Стабильность распределения банков как аргумент в пользу концепции агрегированного агента.
The issue about relevancy of usage of concepts of representative and aggregate agents in modern economic science is very actual. The theoretical model [Malakhov, Pospelov, 2014] showed that the distribution of banks on proportions of assets is stable over time. If this result is correct for real data, then it will be another argument to use the concept of an aggregate agent in modeling a banking sector, which is an actual topic for macroeconomists. In this paper we provide an empirical test of this result using data from the Russian banking system. We also analyze other key variables, such as households’ deposits, firm’s credits, interbank credits, etc., because if distributions of proportions of these variables are stable too, then it will be an additional argument to use the concept of aggregate agents. This paper is aimed at selecting the optimal (in some sense) functional forms of distribution of proportions of the key variables and validating stability of these distributions over time. The actuality of this topic is also confirmed by recent events in Russian economy and banking system in particular.
We show that using generalized versions of well-known distributions, we can accurately describe the distribution of Russian banks in terms of a turnover balance sheet. In particular, the Pareto distribution of type IV and asymmetric generalized error distribution show a very high accuracy of approximation, these results being correct for all considered variables. The quality of approximation by these distributions is robust both in time and in the cross-sectional dimensions, however, individual banks can move within this distribution. Thus, we consider rather the distribution of banks of the entire Russian banking system than the distribution of individual banks.
Moreover, estimations of parameters of the distribution of proportions of assets have slightly changed during observation period and these changes could be possibly connected with structural shifts in the banking industry. Kolmogorov-Smirnov test shows that the differences between the distributions of proportions of assets become significant at 5% confidence level only when the difference between periods is more than 8 months. Thus, the theoretical model [Malakhov, Pospelov, 2014] mainly passes the empirical test.