Statistical Analysing Uzbekistan's Insurance Market Data: Approaches to Operational Optimization and Decision-Making

The insurance sector plays a critical role in national economic development, and its effectiveness is significantly influenced by the statistical analysis of market data. In Uzbekistan, the insurance market is undergoing dynamic changes, yet regional disparities and limited analytical frameworks have constrained its full development. Despite global advancements in modeling insurance markets, there remains a lack of integrated statistical and econometric analysis focused on Uzbekistan’s regional insurance trends. This study aims to statistically analyze the insurance premium data across Uzbekistan's regions, identify non-normal data distributions, and develop ARIMA-based econometric models for forecasting regional market development. The Shapiro-Wilk test confirmed the non-normality of the insurance premium data, leading to the adoption of the Gamma distribution for modeling. Region-specific ARIMA(p,d,q) models were estimated, with their effectiveness evaluated using log likelihood, AIC, AICc, and BIC criteria. Additional statistical methods, including regression, factor, and cluster analysis, supported the identification of regional differences in insurance development. The study uniquely integrates time-series forecasting, statistical distribution testing, and multivariate analysis to produce region-specific models for the insurance sector in Uzbekistan, accounting for structural market shifts in areas such as Karakalpakstan and Tashkent. The findings provide an empirical foundation for optimizing insurance services, guiding policy development, and supporting strategic decision-making in regional insurance planning, thereby promoting inclusive market growth and economic sustainability.

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