Using Digital Economy Models to Forecast Macroeconomic Indicators

Abstract

The study aimed to analyse the potential of digital economic models in forecasting macroeconomic indicators. The main novelty of the study is the combination of modern digital technologies with traditional macroeconomic models. In the context of rapid global change, the accuracy of macroeconomic forecasts is critical, as it determines the effectiveness of economic policy. Digital technologies are offered as new tools for improved analysis and forecasting.

The research methodology involved studying existing digital models, including machine learning, big data, and artificial intelligence, with a focus on their ability to process large amounts of data and identify hidden patterns. Traditional econometric models were compared with modern digital approaches to assess their effectiveness in forecasting key macroeconomic parameters such as gross domestic product, unemployment, and inflation. Data from various sources, including national statistics, international organisations, and surveys of businesses and households, were used to validate the digital models.

The study results show that digital economy models are more efficient than traditional methods, especially in terms of accuracy and speed of forecasting. The use of machine learning algorithms provides a more accurate assessment of the impact of various factors on macroeconomic indicators, significantly reducing the likelihood of errors. The study emphasises the importance of a comprehensive approach to integrating data from various sources, such as social media, financial markets, and analytical platforms, to ensure a more complete reflection of economic processes.

The paper's conclusions emphasise the need to implement digital economic models actively in macroeconomic forecasting. Adapting existing macroeconomic models through the integration of machine learning algorithms will help improve the accuracy of forecasts based on big data on consumer trends and investments. This, in turn, will allow government agencies to respond more quickly to changes in the economic environment while involving the private sector in developing and implementing digital models, stimulating innovation and increasing competitiveness.