Data of Sectoral Financial Flows as a High-Frequency Indicator of Economic Activity

N. Turdyeva, A. Tsvetkova, L. Movsesyan, A. Alexey, Dmitriy Chernyadev
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引用次数: 4

Abstract

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.
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作为经济活动高频指标的部门资金流动数据
在危机时期,事态发展迅速,发布的标准宏观经济统计数据存在滞后性,无法完全跟上不断变化的形势。在此期间,越来越需要使用高频指标,以便几乎实时监测经济活动。在许多国家,这是通过使用金融交易数据来实现的。在本文中,我们提出了一种基于俄罗斯银行支付系统数据的俄罗斯经济部门资金流动的当前分析方法。我们利用每一类OKVED 2(俄罗斯国家经济活动分类器)的平均每日支付动态信息来制定经济活动的高频指标,这些指标自2020年4月以来已在俄罗斯银行网站上发布。我们还试探性地讨论了金融交易数据在改善商业活动动态短期预测工具和解决其他研究问题方面的潜力。
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