Modeling the Covid-19 Epidemic using Time Series Econometrics

Goliński, A., & Spencer, P. (2021). Modeling the Covid-19 epidemic using time series econometrics. Health Economics, 1– 21. https://doi.org/10.1002/hec.4413

30 Pages Posted: 9 Sep 2021

Date Written: May 7, 2021

Abstract

The classic 'logistic' model has provided a realistic model of the behaviour of Covid-19 in China and many East Asian countries. Once these countries passed the peak, the daily case count fell back, mirroring its initial climb in a symmetric way, just as the classic model predicts. However, in Italy and Spain and most other Western countries, the first wave of the epidemic was very different. The daily count fell back gradually from the peak but remained stubbornly high. The reason for the divergence from the classical model remains unclear. We take an empirical stance on this issue and develop a model framework based upon the statistical characteristics of the time series. With the possible exception of China, the workhorse logistic model is decisively rejected against more flexible alternatives.

Note: Funding: None to declare.

Declaration of Interests: None to declare.

Keywords: epidemic modeling, logistic model, gamma model, beta model

JEL Classification: C01

Suggested Citation

Golinski, Adam and Spencer, Peter, Modeling the Covid-19 Epidemic using Time Series Econometrics (May 7, 2021). Goliński, A., & Spencer, P. (2021). Modeling the Covid-19 epidemic using time series econometrics. Health Economics, 1– 21. https://doi.org/10.1002/hec.4413, Available at SSRN: https://ssrn.com/abstract=3918317 or http://dx.doi.org/10.2139/ssrn.3918317

Adam Golinski

University of York ( email )

Heslington
York, YO1 5DD
United Kingdom

Peter Spencer (Contact Author)

University of York ( email )

Heslington
York, YO1 5DD
United Kingdom

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