Small business access to bank leverage under crisis circumstances

Transcription

1 9 e Congrès de l Académie de l Entrepreneuriat et de l Innovation ENTREPRENEURIAT RESPONSABLE : PRATIQUES ET ENJEUX THEORIQUES Nantes, France, mai 2015 Small business access to bank leverage under crisis circumstances Dr Ramzi BENKRAIEM Audencia Nantes Ecole de Management 8 Route de la Jonelière Nantes rbenkraiem@audencia.com Abstract: This article relies on a dynamic theoretical framework to empirically investigate corporate drivers of small business access to bank leverage during the global crisis period. The empirical analysis leads to several interesting results. In particular, indicators of size and tangibility are positively related to bank leverage proxies. Moreover, they are by far more important than those of profitability, growth and earnings volatility in explaining access to bank leverage. These findings lay stress on the need of small businesses, above all, to provide sufficient guarantees when they wish to incur new bank leverage under crisis circumstances. Thus, they contribute to the debate on small business financing at a time when consequences of the global crisis on this category of firms are more and more evoked. Keywords: Bank leverage; small businesses; global crisis.

2 1. Introduction Small businesses play a crucial role in fostering growth and employment in many European countries like France. However, these firms face serious difficulties to rely on bank lending, especially in times of crisis. Consequently, this paper employs a corporate characteristic framework to study the main features of small business access to bank leverage under crisis circumstances in France. The sample, studied over a period going from 2008 to 2011, consists of 1,655 firms-years which employ fewer than 250 persons and whose annual turnover does not exceed 50 million euro. The empirical analysis examines the influence of such determinants as size, profitability, growth, tangibility and earnings volatility on bank debt proxies, namely debt to assets, debt to equity and debt to market ratios. The findings presented and discussed in this paper provide useful insights for academics, practitioners, and policy makers. The study enriches the existing literature on capital structure of SMEs, dealing with a level of analysis unmatched by previous research on French firms in times of crisis. Moreover, the findings can increase the knowledge and understanding of corporate managers, helping them in taking better decisions regarding financing options and capital structure of their SMEs. Finally, the results of this study can be used by French as well as European policy makers in order to design better financing tools, facilities and services for small businesses to face the crisis consequences. The rest of the paper is structured as follows: Section 2 reviews the theoretical background. Section 3 specifies the research design. Section 4 presents and discusses the empirical results and Section 5 serves as a conclusion. 2. Theoretical background In this study, trade-off and pecking order theories are applied together as a dynamic theoretical framework. Trade-off theory suggests that the debt structure of a firm is the result of a rational decision that attempts to balance the costs and the advantages of leverage. Corporate managers attempt to maximize firm value by reaching an optimal debt ratio, in which the marginal value of the benefits associated with debt exactly offsets the costs of issuing more debt (Myers, 2001). The trade-off choice takes into consideration three financial

3 elements: tax shields, bankruptcy costs and agency costs. An increase in the amount of debt will reduce the tax liability of the firm and increase after-tax payments towards fund providers. The value of the firm will therefore have a positive relationship with the corporate tax shields. Direct and indirect bankruptcy costs are engaged when the indebted firm is not able to pay its bondholders. The direct bankruptcy costs represent the costs related to the administration of the bankruptcy process (legal fees and management time) which, although insignificant in comparison with the market value of large firms, can represent a more substantial cost for the SMEs (Andrade and Kaplan, 1998). On the other hand, indirect bankruptcy costs become manifest in the area of investment policy, reducing drastically customers trust, as well as the firm value. Small firms are particularly subjected to the influence of indirect bankruptcy costs (Drobetz and Fix, 2003). Agency costs result from the specific relationship between corporate managers and debt holders. Since the financing policy developed by the corporate manager generally favors equity holders, bondholders can impose the incorporation of additional monitoring devices into debt agreements to protect their interests. These measures increase the costs of leverage and may push the firm to prefer internal equity over external sources of funding (Cassar and Holmes, 2003). Pecking order theory was developed by Myers (1984) and Myers and Majluf (1984). This theory suggests that firms have a particular preference order for financing decisions. In particular, it specifies that since managers are generally better informed than external investors about the true value and perspectives of the firm, the costs of finance will vary according to the financing decisions. For instance, when financing investment projects, the corporate owner-manager may prefer to use internal fund firstly; short-term debt secondly; long-term debt thirdly; and external equity fourthly (Cosh and Hughes, 1994). This strategy based on the pecking order of various sources of finance enables the owner-manager to retain control over the firm and to maintain operational independence (Jordan et al., 1998). Pecking order theory can explain why less profitable firms generally have more debt. These firms borrow because they do not have sufficient internal funds and because debt has lower costs for them than external equity. Pecking order theory, in contrast to trade-off theory, does not envisage a target leverage ratio. However, the two theories may be of particular relevance to identify the determinants of small business access to bank leverage (Holmes and Kent, 1991; Reid, 1996; Berggren et al, 2000; Watson and Wilson, 2002).

