Identification of depressed areas and their development modeling: Russian and foreign experience

This paper suggests some approaches to identification, modeling and monitoring of depressed areas in Russia and other countries. It contains a survey of programs (strategies) and economic-mathematical modeling experience for socio-economic development of depressed areas. We have identified several most applicable economic-mathematical modelling methods, such as: analytic hierarchy process for choosing strategic alternatives of overcoming depressed development in regions; regression analysis for regional depression factors identification, GRP-modeling, and testing beta-convergence hypothesis; cluster analysis for depressed regions identification; production function component analysis for modeling capital investments into the industry; principal component analysis for complex assessment of regional development, and others. In foreign publications we could distinguish Mahalanobis metric matching; input- output model (IMPLAN); ordinary least squares (OLS) regression models; multiple regression models; 3-equation simultaneous equation model; two-stage least squares (2SLS) regressions; discriminant analysis of factors, and others. As a result of the study, some recommendations on application of international experience in managing depressed territories are given for Russia.