The Determinants of SME Capital Structure:
Evidence from Countries of French and Scandinavian Origin
by
Aleksandrina Ralcheva
Supervisor: Dr. H. Vrolijk
Co-assessor: Prof. Dr. C. L. M. Hermes
International Financial Management
Faculty of Economics and Business
1
Abstract
This study examines how the country’s institutional and financial environments influence the capital structure choice of 3842 SMEs in Finland, France, Greece, Italy, Portugal and Sweden. The analysis yields two important results. First, there are consistent differences in the institutional and financial characteristics between the countries of French and Scandinavian origin, as well as in the capital structure of SMEs active in these countries. Second, these differences in the capital structure of SMEs can be explained by the differences in the legal and financial frameworks they operate in. Specifically, SMEs in countries with less effective legal systems and more developed bond markets tend to use less long-term and more short-term debt. These results have important policy implications.
JEL Classification: G32
Keywords: Capital structure; Leverage; Institutional environment; Financial environment;
Scandinavian origin; French origin
1. Introduction
2 environment on capital structures. Within the European framework the ‘capital structure puzzle’ (Myers, 1984) is addressed by exploring the capital structure determinants of SMEs in a single country or a set of countries (e.g. Sogorb-Mira, 2005 and Mateev et al., 2013), however, a little attention is given to a cross-country comparative analysis. Additionally, most research fails to address how the differences in the institutional and financial environments affect the capital structure choices of firms.
This study aims to build on previous research by looking into the differences in the institutional and financial environments as determinants of the capital structure of European micro, small and medium-sized enterprises (hereafter SMEs), focusing on a cross-country comparison between countries of French and Scandinavian origin. I formulate the following broad research question: Does the legal and financial environment influence the capital structure of SMEs? And I try to answer the following more detailed questions: First, are there any differences in the institutional and financial environment French and Scandinavian SMEs operate in? Second, can the differences in the capital structure of SMEs be explained by the differences in the legal and financial frameworks of the surveyed countries? Third, what important implications for policy makers could be drawn from this study? The last question is particularly important, because different institutional factors can promote better access to financing for SMEs and therefore also better growth opportunities. According to the European Commission 99% of all European businesses are considered SMEs, emphasizing on their importance as a key driver for economic growth, innovation, employment and social integration. The issue of how SMEs are financed should be brought to the forefront of the policy makers’ agenda because of the role and importance of SMEs in the context of social and economic development.
3 asset structure, size, growth and profitability. The results suggest that the effectiveness of a country’s legal system and the country’s bond market structure importantly affect the capital structure of SMEs. Operating in a stronger legal environment, Scandinavian SMEs prove to have better access to long-term debt financing, which results in higher long-term debt ratios and lower short-term debt ratios. Additionally, they possess larger levels of tangible assets that can be used as collateral and are more profitable. Interestingly, I find that SMEs in countries with better developed bond markets have lower long-term debt ratios and higher short-term debt ratios and explain this outcome with the larger size of the government bond markets, since government bonds tend to crowd out long-term corporate debt.
The rest of the paper is organized as follows. Section 2 discusses relevant existing literature. Section 3 develops the testable hypothesizes. Section 4 addresses the differences in the institutional and financial environments of the French and Scandinavian countries. Section 5 introduces the data and variables, and Section 6 presents the preliminary results. Section 7 reports and discusses the results of the regressions analysis. Section 8 concludes.
2. Prior studies
Despite the wide variety of capital structure research, in terms of SMEs and cross-country differences in financing decisions, the existing literature so far (with only few exceptions) has focused either on the capital structure determinants of SMEs in a single country (e.g. Van der Wijst and Thurik, 1993; Hall et al., 2000; Sogorb-Mira, 2005), a set of comparable countries (Daskalakis and Psillaki, 2008), transitional economies (Mateev et al., 2013) or on cross-country comparison for a sample of listed companies (e.g. Rajan and Zingales, 1995; Bancel and Mittoo, 2004).
4 how the financing decisions of firms differ within the different institutional and financial environments.
Rajan and Zingales (1995) are one of the first to look into the issue from an international perspective. In their study they use a sample of public firms from the G-7 countries to establish whether the financing decisions in countries with different institutional structures are similar to those in the US. They find that the differences between the G-7 countries are not easily attributable to differences in their institutional environments. Demirgüç-Kunt and Maksimovic (1999) look into the capital structure of large and small companies in 19 developed and 11 developing countries. They find that the underlying legal and institutional differences explain a large portion of the variation in the use of long-term debt. A related study of Booth et al. (2001) tries to assess whether the capital structure theories are portable across countries with different institutional structures by examining the financing decisions of firms in developing countries. They prove that there are persistent differences across countries, implying that country-specific determinants play a certain role; however, they conclude that more research needs to be done to understand the impact of institutional factors. In a later study Giannetti (2003) tries to address this issue by examining a sample consistent of predominantly unlisted companies from several European countries, that way eliminating the bias induced by the use of samples of large listed companies. Her findings suggest that financing decisions differ across countries because of differences in the legal rules and the degree of financial market development. In another study, Bancel and Mittoo (2004) employ a qualitative research by surveying managers from sixteen European countries on the determinants of capital structure. They find that firms’ capital structures are influenced by both the institutional framework of their home country and by their international operations.
5 recent study, De Jong et al. (2008) not only find that firm-specific determinants of leverage differ across countries, but also emphasize that these country-specific factors can affect corporate leverage both directly and indirectly. Building on Demirgüç-Kunt and Maksimovic (1999), Fan et al. (2012) examine how the institutional environment influences capital structure and debt maturity choices of firms in 39 developed and developing countries. They find that a country’s legal and tax system, corruption and the preferences of capital suppliers explain a significant portion of the variation in leverage and debt maturity ratios.
One of the few studies that address the cross-country differences in capital structure of SMEs is the one of Hall et al. (2004). They examine the capital structure of SMEs in eight European countries and find variations across the countries in both their capital structure and the capital structure determinants. However, their main aim is to establish whether these differences are due to country-specific factors or to differences between countries in firm-specific factors. The results show that variations are likely to be due to country differences as well as firm-specific ones. Daskalakis and Psillaki (2008) build on this research by examining the capital structure determinants of SMEs using a sample of Greek and French firms. Their results show that the SMEs in both countries exhibit similarities in their capital structure choices. They attribute these similarities to the institutional and financial characteristics of both countries and in particular the commonality of their civil law systems. In a subsequent study Psillaki and Daskalakis (2009) expand their research by including also Italian and Portuguese SMEs in their sample; however, their work produces similar results. Table A1 in the Appendix summarizes the reviewed literature.
