DOI: 10.32609/j.ruje.11.144107

Authors: Maria S. Lymar, Henry I. Penikas

Abstract: The objective of the current work is to estimate to what extent support measures of the Bank of Russia and the Government of the Russian Federation promoted financial stability of banks and the financial market overall so to sustain lending economy-wide during the crisis periods of 2014, 2020, and 2022. These measures mutually assured the financial stability of the institutions and enabled them to extend lending within the economy for RUB 8 trillion in 2022 (~$100 billion, or 8%+ of the total loan book), of which Bank of Russia measures contributed to RUB 4.3 trillion of the total, the Government of Russia — to RUB 2.0 trillion, while the synergy was RUB 1.7 trillion.

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DOI: 10.32609/j.ruje.11.126000

Authors: Nwabisa Florence Ndzama

Abstract: We find that, while different models used to estimate the output gap in five major emerging economies show similar trends over time, they lead to different conclusions about how well the output gap can predict inflation. This suggests that the choice of model can significantly impact the conclusions drawn about the relationship between the output gap and inflation. The multivariate Hodrick–Prescott filter and the structural vector autoregressive model produce the smallest forecast errors in most cases among the four output gap models considered. We further find some indications of a better inflation forecasting ability of the output gap in countries with inflation targeting, suggesting that the improved transparency related to inflation targeting might support the inflation forecasting process.

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DOI: 10.32609/j.ruje.10.113578

Authors: Inna S. Lola, Dmitry G. Asoskov

Abstract: This study investigates the utility of business uncertainty indicators as predictive tools for forecasting economic activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding the dynamics of economic uncertainty and its impact on overall economic performance is of paramount importance. The study utilizes a comprehensive dataset based on the results of business tendency surveys in Russia, spanning the period from 2009 to the first half of 2024. Given the importance of uncertainty in shaping economic outcomes, the central research question of this study is: can uncertainty indicators predict business activity in Russia or not? To address this question, we compared two alternative approaches to calculating business uncertainty: the ex‑ante approach, which uses the business community’s assessments of future business trends to measure uncertainty as the dispersion of opinions expressed, and the ex‑post approach, which applies entrepreneurial assessments of both future and current trends to determine business uncertainty as the degree of deviation of entrepreneurial expectations from the real picture. National indicators and sectoral indicators were calculated for the mining and quarrying industry, manufacturing industry, construction, retail trade, wholesale trade and services. For most of the industries under consideration (except for the construction and service sector) and at the national level, the specifications of vector autoregression models that were effective for forecasting real indicators of economic activity, characterized by lower forecast errors compared to standard autoregressive models, were built. According to the results obtained, at the national level, when forecasting GDP, clear preference should be given to the ex‑post indicator.

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DOI: 10.3897/j.ruje.4.30163

Authors: Alexey Kudrin, Alexander Knobel

Abstract: This paper investigates the economic efficiency of Russian public expenditures in 2002–2016 by estimation of their multiplicative impact on the GDP level and economic growth. We use the empirical methodology based on Corsetti et al. (2012). We estimate a number of fiscal multipliers: on national security, law-enforcement activity, national defense, education, health care and sport and road infrastructure. For assessing the influence of budget structure on long-term economic growth rates, we estimate the SVAR model in which GDP growth is a structural variable. The research shows a positive influence of budgetary resources redistribution from non-productive government expenditures to productive ones on economic development.

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DOI: 10.1016/j.ruje.2016.04.002

Authors: Eugene Nivorozhkin, Giorgio Castagneto-Gissey

Abstract: This paper studies the dynamic relationship between returns in the Russian stock market and global equity markets in the aftermath of the 2014 Ukrainian crisis. We apply dynamic goodness-of-fit and bootstrapped regression approaches to study the behavior of global equity indices. Our results reveal a significant fall in the degree of synchronicity between the Russian and global equity returns after the crisis outbreak. The Russian stock market clearly decoupled from both developed and emerging markets, as shown by a 30–50% decline in returns correlation. In view of dramatic increase in synchronicity across the Russian sectoral stock indices after the sanctions were introduced, our results suggest that the economic sanctions imposed on Russia during that period have effectively isolated the Russian equity market from the rest of the world and triggered extensive portfolio outflows from the Russian market. As a result of the economic sanctions and the limited choice of investments in Russia, the decreased co-movement between the Russian and global equity returns is unlikely to provide investors with superior diversification opportunities, whilst the returns of the Russian market in the medium-term will likely continue to be predominately driven by idiosyncratic news.

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