate therelationship between ERM rating and firm value during ‘‘extremely adverse times.’’The ERM rating variable allows us to overcome the problems associated with previouswork on the relationship between risk management and firm value As discussed previ-ously, Guay and Kothari (2003) and Jin and Jorion (2006) present arguments on possibleproblems with previous work that finds a positive relationship between hedging and firmvalue They argue that derivatives usage only has a marginal impact on firm value relative

espe-to other risk management facespe-tors and that results are likely espe-to be spurious if these otherfactors add value and are positively correlated with derivatives usage We overcome thisproblem by using the S&P ERM rating variable, which captures all aspects of the risk-management program and reflects the extent of its implementation The ERM variable isalso superior to using the announcement of a CRO as a binary indicator of ERM implemen-tation as in previous studies, which does not capture the extent of ERM implementation

We translate the S&P ERM ratings into numerical scores suitable for statistical analysis

as follows: 1 = weak, 2 = adequate, 3 = adequate with a positive trend, 4 = strong, and 5 =excellent Based on our review of the past risk management literature, we expect thedegree of ERM implementation by an insurer to be positively related to firm value

Control Variables

We investigate the relationship between ERM rating and firm value after controlling forvariables that are motivated by previous risk management research We expect the Sizevariable to be positively related to performance because larger firms should be more capa-ble of capturing economies of scale in underwriting insurance contracts Liebenberg andSommer (2008) find that larger property–liability insurers generate higher returns onequity, and McShane and Cox (2009) find similar results for life–health insurers, whichthey attribute to the greater market power and economies of scale and lower insolvencyrisk of larger insurers We follow previous research in applying the natural logarithm oftotal assets as our size proxy If greater Leverage implies greater default risk, then rationalpolicyholders should pay lower prices for policies issued by more leveraged insurers(Sommer, 1996), which implies a negative relationship between leverage and return Ourmeasure for leverage is the financial leverage index, which is the ratio of return on averageassets to return on average equity

We proxy for Systemic Risk using the insurer’s b, which we expect to be negativelyrelated to firm value An insurer with greater systemic risk will discount expected cashflows at a higher rate, which should result in a relatively lower firm value (Shin & Stulz,2000) We also use control variables for Profitability (return on assets), Cash FlowVolatility (SD of the free cash flow over the previous 5 years scaled by the average freecash flow over the previous 5 years), and Growth Opportunities (average annual salesgrowth over the previous 5 years) We expect our results to be similar to those found inpast previous risk management research; that is, firm value is positively related to profit-ability and growth opportunities and negatively related to cash flow volatility.

We control for insurer complexity by adding a variable that indicates the number oflines of business (LOB) in which the insurer operates We operationalize this by countingthe number of four-digit Standard Industrial Classification (SIC) codes in which the insurerdoes business The managerial discretion hypothesis of Mayers and Smith (1988) suggeststhat insurers operating in fewer LOB (less complex insurers) should have lower monitoringcosts for owners, resulting in higher returns Therefore, we expect the complexity variable

to be negatively related to firm value The number of SIC codes for insurers in our sampleranges from one to eight

non-linear relation between ERM and firm value Table 1 shows the variable descriptions andexpected signs

Research Design

This section describes our data and model

Table 1 Variable Definitions and Expected Signs

Independent variables Expected sign Definition

ERM rating 1 S&P ERM rating for each insurer in April 2008: 1 = weak, 2 =

adequate, 3 = adequate with a positive trend, 4 = strong, and 5

= excellentERM rating2 1/2 S&P ERM2score for each insurer

Size 1 Natural logarithm of total assets at end of 2008

Financial leverage 2 Financial leverage index: ratio of return on average assets to

return on average equity for 2008Systemic risk 2 Insurer’s beta (b)

