Cite this article as:

Rodionova S. Y., Yusupova S. M., Trach T. M. ЭКОНОМЕТРИЧЕСКИЕ ПОДХОДЫ К ОЦЕНИВАНИЮ КРЕДИТНОГО ПОВЕДЕНИЯ НАСЕЛЕНИЯ В РОССИИ. Izv. Saratov Univ., Economics. Management. Law, 2016, vol. 16, iss. 1, pp. 39-?. DOI:

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Introduction. Crediting of people has a firm position in last decade, but now there is a problem of the granted loans quality. So the study of the credit behavior, its mechanisms and structures is actual question. In article emphasis was placed on the methodological part of the problem, it was examined various statistical and econometric tools to study of the credit behavior.

Methods. Using binary choice model determinants of credit behavior were identified, and a typical portrait of average borrower was made. Using cluster analysis the volume of consumer loans by region was investigated. By using time series analysis for the volume of granted loans SARIMA-model and forecast was estimated.

Results. The most important determinants of credit behavior are age, sex, level of education, income, the loan experience in the past, the number of income sources. As a result of the cluster analysis Russian regions were divided into three homogenous groups that differ in terms of granted loans, the number of credit institutions, payable on the granted loans. Forecast of the volume of granted loans has shown that the volume of loans will continue to have a positive trend, despite the economic crisis.


1. Tsentral’nyi bank Rossiiskoi Federatsii (The Central Bank of the Russian Federation. Site). Available at: (accessed 29 June 2015).
2. The World Bank. Site. Available at: (accessed 29 June 2015).
3. Ando А., Modigliani F. The «Life Cycle» Hypothesis of Saving: Aggregate Implications and Tests. The American Economic Review, 1963, vol. 53, № 1, pp. 55–84.
4. Magri S. Italian households’ debt: the participation to the debt market and the size of the loan. Empirical Economics, 2007, vol. 33, pp. 401–426.
5. Strebkov D.О. Osnovnye tipy i faktory kreditnogo povedeniia naseleniia v sovremennoi Rossii [The main types and factors of population’s credit behavior in modern Russia]. Voprosy ekonomiki, 2004, vol. 22, pp. 109–128.
6. Ivashinenko N. N. Mekhanizm vzaimodeistviia na fi - nansovom rynke Rossii: naselenie i fi nansovye struktury [The mechanism of interaction on the Russian fi nancial market: the population and fi nancial structures]. Ekonomicheskaya sotsiologiya [Economic Sociology], 2001, vol. 3, no. 2, pp. 27–43.
7. Kuzina О. Y. Analiz dinamiki pol’zovaniia bankovskimi kreditami i dolgovoi nagruzki rossiian [An analysis of the bank loans dynamics and debt load of Russians]. Dengi i kredit [Money and Credit], 2013, vol. 11, pp. 30–36.
8. Obsledovanie «Roditeli i deti, muzhchiny i zhenschiny v sem'e i obschestve» (The survey «Parents and children, men and women in family and society»). Available at: (accessed 29 June 2015).
9. Tsentral’naya baza statisticheskikh dannykh (The central statistical database). Federal’naya slyzhba gosudarstvennoi statistiki (Federal state statistics service. Site). Available at: 29 June 2015).
10. Kantorovich G. G. Lektsii: Analiz vremennykh ryadov [Lectures: Time Series Analysis]. Ekonomicheskii zhurnal VShE [The HSE Economic Journal], 2003, vol. 1, no. 7, pp. 79–103.

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