Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/247597 
Autor:innen: 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 9 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-25
Verlag: 
MDPI, Basel
Zusammenfassung: 
This study proposes a nonlinear cointegrating regression model based on the well-known energy balance climate model. Specifically, I investigate the nonlinear cointegrating regression of the mean of temperature anomaly distributions on total radiative forcing using estimated spatial distributions of temperature anomalies for the Globe, Northern Hemisphere, and Southern Hemisphere. Further, I provide two types of nonlinear response functions that map the total radiative forcing level to mean temperature anomalies. The proposed statistical model provides a climatological implication that spatially heterogenous warming effects play a significant role in identifying nonlinear climate sensitivity. Cointegration and specification tests are provided that support the existence of nonlinear effects of total radiative forcing.
Schlagwörter: 
climate change
climate sensitivity
cointegration
distributional time series
energy balance climate model
JEL: 
C14
C23
C33
Q54
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