4 In a context of crisis, the accentuation of SME difficulties to rely on financial leverage could be mainly explained by two factors: the unfavorable evolution of credit supply and demand mechanisms and the aggravation of firm default risk. According to the Bank of France (2012, Bulletin No. 188), the 2008 global crisis has led for most of the European countries, including France, to a slowdown in funding approval and disbursement to applicant businesses. The annual growth rate of credits has significantly decreased during the crisis period. This rate fell brutally to become negative for certain categories of firms, primarily SMEs. Despite a slower deceleration of credits granted to firms in France in comparison with some other European countries, the situation reflects a sharp deterioration in access to loans. Credit institutions, particularly banks which have accepted high levels of firm risk before the crisis, experienced substantial losses during the economic downturn. Henceforth, these losses forced them to reduce their lending activity until restoring a proportion of equity considered as sufficient in the meaning of Basle standards. Following the crisis, credit institutions have therefore tried to reduce their exposure to risk by reducing the availability of credit or restricting its access. Consequently, the 2008 global crisis appears to aggravate the financing conditions of SMEs, deemed risky by nature. Moreover, it simultaneously worsens their default risk. In this regard, Fougère et al. (2012) investigate the effect of the 2008 financial crisis on firm failures in the French context. They base their analysis on a wide sample of firms created between January 1, 2000 and December 31, First, they note that failures of companies during the period 2008 to 2010 were preceded by an increase in business creations during the period 2003 to Therefore, they decide to distinguish among the failures from 2008 to 2010, those arising from the global crisis of those resulting mechanically from the business demography since many disappear during their first years of existence. This distinction is interesting because it allows identifying and isolating the only impact of the financial crisis. Finally, they find significant proportions of crisis-related failures. These proportions vary according to the industry and amount to 27% in the retail trade sector, 35% in the transport sector, 43% in the manufacturing sector and 46% in the construction sector. As explained above, trade-off and pecking order theories are here applied together as a dynamic theoretical framework to identify a set of firm attributes that may influence small business access to bank leverage during the global crisis period. The study examines the

5 influence of such corporate drivers as size, profitability, growth, tangibility and earnings volatility on bank debt proxies, namely debt to assets, debt to equity and debt to market ratios. 3. Research design 3.1. Sample The financial information used in this article is available on DIANE, which is managed and commercialized by Van Dijk Electronic Publishing Office 1. This database provides financial information of French firms listed on the Euronext Paris stock exchange. In this study, the initial sample is composed of all non-financial French SMEs available on DIANE over the four-year period between 2008 and Financial, insurance and holding firms ( and NACE codes 2 ) are excluded because of their specific accounting rules. The studied period is of a particular importance. It offers the possibility to investigate small business access to bank leverage during the recent global crisis. The initial sample represents 1,766 small businesses-years. Then, 111 observations have been eliminated because of insufficient data. Hence, the final sample consists of 1,655 small businesses-years employing less than 250 people, with sales under 50 million, and whose balance sheet does not exceed 43 million (European Commission criteria) Empirical model specifications In order to study the determinants of small business access to bank leverage under crisis circumstances, we use the regression model given below: BL {D/A, D/E or D/M} it = α 0 + α 1 SI it + α 2 PR it + α 3 GR it + α 4 TA it + α 5 VO it + λ i + μ t + ε it Where for firm i, year t: D/A = Bank Leverage (BL) measured as Debt to Asset ratio; The NACE code is a European industry classification chart which is comparable to the US or UK SIC.

