Research

Working papers

"External Adjustment in Commodity Exporting Countries During Energy Price Downturns", with Anna Burova and Alexander Reentovich.

Recent examples of energy price downturns did not alter trade surpluses in commodity exporting countries, as both exports and imports decreased in equal measures on average. Economic theory contends that such developments may indicate that the changes observed in energy prices are perceived as permanent by the market. We believe that this is a feasible interpretation that is in line with the recent evidence of the financialisation of oil markets (i.e., the situation in which expected supply and demand developments are immediately incorporated into prices, while transitory developments are filtered out by well-informed and proactive market participants).

"Exploring the Conjunction Between the Structures of Deposit and Credit Markets in the Digital Economy under Information Asymmetries", with Elena Deryugina and Andrey Sinyakov.

Customer data is particularly valuable in the digital economy. Customer transactions monitored by banks, payment systems, and retail platforms are a useful source of information in assessing potential borrowers’ credit risk. Thus, the dominant player in a payment or deposit market, behaving strategically, may influence outcomes in the loan market. In this paper, we discuss these effects using a game-theoretic model. Our results indicate that information asymmetries allow the dominant player to increase its profits at the expense of the profits gained by other players. Interestingly, in certain environments, the dominant bank may find it optimal to limit the availability of loans to the risky borrowers among its clients while increasing availability to riskless borrowers.

"Measuring Market Liquidity and Liquidity Mismatches across Sectors", with Artur Akhmetov, Anna Burova and Natalia Makhankova.

We offer tools for measuring, monitoring and analysing the liquidity of financial markets in the context of various liquidity aspects. The liquidity mismatch concept makes it possible to assess how liquidity risk acceptance varies across economic sectors. We calculate liquidity indices – that is, liquidity mismatch indicators, and conduct a comparative analysis of the degree of liquidity risk acceptance by various sectors of the Russian economy. The values of liquidity indices in the household sector vary significantly across countries, depending on the degree of population involvement in the stock market.  We use the proposed tools to assess the development of financial market segments in Russia and conduct cross-country comparisons of the degree of liquidity of capital markets. Higher liquidity of financial markets is associated with a higher development of these markets; however, this is fraught with liquidity risks that may lead to financial losses.  Considering the concept of liquidity in various aspects, we expand the discussion of the availability and development of long-term investment financing in Russia.

"Macro-financial linkages: the role of liquidity dependence", with Anna Rozhkova and Sergei Seleznev.

We estimate a panel Bayesian vector autoregression model for a cross-section of seven advanced European economies and produce out-of-sample forecasts of GDP conditionally on observed developments of interest rates and credit. We show that by using a smooth transition version of the model and allowing the parameters to vary across economies conditionally on their liquidity dependence it is possible to improve the forecasts’ accuracy. We conclude that degree of liquidity dependence is likely to be among the important predictors of heterogeneity in macro-financial linkages across countries.

Published articles

"A Feasible Approach to Projecting Household Demand for the Digital Ruble in Russia", with Vadim Grishchenko and Sergei Seleznev. Borsa Istanbul Review, in press

We estimated a model of households’ usage of alternative payment instruments (cash and bank cards) using a new dataset from a survey of Russian households. In our modelling set-up, households’ preferences are determined by the instruments’ perceived attributes and hence their choice regarding payment methods depends on the differences across instruments in these attributes. The results indicate a statistically significant sensitivity of consumer choice to the perceived attributes. We employ the estimated model to evaluate the demand for CBDC depending on its expected design and consumers’ perception of it. We discuss several illustrative projections to demonstrate the application of the tool developed. The predicted utilisation of CBDC varies considerably depending on the percieved attributes, although under the conservative assumptions, the projected use of CBDC in household transactions is limited.

"Banks’ Interest Rate Setting and Transitions between Liquidity Surplus and Deficit", with Tatiana Grishina. SN Business & Economics, 3, 216 (2023)

Assuming that a central bank is successful in steering money market interest rates, commercial banks’ loan rate setting behaviour is not expected to change during a transition between liquidity surplus and deficit. However, this logic does not hold if the interest rates for the lending and borrowing activities of an individual bank on the money market do not coincide. In this environment, it may be appropriate to adjust the loan rates when a bank transitions between liquidity surplus and deficit (i.e. switches between the benchmark money market rates). This strategy is fundamentally different from linking the loan rates to the average cost of funding (i.e. the average between retail and wholesale funding rates). The magnitude of such loan rate adjustment is limited by the (usually moderate) spread between the funding and investment money market rates. 

"Incorporating Financial Development Indicators Into Early Warning Systems", with Stas Tatarintsev, The Journal of Economic Asymmetries, Volume 27, June 2023, e00284

We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators (e.g. levels of credit to GDP ratio) in addition to conventional imbalances measures (e.g. credit gaps). The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system.

