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Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature

1
CREATES, Department of Economics and Business Economics, Aarhus University, 8000 Aarhus, Denmark
2
Department of Economics, University of Copenhagen, 1353 Copenhagen K, Denmark
3
Danish Metorological Institute, 2100 Copenhagen, Denmark
*
Authors to whom correspondence should be addressed.
Econometrics 2020, 8(4), 41; https://doi.org/10.3390/econometrics8040041
Received: 28 November 2018 / Revised: 16 October 2020 / Accepted: 21 October 2020 / Published: 2 November 2020
(This article belongs to the Special Issue Celebrated Econometricians: David Hendry)
We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880–2001 and 1880–2013. We find that temperature and sea level updates and revisions have a substantial influence both on the magnitude of the estimated coefficients of influence (differences of up to 50%) and therefore on long-term projections of sea level rise following the RCP4.5 and RCP6 scenarios (differences of up to 40 cm by the year 2100). This shows that in order to replicate earlier results that informed the scientific discussion and motivated policy recommendations, it is crucial to have access to and to work with the data vintages used at the time. View Full-Text
Keywords: sea level; temperature; semi-empirical models; data revisions sea level; temperature; semi-empirical models; data revisions
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Hillebrand, E.; Johansen, S.; Schmith, T. Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature. Econometrics 2020, 8, 41.

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