Profitability 1 ROA in percentage for 2008

Cash flow volatility 2 Standard deviation of the free cash flow over the previous 5

years (years 2004–2008) scaled by the average free cashflow over the previous 5 years (years 2004–2008)Growth opportunities 1 Average annual sales growth in percentage over the previous

5 years (2004-2008)Complexity 2 Number of four-digit SIC codes in which insurer operates

Note: ERM = enterprise risk management; ROA = return of assets; SIC = Standard Industrial Classification This table provides the definition and the expected sign for each independent variable Dependent variable is firm value, which is proxied by Tobin’s Q: market value of equity plus the book value of liabilities divided by the book value of assets Point data, such as total assets, are measured at the end of 2008 Average data are the average of the value

on the last day of 2007 and the value on the last day of 2008 Return data are measured over the period from the last day of 2007 to the last day of 2008.

We investigate the relationship between firm value and the degree to which insurers haveimplemented ERM using the following model The variable definitions and expected signsare shown in Table 1

ð1Þ

Results

Descriptive statistics are shown in Table 2, which includes the mean values for the dent and independent variables for each S&P ERM rating category The relationshipbetween ERM rating and firm value is somewhat in line with our expectation, that is, aroughly positive relationship, though it appears to peak out for ERM3 and ERM4 insurers

relationship Table 2 also indicates a positive relationship between ERM rating and firmsize but no obvious pattern for the relationship of ERM rating and the other controlvariables

Table 3 shows the Pearson correlation coefficients The signs of the correlations of theindependent variables with firm value are roughly as expected though insignificant in manycases The only correlation above 5 is between two independent variables: ERM rating andsize We therefore compute the variance inflation factors (VIFs) developed by Belsley,Kuh, and Welsch (1980) With all VIFs below 2.5, collinearity is unlikely to be a problem

Table 2 Descriptive Statistics Categorized by ERM Rating

ERM rating

No of

firms

Firmvalue

Firmsize

Financialleverage

Systemicrisk Profitability

Cash flowvolatility

Growthopportunities Complexity

Next, we move on to our multivariate tests to investigate further with results shown inTable 4 We perform four different regressions to investigate the relationship between ERMrating and firm value In Regression (1), ERM rating is positive and significantly related tofirm value with a p value of 027 In this regression, ERM rating is the only regressor and

rating is still positive and significant at the 5% level A squared ERM rating variable isadded in Regression (3) to test for nonlinear effects ERM rating is still positive and signifi-cant at the 1% level, and the squared ERM rating coefficient is negative with a p value of.026, indicating that ERM rating has a nonlinear relationship to firm value

We investigate this nonlinear relationship further in Regression (4) by using dummyvariables for each ERMrating category We omit ERM3 in the regression so results for theother ERM ratings will be in relation to ERM3 In Regression (4), ERM1 and ERM2 areboth negatively related at the 5% significance level to firm value relative to ERM3,whereas ERM4 and ERM5 are not close to having a significantly different effect on firmvalue relative to ERM3 Overall, Regression (4) suggests that firm value increases fromERM1 to ERM3, but beyond that, there is no significant difference in firm value betweenERM3, ERM4, and ERM5 firms

Together, these regressions indicate a positive relationship between ERM rating andfirm value up to about the ERM3 rating, but after that point, an increase in ERM ratingprovides no significant difference in performance results As discussed previously, we con-sider the ERM1 to ERM3 ratings to indicate an increasingly positive opinion of S&P aboutthe insurer’s implementation of TRM process, whereas ERM4 and ERM5 indicate that theinsurer has moved beyond TRM and has implemented ERM In other words, our resultssuggest that increasingly sophisticated TRM is related to higher firm value, but beyondthat, there is no apparent increase in firm value for insurers that implement ERM

