Family control and crash risk in East Asian firms: The mediating role of opacity

Hendra, Edwin; Utama, Cynthia Afriani; Lubis, Arief Wibisono; Suk, Kim Sung Article Family control and crash risk in East Asian firms: The mediating role of opacity Contemporary Economics Provided in Cooperation with: VIZJA University, Warsaw Suggested Citation: Hendra, Edwin; Utama, Cynthia Afriani; Lubis, Arief Wibisono; Suk, Kim Sung (2025) : Family control and crash risk in East Asian firms: The mediating role of opacity, Contemporary Economics, ISSN 2300-8814, University of Economics and Human Sciences in Warsaw, Warsaw, Vol. 19, Iss. 1, pp. 100-120, https://doi.org/10.5709/ce.1897-9254.556 This Version is available at: https://hdl.handle.net/10419/315388 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ www.ce.vizja.pl 100 This work is licensed under a Creative Commons Attribution 4.0 International License. This study examines family control's direct and indirect impacts (mediated by opacity) on crash risk in East Asian firms. We hypothesize that family control can mitigate agency problems of bad news hoarding due to increasing firm opaqueness. We chose six East Asia countries as the research sample due to their unique features that differ from developed countries, such as relatively weaker investor protection and higher earnings management practices that might positively contribute to firm opaqueness. Meanwhile, East Asian firms are also characterized by more concentrated ownership of family shareholders. Our research sample is 4,847 publicly listed firms (19,681 firm-year observations) in Hong Kong, Indonesia, Malaysia, Singapore, South Korea, and Taiwan from 2014 to 2019. This study primarily employs pooled OLS regression to test the hypotheses. As a robustness test, we conduct Fama-MacBeth regression to address the time-invariant property of family control measures and unobserved individual firm heterogeneity. This study finds robust results that family control negatively impacts crash risk, where this relationship is partly mediated by opacity. Therefore, we might argue that family control alleviates agency problems of bad news hoarding among East Asian firms. 1. Introduction1. Introduction Practitioners and academicians have paid more attention to the crash events since the cases of corporate scandals around the year 2000, such as Xerox, WorldCom, and Enron, and the global financial crisis 2008. As a result, scholars have explored various determinants to predict crash risk, developing the crash risk literature strand (Habib et al., 2018). Crash risk is the likelihood of a firmspecific (idiosyncratic) stock price crash caused by an all-at-once release of accumulated bad news. While stock price crashes frequently occur with unclear fundamental explanations (Chen et al., 2001; French, 1988), the earlier literature relates it to leverage effects (Christie, 1982), volatility feedback (Campbell & Hentschel, 1992; French et al., 1987; Pindyck, 1984), and bubble theories (Blanchard & Watson, 1982). Later, scholars postulate two streams of explanations for idiosyncratic crashes. First, the investor information-hoarding models suggest that informed investors conceal private information due to short-sale constraints and fixed setup costs of trading, which cause increasing trading volume and upward trend before a stock price crash (Cao Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity ABSTRACT G11. KEY WORDS: JEL Classification: crash risk, family control, opacity. 1 Universitas Bina Nusantara, Indonesia 2 Universitas Indonesia, Indonesia 3 Universitas Pelita Harpaan, Indonesia Correspondence concerning this article should be addressed to: Edwin Hendra, Universitas Bina Nusantara, Indonesia, E-mail: [email protected] Edwin Hendra1, Cynthia Afriani Utama2, Arief Wibisono Lubis2, Sung Suk Kim3 Primary submission: 28.10.2023 | Final acceptance: 13.06.2024 101 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 et al., 2002; Chen et al., 2001; Hong & Stein, 2003; Lv & Wu, 2019). Second, the manager informationhoarding models posit that opportunistic managers exploit information asymmetry (opacity) to conceal bad news from corporate outsiders (Jin & Myers, 2006), keeping overvalued stock prices to fulfill personal gains, such as higher stock-price-based compensation (Benmelech et al., 2010) and better access to cheaper capital (Jensen, 2004, 2005). To this extent, the second stream of crash risk explanations is grounded on the Agency Theory framework (Jensen & Meckling, 1976). Family presence in public corporations can mitigate agency problems (Type I) due to tight monitoring of family shareholders or direct control of family members involved in management (Fama & Jensen, 1983). Family shareholders are strongly incentivized to monitor managers due to their concentrated and under-diversified ownership (Kim et al., 2014). Meanwhile, family managers possess stewardship behavior, acting as loyal