Analysis of the relationship between classical finance determinants and capital structure: A multiple regression approach

Abstract

The way capital is structured is a major issue for key players in the business world, such as business leaders, investors, financial analysts, and economists. This refers to the financing choices that are used to support the company's current activities and investment projects. To understand companies' decisions regarding financing structures, multiple regression estimation models should be used. The data can be estimated either by Ordinary Least Squares (OLS) or by Generalized Least Squares (GLS) methods. Regression can be estimated using the OLS method, but this estimation method can be biased as it assumes that the sample companies are endogenous, thus ignoring possible individual effects. To remedy this, the standard fixed-effects estimator controls for heterogeneity of companies by allowing specific company intercept terms in the regression.

The aim of this study is to analyze the links between classical finance determinants and capital structure, using multiple regression estimation models to identify the most significant variables of companies' capital structure. To do so, we conducted a quantitative study of a sample of 65 companies listed on the Casablanca Stock Exchange, operating in 22 sectors, and covering 10 consecutive years from 2012 to 2021.

The results of the quantitative study present significant links between classical determinants and companies' capital structure. Indeed, company size, profitability, and debt level are identified as the most significant determinants of companies' capital structure. The results also indicate that companies tend to favor external financing rather than internal financing to finance their growth.

Keywords : Capital Structure, Finance, Panel Data, Multiple Regression, Morocco.

JEL Classification : G41

Paper type : Empirical Research