The topic of quantitative research on informal employment has a consistently high relevance both in the Russian Federation and in other countries due to its high dependence on cyclicality and crisis stages in economic dynamics of countries with any level of economic development. Developing effective government policy measures to overcome the negative impact of informal employment requires special attention in theoretical and applied research to assessing the factors and conditions of informal employment in the Russian Federation including at the regional level. Such effects of informal employment as a shortfall in taxes, potential losses in production efficiency, and negative social consequences are a concern for the authorities of the federal and regional levels. Development of quantitative indicators to determine the level of informal employment in the regions, taking into account their specifics in the general spatial and economic system of Russia are necessary to overcome these negative effects. The article proposes and tests methods for solving the problem of assessing the impact of hierarchical relationships on macroeconomic factors at the regional level of informal employment in constituent entities of the Russian Federation. Majority of the works on the study of informal employment are based on basic statistical methods of spatial-dynamic analysis, as well as on the now «traditional» methods of cluster and correlation-regression analysis. Without diminishing the merits of these methods, it should be noted that they are somewhat limited in identifying hidden structural connections and interdependencies in such a complex multidimensional phenomenon as informal employment. In order to substantiate the possibility of overcoming these limitations, the article proposes indicators of regional statistics that directly and indirectly characterize informal employment and also presents the possibilities of using the «random forest» method to identify groups of constituent entities of the Russian Federation that have similar macroeconomic factors of informal employment. The novelty of this method in terms of research objectives is that it allows one to assess the impact of macroeconomic indicators of regional development on the level of informal employment, taking into account the implicit, not predetermined by the initial hypotheses, hierarchical relationships of factor indicators. Based on the generalization of the studies presented in the literature, as well as the authors’ statistical calculations using Rosstat data, the authors came to the conclusion about the high importance of macroeconomic parameters of regional development and systemic relationships of macroeconomic indicators in substantiating the differentiation of the informal level across the constituent entities of the Russian Federation.
A New Random Forest Method for Longitudinal Data Classification Using a Lexicographic Bi-Objective Approach
