TY - JOUR
T1 - On the invalidity of the ordinary least squares estimate of the equilibrium climate sensitivity
AU - Kim, Dukpa
N1 - Funding Information:
This research is supported by the Korea University Grant (K1911951).
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
PY - 2021/10
Y1 - 2021/10
N2 - The equilibrium climate sensitivity is often estimated by the ordinary least squares applied to annual data of observed/calculated temperature and forcing series. One of the conditions under which the ordinary least squares estimator is consistent is the uncorrelatedness of the regressor and regression error. However, this condition can fail in a regression using historical data of temperature and forcing. Alternative estimators established in econometrics are shown to mitigate the impact of the correlated regressor and regression error and deliver a more reliable estimate of the equilibrium climate sensitivity.
AB - The equilibrium climate sensitivity is often estimated by the ordinary least squares applied to annual data of observed/calculated temperature and forcing series. One of the conditions under which the ordinary least squares estimator is consistent is the uncorrelatedness of the regressor and regression error. However, this condition can fail in a regression using historical data of temperature and forcing. Alternative estimators established in econometrics are shown to mitigate the impact of the correlated regressor and regression error and deliver a more reliable estimate of the equilibrium climate sensitivity.
UR - http://www.scopus.com/inward/record.url?scp=85115225112&partnerID=8YFLogxK
U2 - 10.1007/s00704-021-03719-5
DO - 10.1007/s00704-021-03719-5
M3 - Article
AN - SCOPUS:85115225112
SN - 0177-798X
VL - 146
SP - 21
EP - 27
JO - Theoretical and Applied Climatology
JF - Theoretical and Applied Climatology
IS - 1-2
ER -