قوانین سیاست های پولی و کاربرد آنها در روسیه

This paper examines the behaviour of the Bank of Russia in post-crisis period (1999–2003). Special attention is devoted to econometric modelling of monetary policy rules of various types. Our empirical results support our preliminary assumptions: despite the officially declared priority of anti-inflation policy, the major efforts of the Bank of Russia were aimed at affecting the exchange rate's smoothness and the level. For that the Bank of Russia relied mainly on monetary targeting, which is the consequence of underdevelopment and low efficiency of the Russian financial sector and banking system.

The upsurge in research aimed at analysing monetary policy observed in the past decade was encouraged by the seminal work conducted by Taylor in 1993 (Taylor, 1993). His simple monetary policy rule offered a surprisingly good description of the actual behaviour of the US's federal funds rate. In subsequent years numerous researches conducted for different countries showed that in practice central banks do follow some sort of pre-set rules in response to macroeconomic shocks. Such rules are not applied mechanically by central banks. A “rule-like behaviour”, as it is specified in McCallum (1997), simply suggests the implementation of a contingency formula for instrument settings that has been selected to be generally applicable for an indefinitely large number of decision periods, as oppose to period-by-period dynamic optimisation on the part of the monetary policy. To say it another way, the policy rule is thought as a formula that specifies instrument settings that are designed to keep a target variable close to it specified target path. The most usual target variable for the monetary authority is the inflation rate. Other leading target-variable choices are macro variables such as GDP. As to the instruments used, some short-term interest rate is usually chosen. The simple Taylor Rule specifies the central bank's policy rate as a linear function of actual or expected inflation and of the actual or expected output gap (that is, a measure of the deviation of output from capacity or trend output). equation(1) View the MathML sourceRt=r¯+Δpta+α1(Δpta−π*)+α2y˜t Turn MathJax on Here, R t is the short-term nominal interest rate that the central bank in question uses as its instrument or “operating target”, i.e. the interest rate over which it exerts control at a daily or weekly frequency. Next, View the MathML sourcer¯ is the long-run average real rate of interest, View the MathML sourceΔpta is an average of recent inflation rates (or a forecast value), and π * is the central bank's target inflation rate. Finally, View the MathML sourcey˜t is a measure of the output gap, the percentage difference between actual and capacity output values. Subsequent applications of the Taylor rule have modified or extended formula (1) in several ways. Some have used proxies for expected future inflation in place of View the MathML sourceΔpta while others have done something similar for View the MathML sourcey˜t or used View the MathML sourcey˜t−1 instead. A special case of the Taylor rule, where the weight on the output gap is zero, is ‘inflation targeting’, in which the policy rate responds only to expected inflation. One widely adopted modification of the Taylor rule is to permit partial adjustment of the central bank's rate, i.e. to include Rt−1 on the right-hand side as a determinant of Rt; this adjustment is intended to reflect the practice of interest rate smoothing, which is widely believed to be prevalent in the behaviour of many central banks. An important line of investigation has been pioneered by Orphanides (1998), who has attempted to base rule calculations on values of ΔptΔpt (inflation) and View the MathML sourcey˜t that were actually available to central bank policymakers at the time that historical instrument settings were chosen. Orphanides recognises that current-period values for View the MathML sourcey˜t could not be known until after the end of period t, and also emphasises the fact that macroeconomic data is often substantially revised after its initial reporting. The rule proposed by McCallum (1993) used base money instead of interest rate as the instrument and nominal income growth target. equation(2) View the MathML sourceΔbt=Δx*−Δvta+β(Δx*−Δxt−1) Turn MathJax on Here, ΔbtΔbt is the change in the log of the adjusted monetary base, i.e. the growth rate of the base between t − 1 and t periods. The term Δx * is a target growth rate for nominal GDP, Δx t being the change in the log of nominal GDP. This target value Δx * is specified as π * + Δy *, where Δy * is the long-run average rate of growth of real GDP. The second term on the right-hand side of (2), View the MathML sourceΔvta is the average growth of base velocity. This term is intended to reflect long-lasting changes in the demand for the monetary base that occur because of technological developments or regulatory changes (presumed to be permanent); it is not intended to reflect cyclical conditions. These conditions are represented by the final term, which prescribes that base growth is adjusted upward (i.e. policy is loosened) when Δxt−1Δxt−1 falls short of Δx*. The main open economy alternative to the simple, closed economy Taylor rule was introduced by Ball (1999). It uses a Monetary Conditions Index (MCI) as an instrument—a weighted average of interest rate and exchange rate instead of the interest rate only. On the right-hand side of the rule, inflation is replaced by ‘long-run inflation’, a variable that filters out the transitory effect of exchange rate movements. The study of monetary policy rules in Russia was first made by Drobyshevsky and Kozlovskay (2002). Following Clarida et al. (1998), the authors used a Generalized Method of Moments (GMM) methodology. They use only the short-term interbank rate as an instrument, not investigating any potential alternatives (for instance, the deposit rate or base money). Drobyshevsky and Kozlovskay estimate the theoretically expected response of the interest rate on inflation and exchange rate developments, but failed to incorporate an output variable into their model. Another weakness of their work is low reliability of estimated coefficients, due to the very short period used (covering only three years from 1999 to 2001) and most likely inadequate set of instruments used (see below the section on “Validity of Instruments”). The models and the set of target variables examined by the authors in this paper differ from those used by Drobyshevsky and Kozlovskay. However, our general conclusions are similar to theirs

In the initial part of our research, we estimated monetary policy rules using the Generalised Method of Moments and both interest rates and monetary base as instruments. The obtained results demonstrate that the interest rate policy of the Bank of Russia has been rather accommodative in post crisis period, while the management of base money dynamics possessed a pronounced stabilising pattern. These findings are in accordance with our knowledge and understanding of monetary policy as well as the official statements of the Central Bank itself. Further, our analysis revealed that, despite the officially declared priority of anti-inflation policy, the major efforts of the Bank of Russia were turned to the regulation of the exchange rate. There are some reasons to suggest that the Central Bank intervened in the exchange market with the aim to affect not only the smoothness of the exchange rate but also its equilibrium level. These conclusions are proved by the estimation results obtained though the application of three different methods. It is also should be noted, nevertheless, that the construction of monetary policy rule in the form of a system of two simultaneous equations (for intervention and sterilisation) does not have an analogue in the literature and offers the ground for further investigation. As a direction of the further research it is possible to suggest the discussion of the following problems. What parameters should the central bank include in its reaction function? What can be their values, taking into account the specific Russian situation? Do the empirical results obtained by the authors of this paper correspond to these optimum values?