El endeudamiento empresarialfactores determinantes e influencia en la cotización bursátil. Una comparación internacional
- Arruebarrena Alonso, José Ramón
- Eduardo Martínez Abascal Director
- Carmen Aranda León Co-director
Universidade de defensa: Universidad de Navarra
Fecha de defensa: 12 de xaneiro de 2016
- Fernando Gómez-Bezares Pascual Presidente/a
- Antonio Moreno Ibáñez Secretario/a
- Gabriel de la Fuente Herrero Vogal
- Teresa Corzo Santamaría Vogal
- Pablo Fernández Vogal
Tipo: Tese
Resumo
The international analysis of firm¿s financing in 31 countries and 44 sectors between 1989 and 2007 shows that equity is 50 % of total assets and debt is 21 % of total assets -13 % long term debt and 8 % short term debt-. In the sample period there is a decrease in long term financing compensated with an increase in equity. Leverage is different among countries and sectors -using the Kruskal-Wallis test, a test of mean differences or a Tobit regression-. Both country and sector are determinants of corporate leverage, but they explain only a small part of the whole variance, a different part of the variance each of them. Using Kruskal-Wallis critical difference it is not possible to group similar countries or sectors by long, short and total debt ratios. Groups built on just two of these ratios are not stable in the sample period and the characteristics of the members do not show any common pattern. Credit accessibility increases long term debt, decreases short term debt and decreases trade credit, therefore reducing firm¿s vulnerability. Both country and sector are statistically significant but not enough to explain the variability of debt ratios. Including 25 firm-specific and macroeconomic variables, a panel data model estimated with fixed effects explains up to 84 % of the total variance of 127.779 observations belonging to 18.076 firms of 29 countries and 45 sectors between 1989 and 2007. Among the variables, the study considers the cost of debt and the GDP growth up to six years lagged. To our knowledge, these variables have not been studied before. The main determinant of leverage is the individual effect -more than 50 % of total leverage-. The country and the sector, as part of it, explain together up to 19 % of variance. The independent variables explain up to 36 % of variance. There is not a main independent variable explaining total debt -the most relevant one explains only 9 % of total variance- and the six more relevant variables account only for 29 % of total variance. The same pattern applies to long term debt. In the short term debt, the working capital, tangible and intangible assets are the main variables. The sign of the coefficients is the same among countries and sectors but relative importance of each variable is not the same. Results have been checked using a Tobit panel data model and a dynamic panel data model. An alternative specification of the dependent variable has also been used without substantial change in the results. Using a 2SLS panel data model to take into account endogeneity between firm value and leverage, a open function of leverage is used -eight different polynomic functions from the simplest one to an order four polynomial- and the one that best fits the data using the adjusted R2 is chosen. To control for sector risk only 7 sectors of USA are analyzed -4.886 observations belonging to 666 firms between 1989 and 2007-. As a conclusion the market does not consider leverage as a value driver. Firms that are not financially constrained are explained better than those who are. To check the robustness of the results, portfolios are built on leverage and analyzed; a different sample has been used; different definitions of the dependent variable have been used; different definitions of the independent variable have been used; and different criteria to split the sample in constrained and unconstrained firms have been used. Conclusions hold: leverage is not a driver of share value; the relationship between firm value and leverage is different among sectors and changes over time; there is not a hump-shaped function none of the estimated functions and only 15 % of the portfolios show this pattern-; in 43 % of all portfolio-year snapshots the maximum Tobin-q value belongs to the portfolio with the minimum leverage; and, the leverage of portfolios with the highest Tobin-q, leverage is lower than 24 %.