title: The development of bankruptcy prediction models in modern Russian economy
metadata.name: dc.contributor.author
metadata.value: Kazakov, Aleksandr V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Kolyshkin, Alexander V.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2018-06-21T11:22:32Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2018-06-21T11:22:32Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2018-06
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Kazakov A. V., Kolyshkin A. V. The development of bankruptcy prediction models in modern Russian economy. St Petersburg University Journal of Economic Studies, 2018, vol. 34, issue 2, pp. 241–266.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: 10.21638/11701/spbu05.2018.203
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/10302
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The paper focuses on problems of bankruptcy prediction models in Russia. This issue gains more and more relevance in recent years, in the light of falling incomes of population. The bankruptcy prediction models are widely used to predict bankruptcy. However, they might have low accuracy. In that regard, there is an active discussion in the foreign literature. In Russia there is a growing number of models developed, however so far no detailed studies to assess their efficiency. There are several objectives of the current study: a detailed review of domestic literature to reveal the flaws of existing models; design of a new set of models accounting to analyzed flaws; suggestions for future research. The estimation of Russian models revealed their inefficiency, due to data instability problem, poor financial reports quality, insufficient sample size, and distortion effect of “black accounting” and criminal bankruptcy practices. The set of models offered was proved to be efficient and robust. As the way of further model improvement it was suggested to distinguish between possible scenarios of failure (including liquidation, merger and “freezing”) using statistical classification methods. The Benfords Law analysis was introduced to separate companies falsifying financial statements. The application showed this method as promising.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: St Petersburg University Journal of Economic Studies;Volume 34; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: financial insolvency forecasting
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: financial insolvency
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: logit-regression
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: crisis management
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: The development of bankruptcy prediction models in modern Russian economy
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 03-Kazakov.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/10302/1/03-Kazakov.pdf
resources.format: Adobe PDF
resources.size: 986,91 kB