This article analyzes modern approaches to forecasting regional socio-economic development, including the use of economic-mathematical models, artificial intelligence, and geoinformation technologies. The study highlights the significance of integrating targeted and empirical approaches with composite indicators to ensure sustainable development. Reducing interregional disparities, stimulating investment activity, and preparing reliable forecasts for policymaking are considered important scientific and practical tasks. Thus, the role of forecasting and planning processes as a scientific foundation for strategic governance is substantiated.

This study is devoted to the analysis of the current state of practice in Uzbekistan in improving the methodology for forecasting direct taxes. The study studied the current mechanisms of forecasting processes for the main direct taxes, such as profit tax, personal income tax, and property and land taxes. Based on statistical analysis, comparative assessment, and economic modeling methods, factors affecting the accuracy and stability of forecast indicators were assessed. The impact of macroeconomic indicators, tax base expansion, and tax administration digitization processes on the quality of forecasting was also revealed. Based on the results of the study, scientific and practical proposals and conclusions were developed aimed at using modern economic and mathematical models in forecasting accurate tax revenues, improving the information base, and strengthening the institutional approach

This article develops a multiple econometric model to assess the efficiency of managing state assets in the Republic of Uzbekistan. The dependent variable is the volume of valuation services performed (Y), while the explanatory variables include the number of privatized state assets (X1), the number of certified appraisers (X2), and the initial value of intangible assets (X3). The reliability of the model was verified using descriptive statistics, correlation analysis, VIF and ADF tests. The results demonstrate the significant impact of the selected factors on the volume of valuation services and confirm the model’s applicability for forecasting purposes

In this study, a methodology for using geographic information systems (GIS) technologies in forecasting the demographic development of the population of Uzbekistan until 2050 will be developed. The main goal of the research is to improve the mechanism for comprehensive analysis and forecasting of population size, age-sex composition, territorial distribution, urbanization processes, as well as internal and external migration flows by region. The research results are important for optimizing state planning, regional development strategies, labor market forecasts, and social infrastructure. The use of GIS technologies serves to scientifically substantiate the decision-making process, increasing the accuracy of demographic forecasts and the possibilities of visual analysis

Forecasting socio-economic development indicators plays a crucial role in modern economics and social spheres. This process is utilized by governments, businesses, and international organizations to develop long-term strategies, allocate resources efficiently, and reduce social inequality. The present research examines theoretical and methodological aspects of forecasting socio-economic development indicators.

This article analyzes the development trends of communication and informatization services for the population in the Kashkadarya region and develops multifactor empirical models for forecasting these services. Based on regional statistical data, the key influencing factors are identified, and their impact on service volume is assessed using econometric methods. The study employs regression analysis, time series analysis, and modern econometric approaches in model construction. The obtained results allow forecasting the future dynamics of communication and informatization services and provide practical recommendations for sector development. The findings are significant for enhancing regional economic growth, improving digital infrastructure, and ensuring effective management of the service market

This article analyzes the development trends of the chemical industry in the Republic of Uzbekistan, the dynamics of production volumes, and the possibilities of modeling this process. The study empirically evaluates the elasticity of production volume in relation to investment and employment levels based on the Cobb–Douglas production function. A classical linear regression model was constructed using statistical data from 2010 to 2023, and analyses were conducted in the Stata software. Regression results indicate that the growth in production volume is more closely associated with the increase in labor resources. Additionally, forecast values for 2024–2028 were calculated using an autoregressive (AR) model, demonstrating a steady growth in chemical product output. The results of the study hold significant practical importance for strategic management of the chemical industry and for shaping investment policy.

This article explores the theoretical and practical aspects of economic-mathematical modeling of the electronic commerce system based on interval data. The study analyzes the advantages of using interval data in evaluating e-commerce indicators, the possibilities of modeling economic processes under uncertainty, and mechanisms for forecasting the efficiency of electronic commerce in the digital economy. In addition, the economic significance of decrees and resolutions adopted in the Republic of Uzbekistan for the development of electronic commerce is highlighted. According to the research results, it is substantiated that interval modeling methods can serve to reduce risks in the electronic commerce system, increase the accuracy of forecasts, and optimize management decisions

The article examines the impact of digitalization on business planning in commercial banks. It analyzes artificial intelligence, Big Data, and cloud computing technologies that improve forecasting accuracy. Key digital solutions and their further development prospects in the banking sector are identified.

This study analyses historical data (2000–2024) to forecast Uzpromstroybank’s deposit base and total resource trends using simple OLS regression models. A linear time-trend model is estimated for both series to capture long-run growth. The regression results show strong, significant upward trends (high R², statistically significant coefficients) for deposits and resources, indicating robust growth. Forecasts generated by extrapolating these trends suggest continued expansion of the bank’s deposits and resources in the short term. The findings are relevant for bank management and policymakers, as they highlight the trajectory of funding sources in Uzbekistan’s banking sector. Limitations include the simplicity of the linear model and potential structural changes, nonetheless, the results provide a baseline projection and underline the importance of improving deposit mobilization and financial sector reforms.

This article analyzes the development of the fisheries sector in the Republic of Uzbekistan, particularly in the Syrdarya region, using econometric methods. The study highlights the role of fish products in food security, public health, and economic diversification. The analysis is based on statistical data from 2010 to 2023 and evaluated using autocorrelation and the Durbin-Watson test. Forecast values for the next five years are developed, and practical conclusions are presented to further enhance the fisheries sector.

