The article analyzes the dynamics of the main economic indicators of the trade
sector of the Bukhara region in 2012-2023. Based on the trend analysis of socio-economic indicators of the dynamics of trading activity, a generalized complex forecast model has been developed and optimistic and pessimistic forecast scenarios for 2025-2027 have been developed.

Accurate exchange rate forecasting is of considerable practical importance for emerging and frontier markets. In such markets, exchange rates tend to exhibit high volatility and may fluctuate significantly due to depreciation pressures, external economic shocks, inflation differentials, and uncertainty in financial markets. This study employs the ARIMA–eGARCH–Monte Carlo modeling framework to forecast the USD/UZS exchange rate. The analysis is based on daily exchange rate data covering the period from January 2018 to April 2026. First, logarithmic exchange rate returns were calculated, and their stationarity was examined using the Augmented Dickey–Fuller (ADF), Phillips–Perron (PP), and KPSS tests. Subsequently, the ARIMA model was employed to capture the conditional mean dynamics of exchange rate returns, while sGARCH, eGARCH, and gjrGARCH models were compared to evaluate volatility clustering and asymmetric shock effects. The empirical results identified the eGARCH(1,1) specification as the best-performing model. In the next stage, 50,000 Monte Carlo simulations were conducted based on the selected model to generate exchange rate forecasts for a 252-trading-day horizon. The simulation results provided probability-based scenarios for the future path of the USD/UZS exchange rate over the following year. The baseline median forecast indicated an exchange rate of UZS 12,518 per US dollar, while the 90% prediction interval ranged from UZS 11,621 to UZS 13,218. The findings suggest that depreciation shocks have a significant impact on the dynamics of the USD/UZS exchange rate and that probability-based forecasting provides a more informative assessment of future exchange rate movements than conventional point forecasts. The proposed approach offers practical implications for the Central Bank, commercial banks, export-import enterprises, and risk managers in assessing foreign exchange risk and conducting stress testing.

It is vital to establish trustworthy forecasting methodologies in order to predict and assess a country's energy consumption ahead of time. This enables economists to better track and analyze consumers' energy needs. To that purpose, this study was done to establish the Republic of Uzbekistan's long-term energy consumption forecast using data on energy consumption volume acquired between 1985 and 2023. The forecasting procedure used the econometric ARIMA model. The Box-Jenkins approach was used to determine the optimal ARIMA order. According to the findings, the ARIMA (0,1,3) model was shown to be the most accurate. Based on this model, the entire predicted results had an average percentage inaccuracy of 7.2 percent. It was discovered that ARIMA is the most effective model for making long-term strategic decisions about energy consumption.

The article provides detailed reviews and analyzes of the perspective of artificial intelligence in Uzbekistan. The importance of artificial intelligence in the development of firms, companies, as well as in the fields of medicine, agriculture has been need by process of digitalization. Also, the demographic changes of the Republic of Uzbekistan were analyzed and forecast indicators for 2024-2030 were developed. Based on these forecast indicators, it was determined that by 2030, the demand of the population of the Republic for meat and dairy products will increase by 19.2%, and for milk products by 16.3%. To meet this demand, suggestions
and recommendations have been developed for the automation of livestock complexes based on digital technologies, the use of robotic CR-1 and MR-S2 remote-controlled digital technologies for increasing the milk yield of dairy cows

This article examines the specific aspects of econometric modeling in the dynamic and complex conditions of the modern economy. The paper highlights contemporary trends such as the integration of big data, machine learning, and artificial intelligence, which play a crucial role in forecasting the impacts of inflation, unemployment, climate change, and pandemics. The methodology employs a systematic literature review, drawing on scientific articles from the Scopus, Web of Science, and ResearchGate databases over the last five years (2020-2025). The results indicate that ML-hybrid models enhance forecast accuracy (with reductions in RMSE and MAE), although the adverse effects of climate change and data uncertainty pose significant challenges. The conclusions and recommendations propose increasing the robustness of models in policy formulation, strengthening interdisciplinary collaboration, and implementing ethical standards, thereby contributing to sustainable development and economic recovery.

Big Data plays a crucial role in the transformation of medical management by providing new opportunities for analyzing large volumes of data, predicting diseases, and optimizing healthcare decision-making. This article examines the fundamental principles of using Big Data in medical management, the impact of analytics on decision-making, and the challenges associated with processing medical information. The study analyzes modern approaches to integrating Big Data into medical information systems and managing healthcare resources. The prospects of using artificial intelligence and machine learning in medical analytics, as well as issues related to data security and standardization, are discussed.

This comprehensive article will discuss the situation of unemployment in Uzbekistan with special attention. The article examines the economic and social consequences of unemployment, its causes and effects on individuals and society. It provides an in-depth analysis of the level of unemployment in Uzbekistan based on statistical data and a forecast of future trends. In addition, the article highlights the need for strategic planning and intervention, and suggests a number of preventive measures to address the problem. The article represents a combination of quantitative and qualitative research methods that offer a holistic view of the topic.

In this article, the demographic status of the Republic of Uzbekistan was analyzed using the R Studio program. During the study, the main demographic indicators of the country, such as birth, death, migration and urbanization, were studied. The results provide the basis for the formation of important recommendations for the economic and social development of the country.

