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The Financial Structure of Italian Companies

The choice of capital structure by firms is a recurring topic of corporate finance and evolving on a theoretical and empirical level. On a theoretical level, scholars propose variations to the models by removing the theoretical hypothesis or expanding variables considered, likewise, on an empirical level, researchers provide survey, which contributions aimed at increasing the understanding of the phenomenon as a whole, considering the possible events in the variety and variability of firms. In particular, one of the most debated topics in the literature regards the existence or absence of relationship between the choices of financial structure and firm value, or the determination of an optimal leverage for the value. Therefore, the attention of researchers has focused on the identification of relationship between debt and equity that maximizes firm’s performance and meet shareholders’ expectations in terms of return on capital employed for the same risk. Hence, the aim of this paper is to provide another piece to the cognitive complexity of the phenomenon, focusing the research on Italian firms, given the importance of leverage in the financial structure of Italian firms. The methodology used is based on the analysis conducted using the Mediobanca database aggregated sector by sector to identify the main determinants of financial structure. The conclusion is that it is not possible to say with certainty which financial structure theory better represents the behavior of Italian firms concerning financial structure.


Introduction
Since Modigliani and Miller argued the irrelevance of financial structure on the economic value of the firm under certain conditions, several studies have also tried to identify and justify the relationship between leverage choices and firm context.
In particular, in recent years different studies have tested this argument referring exclusively to U.S. firms.
The topic of financial structure plays a crucial role especially for the effects that they produce on the risk, the cost of capital, the cash flow dynamics and, more in general, on the firm value.
For Italian firms, the choice of financial structure has a great importance, considering the different respects to the European firms, such as the undercapitalization and the excessive incidence of short-term debt. characteristics, the structure of Italian firms has high levels of leverage, with strong exposure to the forms of short-term debt, a general level of undercapitalization, with high incidence of loan capital respect to equity.
The effect of managerial and financial characteristics qualifies the intensity and the structure of the relationship between firms and financial system. In particular, the excessive use of leverage and the high incidence of short term debt are at the origin of the reasons for the fragility of the financial structure that are represented respectively by the exposure to financial risk, given the rigidity of financial costs, and the instability of funding sources which is linked to their maturities. This is due to the fact that the development and the financial complexity of firms are related to their size, as evidenced by the size of Italian firms, resulting in average smaller than the main international competitors.
A second cause is to be found in the conformation of Italian financial system, as a result of banking legislation of 1930s remained in force until the 1993 Consolidated Law on Banking. However, neither the Consolidated Law on Banking nor Consolidated Law on Finance was able to bring solutions to the financial imbalance of Italian firms, moreover amplified due to of financial crashes in recent years (Forestieri, 2005).
In light of this, the present paper has two objectives, the first is to identify the behavior of the level of debt for each sector under investigation, and the second is to ascertain the methodological superiority of a theory respect the other in the field of financial structure.

Literature
The literature has offered several models of interpretation on the financial structure of firms related to the types of funding sources and to their dimensional characteristics. The school of traditionalists, which included among others, Dean (1951), Graham and Dodd (1951), Guthmann and Dougall (1955) argued that a certain level of debt has a positive impact on value theorizing, in this sense, which exists of an optimal debt ratio. According to this approach, a special relationship exists between debt and equity that minimizes the weighted average cost of capital and maximizes the total value invested in the firm. Then the propositions of Modigliani and Miller (1958) have represented the heart of the modern theory of finance, not only for its content, but also to the methodological approach, demonstrating that in the presence of perfect capital markets, the value of a firm is independent of its funding policy, whit equity or debt.
Several studies have also tried to identify and justify the relationship between choices of leverage and firms' context.
The Trade-Off Theory (Kraus & Litzenberger, 1973) can be considered as the most direct evolution of the classical theory. Subsequently, the contributions of Myers (1984), Myers and Majluf (1984) and Fazzari, Hubbard, and Petersen (1988) have laid the foundation for the study of hierarchies of firms financing.
The Pecking Order Theory (Myers, 1984;Myers & Majluf, 1984) says, in fact, that firms in making choices on capital structure would follow a precise hierarchy using financial sources on the basis of a strategy of financial self-sufficiency.
The Asymmetric Information Theory (Myers & Majluf, 1984) bases its assumptions on the existence of asymmetric information between the management and the financial market, so that asymmetric information influences the choices between internal and external financing, or between debt and equity, reinforcing the principle of the existence of a clear hierarchy between the financial sources.