6
3. Capital structure determinants and hypotheses development
This section discusses how institutional and financial differences between countries can affect the way SMEs within these countries are financed. I consider some country-specific variables that have been identified by previous literature as determinants of the capital structure of the firm. Overall, I expect that weaker legal systems are associated with less external financing and that the leverage of the firm depends on the availability of the different sources of financing, introduced in the following subsections.
3.1. Legal system effectiveness
La Porta et al. (1998) argue that the extent of legal protection of external investor varies across countries and that the quality of enforcement of these laws matters for the corporate ownership patterns around the world. Their findings suggest that legal systems based on common-law tradition offer considerably higher investor protection compared to those based on civil-law tradition. According to the same authors, within the civil-law family the French countries offer the worst legal protection for both shareholders and creditors, while the Scandinavian countries score the highest on the anti-director and creditor rights indices. Additionally, the French civil law countries have the lowest quality of law enforcement and the Scandinavian countries – the highest. The results of the study of La Porta et al. (1997) suggest that the legal environment, as described by both legal rules and their enforcement, matters for the size and the extent of a country’s capital markets. French civil law countries prove to have both the weakest investor protection and the least developed capital markets.
In a subsequent study Demirgüç-Kunt and Maksimovic (1999) find evidence that firms in countries with effective legal system have more long-term debt and lower short-term liabilities as compared to companies in countries with less effective legal system. Additionally, Fan et al. (2012) find that the strength of a country’s legal system and public governance affect the firm capital structure, as weaker laws and more government corruption are associated with higher corporate debt ratios.
7 H1: The legal system effectiveness has a positive effect on long-term leverage and a negative effect on short-term leverage.
3.2. Banking sector development
Demirgüç-Kunt and Maksimovic (1999) argue that financial intermediaries, such as banks, directly influence the financial structure of firms. They postulate that financial intermediaries have economies of scale in obtaining information and since their prime function is to monitor borrowers, banks also have incentives to use the collected information to discipline borrowers. Thus, Demirgüç-Kunt and Maksimovic (1999) expect that a developed banking sector would facilitate access to external finance, particularly among smaller firms.
Based on the argument above, I argue that SMEs in countries with more developed banking sector will have access to more external financing and formulate the following hypothesis:
H2: The banking sector development has a positive effect on leverage.
3.3. Bond market development
Booth et al. (2001) find that more highly developed debt markets are associated with higher private sector debt ratios. De Jong et al. (2008) argue that leverage is positively influenced by the bond market development, because firms have more options of borrowings and creditors are more willing to provide debts.
In the same line of thought, I expect that SMEs in countries with more developed bond markets will have higher leverage ratios. Therefore, the next hypothesis states the following:
H3: The bond market development has a positive effect on leverage.
3.4. Stock market development
8 postulate that with the development of the stock market firms face more supply of funding and thus lower costs of equity.
As a result of the aforementioned, I expect SMEs to behave similarly, therefore, lowering their leverage when operating within countries with more developed stock markets. I formulate the following hypothesis:
H4: The stock market development has a negative effect on leverage.
4. Cross-country
comparison
of
the
institutional
and
financial
environments
The purpose of this section is to provide information on the differences in the financial and legal environments in the countries being surveyed: Finland, France, Greece, Italy, Portugal and Sweden and to explore how these differences could be linked to the capital structure choices that the SMEs in these countries face.
Based on La Porta et al. (1998), the sample countries are classified into two groups, namely countries with French origin (France, Greece, Italy and Portugal) and countries with Scandinavian origin (Finland and Sweden). Both groups belong to the so called civil-law tradition, which according to legal scholars is the oldest, most influential and the most widely distributed legal tradition around the world. As the Scandinavian legal tradition is to a lower extent derived from the Roman law as compared to the French and although it is usually viewed as part of the civil-law family, the Nordic tradition is described by most scholars as ‘distinct’ from others.
9 improvement. The 2012 report is based on the Financial Development Index, which ranks 62 of the world’s leading financial systems and capital markets. There are seven broad ‘pillars’ of the Index1:
1) Institutional environment: encompasses financial sector liberalization, corporate governance, legal and regulatory issues, and contract enforcement;
2) Business environment: considers human capital, taxes, infrastructure, and costs of doing business;
3) Financial stability: captures the risk of currency crises, systemic banking crises, and sovereign debt crises;
4) Banking financial services: measures size, efficiency, and financial information disclosure;
5) Non-banking financial services: includes IPO and M&A activity, insurance, and securitization;
6) Financial markets: encompasses foreign exchange and derivatives markets, and equity and bond market development;
7) Financial access: evaluates commercial and retail access.
An overview of how each of the surveyed countries performs according to the different pillars is available under Table A3 in the Appendix. Among all six countries, Sweden scores the highest on the Financial Development Index, followed by France, Finland and the rest of the French countries. Overall, the Scandinavian countries seem to offer better corporate governance, contract enforcement and legal regulation, therefore also better institutional environment. Finland and Sweden also offer better business environment, financial stability and financial access. The rest of the results are rather mixed with Portugal and Sweden scoring the highest in terms of banking financial services and France scoring the highest in terms of non-banking financial services and financial markets. However, the seven pillars and their subpillars represent really broad measures of the institutional and financial environment the countries offer, which implies the necessity to explore them in greater depth, thus addressing some indicators entering the composition of the Index.
10 For the purpose of this paper, I am going to discuss in more detail some indices (that were also found relevant in the extant literature, e.g. Antoniou et al., 2008; De Jong et al., 2008; Gianetti, 2003 and Psillaki and Daskalakis, 2009)2 of the Institutional environment, Banking financial services, Financial markets and the Financial access pillars for each of the countries surveyed. They are presented in Table 1.3 The indicators of the Business environment, Financial stability and Non-banking financial services pillars are not found so relevant for the capital structure choice of companies.
