Are family firms financially healthier than non-family firm?

Ntoung, Lious Agbor Tabot; de Oliveira, Helena Maria Santos; de Sousa, Benjamin Manuel Ferreira; Pimentel, Liliana Marques; Bastos, Susana Adelina Moreira Carvalho Article Are family firms financially healthier than non-family firm? Journal of Risk and Financial Management Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Ntoung, Lious Agbor Tabot; de Oliveira, Helena Maria Santos; de Sousa, Benjamin Manuel Ferreira; Pimentel, Liliana Marques; Bastos, Susana Adelina Moreira Carvalho (2020) : Are family firms financially healthier than non-family firm?, Journal of Risk and Financial Management, ISSN 1911-8074, MDPI, Basel, Vol. 13, Iss. 1, pp. 1-18, https://doi.org/10.3390/jrfm13010005 This Version is available at: https://hdl.handle.net/10419/239100 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/ Journal of Risk and Financial Management Article Are Family Firms Financially Healthier Than Non-Family Firm? Lious Agbor Tabot Ntoung 1,*, Helena Maria Santos de Oliveira 2,* , Benjamim Manuel Ferreira de Sousa 2, Liliana Marques Pimentel 3and Susana Adelina Moreira Carvalho Bastos 2 1Department of Economics, University of Buea, Buea 00237, Cameroon 2School of Accounting and Administration of Porto (ISCAP), Polytechnic Institute of Porto (IPP), 4200-465 Porto, Portugal; [email protected] (B.M.F.d.S.); [email protected] (S.A.M.C.B.) 3Department of Economic, University of Coimbra, 3004-531 Coimbra, Portugal; [email protected] *Correspondence: [email protected] (L.A.T.N.); [email protected] (H.M.S.d.O.) Received: 19 October 2019; Accepted: 23 December 2019; Published: 29 December 2019   Abstract: This study examines the whether or not family firms are financially healthier than non-family in terms of capital structure and leverage. It therefore takes into consideration the existence of any significant differences between the leverage and risk choices of family and non-family firms. Using a panel data set of 888 firms and 7104 firm-year observations of unlisted small and medium size firms over the period 2007–2014, we present that family owned businesses have lower financial structure than those of non-family owned businesses. This indicates that most family firms use less debt financing than non-family firms, and as such maintain a lower level of debt. Secondly, family firms demonstrate lower risk as illustrated by the Altman Z-score. The Altman Z-score scale illustrates a contrary relationship of significance with respect to family firms and their counterparts in terms of the operation aspect of the business’s risk factors. Family firms managed their business operations with lower risk and are generally healthier financially than their counterpart firms. Lastly, findings from the robust tests for the hypotheses using a sample of bankrupt firms in Iberian Balance sheet Analysis System (SABI) reveal that the proportion of failure of family firms as opposed to their counterpart firms is relatively low. Analyzing the bankruptcy files of firms from 2002 to 2014 shows a considerably low ratio of family firms at the 5% significant level. This affirms that the low risk illustrated in the Altman Z-score regression is consistent to the lower ratio of family firms that were declared bankrupted over the study period, which makes Spain an important case in this study. Keywords: capital structure; family firms; leverage; non-family firms; risk JEL Classification: G1; G32; G38 1. Introduction and Literature Review Following the evidence cited by several researchers over the years (such as Shleifer and Vishny 1986;DeAngelo and DeAngelo 2000;Anderson and Reeb 2003), one principal characteristic to influence the management of firms is that of its risk profile. Even though very little empirical research has shown light on this topic, the small amount of existing empirical research suggests that the characteristics of family owned companies could be a possible reason for family business risk aversion and the choice of capital structure. Anderson and Reeb (2003) argue that the agency problems that exist between management and stakeholders is reduced when the structure of a family firm is adopted by a company. They suggest J. Risk Financial Manag. 2020,13, 5; doi:10.3390/jrfm13010005 www.mdpi.com/journal/jrfm J. Risk Financial Manag. 