Functional form issues in the regression analysis of financial leverage ratios
Abstract
Linear models are typically used in the regression analysis of capital structure choices. However, given the proportional and bounded nature of leverage ratios, models such as the tobit, the fractional regression model and its two-part variant are a better alternative. In this paper, we discuss the main econometric assumptions and features of those models, provide a theoretical foundation for their use in the regression analysis of leverage ratios and review some statistical tests suitable to assess their specification. Using a dataset previously considered in the literature, we carry out a comprehensive comparison of the alternative models, finding that in this framework the most relevant functional form issue is the choice between a single model for all capital structure decisions and a two-part model that explains separately the decisions to issue debt and, conditional on the first decision, on the amount of debt to issue.Download Info
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Paper provided by University of Evora, CEFAGE-UE (Portugal) in its series CEFAGE-UE Working Papers with number 2011_28.Length: 42 pages
Date of creation: 2011
Date of revision:
Handle: RePEc:cfe:wpcefa:2011_28
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Related research
Keywords: Capital structure; Zero leverage; Fractional regression model; Tobit; Twopart model.;Other versions of this item:
- Joaquim Ramalho & J. Silva, 2013. "Functional form issues in the regression analysis of financial leverage ratios," Empirical Economics, Springer, vol. 44(2), pages 799-831, April.
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-02-20 (All new papers)
- NEP-ECM-2012-02-20 (Econometrics)
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