Table 1: Some economic indicators and indicators of the institutional and financial environment
Origin French Scandinavian
Country France Greece Italy Portugal Finland Sweden
Panel A - Economic indicators
GDP per capita (in US$, 2011) 44,008.2 27,073.4 36,266.9 22,413.5 49,349.5 56,956.3 Real GDP growth rate (in %, 2007-2011) 0.04 -2.79 -0.91 -0.61 -0.39 0.77 Financial assets of major type to GDP (in %, 2010) 373.0 361.5 330.2 412.7 217.5 367.6 Public debt securities (in % of total fin. assets) 22.1 40.1 36.0 22.6 22.3 10.7 Private debt securities (in % of total fin. assets) 35.6 27.4 31.9 37.8 25.4 37.6
Banking deposits (in % of total fin. assets) 22.1 25.9 27.5 30.9 29.5 17.5
Equity securities (in % of total fin. assets) 20.2 6.6 4.7 8.7 22.8 34.2
Panel B - Institutional environment
Shareholder rights (on the scale from 1 to 7) 4.64 4.28 3.53 4.31 6.06 5.63 Corruption (on the scale of 1 to 10) 7.01 3.39 3.91 6.10 9.40 9.30 Legal rights (on the scale from 1 to 10) 7.00 4.00 3.00 3.00 8.00 7.00 Legal efficiency (on the scale from 1 to 7) 4.54 3.08 2.79 3.51 5.60 5.47
Panel C - Financial environment
Bank assets (in % of GDP, 2010) 130.38 128.96 145.17 201.15 97.93 138.67 Private credit (in % of GDP, 2010) 111.59 105.92 114.79 186.57 92.04 133.42 Stock market capitalization (in % of GDP, 2011) 74.65 20.79 15.17 38.66 43.11 111.98 Private bond market cap. (in % of GDP, 2011) 54.71 32.92 49.96 67.26 20.82 52.35 Public bond market cap. (in % of GDP, 2011) 61.34 51.03 88.59 47.07 11.88 24.44 Credit access (on the scale from 1 to 7) 2.93 1.72 2.94 2.37 4.77 4.58 Stock access (on the scale from 1 to 7) 4.72 2.48 3.41 3.04 4.55 4.84 Loan access (on the scale from 1 to 7) 2.97 1.71 1.98 2.30 4.41 4.56 Source: The Financial Development Report 2012
2 Table A2 in the Appendix reviews, among others, relevant institutional and financial variables used in previous
studies.
11 4.1. Economic indicators
Panel A of Table 1 gives an overview of two main indicators of economic development: GDP per capita and the real GDP growth rate. The GDP per capita indicates differences in wealth in each country. Across the countries surveyed the indicator ranges from 22,413.5 in Portugal to 56,956.3 in Sweden. The countries with Scandinavian origin distinguish themselves with really high values of the indicator with an average of 53,152.9, while the GDP per capita of the French countries averages 32,440.5.4 The real GDP growth rate is a measure of the general economic conditions. Within the sample only Sweden and France show positive growth rate and Greece seems to be performing the worst.
Panel A of Table 1 also includes the distribution of the four major type of financial assets: Public and Private debt securities, Banking deposits and Equity securities, from which conclusions regarding the financial development and tradition in each country could be drown. In Sweden the Equity and the Private debt securities markets seem to dominate, while in countries like Greece, Italy and Portugal the Equity securities sector seems to play an insignificant role. The Banking deposits as a proportion of all assets available seem to be highest in Finland, but overall the distribution of assets within the country is similar. Within the French countries, the Public and Private debt securities markets seem to be most developed.
4.2. Institutional (legal) environment
Panel B of Table 1 presents some indicators of the institutional environment. As an indicator of the efficiency of the legal system, I incorporate the so called Effectiveness of law-making bodies index that ranges from 1 (very ineffective) to 7 (very effective). The Scandinavian countries in the sample score really high on the index and seem to have the most efficient legal systems (2nd and 3rd place) within the 62 countries included in the Financial Development Report 2012. In comparison, Portugal, Greece and Italy score below the mean of 3.79 (n=62), implying that they have much less efficient legal systems in place. The legal system of France is rated in between. The Corruption index provides additional information for the efficiency of the legal system and is an aggregate indicator that ranks countries in terms of the degree to which corruption is perceived to exist among public officials and politicians. Higher scores indicate less
12 extensive corruption. The results of the Corruption index complement these of the Legal efficiency index. Finland and Sweden again score the highest (1st and 3rd place respectively) among 62 countries, implying that they have the lowest levels of corruption. Among the French countries in the sample, Greece and Italy have the lowest values of the index, while Portugal and France perform averagely. Overall, the French countries seem to have less efficient legal system with higher levels of corruption as compared to the Scandinavian countries.
The Legal and Shareholder rights indices are used as a further comparison of the legal environment French and Scandinavian firms operate in. The Legal rights index measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and lenders and thus facilitate lending. It ranges from 0 to 10, with higher scores indicating better creditor protection and therefore better access to credit. According to Panel B of Table 1, Finland, Sweden and France score the highest on the index with a huge difference between them and the rest of the French countries. The Shareholder rights index measures the degree of protection of minority shareholders and ranges from 1 (not protected at all) to 7 (fully protected). The Scandinavian countries again score at the top (1st and 4th place) among 62 countries. From the French countries surveyed Italy has the lowest value of the index, thus, also the lowest quality of shareholder protection. France, Portugal and Greece score around the mean of 4.48 (n=62). Overall, the Scandinavian countries seem to offer both better creditor and shareholder protection.
4.3. Financial environment
Panel C of Table 1 summarizes selected indicators of the financial environment. The Deposit money bank assets to GDP (Bank assets) ratio is used as a proxy for the access to financial intermediaries by firms. There are variations across the two sets of countries. Portugal has the highest and Finland the lowest ratio, while the rest of the countries score in the middle. The Private credit to GDP (Private credit) ratio is used as an additional measure of the banking sector development. The countries surveyed show similar results as compared to the previously discussed ratio. Portugal again has the highest ratio and Finland – the lowest.
13 According to Table 1, Sweden has the highest Stock market capitalization, while Italy has the highest (both public and private) Bond market capitalization indicator. Overall, the Scandinavian countries seem to have more developed stock markets and the least developed bond markets, while countries with French origin have more developed bond markets and the least developed stock markets.