6 D/E = Bank Leverage measured as Debt to Equity ratio; D/M = Bank Leverage measured as Debt to Market Value ratio; SI = Size = Ln (total assets); PR = Profitability = ROA (Return on Assets = Net Income divided by total assets); GR = Growth = Growth in sales; TA = Tangibility = Non-current assets divided by total assets; VO = Volatility = Coefficient of variation in net income; λ = Individual effect of each firm in the sample; μ = A set of dichotomous variables controlling for time effect of each year, and ε = Error term. 4. Results 4.1. Descriptive statistics Table 1 summarizes the descriptive statistics regarding both dependent and independent variables. The Debt to Assets ratio represents an average of 20.2%. The Debt to Equity ratio reaches an average of 49%. The Debt to Market Value ratio shows an average of 26.8%. These findings indicate that French SMEs use significant proportions of bank leverage to finance their operations. They are relatively similar to those obtained by Cassar and Holmes (2003) in Australia and Degryse et al. (2012) in Germany. Regarding the independent variables, the average firm size, calculated as the natural logarithm of total assets, is The average profitability is -1.8%, i.e. the net income of French SMEs represents on average -1.8% of total assets during the crisis period. The average growth in sales reaches 12.9%. However, there are important differences for this variable between the first and the third quartiles (-9% and 18%, respectively).the average level of tangibility is 45.9%%. More than 45% of the total assets of French SMEs comprise noncurrent assets. Finally, the volatility of earnings has an average value of -44.7%. Take in Table 1 Table 2 presents the Spearman correlation matrix for the independent variables. This matrix allows us to identify possible problems of co-linearity between the various

7 independent variables. As expected, some of the correlations are statistically significant. For example, size is positively correlated with tangibility at the 1% level, which shows that large firms have high levels of asset tangibility. On the other hand, profitability is negatively correlated with earnings volatility at the 5% level, which indicates that profitable firms have low levels of earnings volatility. Despite the existence of some statistically significant correlations among these variables, the coefficients do not appear to be high enough to cause co-linearity problems. Take in Table Regression analysis Table 3 presents the results of the regression analysis. Size is positively linked to bank leverage. This result is coherent with that of previous empirical studies on SMEs (Bougheas et al, 2006; Degryse et al, 2012). Effectively, a high accounting value of a firm measured by its total assets provide for creditors an interesting reimbursement guarantee with respect to an asset-based approach of solvency. This variable behaves as an approximation of long term guarantees available for creditors. The explanation of this phenomenon can be found in bank perception of project risk. Banks are more incited to finance tangible asset renewal than projects aimed at establishing an R&D process or purchasing a patent. On the other hand, the asset tangibility positively affects bank leverage for French SMEs. This result is consistent with that obtained for the size variable. The presence of collateral is an important factor for small business access to external financing sources. These guarantees help decrease information asymmetries between a firm and its creditors. Their presence also provides banks with reducing exposure to bankruptcy risk. Profitability is negatively correlated with the different proxies of bank leverage. The relationship is statistically significant at the 1% and 5% levels for the Debt to Assets and Debt to Equity ratios, respectively. This variable of profitability increases agency costs and impels managers not to use bank leverage, or even decrease it, which would explain the obtained negative relationship. According to the picking order theory, this negative relationship reveals a preference of corporate managers for internal over external (i.e. bank leverage) sources of financing. This preference helps corporate managers of profitable firms to maintain a high degree of control and decisional independence (Cosh and Hughes, 1994; Jordan et al., 1998).

8 In addition, the growth variable shows alternately positive and negative regression coefficients. However, these coefficients are not statistically significant at the 10% level. These findings indicate that growth has no impact on access to bank leverage during the crisis, although listed SMEs tend to be growth-oriented organizations. In contradiction with the prediction of both trade-off and pecking order theories, earnings volatility seems to have no influence also on bank leverage of French SMEs throughout the crisis lapse of time. This result may be due to the fact that bankers expect to observe high earnings volatility for a large fraction of SMEs during a period of crisis and, consequently, do not subject their decisions to such a variable. On the whole, the findings show that indicators of size and tangibility are by far more important than those of profitability, growth and earnings volatility in explaining access to bank leverage under crisis circumstances. Take in Table 3 5. Conclusion This paper employs a corporate characteristic framework to study the main features of small business access to bank leverage under crisis circumstances. The sample, studied over a period going from 2008 to 2011, consists of 1,655 firms-years which employ fewer than 250 persons and whose annual turnover does not exceed 50 million euro. The empirical analysis examines the influence of such determinants as size, profitability, growth, tangibility and earnings volatility on bank debt proxies, namely debt to assets, debt to equity and debt to market ratios. From a broad perspective, the empirical analysis leads to several interesting results. In particular, indicators of size and tangibility are positively related to bank leverage proxies. Moreover, they are by far more important than those of profitability, growth and earnings volatility in explaining access to bank leverage. These findings lay stress on the need of small businesses, above all, to provide sufficient guarantees when they wish to incur new bank leverage under crisis circumstances. The study deals with a level of analysis unmatched by previous research on French small businesses in times of crisis. Thus, the findings discussed in this paper may be useful for academics, practitioners, and policy makers at a time when consequences of the global crisis on this category of firms are more and more evoked.