Table 3 Pearson Correlation Coefficients

Firm

value

ERMrating Size

Financialleverage

Systemicrisk Profitability

Cash flowvolatility

Growthopportunities ComplexityFirm value 1.00

ERM rating 0.22 1.00

.08Size 0.11 0.58 1.00

.39 \.01Financial

leverage

20.18 20.09 20.48 1.00

.17 48 \.01Systemic risk 20.38 0.02 0.34 20.39 1.00

opportunities

0.11 0.06 0.06 0.05 20.25 0.48 0.13 1.00

.38 63 67 67 05 \.01 33Complexity 20.03 20.17 20.15 20.03 20.09 20.41 0.21 20.16 1.00

.84 17 26 84 51 \.01 14 24

Note: ERM = enterprise risk management This table provides the Pearson correlation coefficients for the ables Variable definitions are provided in Table 1 p values for the correlations are in italics.

vari-The results for four of our control variables are as expected: financial leverage, systemicrisk, and cash flow volatility are negative and significantly related to firm value, whereasprofitability has a positive and significant relation to firm value Unexpectedly, firm size isinsignificant in the regressions According to the Pearson correlation analysis in Table 2,size is significantly correlated with ERM rating We ran a regression alternately omittingsize and ERM rating from the regression The significance of ERM rating does not changewhen size is omitted, whereas size becomes significant when ERM rating is omitted, sug-gesting that the ERM rating variable co-opts the explanatory power of the size variable.Also against expectations, the growth opportunities variable is negative and significantlyrelated to firm value at the 10% level in Regressions (2) and (3) These results may be due

to the weakness of our proxy For growth opportunities, we use average sales growth overthe previous 5 years Most other risk management studies have been on samples of nonfi-nancial firms and use ratios such as annual ratios of capital expenditures or research anddevelopment to sales, which are not appropriate for financial firms Another explanationcould be that insurers are attempting to increase market share at the cost of firm value orare increasing premium revenue to be invested in the stock market at the expense of soundunderwriting

Table 4 Results of Regressions of S&P ERM Rating on Firm Value

Firm value

Coefficient p value Coefficient p value Coefficient p value Coefficient p valueIntercept 0.890 \.001*** 1.135 \.001*** 1.000 \.001*** 1.322 \.001***ERM rating 0.025 027** 0.026 034** 0.162 010***

volatility

21.177 018** 21.177 013** 20.899 075*Growth

opportunities

20.002 100* 20.002 068* 20.002 121Complexity 0.001 410 0.001 137 0.001 201Adjusted R2 072 535 586 593

Note: ERM = enterprise risk management This table shows the results of four different regressions of S&P ERM rating on firm value In Regression (4), ERM1 is set to 1 if the insurer’s S&P ERM rating = weak, 0 otherwise ERM2 is set to 1 if the insurer’s S&P ERM rating = adequate, 0 otherwise ERM3 is set to 1 if the insurer’s S&P ERM rating = adequate with a positive trend, 0 otherwise Note: ERM3 is omitted in the regression, so the other ERMn results are relative to ERM3 ERM4 is set to 1 if the insurer’s S&P ERM rating = strong, 0 otherwise ERM5

is set to 1 if the insurer’s S&P ERM rating = excellent, 0 otherwise The other variables are defined in Table 1.

***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively.

At the beginning of the article, we described several reasons that boards of directors arebecoming increasingly involved in risk management activities The regressions described inTable 4 do not control for differences in boards, which could be a possible source ofomitted variable bias Table 5 includes variables for additional testing that control for therelative strength and engagement of the board (and its committees) in risk oversight Oneway we control for differences in board activity is by adding a binary variable indicatingwhether the insurer is listed on the NYSE In 2003, the NYSE implemented new corporategovernance rules specifying that the internal audit function provides management and theaudit committee with ongoing assessments of the company’s risk management processesand system of internal control We also include a variable that indicates the percentage ofdirectors who are independent because Beasley et al (2005) had found that firms with ahigher percentage of independent directors were further along in implementing ERM.The results shown in Table 5 generally support our conclusion from the previous results.The S&P ERM rating variable is positive but not significant in Regression (1) However,the coefficients on the ERM rating variable and its square are even more significant inRegression (2) than in the previous regression that did not include the board-related vari-ables In Regression (3), ERM1 and ERM2 are still significantly negative relative to theomitted categorical variable ERM3, whereas ERM4 and ERM5 are not significantly differ-ent from ERM3 These results support our previous finding that indicate a positive