2020,13, 5 2 of 18 however that the risk averse nature of the controlling families is disintegrated through monitoring. DeAngelo and DeAngelo (2000) add that the risk nature of family firms achieved through engaging in lower risky activities that promote net present value by large and undiversified shareholders might impose costs to well-diversified shareholders with minority power. Following the illustration in (Miller et al. 2007;Villalonga and Amit 2006;Pison et al. 2014), 65%–80% of firms around the world are managed by one or more families, and generate approximately 70%–90% of the gross domestic product. Neubauer and Lank (2016) add that family owned businesses create approximately 70%–80% of jobs on a yearly basis. Meanwhile, evidence from the European Family Businesses (2012) present that over the globe, 85% of business startups are family orientated. The fundament reason for the said study using Spain as the case is due to the peculiarities of the Spanish system being made up of approximately 90% family orientedbusinesses contributing to 60% of the country’s GDP. In (P é rez and Lluch 2015;Pison et al. 2014;European Family Businesses 2012), family-oriented businesses generate over two-thirds of the total employment, and often these firms are thought to be small and medium size enterprises. Yet little attention has been provided to the financial health of the business in terms of capital structure and leverage. A review of both management and finance empirical evidence regarding the risk profile of family businesses suggests the main hypothesis that family-oriented businesses have lower leverage and lower risk, which could actually benefit the company during times of economic downturn. Thus, from a financial standpoint, this paper presents indicators that are specific to family-orientedbusiness with long-time horizon, family orientation, and generational continuity as potential reasons for family business risk aversion and the choice of capital structure for medium and small oriented family companies in Spain. In order to answer the hypothesis, we first examine the characteristics of family firms in term of the operation aspect of the business’s risk factors and whether family firms managed their business operations with lower risk and are generally healthier financially than their counterpart firms. Next, we examine a series of bankruptcy filings in Spain from 2002 to 2014 and evaluate the proportion of family businesses in the sample. Accordingly, March and Shapira (1987) consider decision investment as the deal between expected return and risk per the conventional theory. Masulis (1988, pp. 14 − 16) suggests that “managers in both family and non-family businesses will prefer having less leverage than shareholders in order to reduce the risk of their undiversified investment in the company”. Consistent with this view, Grossman and Hart (1986) argue that increased leverage reduces the agency cost of type I associated with managerial discretion and managers’ discretion over corporate decisions. In Bangladesh, Dey et al. (2018) present findings of financial risk disclosure indices in annual reports of 48 manufacturing companies over six-year period (2011–2015) using 30 disclosure identifiers. Their results show that there is a positive and significant relationship between the level of financial risk disclosure and firm size, financial performance, and auditor type. A more recent study suggests “that risk is an unavoidable part of life, including business life and therefore, it exists in the content of uncertainty” (Garland 2003, p. 4). Furthermore, “it is no surprise that predicting the future is an uncertain task, involving, at best, probabilities, and inferences since the memory of the past is sometimes flawed and our knowledge of the present is incomplete” (Garland 2003, pp. 4–5) .Hollenbeck et al. (1994) find that individuals treat risk as a dynamic factor, because the future carries its opportunities as well as it risks. They add that the “perspective of change in value rather than total value to evaluate a decision and to separate gains but not losses from initial outlay” is preferred by most risk analysis treating risk as a dynamic factor. Furthermore, Bernstein and Bernstein (1996) add that the nature of risk has been sharp by the time horizon. May (1995) posits that the reason behind managers using only approximate time frames in their planning rather than the accurate time forecast is due to the personal risk when making decisions regarding firms risk. De Vries (1993) add that family businesses have a longer-term perspective than non-family businesses, (Oswald and Jahera 1991;Ntoung et al. 2016a), which may “improve J. Risk Financial Manag. 