Indebtedness and profitability – A threshold model approach
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DOIhttp://dx.doi.org/10.21511/imfi.19(3).2022.02
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Article InfoVolume 19 2022, Issue #3, pp. 13-27
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This study seeks to expand upon existing empirical results about the effect of debt on corporate profitability. Indicators Debt ratio (DR) and Return on Equity (ROE) were used to examine the relationship between debt and corporate profitability. The input data for the analysis represented the financial data of companies operating in the construction industry in Slovakia. The total sample included 7,529 companies. After excluding companies with extreme values, the sample consisted of 6,402 companies. Indicators ROE and DR were used in the given research. To determine the debt threshold, a threshold regression model was applied. Using this model, a nonlinear relationship between debt and profitability was found. An indebtedness threshold has also been identified. Once the threshold is exceeded, the positive relationship between indebtedness and ROE changes to negative. The results, in particular those which indicate a significant non-linear relationship between debt and profitability, are particularly useful for all stakeholders (internal and external) interacting with analyzed companies.
Acknowledgments
The research was prepared within the grant scheme VEGA 1/0741/20 – The application of variant methods in detecting symptoms of possible bankruptcy of Slovak businesses in order to ensure their sustainable development.
- Keywords
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JEL Classification (Paper profile tab)M21, G32, C24
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References55
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Tables3
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Figures6
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- Figure 1. The share of the construction industry in GDP (%)
- Figure 2. The share of the construction industry in total employment (%)
- Figure 3. The share of constructions and buildings in gross fixed capital formation (%)
- Figure 4. Kernel density estimate of Return on Equity (ROE)
- Figure 5. Kernel density estimate of Debt ratio (DR)
- Figure 6. Scatter plot (ROE, DR)
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- Table 1. Descriptive statistics of ROE and DR
- Table 2. The threshold model with two thresholds
- Table 3. The threshold model with one threshold
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