BANKRUPTCY PREDICTION MODELS IN THE SERBIAN AGRICULTURAL SECTOR

Danica Rajin; Danijela Milenković; Tijana Radojević

doi:10.5937/ekoPolj1601089R

Authors

Danica Rajin, Ph.D. Singidunum University, Faculty of Economics, Finance and Administration FEFA, Belgrade
Danijela Milenkovi?, Ph.D. Singidunum University, Faculty of Economics, Finance and Administration FEFA, Belgrade
Tijana Radojevi?, Ph.D. Singidunum University, Faculty of Business in Belgrade, Belgrade

DOI:

https://doi.org/10.5937/ekoPolj1601089R

Keywords:

Altmans Z-score, DF model, Quick test, models of predicting bankruptcy proceedings

Abstract

The aim of this paper is to present different models for predicting the possibility of opening bankruptcy proceedings in companies in Serbia, as well as to research which models are most suitable for companies in the agricultural sector. In this paper, we have used and displayed three models: the Altmans Z-score model, Kraliceks DF model and Quick test. Many authors have dealt with this issue, but most of them have developed models for developed markets, which are different from market of Serbia. Striving towards improving the analysis and prediction of bankruptcy has led to comparison of the reference value, in order to obtain concrete models for the evaluation of difficulty in the functioning of the company. In this connection, on a sample of fve companies operating on the territory of the Republic of Serbia, we have applied three models that used standard fnancial indicators to show the fnancial condition and stability of the company. Results suggest that Kraliceks DF model indicates better fnancial state of the company than Altmans Z-score model, considering the characteristics of the market in which the model is formed.

Downloads

Download data is not yet available.

References

1. Agarwal, V., Taffler, R. (2007): Twenty-fve years of the Taffler z-score model: does it really have predictive ability? Accounting and Business Research, Vol. 37, No. 4, pp. 285-300.
2. Alihodžić, A. (2013): Testing the Kralicek DF indicator application on the Belgrade Stock Exchange. Banking, No. 3, pp. 70-95.
3. Altman, E. (1968): Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, Vol. XXIII, No. 4, pp. 589-609.
4. Beaver, W. H. (1966): Financial Ratios as Predictors of Failure. Empirical Research in Accounting, selected studies (in supplement to the Journal of Accounting Research, January, 1967), pp. 71-111.
5. Deakin, E. B. (1972): A discriminant analysis of predictors of business failure. Journal of Accounting Research (spring), pp. 167-179.
6. Didenko, K., Meziels, J., Vornova, I. (2012): Assessment of Enterprises Insolvency: Challenges and Opportunities. Economics and Management, Vol. 17, No. 1, pp. 69-76.
7. Jakovčević, K., Andrašević, J. (2011): Indikatori poteškoća u funkcionisanju industrijskog preduzeća. Industrija, No. 3, pp. 175-192.
8. Jakšić, D., Vuković, B., Mijić, K. (2011): Analiza fnansijskog položaja poljoprivrednih preduzeća u Republici Srbiji. Ekonomika poljoprivrede, Vol. 58, No. 1, pp. 81-90.
9. Machek, O. (2014): Long-Term Predictive Ability of Bankruptcy Models in the Czech Republic: Evidence from 2007-2012. Central European Business Review, Vol. 3, No. 2, pp. 14-17.
10.Maletić, R., Ćeranić, S., Popović, B. (2011): Mala i srednja preduzeća kao činioci smanjenja siromaštva u ruralnim zajednicama Srbije. Ekonomika poljoprivrede, Vol. 58, No. 1, pp. 121–131.
11.Ministry of Agriculture, Forestry and Water Management of the Republic of Serbia (2014): Strategija poljoprivrede i ruralnog razvoja Republike Srbije za period 2014-2024. godine, Offcial Gazette of the Republic of Serbia, No. 85/2014, Belgrade, available at http://uap.gov.rs/wp-content/themes/uap/STRATEGIJA%202014-2020%20.pdf
12.Muminović, S., Pavlović, V., Cvijanović, J. M. (2011): Predictive ability of various bankruptcy prediction z-score models for Serbian publicly listed companies. Industrija, Vol. 39, No. 3, pp. 1-12.
13.Muminović, S., Pavlović, V., Cvijanović, J. M. (2012): The impact of investments and changes in the production regime on the results of creditworthiness assessment and bankruptcy prediction models: Case study: Company Bulgari Filati d.o.o. Industrija, Vol. 40, No. 2, pp. 3-18.
14.Ohlson, J. (1980): Financial Ratios and the Probabilistic Prediction of Bankruptcy, Journal of Accounting Research, Vol. 18, No. 1. pp. 109-131.
15.Pavlović, V., Muminović, S., Cvijanović, J. M. (2011): Adequacy of Tafflers model for bankruptcy prediction of Serbian companies. Industrija, Vol. 39, No. 4, pp. 57-70.
16.Polo, A., Caca, E. (2014): Kralicek Quick Test – an Analysis Tool for Economic Units Determination in Liability Diffculty. Europena Scientifc Journal, Vol. 10, No. 19, pp. 142-152.
17.Smaranda, C. (2014): Scoring Functions and Bankruptcy Prediction Models – Case Study for Romanian Companies. Procedia Economics and Finance Vol. 10, pp. 217 – 226
18.Stanišić, N., Mizdraković, V., Knežević, G. (2013): Corporate Bankruptcy Prediction in the Republic of Serbia. Industrija, Vol. 41, No. 4, pp. 145-159.
19.Vapa Tankosić, J., Stojsavljević, M. (2012): New perspectives for economic growth: Agribusiness as Serbias way out of fnancial crisis, in: European Integration Process in Western Balkan Countries, Teixeira, P., Portugal Duarte, A., Redžepagić, S., Erić, D., Andrejević, S. (Eds.), Faculty of Economics of the University of Coimbra, Coimbra, Portugal, pp. 726-740.
20.Zenzerovic, R., Perusko, T. (2006): Kratki osvrt na modele za predviđanje stečaja? Ekonomska istraživanja, Vol. 19, No. 2, pp. 132-151.