Statistics and Its Interface

Volume 16 (2023)

Number 2

Special issue on recent developments in complex time series analysis – Part II

Guest editors: Robert T. Krafty (Emory Univ.), Guodong Li (Univ. of Hong Kong), Anatoly Zhigljavsky (Cardiff Univ.)

Study of impact of COVID-19 on industrial production indices using singular spectrum analysis

Pages: 181 – 188

DOI: https://dx.doi.org/10.4310/21-SII719

Authors

Sofia Borodich Suarez (Department of Economics and Management, University of Luxembourg)

Andrey Pepelyshev (School of Mathematics, Cardiff University, Cardiff, United Kingdom)

Abstract

This paper investigates the impact of the COVID-19 pandemic on 8 different indices of industrial production (IIPs) for three major European countries: France, Germany, and the UK. The analysis is based on applying a combination of Singular Spectrum Analysis (SSA) algorithms, in a way that allows for the proper separation of the trend and seasonal subcycles of the IIPs. The main purpose is to illustrate how to carry out the procedure of the correct decomposition by SSA for the specific series. The accurately extracted trends are analysed and the influence of the pandemic is calculated. The results confirm that necessary goods, such as food and utilities, have low income elasticity of demand since the effect of COVID-19 is negligible for these IIPs. However, for the IIPs of less essential products, the negative impact is much more extreme, although the severity varies depending on several factors, which also aligns with the economic theory.

Keywords

decomposition, separability, trend extraction, cycles

2010 Mathematics Subject Classification

62M20

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The work of A. Pepelyshev was partially supported by the Russian Foundation for Basic Research (no. 20-01-00096).

Received 4 May 2021

Accepted 24 December 2021

Published 13 April 2023