I also present three additional indicators that complement the discussion so far. The Credit access index measures the ease of access to credit for companies and is a proxy for the availability of short-term debt in each country. According to Table 1, the Scandinavian environment offers a lot better access to that type of financing as compared to the French countries in the sample, which score way below the mean of 3.71 (n=62). The Loan access index measures how easy it is for companies to obtain a bank loan with only a good business plan and no collateral and is a proxy for the availability of long-term debt financing. In terms of this index the surveyed countries show similar results as before. The Stock access index measures how easy it is for companies to raise money by issuing shares on the stock market and is a proxy for the availability of equity financing in each country. Sweden, France and Finland offer much better access to that type of financing as compared to the rest of the countries in the sample, which generally score beyond average (3.97, n=62).
Based on the previous section and the preliminary evidence presented in this section, I expect that leverage is higher in counties with good quality of the legal system, good creditor rights protection, well developed banking system, low stock market capitalization and high bond market capitalization. My overall conclusion is that Scandinavian firms should have better access to external sources of finance and more specifically long-term financing.
5. Description of the data and variables
14 5.1. Data selection
The sample of SMEs considered in this study has been extracted from the Orbis database5. Only firms that meet the European Commission criteria regarding SMEs have been selected. The European Commission defines micro, small and medium-sized enterprises (hereafter SMEs) as enterprises, which employ fewer than 250 persons and which have an annual turnover not exceeding 50 million euro, and/or an annual balance sheet total not exceeding 43 million euro.6
In order to enhance the quality of the data, some filters are applied based on data quality and availability (specifically availability of all essential financial variables and a complete record over the period of the examination). As per standard practice, companies from the financial and utility sector are excluded. The companies from each country are randomly selected and represent around 0.05% of the population, information for which was retrieved from the database for the Annual report on European SMEs 2012/2013 of the European Commission ‘A recovery on the horizon?’7. The sample consists of 3842 SMEs situated in one of six countries: Finland, France, Greece, Italy, Portugal or Sweden, and covers a five-year period from 2008 to 2012, resulting in a total of 19 210 balanced panel data observations.
5.2. Sample overview
Table A5 in the Appendix gives an overview of the sample, broken down by country code, firm size defined as micro, small or medium, legal form, age and sector according to the NACE Rev. 28 classification. The different countries are also grouped according to their legal system origin, which is either Scandinavian or French as defined by La Porta et al. (1998). The countries with Scandinavian origin (Finland and Sweden) represent 13% of the whole sample, while those with French origin (France, Greece, Italy and Portugal) take up the reminder of 87%. Amongst all, Italy and France are represented the most, as the highest amount of total SMEs in Europe is located there. Furthermore, micro companies (defined as having less than 10 employees)
5 Orbis is a database provided by Bureau Van Dijk. It contains comprehensive information on companies worldwide,
with an emphasis on private company information.
6 Source is the website of the European Commission: http://ec.europa.eu/index_en.htm, last accessed on 08.01.2014
at 10:00.
7
The database is available at http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/performance-review/, last accessed on 06/06/2014.
8 NACE Rev. 2 is a statistical classification of economic activities in the European Community, launched on 1st of
15 represent the largest share of all companies in the sample – 48%. Another 39% of the sample consists of small companies (less than 50 employees), while medium-sized companies (less than 250 employees) take up only 13%. The sample consists predominantly of private companies (75%) and does not include public companies from the Scandinavian countries, which is also one of the limitations of this study. The sample includes companies of various age with the largest group between 10 and 30 years. The sample consists also of companies from various industries (classified according to NACE Rev. 2). However, both manufacturing and wholesale and retail trade prevail over the rest of the sectors.
5.3. Choice of variables
Following Rajan and Zingales (1995), Michaelas et al. (1999), Sogorb-Mira (2005), the variable that I intend to explain is SME capital structure, which is measured by the total leverage ratio (total debt to total assets). However, some scholars argue (e.g. Van der Wijst and Thurik, 1993) that any analysis of leverage determinants based only on total liabilities may screen the important differences between long-term and short-term debt. To tackle this issue and since short-term debt is an important mean of financing for SMEs, I introduce the following two measures of leverage: long-term leverage ratio (long-term debt to total assets) and short-term leverage ratio (short-term debt to total assets).
16 To control for the differences in firm characteristics between countries I introduce a set of firm-specific variables that are suggested by previous literature to be empirically useful in explaining capital structure decisions of SMEs (Hall et al., 2004, Daskalakis and Psillaki, 2008 and Psillaki and Daskalakis, 2009) – Asset structure, Size, Growth and Profitability. The asset structure is represented by the ratio of tangible assets to total assets and is used as a measure of collateral. Firms with a high ratio of tangible assets should have greater borrowing capacity. Firm size is calculated as the natural logarithm of total assets and is used as an inverse proxy for the probability of bankruptcy, whereby larger firms are less likely to face financial distress and bankruptcy. Growth is calculated as the annual change in total turnover. Firms with significant growth opportunities are likely to take more risk and therefore are considered risky, which is the reason they face difficulties in raising debt capital on favorable terms. As a proxy for profitability I use the ratio of earnings before tax to total assets. Profitable firms would have more internal financing available, therefore they would rely less on external financing.
I also include a dummy variable that takes the value of 1 if the country the SME operates in is of a Scandinavian origin and 0 otherwise. Table A6 in the Appendix presents a summarized description of all the variables discussed.
6. Preliminary evidence on capital structure
In section 4 I discussed the differences in the institutional and financial environment French and Scandinavian SMEs operate in. As a result, the financial structures of the sample of firms should vary systematically across countries. In this chapter I try to assess the extent of these differences by discussing the descriptive statistics of selected variables.
6.1. Descriptive statistics
17 but the lowest short-term leverage in their capital structure. SMEs in the countries of French origin seem to have the highest levels of short-term leverage. These differences can easily be attributed to the differences in the institutional and financial environments SMEs operate in. However, SMEs with different characteristics have different access to the financial markets even within the same country. Table A7 in the Appendix presents the average ratios of short-term, long-term and total leverage by year, firm size (micro, small or medium), legal form, age and sector. Significant differences across the firm sizes do not appear. Significant year to year changes in leverage are also not observable. However, private firms seem to have both higher short-term and long-term debt ratios, which implies that public firms tend to substitute debt financing with equity financing. In terms of age, younger firms seem to rely more on short-term debt as compared to older SMEs, which could be explained by the fact that younger firms are considered a lot more risky and therefore are less likely to be granted access to long-term debt financing. Panel E of table A7 illustrates that leverage ratios vary across industries. The average long-term debt ratios are highest in the Agriculture, forestry and fishing sector and lowest in the Mining and quarrying, Manufacturing, Construction and Wholesale and retail trade industries (consistent with Hall et al., 2000). The average short-term debt ratios are highest in the Information and communication and Administrative activities sectors and consequently lowest in the Agriculture, forestry and fishing sector.
