Statistical Modeling of Regional Insurance Market Dynamics in Uzbekistan

General Background: The insurance sector significantly supports economic growth, requiring accurate statistical modeling. Specific Background: In Uzbekistan, despite rapid market expansion, regional disparities and weak analytical tools limit development. Knowledge Gap: Previous global studies have applied advanced models, but integrated statistical and econometric analysis of Uzbekistan’s insurance market remains scarce. Aims: This research analyzes regional insurance premiums, tests data distribution, and builds econometric forecasting models. Results: Shapiro-Wilk tests confirmed non-normality, leading to Gamma distribution modeling, while region-specific ARIMA(p,d,q) models were validated through AIC, AICc, BIC, and log likelihood. Regression, factor, and cluster analyses highlighted structural differences between regions. Novelty: The study combines distribution testing, time-series forecasting, and multivariate analysis to create region-specific models, accounting for market shifts in areas such as Karakalpakstan and Tashkent. Implications: Findings provide a basis for optimizing insurance services, improving tariff policies, and supporting inclusive and sustainable regional insurance development in Uzbekistan.Highlight : Statistical analysis identifies non-normal distribution in insurance premiums. ARIMA models provide accurate regional forecasting of market trends. Results guide policy and support sustainable insurance development.