Sergey Drobyshevsky

Analysis of the Bank of Russia information policy

The article investigates the Bank of Russia information policy using a new approach to measuring information effects on Russian data, including the analysis of the tonality of news reports, as well as internet users’ queries on Google. The efficiency of regulator’s information signals is studied using EGARCH-, VAR-models, as well as nonparametric tests. The authors conclude that the regulator communicates effectively in terms of the predictability of interest rate policy, the degree to which information signals affect the money and foreign exchange markets.The article investigates the Bank of Russia information policy using a new approach to measuring information effects on Russian data, including the analysis of the tonality of news reports, as well as internet users’ queries on Google. The efficiency of regulator’s information signals is studied using EGARCH-, VAR-models, as well as nonparametric tests. The authors conclude that the regulator communicates effectively in terms of the predictability of interest rate policy, the degree to which information signals affect the money and foreign exchange markets.

Russian Economy as the Hostage of High Oil Prices

This paper is about the bane of the Russian economy: rich oil and gas reserves, which hamper the implementation of structural economic reforms. Oil industry forms the backbone of the Russian economy playing a major role in ensuring revenues of the government budget and the country’s favorable trade balance.

Fiscal and Monetary Policy

For 25 years since the start of market reforms, Russian progress in fiscal (budgetary) and monetary policy in the direction of developed countries has been significant. Russia has created a modern tax system, institutional mechanisms for administering revenues from the export of oil, an expenditure management system and a system of fiscal federalism. It has provided a high degree of independence to the central bank (the Bank of Russia), transitioning to an inflation-targeting regime and a floating exchange rate. In this chapter, we aim to explain how fiscal and monetary policy has evolved over the course of the post-Soviet history of Russia, which problems have been addressed by the Russian government by means of fiscal and monetary instruments and which ones remain and how they should be addressed. Among the remaining challenges, perhaps the most important one is the continued lack of “coordination” or, more precisely, the lack of mutual regard between fiscal and monetary policies in Russia. This has militated against macroeconomic stability and led to recurring economic crises (or otherwise complicated the economy’s exit from these crises).

Macroeconomic Projections for 2017-2019: A Growth of 1.0-1.5%

The results of H1 2017 on the one hand support the previous assumptions that the Russian economy is entering a growth phase, and on the other hand provide evidence of elevated uncertainty regarding the terms and prospects of economic development in the future. We expect that key macroeconomic indicators will be positive in the next 2.5 years, as well as the inflation target will be achieved. However, extremely low economic growth rates coupled with a tenuous external environment are posing high risk of loss of federal budget revenues.

A View on Russian Economy Mid-Term Perspectives

We use to consider Russia as a commodity state whose welfare was mainly based on extraction and export of hydrocarbons. Well, Russia has one of the biggest oil and natural gas endowments, virtually dominates at the European crude oil and natural gas markets and actively builds up export of oil and gas to China South East Asia. Export of oil and gas accounts for 2/3 of exports, and taxes from those industries provide more than 50% of federal budget revenues. But, the world is changing, traditional assumptions are no longer valid, and the oil and gas sector is not a key driver of Russian economic growth anymore.

Domestic Monetary Policy and World Oil Prices

In 2000 and 2001 Russia faced a puzzle: high world oil prices, while ensuring GDP growth and strong fiscal balance, generated serious problems for domestic monetary and exchange rate policies. The Central Bank was forced to buy excess foreign exchange supply on the market, thereby paving the way for monetary expansion and inflation. On the other hand, the Central Banks rejection of rouble interventions in the forex market would have resulted in nominal appreciation of the rouble. In either case the outcome is fast real appreciation of the rouble, deterioration of the current account and slowdown of the economy. This article attempts to provide grounds for optimal monetary policy choice within the framework of a theoretical model of an open economy, which is similar to that of Russia in 2000 and 2001.

Modelling Spot Rate Process in the Russian Treasury Bills Market

The paper deals with modelling of spot rate process in the market for government securities in transitional economy. The case of the Russian Treasury bills market is taken as an example. We use three approaches to estimation of parameters of spot rate stochastic process: AR-GARCH time series models, GMM estimates and stochastic volatility models (QML estimates and Kalman filter). The most general conclusion is that pattern of spot rate process in transitional economy can be nested in existing theoretical model of term structure of interest rates. Estimated parameters of the spot rate process indicate that the Russian market for government securities by its features is closer to the European financial markets compared to the market for US Treasury bills. This conclusion is supported by estimates of parameters of the GKO spot rate stochastic process using both the GMM and QML estimates of spot rate nonlinear models. The Cox-Ingersoll-Ross 1985 model of term structure of interest rates is the most adequate for the Russian GKO market. The behaviour of the term structure of GKO yields in 1994 through 1998 did not contradict to theoretical conclusions from the model; analytical yield curves have satisfactory accuracy of approximation of actual GKO yield curves. The spot rate stochastic process is mean-reverting, but its variance although being stochastic does not exhibit mean-reverting property (according to Kalman filter estimates). The stochastic nature of spot rate volatility origins from different responses to good and bad news and a proportion to current spot rate level (but less than one by one).