POSSIBILITIES TO APPLY CLASSICAL BANKRUPTCY PREDICTION MODELS IN THE CONSTRUCTION SECTOR IN LITHUANIA

Abstract

The paper presents the results of a research of the bankruptcy prediction models’ application in the construction sector in Lithuania. During the financial crisis, many companies in the construction sector went bankrupt. Therefore, the research aims to reveal if conventional bankruptcy prediction models are applicable in this sector. Moreover, Lithuanian researchers have contradictory opinions about the possibilities to apply bankruptcy prediction models. Empirical researches provide conflicting results as well. It should also be noted that earlier Lithuanian researches (1999-2013) featured small samples of companies which could have an impact on great errors of the research results. The above mentioned reasons encourage to evaluate the accuracy of bankruptcy prediction models by examining large samples of companies and evaluating real benefits obtained from the acquired information.

The present study distinguishes by its large sample of companies that was selected for the first time (433 companies that were filed for bankruptcy in 2009-2013 were examined). To achieve the aim of the research, i.e., to evaluate the applicability of bankruptcy prediction models in Lithuanian companies of the construction sector, 5 classical statistical bankruptcy prediction models were chosen: 3 linear discriminant analytical models (Altman, Springate, Taffler) and 2 logistic regression models (Chesser, Zavgren). From Altman models, the Altman model for companies whose shares are not quoted in the stock exchange markets, Altman Z”-Score Model for the service companies and Altman Z”-Score Model for emerging countries were investigated. From Taffler models, Taffler (1973) and Taffler & Tisshaw (1977) models were analysed. The results of the research might be useful for both the executive managers of companies in the construction sector and investors who analyse the problems of the operation continuity.

The type of the article: Research paper.

Keywords: bankruptcy, bankruptcy prediction, bankruptcy prediction models.

JEL Classification: G33.

DOI: http://dx.doi.org/10.5755/j01.em.19.4.8095