Analysis of I-DESI dimensions of the digital economy development of the Russian Federation and EU-28 using multivariate statistics

Abstract

This paper continues the authors’ earlier analysis, in which we used five principle dimensions of the International Digital Economy and Social Index (I-DESI) for the 28 countries of the EU and the Russian Federation to examine how Russia’s development relates to that of other EU countries. The aim of this paper is not to establish a ranking, but to determine the relationship between each dimension and the groups into which these 29 countries can be divided by multivariate statistical analysis tools and to analyze the group to which the Russian Federation belongs. We use Principal Component Analysis (PCA) to map our data to a lower-dimensional space (revealing two latent dimensions), and to analyze causal relations between the principal dimensions using partial correlation coefficients, concluding that two of the five main dimensions can be explained by three independent dimensions. Thereafter, we use cluster analysis to group our objects (i. e. the 29 countries) into clusters, and multidimensional scaling (MDS) to visualize the location of these groups and countries on the plane of the two components (from the PCA), focusing on the Russian Federation. According to our results, the Russian Federation can be classified as a moderately developed country in terms of its I-DESI score, but its location on the plane of principle components differs from the group of moderately developed EU-countries, forming a separate “group” on its own, largely owing to the unique characteristics of the country’s digital development.

Keywords:

digital transformation measurement, DESI index, connectivity, human capital correlation analysis, principal component analysis, partial correlation analysis, cluster analysis, multidimensional scaling, Russia