{"title":"Forecasting the COVID-19 epidemic: the case of New Zealand","authors":"P. Ho, T. Lubik, C. Matthes","doi":"10.1080/00779954.2020.1842795","DOIUrl":null,"url":null,"abstract":"ABSTRACT We estimate a statistical model for COVID-19 cases and deaths in New Zealand. New Zealand is an important test case for statistical and theoretical research into the dynamics of the global pandemic since it went through a full cycle of infections. We choose functional forms for infections and deaths that incorporate important features of epidemiological models but allow for flexible parameterization to capture different trajectories of the pandemic. Our Bayesian estimation reveals that the simple statistical framework we employ fits the data well and allows for a transparent characterization of the uncertainty surrounding the trajectories of infections and deaths.","PeriodicalId":38921,"journal":{"name":"New Zealand Economic Papers","volume":"56 1","pages":"9 - 16"},"PeriodicalIF":0.8000,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/00779954.2020.1842795","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Zealand Economic Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00779954.2020.1842795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT We estimate a statistical model for COVID-19 cases and deaths in New Zealand. New Zealand is an important test case for statistical and theoretical research into the dynamics of the global pandemic since it went through a full cycle of infections. We choose functional forms for infections and deaths that incorporate important features of epidemiological models but allow for flexible parameterization to capture different trajectories of the pandemic. Our Bayesian estimation reveals that the simple statistical framework we employ fits the data well and allows for a transparent characterization of the uncertainty surrounding the trajectories of infections and deaths.