9 References Andrade, G. and Kaplan, S. (1998). How costly if financial (not economic) distress? Evidence from highly leveraged transactions that became distressed. Journal of Finance, Vol. 53, No. 5, pp Bank of France (2012). Firm financing and default risk [in French]. Bank of France, Bulletin No. 188, pp Berggren, B., Olofsson, C. and Silver, L. (2000). Control Aversion and the Search for External Financing in Swedish SMEs. Small Business Economics, Vol.15, No.3, pp Cassar, G. and Holmes, S. (2003). Capital structure and financing of SMEs: Australian evidence. Accounting and Finance, Vol.43, No.2, pp Cosh, A.D. and Hughes, A. (1994). Size, financial structure and profitability, in A. Hughes and D.J. Storey (eds.), Finance and the small firm, Routledge, London, pp Degryse, H., Goeij, P., and Kappert P. (2012). The Impact of Firm and Industry Characteristics on Small Firms Capital Structure. Small Business Economics, Vol. 28 No. 4, pp Drobetz, W. and Fix, R. (2003). What are the determinants of the capital structure: some evidence from Switzerland. Research Paper, University of Basel, Basel. Fougère P., Golfier C., Horny G. and Kremp E. (2012). Did the 2008 crisis affect the survival of French firms? Research Paper, CNRS - Bank of France. Holmes, S. and Kent, P. (1991). An empirical analysis of the financial structure of small and large Australian manufacturing enterprises. The Journal of Small Business Finance, Vol.1, No.2, pp Jordan, J., Lowe, J. and Taylor, P. (1998). Strategy and financial policy in UK small firms. Journal of Business Finance & Accounting, Vol.25, No.1/2, pp.1-27.

10 Myers, S.C. (1984). The capital structure puzzle. The Journal of Finance. Vol.39, No.3, pp Myers, S.C. (2001). Capital structure. Journal of Economic Perspectives, Vol.15, No.2, pp Myers, S.C. and Majluf, N.S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, Vol.13, No.2, pp Reid, G.C. (1996). Mature micro-firms and their experience of funding shortages. Small Business Economics, Vol.8, No.1, pp Watson, R. and Wilson, N. (2002). Small and medium size enterprise financing: A note on some of the empirical implications of a pecking order. Journal of Business Finance and Accounting, Vol.29, No.3/4, pp

11 Table 1: Descriptive statistics for dependent and independent variables Variables Mean Std. Dev. Quartiles D/A 0,202 0,285 0,026 0,124 0,318 D/E 0,490 0,341 0,147 0,525 0,807 D/M 0,268 0,583 0,000 0,052 0,327 SI PR GR TA 0,459 0,278 0,219 0,443 0,682 VO

12 Table 2: Pearson correlation matrix Variables SI PR GR TA VO SI (0.000) (0.698) (0.000) (0.562) PR (0.001) (0.291) (0.013) GR (0.916) (0.975) TA (0.453) VO 1

13 Table 3: Regressions of bank leverage proxies on corporate characteristics Variables Eq. (1) D/A Eq. (2) D/E Eq. (3) D/M Intercept -0,169 [0,040] -0,293 [0,045] -0,508 [0,184] (0,000) (0,000) (0,006) SI 0,248 [0,004] 0,426 [0,004] 0,259 [0,017] (0,000) (0,000) (0,000) PR -0, 027 [0,025] -0,059 [0,028] -0,029 [0,100] (0,000) (0,011) (0,566) GR -0,028 [0,001] 0,006 [0,002] -0,001 [0,002] (0,240) (0,796) (0,982) TA 0,069 [0,052] 0,074 [0,060] 0,035 [0,243] (0,004) (0,001) (0,085) VO 0,035 [0,001] 0,034 [0,001] -0,007 [0,002] (0,143) (0,130) (0,893) Fixed effects Y Y Y Obs. 1,625 1,625 1,625 R2 0,091 0,174 0,099 This table reports regression coefficients, standard errors in brackets and P values in parenthesis.