This study used econometric panel models to examine the influence of water shortage on economic growth in Central Asian countries. To evaluate long-term panel data, we used a pooled regression model, a fixed effect model, and a random effect model on annual data from 1990 to 2023 across five nations. After creating the models, we ran diagnostic tests using several statistical techniques. After analyzing the models listed above, we determined that the Pooled regression model is best suited to our panel data. Based on the indicators of this model, it was discovered that increased water shortage in Central Asian countries had a negative impact on economic growth. Each unit increase in water scarcity causes a 0.0166 unit loss in GDP. The findings suggest that countries experiencing severe water scarcity should prioritize water resource management and establish a water conservation program that includes the construction of infrastructure to alleviate the shortage.

This article examines the impact of agro-industrial integration on the economic efficiency of Uzbekistan’s agricultural sector using econometric methods based on panel data covering 13 regions. The main indices of agro-industrial integration are represented by the shares of farm households, dekhkan and subsidiary farms, and agricultural organizations in the total volume of agricultural output. Panel regression results confirm a positive and statistically significant effect of integration indicators on agricultural output growth rates. The findings suggest that institutional strengthening of agro-industrial integration creates opportunities to enhance agricultural sector efficiency, increase farmers’ incomes, and promote rural employment.

This article develops an econometric framework to formalize the determinants of consumer behavior and to quantify their effects on purchase decisions and consumption volumes. The analysis systematizes key drivers such as income and income uncertainty, prices and inflation expectations, household socio-demographic characteristics, access to information and digital channels, marketing exposure, and behavioral factors (trust and risk preferences). Methodologically, the study employs discrete-choice models (logit/probit) to estimate purchase probabilities, regression and panel data specifications (fixed/random effects) to model demand intensity, and strategies to mitigate endogeneity (instrumental variables and robustness checks). The proposed formalization supports evidence-based consumer policy design, market monitoring, and evaluation of interventions aimed at improving market transparency and consumer welfare.

The article analyzes the economic foundations of Uzbekistan's integration into the international trading system, in particular, the policy of participation in the World Trade Organization. The study reveals the impact of trade agreements on exports, investments and competitiveness. The importance of inclusiveness, institutional coordination and stakeholder participation in the formation of trade policy based on international and regional experience is highlighted. The empirical analysis is carried out using a panel regression model based on data for Uzbekistan, Kazakhstan and Kyrgyzstan for 2000–2024. The results show that WTO membership increases GDP by an average of 17%. It is also found that WTO membership improves the investment climate, increases export diversification and accelerates institutional reforms. According to the forecast analysis, by 2030, Uzbekistan's GDP could reach 245 billion US dollars under WTO membership. The article also focuses on the potential social and cross-sectoral risks of trade liberalization and provides practical recommendations for a balanced trade policy.

This article analysis the impact of global climate change on agricultural production based on international scientific research. The study explores how factors such as rising temperatures, changes in precipitation patterns, and water scarcity affect crop yields. In particular, it has been proven that shifts in heat and moisture balance directly influence the growth phases and yield levels of major crops such as wheat, cotton, and maize. Empirical studies conducted in various countries using panel regression, ARIMA, and GARCH models demonstrate that climate change significantly and negatively affects agricultural production. This article emphasizes the importance of conducting similar research under the specific climatic and agronomic conditions of Uzbekistan.

The resource dependency theory (RDT) is used to guide an empirical analysis of the higher education system in Uzbekistan. The regression models are applied to a panel dataset consisting of 62 Uzbek higher education institutions, covering the period 2000-2013, to examine the determinants of the expenditure decisions made by institutions. The key hypothesis is concerned with the relationship between the share of revenue from tuition fees and the share of expenditure spent on teaching. The analysis attempts to control for unobserved heterogeneity through the inclusion of fixed effects. Instrumental variables estimation is used to address the potential endogeneity of the relationship between these two variables. The main finding is that there is a positive and statistically significant relationship between the share of revenue from tuition fees and the share of expenditure spent on teaching, even after other factors are held contact, which is consistent with a core premise of RDT.

In this article, digitization of the payment sector has become a real need of the hour, because life in the digital world imposes various demands on financial processes, which innovative technologies, including distributed ledgers and smart contracts, are designed to meet.