Table 5 Results of Regressions of S&P ERM Rating on Firm Value

Firm value

Coefficient p value Coefficient p value Coefficient p valueIntercept 1.164 \.001*** 1.036 \.001*** 1.318 \.001***ERM rating 0.018 184 0.144 032**

Note: ERM = enterprise risk management; NYSE = New York Stock Exchange This table shows the results of three different regressions of S&P ERM rating on firm value Ind Directors% is the percentage of directors on the

Exchange, 0 otherwise The other variables are defined in Tables 1 and 4.

***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively.

relationship between risk management level indicated by the S&P ERM rating and firmvalue up to the third level but no difference after the third level.

Conclusion

Managing risks has become a critical function for CEOs as organizational environmentsbecome increasingly turbulent and complex Traditionally, firms have managed risk insilos, and researchers have examined narrow slices of the corporate risk management spec-trum Previous empirical risk management research has investigated the relationshipbetween the hedging of financial risk using derivatives and firm value In recent years,some firms have started to adopt a more comprehensive approach, called ERM, butresearch on the relationship between ERM and firm value has been sparse We believe thatone main constraint that limited research in this stream was the lack of an effective proxyfor the degree of ERM capability and implementation We were able to overcome this con-straint by using a newly available measure of ERM (from S&P) that was comprehensive incharacter and overcomes some of the limitations of the earlier proxies that have been used

in ERM research

The overwhelming majority of empirical risk management research has investigatednonfinancial firms However, financial institutions are in the business of pricing risk andhave been leaders in implementing ERM Since 2007, S&P has incorporated an ‘‘ERMrating’’ for insurers in the overall ratings process We use this new rating in our model toinvestigate the relation between risk management and firm value Our interpretation ofS&P’s ERM rating is that the lower three categories (weak, adequate, and adequate with apositive trend) reflect increasing levels of TRM implementation S&P gives a ‘‘strong’’rating to insurers who have progressed beyond silo risk management We consider a strongrating to indicate that a firm has moved past TRM to ERM, and an excellent rating means

an even further move into ERM Based on that interpretation of the S&P ERM rating, ourresults suggest that firm value increases as firms implement increasingly more sophisticatedTRM but does not increase further as firms achieve ERM

Our results spawn a considerable number of questions for future research Why does astrong or excellent ERM rating not lead to higher firm value? Is it possible that a strongERM culture constrains firm growth that gets reflected in its market value? Is it possiblethat firms with strong ERM systems take bigger risks in areas that constitute their core cap-abilities (as they are expected to); however, environmental changes may have made theircore capabilities ineffective or irrelevant (Priem & Butler, 2001), thereby adversely affect-ing firms Is the relationship between ERM and firm value stable and true in the long run?That is, as other firms adopt ERM systems, practices, and culture, will the advantages ofERM adoption disappear?

Clearly, our setting is unique; financial firms’ value imploded as investors grew wary ofthe fallout of the subprime lending mess However, we expected that insurers with strong

or excellent ERM ratings would distinguish themselves particularly under these extremelyadverse situations This also begs the question: What would be the relationship betweenERM and firm value under more normal conditions? In the past, media reports have sug-gested that rating agencies have been suspected of offering ratings that are distorted bytheir business relationships with clients Do our results indicate a problem with S&P’s eva-luation or with the ERM construct itself? As the S&P ERM rating includes a firm’s riskmanagement culture, can firm ERM capabilities and ratings change rapidly? We expect to

continue our investigation into these questions as more years of ERM data becomeavailable.

