2006. vol. 10. No. 2

The paper studies major functions of the “stabilization fund” created in Russian economy in the last three years. It is shown that the fund usage as an instrument of money sterilization was not justified by the recent economic performance in Russia, and the empirical evidence casts doubts upon the fund capability to restrict money supply not to mention damping of inflationary pressure. The deterministic model of the fund dynamics did produce fundamentally different conclusions with regard to its macroeconomic role which depends upon assumptions with regard to the future dynamics of the monetary base. The alternative view of the stabilization fund based upon its analogy with the financial derivative, namely to the forward contract, was developed in the second part of the paper. Assuming the process of “oil incomes” of the government to be lognormally distributed the stochastic model of stabilization fund dynamics was constructed and evaluated. In particular, it proved that the growth rate of the fund should be significantly less than that of ”oil incomes”. This corollary appeared to be fully in accord with the view of the fund as the risk neutral insurance against different risks.

The paper is devoted to the analysis of dynamic behavior of fixed assets and investments in fixed capital in the Russian economy in transition. It was shown, that the official Rosstat technique implementation of fixed assets and investments measurements may lead to the substantial understatement of fixed assets renovation and replacement rates. The depth of the decline in investment spending during the transition period might become overstated. The bias may be explained by severe difficulties in measurement of price dynamics and capital replacements in first years of transition.

Alternative estimations of indices of physical volume of fixed assets and investments in fixed capital by 15 main industries and branches of industry in 1991-2003 were obtained. Industry-specific features of investment and fixed assets dynamics were discussed. Taking into account the alternative estimations of fixed assets and investments, conventional approaches to the investment behavior and capital stock dynamics explanations in the Russian economy in transition need to be revised.

Decision making problem of a bank consisting large number of branches and the head office that supplies «collectively used inputs» is considered.

This paper is devoted to the construction and analysis of empirical macroeconomic model of Russia during the postcrisis period. In the first part we analyze the vector error correction model that describes the most important relations in the real sector of economy. Besides, a particular attention is paid to the dependence on the parameters reflecting a conjuncture of the world markets, and also to the revealing of internal factors of economic growth. In the second part of this article we focus on the construction of the model of monetary sector. We analyze mechanisms of monetary and currency policies, the direction and efficiency of their influences on the basic macroeconomic parameters, such as GDP and inflation. It is also checked the correspondence of stabilization policy to the Government and Central Bank purposes.

The course of lectures is devoted to one of the most claimed modern tools of the quantitative analysis of the statistical information in economy – to panel data analysis which represent the pooling of observations on a cross-section of households, countries, firms etc. over several time periods.

The panel data are applied in empirical researches of economic phenomena since 60th years of XX century. Their use gives a number of essential advantages in regression parameters estimation as they combine opportunities, both time series and cross-section analysis. With the help of the panel data there is possible a studying of such chronic problems of a society, as poverty, unemployment, criminality, and also consequences of carrying out of various state social and economic and political programs.

In the course a panel data analysis foundation and principles of construction of the most claimed models are considered. One of lectures is devoted to the analysis and interpretation of the models constructed on real Russian panel data – RLMS (Russia Longitudinal Monitoring Survey).

In this release four first lectures of the course are published. In the first of them general information about panel data is presented: sources of the panel data and some features of their use. In the second lecture there are given a representation of simplest models of the panel data analysis and some most wide used estimation methods. The third lecture is devoted to discussion of estimator’s properties and specification tests. In the fourth lecture discussion of specification tests proceeds and an example of the practical application of the stated methods to RLMS data analysis is considered.