Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections
Author
Abstract
Suggested Citation
Note: EEE
Download full text from publisher
Other versions of this item:
- 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," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- 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," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco.
References listed on IDEAS
- Luke D. Trusel & Sarah B. Das & Matthew B. Osman & Matthew J. Evans & Ben E. Smith & Xavier Fettweis & Joseph R. McConnell & Brice P. Y. Noël & Michiel R. Broeke, 2018. "Nonlinear rise in Greenland runoff in response to post-industrial Arctic warming," Nature, Nature, vol. 564(7734), pages 104-108, December.
- Eddy Bekkers & Joseph F. Francois & Hugo Rojas†Romagosa, 2018.
"Melting Ice Caps and the Economic Impact of Opening the Northern Sea Route,"
Economic Journal, Royal Economic Society, vol. 128(610), pages 1095-1127, May.
- Francois, Joseph F. & Rojas-Romagosa, Hugo, 2013. "Melting Ice Caps and the Economic Impact of Opening the Northern Sea Route," Conference papers 332392, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
- Francois, Joseph & Bekkers, Eddy & Rojas-Romagosa, Hugo, 2016. "Melting Ice Caps and the Economic Impact of Opening the Northern Sea Route," CEPR Discussion Papers 11670, C.E.P.R. Discussion Papers.
- Hugo Rojas-Romagosa & Eddy Bekkers & Joseph F. Francois, 2015. "Melting Ice Caps and the Economic Impact of Opening the Northern Sea Route," CPB Discussion Paper 307, CPB Netherlands Bureau for Economic Policy Analysis.
- 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.
- Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2013.
"Inference on Structural Breaks using Information Criteria,"
Manchester School, University of Manchester, vol. 81, pages 54-81, October.
- Alastair R. Hall & Denise R. Osborn & Nikolaos D. Sakkas, 2012. "Inference on Structural Breaks using Information Criteria," Centre for Growth and Business Cycle Research Discussion Paper Series 173, Economics, The University of Manchester.
- Michael D. Bauer & Glenn D. Rudebusch, 2016.
"Monetary Policy Expectations at the Zero Lower Bound,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(7), pages 1439-1465, October.
- Michael D. Bauer & Glenn D. Rudebusch, 2013. "Monetary Policy Expectations at the Zero Lower Bound," Working Paper Series 2013-18, Federal Reserve Bank of San Francisco.
- Maria-Vittoria Guarino & Louise C. Sime & David Schröeder & Irene Malmierca-Vallet & Erica Rosenblum & Mark Ringer & Jeff Ridley & Danny Feltham & Cecilia Bitz & Eric J. Steig & Eric Wolff & Julienne , 2020. "Sea-ice-free Arctic during the Last Interglacial supports fast future loss," Nature Climate Change, Nature, vol. 10(10), pages 928-932, October.
- Chad W. Thackeray & Alex Hall, 2019. "An emergent constraint on future Arctic sea-ice albedo feedback," Nature Climate Change, Nature, vol. 9(12), pages 972-978, December.
- Nelson, Charles R, 1972. "The Prediction Performance of the FRB-MIT-PENN Model of the U.S. Economy," American Economic Review, American Economic Association, vol. 62(5), pages 902-917, December.
- Diebold, Francis X. & Shin, Minchul, 2019.
"Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
- Kenneth F. Wallis, 1987. "Time Series Analysis Of Bounded Economic Variables," Journal of Time Series Analysis, Wiley Blackwell, vol. 8(1), pages 115-123, January.
- David Schröder & Daniel L. Feltham & Daniela Flocco & Michel Tsamados, 2014. "September Arctic sea-ice minimum predicted by spring melt-pond fraction," Nature Climate Change, Nature, vol. 4(5), pages 353-357, May.
- Julienne Stroeve & Walter Meier, 2012. "Arctic Sea Ice Decline," Chapters, in: Guoxiang Liu (ed.), Greenhouse Gases - Emission, Measurement and Management, IntechOpen.
- Julienne Stroeve & Mark Serreze & Marika Holland & Jennifer Kay & James Malanik & Andrew Barrett, 2012. "The Arctic’s rapidly shrinking sea ice cover: a research synthesis," Climatic Change, Springer, vol. 110(3), pages 1005-1027, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- 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. & 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.
- 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).
- Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.
- 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 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 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 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.
- 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.
- 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.
- 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. & 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).
- B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.
- 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.
- 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.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 19-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- 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. & 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).
