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.
This paper constructs a DSGE model for an economy with commodity . exports. We estimate the model using Russian data, making a special focus on quantitative effects of commodity price dynamics. There is a widespread belief that economic activity in Russia crucially depends on oil prices, but quantitative estimates are scarce. We estimate an oil price effect on the Russian economy in a general equilibrium framework. Our setup is similar to those of Kollmann (2001) and Dam and Linaa (2005), but we extend their models by explicitly accounting for oil revenues. In addition to standard supply, demand, cost-push, and monetary policy shocks, we include the shock of commodity export revenues. The main objective of the paper is to identify the contribution of structural shocks to business cycle fluctuations in the Russian economy. We found that despite a strong impact on GDP from commodity export shocks, business cycles in Russia are mostly domestically based.
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.
In this paper, a Kalman filter-type model is used to extract a global stochastic trend from discrete non-synchronous data on daily stock market index returns from different markets. The model allows for the autocorrelation in the global stochastic trend, which means that its increments are predictable. It does not necessarily mean the predictability of market returns, since the global trend is unobservable. The performance of the model for the forecast of market returns is explored for three markets: Japan, UK, USA.
What are the attitude of people in Russia and Ukraine about coexistence with immigrants? Are they similar to the attidudes of people in European countries? This study compares possible determinants of attitudes toward immigrants in the European Union, Russia and Ukraine. The comparative analysis revealed both similarities and differences in public attitudes towards immigrants in Russia and Ukraine and in European countries. In particular, in Russia, Ukraine and Europe, the public perception of immigrants improves as the educational level of respondents increases. At the same time, more religious citizens in Russia, Ukraine and new European countries (joined the EU after 2004) perceive the cultural impact of immigrants to be greater, whereas those in old European countries (joined the EU before 2004) exhibit the opposite tendency. So, Russia and Ukraine should use the European countries experience in this area cautiously.
We study game equilibria in a network, in each node of which an economy is described by a two-period model of endogenous growth with production and knowledge externalities. Each node obtains an externality produced by the sum of knowledge in neighbour nodes. Uniqueness of the inner equilibrium is proved. Ways of behaviour of agent (passive, active, or hyperactive) in dependence on received externalities are studied. Classification of networks based on a notion of type of node is provided. It is shown that the inner equilibrium depends not on the network's size or topology but on its structure in terms of the types of nodes, and in networks with similar types structure agents in nodes of the same type behave similarly. Changes of the equilibrium under changes in the network structure are studied, as well as network formation, in particular, connection of network components, and appearance of new links.
Since 2013, we have observed an increasing number of failed Russian banks with negative capital and falsified financial reporting. We use previously unavailable data for the period 2010 – 1H2015 to develop a logit model predicting the probability of bank failure with negative capital. In order to do so, we suggest solutions for the class imbalance and variable selection problems. The models chosen are confirmed to be robust and have longer forecasting horizons compared to previous research. Also, we implement a novel probability-based approach to the out-of-sample forecasting evaluation which confirms a good fit of the selected models to data. The model predicts bank failures in three quarters and finds 33% of actual failures among 5% of banks with the highest predicted probability to fail (out-of-sample). In addition, we make available previously unpublished banking data for Russia
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.