Economic and financial snapshot of small Spanish family firms

Revista de Contabilidad Spanish Accounting Review 22 (1) (2019) 21-31 REVISTA DE CONTABILIDAD SPANISH ACCOUNTING REVIEW revistas.um.es/rcsar Economic and financial snapshot of small Spanish family firms Sara Terrón-Ibáñeza,*, María Elena Gómez-Mirandab, María del Mar Miras-Rodríguezc, Lázaro Rodríguez-Arizad a, b, d) Universidad de Granada. Facultad de Ciencias Económicas y Empresariales, Campus Universitario de La Cartuja, Granada, España c) Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones. Facultad de Ciencias Económicas y Empresariales, Sevilla, España ARTICLE INFO Article history: Received 14 March 2018 Accepted 29 May 2018 Available online 31 December 2018 JEL classification: G4 M1 Keywords: Family business Economic cycle Economic and financial indicators Productivity Size Performance ABSTRACT The aim of this study is to determine whether there are statistically significant differences between small Spanish companies according to their family or non-family nature, in terms of their main economic and financial indicators. The study data analysed correspond to the years 2003, 2007 and 2013, which enabled us to examine whether the characteristics observed and any differences between these companies persisted during a period featuring three different economic scenarios. The study sample was composed of 21,192 small family firms and 4,449 small non-family firms. The results obtained show that, regardless of the national economic situation, there were statistically significant differences between the two types of companies for certain economic and financial indicators. We conclude that the family nature of a company has a negative impact on productivity, the number of employees and levels of investment and turnover. Moreover, family firms face higher costs of external financing than do non-family businesses. ©2018 ASEPUC. Published by EDITUM - Universidad de Murcia. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Códigos JEL: G4 M1 Palabras clave: Empresa familiar Indicadores económico-financieros Ciclos económicos Productividad Tamaño Rentabilidad Radiografía económico-financiera de las pequeñas empresas familiares españolas RESUMEN En el presente trabajo se analiza, en primer lugar, si existen diferencias estadísticamente significativas entre las pequeñas empresas familiares y no familiares españolas en relación a sus principales indicadores económico-financieros. Se estudian datos referidos a los años 2003, 2007 y 2013, lo que nos permite analizar si las posibles diferencias se mantienen en tres escenarios económicos distintos, para 21192 pequeñas empresas familiares y 4449 pequeñas empresas no familiares. Las conclusiones obtenidas demuestran que, con independencia de la situación económica nacional, entre ambos tipos de empresas se han detectado diferencias estadísticamente significativas en el valor de determinados indicadores económico-financieros. Concluimos que es el carácter familiar de las organizaciones el factor que afecta negativamente a la productividad de los empleados, al número de trabajadores, a la inversión y a la cifra de negocios. En cuanto al coste de la financiación ajena, las empresas familiares presentan valores más elevados que las empresas no familiares. ©2018 ASEPUC. Publicado por EDITUM - Universidad de Murcia. Este es un artículo Open Access bajo la licencia CC BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/4.0/). * Corresponding author. E-mail address: [email protected] (S. Terrón-Ibáñez). https://www.doi.org/10.6018/rcsar.22.1.354281 1988-4672 (online) /1138-4891 (printed) /©2018 ASEPUC. Published by EDITUM - Universidad de Murcia. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 22 Introduction The family business is a predominant form of economic organisation in most world economies (Burkart et al., 2003; Stewart & Hitt, 2012), and so its success or failure often has a major impact on economic growth (Craig & Moores, 2010; Memili et al., 2015). According to the resource-based view, companies generate resources from which they can achieve a competitive advantage and hence superior long-term economic performance (Teece et al., 1997). Many family firms develop their own resources and competences, reflecting their specific nature in terms of governance structure and leadership (Chrisman et al., 2005;Le Breton-Miller, 2006;Le Breton-Miller et al., 2011). Basing their study on this approach, Habbershon & Williams (1999: 3) described family businesses as “complex, dynamic, and rich in intangible resources”, and introduced the concept of familiness (1999: 11), which they defined as “the unique bundle of resources a particular firm has because of the systems interaction between the family, its individual members, and the business”, to explain how the family connection contributes to business success. These authors, therefore, consider familiness to be a source of competitive advantage for family businesses, derived from their organisational performance and their wealth creation capabilities (Habbershon et al., 2003). However, the possession of resources and capacities is not sufficient to guarantee business success (Cabrera-Suárez et al., 2001). As explained by Habbershon & Williams (1999: 13), although familiness provides family businesses with unique resources, these “needs to be managed and maintained if it is to provide an advantage”, and their potential thus realised as the creation of value (Sirmon et al., 2007). Hence, the concept of familiness produces a competitive advantage when the resources it generates are correctly managed, and at the same time it is a factor that significantly influences the management of the organisation (Pearson et al., 2008). Rutherford et al. (2008: 1089) concluded that familiness is “showed associations with revenue, capital structure, growth, and perceived performance; however, the relationships were both positive and negative”. In consequence, the differences in terms of economic performance between family and non-family businesses will largely depend on the influence exerted by the family on the ownership, control and management of the organisation, and on how these elements are incorporated into its definition (Villalonga & Amit, 2006;Carney et al., 2013). It has been shown that competitive advantages can emerge from the intersection between family and business (Le Breton-Miller et