servants to the family (Davis et al., 1997). Hence, family firms are less opaque (Achleitner et al., 2014; Ali et al., 2007; Wang, 2006), thus less likely to hoard bad news. On the other hand, family firms might exacerbate agency problems (Type II) when entrenched managers side to controlling family, expropriating non-controlling shareholders via non-arm's-length transactions ("tunneling") (Morck & Yeung, 2003). In East Asia, Type II agency problems occur among firms with excess control over cash flow rights exercised via pyramid and cross-holding structures (Claessens et al., 2000, 2002). In addition, family firms tend to manage earnings to hide expropriation (Leuz et al., 2003), increasing the opacity (Anderson et al., 2009; Hsu et al., 2017), thereby more likely to conceal bad news. The theory and earlier empirical findings suggest that opacity is the channel that mediates crash risk; however, recent evidence reveals a different conclusion. Jin and Myers (2006) initially found a higher crash risk among more opaque countries. In addition, Hutton et al. (2009) find that firms with higher financial report opacity (accrual earnings management) also exhibit higher crash risk. Furthermore, Andreou et al. (2016, 2022) show that financial report opacity is limited in explaining crash risk. They argue that U.S. public corporations become more transparent post-Sarbanes–Oxley period because of stronger corporate governance functions that enhance board purview and oversight of management's actions. Nevertheless, it remains a question mark whether a similar phenomenon occurs among East Asian public firms. East Asia countries are interesting research contexts since they have unique features that provide a proper setting for our study. First, investor protection and law enforcement among East Asian countries are relatively weak compared to developed countries, leading to a more concentrated ownership structure (La Porta et al., 1998) and higher earnings management (Leuz et al., 2003). Second, most large public firms in East Asia are controlled by families (Claessens et al., 2000), where Type II agency conflicts are more common (Claessens et al., 2002). Third, as emerging economies, the financial market and corporate governance system are less developed; thus, East Asian countries might exhibit higher crash risk than developed countries due to higher stock price synchronicity and opacity. (Jin & Myers, 2006; Morck et al., 2000). According to the study background above, the extent literature leaves two research gaps. First, the impact of family control on crash risk has not been examined in East Asia countries, which have specific characteristics as mentioned above. Second, previous studies show mixed findings regarding the efficacy of opacity in explaining crash risk (Andreou et al., 2022; Hutton et al., 2009; Zachro & Utama, 2021). Third, to the best of our knowledge, the simultaneous relationship between family control, opacity, and crash risk has not been investigated. Therefore, this study fulfills these three research gaps by examining family control's direct and indirect impacts (mediated by opacity) on crash risk in East Asia. This paper provides several contributions to the literature. First, we examine the influence of family control on crash risk in the East Asian firms' context, where Type II (rather than Type I) agency problems are more prevalent among public corporations (Claessens et al., 2002). Therefore, our paper complements Srinidhi and Liao (2020), who examined the impact of family control on crash www.ce.vizja.pl 102 Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity This work is licensed under a Creative Commons Attribution 4.0 International License. risk among U.S. public corporations. Second, we reaffirm the relationship between family control and opacity in East Asian countries, where earnings management levels are higher due to relatively weak investor protection, more concentrated ownership, and less developed stock markets (Leuz et al., 2003); thereby, our paper extends Achleitner et al. (2014) and Hsu et al. (2017), who studied a similar topic using German and U.S. samples. Third, as the main contribution, this paper examines the mediating effect of opacity on the relationship between family control and crash risk using Muller et al.'s (2005) three-step procedure. Therefore, it differs from parallel studies examining the moderating effect of family control on the impact of busy directors (Zachro & Utama, 2021) and Corporate Social Responsibility (CSR) (Yang et al., 2023) on crash risk. Finally, this study responds to Andreou et al. (2022), who question the efficacy of opacity in channeling crash risk. 2. Literature Review and 2. Literature Review and Hypotheses DevelopmentHypotheses Development 2.1. Crash Risk Theories Crash risk theory falls into two broad categories: investor information hoarding and managerial hoarding models. The investor information hoarding