Table 2: Descriptive statistics of the dependent variables by country and country origin
Table 3: Descriptive statistics of the firm-specific variables by country and country origin Variable
Descriptive stat. N Mean Med Max Min SD Mean Med Max Min SD Mean Med Max Min SD
French origin 16710 0.602 0.600 73.240 0.003 0.650 0.077 0.013 2.177 0.000 0.126 0.524 0.505 73.240 0.000 0.648 France 6130 0.620 0.585 73.240 0.004 0.998 0.073 0.014 1.664 0.000 0.121 0.547 0.499 73.240 0.004 0.994 Greece 360 0.593 0.600 1.619 0.011 0.262 0.109 0.025 0.652 0.000 0.153 0.484 0.456 1.569 0.011 0.263 Italy 8635 0.585 0.608 5.553 0.003 0.260 0.066 0.003 2.177 0.000 0.111 0.520 0.524 5.553 0.000 0.256 Portugal 1585 0.622 0.635 10.814 0.010 0.474 0.150 0.102 1.836 0.000 0.177 0.471 0.431 10.814 0.000 0.478 Scandinavian origin 2500 0.603 0.567 15.783 0.005 0.624 0.200 0.071 15.572 0.000 0.580 0.403 0.356 3.151 0.005 0.258 Finland 750 0.656 0.630 6.679 0.005 0.456 0.258 0.170 5.154 0.000 0.375 0.397 0.345 2.216 0.005 0.252 Sweden 1750 0.580 0.524 15.783 0.013 0.682 0.174 0.018 15.572 0.000 0.647 0.406 0.361 3.151 0.011 0.260 Total sample 19210 0.602 0.597 73.24 0.003 0.647 0.093 0.017 15.57 0.000 0.243 0.508 0.484 73.24 0.000 0.613
Total leverage Long-term leverage Short-term leverage
Variable
Descriptive stat. N Mean Med Max Min SD Mean Med Max Min SD Mean Med Max Min SD Mean Med Max Min SD
French origin 16710 0.201 0.120 0.997 0.000 0.212 7.432 7.507 10.665 2.090 1.666 0.017 -0.002 27.362 -0.998 0.468 0.032 0.026 1.178 -7.880 0.172 France 6130 0.148 0.090 0.958 0.000 0.163 6.186 6.026 10.616 2.090 1.429 0.037 0.013 17.760 -0.981 0.429 0.052 0.051 0.996 -4.126 0.192 Greece 360 0.298 0.236 0.949 0.000 0.256 8.215 8.220 10.392 4.685 1.194 -0.031 -0.043 2.030 -0.760 0.313 0.020 0.013 0.505 -0.635 0.104 Italy 8635 0.226 0.140 0.997 0.000 0.230 8.152 8.323 10.665 2.567 1.353 0.010 -0.009 27.362 -0.998 0.503 0.022 0.020 1.029 -7.880 0.157 Portugal 1585 0.246 0.188 0.935 0.000 0.220 8.150 8.211 10.619 3.909 1.260 -0.012 -0.031 10.217 -0.949 0.443 0.013 0.014 1.178 -4.861 0.174 Scandinavian origin 2500 0.305 0.193 0.994 0.000 0.290 6.254 6.212 10.444 1.911 1.527 0.083 0.042 16.681 -0.992 0.570 0.056 0.063 1.004 -2.742 0.218 Finland 750 0.438 0.446 0.994 0.000 0.287 7.091 6.920 10.444 3.466 1.380 0.058 0.042 3.526 -0.970 0.332 0.031 0.051 0.599 -2.742 0.227 Sweden 1750 0.248 0.117 0.987 0.000 0.272 5.895 5.845 10.280 1.911 1.444 0.094 0.042 16.681 -0.992 0.645 0.067 0.070 1.004 -2.279 0.213 Total sample 19210 0.214 0.125 0.997 0.000 0.226 7.279 7.305 10.66 1.911 1.695 0.025 0.002 27.36 -0.998 0.483 0.035 0.028 1.178 -7.880 0.179
Size Growth Profitability
6.2. Correlation matrices
Table 4: Correlation matrices
Note: Panel A presents the correlations between the dependent and independent variables. Panel B presents the cross-correlations of the independent variables. P-values are given in italics. The abbreviations of all variables are explained in Table A6 in the Appendix.
LegEff Corrupt ShrareR LegalR BankA PrCre StMCap BMCap GDPCap GDPGr AssStr Size Growth Profit SoDum
21 Panel B of Table 4 presents the correlations between the explanatory variables. The Legal efficiency, Corruption, Shareholder rights and Legal rights indices are strongly positively correlated with each other, which may lead to a problem of multicollinearity. These four institutional environment indicators are also strongly positively correlated with the Stock market capitalization index, strongly negatively correlated with the Bond market capitalization index and strongly positively correlated with GDP per capita and the real GDP growth rate. SMEs in countries with an effective legal system tend to be smaller, more profitable and have higher growth opportunities. The Scandinavian origin dummy is strongly positively correlated with all the indicators of the legal environment. In these countries, the correlation with shareholder rights is stronger as compared to legal rights, implying a preference towards protecting shareholders. The relation between the financial environment indicators and the other variables is mixed. Countries with larger banking systems tend to have lower ratios of stock market capitalization to GDP and higher ratios of bond market capitalization to GDP. Larger banking sector is also significantly negatively correlated with the GDP variables. Better developed stock markets are consistent with higher GDP per capita and higher GDP growth. The opposite applies for better developed bond markets. SMEs in countries with a better developed banking system and a better developed bond market tend to be bigger, less profitable on average. On the opposite, SMEs in countries with better developed stock markets tend to be smaller and more profitable. The Scandinavian origin dummy is strongly negatively correlated with the size of the banking system and the bond market development index, but strongly positively correlated with the stock market development index. The four firm-specific variables do not show strong correlations.
