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on Confederation of Independent States |
| By: | Svetlana Popova (Bank of Russia, HSE University, Russian Federation); Natalia Turdyeva (Bank of Russia, Russian Federation) |
| Abstract: | This paper analyses how Russian banks incorporate environmental and climate factors into corporate loan pricing. Our findings suggest that, in the absence of any regulation of †green†finance in Russia, banks do not take into account the impact of borrowers on the environment when setting interest rates. While Russian banks impose markups on interest rates for loans to more polluting firms, those markups are economically insignificant. The largest markups are observed among large private domestic banks, while state-owned banks impose the lowest. Specifically, the interest rate on loans from large private domestic banks to highly-polluting firms is only 0.04–0.07 percentage points higher than that for ’green’ firms. These minimal differences in loan pricing indicate that under the current regulations, Russian banks do not significantly differentiate lending terms between ’green’ companies and others. We examine the heterogeneity of the price setting across different bank groups — state- owned, foreign-owned, or privately-held banks — considering the intensity of CO2 emissions at the industry and firm level, as well as firms’ export status. For the analysis, we exploit unique monthly loan-level data provided by the Central Bank of Russia’s credit register, covering the period from 2017 to 2022, along with firm-level data on environmental fees for pollution of air, water and waste disposal. |
| Keywords: | Corporate loan pricing, credit register, Russian banks, loan-level data, †brown†companies, †green†companies, environmental fees, pollution, state-owned banks, export |
| JEL: | G21 G28 Q56 D22 E43 L51 O13 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps143 |
| By: | Denis Krylov (Bank of Russia, Russian Federation); Nikita Pakhmutov (Higher School of Economics, Russian Federation) |
| Abstract: | The past two decades have seen a rise in China’s share of global trade. Its role has become particularly prominent in Russia’s foreign economic relations after 2022, due to the reorientation of trade flows from Europe and the United States toward China and other Asian countries. This study aims to assess the impact of the changes in foreign trade on Russian business cycles. Specifically, we intend to verify a hypothesis about a greater degree of synchronisation in the business cycles of China and Russia since 2022, driven by the higher volumes of bilateral trade. We use GVAR with time-varying weights as the method of our analysis. The weights are the shares of the countries that generate value-added foreign trade. We measure the degree of synchronisation between Russia and China based on an analysis of Russia's output impulse responses to simulated positive output shocks for China, taking into account the secondary effects of Asia, the US and Europe. According to our research, the response of Russia's output to positive shock of China’s local output in 2023 was almost double that in 2019. If we simulate a global economic crisis in which a shock in China triggers a proportional drop in the output of other countries, particularly the US and the EU, we find that the degree of synchronisation between 2019 and 2023 remains unchanged. Put differently, the response of Russia’s output to shock of output in China is unchanged under this scenario. Our results can be used to adjust macroeconomic models to the new environment for the Russian economy and thus improve predictive capabilities and analytics. |
| Keywords: | Russia, China, international business cycles, trade relations, OECD TiVA, Global VAR |
| JEL: | C32 E32 F15 F44 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps150 |
| By: | Jacob Funk Kirkegaard (Peterson Institute for International Economics) |
| Abstract: | Despite the increasingly direct military threat from Russia and a weakening US commitment to the North Atlantic Treaty Organization (NATO), the European Union's 27 member states have proven unwilling to harness their union to provide a common defense. Instead, EU members have responded individually, based on their own national interests and circumstances, such as their geographic proximity to Russia and levels of government debt. Failure to act collectively represents a wasted opportunity with potentially far-reaching and negative implications for the prospects of any further meaningful EU institutional integration. This Policy Brief analyzes the drivers of rearmament, especially military aid to Ukraine, and the ways in which such aid is increasingly being provided by different "coalitions of the willing" consisting of subsets of EU members and other countries, working with the Ukrainian military industrial sector. Kirkegaard argues that this approach will likely reduce the European Union to a peripheral role in providing for the continent's military defense and national security. Instead, the European Union's principal role will be that of a financier, limited to providing financial support for Ukraine, increasing sanctions pressure on Russia, overseeing Kyiv's accession to the European Union, and trying to carve out a coordinating role in EU defense-related research and development. Rather than the European Union as a single institution, subsets of EU members together with nonmembers will drive European rearmament and the establishment of a largely independent long-term military deterrent to Russia. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:iie:pbrief:pb26-1 |
| By: | Evguenia Bessonova (Bank of Russia, HSE University, Russian Federation); Irina Denisova (NES, MSU, Russian Federation); Nadezhda Ivanova (Bank of Russia, RANEPA, Russian Federation); Alexandra Moskaleva (Bank of Russia, MSU, Russian Federation) |
