Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data

A-Tier
Journal: Energy Economics
Year: 2025
Volume: 147
Issue: C

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:eneeco:v:147:y:2025:i:c:s0140988325003445
Journal Field
Energy
Author Count
3
Added to Database
2026-01-25