Corresponding author: Riikka Nuutilainen ( riikka.nuutilainen@bof.fi ) © 2017 Nonprofit partnership “Voprosy Ekonomiki”.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BYNCND 4.0), which permits to copy and distribute the article for noncommercial purposes, provided that the article is not altered or modified and the original author and source are credited.
Citation:
Korhonen I, Nuutilainen R (2017) Breaking monetary policy rules in Russia. Russian Journal of Economics 3(4): 366378. https://doi.org/10.1016/j.ruje.2017.12.004

This study estimates whether the monetary policy rules of Bank of Russia have changed recently. Russia has moved towards inflation targeting over the past years, which is reflected in our empirical estimations. We start by estimating various monetary policy rules for Russia, concluding that a variant of the Taylor rule depicts Bank of Russia's monetary policy over the past decade well. Moreover, there have been two clear breaks in the coefficients of the estimated monetary policy rule, possibly signifying a shift towards traditional inflation targeting and also the current recent economic turbulence.
monetary policy rule, Taylor rule, McCallum rule, Russia, inflation
In this paper, we analyze whether the monetary policy rules of the Bank of Russia have changed over the past years. This could be possible a priori, given the changes in the explicit monetary policy framework, as well as the further development of Russia's financial system.
Broadly, previous studies (see section 2 for a brief literature review) determined that, in recent years, Russia's monetary policy can be described in terms of the Taylor rule, where the central bank's steering of the interest rate responds to deviations from its inflation target as well as the output gap. The central bank's aim is to stabilize inflation around its target and output around the level of potential output. In Russia, as in numerous other open economies, the exchange rate is often included in estimations.
We find that estimated monetary policy rules do indeed contain breaks, or at least a break. We observe a break in the estimated Taylor rule in February 2015, broadly coinciding with the formal start of inflation targeting. It is also interesting that before the summer of 2006, the Taylor rule did not explain Bank of Russia's interest rate policy. This would hint that the changes in Russia's monetary policy have been gradual, and the central bank perhaps behaved differently in earlier periods.
This paper is structured as follows. The subsequent section offers a short introduction to Russia's monetary policy, as well as a review of the literature on the estimated monetary policy rules in Russia. Section 3 introduces the data and the estimated monetary policy rules. In the fourth and fifth sections, we estimate different versions of monetary policy rules, with and without breaks. Section 6 concludes the paper.
Our data sample runs from the beginning of 2004 to August 2017.
The Bank of Russia first stated price stability as its primary policy objective in the 2007 monetary policy guidelines (
While empirical estimates of different monetary policy rules are relatively common in advanced OECD countries, similar exercises for emerging market countries are still rare. Moreover, there are only a handful of published papers on monetary policy rules in Russia, and their data samples typically end more than a decade before our data. For instance,
One can also note that a somewhat stable link between monetary aggregates and other economic variables —that is, a money demand function —is needed for the McCallum rule to be a viable strategy for a central bank to follow. For Russia,
We estimate two types of monetary policy reaction functions to evaluate the Bank of Russia's behavior from 2004 to August 2017. We utilize the literature on monetary policy rules to formulate the reaction functions. To timely capture the recent policy changes, we use monthly data in our estimations. This section introduces the estimated policy rules and the data used in the empirical analysis. Data and their original sources are listed in Appendix
The estimated interest rate rule is a version of the famous
Taylor (
We estimate the Taylor interest rate rule of the form:(1)
In the empirical estimations, we use the Bank of Russia's key policy rate (the one week repo credit rate) as the policy interest rate it from February 2011 onwards, when the central bank adopted this instrument and started to publish the data. Prior to that, the refinancing rate is selected as the policy interest rate.
We assume that monetary policy reacts only to deviations in output growth, as well as exchange rate and oil prices from the longrun trend level. Following the literature, we use HP filtering to calculate our deviation series.