7. The determinants of SME capital structure
22 7.1. Methodology
As significant changes in the legal systems of countries from year to year are rare and the financial development indicators do not vary over time, and consistent with Demirgüç-Kunt and Maksimovic (1999), my investigation of the determinants of capital structure relies primarily on cross-sectional analysis across countries, taking as observations the time-series country means of each variable. To avoid the problem of multicollinearity arising from the high correlations between several of the country-specific variables and following De Jong et al. (2008), I construct four new variables to use as alternatives in the regression analysis. I utilize Legal system effectiveness (LSE) variable calculated as the average of the normalized values of the Legal efficiency and the Corruption indices, Banking sector development (BSD) variable calculated as the average of the normalized values of the Bank assets and the Private credit variables, Bond market development (BMD) variable calculated as the average of the normalized values of the Legal rights and the Bond market capitalization indices, and Stock market development (SMD) variable calculated as the average of the normalized values of the Shareholder rights and the Stock market capitalization indices.
I adopt the following methodology, estimating OLS regressions with leverage as the dependent variable:
LEV = β0 + β1LSE + β2BSD + β3BMD + β4SMD + β5GDPCap + β6GDPGr +
+ β7AssStr + β8Size + β9Growth + β10Profit + β11SoDum + ε
7.2. Results
The results of the regression analysis are reported in Table 5. Panel A and B present the OLS regressions with the two dependent variables – long-term leverage and short-term leverage, respectively. Table A8 in the Appendix reports the results of the regressions estimated with total leverage as dependent variable. Equations 1, 2, 3, 4, 7 and 8 include the whole sample, while equations 5 and 6 look into the private and public subsamples respectively.9 Equations 9 and 10
9
23 consider additional two subsamples based on the NACE Rev. 2 classification. I look separately into the capital structure determinants within the service and trade industries (SE & Trade)10 and the rest of the industries included in the sample (Non-SE&T)11. This distinction is important, because companies within the service and trade sectors generally possess fewer tangible assets and therefore have also lower tangible to total assets ratios. This in turn means fewer assets available to serve as collateral and thus restrained access to long-term leverage, which is also evident from Table A7 in the Appendix. The explanatory and control variables are as defined in previous sections. Equation 1, 2 and 3 include a Scandinavian origin dummy, GDP per capita and GDP growth variables to control for the impact of the general economic conditions. However, they do not alternate the results nor show any significance. Equation 7 and 8 exclude the LSE and SMD variables respectively. This is important, as these two variables measuring the Legal system effectiveness and the Stock market development are still strongly positively correlated with each other and their joint impact should be interpreted with caution. The number of observations and the values of the adjusted R-squared are also included. The adjusted R2 of all the regressions is generally low, which is typical for this type of research and consistent with Hall et al. (2004). However, the value of the adjusted R2 raises considerably when the sample of public SMEs is taken into account. This indicates that this model specification captures a better part of the variations in SME capital structure. Therefore, the differences between public and private companies should not be neglected in capital structure studies.
The top half of Panels A and B in Table 5 reports the coefficient estimates for the country-specific variables. For the whole sample of SMEs the results indicate that long-term leverage is positively related to the legal system effectiveness (consistent with Hypothesis 1) and negatively related to the bond market development (opposite sign as predicted by Hypothesis 3), but unrelated to the banking system development (Hypothesis 2). Short-term leverage, on the other side, is positively related to the bond market development (Hypothesis 3). The banking system development (Hypothesis 2) variable also fails to explain the short-term debt ratio. Additionally,
10
The European Commission considers as service sectors the industries from I to N according to NACE Rev. 2 (I – Accommodation and food services; J - Information and communication; L - Real estate activities; M - Professional, scientific and technical activities; N - Administrative and support services). It is referred to G - Wholesale and retail trade as trade sector.
11 The Non-SE&T subsample includes the industries A - Agriculture, forestry and fishing; B - Mining and
24 Equations 7 and 8 offer some partial support for Hypothesizes 1 and 4. According to the results, the stock market development has a significant positive effect on long-term leverage and significant negative effect on short-term leverage. The legal system effectiveness has also a negative impact on short-term leverage.
There are some significant differences between the subsamples. In particular, the legal efficiency variable is significant for the set of private SMEs, but insignificant for the sample of public SMEs. There are two explanations for this outcome. Firstly, this study has some data limitations, since it does not include any public SMEs from the Scandinavian countries. Second, the relation between the legal system development and stock market structure variables is especially relevant for the subsample of public SMEs and is such that the effects on the capital structure choice seem to be mutually exclusive. Another important difference is evident from equations 9 and 10. A better developed legal system seems to be especially important for the access to long-term debt of SMEs within the service and trade sectors. SMEs in sectors with higher tangibility, such as Manufacturing and Construction, can compensate the lack of efficient legal system with better collateral, therefore gaining better access to long-term debt financing. Additionally, the results suggest that the stock market development is significantly negatively related to the long-term leverage of SMEs within the service and trade industries and to the short-term leverage of SMEs within the other industries.
The results of the analysis of total debt as dependent variable presented in Table A8 in the Appendix barely show any significance in terms of the country specific variables. This is important to note, as the results emphasize on the important differences between short-term and long-term financing and support the fact that the use of total leverage masks the two opposite effects of the explanatory variables on long-term and short-term leverage.
25
Table 5: Regression results
Equation 1 2 3 4 5 6 7 8 9 10
Sample All sample All sample All sample All sample Private Public All sample All sample SE&Trade Non-SE&T
27 The results regarding asset structure are consistent with Demirgüç-Kunt and Maksimovic (1999) and Hall et al. (2004). As expected, long-term leverage is correlated with the amount of tangible assets, which serve as good collateral for long-term debt. Also according to Myers (1977), the length of the loan is likely to be matched to the length of life of assets used as collateral, implying that long-term debt will be increased at the expense of short-term debt where long-term assets are available. Other scholars look into the total leverage and find out that it is positively related to asset tangibility (Rajan and Zingales, 1995, Booth et al., 2001, De Jong et al., 2008 and Fan et al., 2012). Psillaki and Daskalakis (2009) find a negative relation between asset structure and the leverage of SMEs, but this could be explained by the fact that SMEs are financed with a higher portion of short-term debt as compared to long-term debt. With regard to profitability, the results are also consistent with Hall et al. (2004), but inconsistent with Demirgüç-Kunt and Maksimovic (1999). More profitable firms naturally possess more internally generated funds, which would reduce the need of borrowing. Rajan and Zingales (1995), Booth et al. (2001), De Jong et al. (2008), Psillaki and Daskalakis (2009) and Fan et al. (2012) also find a negative relation between profitability and leverage. Again consistent with Hall et al. (2004) growth is positively related to short-term debt. SMEs with growth opportunities have incentives to take risk to grow. This increased risk is reflected in increased cost of long-term financing, which would lead to higher reliance on short-term financing.