al., 2011). On the other hand, the disadvantages arising from the singularities of this type of organisation can negatively affect their economic performance (Kammerlander et al., 2015). While some studies have argued that family businesses achieve better economic results than non-family companies, mainly due to the competitive advantage derived from their family nature (Blanco-Mazagatos et al., 2007; Mazzi, 2011), others maintain that the peculiarities of these companies, such as nepotism, altruism and/or lack of professionalism, among other aspects, negatively affect their economic performance (Miller et al., 2013;Kammerlander et al., 2015). Numerous studies have reported that the behaviour of family businesses can vary with changes in the business environment, mainly arising from the presence of the family in the boardroom. Thus, it has been shown that during a period of economic recession, family firms face a challenge from which their non-family counterparts are exempt, namely that of safeguarding their socio-emotional wealth in this situation of crisis (Faghfouri et al., 2015). However, other researchers believe that the singularities of the family firm allow it to better resist the impact of a financial crisis (Felicio & Galindo- Villardón, 2015), explaining that family organisations may have capital to which their non-family counterparts do not have access, such as labour assistance from family members who are willing to work at below-market rates, or loans from the family at low interest or on other preferential terms (Gómez-Mejía et al., 2007). Taking into account the considerable presence of family firms in Spain, as in most economies worldwide, the aim of this study is to extend our understanding of the economic and financial behaviour of family companies, in the view that they are crucial to economic growth and development. We do so by conducting a comparative analysis of family and non-family companies, eliminating possible bias arising from company size and focusing on three economic scenarios, representative of economic expansion, recession and recovery, which Spain has undergone, successively during this century. Little previous research has been undertaken to analyse economic and financial differences between Spanish companies according to the type of organisation. Among this limited number of studies, Barontini and Caprio (2005) examined a sample of 127 listed family companies, using data for the period 1997-2001, and concluded that the type of family business positively influences the Tobin’s Q ratio and economic profitability. In a similar study, Menéndez-Requejo (2006) analysed data for the year 2002, for 7,775 large and mediumsized Spanish companies, both listed and unlisted, and observed a positive effect of the family nature of these companies on their financial profitability. In related work, Miralles- Marcelo, Miralles-Quirós and Lisboa (2014) analysed all the companies listed in Spain and Portugal, for the period 1999- 2008, and found that Spanish family businesses achieved a higher average economic profitability than non-family companies. In addition, these authors observed a positive effect of the type of family business on economic profitability, both for the total sample and when the analysis was restricted to the smaller firms, as well as on the Tobin’s Q ratio for small Spanish family firms. Finally, recent research in Spain has highlighted differences in the economic and financial situation of family businesses with respect to that of their nonfamily counterparts (Instituto de la Empresa Familiar y Red de Cátedras de la Empresa Familiar [Family Business Institute and Network of Family Business Chairs, henceforth IEF], 2016, 2018;Rojo Ramírez et al., 2015). However, to our knowledge no specific analysis has been made contrasting small Spanish firms according to their family or non-family nature, including in this study an analysis of the economic and financial differences between them, providing empirical evidence of the results presented and eliminating bias arising from company size. To address this perceived research gap, we conducted a comparative analysis of small Spanish family and non-family companies, to determine whether there are statistically significant differences in the values of their main economic and financial indicators, and whether the family nature of the firm is a relevant factor in this respect. Specifically, we analysed accounting information obtained from a broadbased, homogeneous and strictly-filtered database composed of 25,641 small private Spanish companies, of which 21,192 (83%) were family firms and 4,449 (17%) were of a nonfamily nature. The data correspond to the years 2003, 2007 and 2013, which characterised, respectively, a situation of economic boom, the outbreak of a recession and the begin- S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 23 ning of economic recovery. A comparison of the differences observed during these very different economic scenarios will allow us to determine whether the overall conclusions drawn from our study are dependent or otherwise on the state of the economy during the period considered. In our opinion, the results obtained from this study contribute to a greater understanding of the economic and financial situation of the Spanish business fabric, via an empirical analysis comparing the values of the main economic and financial indicators, according to the family or non-family nature of small companies in Spain, during three different economic scenarios. A very large sample of small unlisted family firms was considered in this study, which enabled us to focus the analysis on a specific type of business organisation, albeit one that corresponds to the majority of companies in this country. Otherwise, the present paper makes a more general research contribution in the field of family business. Our study of the influence of the type of company on the values of various economic and financial indicators shows that, regardless of the state of the economy, the family nature of a company has a negative impact on some of its main economic and financial indicators, namely employee productivity, investment, turnover and the number of employees (the last three of these factors are representative of business growth). Moreover, family businesses have higher borrowing costs than non-family companies. The conclusions we draw from this analysis