2020,13, 5 3 of 18 decision-making resulting in higher earnings and dividends. After controlling for a variety of factors that affect cross-sectional debt levels among all firms”, Mishra and McConaughy (1999) conclude that family-controlled firms using less debt. This is indeed true because the use of less debt creates the founding family’s aversion to the risk of loss of control. 2. Family Control and Firm Value Family control businesses have been debated over century by prior research that it enhances family firm value. Some classical research argues that the ownership structures in widely held firms create opportunities for conflicts of interest between managers and shareholders. This can reduce the value of the firm since managers of such firms are more concerned about the maximization of private benefits at the expense of the owner of the firms (Agency Cost of Type I). Other school of thought claim that the most suitable instrument to correct the action of such sulphurous management behaviour is through concentrated ownership, (Ntoung et al. 2017, p. 127). For instance, in (Ntoung et al. 2016a) (Jensen and Meckling 1976;Sraer and Thesmar 2007) claim that separation between ownership and control can involveimportant costs and problems forshareholders. Their classical agency problem suggests that one way to resolve the conflict of interest between shareholders and managers is to increase the proportion of shares in the hands of the controlling shareholder. “In light of the above, minority shareholders are victimised as ownership becomes more concentrated, while controlling shareholders tend to engage in undesirable behaviours. In a similar way, Schulze et al. (2001) examine the consequences of altruism concept and pay of incentives by controlling shareholder, and their influence in the level family firm’s performance. They affirm that family firms with concentrated ownership are more exposed to agency danger. Chrisman et al. (2004) conclude that agency cost affects the performance of family business. Researches in Austria, Italy, and Spain show a positive and signification relationship between incentive and performance”, (Ntoung et al. 2016b). Furthermore, Asghar Butt et al. (2018) add that most family owners are less likely to use derivatives for hedging purposes as compared to non-family owners. Examining corporate derivatives and the ownership concentration of 101 Pakistani non-financial firms over the period 2012–2016, they concluded that non-family firm are more likely to use derivativemeasures to increase the value of their stocks. Meanwhile, Yang et al. (2018) conclude by attesting that in order to perform risk management practices in a way that will guarantee competitive position in the market, the top management need to have enough financial skills. Finally, “their findings suggest that these characteristics of family firms do influence their performance. In Europe, Barontini and Caprio (2006) provide similar evidence to those of Villalonga and Amit. According to them, family firms with a founder or descendants as CEO or Chairman outperform other firms. However, family firms with a founder as CEO outperform family firms with descendants as CEO. Also, if no member of the family is involved in the management (passive), then the firms perform worse” (Ntoung et al. 2017, p. 125). Hypotheses With respect to the mixed empirical evidence from prior research, one can clearly argue that financial and capital structure choices by family businesses are motivated by the level of risk assumed. Anderson and Reeb (2003) argue that “the principal-agent cost and the asymmetric information between shareholders and managers” is reduced when a structure of family firm is adopted in a company. They suggest however that the risk averse nature of the controlling families is disintegrated through monitoring. DeAngelo and DeAngelo (2000) add that the risk aversion of family companies is achieved through avoiding high risk projects even when they have positive net present value as large and undiversified shareholders might impose costs to well-diversified shareholders with minority power. Thus, our first hypothesis: Hypothesis 1 (H1). Family firms have lower leverage than non-family peers. J. Risk Financial Manag. 