Econometric Modeling of an Early Warning System for Financial Instability: Evidence from JSC “Uzkimyosanoat”

This article is devoted to the econometric modeling of an early warning system for financial instability in chemical industry enterprises, using Joint-Stock Company “Uzkimyosanoat” as a case study. The study develops and empirically tests a model examining the relationship between the current liquidity ratio and key financial indicators, including return on assets (ROA), return on equity (ROE), inventory turnover, and the share of inventories in current assets. Panel data from three enterprises within the JSC “Uzkimyosanoat” system for the period 2015–2024 are utilized. The model is estimated using multiple linear regression, with tests conducted for the statistical significance of coefficients, multicollinearity, heteroskedasticity, and autocorrelation of residuals. The results show that inventory turnover and the share of inventories are the most significant factors affecting current liquidity, whereas ROA and ROE demonstrate weak and unstable relationships with liquidity.
The findings support the application of the proposed model within early warning systems for financial risk management in chemical industry enterprises and contribute to improving the efficiency of short-term financial resource management.