Empirical Evidence
The empirical analysis was conducted using the accounting data aggregated sector by sector for the period 1998/2007, given by Mediobanca's 2009 database (Cumulative data of 2020 Italian companies), in which there are economic and financial data of 2020 firms, aggregated in 30 different sectors.
A first level of investigation was carried out by reclassifying the sectors according to the Pavitt Taxonomy (1984), which provides the classification of sectors in relation to the sources, the technological opportunities, the level of innovation, the intensity of research and development, and the type of knowledge flows.
Theories on the financial structure recognize the existence of significant differences in the financial structure of the different sectors. In particular, according to the Bankruptcy Costs Theory, the sectors that produce goods with unique characteristics should have lower leverage, as well as, according to the Agency Costs Theory, the traditional and mature industries will have a higher level of debt (Sapienza, 1997).
This empirical analysis excludes the financial intermediation sector and the insurance sector, whose fund raising is their core business, and which financial structure must still comply with the obligations established by the Financial Regulator, and it also excludes the real estate, agriculture, and hospitality sector. In fact, data aggregates are not available for these sectors.
Data analysis was carried out on the basis of financial structure indicators and specific explanatory variables of the level of debt, considered useful to the survey. In light of this, reference is made to the study of Bigelli, Mengoli, and Sandri (2001) in their paper The determinants of financial structure of Italian firms: An empirical test on Italian companies.
The indicators of financial structure used are:  Debt Financing Ratio (DFR), which is the ratio between the debt (short-term loans, medium-term loans and bonds) and the set of sources of funding;  Debt Ratio (DR), whichis the ratio of all liabilities in the short and medium term and the total amount of sources;  EBITDA Coverage Ratio (ECR), whichis the ratio between EBITDA and interest costs.
The first ratio, DFR, is a measure that takes into account only the financial debt, considering the funding in the short and the long term. DR takes into account, in addition to the financial debt, even funding from third parties, including, trade payables and payables to employees. ECR expresses the level of interest coverage.
The explanatory variables are:  Tax Ratio (TR), which is the ratio between total taxes paid by the firm and the total turnover;  Tax Shield Ratio (TSR), which is the ratio between alternative tax shields on debt and total assets;  Tangible Assets Ratio (TAR), which is the ratio between net fixed assets and total assets;  Current Ratio (CR), which is the ratio between current assets and liabilities;  Rate of Return on Common Stockholders' Equity (ROE), which is the ratio between net income and shareholders' equity;  EBITDA Return on Assets (EROA), which is the ratio between EBITDA and total assets.

Analysis of Result
Regarding the DFR, the overall average of the sectors leads to values between 0.40 and 0.50 during the 10 years considered, as the results in Table 1 As the results in Table 3 In conclusion, in the 10 years considered DFR and DR increase up to 2003, before declining in 2004 and rise slightly in 2007, while ECR declines after 1999, before recovering slightly in 2005 and decreases in the following two years.
In Table 4, the average values of the indicators previously analyzed for each sector are reported. Table 2 Average Values of DR   ECR has a more even distribution, compared with previous results. This ratio assumes a value between 3 and 7: more precisely 8 out of 28 sectors have a value between 3 and 4, five sectors between 4 and 5, four sectors between 5 and 6, three sectors between 8 and 9, two between 6 and 7, two sectors between 1 and 2, one sector between 1 and 3, and one sectors between 0 and 1. The analysis shows good interest coverage for the sectors analyzed.

