METHODS TYPOLOGY OF RURAL AREAS IN TERMS OF SOCIO-ECONOMIC SECURITY

Issue № 9, 2013, article № 9, pages 63-69

Section: Social problems of rural territories

Language: Russian

Original language title: МЕТОДИКА ТИПОЛОГИЗАЦИИ СЕЛЬСКИХ ТЕРРИТОРИЙ ПО УРОВНЮ СОЦИАЛЬНО-ЭКОНОМИЧЕСКОЙ БЕЗОПАСНОСТИ

Keywords: SOCIO-ECONOMIC SECURITY, RATING, RURAL AREAS, METHODS, CLUSTER ANALYSIS, A METHOD OF MULTI-DIMENSIONAL MEDIUM, THE METHOD OF INTEGRAL MEAN

Abstract: In the economic and social conditions in rural areas, there are significant differences. There is a real need to identify the level of differentiation of the territory to determine appropriate areas for development. The article presents the results of the evaluation of socio-economic security in rural areas of the Vologda region. The evaluation methods used for rating multidimensional medium and the total mean, and cluster analysis. These methods allow you to define a typology backbone industry, to consider the opportunities and threats of rural development, as well as suggestions for optimizing the most appropriate planning of territorial development programs, taking into account the socio-economic and agro-climatic conditions. Comparative evaluation of the current situation in the economic security in rural areas of the Vologda region made ​​on the basis of statistical data on the state of security areas of the Vologda region in recent years, including socio- economic and demographic factors, to varying degrees, affecting the economic well-being and social infrastructure of rural life. Typology method of rating allows without any additional software to generate the rating on any number of the studied areas. That confirms the relevance of the presented methods of rating by the integral mean. Typology of rural areas clustering method allows us to supplement and clarify the results of rating. Cluster analysis method allows to classify multi-dimensional observations, each of which is described by a set of indicators of social and economic status of rural areas. Difference presented techniques is to determine the time series of basic statistical data. Rating evaluation conducted on the statistical data on the average for 20 years, clustering is presented in terms of a single in 2012.

Authors: Logantsova Natalia Vladimirovna