Agri25: Value Creation Rating Model for Agricultural Enterprises - Comparison of Logistic and Discriminant Analysis in Czech Conditions

Jindřich ŠpičkaZdeňka Náglová

DOI 10.7160/aol.2026.180306
No 3/2026, September
pp. 60-77

Špička, J. and Náglová, Z. (2026) "Agri25: Value Creation Rating Model for Agricultural Enterprises - Comparison of Logistic and Discriminant Analysis in Czech Conditions", AGRIS on-line Papers in Economics and Informatics, Vol. 18, No. 3, pp. 60-77. ISSN 1804-1930 DOI 10.7160/aol.2026.180306.

Abstract

This study develops a sector-specific value creation rating model for Czech agricultural enterprises using Economic Value Added (EVA) as the classification criterion. Based on accounting data from the CRIBIS database covering period 2019-2023, we compare logistic regression and discriminant analysis for distinguishing value-creating from value-destroying firms. Results demonstrate that logistic regression provides superior predictive accuracy, with efficient return on invested capital and adequate working capital relative to long-term financing emerging as the primary determinants of positive EVA. The findings confirm that traditional rating models developed for industrial enterprises exhibit limited applicability in agriculture due to the sector's unique characteristics, including Common Agricultural Policy (CAP) subsidies that suppress bankruptcy rates and create distinct financial dynamics. This research highlights the necessity of sector-adapted analytical tools that shift focus from bankruptcy prediction to value creation assessment, providing practical frameworks for financial institutions, farm managers, and policy-makers evaluating agricultural financial performance and sustainability.

Keywords

Agriculture, creditworthiness, logistic regression, discriminant analysis, economic value added, financial health, Czech farms

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