EconPapers    
Economics at your fingertips  
 

Copula Modeling of COVID-19 Excess Mortality

Jonas Asplund and Arkady Shemyakin ()
Additional contact information
Jonas Asplund: Mathematics Department, University of St. Thomas, 2115 Summit Ave, St. Paul, MN 55105, USA
Arkady Shemyakin: Mathematics Department, University of St. Thomas, 2115 Summit Ave, St. Paul, MN 55105, USA

Risks, 2025, vol. 13, issue 7, 1-18

Abstract: COVID-19’s effects on mortality are hard to quantify. Issues with attribution can cause problems with resulting conclusions. Analyzing excess mortality addresses this concern and allows for the analysis of broader effects of the pandemic. We propose separate ARIMA models to analyze excess mortality for several countries. For the model of joint excess mortality, we suggest vine copulas with Bayesian pair copula selection. This is a new methodology and after its discussion we offer an illustration. The present study examines weekly mortality data from 2019 to 2022 in the USA, Canada, France, Germany, Norway, and Sweden. Previously proposed ARIMA models have low lags and no residual autocorrelation. Only Norway’s residuals exhibited normality, while the remaining residuals suggest skewed Student t-distributions as a plausible fit. A vine copula model was then developed to model the association between the ARIMA residuals for different countries, with the countries farther apart geographically exhibiting weak or no association. The validity of fitted distributions and resulting vine copula was checked using 2023 data. Goodness of fit tests suggest that the fitted distributions were suitable, except for the USA, and that the vine copula used was also valid. We conclude that the time series models of COVID-19 excess mortality are viable. Overall, the suggested methodology seems suitable for creating joint forecasts of pandemic mortality for several countries or geographical regions.

Keywords: ARIMA; pair copula; vine copula; Bayesian analysis (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/13/7/119/pdf (application/pdf)
https://www.mdpi.com/2227-9091/13/7/119/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:13:y:2025:i:7:p:119-:d:1686028

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-06-25
Handle: RePEc:gam:jrisks:v:13:y:2025:i:7:p:119-:d:1686028