In this article, mathematical models are compiled based on the dynamics of electricity supply volumes in the Republic of Uzbekistan for 2010-2023, as well as for the period from 2010 to 2017 and beyond. The forecast indicators for the period from 2024 to 2030 have been determined. The dynamics of the growth of electricity supply volumes during the study period is also analyzed.

In this article, based on the dynamics of electricity production and gross domestic product in the Republic of Uzbekistan, mathematical models were constructed for the period 2010-2023 and further until 2017. Forecast indicators for the period from 2024 to 2030 were determined. An econometric analysis of the impact of electricity production on GDP for the period under study was also conducted.

Based on statistical data, this article will highlight the dynamic changes observed in the agricultural sector of the Republic of Uzbekistan during 2020-2024, individual patterns in them and their impact on forecast indicators for the coming periods. Based on official statistics related to the agricultural sector, the observed changes in macroeconomic indicators as a result of modernization processes in agriculture and their impact on the well-being of the population are analyzed.

The article is devoted to the analysis of strategies and methods aimed at optimizing taxation within the framework of the digital economy. In the context of the rapidly developing digital market and the emergence of new forms of commercial activity, effective tax planning is becoming the main aspect of the state's financial stability. The article covers the use of digital technologies in the harmonization of tax legislation, data collection and analysis. Particular attention is paid to the development of effective tax collection mechanisms for digital transactions and services, which are the main factor for ensuring stable and predictable government revenues.

An increase of 1% in the region’s share in citrus production in the republic leads to a 0.09% growth in the total volume of citrus production. Although this level of impact shows a positive trend, it is expressed on a relatively small scale.

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 study intends to forecast the agricultural commodities in Uzbekistan. The data were obtained from National Statistical Committee of the Republic of Uzbekistan. The study’s 15-year duration spans from 2010 until 2024. Box-Jenkin’s methodology, known as Auto Regressive Integrated Moving Average (ARIMA) approach was used in this study on a number of specific Uzbek agricultural commodities. According to the methodology requirement for large amount of data points, 10 species of agricultural products were chosen. All the essential steps of the model were utilized methodically for dynamic forecasting 5 periods ahead from 2025onwards. Using various model selection criteria, including Adj R^ 2, the minimum AIC value, and the lowest MAPE values, the study confirmed the accuracy of the model. Barley had the lowest Akaike Information Criterion (AIC) value among these products, while cabbage had the lowest Mean Absolute Percentage Error (MAPE) value.

This article examines the modeling and forecasting of urban population spatial distribution based on Geographic Information Systems (GIS) technologies. The study conducted geospatial analysis of population density, urbanization processes, and demographic changes using Tashkent city as a case study. Population spatial distribution forecasting models were developed using modern GIS software - ArcGIS, QGIS, and Python libraries. As a result, a forecast of geographic distribution of urban population for 2025-2035 has been prepared and practical recommendations for urban planning have been developed.

This article is devoted to assessing the prospects for attracting foreign direct investment (FDI) to Uzbekistan until 2030 in the context of accelerating structural modernization of the economy, expanding public-private partnerships, the growth of the "green" agenda, and the deepening of digital reforms. The purpose of the study is to identify factors that determine not only the quantitative scale of capital inflow but also its qualitative contribution to productivity, technological renewal, export diversification, and the formation of local value chains. The methodological framework combines comparative-institutional, structural, and problem-oriented analysis of official and analytical materials from 2022-2025. Based on a literature review, it is shown that for developing and transition economies, the sustainable effect of FDI depends on the quality of institutions, the predictability of the regulatory environment, the depth of the financial market, and the state's ability to link investment policy with industrial, innovation, and infrastructure strategies. It is established that Uzbekistan possesses significant competitive This article is devoted to assessing the prospects for attracting foreign direct investment (FDI) to Uzbekistan until 2030 in the context of accelerating structural modernization of the economy, expanding public-private partnerships, the growth of the "green" agenda, and the deepening of digital reforms. The purpose of the study is to identify factors that determine not only the quantitative scale of capital inflow but also its qualitative contribution to productivity, technological renewal, export diversification, and the formation of local value chains. The methodological framework combines comparative-institutional, structural, and problem-oriented analysis of official and analytical materials from 2022-2025. Based on a literature review, it is shown that for developing and transition economies, the sustainable effect of FDI depends on the quality of institutions, the predictability of the regulatory environment, the depth of the financial market, and the state's ability to link investment policy with industrial, innovation, and infrastructure strategies. It is established that Uzbekistan possesses significant competitive

The article theoretically and scientifically examines the priority directions of modeling investment management processes in the tourism sector and effective activity management. Based on a comparative analysis of approaches by foreign and domestic scholars to the concepts of investment activity and investment activity in the tourism sector, an author’s definition is formulated. In the course of the study, the volume of investments in the tourism industry for 2024–2025 and the factors influencing its changes were modeled using correlation-regression analysis, and forecast indicators up to 2030 were developed. In addition, a scientific and methodological approach to assessing the investment attractiveness of the tourism sector is proposed, and directions for its practical application are substantiated.

This article discusses the issues of ensuring the transparency of the economic indicators of joint-stock companies in our republic and the open placement of changes in the value of their shares in the secondary market. This article discusses the development of short-term forecasts of changes in the value of shares of joint-stock companies in the stock market and the factors affecting them using the Bernoulli random walk method.