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Open AccessJournal ArticleDOI

Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses

Róbert Štefko, +2 more
- Vol. 13, Iss: 9, pp 212
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TLDR
In this paper, the Data Envelopment Analysis (DEA) method has been applied to predict bankruptcy of a business with the aim of choosing a prediction method which will have exact results.
Abstract
The paper deals with methods of predicting bankruptcy of a business with the aim of choosing a prediction method which will have exact results. Existing bankruptcy prediction models are a suitable tool for predicting the financial difficulties of businesses. However, such tools are based on strictly defined financial indicators. Therefore, the Data Envelopment Analysis (DEA) method has been applied, as it allows for the free choice of financial indicators. The research sample consisted of 343 businesses active in the heating industry in Slovakia. Analysed businesses have a significant relatively stable position in the given industry. The research was based on several studies which also used the DEA method to predict future financial difficulties and bankruptcies of studied businesses. The estimation accuracy of the Additive DEA model (ADD model) was compared with the Logit model to determine the reliability of the DEA method. Also, an optimal cut-off point for the ADD model and Logit model was determined. The main conclusion is that the DEA method is a suitable alternative for predicting the failure of the analysed sample of businesses. In contrast to the Logit model, its results are independent of any assumptions. The paper identified the key indicators of the future success of businesses in the analysed sample. These results can help businesses to improve their financial health and competitiveness.

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Citations
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Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries

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The Application of Graphic Methods and the DEA in Predicting the Risk of Bankruptcy

TL;DR: The important finding is that the statistical graphical methods—PCA and MDS—are very helpful in identifying outliers and selecting key performance indicators entering the DEA model.
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Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure

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References
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Measuring the efficiency of decision making units

TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.
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Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis

TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Journal ArticleDOI

The Measurement of Productive Efficiency

M. J. Farrell
Journal ArticleDOI

Financial ratios and the probabilistic prediction of bankruptcy

TL;DR: In this paper, the authors present some empirical results of a study predicting corporate failure as evidenced by the event of bankruptcy, and the methodology is one of maximum likelihood estimation of the so-called conditional logit model, in which the data set used in this study is from the seventies (1970-76).
Journal ArticleDOI

Financial Ratios As Predictors Of Failure

TL;DR: In this article, the authors focus on the use of ratios as predictors of failure, defined as the inability of a firm to pay its financial obligations as they mature, and demonstrate that a firm is said to have failed when any of the following events have occurred.
Related Papers (5)
Trending Questions (2)
What is an appropriate Threshold point in bankruptcy prediction model?

The paper determined an optimal cut-off point for the Additive DEA model and Logit model in bankruptcy prediction, enhancing accuracy and reliability in predicting business failures.

How have bankruptcy prediction models evolved over time in Slovakia, and what advancements have been made?

Bankruptcy prediction models in Slovakia have evolved to include Data Envelopment Analysis (DEA), offering flexibility in choosing financial indicators. DEA provides reliable, assumption-independent results for predicting business failures.