| Abstract: | We utilise data from the biennial longitudinal survey Financial Behaviour of Russian Households (waves 2013–2022) to examine the saving patterns across Russian households. We find that female-headed households are less likely to save – this holds for all age groups and is especially pronounced among women aged over 40. Furthermore, single-person households in Russia are characterised by a lower probability of saving compared to other types of households – this finding is very consistent but differs from the estimates obtained for other countries. Since the demographic trends demonstrate a rising percentage of single- person households, behaviour patterns in this group may increasingly determine the saving behaviour of the population in the long term. At the same time, our analysis shows that the impact of individual time and risk preferences such as a saving horizon, future discounting and risk aversion on saving behaviour in the group of single-person households differs from the estimated effects for other types of households. Thus, standard policies to encourage savings may become less effective in the near future because they will have to deal with a large group of the population with a short planning horizon and high future discounting. |
| Keywords: | demographic trends, savings, single households, female-headed households |
| JEL: | D14 J10 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps135 |
| By: | Denis Krylov (Bank of Russia, Russian Federation) |
| Abstract: | Movements in food prices have a major input in consumer price index and, thus, a significant impact on the living standards. Given the increased volatility of world food prices, it is essential that we understand the impact of this external driver of inflation on domestic price trends in order to produce a more accurate forecast of inflation and conduct a more efficient monetary policy. This work presents a VARX model applied to data from 2003 to 2021. Statistically significant impact of world food prices on domestic consumer and producer food prices in Russia was observed in 2003-2014, both at nation level and across its regions. After 2014, when there was a transition to a floating exchange rate, inflation targeting policy, accelerated development of import-substituting agricultural production and the Russian government employment of a more active trade policy in agriculture and food products, the average pass- through effect declined materially and is no longer statistically significant. The overall pass-through effect is greater in the case of rising world prices compared to decreasing world prices, while no statistically significant differences are found among regions. Meanwhile, the pass-through effect of world food prices on internal producer prices exhibits a significant regional heterogeneity. |
| Keywords: | world food prices, pass-through effect, Russian regions, consumer prices, producer prices, vector autoregression |
| JEL: | C32 E31 F42 R11 |
| Date: | 2024–02 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps126 |
| By: | Evguenia Bessonova (Bank of Russia, HSE University, Russian Federation); Svetlana Popova (Bank of Russia, Russian Federation); Konstantin Styrin (Bank of Russia, NES, Russian Federation) |
| Abstract: | We study the effect of the participation in a subsidized lending program on economic outcomes of small and medium-sized enterprises (SMEs) in Russia. The estimated effect on sales and employment is statistically and economically significant and robust. The annual growth of sales increases by 10.7-11.4 p.p. and of employment by 4-7 p.p. The effect on profits is sizeable but not robust, being very sensitive to the way the control sub-sample is constructed. |
| Keywords: | Firm dynamics; Small and medium-sized enterprises; Subsidized lending; Loan guarantee programs |
| JEL: | D22 G38 L25 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps140 |
| By: | Alexander Eliseev (Bank of Russia, Russian Federation) |
| Abstract: | This study focuses on improving the accuracy of nowcasting in DSGE models. We extend one of the general equilibrium models of the Russian economy by incorporating mixed-frequency data. Specifically, we introduce an equation that links a panel of non-modelled high-frequency indicators to observable variables, whose dynamics are determined directly by the model. The out-of-sample pseudo-real-time forecasting procedure demonstrates that incorporating these additional variables enhances the accuracy of Russian GDP nowcasting using the DSGE model. This improvement makes the model’s forecasts comparable in accuracy to state-of-the-art econometric models and superior to univariate models. We also investigate the extent to which fluctuations in high-frequency indicators are associated with macroeconomic factors, as well as the economic shocks driving the explained portion of these fluctuations. While the structural interpretation of non-modelled variables is a potential strength of the model, caution is warranted due to the econometric methodology employed. |
| Keywords: | nowcasting, GDP, DSGE model, mixed frequency data, pseudo real-time forecasting |
| JEL: | C53 C82 E32 E37 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps145 |
| By: | Anna Burova (Bank of Russia, Russian Federation); Kristina Virovets (Bank of Russia, Russian Federation); Denis Koshelev (Bank of Russia, Russian Federation); Ekaterina Petreneva (Bank of Russia, Russian Federation); Alexey Ponomarenko (Bank of Russia, Russian Federation) |