models theorize that crash risk is the aftermath of delayed trading of investors, mainly when negative information occurs. For instance, the "information blockages" model posits that the "information pipeline" is intermittently "clogged" and then releases information in large lumps due to the presence of fixed setup costs of trading, such as brokerage fees and the time and attention required to execute a trade (Cao et al., 2002). In this setting, some investors prefer to delay their trading until the price movement validates their private signals. As a result, this model predicts negative (positive) skewness following stock price run-ups (rundowns). Alternatively, the "differences of opinion" model posits that stock price crashes occur following high trading volume, reflecting opinion differences between constrained bearish investors who cannot execute short-sale tradings (such as mutual funds) regarding the fundamental stock value (H. Hong & Stein, 2003). Instead, they prefer not to trade, acting as "support buyers" until the stock price drops to a desirable range. On the other hand, uninformed investors (arbitrageurs) can learn new information and decide to trade when these informed investors engage in the market, increasing trading volume further. The managerial information hoarding models theorize that crash risk results from bad information concealing by opportunistic managers. The "control and risk-bearing" model assumes that managers have two choices in addressing bad corporate performance, namely "bearing risk" and "abandonment" options (Jin & Myers, 2006). In a setting where the firm is partly opaque—outside investors cannot determine the true value of the firm; corporate insiders have incentives, such as to secure their job, to conceal the bad news as long as the firm can produce enough internal cash flow to fulfill investors' dividend expectations. However, after a series of bad performances, the internal cash flow would no longer be sufficient. Therefore, managers would exercise the "abandonment" option—announcing the hoarded bad news all at once, causing a stock price crash. The "dynamic rational expectation" model argues that fully stockbased compensation has downside consequences under an asymmetric information environment (Benmelech et al., 2010). When the company is not performing well, the manager has two options. First, they may immediately disclose this information to shareholders, letting the stock price decline. Second, they may conceal the bad news, keeping the stock price overvalued. The latter option is more tempting since it can maximize stock-based compensation but might lead to a stock price crash. 2.2. Crash Risk Determinants The extant literature on crash risk has examined various determinants of crash risk, classifying them into five categories: (a) financial reporting (corporate disclosure), (b) managerial incentives (characteristics), (c) capital market transactions, (d) informal institutional mechanisms, and (e) corporate governance mechanisms (Habib et al., 2018). Jin and Myers (2006) are among the earliest to study financial reporting-related determinants of 103 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 crash risk. They show higher stock-crash frequencies and stock-price synchronicity (R-squared) appear in more opaque countries. Hutton et al. (2009) show that firms with stronger earnings management practices (more opaque) have higher stock-crash frequencies and stock-price synchronicity and are more inclined toward crash risk. Salehi et al. (2022) find a negative relationship between the accounting quality, audit, auditor industry specialization and crash risk. Concerning managers' characteristics, firms managed by female CEOs exhibit lower crash risk (Li & Zeng, 2019), while firms managed by more powerful CEOs have higher crash risk (Al Mamun et al., 2020). Jebran et al. (2020) show that greater board diversity can mitigate crash risk. A higher likelihood of crash risk is also positively related to trading volume (Chen et al., 2001) and stock liquidity (Chang et al., 2017) as capital market transaction determinants. Crash risk studies with informal institutional mechanism determinants have developed rapidly in China. Piotroski et al. (2015) reveal that stock-price crashes are lower during political events but higher in the post-event years. Li and Chan (2016) find that state-owned enterprises where Communist Party of China committee members serve as directors have lower stock-price crash risk. Hu and Wang (2018) show that corporate political connections can mitigate crash risk. Jebran et al. (2019) find that the degree of informality among directors can exacerbate crash risk. Li and Jiang (2022) find a positive association between institutional investor networks and crash risk. Jebran et al. (2022) find a positive (negative) relationship between internal (external) board social capital and crash risk. On the contrary, Jin et al. (2022) find