2020,13, 5 4 of 18 Hypothesis 2 (H2). Family owned companies are less risky than non-family firms. These hypotheses suggest that family owned firms possess some characteristics, such as family legacy, generational succession, and longer-term horizons, which might potentially be responsible for the capital structure choice and make family business more risk averse and conservative. 3. The Hypothesis, Methods and Data 3.1. Empirical Model This study examines if family firms are financially healthier than their counterpart firms. This led us to two specific factors that determine the financial health of the firm as shown in Sections 3.1.1 and 3.1.2 below. 3.1.1. Leverage “We use a panel regression analysis to evaluate whether a family owned company has a different level of leverage to a similar non-family” (Ntoung et al. 2017) to examine the level of a firm’s leverage (debt/EBITDA ratio and interest coverage ratio). One reason for excluding the usual ratio of debt/capital is because it is influenced not only by the choice of debt level the company makes, but also by the level of equity the company has. Also, the debt/capital ratio induced the market perception of the firm into the equation, thus it wouldn’t provide aclean estimate of the leverage choices made by the firm. We run five regression equations regarding our two dependent variables for leverage. The regression equation is illustrated as follows: Leverage =α1×(Family dummy) +α2×Age +α3×Size measure +α4×Industry Dummy +α5×Profitability measure +α6×Interactive Variables (1) where, Leverage: Debt/EBITDA and Interest Coverage Ratio. Family firm takes: dummy equals 1 when a firm is a family firm or zero otherwise Profitability measure: refers to return of equity, return on assets, EBITDA margin, netincome margin Size measure: refers to number of employees, total revenues, total assets Age: calculate based on the company date of establishment. Industry dummy: equaling 1 as dummy for each IAC classification code, Year dummy: equals 1 for each year considered in the analysis. Furthermore, to correct the presence of heteroskedasticity and serial correlation in the data, we employ the Huber–White sandwich estimator for variance (Ntoung et al. 2017). 3.1.2. Risk Exposure “To critically analyze the risk profile of family businesses as opposed to their non-family peers, it is vital to examine beyond leverage, factors that reflect overall risk. We further evaluate these factors by employing the Altman Z-score, a predictive model developed to determine acompany’s probability of filing for bankruptcy in the next subsequence of years and to measure the overall financial health of a company” (Ntoung et al. 2016b). Altman Z-score: We consider the Altman Z-score as a dependent variable. “The choice of variable regarding a company risk’s of survival was based on four balance sheet and income statement variables, namely profitability, leverage, solvency, liquidity, and activity. The result of the combination of ratios gives rise to a discriminantscore, otherwise called the Z-Score. The ratios are X 1 =working capital/total assets, X 2 =retained earnings/total assets, X 3 =earnings before interest and taxes/total assets, X 4 = market value of equity/book value of total debt, and X 5 =sales/total assets. In 1998, Altman redefined J. Risk Financial Manag. 2020,13, 5 5 of 18 his model by excluding X 5 (sales/total assets) to forecast the corporate risk of survival for manufacturing firms in Mexico. The weighted coefficients thus have different values” (Ntoung et al. 2017). Z” =6.5X1+3.2X2+6.72X3+1.0X4(2) Source: Altman et al. (1998, p. 3). The analysis of family business risk characteristics using Altman Z-score provides information about risk exposure the company is willing to take on, hypothesizing that family firms would have a tendency to be more risk averse, if all things being equal. We run five regression equations regarding our two dependent variables for leverage. The regression equation is illustrated as follows: Altman Z-Score =α1×(Family dummy) +α2×Age +α3×Size measure +α4×Industry Dummy +α5×Profitability measure +α6×Interactive Variables (3) where, Altman Z-Score: 6.5X1+3.2X2+6.72X3+1.0X4 Family firm takes: dummy equals 1 when a firm is a family firm or zero otherwise Profitability measure: refers to return of equity, return on assets, EBITDA margin, netincome margin Size measure: refers to number of employees, total revenues, total assets Age: calculated based on the company date of establishment. Industry dummy: equaling 1 as dummy for each IAC classification code, Year dummy: equals 1 for each year considered in the analysis. Furthermore, to correct the presence of heteroskedasticity and serial correlation in the data, we employ the Huber–White Sandwich estimator for variance (Ntoung et al. 2017). 