In addition to the interest rate rule, we also estimate the money supply rule introduced by
The McCallum rule estimated is of the form:(2)
The nominal base money growth, Δbmt, is the yoy change in the M0 money aggregate. Fortunately, the Ministry of Finance of Russia publishes a monthly GDP estimate in roubles. We use this series to calculate the yoy nominal GDP growth rate and the HP filter to obtain the nominal output growth deviation, ${\stackrel{\u02c6}{\Delta x}}_{t1}$. The exchange rate and oil price gaps are calculated similarly to (1), but using the nominal effective exchange rate (NEER) index. Again, β0 is a constant term, β1–β4 measure the strength of policy reactions in the base money supply to macroeconomic variables, and β5 measures policy inertia. Error term ɛt captures the elements of random behavior that might be present at time t, potential omitted variables, and specification errors. Increases in the base money supply indicate policy easing. Therefore, the signs in countercyclical policy reactions are the opposite of the Taylor rule: β1 < 0, β2 > 0, and β3, β4 > 0. To adequately account for policy reactions to oil prices, the second lag of the oil price deviations also need to be added to the policy rules.
The estimated policy rules are formulated to retain operationality. Policy is assumed to react to macroeconomic variables prevailed in the previous period and, thus, are available at time t. Another possibility would be to allow the central bank consider expectations about future inflation and output when making policy decisions (see, for example, Clarida et al.,
Appendix
Here, we replicate the monetary policy rule estimations from
The policy reaction functions are empirically estimated using a general method of moments (GMM) estimator. The use of GMM is fairly standard in estimating policy reaction functions with inertia and possible measurement errors for variables. The estimation results are presented in Tables
Taylor rule estimation results.
McCallum rule estimation results.
The estimated policy reactions of the Taylor rule (1) for the full sample period are presented in
The policy reactions to exchange rate developments and oil prices are more difficult to interpret, as these two variables are largely interrelated. The interest rate reactions to oil prices are statistically significant, but the sign of the estimated reactions to the first lag of the oil price are opposite from those expected. The increase in oil prices is assumed to lead to policy tightening, as it will boost future output growth and increase inflation. However, the second oil price lag has the opposite sign and counteracts the negative response to the first lag.
The sign of the estimated exchange rate reaction is opposite from the expected one. In the policy rules literature, policy easing is assumed to follow exchange rate appreciation. Here, we find the reverse. Oil prices and the exchange rate are closely interconnected and, in our estimation, we are perhaps unable to completely disentangle these two effects. When discarding the effect of oil prices, the exchange rate is not statistically significant.
The estimated McCallum rule policy reactions are presented in
During our estimation period, the Bank of Russia's monetary policy framework has gone through several changes in terms of both policy instruments as well as policy objectives, as described in section 2. Therefore, a single monetary policy rule may not fit the Russian data well for the entire period, and presumably the policy rules are subject to structural breaks.
The existence of possible breaks in the estimated rules is studied using the AndrewsFair Wald and LRtype tests suitable for GMM estimations. The test statistics show statistically significant breaks in the estimated rules. The most likely dates for the breaks are estimated by maximizing the value of the AndrewsFair LRtype statistic. First, we estimate the date for the most likely break and, given the most likely first breakpoint, test the possible subsequent breaks.
For the Taylor rule, the first breakpoint is February 2015, that is, when the rapid interest rate increases were followed by interest rate cuts (see Appendix
Taylor rule estimation results for different subperiods.
During 2006–2015, the monetary policy of Russia moved more towards price stabilization and started using the interest rate as a predominant policy instrument. During this period, the Taylor rule fits the data well. Coefficients on both inflation and output gap have the expected signs. Additionally, the effective exchange rate is statistically significant for Bank of Russia's interest rate formation. However, the sign of the estimated exchange rate reaction is opposite from the expected one. Our results may have the following explanation. When oil price increases, this also leads to an exchange rate appreciation and perhaps to expectations of further appreciation. In our estimation, we are unable to completely disentangle these two effects, which may lead to the observation that exchange rate appreciation is followed by a monetary policy tightening, even if an oil price increase is its ultimate cause.