"Measuring Heterogeneity in Banks’ Interest Rate Setting in Russia", with Anna Burova, Svetlana Popova, Andrey Sinyakov and Yulia Ushakova, Emerging Markets Finance and Trade, Volume 58, 2022, pages 4103-4119

We use credit registry data on all corporate loans issued by Russian banks since 2017 to decompose bank interest spreads into a common factor, borrower- and lender-specific components. We find that the variation in loan rates associated with lender-specific factors (heterogeneity of banks) and borrower-specific factors (heterogeneity of borrowers) is substantial. We use the bank-specific components identified to measure the fragmentation of the corporate credit market in Russia. The results indicate that heterogeneity in banks’ interest rate setting is high and increased in the early stage of the pandemic. Finally, our results suggest that banks tightened non-interest loan conditions during the pandemic

"An Empirical Behavioral Model of Households’ Deposit Dollarization", with Ramis Khabibullin, Journal of Economic Interaction and Coordination, 17, pages 827–847 (2022)

We use the behavioral concept to endogenously model the evolution of the link between households’ deposit dollarization and exchange rate developments in Russia. We estimate the model empirically and show that the reaction of households to exchange rate appreciation weakens when exchange rate developments become more volatile. The proposed model outperforms the contemporary nonlinear time series models in forecasting the changes in dollarization during the Bank of Russia’s transition to a flexible exchange rate regime.

"Forecasting the implications of foreign exchange reserve accumulation with a microsimulation model", with Ramis Khabibullin and Sergei Seleznev,  Journal of  Simulation, Volume 16 Issue 3 (2022), pp. 298-311

We develop a stock-flow-consistent microsimulation model that comprises a realistic mechanism  of money creation and parametrize it to fit actually observed data. The model is used to make  out-of-sample projections of broad money and credit developments under the commencement/termination of foreign reserve accumulation by the Bank of Russia. We use direct forecasts from the agent - based model as well as the two-step approach, which implies the use of artificial data to pre-train the Bayesian vector autoregression model. We conclude that the suggested approach is competitive in forecasting and  yields promising results.

"Money Creation and Banks’ Interest Rate Setting",  Journal of Financial Economic Policy, Vol. 14 No. 2 (2022), pp. 141-151.

The conventional view on banks’ interest rate-setting strategy implies that the decisions on the deposit and loan rates may be made independently. An alternative approach is based on the assumption of a bank’s predetermined liabilities structure. Such an assumption requires that the availability of deposits automatically increases (decreases) when more (fewer) loans are granted. Arguably, that they may be partially true considering that deposits are created via lending. We set up a microsimulation model and show that in certain environments it may be beneficial for large banks to incorporate information on the retail funding costs into the lending rate-setting decision.

"The credit cycle and measurement of the natural rate of interest", with Elena Deryugina and Maria Guseva. Journal of Central Banking Theory and Practice, 2022, 1, pp. 87-104

We conduct a Monte Carlo experiment using an ad-hoc New Keynesian model and a tractable agent-based model to generate artificial credit cycle episodes. We show that fluctuations in the implicit measures of the natural rate of interest obtained using a conventional trivariate Kalman filter on these artificial datasets occur in the vicinity of credit cycle peaks without any underlying changes in fundamentals (that is the agents’ type or their behaviour). The empirical analysis confirms that the measures of the natural interest rate tend to increase prior to a credit cycle peak and decrease afterwards. We conclude that a decline in the estimated natural rates of interest does not necessarily indicate changes in macroeconomic fundamentals. Instead, it may simply reflect the innate properties of the measurement technique in the vicinity of credit cycle peaks

"Explaining the Lead-Lag Pattern in the Money-Inflation Relationship: A Microsimulation Approach", with Elena Deryugina, Journal of  Evolutionary Economics, 31, pages 1113–1128 (2021)

We set up an agent-based model where the parameters of the firms’ pricing heuristics are determined via evolutionary learning. We argue that there are several key ingredients that result in the emergence of the lead-lag pattern in the money growth-inflation relationship. Firstly, the realistic representation of the money creation through lending mechanism is essential. Secondly, there should be considerable heterogeneity in the distribution of newly created deposits and in the associated changes in demand on the individual firm level.

"Exploring the Interplay Between Early Warning Systems’ Usefulness and Basel III Regulation", with Elena Deryugina and Maria Guseva. Risk Assessment and Financial Regulation in Emerging Markets' Banking (2021) pp 277-286

We analyse the ability of credit gap measures to predict banking crises by estimating the usefulness measure conditionally on policymaker's preferences. The results show that the signals based on the credit gap indicators are most useful when the policymaker’s preferences regarding Type I and Type II errors are approximately equal. However, according to the current consensus, the preferences to avoid missing a crisis are higher than issuing a false signal. This means that the usefulness of the credit-gap-based early warning systems is likely to increase once the static Basel III regulative measures are implemented (assuming that their implementation results in lower financial crises’ costs).

"When are credit gap estimates reliable?", with Elena Deryugina and Anna Rozhkova, Economic Analysis and Policy, 67C (2020) pp. 221-238.

We evaluate the reliability of credit gap measures estimated over time samples of different lengths. We augment our empirical analysis (which turned out to be somewhat inconclusive) with Monte Carlo experiments. For this purpose we build an agent-based model that realistically reproduces credit cycles and use it to generate the artificial data set. We found that 12−15 years of available data is sufficient for the estimation of reliable credit gaps (i.e. the reliability of credit gap estimates will not improve substantially as more data are added to the sample).