extend our understanding of the differences between family and nonfamily businesses, and help explain the specific behaviour presented by small family businesses. This knowledge can be exploited to enhance business management and possibly to generate improvements in corporate governance. The rest of this paper is structured as follows. After reviewing the literature on the study area, we present the hypotheses to be tested. We then describe the sample selection method and explain how the study data were analysed. In the following section, we determine whether there are statistically significant differences between the values of the economic and financial indicators selected according to the type of company, for each economic scenario considered. We then examine the relation between the type of company (family or non-family) and the values of the above indicators. Finally, we discuss the results obtained and present the main conclusions drawn. Study Hypotheses There may be differences between family and non-family businesses, arising specifically from the presence of the family in the organisation (Zahra et al., 2004). In the latter type of company, targets are set, resources generated, capacities developed and investments made in ways that differ from those found in non-family companies (Sharma et al., 1997). In organisations where family relationships predominate, there is a history and a body of knowledge derived from past experiences that influence and shape the firm’s actions, and determine its current relationships (Berrone et al., 2012). Accordingly, a family business can be viewed as a system that contains three fundamental components (Habbershon et al., 2003): the family, with its history, traditions and life cycle; the organisation, which constitutes the strategies and structure employed to generate wealth; and the individual members, who represent the interests and abilities of the family and participate in the firm’s management or ownership. While economic issues are usually at the forefront in nonfamily businesses (Le Breton-Miller, 2006), both economic and non-economic considerations are present in the decision making process within family organisations (Carney, 2005; McGuire et al., 2012). Thus, while the goals of a non-family company are fundamentally those of maximising its value, income, growth or innovation, for a family firm these aspects may be subordinated to family objectives such as maintaining harmony, employment, economic independence or family control of the business (Voordeckers et al., 2006), so that the company may ultimately be transferred to succeeding generations under optimal conditions (Gómez-Mejía et al., 2007). The management model usually found in family businesses means that they must simultaneously address the (sometimes conflicting) priorities of business and family, which may lead to tension between professional and emotional motivations. In this respect, Siakas et al. (2014) showed that the impact of the family on the company is greater than that produced by the company on the family. Therefore, the success of an organisation will depend to a large extent on how the family responds to the tensions that may arise, and not so much on the technical management of the company (Olson et al., 2003;Felicio & Galindo-Villardón, 2015). Socio-emotional wealth is the most important differentiating factor in family businesses, and helps explain why these organisations behave in different ways from all others (Berrone et al., 2012). As Gómez-Mejía et al. (2007: 106) observed, socio-emotional wealth is composed of “non-financial aspects of the firm that meet the family’s affective needs, such as identity, the ability to exercise family influence, and the perpetuation of the family dynasty”. In this respect, too, Berrone et al. (2012: 260) commented, “although Socioemotional wealth may not be unique to an organizational context where family ties are present, for family principals and employees the firm becomes an integral and inescapable part of their lives. This contrasts with nonfamily shareholders or hired managers and employees for whom the relationship with the firm is more distant, transitory, individualistic, and utilitarian”. Moreover, family businesses tend to maintain a degree of emotional involvement with their employees, who are often considered a resource of great value and an indispensable source of knowledge enabling the company to prosper (Le Breton-Miller, 2006). In addition, many family firms seek to create a community culture within the company, based on loyal, highly motivated workers (Arregle et al., 2007). As shown by Deephouse and Jaskiewicz (2013), family members normally place more value on their continuing relation with the business than do the co-owners of firms with no family involvement. When decision-making is not guided merely by economic objectives, as in the case in family firms, the family might even be prepared to put the company at risk if this were necessary to preserve the family legacy (Zhang et al., 2012). This does not imply that family businesses, in order to preserve their socio-emotional wealth, ignore the financial issues of the organisation, rather that they are willing to assume certain costs associated with performing actions from which they will obtain non-economic benefits (Berrone et al., 2012). The deep-rooted connection between the family and the company is also motivated in part by the economic risk faced by the family in these types of organisations, in putting their capital at stake, as well as risking their reputation and the future job opportunities of their members (Miller et al., 2008). The conservation of socio-emotional wealth in family businesses is an aspect of special importance in this context because the negative effects of any conflicts that may arise within the family business can directly harm its economic performance (Simons and Peterson, 2000). S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 24 In view of these considerations, and given the impact of family involvement on the firm’s development, we propose the following hypotheses: H1: Regardless of the stage of the economic cycle, there are statistically significant differences in the value of certain economic and financial indicators between family and non-family businesses. H2: The value of certain economic and financial indicators is inversely associated with the family nature of the company.