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Differentiating the Russian regions through an econometric analysis by socio-economic indicators influencing the consumer demand

Vol. 13, Iss. 12, DECEMBER 2017

PDF  Article PDF Version

Received: 13 September 2017

Received in revised form: 6 October 2017

Accepted: 23 October 2017

Available online: 22 December 2017


JEL Classification: С10, C80, E42, O18

Pages: 2200–2217

Pakhomov A.V. NPK Dedal (Rosatom State Corporation Company), Dubna, Moscow Oblast, Russian Federation

Pakhomova E.A. Dubna State University, Dubna, Moscow Oblast, Russian Federation

Rozhkova O.V. Dubna State University, Dubna, Moscow Oblast, Russian Federation

Importance The article focuses on a correlation between regional socio-economic indicators and amount of various retail loans, gross portfolio of which represents one of the institutional determinants of consumer demand. We review a spectrum of characteristics for finding the best forms to interact and coordinate interests of the State, real economy, banking and the public in socio-economic transformations.
Objectives The regions are differentiated by aspect influencing retail lending.
Methods The research is performed in two steps. First, socio-economic indicators are checked. Second, the regions are differentiated on the basis of the analyzable socioeconomic indicators using cluster analysis methods.
Results Classifications based on different indicators and methods may lead to similar and even approximate results. However, as an in-depth analysis of items within the same population (cluster) shows, substantial discrepancies may arise from one or several factors, thus proving that they shall be attributed to different groups. The substantive interpretation of regions' similarities and differences helps adjust the outcome, consider the specifics of each subject and create conditions for making informed decisions on governance of vast territories.
Conclusions and Relevance The research may become a substantive and instrumental underpinning for further recommendations for federal and regional authorities to address consumer demand issues and assess its effect on the development of economic systems at different levels.

Keywords: socio-economic indicator, consumer demand, correlation and regression analysis, structural equation, cluster analysis


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