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National Interests: Priorities and Security
 

Evaluating the economic mechanism of the agricultural sector as a tool to ensure the food security of the region

Vol. 12, Iss. 2, FEBRUARY 2016

PDF  Article PDF Version

Received: 14 October 2015

Received in revised form: 2 November 2015

Accepted: 12 November 2015

Available online: 28 February 2016

Subject Heading: FOOD SECURITY

JEL Classification: Q18

Pages: 81-93

Filimonova N.G. Krasnoyarsk State Agrarian University, Krasnoyarsk, Russian Federation
natali_f08@mail.ru

Ozerova M.G. Krasnoyarsk State Agrarian University, Krasnoyarsk, Russian Federation
ozerova_m71@mail.ru

Importance Sustainable development of the agricultural sector depends on the economic mechanism. Its efficiency evaluation helps determine the effectiveness of changes in agriculture and elaborate the main areas for improving agricultural policies.
Objectives The research devises a methodological approach to evaluating the economic mechanism efficiency in the agricultural sector and its implementation, illustrating the regions of the Siberian Federal District.
Methods The efficiency of the economic mechanism was evaluated through methods of multivariate statistical analysis. We applied a factor analysis to make an integral evaluation of the economic mechanism and a cluster analysis to classify regions in terms of the economic mechanism efficiency.
Results We evaluated the economic mechanism in the agricultural sector of the Siberian Federal District, ranked the regions per efficiency and identify three clusters, i.e. the effective, moderately effective, and ineffective ones. When forming the economic mechanism, regions should consider climatic, national and organizational specifics of agriculture.
Conclusions and Relevance The outcome not only reflect the extent of regional differentiation in agricultural development of the Siberian Federal District, but also lay the basis for initiative to tackle it as part of the general agricultural policy.

Keywords: food security, economic mechanism, factor analysis, cluster analysis, regions, ranking

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