The Results of Macro-sectors
In order to facilitate the analysis of the results and correlations, the 28 sectors are classified into four macro-sectors, according to the Pavitt Taxonomy (1984) that results in Table 5.
Considering average values of the three indicators of financial structure calculated by macro-sectors, the analysis shows, as regards DFR, there is no significant differences between the traditional sectors and sectors with large economies of scale and technological sectors. In particular, the first three sectors present an average value between 0.40 and 0.50, while the sector of specialized suppliers has an average value of 0.38, as it results in Table 6.
On the contrary, as regards the DR, the Specialized Suppliers sector presents a higher value, since its range of values is between 0.70 and 0.80. The technological sector and traditional sector have a DR average value equal to 0.60 and 0.61, while the macro-sector of industries with large economies of scale has a slightly lower value equal to 0.58. These results confirm, therefore, that firms belonging to the sectors of specialized suppliers prefer more to the net operating debt respect the financial debt. This is due to the fact that this macro-sector is characterized by the presence of small firms, which have more difficulties recurring to loans, because they are unable to provide guarantees and because they cannot access to the bond market or equity market. Moreover, it seems to be confirmed by the theory of the Trade-Off, according to which firms operating in mature markets (traditional sectors) have higher levels of debt, as opposed to firms that operate on the basis of intangible assets (technology-intensive sectors). In fact, for both debt ratios, the traditional sectors show an average value higher than the technology sectors.  The values of ECR are higher for Technology sector which has an average value of 6.05, followed by the It appears that the Traditional sector has a higher frequency that is between 0.40 and 0.50, while the others one are positioned almost equally between 0.30 to 0.40 and from 0.50 to 0.60.
Regarding DR, the ratios are higher than the DFR, for all the main categories. Specialized suppliers have a DR very high, the Technological sector has values ranging between 0.50 and 0.70. The macro-sector of economies of scale has a symmetric distribution with six sectors between 0.50 and 0.70.
The frequency distribution of ECR for Traditional sectors is more homogeneous, with 50% of them with a value between 4 and 6 and the remaining 50% for the other values.

The Correlations With Determinants of Financial Structure
It proceeds with the calculation of the correlations of the three explanatory variables of financial structure with the determinants, so as to compare them with the financial structure theories.
These correlations are calculated using the Pearson coefficient between the average values aggregated and the average values of the macro-sectors, as it results in Table 7.  (1980) and according to the studies of Bigelli, Mengoli, and Sandri (2001) and Buttignon and De Leo (1994), DFR and DR should be negatively correlated with TSR, on the contrary of ECR which should present a positive correlation. The results of the survey confirm the sign of the correlations for ECR and DR and show a positive correlation for DFR. Moreover, even Bradley, Jarrel, and Kim (1984) showed a significant positive relationship between the level of debt and the tax shields.
With regard to TAR, the positive correlation emerged with DFR is consistent with the Asymmetric Information Theory and with the theory of trade off. According to these theories which firms with more intangible assets are more indebted because they can provide more guarantees, while its correlation with DR and ECR confirms the theory by Grossman and Hart (1982) that considered debt as a form of financing that allowed ownership to monitor the management. The variable CR is negatively correlated with DFR and DR and positively with ECR. This is perfectly consistent with the theory of the choice by Myers (1977Myers ( , 1984 and with the results obtained by Bigelli, Mengoli, and Sandri (2001). With regard the ROE, it results a non-significant correlation with DR, while the positive correlation with DFR seems to confirm the trade off Theory.
The correlation with EROA evidences some conflicting results. DFR is positively correlated with this variable in accordance with the trade off Theory, on the contrary of DR and ECR that confirm both results by Bigelli, Mengoli, and Sandri (2001) and by the Pecking Order Theory.  Different considerations apply to sectors that have large economies of scale, as it results in Table 9.
Regarding TR, the survey shows opposite results to those of Bigelli, Mengoli, and Sandri (2001) with a negative correlation to DR and DFR and a positive correlation for ECR. The correlations with TSR fully confirm to the De Angelo and Masulis model. The correlations with TAR confirm the theory of Grossman and Hart (1982) much more than the average values because in this case, both DFR and DR are negatively correlated. CR shows conflicting results. Its correlation with ROE and DFR is positive, while the one with the DR and ECR seems to confirm the hypothesis of Pecking Order Theory. Even the EROA meets the expectations of the Pecking Order Theory, although the correlation with the DFR is rather weak.
As regard the technological sector and the sector of specialized suppliers the correlation is not statically significant since these consist of only two sectors.

Conclusions
This paper has tried to identify the main determinants of financial structure starting from the aggregate data of every sector, in order to identify the sectoral behavior of the debt level. Specifically, the trend of debt during the period of analysis shows that DFR reaches a peak in 2003, it decreases during next period as a result of the tax reform, and finally it increases again in 2007 because of the financial crisis. ECR. This may be due to the fact that the tax reform has mitigated the tax benefits of debt compared with equity.
Also the correlations with TAR, ROE, and EROA indicate conflicting conclusions, while the correlations with CR fully confirm the Pecking Order Theory. In light of this, the paper proves that it is not possible to say with certainty which is the financial structure theory that better represents the behavior of Italian firms concerning financial structure.