3.2. Data In this section we examine the hypothesis that family owned companies have lower leverage and lower risk than non-family peersof unlisted small and medium size sing data constructed based on the Iberian Balance sheet Analysis System (SABI) of the Bureau Van Dijk, containing detailed financial information on more than 2,000,000 Spanish businesses. Next, we employ the IAC2015 classification code excludingall financial and utilities firms using the industry classification. The reason for the exclusion of firms in these industries is due to the fact that firms are strongly regulated and influenced by the government. We also excluded all firms with incomplete accounting information. Our final sample consists of 888 firms and 7104 firm-year observations of unlisted small and medium size firms over the period 2007–2014. The study is based on Spain because Spain was one of the European countries that suffered greatly duringthe 2008 financial crisis. Many small and medium size businesses experienced bankruptcy and, as a result of this, it reveals an important case to study. We were interested to investigate whether the businesses failure was due to a high leverage or risk profile. 3.3. Variables Measurement 3.3.1. Dependent Variables Leverage is measured using the debt/EBITDA and interest coverage ratio and Altman Z-score. This is consistent with (Shleifer and Vishny 1986;DeAngelo and DeAngelo 2000; Anderson and Reeb 2003). 3.3.2. Independent Variables—Ownership structure The criteria used for the ownership structure of firms in Spain are based on the Iberian balance sheet analysis system (SABI). These criteria focus on the holding of a shareholder’s ultimate voting J. Risk Financial Manag. 2020,13, 5 6 of 18 rights across these firms, which differ from the ultimate cash flow rights. In cases where information was available about the ownership structure of a company, we search this property directly on the company websites. Firms in Spain were classified through the aid of the BvD independence indicator available in SABI. The BvD independence indicator has five levels, namely “A”, “B”, “C”, “D”, and “U”. According to SABI, independent indicator “A” denotes that a company is said to be independent if the shareholder must be independent by itself (i.e., no shareholder with more than 25% of ownership of ultimate voting rights), whereas independent indicator “B” is when no shareholders with more than 50% exist but one shareholder with voting rights between 25.1% to 50%. For a company to be classified with independent indicator “C”, the company must have a recorded shareholder with a total or calculated ownership of 50.1% or higher, whereas a company is classified as “D” when a recorded shareholder demonstrates direct ownership of over 50% with branches and foreign companies (Ntoung et al. 2017). Independent indicator “U” is applied when a company does not fall into the categories “A”, “B”, “C” or “D”. Based on the above features and prior studies, a company with a shareholder having more than 25% is classified as family-run firm, while firms with no shareholder with more than 25% areclassified as widely held firms. This threshold of 25% allows shareholder to have significant influence on the firm. Therefore, firms categorized as “A” are widely held firms while firms in “B”, “C”, and “D” are family firms. Our next criteria for family is that, in a family firm, an individual or a family must be the largest shareholder and be categorized in “B”, “C”, and “D”. The individual must be part of the founding family. If this is not the case, the controlling shareholder must have had the largest percentage of ultimate voting right over a long time period.For each firm, we identify founding family presence using information provided by SABI about corporate proxy statements on board structure and characteristics, ECO attributes, equity ownership structure, and founding-family attribute” (Ntoung et al. 2017). In case where there weremissing data, we directly search the company website for extra detail. 