S&P provides these separate ERM assessment ratings for insurance companies, and wecannot generalize the results outside the industry From 2010, S&P plans to start includingERM discussion into corporate credit rating reports for nonfinancial firms but has notdecided when or whether to produce a separate ERM component for these firms We willeagerly monitor S&P’s actions, and as more data become available, our future research willinvestigate the relation between ERM and firm value for firms outside the insurance indus-try to understand the effects of ERM based on industry differences

Research into ERM is just beginning, and as S&P expands ERM ratings to other tries, the pressure on firms to implement ERM will intensify If a higher degree of ERMimplementation does lead to higher firm value, what is the source of the value? Is it mainlydue to the TRM arguments for increased firm value related to the effects of cash flow vola-tility on asymmetric information, financial distress, or tax costs? Or is there some addi-tional benefit of ERM, such as managing risks in portfolios, strategically allocating capital

indus-to maximize risk-adjusted returns, or increased ability indus-to envision and deal with emergingrisks? That is, we need to unpack the source of value to understand how much of it isattributable to ERM that goes beyond the effects of TRM We believe these are interestingquestions that future research could investigate as more years of ERM data and otherproxies become available

Future work on a broad subject such as ERM can benefit from cross-disciplinaryresearch Just as firms are breaking down risk silos and implementing ERM, academicsmay have to cooperate across disciplines to gain a comprehensive understanding of ERM.For example, finance research has mainly focused on quantifiable, tactical risks, such asfinancial risks that can be hedged using derivatives in what we call TRM, but over the pastfew years, accounting and finance research has broadened to investigate ERM, while strate-gic management research has focused on strategic risks that can be mitigated using realoptions and scenario analysis We expect that such interdisciplinary research would lead tomore clarity on the relationship between ERM and firm performance

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/

or publication of this article

2 For risk management–related research for these items, see the following: tax payments (Graham

& Rogers, 2002; Leland, 1998; MacMinn, 1987; Mayers & Smith, 1982; Mian, 1996;Ross, 1996; Smith & Stulz, 1985); financial distress (Dolde, 1995; Haushalter, 2000; Mayers &Smith, 1982; Nance, Smith, & Smithson, 1993; Smith & Stulz, 1985); underinvestment(Bessembinder, 1991; Froot, Scharfstein, & Stein, 1993; Geczy, Minton, & Schrand, 1997;

Myers, 1977; Nance et al., 1993); asymmetric information (Breeden & Viswanathan, 1998;DeMarzo & Duffie, 1995); and undiversifiable stakeholders (Mayers & Smith, 1990; Stulz, 1984,1996; Tufano, 1996).

3 The studies listed so far involve financial risk management, specifically hedging using tives Until the late 1970s, risk management focused on reducing losses related to pure risks, that

deriva-is, hazard risks, and not reducing losses related to speculative types of risks, such as financialrisk Financial risk management did not become practical until the development of the options-pricing model by finance academics (Black & Scholes, 1973; Merton, 1973) This model gaverise to the derivatives industry, which allowed the hedging of financial risk

4 Financial institutions are excluded in previous risk management research using derivativesbecause financial institutions are both users and providers of derivatives

5 Pure risks are also known as hazard risks, which are typically insurable These are accidentalrisks for which there is no possibility of gain, such as property and liability risks, as opposed tobusiness risks, such as financial, operational, and strategic risks for which there is a possibility ofgain

6 The classic example of such ERM is an insurance company that sells life insurance and annuities

to similarly situated customers to hedge mortality risk Considering risks in a portfolio, life ance and annuities are natural hedges Hedging the risks separately through reinsurance is ineffi-cient Firm value can be increased by hedging only the residual risk of the portfolio Similarly,one subsidiary of a multinational company could be long on one currency, whereas another divi-sion could be shorting the currency; in this case, what is good for subsidiary managers may beinefficient for the firm as a whole

insur-7 Most of the information in this section comes from the following documents on Standard andPoor’s (S&P) website: Insurance Criteria: Refining the Focus of Insurer Enterprise RiskManagement Criteria (2006); Enterprise Risk Management: ERM Development in the InsuranceSector Could Gain Strength in 2008 (2008); and Enterprise Risk Management Is Improving inBermudan and North American Insurers (2008)