higher crash risk among firms in areas that adopt Confucianism. Finally, Chen et al. (2022) show that firms in regions with stronger tax enforcement exhibit lower crash risk. S. Li et al. (2023) find an inverse U-shaped relationship between the number of subsidiaries and crash risk. Aldhamari et al. (2023) found a lower crash risk among Malaysian firms with a stand-alone risk committee. In terms of the extent of the determinants of corporate governance mechanisms, Andreou et al. (2016) show that CEO's stock option incentives, transient institutional ownership, and outside directors' shareholdings exacerbate crash risk, while accounting conservatism, insider shareholding, board size, and companies' mandates of formal corporate governance policy alleviate crash risk. Finally, recent studies show that particular ownership structures, such as insider ownership (Hu et al., 2022), institutional crossownership (Hou & Liu, 2023), and institutional common ownership (Chen et al., 2024), have corporate governance functions that can mitigate crash risk. 2.3. Bad News Hoarding Channels The extant literature documents three bad news hoarding channels leading to stock price crash risk: opacity, overinvestment, and overvaluation. The opacity channel argues that managers conceal bad news via accrual earnings management practices (Hutton et al., 2009). The firm becomes more opaque as more bad news is hidden, causing the stock price to deviate from the true value and more prone to crashes (L. Jin & Myers, 2006). The overinvestment channel posits that managers conceal bad news by choosing sub-optimal investments to satisfy their interests (Benmelech et al., 2010). The overvaluation channel argues that managers have incentives to retain overvalued equity to gain benefits from stock-price-based compensation, precieived performance, and access to cheaper capital (Jensen, 2004, 2005). 2.4. Family Control and Crash Risk This study proposes the incentive hypothesis that family firms have the incentive to reduce opacity and bad news hoarding, thereby mitigating crash risk. Family firms possess unique characteristics, such as concentrated ownership (wealth) of family shareholders (Barontini & Caprio, 2006; Barth et al., 2005; Srinidhi et al., 2014) and involvement of family members (founder or founder's descendant) in top management or board positions (Ali et al., 2007; Anderson & Reeb, 2003, 2004). Therefore, family firms bear minimum or no agency problems (Type I) due to unified ownership and management (Fama & Jensen, 1983; Jensen & Meckling, 1976). Family shareholders are long-term-oriented investors (James, 1999); thus, family firms are less likely to be involved in practices that produce a short-term gain while sacrificing value www.ce.vizja.pl 104 Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity This work is licensed under a Creative Commons Attribution 4.0 International License. in the long run, which might tarnish the family's reputation (Cheng, 2014), such as bad news hoarding. However, family firms might increase their risk-taking behaviour during recession, such as during COVID 19 period (Al-Maliki et al., 2023). Meanwhile, family managers exhibit stewardship behavior; hence, they are less likely to conduct opportunistic practices that inflict a financial loss on family shareholders (Donaldson & Davis, 1991). Prior empirical studies show that family ownership is negatively associated with opaqueness to the extent of lower abnormal accruals (Wang, 2006), providing early warnings about incoming bad news (Ali et al., 2007), lower market opacity index (Hsu et al., 2017), and higher accounting conservatism (Avabruth et al., 2024). Family shareholders possess concentrated wealth in the company (Kim et al., 2014); hence, to the extent of higher cash-flow rights, family firms might exhibit the incentive effect (Claessens et al., 2002). Considering the arguments above, we propose the first hypothesis as follows: H1: Family control negatively impacts crash risk among East Asian firms. 2.5. Mediating Role of Opacity The "control and risk-bearing" theory suggests that opacity is the channel that facilitates bad news hoarding, which leads to a stock price crash. When the firm is partly opaque, outside investors can learn about macroeconomic but not firm-specific information indicated by a higher stock price synchronicity (R-squared). Jin and Myers (2006) find a positive relationship between R-squared, opaqueness, and crash risk. Alternatively, Hutton et al. (2009) posit that managers utilize accrual earnings management as the bad news hoarding vehicle, thus representing opacity for individual firms. Besides, they also found a positive relationship between financial report opacity and crash risk. Bad news hoarding mechanism via earnings management is consistent with the "equilibrium reporting strategy" model (Kirschenheiter & Melumad, 2002). The manager tends to under-report (over-report) over slightly