| Abstract: | The analysis of banks referred to as community banks in the international literature is a widespread application problem within the scope of regulators’ concerns. Such banks are characterised by closer relationships with borrowers (relationship banking), as opposed to a formalised and automated approach (transactional banking). There is no consensus on the method for defining community banks. We presented an algorithm for determining community banks, taking into account the specifics of the Russian banking sector and revealed the following. A community bank is a profitable bank, in the funding structure of which half of the funds are funds from individuals, and in the allocated funds the share of the corporate loan portfolio predominates. Community banks have a balanced funding structure. Profitability of placement is consistently higher than the cost of funding for funds from legal entities, but has a very small differential for funds from individuals. The main factor in the growth of ROA for a community bank will most likely be an increase in net interest income, the main factor in decreasing ROA is the additional formation of reserves for corporate loans (at the same time, the loan portfolio of the community bank is of relatively high quality). Although the total loan portfolio of community banks is relatively small, their operations are deemed crucial in certain segments of the economy. The reason is that such banks possess a number of important features. The main purpose of our study is to explore and outline the differences between community banks and other (larger) banks. Identifying such differences is essential to understand the degree of heterogeneity in the banking sector. First, community banks are ready to deal with small borrowers and specialise in niche markets and industries. Approximately one third of the volume of corporate loans issued by a community bank are loans to small borrowers. Second, they are open to working with financial instruments of limited demand and/or customising products to meet the needs of a small group of clients. In addition, community banks are willing to handle loans that are limited in size and are not massmarket, and to take non-standard approaches to setting interest rates. The bulk of corporate loans issued by community banks will most likely go to companies that also have loans from other banks that are not classified as community. In addition, community banks are ready to work with medium-sized (and not massive) loans and approach setting rates in a customised manner. The community bank is active in the short-term corporate lending segment. At the same time, in lending to both medium/large and small borrowers, loans at a fixed rate and issuance under credit line agreements (CL) are more likely to prevail. In general, community banks show similar results relative to other groups. The findings rather indicate the stable position of community banks in the corporate lending market. |
| Keywords: | community banks, lending strategy, relationship lending, transactional lending |
| JEL: | G21 G32 D40 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps139 |
| By: | Шамар Бауыржан // Shamar Bauyrzhan (National Bank of Kazakhstan) |
| Abstract: | В данном исследовании приводится базовый расчет премии за срочность исходя из динамики структуры доходностей кривой доходности казахстанских ГЦБ. Долгосрочная нейтральная базовая ставка в Казахстане согласно макроэкономическому опросу Национального Банка существенно отличается от форвардной кривой на длинном конце. Эта разница свидетельствует о том, что на рынке есть иные факторы, помимо предпочтения ликвидности, которые влияют на премию за срочность. Хотя результаты Макроэкономического опроса Национального Банка могут быть использованы для выделения компоненты премии за срочность из долгосрочной доходности, сам опрос проводится 8 раз в год и данные опроса могут быть смещены. Подход, который приводится в данном исследовании предполагает выделение премии за срочность только из данных о доходностях ГЦБ при помощи методологии ACM и строится на сугубо статистических техниках, не требуя дополнительных предпосылок. Такой подход позволяет разделить долгосрочные доходности на нейтральную долгосрочную номинальную базовую ставку и премию за срочность. В дальнейшем это позволит делать дополнительные предположения о природе поведения долгосрочных доходностей и влиянии на них инфляционных рисков. В дополнение на основании этого расчета была получена оценка долгосрочной нейтральной номинальной ставки, основываясь только на рыночных данных о кривой доходности в диапазоне 9-9, 2%. |
| Keywords: | кривая доходности, премия за срочность, денежно-кредитная политика, инфляционная риск премия, yield curve, term premium, monetary policy, inflation risk premium |
| JEL: | G12 E43 E44 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:aob:wpaper:66 |
| By: | Anna Burova (Bank of Russia, Russian Federation); Denis Koshelev (Bank of Russia, Russian Federation); Irina Kozlovtceva (Bank of Russia, Russian Federation) |
| Abstract: | Credit lines are an important source of financing for economic activities in different countries, including Russia. It is important to identify the factors affecting the utilisation of contingent loans in order to better understand the tendencies on the financial market and to identify possible risks for all participants in the loan market. We use credit registry data on all the credit on banks’ balance sheets as of the beginning of 2017. We split our study into three parts: credit lines which have reached their limits, credit lines with the full limit still available and credit lines in the middle state. For fully used credit lines, we show that a large share of them appear similar to regular loans (the company immediately uses the entire available limit and repays the funds when the loan matures). For two other groups we identify factors affecting the timing of the first credit line draw-down and the utilisation rate. For several factors we show that their impact coincides with what has been shown in other studies: dummy variable on the credit line issued by the company’s main bank (credit lines obtained from the main bank are used more intensively), the age of credit line (the older the credit line, the less the utilisation rate), etc. Other variables in this study show the opposite effect compared to other papers. For example, the length of relationship with the bank in earlier studies negatively affects the utilisation rate of the credit line, while we can see that this factor has a positive impact in this study. We also show that lines with the fixed interest rate are used more intensively than those with floating rates. In cases of non-revolving credit lines this result is robust across all time sub-samples, both during tightening and easing of credit conditions. These findings may be significant for understanding the credit line utilisation process for the financial market participants as well as for monetary and prudential policies. |