* Method Sample The sample of companies analysed in this study, and the corresponding data, were obtained from the database created in Spain by IEF (2016). This database, termed SABI (Iberian Balance Sheet Analysis System), contains economic and financial information from the annual accounts reported to the Mercantile Registries. The study sample was obtained in several stages. First, we selected all the public limited and limited liability companies that were active during the period 2003-13, that had provided information for the three particular years analysed in this study (2003, 2007 and 2013) and that had been incorporated in the year 2001 or earlier (thus, in the first year analysed every company had been in existence for at least two years). In total, 70,611 companies met these requirements. The subsequent classification of these firms as family or non-family was obtained according to the results obtained by IEF (2016), in a two-phase approach. In the first, the automated processes of the SABI database were applied, taking into account the companies’ ownership structure and the participation of the family in the governing body. A company was considered to be a family firm when any of the following criteria were met: 1. Concentrated ownership: if family shareholders controlled 50% or more of the ownership, or if family shareholder-directors had a combined ownership exceeding 50%. 2. Diversified ownership: if a family or an individual shareholder controlled 5% or more of the ownership; similarly, if shareholder-directors or administrators who as individuals were shareholders controlled 20% or more of the ownership. 3. Indeterminate ownership: if the firm had shareholderdirectors or managers who, as individuals, participated in the ownership of the company. In the second stage of the process, the IEF reviewed the initial classification, to detect possible errors and to determine the family nature or otherwise of the firms initially classed as ‘doubtful’. This process revealed that of the 70,611 companies considered, 54,834 (77.7%) were family firms, and 15,777 (22.3%) were non-family. The following information was then obtained for each firm: company name, tax code, date of incorporation, domicile (by region, termed Autonomous Community in Spain), business activity according to the 2009 National Classification of Economic Activities, and economic-financial information for the years 2003, 2007 and 2013. These years coincide with points of inflection in the Spanish GDP (Bank of Spain, 2017), and are representative of three economic scenarios: the beginning of a period of expansion (2003), the outbreak of the subsequent recession (2007) and the start of economic recovery (2013). The database was then exhaustively filtered to remove firms that provided incomplete or erroneous data or which presented extreme values (the 5% largest companies, in order to avoid distortions due to their singular dimensions, and also all the microenterprises detected, since this category would be under-represented due to the large proportion of these firms that do not present their annual accounts to the mercantile registry). In total, 33,685 companies were excluded from the study for these reasons, and so the final database analysed consisted of 35,284 companies, of which 26,062 (73.9%) were family and 9,222 (26.1%) were nonfamily. Finally, the family firms were classified by business size, in accordance with the EU criteria (European Commission 2003) shown in Table 1. For the three years analysed, we observed that of the 35,284 companies, over 70% were classed as small. Due to the great variability between the different business dimensions, and in order to obtain a homogeneous sample, our final analysis was based exclusively on the small companies. Thus, the final study sample was composed of 25,641 small companies, 21,192 of which were family firms and 4,449 non-family. Table 1 Criteria for classification by company size TABLES Table 1. Criteria for classification by company size Type of company No. of employees Turnover or Annual general balance Microenterprise < 10 < 2 m ! < 2 m ! Small < 50 2-10 m ! 2-10 m ! Medium-sized < 250 11-50 m ! >10 ≤ 43 m ! Source: European Commission (2003) Source: European Commission (2003) Variables The data analysis was performed in two stages. First, based on the accounting information provided by the companies, we obtained the corresponding economic and financial indicators for analysis. These magnitudes, and a description of each one, are presented in Table 2. Table 2 Financial and economic indicators analysed Table 2. Financial and economic indicators analysed INDICATOR CALCULATION ACCORDING TO SABI DATABASE CONCEPTS Economic profitability (Pre-tax ordinary returns + Financial costs) / Total assets Level of borrowing (Total assets – Own funds) / Own funds Pre-tax financial profitability Pre-tax ordinary returns / Own funds Cost of borrowing Financial costs / (Total assets – Own funds) Labour productivity Operating income / Number of employees Number of employees Number of employees Investment Total assets Turnover Operating income Source: The authors Source: The authors Economic profitability is taken as the potential of all the company’s investments to generate a return, without taking into account the financial structure adopted for this purpose, i.e., regardless of the type of financing. Financial return is the remuneration corresponding to the financial resources immobilised by the firm’s investors. The level of borrowing, indicative of the composition of the firm’s financial structure, S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 25 reflects whether the company is self-financing or relies on external funds, the remuneration of which is measured as the cost of borrowing.Business size is expressed in terms of turnover, investment and number of employees. The productivity of the latter is taken as the measure of business efficiency. In the second stage of the analysis, we examined whether the family or non-family nature of the firm influenced the value of the economic and financial indicators considered. To do so, a number of multiple linear regressions were performed, in which the dependent variables were the economic and financial indicators calculated as shown in Table 2. The explanatory variable was the categorical variable considered for each of the regressions, ‘type of firm’, assigned