- Liu, ChengCheng & Lian, Feng & Yang, Zhongzhen, 2021. "Comparing the minimal costs of Arctic container shipping between China and Europe: A network schemes perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
- Tuomas Kiiski & Tomi Solakivi & Juuso Töyli & Lauri Ojala, 2018. "Long-term dynamics of shipping and icebreaker capacity along the Northern Sea Route," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 375-399, September.
- Bauer, Michael D. & Neely, Christopher J., 2014.
"International channels of the Fed's unconventional monetary policy,"
Journal of International Money and Finance, Elsevier, vol. 44(C), pages 24-46.
- Michael D. Bauer & Christopher J. Neely, 2012. "International channels of the Fed’s unconventional monetary policy," Working Papers 2012-028, Federal Reserve Bank of St. Louis.
- Michael D. Bauer & Christopher J. Neely, 2012. "International channels of the Fed’s unconventional monetary policy," Working Paper Series 2012-12, Federal Reserve Bank of San Francisco.
- Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
- Uniejewski, Bartosz & Maciejowska, Katarzyna, 2023.
"LASSO principal component averaging: A fully automated approach for point forecast pooling,"
International Journal of Forecasting, Elsevier, vol. 39(4), pages 1839-1852.
- Bartosz Uniejewski & Katarzyna Maciejowska, 2022. "LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling," Papers 2207.04794, arXiv.org.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015.
"Golden rule of forecasting: Be conservative,"
Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
- Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
- Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
- Hommes, Cars & Zhu, Mei, 2014.
"Behavioral learning equilibria,"
Journal of Economic Theory, Elsevier, vol. 150(C), pages 778-814.
- Hommes, C.H. & Zhu, M., 2012. "Behavioral Learning Equilibria," CeNDEF Working Papers 12-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Cars Hommes & Mei Zhu, 2013. "Behavioral Learning Equilibria," Tinbergen Institute Discussion Papers 13-014/II, Tinbergen Institute.
- Zhang, Han & Guo, Bin & Liu, Lanbiao, 2022. "The time-varying bond risk premia in China," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 51-76.
- Tedesco, Letizia & Vichi, Marcello & Thomas, David N., 2012. "Process studies on the ecological coupling between sea ice algae and phytoplankton," Ecological Modelling, Elsevier, vol. 226(C), pages 120-138.
- Gadamus, Lily & Raymond-Yakoubian, Julie & Ashenfelter, Roy & Ahmasuk, Austin & Metcalf, Vera & Noongwook, George, 2015. "Building an indigenous evidence-base for tribally-led habitat conservation policies," Marine Policy, Elsevier, vol. 62(C), pages 116-124.
- Mariano Kulish & James Morley & Tim Robinson, 2014.
"Estimating the expected duration of the zero lower bound in DSGE models with forward guidance,"
Discussion Papers
2014-32, School of Economics, The University of New South Wales.
- Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating the Expected Duration of the Zero Lower Bound in DSGE Models with Forward Guidance," Melbourne Institute Working Paper Series wp2014n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
- Gustavsson, Magnus & Österholm, Pär, 2012.
"Labor-force participation rates and the informational value of unemployment rates: Evidence from disaggregated US data,"
Economics Letters, Elsevier, vol. 116(3), pages 408-410.
- Gustavsson, Magnus & Österholm, Pär, 2010. "Labor-Force Participation Rates and the Informational Value of Unemployment Rates: Evidence from Disaggregated US Data," Working Paper Series 2010:14, Uppsala University, Department of Economics.
- Gustavsson, Magnus & Österholm, Pär, 2010. "Labor-Force Participation Rates and the Informational Value of Unemployment Rates: Evidence from Disaggregated US Data," Working Papers 120, National Institute of Economic Research.
- Gustavsson, Magnus & Österholm, Pär, 2010. "Labor-Force Participation Rates and the Informational Value of Unemployment Rates: Evidence from Disaggregated US Data," Working Paper Series, Center for Labor Studies 2010:13, Uppsala University, Department of Economics.
- Ma, Chaoqun & Tian, Yonggang & Hsiao, Shisong & Deng, Liurui, 2022. "Monetary policy shocks and Bitcoin prices," Research in International Business and Finance, Elsevier, vol. 62(C).
- John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006.
"Econometrics: A Bird’s Eye View,"
CESifo Working Paper Series
1870, CESifo.
- Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, Institute of Labor Economics (IZA).
- Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
- Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2017.
"The asymptotic behaviour of the residual sum of squares in models with multiple break points,"
Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 667-698, October.
- Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2015. "The Asymptotic Behaviour of the Residual Sum of Squares in Models with Multiple Break Points," Economics Discussion Paper Series 1504, Economics, The University of Manchester.
More about this item
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- 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-2021-02-08 (Environmental Economics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:28228. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.