Interaction of Regional Labour Markets in Russia: Spatial Econometric Analysis

Abstract

With the help of spatial regression models and classical models of panel data the study identifies and assesses the various factors’ influence on the unemployment rate in Russian regions from 2005 to 2010. Using the spatial autoregressive lag model the authors revealed that the change (increase or decrease) in the level of unemployment in one region leads to its changes in other regions. The use of spatial regression models allowed the researchers to identify the effect of higher education on the unemployment rate in the region: the higher share of the employed with higher education corresponds to the lower unemployment rate. This can’t be revealed with the help of classical models of panel data. In addition, some regional characteristics have nonlinear functional dependence of unemployment rate, which requires the algorithm modification for finding direct, indirect and total effects and their confidence intervals using the Monte Carlo approach

Keywords

• spatial econometric modeling
• unemployment rate
• region
• Russia