3.3.3. Other Independent Variables Profitability measure refers to the return of equity, return on assets, EBITDA margin, and net income margin. Size measure refers to number of employees, total revenues, and total assets. Age is calculated based on the company’s date of establishment. Table 1provides a detailed definition of the variable used. 3.4. Descriptive Statistics Table 2shows a simple t-test analysis and itssignificance of the difference between family and non-family firms on each of the independent variables used in this study. With respect to the dependent variables, from our t-test presented in Table 2, both family and non-family firms exhibit the same risk profiles, even though family firms seem to be less risky than non-family firms. However, further examination is needed for the relationship between the variables in the form of regression estimates while controlling for other possible explanations for the outcome, as revealed in the t-test. Also, the outcomes of the different t-tests indicate that most of the controlling variables are different for both family and non-family firms. With respect toprofitability measures, non-family firms appear to be more profitable than their peers. The proxy of age reveals that family firms have a longer time-horizon than non-family firms. Lastly, across the different industrial sectors, the outcome from the t-test shows that, for construction, other services, and restaurant and lodging trades, family firms significantly dominate their non-family counterparts. However, for transport, communication, management and insurance activities, as well as energy, water, and metal transforming industries, non-family firms significantly dominate family firms (See Table 2). J. Risk Financial Manag. 2020,13, 5 7 of 18 Table 1. Definition of variable. Dependent Variables Debt/Earnings before interest, tax, depreciation and amortization (EBITDA), Interest Coverage Ratio and Altman Z-Score. Independent Variables “A” “Indicates a dummy equaling 1 if no shareholder with more than 25% of ownership of ultimate voting rights);” “B” “Indicates a dummy equaling 1 if no shareholder with more than 50% but exist one shareholder with voting rights between 25.1% and 50%.” “C” “Indicates a dummy equaling 1 if a recorded shareholder with a total or a calculated ownership of 50.1% or higher” “D” “Indicates a dummy equaling 1 if a recorded shareholder with a direct ownership of over 50% with branches and foreign companies” Family Firms “B”, “C” and “D” Non-family firms “A” Family characteristics “A family member is CEO, Chairman, CEO and Chairman, respectively in a family firm; the family only holds shares in the company without taking an active position; and the founder or a descendant is actively managing the company as Chairman or CEO.” Widely held corporation “Denote a dummy variable 1 if the largest ultimate shareholder owns more than 25% of the shares in one of the categories.” Profitability measure ROA, ROE, EBITDA margin, and Net income margin. Size measure Number of employees, total revenues, and total assets. Firm age “Defined the logarithm of the date of establishment” Industry “Defined according IAC classification code” J. Risk Financial Manag. 2020,13, 5 8 of 18 Table 2. Descriptive Statistics. Descriptive Statistics All Sample Non-Family Firms Family Firms Difference in mean (Non-Family-Family Firms) t-Test Mean Std. Mean Std. Mean Std. Independent Variables Number of Employees 110.79 96.77 123.63 221.34 112.78 73.17 10.85 1.41 Total Assets 20,108.90 14,480.30 18,331.50 9231.54 26,191.18 27,523.31 −7859.66 −8.248 * Total Revenue 20,206.30 13,224.60 19,062.50 9356.42 22,025.11 23,499.49 −2962.58 −3.514 Age 24.44 11.41 25.50 11.21 28.61 11.82 3.11 7.05 ** Return on Assets 2.84 8.05 2.57 6.45 2.60 7.60 −0.03 −0.10 ** Return on Equity 7.79 48.41 6.96 14.23 7.28 21.60 −0.32 −0.38 * Net Income Margin −19.22 1812.36 2.33 6.79 2.14 9.67 0.19 −0.50 * Industry dummy Cattle raising 0.82 0.39 0.11 0.31 0.19 0.31 −0.08 − 55.338 *** Energy and water 1.