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Data of Sectoral Financial Flows as a High-Frequency Indicator of Economic Activity
Russian Journal of Money and Finance. 2021. No. 80(2). P. 28–49.
Turdyeva N., Tsvetkova A., Movsesyan L., Porshakov A., Chernyadyev D.
In times of crisis, events are moving fast and standard macroeconomic statistics published with a lag cannot quite keep pace with the changing situation. During such periods, there is an increasing need to use high-frequency indicators that allow virtually real-time monitoring of economic activity. In many countries, this is achieved by using financial transaction data. In this paper, we present a methodology for the current analysis of sectoral financial flows in the Russian economy based on data from the Bank of Russia payment system. We use the information on the dynamics of average daily payments for each class of OKVED 2 (the Russian National Classifier of Economic Activities) to develop high-frequency indicators of economic activity, which have been published on the Bank of Russia website since April 2020. We also tentatively discuss the potential of financial transaction data in terms of improving the tools for short-term forecasting of business activity dynamics and solutions to other research problems.
Smirnov S. V., Вопросы экономики 2025 № 10 С. 131–154
The paper summarizes machine-learning (ML) methods most relevant to macroeconomics and assesses their performance in forecasting and nowcasting key macro indicators. Despite rapid methodological progress and a surge of publications over the past 25 years, gains in forecast accuracy with traditional statistical (economic, financial, and survey) data remain modest. ML models often outperform naïve and ...
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Makeeva N., Экономика и математические методы 2026 Т. 62 № 2 С. 58–72
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Bronitsky G., Population and Economics 2024 Vol. 8 No. 2 P. 133–154
Analysis of migration flows is crucial for understanding and forecasting social and economic trends. This paper presents an algorithm for obtaining migration estimates with minimal time delay (nowcasting) using Google Trends Index (GTI) search queries. The predictive power of the models is assessed across different periods, including one marked by the restrictions imposed due to ...
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Makeeva N., Stankevich I., Любайкин Н. С., Вопросы экономики 2024 № 3 С. 120–142
In this paper the following models are compared: restricted and unrestricted MIDAS-models (mixed data sampling models), MFBVAR-model (mixed frequency Bayesian vector autoregression), Linear model with regularization (MIDAS_L1-, MIDAS_L2- and MIDAS_PC-model) and dynamic factor model. The results are compared with classical autoregression as a benchmark. Production indices for different industries and indicators characterizing Russian GDP and ...
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The present study develops a methodology of business expectations index nowcasting with testing on data for the Russian economy as a whole and its regions. The methodology differs from the existing solutions in that it introduces a Bayesian averaging approach to define a set of search patterns for nowcasting and solves the issue of aggregation ...
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The paper investigates the application of Markov-Switching MIDAS (Mixed Data Sampling) models to nowcasting of Russian GDP and its components. Different methods to get the resulting nowcast based on nowcasts under different regimes are proposed: weighted by regime probabilities, most probable regime, and perfectly predicted regime nowcasts. The model obtained is compared with standard econometric ...
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This paper proposes a method for predicting migration based on search query data statistics using Google Trends Index (GTI). We improved the existing methodology in two directions: firstly, we proposed an approach for selecting key search queries and aggregating them based on various statistical criteria; secondly, we showed the importance of including in the migration ...
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The paper discusses the problem of nowcasting the current growth rates of Russian GDP and its components using quarterly data. The quality of restricted and unrestricted MIDAS models (models with mixed data), MIDAS model with L1 regularisation and MFBVAR model (Bayesian vector autoregression of mixed frequency) are compared. The results are compared with classical autoregression ...
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Bronitsky G., Vakulenko E., Демографическое обозрение 2022 Т. 9 № 3 С. 75–92
International migration statistics are published with a delay of up to several years. This prevents researchers from making timely analyses of migration flows. The article reviews a method for forecasting international migration flows based on search queries on the Internet using the example of flows from Russia to Germany during 2011-2020. Rosstat, German and OECD ...
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The article is devoted to the analysis of the impact of the coronacrisis on various segments of the population. The purpose is to identify the universal and local consequences of the pandemic, as well as the sources of resistance to new challenges. For the analysis we use data from a study by the FCTAS RAS, ...
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Zhemkov M., Деньги и кредит 2022 № 2 С. 79–104
This paper presents an approach to the estimation of monthly GDP growth in Russia using temporal disaggregation. This method represents a balanced view of the current economic situation that relies on a model framework and encompasses all economic sectors. The paper makes a meaningful contribution to the existing academic literature on the topic by combining ...
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Динамика инфляции выступает ключевым фактором макроэкономической и социальной устойчивости, непосредственно влияя на все структурные пропорции в экономике и на благосостояние населения. Это особенно заметно в периоды острых шоков и кризисов. В статье предпринята попытка осмыслить инфляционные последствия кризиса неэкономической природы, связанного с пандемией коронавируса. Глобальный характер этого кризиса, а также его влияние на все секторы ...
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Zhemkov M., International Economics 2021 Vol. 168 P. 10–24
This paper presents a forecast combination approach for short-term assessment of economic growth in Russia. Our method significantly expands the existing domestic academic literature and embraces most advanced nowcasting techniques. The key feature of our approach is forecasting the growth rates of components GDP by expenditure using scenario indicators and a huge set of high-frequency ...
Added: November 1, 2021
Khabibullin R. A., Турдыева Н. А., Селезнев С. М. et al., / Series wps "Bank of Russia Working Paper Series". 2020. No. 65.
This paper describes the seasonal adjustment algorithm used by the Bank of Russia to clean up data for ‘Monitoring of Sectoral Financial Flows’ weekly publication. We have developed a simple and fast procedure based on a set of trigonometric functions and dummy variables that demonstrates good results in terms of various quality metrics and can ...
Added: October 29, 2021
Turdyeva N., Tsvetkova A., Movsesyan L. et al., Russian Journal of Money and Finance 2021 Vol. 80 No. 2 P. 28–49
In times of crisis, events are moving fast and standard macroeconomic statistics published with a lag cannot quite keep pace with the changing situation. During such periods, there is an increasing need to use high-frequency indicators that allow virtually real-time monitoring of economic activity. In many countries, this is achieved by using financial transaction data. ...
Added: October 12, 2021
Kashin D., В кн.: Приоритетные направления инновационной деятельности в промышленности.: Каз.: ООО «Конверт», 2021. С. 209–214.
The article provides an overview of the socio-economic consequences of the spread of the COVID-19 pandemic in different countries of the world. Analyzing open resources, the author revealed that both in developed countries with a stable economy and in developing countries, the coronavirus increased social imbalances among the population and exacerbated economic inequality. ...
Added: October 12, 2021