good (bad) news to smooth earnings, adjusting its level to the investors' expected earnings. However, when the bad news is sufficiently large, the manager prefers a "big bath" strategy, underreporting at the maximum amount possible in the current period to report higher earnings in the future, causing an occasional stock price crash. Nevertheless, recent empirical evidence finds that financial report opacity is limited as an agency channel in explaining crash risk post-Sarbanes–Oxley period (Andreou et al., 2016, 2022). To this extent, family firms might avoid earnings management practices which can damage their reputation (Salehi et al., 2020). Considering the arguments above, we propose the second hypothesis as follows: H2: The relationship between family control and crash risk is mediated by opacity. 3. Methodology 3. Methodology 3.1. Data and Sample The research sample is publicly listed firms in six East Asian countries between 2014 and 2019 for which Thomson Reuters Eikon and S&P Capital IQ provide data on stock prices and financial reports, respectively. We deliberately do not use the year 2020 and after to avoid bias from the COVID-19 period on the stock market. Referring to Claessens et al. (2000) and Lins and Servaes (2002), we selected Indonesia, Hong Kong, Malaysia, Taiwan, Singapore, and South Korea as the research sample because these six countries are emerging economies in the East Asia region. Since the data are provided in U.S. dollars, we find no difficulties matching different currencies across countries. The S&P Capital IQ records 8,335 publicly listed firms (41,675 firm-year observations) together in selected six East Asian countries, excluding firms operating in the financial service industry. After screening out firms not listed on the major stock exchanges of a country and firms with no ownership data, the remaining sample consists of 6,810 publicly listed firms (34,050 firm-year observations). Finally, following Hutton et al. (2009), we eliminate firms operating in the financial service industry, firm-year observations with less than twenty-six weeks of stock-return data in a fiscal year, firm-year observations with a negative book value of equity, and firm-year observations with inadequate financial data to measure control variables. Thus, the final sample consists of 16,488 firm-year observations from 2014 until 2019. Table 1 provides details of this sample selection procedure. 105 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 3.2. Variables 3.2.1. Dependent Variables Crash risk: This study defines crash risk as the tendency of firm-specific stock price crashes in a year. Following prior studies, we proxy crash risk using three alternative measures. The first measure, the negative skewness coefficient (NCSKEW), is the negative value of the skewness of the firm-specific weekly abnormal return distribution (Chen et al., 2001), as presented in Equation (1). (1) The firm-specific weekly abnormal return is denoted by w i,t = ln(1+ε i,t ), where ε i,t is the regression residual of the expanded market model in Equation (2), (2) n is the number of weekly returns in a fiscal year, and t is the week in a fiscal year τ. The lead and lag terms of the stock return (r i ) and the market return (r m ) are included in the model to address nonsynchronous trading (Dimson, 1979). The second measure, the down-to-up volatility (DUVOL), is the natural logarithmic ratio of the standard deviation during the up weeks to the standard deviation during the down weeks (Chen et al., 2001), as presented in Equation (3). (3) This measure classifies down (up) weeks if the firmspecific abnormal weekly return is lower (higher) than the annual average weekly return, where n d is the number of down weeks, and n u is the number of up weeks. The third measure, the frequency of crash weeks (FREQ), is the number of firm-specific weekly abnormal returns that exceed two standard deviations below their mean value in a given year (Luo & Zhang, 2020). 3.2.2. Independent Variables Family control: This study defines family control as the controlling degree represented by ownership of the family shareholders—an individual or a nonpublic corporation other than a government, a governmentowned corporation, a public financial institution, or a public corporation (Claessens et al., 2000; La Porta et al., 1999). Although we realize that there are many alternative family control proxies in the literature, we represent family control with three measures due to the limitations of our data. The first measure, the family firm indicator (33%) (FAM33), is a binary indicator that classifies a firm as a family firm if the family is the majority shareholder with at least 33% of the ownership (Barth et al., 2005). The second measure, the family firm indicator (51%) (FAM51), is a more robust binary indicator that classifies a firm as a family firm if the family is the majority shareholder that owns at least 