Methodological approaches to assessing the impact of the digital economy on traditional macroeconomic indicators in the conditions of global digitalization

Abstract

This article examines the methodological approaches to assessing the impact of the digital economy on traditional macroeconomic indicators in the context of global digitalization. The paper is structured according to the IMRAD framework, which allows for a systematic coverage of the problem, beginning with the formulation of the relevance of the study and ending with a discussion of the results obtained. The introduction of the article justifies the importance of studying the digital transformation of the economy. The author points out that the accelerated development of information and communication technologies affects key macroeconomic indicators such as GDP growth, inflation, unemployment levels, and investments. It is emphasized that traditional analysis methods require adaptation in order to adequately reflect the dynamics of the new economic reality. The methodological section of the article describes the application of a comprehensive approach that combines economic-statistical models, time series, and regression analysis to identify the relationships between the degree of digitalization and changes in macroeconomic indicators. A comparative analysis of data is carried out using cross-sectoral modeling, which accounts for the specifics of the digital economy in different countries. Examples of empirical studies are provided to demonstrate the effectiveness of the proposed models in forecasting economic processes. The findings of the study show that digitalization has a significant influence on traditional economic indicators. In particular, a direct correlation was found between the level of digital infrastructure and productivity growth, as well as positive effects in reducing inflation levels due to the optimization of processes within the business environment. In addition, the analysis determined that the implementation of new technologies stimulates investment activity by enhancing the transparency of financial flows. In discussing the obtained data, the emphasis is placed on the need for further research to develop more accurate methods for assessing the impact of the digital economy. The authors propose the integration of modern statistical tools and machine learning methods in future studies, as well as taking into account the specifics of regional features. The conclusion of the article is that adapting traditional analysis methods to the realities of global digitalization is crucial for effective forecasting and managing economic development.