In recent years, the intensification of global financial instability has posed significant challenges to banking markets. In response, commercial banks have placed particular emphasis on enhancing their resilience to economic fluctuations. According to expert forecasts, activity in the global banking sector is expected to increase substantially in 2025–2026. Notably, inflation in the Eurozone in 2024 is projected to be around 2.3% instead of the previously forecast 2.7%. Financial stability, however, remains tied to moderate growth prospects. Various models typically chosen or approved by regulators are used to assess banks’ stability. Contemporary research focuses on improving existing methodologies and financial stability indicators in light of changes in the global macroeconomic environment, raising capital adequacy requirements for banks, and enhancing tools for forecasting their future performance. At the same time, the adoption of new technologies and financial instruments is accelerating banks’ digital transformation and the automation of their business processes. This article offers a comprehensive study of the means and mechanisms for ensuring the financial stability of commercial banks in Uzbekistan. Its primary objective is to analyze the state of the banking sector and identify ways to strengthen its resilience, drawing on global best practices and national specificities. To achieve this, both scientific-pedagogical methods (historical-comparative analysis, structural-logical research) and empirical approaches (statistics from regulatory documents and bank reports, expert surveys) are employed.

This scientific study provides an in-depth analysis of the factors influencing the management efficiency of free economic zones (FEZs) in the Republic of Uzbekistan, assessing their contribution to socio-economic development using mathematical modeling. Using the Jizzakh Free Economic Zone as a case study, the research identifies key factors affecting production volume from 2015 to 2024 — namely, foreign investment and employment levels. The study employs the Cobb-Douglas production function to construct a classical linear regression model, along with an autoregressive (AR) model, correlation-regression analysis, and evaluation through Fisher’s criterion, Student’s t-test, and the Durbin-Watson statistic.

This article considers foreign experience as an important factor in ensuring the effectiveness and sustainable development of financial planning in enterprises. In developed countries, financial planning is carried out, first of all, in combination with market mechanisms, digital technologies and financial control systems. Efficient allocation and optimization of financial resources, the use of automated models for budgeting and forecasting, the implementation of modern risk management methods, compliance with international financial reporting standards, and ensuring financial transparency and accountability based on corporate governance principles are of great importance. At the same time, the experience of foreign enterprises shows the widespread use of innovative financing sources - venture capital, bonds, leasing and crowdfunding. The analysis of these experiences serves as an important methodological basis for Uzbek enterprises to improve the effectiveness of financial planning, strengthen competitiveness and accelerate the integration processes into world markets

The article examines the factors contributing to the improvement of efficiency in regional hotel enterprises, the directions for the development of tourism infrastructure, and modern methods for forecasting hotel activities. Using the case of Uzbekistan, the dynamics of the number of hotels and forecast indicators calculated based on the ARIMA model are analyzed. The results of the study can be used in the development of regional tourism policy

This study analyzes the interrelationship between consistency and quality in team performance and their impact on efficiency. The research is based on empirical data from the “Iman Invest Fintech” company, in which the daily activities of teams, the stability of results, and service quality indicators were examined in depth. The main focus is on identifying the role of consistency (stability, adherence to processes, and repeatability of results) in overall performance. The results indicate that for teams, the ability to consistently deliver stable outcomes is, in some cases, more important than achieving high but inconsistent quality results. Consistency strengthens collaboration within the team, reduces errors, and improves predictability, which in turn enhances overall efficiency. The study employs regression and panel analysis methods to evaluate the relative impact of consistency and quality. In addition, although diminishing marginal returns of consistency were identified, it still remains a significant factor. In conclusion, developing consistency as a priority direction for fintech teams is considered an effective strategy for improving efficiency

In this article, a multifactor econometric model was developed to forecast the volume of e-commerce services in Uzbekistan and its reliability was assessed based on relevant statistical approaches. The study analyzed the impact of factors through elasticity indicators and determined the degree of their impact on the resulting indicator. Also, the future development prospects of e-commerce were forecasted based on pessimistic, inertial and optimistic scenarios, and the growth trends of the industry were substantiated

This article examines the financing trends of business models of innovative entrepreneurship subjects, particularly startup ecosystems, in the national economy and mechanisms for assessing related risks. The support framework for startup projects through traditional and alternative financial instruments (venture capital, crowdfunding) under current digital transformation has been systematically analyzed. The results show that the sustainability of innovative business models depends on the correct forecasting of their financial flows and strategies for minimizing specific risk factors. In conclusion, practical proposals have been developed to increase the financial sustainability of national startup projects and reduce risks in their business models

This article analyzes the problem of optimizing investment flows in a self-organizing trading system. From a mathematical perspective, the apparatus of stochastic calculus, particularly Itô stochastic differential equations, is employed. The trading system is modeled as a self-organizing structure capable of adapting to external economic processes. Based on the Gronwall–Bellman equation, a mathematical model is proposed that enables the determination of the optimal trajectory for the allocation of investment resources. The obtained results are of significant importance for forecasting economic systems, optimizing resource allocation, and developing market strategies

The article presents an econometric analysis of trends in the development of industrial infrastructure in the Kashkadarya region. Based on the parameters of the production function, which expresses the dependence of the volume of industrial production on the cost of fixed assets and the amount of labor resources, an econometric model was created, and the reliability of the model was assessed. The efficiency indicators of the model factors and forecasts of industrial production volumes were calculated, conclusions and proposals were made