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 Extraction, transformation of non-energetic minerals 0.10 0.47 0.15 0.36 0.06 0.36 0.09 25.974 *** Metal transforming industries 0.09 0.50 0.12 0.33 0.08 0.33 0.04 39.118 * Other manufacturing industries 0.43 0.50 0.17 0.30 0.10 0.30 0.07 58.663 ** Construction 0.85 0.36 0.15 0.36 0.85 0.36 −0.70 − 17.507 *** Restaurant and lodging trade 0.00 0.06 0.17 0.38 0.83 0.38 −0.65 − 38.056 *** Transport and Communication 0.47 0.31 0.66 0.23 0.34 0.23 0.32 44.443 ** Management and insurance activities 0.35 0.42 0.54 0.69 0.39 0.31 0.13 14.924 ** Other services 0.86 0.34 0.14 0.34 0.86 0.34 −0.73 −18.331 ** Dependent Variables Z-Score 2.91 1.41 2.75 1.46 3.04 1.41 −0.30 −4.502 * Debt/Capital 71.92 319.88 36.67 60.27 68.61 197.29 −31.95 −4.678 *** EBIT/Interest Expense 5.78 1.33 4.17 1.32 9.05 51.21 −4.88 2.875 ** Debt/EBITDA 3.09 0.45 −1.45 184.97 3.11 210.59 −4.56 0.49 ** ***, **, * significant at 1%, 5% and 10% levels. J. Risk Financial Manag. 2020,13, 5 15 of 18 Table 6. Bankrupt Firms over the period 2014–2002. Family Ownership Year Number of Firms Family Firms % Family Insiders % Family Blockholders % Both Insiders & Blockholders % 2014 0 0% 0% 0% 0% 2013 6 50% 50% 50% 0% 2012 4 0% 0% 0% 0% 2011 4 33.3% 100% 0% 0% 2010 6 20% 0% 100% 0% 2009 15 50% 80% 20% 0% 2008 22 29.4% 60% 40% 0% 2007 22 29.4% 60% 40% 0% 2006 78 27.9% 65% 35% 0% 2005 137 31.7% 67% 33% 0% 2004 189 32.2% 76% 24% 0% 2003 126 21.2% 91% 9% 0% 2002 75 44.2% 65% 35% 0% According to the difference between family and non-family with regards to number of employees, the age of firm, debt at bankruptcy, and the ratio of amortization/cash flows, our findings are significant at 5% and 10% levels. However, when evaluating the age of the firms that file for bankruptcy, it is apparent that family firms are younger on average. A potential explanation for this significant difference is that many of the firms categorized as family firms following the definition are start-ups or in their early stage in their life cycle. Such young firms are at greater risk to fail as compared to more established firms as in Table 7. Table 7. Bankrupt Firms over the period 2014 to 2002. Year Mean Age All Bankrupt Firms Mean Age (Non-Family Firms) Mean Age (Family) Firms Difference (Non-Family-Family Firms) t-Test p-Value 2014 13.441 16.267 0.000 16.267 67.673 0.000 *** 2013 23.280 26.850 12.330 14.530 1.360 0.268 2012 44.000 22.500 0.00 −7.250 −0.298 0.816 2011 16.500 26.700 23.900 2.800 0.000 0.000 *** 2010 19.843 26.900 8.467 18.433 1.307 0.321 2009 19.096 23.900 2.600 21.230 3.597 0.023 ** 2008 17.755 7.380 14.240 −6.860 −2.568 0.062 * 2007 19.382 0.000 17.540 −17.540 −4.236 0.013 ** 2006 14.691 0.000 18.760 −18.760 −3.028 0.039 ** 2005 14.738 0.000 13.429 −13.429 −7.551 0.000 *** 2004 12.192 18.013 12.392 5.621 1.989 0.054 * 2003 10.274 14.246 4.015 10.229 7.902 0.000 *** 2002 9.046 12.059 2.152 9.908 10.118 0.000 *** Note: ***, **, *, significance levels1%, 5%, and 10% of the difference of family and non-family bankrupted firms. Number of employees refers to the latest number of employees available at bankruptcy date. Younger firms tend to have founders present due to their phase in the cycle and therefore are categorized as family companies in this sample. However, these firms do not necessarily share the characteristics associated with family firms, such as long-term time horizon, succession planning considerations, and risk aversion. To eliminate this bias, we re-runa t-test for firms that filed for bankruptcy with the age of 10 years and above. Table 8shows a duplicated version of Table 7, but only includes firms with an age above 10 years before declaring bankruptcy. As expected, the sample of family firms decreases in each of the years except for 2004. Specifically, in the year of financial crisis (2008–2013), the ratio of family firms filing for bankruptcy waslower than in the years of economic J. Risk Financial Manag. 