Taylor rule longrun coefficients.
From the beginning of 2015, the Bank of Russia has been committed to fullfledged inflation targeting. Nonetheless, during this time, Russia has also been faced with a severe economic downturn as well as rapidly accelerating inflation due to the depreciation of the rouble. Consequently, the monetary policy had to balance between supporting the real economy and counteracting inflation. Our estimation results show that, after 2015, the interest rate policy has indeed followed the Taylor rule, and both reactions to inflation deviation and output gap are statistically significant. However,
We can also identify two statistically significant breakpoints for the McCallum rule. The first breakpoint, maximizing the value of the AndrewsFair LRtype statistic, is in March 2014. Given this break, the most likely second break is in January 2011.
McCallum rule estimation results for different subperiods.
After 2011 this is not the case anymore. From 2011 to early 2014, the central bank base money supply reaction is statistically significant only to oil prices. After March 2014, the nominal output growth deviation is statistically significant, but the sign of the policy reaction is positive, indicating procyclical reactions in the money supply to nominal output growth. This is contrary to the theoretical assumptions in the monetary policy rules literature.
We have shown that Russia's monetary policy can be characterized by the Taylor rule at least since 2006. This seems to be also in consensus with more recent papers on this topic. We explicitly consider possible breaks in the estimated monetary policy rules. As some extant studies have found that Russia's monetary policy could be characterized by the McCallum rule in the late 1990s and early 2000s, our results may provide a way to link these older and the newer results on the topic.
When more data from the recent period of full inflation targeting become available, it will be interesting to observe whether the estimated coefficients on inflation and output variables would have changed. We leave this for future work.
Variables.
Descriptive statistics.
Our sample starts from 2004, as inflation had decelerated close to 10% by that time. At the same time, our current data sample contains several different monetary and exchange rate policy regimes, which allows us to search for breaks.
The majority of empirical studies include policy smoothing in the estimated policy rules. Examples of these include Clarida et al. (1998), who estimate such a rule for large developed countries, Mehrotra and SánchezFung (2011) for 20 emerging countries, as well as Vdovichenko and Voronina (2006) and Esanov et al. (2005) for Russia.
The level of the policy rate is increased to match the refinancing rate in February 2011, so that only true policy changes affect the interest rate variable.
For a robustness check, a HodrickPrescott (HP)filtered inflation deviation series is also considered. However, there is no significant difference between using the official inflation target or the HodrickPrescott filtering to determine the inflation rate trend.
HP filtering is a standard method for removing trend and calculating the output gap. However, the detrendedvalues may be unreliable at the beginning and the end of the data sample. In calculating the detrended series, we have used data starting from January 1999, when available. To make the rules fully operational in practice, we also estimated the rules using deviation series (output gap, exchange rate gaps, and oil price gap), where the average value over the previous three years is used instead of the HPfiltered trend. The main findings do not differ between the different detrending methods. The estimation results are available upon request.
In 2017, the monthly GDP estimate has not been available at the time of the policy decisions, because of Rosstat's GDP data revisions. The estimates for March – July 2017 were published in August 2017, but the values for January and February were still missing. Therefore, for the real output growth in 2017, we use the growth in the Output Index for Key Economic Activities published by Rosstat. The correlation between the two series for the common sample of 2012–2016 is 0.94.
The augmented DickeyFuller (ADF) unit root test cannot reject the null hypothesis of a unit root in the interest rate variable, but the KwiatkowskiPhillipsSchmidtShin (KPSS) test does not reject the null for stationarity either. All other variables are stationary at least at the 10% significance level based on the ADF test.
We test the possible breaks for the monetary policy rules estimated from January 2004 to August 2017. In the estimations, we let the first possible breakpoint be June 2006 and the last one March 2015, allowing 31 observations in the subsamples before/after the breakpoint. The detailed breakpoint estimation results are available upon request.