| Keywords: | Corporate credit, credit line utilisation, credit registry, micro-level data, bank lending, Russia |
| JEL: | G21 G32 D22 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps158 |
| By: | Alexandra Glazova (Bank of Russia, Russian Federation); Maxim Nevalennyi (Bank of Russia, Russian Federation); Andrey Sinyakov (Bank of Russia, Russian Federation) |
| Abstract: | This article presents a diagrammatic model of a small open economy. The dynamics of this graphical model are illustrated using impulse responses from the corresponding formal semi- structural model (Quarterly Projection Model, QPM). This graphical model reflects the modern understanding of how a fiat monetary economy and the current global financial system operate.1 It describes the specifics of monetary policy (MP) responses to supply and demand shocks under inflation targeting and the importance of anchoring inflation expectations. It explicitly considers the foreign exchange market (taking into account its potential imperfections) and demonstrates the role of the exchange rate in the transmission of MP. The model helps to link the global financial (credit) cycle to accumulating risks to financial stability, which create constraints on MP (‘dilemma, not trilemma’) and require the use of additional policy instruments. In our view, the presented diagrammatic model is a simpler version of the graphical model for analysing monetary policy in a small open economy than that proposed by Basu and Gopinath (2024). Therefore, it is suitable for less experienced readers—undergraduate students. The model not only accounts for the constraints facing monetary policy in a small open developing economy with developed financial markets but also allows for the analysis of extreme cases, like the closure of the financial account of the balance of payments and the associated changes in monetary policy transmission. Consequently, the model can be used to explain the rationale behind the Bank of Russia’s monetary policy decisions over the entire inflation targeting period. The authors provide a detailed analysis of the Bank of Russia’s decisions from 2022 onward using the model. |
| Keywords: | monetary policy, small open economy, foreign exchange market, inflation targeting, monetary policy dilemma, diagrammatic general equilibrium model, Quarterly Projection Model (QPM), Bank of Russia |
| JEL: | E58 F38 F41 G28 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps154 |
| By: | Alina Evstigneeva (Bank of Russia, Russian Federation); Yulia Shchadilova (Bank of Russia, Russian Federation) |
| Abstract: | Transparency is one of the key quantitative indicators of the quality of central bank communication. The more information a central bank releases about its policy, the more transparent its communication is considered to be. Globally, there are several popular indices to assess the transparency of communication. However, all of them fail to assess the transparency of central banks for the population. This paper is set to fill in this gap, which is especially important given the pivot of monetary authorities towards expanding communication with the general public. The BATI (Broader Audience Transparency Index) assesses 20 central banks in developed and developing countries in terms of the key functions of their public communication (information, education, accountability, and signalling). In total, the index has 40 criteria, of which three are punitive. They downgrade central bank assessments for redundant style, bureaucratic syntax, and contradictory signals, which may endanger dialogue with the public. When drafting the BATI criteria we incorporated the results of other researchers across various areas, i.e. monetary policy, government information policy in a general sense, marketing, brand management, and cognitive psychology. The BATI is based on indicators the value of which has been established in empirical studies or thoroughly founded in theoretical academic papers. When evaluating the index criteria, we employed both the standard method of expert assessment of communication with the help of lists (traditionally used to create transparency indices) and NLP and LLM methods for handling non-structured data. Specifically, 23 out of the 40 criteria of the index were defined using expert assessment, four – LLM models, and 13 – machine text analysis. The Bank of Canada, the Bank of England and the European Central Bank received the highest BATI scores among central banks for communication with the general public. The Bank of Russia is ranked fourth with 17.31 points out of 37. It belongs to the group of central banks that use advanced practices in communication with the public but have certain gaps in some communication functions. At the same time, the Bank of Russia has the highest score in audience education (tied with the US Federal Reserve System and the Reserve Bank of Australia). In general, the BATI index value is significantly higher in developed economies than in developing countries. This is consistent with the findings of studies on central bank transparency for professional audiences. The Bank of Russia is an exception among developing countries. It is closer to central banks in developed economies on almost all criteria of transparency for broader audience. The main academic novelty of this paper is the attempt to bridge the gap in terms of the absent instrument for assessing central bank efforts to enhance transparency for the general public. Our proposed BATI index assesses the extent of central bank efforts within each of the main communication functions and can help monetary authorities choose the options how to further develop their information policies. Moreover, our newly created instruments for automated handling of non-structured data also make a contribution to the literature. |
| Keywords: | monetary policy, communication, transparency, text analysis, LLM |
| JEL: | E52 E58 E71 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps136 |