51% of the ownership (Barontini & Caprio, 2006). The third measure, the family ownership fraction (FAMOWN), is the fractional equity ownership of family shareholders (Anderson & Reeb, 2003). Opacity: This study employs the modified Jones's (1991) model, which is proposed by Dechow et al. Table 1 Sample Selection Description Number of firm-year observations Initial Observations 41,675 - Observations not listed on the major stock exchange of a country (3,315) - Observations with no ownership data (4,310) - Remaining Observations - Observations with less than twenty-six weeks of stock-return data in a fiscal year (6,071) - Observations with the negative book value of equity and inadequate financial data to measure control variables (8,120) Final Observations 19,859 www.ce.vizja.pl 106 Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity This work is licensed under a Creative Commons Attribution 4.0 International License. (1995) to proxy opacity (OPAQUE). This method involves two steps. We realize that this two-step procedure is limited to the extent that it can generate biased coefficients and standard errors, leading to incorrect inferences (Chen et al., 2018). First, we conduct crosssectional regression for each sample year to obtain the estimated regression coefficients ( , and ) with the model described in Equation (4), where ε i,τ , i, and τ represent error terms, firms, and years, respectively. (4) where total accruals (TA i,τ ) is calculated with Equation (5). (5) The discretionary accruals are computed by those parameter estimates, as described in Equation (6). (6) Second, financial report opacity for each firm-year observation is measured with the sum of the annual discretionary accruals' absolute values, as described in Equation (7). (7) Control variables: We refer to Chen et al. (2001) and Srinidhi and Liao (2020) in employing several variables to control stock trading and firm characteristics. Lagged crash risk (CrashRisk) captures the property of conditional skewness (Harvey & Siddique, 1999). Share turnover (TURN) represents the intensity of investors’ disagreements over the stock's true value (H. Hong & Stein, 2003). Stock return volatility (SIGMA) captures the “volatility feedback” property—a possibility of increasing volatility along with negative returns (Campbell & Hentschel, 1992). Yearly abnormal return (WRET) explains the “stock price reversal” or “stock price bubble” phenomenon (Blanchard & Watson, 1982). In addition to prior studies, we introduce a new control variable, information discreteness (ID), to reveal the degree of the information flow disclosed by the firm (Da et al., 2014). Firm size (SIZE) is an atheoretic control widely used in finance research. However, we can presume that the firm size is negatively associated with the incentive of managers to withhold bad news due to more scrutiny from outside investors and analysts (Chen et al., 2001). Leverage (LEV) captures the level of debt holders’ monitoring function in mitigating bad news hoarding (Wang et al., 2020). Return on assets (ROA) is an atheoretic control trepresentingprofitability. Since this study employs a cross-countries sample, we also added variables to control the fixed effect of country characteristics. The financial system dummy (FINSYS) captures differences between the market and bank-based financial systems (Maksimovic & Demirgüc-Kunt, 2002). The disclosure requirement index (DISCREQ) and anti-director rights score (ADRIGHT) represent the soundness of the corporate governance system (La Porta et al., 1998, 2006). The importance of the equity market score (IEM) captures the important role of the equity market (Leuz et al., 2003). Finally, yearly inflation (INF) and GDP per capita (GDPCAP) represent countries’ macroeconomic conditions. Table 2 presents details of names, symbols, and descriptions of all variables. 3.3. Empirical Models This study employs the three-step procedure proposed by Muller et al. (2005) To test H1 and H2, in the first step, we employ OLS regression using the pooled model on the empirical model described in Equation (8), which also infers H1. (8) The model above uses β 0 as a constant factor, β 1 as a coefficient of family control, β K as coefficients of control variables, ε i,τ as the error term, and i and τ to indicate firms and years, respectively. CrashRisk i,τ represents crash risk proxied by three alternative measures: negative skewness coefficient (NCSKEW), down-to-up volatility (DUVOL), and frequency of crash weeks (FREQ) of firm i in the year τ. Family i,τ-1 represents family control proxied by three alternative 107 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 Table 2 Definitions and Operations of Variables Variables Abbreviation Description Negative skewness coefficient NCSKEW The negative value of skewness of the firm-specific weekly abnormal return distribution (Chen et al., 2001). Down-to-up volatility DUVOL The natural logarithmic ratio of