The Influence of Data Imputation Methods on the Classification Efficiency of the Logit Model Used for Forecasting the Bankruptcy of Companies

Dorota Ewa Grochowina ()
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Dorota Ewa Grochowina: Cracow University of Economics

Acta Universitatis Nicolai Copernici, Ekonomia, 2014, vol. 45, issue 2, 187-203

Abstract: Forecasting the bankruptcy of companies exposes the missing data problem, which applies chiefly to entities having financial problems, who wish to conceal thereby their bad situation. One of the methods of making up incomplete data is imputation. The aim of the paper is to present different data imputation variants and to compare their influence on the classification efficiency of one of the statistical bankruptcy forecasting methods – the logit model. The results have shown that the best approach is to use the median as determined separately for healthy and bankrupt companies.

Keywords: bankruptcy; forecasting bankruptcy; logit model; imputation; missing data estimation; model classification efficiency. (search for similar items in EconPapers)
JEL-codes: C53 G17 G33 (search for similar items in EconPapers)
Date: 2014
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