7.3. Discussion
28 Italy, Portugal and Sweden. As expected on average the Scandinavian SMEs have higher long-term-leverage, and the French SMEs higher levels of short-term leverage. What is more, the Scandinavian as compared to the French SMEs seem to have higher ratio of tangible assets to total assets, to be smaller in size, to have higher growth rate and to be more profitable.
Secondly, I try to analyze whether the differences in the capital structure of SMEs can be explained by the differences in the legal and financial framework of their home countries. I formulate four hypothesizes that way linking the financing patterns of SMEs to their business environment and in particularly its legal effectiveness and market development.
The first hypothesis states that the legal system effectiveness has a positive effect on long-term leverage and a negative effect on short-long-term leverage. The preliminary results already show that there is a positive relation between all the legal environment indicators and long-term leverage, and a negative relation between them and short-term leverage. The results of the regression analysis offer additional strong support and are consistent with the results of Demirgüç-Kunt and Maksimovic (1999). More effective legal systems can mitigate agency problems and facilitate for increasing creditors’ confidence, thus granting better access to long-term debt financing.
The second hypothesis I formulate predicts a positive relation between the banking sector development and leverage, but doesn’t differentiate between long-term and short-term leverage. The preliminary results show that the Private credit variable is positively related to long-term leverage and negatively related to short-term leverage. However, the regression analysis predicts the same relation between the Banking sector development variables and the two dependent variables, but the results show no significance. Although Demirgüç-Kunt and Maksimovic (1999) find also that the size of the banking sector by itself is not significant, they also find that creditor rights are and important determinant of the banking sector development, implying that the strong creditor rights in this case indirectly promote access to long-term credit for small firms.
29 This outcome is later confirmed by the regressions analysis, according to which the bond market structure has significant negative impact on long-term leverage and significant positive impact on short-term leverage. The results are quite surprising, as the primary goal of the bond market is to provide a mechanism for long-term financing. This phenomenon can be caused by the inclusion of the Public bond market development index in the analysis. Although the presence of government borrowers can help the debt market develop by increasing the demand for corporate debt, it can also have a negative effect on corporate borrowing. According to Fan et al. (2012), if there is a fixed supply of debt capital, then government debt can compete for that fixed supply and leave less available for corporate borrowers. In contrast, De Jong et al. (2008) find that the level of bond market development has a positive impact on capital structure by looking into a sample of 11,845 firms in 42 countries.
The fourth hypothesis predicts that the stock market development would have a negative effect on leverage. However, the preliminary results for both the Shareholder rights and the Stock market development indices show a positive relation to long-term leverage and a negative relation to short-term leverage. The regression analysis gives contradicting, but overall not significant results. Demirgüç-Kunt and Maksimovic (1999) get a similar outcome. This could be explained with the fact that the marginal effect of stock market development is relatively smaller than that of the effectiveness of the legal system, thus yielding insignificant results. De Jong et al. (2008) also do not find support for the negative impact of stock market structure on leverage.
Taken together, the results suggest that for SMEs the observed variation in the levels of long-term and short-long-term debt across countries of French and Scandinavian origin is related to the effectiveness of the legal system and the development of the bond market. Additionally, the availability of collateral is associated with better access to long-term financing, while high profitability seems to reduce the use of both short and long-term leverage. Growth is associated with better access to short-term financing.
30 business environment for SMEs. More effective legal and financial institutions such as the Scandinavian help alleviate SMEs’ growth constraints and increase their access to external financing, which in terms also promotes their development.
According to the European Commission SMEs are a key part of the European Union corporate sector accounting for more than 99% of all business and two-third of the employment, which reflects their importance within the overall economic development of Europe. The analytical report of the European Commission ‘2013 SMEs’ access to finance survey’ additionally stresses that the access to finance is one of the most pressing problems SMEs face. They have very different needs and face different challenges with regard to financing compared to large businesses, which have ready access to equity capital markets not so easily accessible for SMEs. That makes small business more reliant on short-term financing and on different external sources of financing such as bank loans. These differences in the financing patterns of SMEs require special policy attention addressing the needs of SMEs for adequate financing. A focus on improving the legal and financial environment for SMEs is important, as it facilitates growth not only for the SME sector, but for the entire economy.
8. Conclusions
31 development seems to have a negative impact on long-term leverage and a positive impact on short-term leverage. However, due to data limitations (insufficient amount of public SMEs with Scandinavian origin) the effect of the stock market development is not clearly observable.
The results and conclusions of this study are also limited to the specific sample and capital structure determinants used. Additionally, the data set only distinguishes between short-term and long-term debt and does not provide information on the composition of the external financing, which leaves many issues regarding the choice of source of financing for SMEs unexplored.
Future research can greatly benefit if these limitations are overcome. Looking into a larger set of countries would definitely contribute the analysis with respect to reducing the correlation between the variables and to finding more significant results. A wider range of country-specific, as well as firm-specific variables should also be considered, as well as the possible impact of indicators comprising the three not included pillars of the Financial Development Index. As this study only touches upon the differences between public and private SMEs, it will be of additional interest for future research to explore them in more detail. The analysis could further be improved by considering an alternative model and a broader time period in order to track whether the capital structure choice of SMEs is greatly influenced by changes in the economic conditions. Specifically, it would be of interest to analyze how the financial crisis and the related policies changed the institutional environment SMEs operate in and as a result also their capital structures.
32
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35
Appendix
Table A1: Summary of the reviewed literature
Study Aim Sample Period Findings
Rajan and Zingales (1995)
Their primary objective is to establish whether capital structure in other countries is related to factors similar to those appearing to influence the capital structure of US firms.
Public firms in the G-7 countries (the US, Japan, Germany, France, Italy, the UK and Canada)
1987-1991 Firm leverage is more similar across the G-7 countries than previously thought, and the differences that exist are not easily
explained by institutional differences previously thought important.
Demirgüç-Kunt and Maksimovic (1999)
Their main objective is to examine how differences in financial and legal institutions affect the use of debt and especially the choice of debt maturity.
