Assessment Of The Socio-Economic Effects Of Labor Conservation In Small Settlements And Hard-To-Reach Areas[Оценка Социально-Экономических Эффектов Сохранения Трудовых Ресурсов В Мелких Поселениях И На Труднодоступных Территориях]

The processes of population concentration in Russian cities lead to a decrease in the population in certain territories, the depopulation of rural settlements and in some cases conflicts with national interests. In this regard, the development of an approach to assessing the socio-economic effects of the containment of labor resources in small settlements and hardto-reach areas seems to be an urgent research task. The purpose of the study is to develop an approach to assessing the socio-economic effects of the containment of labor resources in small settlements and hard-to-reach areas. Among the main tasks to be solved in the course of this study, one can single out: a review of the retrospective and forecast dynamics of the population of Russia in a spatial context; review of theoretical and practical research approaches to the analysis and evaluation of the effects of urbanization processes; development of an approach to assessing the socio-economic effects of the containment of labor resources in small settlements and hard-to-reach areas; empirical assessment of socio-economic effects from documents implemented in Russia on the development of individual territories; development of evidence-based recommendations on economic policy. Research method or methodology -systematization and analysis of international literature, economic modeling, econometric analysis. The main results of the study: developed a scientifically based approach to assessing the socio-economic effects of the regulation of migration processes based on the econometric model and the model of spatial equilibrium; an empirical assessment of the socio-economic effects of measures affecting migration flows was carried out, including the following scenarios: expansion of preferential mortgage programs, cash transfers, development of transport infrastructure, changes in the cross elasticity of urban amenities, a scenario of increasing or decreasing the elasticity of substitution for workers of different qualifications. The results obtained allow us to draw a number of conclusions. According to the estimates obtained, a positive effect on migration is exerted by: the size of the population in the region, consumer spending per capita and the availability of transport infrastructure; negative effect - prices in the primary housing market, unemployment rate, crime rate. The greatest magnitude effect (in modulus) falls on consumer spending. Due to the introduction of an optimizing transfer, about 15.7% of the economically active population (11.8 million people) are resettled. This type of migration provides an increase in general welfare by 10.06%. At the same time, the most mobile category of workers, on average, is highly qualified personnel who move from large industrial zones. the population of regions in medium and sparsely populated areas. Low-skilled personnel have limited mobility. The main direction of resettlement for highly skilled workers is from the South-West to the North and East, for low-skilled workers - from the East to the South-West. Preferential mortgage increases the migration inflow in the target regions by 11.6-4.3 thousand people per year, which ensures an increase in GVA by 1.6-4.2 billion rubles, an increase in output by 3.1-8.2 billion rubles. and 1.5-3.8 thousand jobs. An increase in consumer spending may increase the migration inflow in the target regions up to 50 thousand people per year (depending on the conditions of the policy), which ensures an increase in GVA to 18.2 billion rubles, an issue of 35.1 billion rubles. and employment by 16.3 thousand people. The development of road infrastructure reduces the migration outflow in the target regions by 2-7 thousand people per year, which saves the regions 0.7-2.5 billion rubles. GVA, RUB 1.4-5 billion output and 0.7- 2.3 thousand jobs. Further work can be aimed at decomposing the obtained regional results at the municipal level, as well as developing the complexity of the factors taken into account by the proposed models.