8 We only include insurers in our data set because at this time, S&P produces an ERM rating onlyfor insurers and not for nonfinancial firms An advantage of using only insurance firms is thatthese firms are in the business of pricing risk and thus should be further down the road in riskmanagement sophistication than nonfinancial firms An advantage of a single-industry study isthat we do not have to add variables to control for the considerable differences across industries

An obvious disadvantage is that we cannot generalize these results outside the insuranceindustry

9 The other seven components are financial flexibility, earnings, liquidity, management strategy,market position, investments, and capital adequacy S&P added the ERM component for insurersfirst and plans to add it later for nonfinancial firms Also, S&P does not include an ERM compo-nent for all insurers but is increasing the number over time

10 S&P uses the term ‘‘ERM rating’’ for these five categories to indicate the level of ERM mentation Although we use this S&P terminology in the remainder of this article, we considerthe ‘‘weak,’’ ‘‘adequate,’’ and ‘‘adequate with a positive trend’’ ratings to indicate increasingsophistication of traditional risk management (TRM) implementation and the ‘‘strong’’ and

imple-‘‘excellent’’ ratings to indicate increasing levels of ERM implementation In other words, weconsider these five levels to represent not five levels of ERM implementation, but five levels ofrisk management ratings, ranging from weak TRM to excellent ERM We thank an anonymousreviewer for pushing us toward this understanding

11 Our main source for independent director data was each insurer’s 10K form available in theEDGAR database For a few firms for which the data were not on the 10K, we found the datafrom other sources, such as the insurer’s website We could not find this data for 5 firms, so weomitted those firms in this regression and ended with a total of 77 insurers

Beasley, M S., Pagach, D P., & Warr, R S (2008) Information conveyed in hiring announcements

of senior executives overseeing enterprise-wide risk management processes Journal ofAccounting, Auditing, & Finance, 23, 311–332

Belsley, D A., Kuh, E., & Welsch, R E (1980) Regression diagnostics: Identifying influential dataand sources of collinearity New York, NY: John Wiley

Bessembinder, H (1991) Forward contracts and firm value: Incentives and contracting effects.Journal of Financial and Quantitative Analysis, 26, 491–532

Black, F., & Scholes, M (1973) The pricing of options and corporate liabilities Journal of PoliticalEconomy, 81, 673–684

Breeden, D., & Viswanathan, S (1998, February) Why do firms hedge? An asymmetric informationmodel (Working paper) Durham, NC: Duke University

Carter, D A., Rogers, D A., & Simkins, B J (2006) Does hedging affect firm value? Evidencefrom the US airline industry Financial Management, 35, 53–86

Chowdhry, B., & Howe, J T B (1999) Corporate risk management for multinationalcorporations—Financial and operational hedging policies European Finance Review, 2, 229–246.Cummins, J D., Lewis, C., & Wei, R (2006) The market impact of operational risk events for U.S.banks and insurers Journal of Banking and Finance, 30, 2605–2634

Cummins, J D., & Nini, G P (2002) Optimal capital utilization by financial firms: Evidence fromthe property-liability insurance industry Journal of Financial Services Research, 21, 15–53.DeMarzo, P M., & Duffie, D (1995) Corporate incentives for hedging and hedge accounting.Review of Financial Studies, 8, 743–771

Dolde, W (1995) Hedging, leverage, and primitive risk Journal of Financial Engineering, 4, 187–216

Fraser, J., & Simkins, B J (2010) Enterprise risk management: Today’s leading research and bestpractices for tomorrow’s executive Hoboken, NJ: John Wiley and Sons