the standard deviation during the up weeks to the standard deviation during the down weeks (Chen et al., 2001). Frequency of crash weeks FREQ The number of firm-specific weekly abnormal return that falls more than two standard deviations below their mean value in a given year (Luo & Zhang, 2020). Family firm indicator (33%) FAM33 The dummy variable equals 1 if a family is the majority shareholder with at least 33% of the ownership and 0 otherwise (Barth et al., 2005). Family firm indicator (51%) FAM51 The dummy variable equals 1 if a family is the majority shareholder with at least 51% of the ownership and 0 otherwise (Barontini & Caprio, 2006). Family ownership fraction FAMOWN The fractional equity ownership of family shareholders (Anderson & Reeb, 2003). Opacity OPAQUE The sum of the annual discretionary accruals' absolute values (Hutton et al., 2009). Share turnover TURN Average monthly trading volume/number of shares outstanding (Chen et al., 2001). Stock return volatility SIGMA The standard deviation of firm-specific weekly abnormal return (Chen et al., 2001). Yearly abnormal return WRET The average firm-specific abnormal weekly returns times one hundred (Srinidhi & Liao, 2020). Information discreteness ID Da et al.'s (2014) information discreteness measure. Firm size SIZE Natural log of total assets. Leverage LEV Total debt/total assets. Market-to-book value MTB Market capitalization/total equity. Return-on-assets ROA Net income/total assets. Financial system FINSYS The dummy variable equals 1 for a market-based country and 0 for a bank-based country (Maksimovic & DemirgücKunt, 2002). Disclosure requirements index DISCREQ The disclosure requirements index of one country (La Porta et al., 2006). Anti-director rights score ADRIGHT The anti-director right score of one country (La Porta et al., 1998). Importance of equity market score IEM The importance of the equity market score of one country (Leuz et al., 2003). Inflation INF The inflation of one country in a fiscal year. Gross domestic product per capita GDPCAP Natural log of the GDP of one country in a fiscal year. www.ce.vizja.pl 114 Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity This work is licensed under a Creative Commons Attribution 4.0 International License. this result is consistent with Andreou et al. (2016, 2022) while negating Hutton et al.'s (2009) finding. 4.3. Robustness Tests This study employs Fama and MacBeth's (1973) regression to address the time-invariant property of family control and unobserved individual heterogeneity as a robustness check. The Fama–MacBeth regression deals with panel data by employing the ordinary least square in two steps. First, the crosssection observations for each year (or any period frequency) are regressed to obtain the yearly slopes. 115 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 Second, the t-statistic for hypothesis testing is obtained by dividing the time-series average of the yearly slope by its time-series standard error. Table 8 presents the Fama-MacBeth regression results of the impact of family control on crash risk while controlling for other independent variables. Consistent with the main analysis, the negative influence of family control on crash risk is significant at the 5% level, except in column (8). Table 9 presents the Fama-MacBeth regression results of the impact of family control on opacity while controlling for other independent variables. Also consistent with the OLS regression, we find a negative effect of family control on opacity that is significant at the 5% level in all columns. Table 10 presents the Fama-MacBeth regression results of the impact of family control and opacity on crash risk. Significant and lower magnitude family control coefficients than those in Table 8 consistently show the partial mediation role of opacity on the www.ce.vizja.pl 116 Family Control and Crash Risk in East Asian Firms: The Mediating Role of Opacity This work is licensed under a Creative Commons Attribution 4.0 International License. relationship between family control and crash risk. Finally, Fama-MacBeth regression analyses show that our hypotheses are robust after addressing the time-invariant limitation of family control measures and unobserved individual firm effect, which might bias the previous OLS regression analyses. 