Considerations on the use of financial ratios in the study of family businesses
ArXiv ID: 2501.16793 “View on arXiv”
Authors: Unknown
Abstract
Most empirical works that study the financing decisions of family businesses use financial ratios. These data present asymmetry, non-normality, non-linearity and even dependence on the results of the choice of which accounting figure goes to the numerator and denominator of the ratio. This article uses compositional data analysis (CoDa) as well as classical analysis strategies to compare the structure of balance sheet liabilities between family and non-family businesses, showing the sensitivity of the results to the methodology used. The results prove the need to use appropriate methodologies to advance the academic discipline.
Keywords: Compositional Data Analysis (CoDa), Family Businesses, Balance Sheet Structure, Financial Ratios, Statistical Methodology, Corporate Finance
Complexity vs Empirical Score
- Math Complexity: 6.0/10
- Empirical Rigor: 3.0/10
- Quadrant: Lab Rats
- Why: The paper employs advanced statistical methods like compositional data analysis (CoDa) and discusses mathematical properties of financial ratios, but uses a theoretical example and survey data without backtesting or quantitative implementation metrics.
flowchart TD
A["Research Goal:<br/>Compare Balance Sheet Structure<br/>Family vs. Non-Family Businesses"] --> B["Data Input:<br/>Financial Ratios from<br/>Balance Sheet Liabilities"]
B --> C{"Methodology Selection"}
C --> D["Classical Analysis<br/>Traditional Statistical Methods"]
C --> E["Compositional Data Analysis<br/>CoDa Methodology"]
D --> F["Computational Process:<br/>Statistical Tests & Ratios"]
E --> G["Computational Process:<br/>Log-Ratio Transformations & Analysis"]
F --> H{"Key Findings & Outcomes"}
G --> H
H --> I["Results are highly sensitive<br/>to methodology choice"]
H --> J["Financial Ratios show<br/>asymmetry & non-normality"]
H --> K["CoDa provides<br/>more robust insights"]
K --> L["Recommendation:<br/>Use appropriate methodologies<br/>for accurate academic conclusions"]