Robust estimation and forecasting of climate change using score-driven ice-age models
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 that model by using score-driven fil...
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ftunivcarlosmadr:oai:e-archivo.uc3m.es:10016/33453 2024-01-21T10:00:27+01:00 Robust estimation and forecasting of climate change using score-driven ice-age models Blazsek, Szabolcs Escribano, Álvaro Universidad Carlos III de Madrid. Departamento de Economía Agencia Estatal de Investigación (España) Ministerio de Economía, Industria y Competitividad (España) Comunidad de Madrid 2021-10-14 http://hdl.handle.net/10016/33453 eng eng Working paper. Economics 21-12 Comunidad de Madrid. S2015/HUM-3444/MadEco-CM Gobierno de España. ECO2016-00105-001 Gobierno de España. MDM2014-0431 Gobierno de España. 2019/00419/001/AEI/10.13039/501100011033 2340-5031 http://hdl.handle.net/10016/33453 DT/0000001932 Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Climate Change Ice-Ages and Inter-Glacial Periods Atmospheric Co2 and Land Surface Temperature Dynamic Conditional Score Models Generalized Autoregressive Score Models working paper AO 2021 ftunivcarlosmadr 2023-12-27T00:19:51Z 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 that model 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 last 100 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 observed Icet, (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. Blazsek acknowledges funding from Universidad Francisco Marroquín. Escribano acknowledges funding from Ministerio de Economía, Industria y Competitividad (ECO2016-00105-001 and MDM 2014-0431), Comunidad de Madrid (MadEco-CM S2015/HUM-3444), and Agencia Estatal de Investigación (2019/00419/001). Report Antarc* Antarctic Universidad Carlos III de Madrid: e-Archivo Antarctic |
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Open Polar |
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Universidad Carlos III de Madrid: e-Archivo |
op_collection_id |
ftunivcarlosmadr |
language |
English |
topic |
Climate Change Ice-Ages and Inter-Glacial Periods Atmospheric Co2 and Land Surface Temperature Dynamic Conditional Score Models Generalized Autoregressive Score Models |
spellingShingle |
Climate Change Ice-Ages and Inter-Glacial Periods Atmospheric Co2 and Land Surface Temperature Dynamic Conditional Score Models Generalized Autoregressive Score Models Blazsek, Szabolcs Escribano, Álvaro Robust estimation and forecasting of climate change using score-driven ice-age models |
topic_facet |
Climate Change Ice-Ages and Inter-Glacial Periods Atmospheric Co2 and Land Surface Temperature Dynamic Conditional Score Models Generalized Autoregressive Score Models |
description |
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 that model 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 last 100 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 observed Icet, (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. Blazsek acknowledges funding from Universidad Francisco Marroquín. Escribano acknowledges funding from Ministerio de Economía, Industria y Competitividad (ECO2016-00105-001 and MDM 2014-0431), Comunidad de Madrid (MadEco-CM S2015/HUM-3444), and Agencia Estatal de Investigación (2019/00419/001). |
author2 |
Universidad Carlos III de Madrid. Departamento de Economía Agencia Estatal de Investigación (España) Ministerio de Economía, Industria y Competitividad (España) Comunidad de Madrid |
format |
Report |
author |
Blazsek, Szabolcs Escribano, Álvaro |
author_facet |
Blazsek, Szabolcs Escribano, Álvaro |
author_sort |
Blazsek, Szabolcs |
title |
Robust estimation and forecasting of climate change using score-driven ice-age models |
title_short |
Robust estimation and forecasting of climate change using score-driven ice-age models |
title_full |
Robust estimation and forecasting of climate change using score-driven ice-age models |
title_fullStr |
Robust estimation and forecasting of climate change using score-driven ice-age models |
title_full_unstemmed |
Robust estimation and forecasting of climate change using score-driven ice-age models |
title_sort |
robust estimation and forecasting of climate change using score-driven ice-age models |
publishDate |
2021 |
url |
http://hdl.handle.net/10016/33453 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
Working paper. Economics 21-12 Comunidad de Madrid. S2015/HUM-3444/MadEco-CM Gobierno de España. ECO2016-00105-001 Gobierno de España. MDM2014-0431 Gobierno de España. 2019/00419/001/AEI/10.13039/501100011033 2340-5031 http://hdl.handle.net/10016/33453 DT/0000001932 |
op_rights |
Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
_version_ |
1788703187078742016 |