Regional population expenditure for foodstuffs in the Russian federation: componential and cluster analyses

Murat B. Guzairov, Irina V. Degtyareva, Elena A. Makarova

Abstract


The article describes the solving of the problem of conducting the component and cluster analyses of population expenditure on food as one of the most important components of the standard of living. The purpose of the analysis is to develop the regional clusters of the Russian Federation, which vary in the structure of household expenditure for foodstuffs. The foodstuffs are presented in absolute units taking into integral account the standard of living index. The methods of intellectual analysis such as component and cluster analyses are applied as the research methods. The procedure for the data intellectual analysis based on the interconnected performance of component and cluster analyses is proposed. The procedure of the data intellectual analysis considers the interrelation between the results received by different methods, and also the possibility to return to the previous method for the purpose of repeating the analysis to specify consistently the clusters composition. Few clusters of the wealthy regions characterized by the high and average levels of expenditure for foodstuffs are revealed as well as the quite many clusters of not enough wealthy and not wealthy regions characterized by the low level of expenditure for foodstuffs. It is shown that the growth of standard of living characterized by the size of a gross regional product per capita is followed by the growth of the Gini coefficient, which indicates both the inequality of income distribution and reduction in expenditure for low-value foodstuffs. The results of the analysis can be applied to the development of the decision-making support system intended for the analysis of the scenarios of macroeconomic regulation in the eld of income policy for the purpose of increasing the standard of living of population. The analysis of the population expenditure for foodstuffs has allowed to reveal the cluster structure of the regions of the Russian Federation, to show it according to the generalized indications, to formulate the specific characteristics of the clusters of the regions and important management decisions.

Keywords


expenditure of households; component and cluster analyses; clusters of regions; scatterplot

Full Text:

PDF

References


Ivanov, V. N. & Suvorov, A. V. (2006). Neravenstvo i bednost naseleniya. Opyt resheniya problemy v Rossii i za rubezhom [Inequality and poverty of population. Experience of solving the problem in Russia and abroad]. Problemy prognozirovaniya [Problems of forecasting], 3, 132–149.

Kolmakov, I. B. (2006). Prognozirovanie pokazateley differentsiatsii denezhnykh dokhodov naseleniya [Forecasting of differentiation indexes of population income]. Problemy prognozirovaniya [Problems of forecasting], 1, 136–163.

Rimashevskaya, N. M. (2006). Nekotoryye problemy sotsialnogo reformirovaniya v Rossii [Some problems of social reformation in Russia]. Problemy prognozirovaniya [Problems of forecasting], 2, 3–17.

Shevyakov, A. Yu. (2010). Neravenstvo dokhodov kak faktor ekonomicheskoy i demograficheskoy dinamiki [Income inequality as a factor of economic and demographic developments]. Moscow: Institute of Socio-Economic Studies of Population of Russian Academy of Sciences Publ., 43.

Ilyasov, B. G., Degtyareva, I. V., Makarova, E. A. & Valitov, R. R. (2013). Sistemnoye modelirovanie dinamiki formirovaniya dokhodov i raskhodov naseleniya s uchyotom ikh differentsiatsii [System modeling of the dynamics of revenues and expenses of the population, taking into account their differentiation]. Problemy upravleniya i modelirovaniya v slozhnykh sistemakh: tr. XV mezhdunar. konf. (19–22 iyunya 2012 g.) [Proceedings of International Conference “Problems of control and modeling in complex systems” (19–22 June 2012)]. Samara: Samara research center of RAS Publ., 179–193.

Ilyasov, B. G., Degtyareva, I. V., Makarova, E. A. & Valitov, R. R. (2012). Sistema intellektualnoy podderzhki prinyatiya resheniy pri upravlenii makroekonomicheskim vosproizvodstvennym protsessom na osnove imitatsionnogo modelirovaniya [The system of intellectual support of decision making in the management of macroeconomic reproduction process on the base of simulation modelling]. Vestnik UGATU [Bulletin of the Ufa State Aviation Technical University], 3, 217–229.

Barsegyan, A. A., Kupriyanov, M. S., Kholod, I. I., Tess, M. D. & Elizarov, S. I. (2009). Analiz dannykh i protsessov: ucheb. posobie [Data and process analysis: a study guide]. 3rd ed., Rev. and ext. St. Petersburg: BKhV-Peterburg Publ., 512.

Demidova, L. A., Kirakovskiy, V. V. & Pylkin, A. N. (2012). Prinyatie resheniy v usloviyakh neopredelennosti [Decision making in the conditions of uncertainty]. Moscow: Goryachaya liniya — Telekom Publ., 288.

Kulaichev, A. P. (2013). Metody i sredstva kompleksnogo analiza dannykh: uchebnoe posobie; 4-e izd., pererab. i dop. [Methods and complex data analysis tools: a study guide; 4th ed. rev. and ext.]. Moscow: FORUM Publ.; Infra-M Publ., 312.

Porshnev, S. V., Ovechkina, E. V., Mashchenko, M. V. et al. (2010). Kompyuternyy analiz i interpretatsiya empiricheskikh zavisimostey: ucheb. posobie [Computer analysis and interpretation of empirical dependences: a study guide]. Moscow: Binom-Press Publ., 336.

Mitra, S. & Acharya, T. (2003). Data Mining. Multimedia, Soft Computing, and Bioinformatics. Hoboken, New Jersey, John Wiley & Sons, Inc., 401.

Han, J. & Kamber, M. (2001). Data mining: Concepts and Techniques. San Mateo: Morgan Kaufmann Publishers, 550.

Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, Cr. D., Silverman, R., Wu, A. Y. (2002, July). An Efficient k-Means Clustering Algorithm. Analysis and Implementation IEEE transactions on pattern analysis and machine intelligence, 24(7), 881–892.

Ruppert, D. (2011). Statistics and Data Analysis for Financial Engineering. New York: Springer Science+Business Media, LLC, 638.

Vercellis, C. (2009). Business Intelligence: Data Mining and Optimization for Decision Making. New York: John Wiley & Sons Ltd, 436.




DOI: https://doi.org/10.15826/recon.2016.2.1.009

Copyright (c) 2018 Murat B. Guzairov, Irina V. Degtyareva, Elena A. Makarova

Сertificate of registration media Эл № ФС77-80764 от 28.04.2021
Online ISSN 2412-0731