The relationship of economic sentiment and GDP growth in Russia in light of the Covid-19 crisis

Abstract

Objective: The objective of the article is to prove the empirical and predictive value of the aggregate opinions of businesses and households for expanding cyclical macroeconomic data in Russia, especially during the coronavirus shocks.

Research Design & Methods: We use qualitative information from surveys that cover about 24 000 organisations and 5100 households in all Russian regions. The total economic sentiment indicator (TESI) combines information on 18 survey-based indicators. Cross-correlation analysis, Hodrick-Prescott filtering, and a vector autoregressive (VAR) model with dummy variables are used as the research methods.

Findings: The study confirms an almost synchronous cyclic conformity of the gross domestic product (GDP) growth and TESI dynamics for the period of 1998-2020. Probable GDP growth until the end of 2021 is estimated based on the expected impulses in the TESI dynamics, including those due to the sudden impact of the coronavirus.

Implications & Recommendations: Assessments of business and household activity are reliable and available much earlier than quantitative statistics on GDP growth. Therefore, we advise to use them as an early warning system about economic growth and take them into account in policymaking.

Contribution & Value Added: We are the first to confirm the effectiveness and reliability of TESI as a leading indicator of GDP growth in Russia, using data from large-scale business surveys and with a focus on crisis shocks.

Keywords

business and consumer surveys; economic sentiment indicator; composite indicators; economic growth; GDP growth; growth cycles

Author Biography

Liudmila Kitrar

Candidate of Sciences (PhD) in Mathematical and Instrumental Methods in Economics; Deputy Director of the Centre for Business Tendency Studies, Higher School of Economics, Moscow, Russian Federation; member of the Russian Association of Statisticians; UNIDO international expert. Her research interests include: indicator approach to measuring economic dynamics; methods of quantification, analysis and visualization of nonparametric statistics; econometric methods of decomposition of unobservable variables in economic dynamics; entrepreneurial expectations; VAR models and statistical filtering in the practice of business tendency monitoring.

Tamara Lipkind

Leading expert of the Centre for Business Tendency Studies, Higher School of Economics, Moscow, Russian Federation. Her research interests include: composite indicators of business cycles; business and consumer surveys; sectoral and regional comparative analysis of economic sentiment and business climate; quantification and visualisation of nonparametric statistics.

Correspondence to: Tamara Lipkind, National Research University Higher School of Economics, Institute for Statistical Studies and Economics of Knowledge, Centre for Business Tendency Studies, Slavyanskaya Sq., 4/2, Moscow, 101000, Russian Federation, e-mail: tlipkind@hse.ru

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