This paper represents an empirical examination of the process of banks' growth in Russia during 2004-2010 years. A Stochastic process of growth is modeled by Markov chain theory. Elements in the transition matrices of Markov Chain are the transition probabilities that provide a plausible estimate of how the banking system structure changes from one period to another. markov chain stationarity check revealed three homogeneous periods. Given adequate robustness proof forecasting for 1, 3, and 10 years ahead was done. it is argues number of banks is expected to decrease mostly two times whereas total assets are envisaged to grow more than 2.5 times, but return on assets is unlikely to increase more than by 12% in 10 years by 2020.
The aim of this research is to identify the process that guides the evolution of inflation expectations in Russia. The significance of this theoretical issue is stipulated by the fact that the characteristics of this process are the key determinants of both inflation dynamics and the effectiveness of disinflation measures introduced by the Central Bank. This paper studies the degree to which inflation expectations appear forward-looking and backward-looking. We estimate the Hybrid Phillips curve that includes proxies for both backward- and forward-looking components of inflation expectations. Applying generalised method of moments we asses, which of the two components play a predominant role in determining Russian inflation. The estimates are based on the monthly macroeconomic statistics for the period 1999-2013. Our analysis suggests that to a large extent inflation expectations in Russia remain backward-looking. Hence, it is recommended to take action to enhance agents confidence in the Central Banks policy before switching to aggressive inflation targeting.
This article presents the general economic equilibrium model of the Republic of Kazakhstan. The model includes eight macroagents. Four of the macroagents, Household, Producer, Bank, Owner, are described by optimization problems. The other four macroagents follow prescribed scenarios. All agents contact through market interactions. This framework appears to be an appropriate method to include the stock, money and product markets in a single macroeconomic model. The version of the model calibrated on quarterly data of 2005-2010 simulates the trajectories of variables that characterize the state of the real and financial sectors. The results presented in this paper demonstrate the ability of the model to represent the main effects and trends in the economy of the Republic of Kazakhstan.
In this paper, we empirically test the dependence of the Russian stock market on the world stock market, world oil prices and Russian political and economic news during the period 2001–2010. We find that oil prices are not significant after 2006, and the Japan stock index is significant over the whole period, since it is the nearest market index in terms of closing time to the Russian stock index. We find that political news like the Yukos arrests or news on the Georgian war have a short-term impact, since there are many other shocks. These factors confirm the structural instability of the Russian financial market.