Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections
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DOI: 10.24148/wp2020-02
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- Diebold, Francis X. & Rudebusch, Glenn D., 2022. "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
- Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.
- Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," NBER Working Papers 28228, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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- Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021.
"Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
- Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," PIER Working Paper Archive 20-012, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.
- Diebold, Francis X. & Rudebusch, Glenn D., 2023.
"Climate models underestimate the sensitivity of Arctic sea ice to carbon emissions,"
Energy Economics, Elsevier, vol. 126(C).
- Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," Papers 2307.03552, arXiv.org.
- Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," PIER Working Paper Archive 24-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Diebold, Francis X. & Rudebusch, Glenn D. & Göbel, Maximilian & Goulet Coulombe, Philippe & Zhang, Boyuan, 2024. "Reprint of: When will Arctic sea ice disappear? Projections of area, extent, thickness, and volume," Journal of Econometrics, Elsevier, vol. 239(1).
- Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025. "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers 2025-002, The George Washington University, The Center for Economic Research.
- Brock, William A. & Miller, J. Isaac, 2024.
"Polar amplification in a moist energy balance model: A structural econometric approach to estimation and testing,"
Journal of Econometrics, Elsevier, vol. 245(1).
- William A. Brock & J. Isaac Miller, 2023. "Polar Amplification in a Moist Energy Balance Model: A Structural Econometric Approach to Estimation and Testing," Working Papers 2304, Department of Economics, University of Missouri.
- B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.
- Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023.
"Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models,"
Energy Economics, Elsevier, vol. 124(C).
- Francis X. Diebold & Maximilian Goebel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Papers 2206.10721, arXiv.org, revised Jun 2023.
- Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers 22-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
- Diebold, Francis X. & Göbel, Maximilian, 2022.
"A benchmark model for fixed-target Arctic sea ice forecasting,"
Economics Letters, Elsevier, vol. 215(C).
- Francis X. Diebold & Maximilian Gobel, 2021. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," Papers 2101.10359, arXiv.org, revised Jan 2022.
- Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.
- Vasco J.Gabriel & Luis F. Martins & Anthoulla Phella, 2021. "Modelling Low-Frequency Covariability of Paleoclimatic Data," Working Papers 2022_17, Business School - Economics, University of Glasgow.
- Diebold, Francis X. & Rudebusch, Glenn D. & Göbel, Maximilian & Goulet Coulombe, Philippe & Zhang, Boyuan, 2023.
"When will Arctic sea ice disappear? Projections of area, extent, thickness, and volume,"
Journal of Econometrics, Elsevier, vol. 236(2).
- Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised May 2023.
- Francis X. Diebold & Glenn D. Rudebusch & Maximilian Gobel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," PIER Working Paper Archive 22-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Glenn D. Rudebusch & Maximilian Göbel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," NBER Working Papers 30732, National Bureau of Economic Research, Inc.
- Yun-Sin Chen & Cheng-Yu Hu & Chun-Yi Li & Jia-Bin Lin & Yi-Che Shih, 2025. "Marine Spatial Planning for Offshore Wind Firms: A Comparison of Global Existing Policies and Data for Energy System Storage," Sustainability, MDPI, vol. 17(13), pages 1-19, June.
- Jennifer Castle & David Hendry, 2020. "Identifying the Causal Role of CO2 during the Ice Ages," Economics Series Working Papers 898, University of Oxford, Department of Economics.
- Philippe Goulet Coulombe & Maximilian Gobel, 2020.
"Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis,"
Papers
2005.02535, arXiv.org, revised Mar 2021.
- Philippe Goulet Coulombe & Maximilian Gobel, 2021. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Working Papers 21-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
- Blazsek, Szabolcs & Escribano, Alvaro & Kristof, Erzsebet, 2024.
"Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models,"
Energy Economics, Elsevier, vol. 134(C).
- Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de EconomÃa.
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Keywords
; ; ; ; ; ;JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ENV-2020-01-27 (Environmental Economics)
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