"A note on observational equivalence of micro assumptions on macro level", Economics: The Open-Access, Open-Assessment E-Journal, 14 (2020-3): 1–15.

The author sets up a simplistic agent-based model where agents learn with reinforcement observing an incomplete set of variables. The model is employed to generate an artificial dataset that is used to estimate standard macro econometric models. The author shows that the results are qualitatively indistinguishable (in terms of the signs and significances of the coefficients and impulse-responses) from the results obtained with a dataset that emerges in a genuinely rational system.

"Disinflation and Reliability of Underlying Inflation Measures", with Elena Deryugina, Central European Journal of Economic Modelling and Econometrics, Volume 12 Issue 1 / 2020: 91-111.

We estimated a Non-Stationary Dynamic Factor model and used it to generate artificial episodes of disinflation (permanent change in the mean inflation rate). These datasets were used to test the performance of alternative underlying inflation measures. We found that the benchmark underlying inflation measures (based on unobserved trend extraction) are more severely affected by disinflation than the alternative simpler methods (based on exclusion or reweighting approaches). Alternatively, a Non-Stationary Dynamic Factor model may be employed for extraction of the unobserved trend to be used as an underlying inflation measure.

"A case for leaning against the wind in a commodity-exporting economy", with Irina Kozlovtceva, Andrey Sinyakov and Stas Tatarintsev, International Economics, vol. 164(C), 2020, pages 86-114.

We report the empirical evidence of procyclicality (regarding the credit developments) of interest rate setting in a group of inflation targeting emerging market economies: monetary policy eases in response to a higher price of an exported commodity while real credit grows. Counterfactual exercises show that in some countries endogenous monetary policy responses to commodity shocks explain a substantial portion of the real credit growth. We also conduct a theoretical analysis and compare stabilisation properties (while accounting for financial stability risks) of the inflation-targeting policy rule and the” leaning against the wind” policy rules. For this purpose, we use the DSGE model with financial frictions and a banking sector calibrated to the Russian economy and measure the efficiency of policy results with different sensitivity to credit developments (“leaning against the wind” rules) under different variances of oil price shocks. The results show that when commodity price volatility is relatively high, leaning against the wind outperforms pure inflation targeting.

"Do sterilized foreign exchange interventions create money?", Journal of Asian Economics, Volume 62, June 2019, Pages 1-16.

The growth of official foreign reserves in emerging Asian countries over recent decades has been extensive but its effects on the money market appear to be well sterilized in that decreases in interest rates or acceleration of credit growth have not been registered. We analyze the effect of foreign exchange intervention on components of the banking system’s balance sheet for 19 emerging economies that pursued an independent interest rate policy and did not maintain an exchange rate peg. The sample includes six Asian countries (India, Indonesia, Korea, Malaysia, the Philippines, and Thailand). We apply a vector autoregressive technique to quarterly data for the period 2001Q4 to 2016Q1. For the sample as a whole, we find that money stock tends to expand in response to an increase in the foreign reserves of the central bank. For the Asian countries in particular, we conclude that external transactions have contributed to money growth acceleration despite sterilization that succeeded in stabilizing interest rates.

"Determination of the Current Phase of the Credit Cycle in Emerging Markets", with Elena Deryugina, Russian Journal of Money and Finance, 78(2), June 2019, pp. 28–42.

We test the ability of early warning indicators that appear in the literature to predict credit cycle peaks in a cross-section of emerging markets, verifying our findings by cross-sectional validation. Our results confirm that the standard credit gap indicator performs satisfactorily. In fact, we find that, in emerging market economies, it seems rather difficult to outperform this indicator by means of augmented multivariate models. Nevertheless, we have found that the robustness of real-time credit cycle determination may potentially be improved (although with a risk of overfitting the data) by simultaneously monitoring GDP growth, banks’ non-core liabilities, the financial sector’s value added and (to a lesser extent) the change in the debt service ratio.

"The role of regional and sectoral factors in Russian inflation developments", with Elena Deryugina, Natalia Karlova and Anna Tsvetkova, Economic Change and Restructuring, Springer, November 2019, Volume 52, Issue 4, pp 453–474.

"What do aggregate saving rates (not) show?", with Alexey N. Ponomarenko, Economics: The Open-Access, Open-Assessment E-Journal, 12 (2018-13): 1–19, March 2018.

Aggregate saving indicator does not directly reflect changes in microeconomic behaviour of individuals. It is a residual concept defined as the difference between aggregate income and consumption. It measures the change in net worth which in a closed economy may only be generated by production of capital goods. Using an agent-based model we show that shocks unrelated to structural changes in households’ behaviour may generate positively correlated fluctuations in aggregate saving rate, productivity growth and lending. Meanwhile, genuine increase in average individual propensity to save is not necessarily associated with higher aggregate saving rate.

"Evaluating underlying inflation measures for Russia", with Elena Deryugina, Andrey Sinyakov and Constantine Sorokin, Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 11(2), pages 124-145, May 2018.