Details
Original language | English |
---|---|
Article number | 108520 |
Number of pages | 17 |
Journal | Energy economics |
Volume | 147 |
Early online date | 11 May 2025 |
Publication status | Published - Jun 2025 |
Abstract
This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely connected. These findings are used to build a forecasting model including the cyclical component as well as the relevant earth and climate variables which outperforms models ignoring the cyclical behavior of the data. Especially the turning points can be predicted accurately using the proposed approach. Out of sample forecasts for the turning points of earth temperature, ice volume and CO2 are derived.
Keywords
- Cyclical fractional cointegration, Forecasting climate data, Paleoclimate cycles
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
- Energy(all)
- General Energy
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In: Energy economics, Vol. 147, 108520, 06.2025.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data
AU - Castro, Tomas del Barrio
AU - Escribano, Alvaro
AU - Sibbertsen, Philipp
N1 - Publisher Copyright: © 2025 The Authors
PY - 2025/6
Y1 - 2025/6
N2 - This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely connected. These findings are used to build a forecasting model including the cyclical component as well as the relevant earth and climate variables which outperforms models ignoring the cyclical behavior of the data. Especially the turning points can be predicted accurately using the proposed approach. Out of sample forecasts for the turning points of earth temperature, ice volume and CO2 are derived.
AB - This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely connected. These findings are used to build a forecasting model including the cyclical component as well as the relevant earth and climate variables which outperforms models ignoring the cyclical behavior of the data. Especially the turning points can be predicted accurately using the proposed approach. Out of sample forecasts for the turning points of earth temperature, ice volume and CO2 are derived.
KW - Cyclical fractional cointegration
KW - Forecasting climate data
KW - Paleoclimate cycles
UR - http://www.scopus.com/inward/record.url?scp=105004873187&partnerID=8YFLogxK
U2 - 10.1016/j.eneco.2025.108520
DO - 10.1016/j.eneco.2025.108520
M3 - Article
AN - SCOPUS:105004873187
VL - 147
JO - Energy economics
JF - Energy economics
SN - 0140-9883
M1 - 108520
ER -