Predicting Turning Points of the Russian Economic Cycle Using Composite Leading Indicators

Author:

Smirnov S. V.1ORCID

Affiliation:

1. National Research University Higher School of Economics

Abstract

The article provides a brief overview of the background of constructing composite leading indicators (CLI) for Russia; the paper defines key indicators which currently are calculated and published monthly; they can be put in practice to monitor the Russian economy. The underlying methodological approaches are analyzed, along with their advantages and disadvantages. The importance of accounting for a factor of regular or irregular updates and revisions of methods for calculating the CLI is emphasized. Due to them not only the current but also the “historical” dynamics of the indices occasionally change. The paper compares various CLI components and reveals both similarities and differences in the notion of the cyclical dynamics of individual components, reaching the point that the same indicators depending on the methodology are considered as leading, or as lagging. A set of “core” indicators included in the calculation of almost all Russian CLIs is determined; the author also noted those indicators that are widely used in other countries but not yet in Russia, for various reasons.Special attention is paid to the problems of dating economic cycle turning points, in particular, those arising from different notions of the very concept of the economic cycle. Dating using formal statistical methods, firstly, is mostly determined by purely technical (and not substantive) nuances, and secondly, it often changes retroactively when revising historical time series. Analysis of global experience indicates that the way out of this impasse can be the detecting of cyclical turning points based on the decisions of the special expert council, whose sole tasks include dating cyclical peaks and troughs. The article describes methodological approaches that the Economic Cycle Dating Committee (Russian Dating Committee, RDC) under the Association of Russian Economic Think Tanks (ARETT), is supposed to follow.The final part of the article analyzes the ability of various Russian CLIs to timely warn when a new phase of the economic cycle is approaching, especially the impending recession. It is shown that expert opinions on the future dynamics of the Russian economy, contained in monthly press releases, are often more accurate than the conclusions that can be obtained based on the CLI trajectory using purely formal decision rules. On this basis, it is concluded that the existing Russian CLIs can be improved; this calls for clarification and finally fixing the dating of cyclical turning points (peaks and troughs), as well as for conducting additional research to identify various economic and financial indicators as the leading, synchronous or lagging indicators of the Russian economic cycle.

Publisher

Information and Publishing Centre Statistics of Russia

Reference22 articles.

1. Davydov A., Popov V., Frenkel A. Index of Business Activity in Russia: Construction and Results. World Esonomy and International Relations. 1993;(12):29-41. (In Russ.)

2. Popov V., Frenkel A. An Index of Business Activity for the Russian Economy. ECO. 1996;(10):76-89. (In Russ.)

3. Bogdanova A.L. Leading Indicators as an Instrument of Economic Forecasting. Economics of Contemporary Russia. 2018;(2):35-56. (In Russ.)

4. Smirnov S.V. Russian Cyclical Indicators and Their Usefulness in «Real Time»: An Experience of the 2008-2009 Recession. HSE Economic Journal. 2012;16(4):479-513. (In Russ.)

5. Burns A.F., Mitchell W.C. Measuring Business Cycles. NBER; 1946.

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