The impact of digitalization on the economic growth of the European Union: an empirical study

Daniil Revenko (), Yuri Romanenkov, Tetiana Polozova, Vira Lebedchenko and Kateryna Molchanova
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Daniil Revenko: National Aerospace University "Kharkiv Aviation Institute"
Yuri Romanenkov: Kharkiv National University of Radio Electronics
Tetiana Polozova: Kharkiv National University of Radio Electronics
Vira Lebedchenko: National Aerospace University "Kharkiv Aviation Institute"
Kateryna Molchanova: National Aviation University

Eastern-European Journal of Enterprise Technologies, 2024, vol. 3, issue 13 (129), 46-56

Abstract: The object of this study was the process of digitalization of the economy and society of the European Union. The task of researching the impact of digitalization on the economic growth of the European Union has been solved. The relevance of the chosen topic is due to the complexity of digital transformation processes taking place in the world economy and the economy of the European Union, in particular, the need to assess their directions and intensity. Four approaches to modeling the impact of digitalization on economic growth based on the neoclassical production function were proposed. The structure of the model was chosen, which makes it possible to evaluate the influence of various factors of digitalization on the key parameters of economic growth. A regression multivariate model for assessing the impact of digitalization on the economic growth of the European Union has been developed. To this end, a sequence of stages was performed: formation of the information base, grouping of digitalization factors, as well as their selection based on correlation analysis. With the help of regression analysis, the parameters of the production function were expressed through digitalization indicators. At the same time, due to the limitation of input data, the Elastic Net Regression method was used. This made it possible to ensure the quality of the new model, namely, to remove low-impact parameters, reduce the multicollinearity of factors, make the model statistically significant, and ensure the stability of coefficients to data changes. The resulting model is eleven-factor; it demonstrates a high predictive ability (the coefficient of determination is 0.987). It can be used as an analytical tool for assessing the impact of digitalization on the economic growth of the European Union. Practical use of the model will help governments and businesses make informed decisions about digital transformation policies

Keywords: digital transformation; economic growth; production function; statistical modeling; European Union (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:baq:jetart:v:3:y:2024:i:13:p:46-56

DOI: 10.15587/1729-4061.2024.304256

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