2020,13, 5 16 of 18 prosperity (2004–2007). This confirmed the fact that family businesses filing for bankruptcy is not due to the high debt and riskiness of the business. Using this sample, we can validate our hypothesis that family firms have lower leverage and are less risky than their counterpart firms. Table 8. Firms older than 10 years. Family Ownership Year Number of Firms % Family Firms % Family Insiders % Family Blockholders % Both Insiders & Blockholders % 2014 0 0 0 0 2013 4 17% 17% 0% 0 2012 0 0% 0% 0% 0 2011 4 25% 25% 0% 0 2010 3 0% 0% 0% 0 2009 7 0% 0% 0% 0 2008 13 18% 14% 5% 0 2007 13 18% 14% 5% 0 2006 16 21% 19% 1% 0 2005 18 24% 18% 7% 0 2004 21 22% 16% 6% 0 2003 0 0% 0% 0% 0 2002 0 0% 0% 0% 0 5. Conclusions Numerous scholars have debated the uniqueness of the characteristics of family firms in terms of performance as opposed to their counterpart firms. The perception that families possess a more conservative attitude towards the management of the business makes family firms less risky. The risk profile of family business has been argued to be one of the characteristics significantly impacting the management of family business. In the light of the above, this paper has as its main objective to predict if family firms have lower leverage and manage their operations in a less risky manner as compared to their counterpart firms. The analysis conducted in this study yields some interesting results regarding the risk profile of the family firm. Firstly, family firms have a lower financial structure than non-family firms. This indicates that most family firms use less debt financing than non-family firms, and as such maintain a lower level of debt. Regarding the profitability measure, this result suggests that most families tend to increase their reserves during the profitable cycle of their firms and later reinvest this reserved profit during economic downturn, rather than using debt finance. In other words, they employ their equity finance rather than debt finance for investment. Secondly, family firms demonstrate lower risk as illustrated by the Altman Z-score. The Altman Z-score captures the financial risk inherent in a firm by examining four financial ratios (such as working capital/total assets, retained earnings/total assets, EBITDA/total assets, and market value of equity/book value of total debt). The significant difference between family firms and non-family firms on the Altman Z-score scale indicates that the lower inherent risk of family firms arises from the operation aspect of the business. Family firms managed their business operation with lower risk and are generally healthier financially than their counterpart firms. This explains the uniqueness of the capital structure of family businesses. Lastly, the robust tests for the hypotheses using a sample of bankrupt firms in SABI reveal that the proportion of failure of family firms as opposed to theircounterpart firms is relatively low. Analyzing the bankruptcy files of firms from 2002 to 2014 shows a considerably low ratio of family firms at the 5% significance level. This affirms that the low risk illustrated in the Altman Z-score regression is consistent withthe lower ratio of family firms that were declared bankrupt over the study period. Lastly, the average debt at bankruptcy was lower and statistically significant for family firms as opposed to J. Risk Financial Manag. 2020,13, 5 17 of 18 non-family firms. Therefore, the findings herein confirm the hypothesis that family firms have a lower capital structure and maintain more financially healthy operations than non-family firms. Author Contributions: Conceptualization, methodology, software, and formal analysis, L.A.T.N.; validation, visualization, supervision and project administration, H.M.S.d.O.; formal writing, software and funding acquisition, B.M.F.d.S.; investigation and data curation and methodology, L.M.P.; visualization, formal analysis and resources, S.A.M.C.B. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Center for Studies in Business and Legal Sciences (CECEJ) and Research Centre for the Study of Population, Economics and Society (CEPESE). Acknowledgments: We will like to give special thanks to the reviewers for their valuable comments. More thanks to Professor Paul Ntungwe Ndue for his remarkable review and assistance. Lastly, thanks to the Center for Studies in Business and Legal Sciences (CECEJ) and Research Centre for the Study of Population, Economics and Society (CEPESE) for all the financial funding and support provided by its members during this research. Conflicts of Interest: The authors declared no potential conflict of interest with respect to the research, authorship, and publication of this article. References Altman, Edward I., John Hartzell, and Matthew Peck. 1998. Emerging market corporate bonds a scoring system. In Emerging Market Capital Flows. Boston: Springer, pp. 391–400. 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