Abstract:

The aim of the work is to study the convergence of regions according to the main socio-economic indicators, taking into account digital aspects and spatial location. The following hypothesis is tested in the article: there is a conditional and unconditional β-convergence of the readiness levels for digital transformation as regards the social and housing infrastructure in the Russian regions. To test for unconditional β-convergence, the empirical model specification proposed by Barro and Sala‐I‐Martin. The most important parameters of the social infrastructure development, such as health care and housing and communal services, taking into account the spatial location of the regions, were chosen as the analyzed indicators. The authors used estimation of β-convergence for the data of the period from 2009 till 2017. Global and local indexes of Moran’s spatial autocorrelation were calculated, spatial scattering diagrams were constructed by the analyzed parameters based on the tools of spatial econometrics. The study used a matrix of inverse distances and a boundary matrix of weights. A regional unconditional β-convergence of the healthcare level was revealed, as well as a positive global spatial autocorrelation in terms of per capita living space for all analyzed periods. Based on the study, it was concluded that, firstly, the distribution of the selected indicators of regional activity is determined by their spatial location, and secondly, the regions, demonstrating convergence processes, are ready for a full digital transformation.