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Problems of forecasting the bankruptcy of agricultural commodity producers: Russian legislation effectiveness assessment

Fedorova E.A. Financial University under Government of Russian Federation, Moscow, Russian Federation ( ecolena@mail.ru )

Khrustova L.E. Financial University under Government of Russian Federation, Moscow, Russian Federation ( khrustoval@yandex.ru )

Chekrizov D.V. ZAO GlobalTel, Moscow, Russian Federation ( CHEKrisovDV@mail.ru )

Journal: Economic Analysis: Theory and Practice, #12, 2017

Importance The article addresses the bankruptcy problem in the agricultural sector and analyzes relevant effective laws to reveal the flaws in the currently applied methodology to assess the financial condition of agricultural goods producers.
Objectives The purpose of the research is to formulate proposals to improve Russian laws in the sphere of agricultural goods producers' bankruptcy prediction.
Methods The research rests on the CART (Classification and Regression Tree) methodology whereby we specify financial ratios that are applied to evaluate agricultural companies. To estimate financial thresholds, we analyze the sampling consisting of 580 companies, including 273 bankrupts.
Results To enhance the Russian laws, we revised financial ratios enabling to determine bankrupt companies, offered a better classification of companies based on their financial ratios, considering the industry-specific features of agricultural producers. We included a new indicator with a high level of predictive capability into the existing methodology, and recommended to exclude the ratio of working capital to inventories as it has low forecasting power.
Conclusions and Relevance If implemented, the offered changes to the methodology will increase the efficiency of bankruptcy forecasting for agricultural goods producers and help take timely measures to prevent failures.


Assessing the efficiency of enterprise bankruptcy prediction on the basis of the Russian legislation

Fedorova E.A. Financial University under Government of Russian Federation, Moscow, Russian Federation ( ecolena@mail.ru )

Chukhlantseva M.A. Higher School of Economics, Moscow, Russian Federation ( chukhlantseva_maria@mail.ru )

Chekrizov D.V. ZAO GlobalTel, Moscow, Russian Federation ( CHEKrizovDV@mail.ru )

Journal: Finance and Credit, #13, 2017

Subject The article addresses the problem of predicting the probability of bankruptcy of Russian enterprises and studies the Russian legislation on the bankruptcy of economic actors, namely, commercial enterprises operating in the Russian Federation.
Objectives The aim of this work is to evaluate the efficiency of predicting the likelihood of bankruptcy based on effective legislation.
Methods We apply a method of constructing a standard logistic regression model. The method helped us to select factors affecting the enterprise bankruptcy. The paper evaluates the predictive capability of 6 models with different sets of financial ratios by building a logistic regression for each selected industry individually.
Results We compare the predictive power of models constructed on the basis of six different sets of financial ratios, three of which were designed subject to Russian regulations on insolvency (bankruptcy). The hypothesis, according to which the financials that are approved by legislative acts of the Russian Federation provide the highest predictive power of the models than the coefficients of classical models, or those that are frequently used in studies on bankruptcy prediction, was not confirmed. However, the study of 'legislative' models showed an improvement in the quality of legislative acts of the Russian Federation over time (an increase in predictive power by a few percentage points).
Conclusions The findings will enable company managers, shareholders, potential investors and other stakeholders to monitor company's current situation and forecast its bankruptcy.


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