the value 1 if the firm was family-owned and 0 otherwise. Company size, the sector of activity and the age of the business were all taken as control variables. Company size was obtained by factorial analysis of the following variables: investment, turnover and number of employees, for each of the three study years. The activity sector was derived from fictitious variables, taking the primary sector as the reference sector. Thus, the variable “Secondary sector” was assigned the value 1 if the company operated in the secondary sector and 0 otherwise. The variable “Tertiary sector” took the value 1 if the company belonged to the tertiary sector and 0 otherwise. The age of the company was measured from its date of incorporation, and represented by Napierian logarithms to minimise asymmetry, in view of the high degree of variability observed. Data analysis First, the mean values of the economic and financial indicators were calculated for the family and non-family groups, for each of the economic scenarios considered. To test hypothesis H1, we then examined whether there were statistically significant differences between these groups, using a difference of the means test, by one-way analysis of variance (ANOVA). In the second part of the study, we tested whether the family or non-family nature of the firm influenced the values of the economic and financial indicators considered. Taking into account that the dependent variables were continuous, hypothesis H2 was tested using multiple regression models (Aiken & West, 1991). Thus, for each of the dependent variables and for the corresponding study year, the following regression models were obtained: γj2003 =β0+β1X1j+β2X2j+β3X3j+... +βjXk j +µj γj2007 =β0+β1X1j+β2X2j+β3X3j+... +βjXk j +µj γj2013 =β0+β1X1j+β2X2j+β3X3j+... +βjXk j +µj where γrepresents the dependent variable, Xthe control and explanatory variables, µthe residuals and βthe estimated coefficients of the marginal effect between each Xand γ Table 3 shows the correlations obtained between the continuous variables used in each of the regressions, for every period analysed. Multicollinearity was examined by considering the variance inflation factor (VIF) calculated for each independent variable. According to Myers (2000), VIF 10 is cause for concern. After determining these values and the tolerance levels of the variables, we concluded that there were no problems of multicollinearity. Table 3 Matrix of correlations Table 3. Matrix of correlations 2003 2007 2013 Size Age Size Age Size Age Age 0.138** - 0.073** - 0.059** - Borrowing cost -0.012 0.035** -0.004 0.020** 0.014* 0.028** Productivity 0.455** 0.162** 0.420** 0.144** 0.339** 0.129** Investment 0.567** 0.272** 0.491** 0.231** 0.457** 0.215** Turnover 0.633** 0.234** 0.527** 0.173** 0.465** 0.148** No. of employees 0.467** 0.189** 0.323** 0.097** 0.396** 0.085** **. The correlation is significant at 0.01 (2-tailed). **. The correlation is significant at 0.01 (2-tailed). Empirical analysis and results Regardless of the stage of the economic cycle, there were statistically significant differences between the family and non-family firms considered, as regards investment, turnover, number of employees, productivity and borrowing costs (Table 4). Specifically, the family firms had lower levels of investment and obtained less income; moreover, they employed fewer people, had less productive workforces and were subject to higher costs of borrowing. Our analysis of the firms’ financing structure showed that both family and non-family businesses obtained their finance more from external sources than from own funds. However, statistically significant differences were only found for borrowing levels in 2013 (at the end of the recession), when family firms had lower levels of debt than non-family firms. In terms of profitability, only in 2003, at the start of the economic boom, did family firms achieve a pre-tax financial return greater than that of non-family companies; indeed, by the end of the boom period, in 2007, their profitability was lower than that of the non-family businesses. These results corroborate hypothesis H1. Tables 5-9 show the results of the linear regressions performed, taking as the dependent variable the borrowing cost, labour productivity, the number of employees, investment and turnover, respectively. In each of these tables, models 1, 3 and 5 illustrate the effect of the control variables on the dependent variables considered, for the years 2003, 2007 and 2013, respectively. Models 2, 4 and 6 show the effect of the family nature of the firm, for each of the years studied. Table 5 shows that business size was inversely related with borrowing costs in 2003 (Model 1), but that in 2013 this association had a positive sign (Model 5). However, in the first study year (2003), the longer-established the company, the greater its borrowing costs (Model 1), while in 2013 (Model 5) the reverse was true. Regarding the firms’ area of business activity, in 2003 the companies that were active in the secondary and tertiary sectors were subject to higher borrowing costs than those operating in the primary sector (Model 1). However, in 2007, this relationship with borrowing costs was only positive and significant for companies in the secondary sector (Model 3). Finally, in 2013 and in comparison with companies in the primary sector, those in the secondary sector had higher borrowing costs and those in the tertiary sector, lower ones. Regarding association between the family or non-family nature of the company and the cost of external financing, we found that regardless of the economic cycle, this relationship was positive and significant (Models 2, 4 and 6), i.e., that the family nature of these firms was associated with higher borrowing costs. Table 6 shows that the larger the firm, and the longer it had been established, the greater its productivity, regardless of the economic period considered. Furthermore, the firms operating in the secondary and the tertiary sectors S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 26 Table 4 Mean values of the indicators Table 4. Mean values of the indicators 2003 2007 2013 Family firm Nonfamily firm Sig. Family firm Nonfamily firm Sig. Family firm Nonfamily firm Sig. Economic profitability 8.0% 7.6% 8.6% 9.1% * 1.6% 1.7% Level of borrowing 3.38 3.70 2.60 2.72 2.18 2.61 ** Pre-tax financial profitability 18.5% 15.1% ** 17.3% 19.8% 