Theoretical and scientific approaches to the application of econometric methods and modelsin economic research

Abstract

Econometric methods and models are widely used in economic research to analyze and forecast economic processes and to justify management decisions.They help to formalize complex economic relationships, identify key influencing factors, and develop scientifically sound forecasts. In today's world, econometricmethods and models are increasingly described in various scientific papers. This is primarily because they allow researchers to identify patterns and relationshipsbetween various economic indicators, as well as to make reasonable forecasts of future economic events. Econometric methods and models play an important rolein modern economic research, providing tools for quantitative analysis of economic phenomena, theory testing, and forecasting. Their value lies in their ability totransform abstract economic hypotheses into empirically verifiable conclusions, allowing researchers not only to describe but also to explain cause-and-effectrelationships. The purpose of this study is to analyze the primary econometric methods and models used in scientific research, to assess their practical value andapplicability in different types of economic research, and to determine recommendations for choosing appropriate models to maximize the accuracy and reliabilityof the results. The methodology of this study is based on an integrated approach that covers the theoretical and scientific aspects of the application of econometricmethods and models in economic research. To achieve the objectives of the study, several methods were used to consider stochastic differential equations, whichare an important tool for modeling dynamic systems under the influence of random factors. The first stage of the research was to develop various types of econo-metric models, such as regression, time series, and random process analysis. An important aspect of this stage is the analysis of one of the most popular time seriesmodels, the Autoregressive Integrated Moving Average (ARIMA) model. The theoretical analysis also included the study of scientific works by domestic research-ers on econometric methods and models. Attention was paid to econometric methods and models that allow analyzing economic phenomena, assessing the impactof various factors on economic indicators, and forecasting indicators depending on various events. To forecast changes in the stock market, it was proved that itis advisable to use stochastic differential equations. It has been determined that econometric methods and models are an important tool in economic research foranalyzing and forecasting economic processes that will allow quantifying the relationships between various economic variables and using these estimates to makeinformed management decisions. Prospects. Econometric methods and models are a dynamic field that is constantly evolving, adapting to new challenges, oppor-tunities, and the growing complexity of economic systems. Among the prospects for the use of econometric methods and models in economic research are integra-tion with machine learning and artificial intelligence; spatial econometrics and network analysis; dynamic stochastic general equilibrium models and their inte-gration; accessibility and interpretability of models. The prospects of econometric methods and models in economic research are related to their ability to adapt tonew data sources, integrate advanced computing technologies, and constantly improve tools for quantitative analysis.