Froot, K A (2007) Risk management, capital budgeting, and capital structure policy for insurers andreinsurers Journal of Risk and Insurance, 74, 273–299

Froot, K A., Scharfstein, D S., & Stein, J C (1993) Risk management: Coordinating corporateinvestment and financing policies Journal of Finance, 48, 1629–1658

Froot, K A., & Stein, J C (1998) Risk management, capital budgeting, and capital structure policyfor financial institutions: An integrated approach Journal of Financial Economics, 47, 55–82.Geczy, C., Minton, B., & Schrand, C (1997) Why firms use currency derivatives Journal ofFinance, 52, 323–354

Gordon, L A., Loeb, M P., & Tseng, C (2009) Enterprise risk management and firm performance:

A contingency perspective Journal of Accounting and Public Policy, 28, 301–327

Goyal, A., & Santa-Clara, P (2003) Idiosyncratic risk matters! Journal of Finance, 58, 975–1007.Graham, J., & Rogers, D (2002) Do firms hedge in response to tax incentives? Journal of Finance,

57, 815–839

Green, R C., & Rydquist, K (1997) The valuation of nonsystematic risks and the pricing of Swedishlottery bonds Review of Financial Studies, 10, 447–480.

Guay, W., & Kothari, S P (2003) How much do firms hedge with derivatives? Journal of FinancialEconomics, 80, 423–461

Hampton, J J (2009) Fundamentals of enterprise risk management: How top companies assess risk,manage exposure, and seize opportunity New York, NY: AMACOM

Haushalter, D (2000) Financing policy, basis risk, and corporate hedging: Evidence from oil and gasproducers Journal of Finance, 55, 107–152

Hoyt, R E., & Liebenberg, A P (2011) The value of enterprise risk management: Evidence from theU.S insurance industry Journal of Risk and Insurance Advance online publication doi: 10.1111/j.1539-6975.2011.01413.x

Jin, Y., & Jorion, P (2006) Firm value and hedging: Evidence from U.S oil and gas producers.Journal of Finance, 61, 893–919

Kim, Y S., Mathur, I., & Nam, J (2006) Is operational hedging a substitute for or a complement tofinancial hedging? Journal of Corporate Finance, 12, 834–853

Leland, H E (1998) Agency costs, risk management, and capital structure Journal of Finance, 53,1213–1243

Levy, H (1978) Equilibrium in an imperfect market: A constraint on the number of securities in theportfolio American Economic Review, 68, 643–658

Liebenberg, A P., & Hoyt, R E (2003) The determinants of enterprise risk management: Evidencefrom the appointment of chief risk officers Risk Management and Insurance Review, 6, 37–52.Liebenberg, A P., & Sommer, D W (2008) Effects of corporate diversification: Evidence from theproperty-liability insurance industry Journal of Risk and Insurance, 75, 893–919

Lintner, J (1965) The valuation of risk assets and the selection of risky investments in stock lios and capital budgets Review of Economics and Statistics, 47, 13–37

portfo-MacMinn, R D (1987) Forward markets, stock markets, and the theory of the firm Journal ofFinance, 42, 1167–1185

Markowitz, H M (1952) Portfolio selection Journal of Finance, 7, 77–91

Mayers, D., & Smith, C W., Jr (1982) On the corporate demand for insurance Journal of Business,

Mossin, J (1966) Equilibrium in a capital asset market Econometrica, 34, 768–783

Myers, S C (1977) Determinants of corporate borrowing Journal of Financial Economics, 5, 147–175

Nance, D R., Smith, C W., Jr., & Smithson, C W (1993) On the determinants of corporate ging Journal of Finance, 48, 267–284

