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Open AccessJournal ArticleDOI

Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health

Jarmila Horváthová, +1 more
- 17 Mar 2020 - 
- Vol. 11, Iss: 3, pp 160
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TLDR
The main conclusion of the paper is that the DEA method is a suitable alternative in assessing the financial health of businesses from the analyzed sample and the results of this method are independent of any assumptions.
Abstract
This paper focuses on business financial health evaluation with the use of selected mathematical and statistical methods. The issue of financial health assessment and prediction of business failure is a widely discussed topic across various industries in Slovakia and abroad. The aim of this paper was to formulate a data envelopment analysis (DEA) model and to verify the estimation accuracy of this model in comparison with the logit model. The research was carried out on a sample of companies operating in the field of heat supply in Slovakia. For this sample of businesses, we selected appropriate financial indicators as determinants of bankruptcy. The indicators were selected using related empirical studies, a univariate logit model, and a correlation matrix. In this paper, we applied two main models: the BCC DEA model, processed in DEAFrontier software; and the logit model, processed in Statistica software. We compared the estimation accuracy of the constructed models using error type I and error type II. The main conclusion of the paper is that the DEA method is a suitable alternative in assessing the financial health of businesses from the analyzed sample. In contrast to the logit model, the results of this method are independent of any assumptions.

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Citations
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Journal ArticleDOI

Management and Economic Sustainability of the Slovak Industrial Companies with Medium Energy Intensity

TL;DR: In this paper, the authors identify the groups of financial ratios that can be used to measure the financial performance of the companies operating in the Slovak mechanical engineering industry (MEI) and select the 236 largest non-financial corporations whose ranking was obtained according to the amount of generated revenues in 2017.
Journal ArticleDOI

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.
Posted Content

Diagnostikovanie finančného zdravia podnikov pomocou metódy DEA: Aplikácia na podniky v Slovenskej republike [Diagnosing of the Corporate Financial Health Using DEA: an Application to Companies in the Slovak Republic]

TL;DR: In this paper, the authors presented a new proposal for diagnosing the corporate financial health by DEA, to predict financial distress of Slovak manufacturing companies using the proposed procedure, and to assess the potential of DEA as a tool for predicting financial distress.
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Estrés financiero en el sector manufacturero de Ecuador

TL;DR: In this paper, the authors classified Ecuadorian manufacturing companies into companies with and without financial distress, based on the previous works of Altman and Ohlson, respectively, and found that microenterprises are the most distressed in a financial sense.

Analyzing the Efficiency of Travel and Tourism in the European Union

TL;DR: In this paper, the authors analyzed the efficiency of the travel and tourism industry in the European Union at the macro level by using the non-parametric approach data envelopment analysis.
References
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Journal ArticleDOI

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TL;DR: In this paper, a set of financial and economic ratios are investigated in a bankruptcy prediction context wherein a multiple discriminant statistical methodology is employed, and the data used in the study are limited to manufacturing corporations, where an initial sample of sixty-six firms is utilized to establish a function which best discriminates between companies in two mutually exclusive groups: bankrupt and nonbankrupt firms.
Journal ArticleDOI

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