5. Conclusions5. Conclusions Crash risk, the likelihood of a firm-specific stock price crash, has caught the attention of stock market practitioners and academicians. A frequent firmspecific stock price crash might erode investors' confidence in stock investing (Merton, 1987), causing difficulties for managers in finding equity financing. Therefore, scholars explore various observable determinants that might predict stock price crashes, contributing to the literature strand of crash risk (Habib et al., 2018). The theory suggests that a stock price crash results from bad news hoarding driven by managers' motives to secure their jobs (Jin & Myers, 2006) and maintain stock-based price compensation (Benmelech et al., 2010). Therefore, crash risk reflects Type I agency problems when managers opportunistically conceal bad news, making the stock price overvalued (Jensen, 2004, 2005). However, in East Asian countries, where investor protection is relatively weaker (La Porta et al., 1999) and ownership structure is more concentrated on a single shareholder, particularly family (Claessens et al., 2000), the crash risk might indicate Type II agency problems (Claessens et al., 2002). This study examines family control's direct and indirect effects on crash risk in East Asian firms. As the main contribution, we investigate whether opacity can mediate the relationship between family control and crash risk. First, our results suggest that family control has a direct negative impact on crash risk and opacity. Therefore, it is consistent with the incentive hypothesis that family control mitigates bad news hoarding practices indicated by lower opacity and, consequently, lower crash risk; thus, we may argue that East Asian family firms commonly exhibit fewer agency problems. These findings are consistent with Srinidhi and Liao (2020), Wang (2006), and Hsu et al. (2017), who find a lower crash risk and accounting opacity among family companies. Second, we find that opacity partly mediates the relationship between family control and opacity. This result then complements Andreou et al. (2016, 2022), who questioned the efficacy of financial report opacity as the agency channel of crash risk. To this extent, this study suggests that, though opaqueness is limited as a direct channel, it still contributes as a mediating channel that conveys crash risk. This study also has limitations, leaving room for further research. First, this research limits its sample to firms operating in non-financial industries; thus, the next researcher could examine a similar topic specifically among public financial companies. Second, we limit control variables to corporate and country characteristics to address fixed effects among firms and across countries. Nevertheless, we realize that there are various crash risk determinants from corporate governance aspects at the firm level (Andreou et al., 2016) and differences in corporate governance systems and institutional contexts across countries (L. Jin & Myers, 2006; Leuz et al., 2003). Therefore, we suggest a further cross-countries study to conduct sensitivity analyses involving corporate governance aspects (such as board structure and processes), corporate governance systems, and institutional contexts that might moderate the effect of family ownership on crash risk. Third, the dependent variable of family control possesses a timeinvariant property. With an assumption that there will not be many changes in the firm’s ownership, this research sample utilizes recent data on firm ownership limited to the first layer only in classifying family firms. Then, it applies them uniformly to each firm-year observation. Fourth, we limit the family owner definition to an individual or a nonpublic corporation other than a government, a government-owned corporation, a public financial institution, or a public corporation (Claessens et al., 2000; La Porta et al., 1999). To this extent, we encourage further research that identifies family firms according to the control rights of family shareholders, as in Claessens et al. (2000, 2002). We also suggest a further study to examine the ownershipcontrol wedge's impact on crash risk, as in H. A. Hong et al. (2017), among family and non-family firms. This study might provide practical insights to investors and managers. Individual investors might consider investing in family-controlled public companies due to the advantages of lower accrual earnings management and lower stock price crash risk; thus, family ownership can substitute the corporate governance monitoring function. Although it is still unclear 117 Adrian Peretz and Fred Strønen 10.5709/ce.1897-9254.556DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 1 100-1202025 whether financial report opacity is inherent in crash risk (Andreou et al., 2022; Zachro & Utama, 2021), this study shows that opacity partly mediates the crash risk-mitigating effect of family control. Meanwhile, this study suggests that family firms' managers to be aware of family shareholders' priorities in long-term investment orientation (James, 1999) and conserving the family's reputation (Cheng, 2014); thus, they are better off disclosing bad news immediately rather than hoarding it. ReferencesReferences Achleitner, A. K., Günther, N., Kaserer, C., & Siciliano, G. (2014). Real earnings management and accrual-based earnings management in family firms. European Accounting Review, 23(3), 431–461. https://doi.org/10.1080/09638180.2014.895620 Al-Maliki, H. S. N., Salehi, M., & Kardan, B. (2023). 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