Informal employment in Russian regions: opportunities and social risks

The relevance of the study is due to the prevalence and long-lasting nature of informal employment practices among the Russian population, as well as the ambiguity of their social and economic implications. The article presents the results of a multidimensional statistical analysis of socio-economic processes in the regions of Russia for 2018 and 2020. The empirical base includes a system of indicators we formed according to Rosstat data. More than 100 variables characterizing the state of the regions have been tested: macroeconomic conditions, labor market, standard of living and quality of life, human capital, and demographic development. According to the calculated factor models for 2018 and 2020, two key components are identified, which we interpret as integral indicators characterizing the intensity of various manifestations of unemployment and informal employment in Russian regions. Further, on the basis of correlation analysis, we show the nature of the interrelationships of the integral indicator (factor) “informal employment” with key macro indicators of regional development. There is a close relationship between informal employment and indicators of economic growth, investment, consumption and income levels, and the lack of connection with indicators of the social sphere. We also classify regions according to indicators of informal employment and analyze the (non)stability of the composition of groups over time and their relationship with the dynamics of regions’ socio-economic development. The novelty of the study consists in an attempt to find hidden patterns and features of manifestation of informal employment in regions and assess their stability over time. The value of the results obtained lies in clarifying the nature of the interrelationships between the specifics of socio-economic development of territories and informal employment models; and also, in designing the approaches to assessing its social and economic effects and identifying regional specifics.