Abstract

Many researchers of migration in Russia note deficiency of the works directed on modeling of migratory processes taking place in the country. This article is devoted to an assessment of impact power of socio-economic factors on interregional migration in Russia and to its comparison to recently found influence on this process of psychological characteristics of the accepting region population. As the aggregated at regional level estimates of intelligence, personal traits and characteristics of response style were calculated on the basis of results of online testing over 200 thousand respondents in 2012–19, indicators of socio-economic development of regions (n=16) are computed by averaging for the same time interval; the source of data - the Russian Federal Service of State Statistics (reference yearbooks “Regions of Russia” and the Uniform Interagency Information and Statistical System). In the analysis data of 78 subjects of the Russian Federation are included, but after association of capital agglomerations the number of regions was reduced to 76. It is established that the majority of the socio-economic indexes included in the analysis shows significant correlations with regional net migration coefficients. In general, the revealed pattern of correlations is agreed with results of other authors received on data of earlier periods of the analysis. Regression of net migration coefficients on socio-economic variables allowed calculating series of linear multifactor models. Best of these models accounted for about 44 % of a dependent variable variance. Earlier it was shown that the models calculated on the basis of limited number of aggregated psychological characteristics of the accepting region have the same level of accuracy. Moreover, addition of psychological variables to the best models based on socio-economic indexes provides essential increase of accuracy of prediction of regional net migration: the share of variance accounted for increases from 44 to 55–57 %. It is supposed that taking into account of psychological variables of the accepting region will create premises for more effective management of migratory processes.

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