{"title":"Data Revisions and the Statistical Relation of Global Mean Sea-Level and Temperature","authors":"Eric Hillebrand, S. Johansen, T. Schmith","doi":"10.2139/ssrn.2612924","DOIUrl":null,"url":null,"abstract":"We study the stability of the estimated statistical relation of global mean temperature and global mean sea-level with regard to data revisions. Using three different model speci?cations proposed in the literature, we compare coefficient estimates and forecasts using two different vintages of the annual time series. We ?find that two out of the three models, proposed in [1] and in [2], are very sensitive to the revisions. The magnitude of the estimated coefficient of infl?uence as well as the implied long-term forecasts change drastically between the two data vintages considered. The model proposed in [3], on the other hand, reacts robustly to the revisions.","PeriodicalId":296234,"journal":{"name":"SRPN: Sustainable Development (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SRPN: Sustainable Development (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2612924","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
We study the stability of the estimated statistical relation of global mean temperature and global mean sea-level with regard to data revisions. Using three different model speci?cations proposed in the literature, we compare coefficient estimates and forecasts using two different vintages of the annual time series. We ?find that two out of the three models, proposed in [1] and in [2], are very sensitive to the revisions. The magnitude of the estimated coefficient of infl?uence as well as the implied long-term forecasts change drastically between the two data vintages considered. The model proposed in [3], on the other hand, reacts robustly to the revisions.