Modeling the Covid‐19 epidemic using time series econometrics

B-Tier
Journal: Health Economics
Year: 2021
Volume: 30
Issue: 11
Pages: 2808-2828

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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 remain 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.

Technical Details

RePEc Handle
repec:wly:hlthec:v:30:y:2021:i:11:p:2808-2828
Journal Field
Health
Author Count
2
Added to Database
2026-01-25