Nelson, J H., Moffitt, J S., & Affleck-Graves, J (2005) The impact of hedging on the market value

of equity Journal of Corporate Finance, 11, 851–881

Pagach, D P., & Warr, R S (2011) The characteristics of firms that hire chief risk officers Journal

of Risk and Insurance, 78, 185–211

Pantzalis, C., Simkins, B J., Laux, P A (2001) Operational hedges and the foreign exchange sure of US multinational corporations Journal of International Business Studies, 32, 793–812.Priem, R L., & Butler, J E (2001) Is the resource-based view a useful perspective for strategic man-agement research? Academy of Management Review, 26, 22–40

expo-Ross, M (1996) Corporate hedging: What, why, how? (Working paper) Berkley: University ofCalifornia

Schrand, C M., & Unal, H (1998) Hedging and coordinated risk management: Evidence from thriftconversions Journal of Finance, 53, 979–1013

Sharpe, W F (1964) Capital asset prices: A theory of market equilibrium under conditions of risk.Journal of Finance, 19, 425–442

Shin, H H., & Stulz, R M (2000, June) Firm value, risk, and growth opportunities (Workingpaper) Columbus: Ohio State University

Smith, C W., Jr., & Stulz, R M (1985) The determinants of firms’ hedging policies Journal ofFinancial and Quantitative Analysis, 20, 391–405

Smithson, C W., & Simkins, B J (2005) Does risk management add value? A survey of the dence Journal of Applied Corporate Finance, 17, 8–17

evi-Sommer, D W (1996) The impact of firm risk on property-liability insurance prices Journal of Riskand Insurance, 63, 501–514

Stulz, R M (1984) Optimal hedging policies Journal of Financial and Quantitative Analysis, 19,127–140

Stulz, R M (1996) Rethinking risk management Journal of Applied Corporate Finance, 9, 8–24.Treynor, J L (1961) Market value, time, and risk Unpublished manuscript

Treynor, J L (1962) Toward a theory of market value of risky assets Unpublished manuscript.Tufano, P (1996) Who manages risk? An empirical examination of risk management practices in thegold mining industry Journal of Finance, 51, 1097–1137

Zhang, T., Cox, L A., & McShane, M K (2011, March) Risk allocation across the enterprise:Evidence from the insurance industry (Working paper) University Circle: University of Mississippi

Auditing & Finance 26(4) 659–676

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http://jaaf.sagepub.com

The Impact of IFRS on

Accounting Quality in a

Regulated Market: An

Empirical Study of China

Chunhui Liu1, Lee J Yao2,3, Nan Hu4, and Ling Liu4

Abstract

As more countries consider the adoption of International Financial Reporting Standards(IFRS) that are based on practices prevalent in the English-speaking countries with free mar-kets, it’s increasingly important to understand the impact of IFRS on countries of differentinstitutional, economic, and political environments This article reports a study that exam-ines the impact of IFRS on accounting quality in a regulated market, China, where new sub-stantially IFRS-convergent accounting standards became mandatory for listed firms in 2007.Accounting quality is examined for the period 2005 to 2008 with only firms mandated tofollow the new standards The empirical results generally indicate that accounting qualityimproved with decreased earnings management and increased value relevance of accountingmeasures in China since 2007 Firms audited by the Big Four are expected to have higherquality before the standard change evidenced quality improvement to a smaller extent.Further analysis shows that such changes are less likely to result from changes in economicconditions but from the changes of the standards Through the analysis of China’s adoption

of the new substantially IFRS-convergent standards, the study provides direct evidence onthe question of whether IFRS can be relevant to markets that are still disciplined mainly byregulators rather than by market mechanisms

Keywords

accounting quality, value relevance, IFRS, IFRS adoption, China

Global adoption of international accounting standards has been increasingly debated.Supporters of International Financial Reporting Standards (IFRS) argue that the use ofIFRS increases the quality of financial reporting and benefits investors (Daske, Hail, Leuz,

& Verdi, 2008) Opponents argue that a single set of standards may not be suitable for allsettings and thus may not uniformly improve value relevance and reliability due to