Small and large firms in 30 developed and developing countries with both common-law and civil-law legal systems
1980-1991 The underlying legal and institutional differences explain a large portion of the variation in the use of long-term debt.
Booth et al. (2001) Their main aim is to assess whether the capital structure theories are portable across countries with different institutional structures.
Largest companies in 10 developing countries (India, Pakistan, Thailand, Malaysia, Turkey, Zimbabwe, Mexico, Brazil, Jordan and Korea)
1980-1990 There are persistent differences across countries, indicating that specific country factors are at work. Although some of the insights from modern finance theory are portable across counties, much remains to be done to understand the impact of different institutional features on capital structure choice.
Giannetti (2003) The paper examines how firm characteristics, legal rules and financial development affect corporate finance decisions.
Unlisted companies from 26 European countries
1993-1997 Financing decisions differ across countries because of differences in the legal rules and the degree of financial market development. Bancel and Mittoo
(2004)
They examine whether European and US managers' views on capital structure are driven by similar factors. They also examine the role of legal institutions in explaining the financing policies of firms across countries.
Managers in 16 European countries
36 Antoniou et al. (2008) The paper investigates how firms
operating in capital market-oriented economies and bank-oriented economies determine their capital structure.
Companies traded in the major stock exchanges of the 5 major
economies of the world (France, Germany, Japan, the UK and the US)
1987-2000 The capital structure of the firm is heavily influenced by the economic environment and its institutions, corporate governance practices, tax systems, the borrower-lender relation, exposure to capital markets and the level of investor protection in the country in which the firm operates.
De Jong et al. (2008) They analyze the importance of firm-specific and country-firm-specific factors in the leverage choice of firms.
Small and large firms in 42 countries
1997-2001 Firm-specific determinants of leverage differ across countries. Although they concur with the conventional direct impact of county-specific determinants of the capital structure of firms, they show that there is an indirect impact because country-specific factors also influence the roles of firm-specific determinants on leverage.
Fan et al. (2012) The study examines how the institutional environment influences capital structure and debt maturity choices of firms.
Firms in 39 developed and developing countries
1991-2006 A country's legal and tax system, corruption and the preferences of capital suppliers explain a significant portion of the variation in leverage and debt maturity ratios.
Hall et al. (2004) The research considers international differences in capital structure and their determinants for small and medium-sized enterprises.
SMEs from 8 countries (Belgium, Germany, Spain, Ireland, Italy, the Netherlands, Portugal and the UK)
1995 There are variations in both SME capital structure and the determinants of capital structure between the countries surveyed. These variations could be due to country differences as well as firm-specific ones.
Daskalakis and Psillaki (2008)
This article examines whether national or firm-specific differences have an effect on SME capital structure.
SMEs from Greece and France
1997-2002 The SMEs in both countries exhibit similarities in their capital structure choices. They attribute these similarities to the institutional characteristics and in particular the commonality of the civil law systems of both countries.
Psillaki and Daskalakis (2009)
This paper compares the capital structures of SMEs across countries, the capital structure determinants of SMEs and their impact on capital structure choice.
SMEs from Greece, France, Italy and Portugal
37
Table A2: Summary of the variables and methods used by other studies
Study Dependent variables Firm-specific variables Country-specific variables Method
Rajan and Zingales (1995)
Book and market leverage (in 1991)
Tangibility, Market-to-book ratio, Logarithm of net sales, Profitability (1987-1990 averages)
OLS-Regression
Demirgüç-Kunt and Maksimovic (1999)
Long-term debt to total assets ratio, Short-term debt to total assets ratio, Long-term debt to total debt ratio
Net fixed assets to total assets, Profitability, Net sales to net fixed assets, Dividends to total assets (1980-1991 averages)
GDP per capita, Growth of real GDP per capita, Inflation, Stock market turnover, Stock market capitalization, Total assets of the deposit money banks divided by GDP, Government subsidies to GDP, Law and order indicator, Legal efficiency indicator, Shareholder rights index, Creditor rights index (1980-1991 averages)
OLS-Regression
Booth et al. (2001) Total debt ratio, Long-term book debt ratio, Long-term market debt ratio
Average tax rate, Assets tangibility, Business risk, Size, Return on assets, Market-to-book ratio
Stock market value to GDP, Real GDP growth rate, Inflation rate
Simple pooling and fixed effects model
Giannetti (2003) Leverage Tangible to long-term assets, Intangible to long-term assets, Non-debt tax shield, Return on assets, Variability of returns
Law enforcement, Creditor protection index, Bond market capitalization, Stock market capitalization, Concentration of the banking system
Firm-fixed effects and two-stages least squares
Bancel and Mittoo (2004)
Major determinants of capital structure according to the respondents, such as Financial flexibility and Tax advantage
Firm size, P/E ratio, Foreign sales, Short-term debt to total debt
Creditors' rights index, Shareholders' rights index, Private credit to GDP, Stock market turnover, Tax rates, Corporate ownership concentration
Questionnaires and Cross-sectional regression analysis
Antoniou et al. (2008) Book leverage, Market leverage
Profitability, Growth opportunities, Tangibility of assets, Firm size, Effective tax rate, Earnings volatility, Dividend payout, Non-debt tax shield, Share price performance
Equity premium, Term structure of interest rate, M&A Activity, Rule of law,
Ownership concentration, Creditor rights index, Anti-director rights index
38 De Jong et al. (2008) Leverage Tangibility, Business risk,
Firm size, Tax rate, Growth opportunity, Profitability, Liquidity (1997-2001 averages)
Efficiency of judicial system, Rule of law, Legality, Corruption, Creditor right protection, Bond market development, Stock market development, Shareholder right protection, Capital formation, GDP growth
OLS-Regression, HLM
Fan et al. (2012) Leverage Tangibility, ROA, Size, Market-to-book ratio
Inflation rate, Corruption index, Bankruptcy code, Tax, Deposits to GDP, Government bonds
GMM approach
Hall et al. (2004) Short-term debt ratio, Long-term debt ratio
Profitability, Growth, Asset structure, Size, Age
Cross-sectional
regression analyses Daskalakis and Psillaki
(2008)
Leverage Asset structure, Size, Profitability, Growth
Balanced panel data
model Psillaki and Daskalakis
(2009)
Leverage Asset structure, Size, Profitability, Growth, Risk
Private credit, Market capitalization, Judicial efficiency, Contract enforcement, Corruption, Property rights, Legal formalism