0.0% -1.8% Cost of borrowing 3.1% 2.6% *** 3.2% 2.9% *** 3.0% 2.7% *** Labour productivity 157.27 310.32 *** 189.06 405.81 *** 166.57 363.49 *** No. of employees 22.63 26.21 *** 24.40 27.64 *** 21.20 25.04 *** Investment 3096.44 9079.92 *** 4266.61 12664.12 *** 4348.53 14656.87 *** Turnover 3521.85 7741.81 *** 4585.54 10957.28 *** 3703.47 8964.08 *** * p<0.10 **p<0.05 *** p<0.01 * p<0.10 **p<0.05 *** p<0.01 Table 5 Results of the regression models. Dependent variable: cost of borrowing Table 5. Results of the regression models. Dependent variable: cost of borrowing Cost of borrowing 2003 Cost of borrowing 2007 Cost of borrowing 2013 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Independent variables Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Constant 7.027*** 5.535*** 3.262*** 2.661*** 2.267** 1.665* Size -0.017 -2.687*** -0.011 -1.762* -0.006 -0.899 -0.004 -0.556 0.013 2.144** 0.015 2.513** Secondary 0.037 5.811*** 0.036 5.629*** 0.020 3.155*** 0.020 3.141*** 0.026 4.323*** 0.027 4.355*** Tertiary 0.041 2.152** 0.039 2.067** 0.019 1.022 0.018 0.975 -0.044 -2.460** -0.045 -2.508** Age 0.033 1.757* 0.034 1.786* 0.011 0.599 0.011 0.607 -0.054 -2.965*** -0.053 -2.944*** Type of firm 0.027 4.240*** 0.013 1.971** 0.017 2.694*** Adjusted R2 0.001 0.002 0.001 0.001 0.001 0.002 F 10.844*** 12.277*** 3.275*** 3.397*** 8.800*** 8.493*** ΔF 17.980*** 3.884*** 7.259*** * p<0.10 **p<0.05 *** p<0.01 * p<0.10 **p<0.05 *** p<0.01 achieved higher levels of labour productivity than those in the primary sector. A significant inverse relationship was obtained between the family nature of the company and its productivity (Models 2, 4 and 6), leading us to conclude that the family nature of a company produces a negative influence on the productivity of its employees. As shown in Table 7, for the three periods, the larger the business and the longer it had been stablished, the greater its number of employees. In 2003 the companies in the secondary sector had more employees than those in the primary sector, although in the tertiary sector had less employees (Model 1). However, in 2007, at the start of the economic recession (Model 3), although the firms in the secondary sector maintained this difference with those in the primary sector, the difference in levels of employment between the firms operating in the tertiary and primary sectors was not statistically significant. By 2013, when the recession was coming to an end, the relationship between the variables corresponding to the sector of business activity and the number of workers was not significant (Model 5). In Models 2, 4 and 6 we can observe a significant inverse relationship between the type of company and the number of employees, which leads us to conclude that the family nature of a company has a negative effect on the number of employees it has. For all three periods analysed, there was a significant positive association between the size and age of the companies analysed and their levels of investment (Table 8). By activity sector, those in the secondary and tertiary sectors invested less than those in the primary sector. Models 2, 4 and 6 reveal a significant inverse relationship between the type of company and its level of investment. Thus, the family nature of a firm was associated with lower levels of investment, for the three periods studied. In Table 9 it can be seen that, for the three periods analysed, the larger the business and the longer it had been established, the greater its turnover. The companies in the secondary and tertiary sectors obtained higher levels of operating income than those in the primary sector. The family nature of a company presented a significant inverse association with turnover for the three years analysed (Models 2, 4 and 6), and so we conclude that the family nature of an organisation has a negative impact on its operating income. The linear relationships between the type of company and the remaining economic and financial indicators (economic profitability, level of borrowing and pre-tax financial profitability) were not statistically significant. Our analysis, therefore, reveals an inverse association between the family nature of a company and its borrowing costs, labour productivity, investment, turnover and number of workers, from which we conclude that the data corroborate hypothesis H2. We evaluated the validity of the proposed model by performing a robustness test, applying the regressions to examine the effect of the type of company on the economic and financial indicators considered. This analysis was performed after balancing the sample by type of company, to obtain S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 27 Table 6 Results of the regression models. Dependent variable: labour productivity Table 6. Results of the regression models. Dependent variable: labour productivity Productivity 2003 Productivity 2007 Productivity 2013 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Independent variables Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Constant 127.588*** 126.164*** 103.842*** 105.614*** 72.377*** 76.718*** Size 0.438 78.193*** 0.424 74.259*** 0.408 71.230*** 0.391 67.684*** 0.331 58.369*** 0.310 54.798*** Secondary 0.054 3.226*** 0.058 3.480*** 0.082 4.840*** 0.089 5.293*** 0.036 2.120** 0.043 2.589*** Tertiary 0.173 10.358*** 0.171 10.304*** 0.159 9.362*** 0.158 9.349*** 0.126 7.506*** 0.123 7.395*** Age 0.104 18.598*** 0.107 19.152*** 0.114 19.892*** 0.115 20.151*** 0.116 20.371*** 0.114 20.304*** Type of firm -0.069 -12.217*** -0.103 -17.775*** -0.140 -24.757*** Adjusted R2 0.232 0.236 0.195 0.206 0.136 0.155 F 1884.151*** 1546.117*** 1495.287*** 1274.716*** 1061.096*** 990.672*** ΔF 149.254*** 315.944*** 612.926*** * p<0.10 **p<0.05 *** p<0.01 Table 7. Results of the regression models. Dependent variable: number of employees * p<0.10 **p<0.05 *** p<0.01 Table 7 Results of the regression models. Dependent variable: number of employees Number of employees 2003 Number of employees 2007 Number of employees 2013 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Independent variables Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Constant 166.185*** 160.694*** 139.733*** 137.813*** 100.574*** 102.002*** Size 0.450 81.234*** 0.445 78.610*** 0.319 53.047*** 0.309 50.824*** 0.392 70.271*** 0.380 67.595*** Secondary 0.063 3.799*** 0.064 3.892*** 0.079 4.415*** 0.082 4.643*** 0.016 0.991 0.021 1.272 Tertiary -0.043 -2.613*** -0.044 -2.645*** 0.005 0.293 0.005 0.256 0.021 1.256 0.019 1.141 Age 0.137 24.714*** 0.138 24.894*** 0.077 12.853*** 0.078 12.945*** 0.063 11.242*** 0.062 11.107*** Type of firm -0.026 -4.551*** -0.057 -9.307*** -0.086 -15.325*** Adjusted R2 0.248 0.249 0.116 0.119 0.161 0.168 F 2068.517*** 1660.263*** 808.371*** 666.268*** 1295.246*** 1092.132*** ΔF 20.715*** 86.615*** 234.866*** * p<0.10 **p<0.05 *** p<0.01 * p<0.10 **p<0.05 *** p<0.01 equal numbers of family and non-family firms. The results of these analyses confirmed those obtained previously. Discussion and conclusions The question of economic and financial differences between family and non-family businesses has been addressed in previous research, but focusing on large, listed companies. However, although the bulk of the business fabric is composed of small companies, this area of the economy has not been subjected to analytical techniques that can reliably detect the existence of statistically significant differences in the value and (where appropriate) origin of their economic and financial indicators. The present study, therefore, contributes to our understanding of the economic and financial behaviour of small Spanish family businesses, a business segment that has received little previous research attention despite the key role it plays in national economic growth and development. Our study is based on a comparative analysis of family and non-family companies, distinguishing in turn between three recent economic scenarios, representative of economic expansion, recession and recovery. The results obtained show that, regardless of the stage of the economic cycle, there are statistically significant differences between family and non-family businesses regarding the average value of certain economic and financial indicators. Our results also show that, together with other business characteristics such as activity sector, company age and size, the family nature of an organisation influences the value of these indicators. Therefore, and in line with previous research (De Massis et al., 2013), we conclude that the presence of the family in the boardroom is associated with a poorer economic performance by small companies in Spain. In contrast to previous research conclusions concerning listed family companies in Spain (Barontini & Caprio, 2005; Menéndez-Requejo, 2006;Miralles-Marcelo et al., 2014), our study shows that on average small family businesses achieved less economic profitability than non-family businesses at the beginning of the economic recession (in 2007), although there were no such differences in the other two periods analysed. Although the economic performance of a company may be improved by family involvement (Le Breton- Miller et al., 2011), an excessive level of family ownership can counteract the advantages that might be brought to the organisation, by distorting its decision making (De Massis et al., 2013). In the present study, no significant relationship was found between the family nature of the company and its return on investment. The financing strategies applied in family firms are strongly influenced by the family, and this can impede access to external capital, thus producing a negative effect on business growth (Zhang et al., 2012). Previous research has shown that family firms often base their financing strategy on the use of internally-generated resources, in order to maintain control and ownership of the organisation (López-Gracia & Sánchez-Andújar, 2007). This approach creates a capital structure featuring less leverage and greater family control (Anderson & Reeb, 2003). However, contrary to what might be expected, our results suggest that, at least in Spain, both types of small business – family and non-family – are financed to a greater extent from external resources than from own funds, regardless of the period under analysis. In addition, previous studies have shown that family businesses have lower levels of borrowing and less leverage than nonfamily concerns (Gallo et al., 2004). As a result, family firms present limited growth, with lower turnover and fewer employees (Zhang et al., 2012). Companies with a high concen- S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 28 Table 8 Results of the regression models. Dependent variable: investment Table 8. Results of the regression models. Dependent variable: investment Investment 2003 Investment 2007 Investment 2013 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Independent variables Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Constant 179.315*** 183.496*** 140.230*** 145.909*** 97.872*** 104.246*** Size 0.539 106.144*** 0.508 99.604*** 0.479 88.583*** 0.452 83.843*** 0.447 84.669*** 0.422 80.670*** Secondary -0.181 -11.971*** -0.172 -11.581*** -0.158 -9.890*** -0.147 -9.347*** -0.177 -11.304*** -0.168 -10.936*** Tertiary -0.200 -13.216*** -0.203 -13.657*** -0.194 -12.123*** -0.196 -12.474*** -0.208 -13.271*** -0.212 -13.779*** Age 0.207 40.703*** 0.213 42.654*** 0.194 35.768*** 0.195 36.662*** 0.186 35.141*** 0.184 35.424*** Type of firm -0.152 -29.958*** -0.164 -30.451*** -0.169 -32.287*** Adjusted R2 0.368 0.390 0.284 0.310 0.249 0.277 F 3637.734*** 3194.137*** 2448.828*** 2218.204*** 2247.736*** 2075.939*** ΔF 897.508*** 927.294*** 1042.460*** * p<0.10 **p<0.05 *** p<0.01 * p<0.10 **p<0.05 *** p<0.01 Table 9 Results of the regression models. Dependent variable: turnover Table 9. Results of the regression models. Dependent variable: turnover Turnover 2003 Turnover 2007 Turnover 2013 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Independent variables Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Coef. β t Constant 224.196*** 220.338*** 171.648*** 173.327*** 112.648*** 118.148*** Size 0.610 126.291*** 0.594 121.045*** 0.515 96.164*** 0.495 92.023*** 0.456 85.750*** 0.433 81.887*** Secondary 0.078 5.451*** 0.083 5.784*** 0.110 6.943*** 0.118 7.536*** 0.038 2.380** 0.046 2.955*** Tertiary 0.137 9.523*** 0.135 9.462*** 0.147 9.272*** 0.145 9.273*** 0.116 7.368*** 0.113 7.253*** Age 0.159 32.945*** 0.162 33.719*** 0.139 25.866*** 0.139 26.286*** 0.126 23.682*** 0.124 23.710*** Type of firm -0.075 -15.378*** -0.119 -22.113*** 112.648*** -0.158 -29.758*** Adjusted R2 0.429 0.435 0.299 0.312 0.237 0.262 F 4701.685*** 3844.105*** 2625.664*** 2239.951*** 2106.774*** 1917.662*** ΔF 236.487*** 488.991*** 885.546*** * p<0.10 **p<0.05 *** p<0.01 * p<0.10 **p<0.05 *** p<0.01 tration of family ownership obtain less external funding (De Miguel & Pindado, 2001), mainly due to the family’s wish to maintain control and ownership. Hence, this type of company is reluctant to open up its capital to non-family owners even if this means renouncing business growth (Sirmon & Hitt, 2003). In many cases, the firm’s income is used to satisfy possible problems of liquidity (Olson et al., 2003), since family owners are willing to reinvest in the business, even if this means waiting longer to obtain benefits (Siakas et al., 2014). In line with this conclusion, the family businesses analysed in our study had lower values of borrowing than the non-family companies. However, these differences in levels of borrowing were only significant for 2013, at the start of the economic recovery. It has been argued that the governance structures of family firms tend to remain unchanged for longer than in nonfamily companies, and therefore that they maintain longer relationships with external agents. As a result, family firms are considered reliable debtors and thus obtain better borrowing conditions, at lower cost (Anderson & Reeb, 2003). Another relevant factor is that the family will have special interest in complying with its debt commitments, due to the use of its personal wealth as collateral, together with the involvement of human capital by family members (Pindado et al., 2015). Our analysis shows that borrowing costs varied significantly, in all the economic scenarios considered, between family and non-family businesses. However, contrary to our expectations, the family businesses in this study faced higher borrowing costs than their non-family counterparts. In short, the family nature of a firm is positively associated with its external financing costs, regardless of the period analysed. The results obtained show that the workforces in small family businesses are less productive than in non-family organisations, in all three economic scenarios analysed. This finding may be influenced by the conflicts between the professional and the emotional that take place within family firms, since efforts to overcome situations posing a threat to the company can have a negative effect on labour productivity (Morgan & Gómez-Mejía, 2014). In fact, conflict among family members is the main factor contributing to the bankruptcy of family businesses (Molly et al., 2010). Another negative factor in family businesses is that of possible nepotism, with subsequent harmful effects on productivity. Although employing family members may be associated with a reduction in agency costs due to the greater alignment between family and business interests, this circumstance can also reflect a lack of professionalism in the firm’s management and leadership (Miller et al., 2013). Moreover, family firms may be less able to attract qualified external managers, if family members receive preferential treatment. Thus, executives are sometimes selected and rewarded on the basis of family ties, rather than according to their professional experience and skills (Carney, 2005). Finally, the inequalities viewed by external professionals, such as the professional advantages conceded to family members, or perceptions that their work will not be appropriately rewarded, can affect not only the performance of the company but also its productivity (Menéndez-Requejo, 2006), by encouraging self-serving behaviour by external personnel (Schulze et al., 2002). Regardless of the stage of the economic cycle, our study shows there are statistically significant differences between small family and non-family businesses as concerns levels of employment, investment and turnover. Specifically, compared with non-family businesses, small family firms have fewer workers, lower levels of investment and of operating income. In addition, we show that the family nature of a S. Terrón-Ibáñez et al. /Revista de Contabilidad Spanish Accounting Review 22 (1)(2019) 21-31 29 company is inversely associated with the values of these indicators. In family firms, the business goal in many cases is not only to obtain an economic benefit, but also to safeguard their socio-emotional wealth and ensure long-term survival. However, such priorities can make this type of organisation less flexible (König et al., 2013). The wish to ensure continuity and longevity (Habbershon & Williams, 1999), together with a high concentration of family wealth in the company, can lead family firms to adopt more conservative business strategies (González et al., 2012) even if this endangers their economic performance (Gómez-Mejía et al., 2007). Such circumstances may limit growth ambitions and make it more difficult to recognise business opportunities (Miller et al., 2008), thus obstructing the creation of new products or services, especially those viewed as innovative or which involve greater risk, even in areas such as differentiating existing products (Kashmiri & Mahajan, 2010). According to Miller et al. (2008), these factors may hinder company growth, which would explain our findings regarding the inverse association between the family nature of the company and its levels of employment, of investment and turnover, both of which are indicators of business growth (Chen et al., 2014;Casillas et al., 2010;Eddleston et al., 2013). Therefore, and in accordance with James (1999), we conclude that successful family businesses are those which are capable of modifying their inherent strengths as family firms to reflect specific organisational needs and respond to the economic demands of the market. The present study has certain limitations. Although the approach adopted enhances our understanding of the economic and financial differences between family and non-family businesses in Spain, under three very different economic scenarios, it would also be useful to determine the effect produced by aspects such as business size and geographical location. To extend our knowledge of the Spanish business fabric and of the impact of family organisations on the national economy, these considerations will be addressed in future research. In addition, a study is needed of how the economic and financial situations of family and non-family businesses evolve over time, and of how the family nature of a company influences its chances of survival when the economy is in recession. 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