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The scientific paper provides a comparative analysis of the development level of the transport infrastructure in the Russian Federation constituents of the Southern Federal District. The analysis of the statistical data on the transport activity shows an increase in the volume of transport services in Rostov-on-Don and Krasnodar from 2012 to 2018. In Volgograd region and Astrakhan Oblast there is a decrease by 22% and 6% respectively. With regard to the motor hard surface highways per 1000 km2 there is a significant difference between the Russian Federation constituents in the Southern Federal District. The gap in the values of indicators in Krasnodar, Rostov-on-Don and other regions reaches 50%. In addition, a direct relationship between the social indicators and the volume of transport services for the period under consideration has been identified. In order to assess the development level of the region's transport and logistics infrastructure an integral indicator has been calculated based on the calculation of the relative coefficients of the transport activity in the Russian Federation constituents. As a result, the study shows that the highest value of the integral indicator characterizing the development level of the vehicular transport infrastructure is in Krasnodar Territory, the lowest value is in the Republic of Kalmykia. It should be noted that there is a significant imbalance in the development level of the transport and logistics infrastructure in different regions, which determines their different investment attractiveness and social and economic progress.

The article shows the relationship between the logistics infrastructure of the Ural Federal District and the economic indicators of both the Russian Federation and the district. The parameters of the logistics infrastructure included indicators of its warehouse, transport, financial, and informational components. The analyzed data are for 2004-2018. To exclude redundant variables, they were tested for normality, multicollinearity, and the measure of the relationship with dependent indicators was assessed. The research method is multiple regression analysis. The study has proved that the relationship between economic indicators and independent variables can be represented as a linear multiple regression model. Based on the models obtained, the significant influence of the transport component of the logistics infrastructure of the Ural Federal District on the economic indicators of the country and the district is shown. The creation of logistics infrastructure development programs based on the results obtained will promote the socio-economic development and investment attractiveness of the district.