RT Generic
T1 Robust estimation and forecasting of climate change using score-driven ice-age models
A1 Blazsek, Szabolcs
A1 Escribano, Álvaro
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB ScScore-driven models applied to finance and economics have attracted significant attention in the last decade. In this paper, we apply those models to climate data. We study the robustness of a recent climate econometric model, named ice-age model, and we extend thatmodel by using score-driven filters in the measurement and transition equations. The climate variables considered are Antarctic ice volume Icet, atmospheric carbon dioxide level CO2,t, and land surface temperature Tempt, which during the history of the Earth were driven by exogenous variables. The influence of humanity on climate started approximately 10-15 thousand years ago, and it has significantly increased since then. We forecast the climate variables for the last100 thousand years, by using data for the period of 798 thousand years ago to 101 thousand years ago for which humanity did not influence the Earth’s climate. For the last 10-15 thousand years of the forecasting period, we find that: (i) the forecasts of Icet are above the observedIcet, (ii) the forecasts of the CO2,t level are below the observed CO2,t, and (iii) the forecasts of Tempt are below the observed Tempt. Our results are robust, and they disentangle the effects of humanity and orbital variables.
SN 2340-5031
YR 2021
FD 2021-10-14
LK https://hdl.handle.net/10016/33453
UL https://hdl.handle.net/10016/33453
LA eng
NO Blazsek acknowledges funding from Universidad Francisco Marroquín. Escribano acknowledges fundingfrom Ministerio de Economía, Industria y Competitividad (ECO2016-00105-001 and MDM 2014-0431), Comunidadde Madrid (MadEco-CM S2015/HUM-3444), and Agencia Estatal de Investigación (2019/00419/001).
DS e-Archivo
RD 1 sept. 2024