Is climate change time reversible?
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- Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is Climate Change Time-Reversible?," Econometrics, MDPI, vol. 10(4), pages 1-18, December.
- Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time-reversible?," Working Papers 498, University of Milano-Bicocca, Department of Economics, revised Nov 2022.
- Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Working Paper series 22-08, Rimini Centre for Economic Analysis, revised Dec 2022.
References listed on IDEAS
- Tommaso Proietti, 2023.
"Peaks, gaps, and time‐reversibility of economic time series,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 43-68, January.
- Tommaso Proietti, 2020. "Peaks, Gaps, and Time Reversibility of Economic Time Series," CEIS Research Paper 492, Tor Vergata University, CEIS, revised 17 Jun 2020.
- Shujun Li & Lixin Wu & Yun Yang & Tao Geng & Wenju Cai & Bolan Gan & Zhaohui Chen & Zhao Jing & Guojian Wang & Xiaohui Ma, 2020. "The Pacific Decadal Oscillation less predictable under greenhouse warming," Nature Climate Change, Nature, vol. 10(1), pages 30-34, January.
- Belaire-Franch, Jorge & Contreras, Dulce, 2003. "Tests for time reversibility: a complementarity analysis," Economics Letters, Elsevier, vol. 81(2), pages 187-195, November.
- Hinich , Melvin J. & Rothman, Philip, 1998.
"Frequency-Domain Test Of Time Reversibility,"
Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 72-88, March.
- Melvin J. Hinich & Philip Rothman, "undated". "A Frequency Domain Test of Time Reversibility," Working Papers 9706, East Carolina University, Department of Economics.
- Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002.
"Bayesian Analysis of Stochastic Volatility Models,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-389, October.
- John Geweke & Gianni Amisano, 2011.
"Hierarchical Markov normal mixture models with applications to financial asset returns,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
- Amisano, Gianni & Geweke, John, 2007. "Hierarchical Markov normal mixture models with applications to financial asset returns," Working Paper Series 831, European Central Bank.
- John Geweke & Gianni Amisano, 2007. "Hierarchical Markov Normal Mixture Models with Applications to Financial Asset Returns," Working Papers 0705, University of Brescia, Department of Economics.
- Chen, Yi-Ting & Chou, Ray Y. & Kuan, Chung-Ming, 2000. "Testing time reversibility without moment restrictions," Journal of Econometrics, Elsevier, vol. 95(1), pages 199-218, March.
- Geweke, John, 2001. "Bayesian econometrics and forecasting," Journal of Econometrics, Elsevier, vol. 100(1), pages 11-15, January.
- Tilmann Gneiting & Fadoua Balabdaoui & Adrian E. Raftery, 2007. "Probabilistic forecasts, calibration and sharpness," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 243-268, April.
- Backus, David K & Kehoe, Patrick J, 1992.
"International Evidence of the Historical Properties of Business Cycles,"
American Economic Review, American Economic Association, vol. 82(4), pages 864-888, September.
- David K. Backus & Patrick J. Kehoe, 1991. "International evidence on the historical properties of business cycles," Staff Report 145, Federal Reserve Bank of Minneapolis.
- David K. Backus & Patrick J. Kehoe, 1992. "International Evidence on the Historical Properties of Business Cycles," Working Papers 92-5, New York University, Leonard N. Stern School of Business, Department of Economics.
- Ramsey, James B & Rothman, Philip, 1996.
"Time Irreversibility and Business Cycle Asymmetry,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(1), pages 1-21, February.
- Ramsey, J.B. & Rothman, P., 1993. "Time Irreversibility and Business Cycle Asymmetry," Working Papers 93-39, C.V. Starr Center for Applied Economics, New York University.
- Fries, Sébastien & Zakoian, Jean-Michel, 2019.
"Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles,"
Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
- Fries, Sébastien & Zakoian, Jean-Michel, 2017. "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper 81345, University Library of Munich, Germany.
- Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
- F. J. Breidt & R. A. Davis, 1992. "Time‐Reversibility, Identifiability And Independence Of Innovations For Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(5), pages 377-390, September.
- Lanne Markku & Saikkonen Pentti, 2011.
"Noncausal Autoregressions for Economic Time Series,"
Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
- Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.
- Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
- Robert M. de Jong & Neslihan Sakarya, 2016. "The Econometrics of the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 310-317, May.
- Robert M. DeConto & David Pollard & Richard B. Alley & Isabella Velicogna & Edward Gasson & Natalya Gomez & Shaina Sadai & Alan Condron & Daniel M. Gilford & Erica L. Ashe & Robert E. Kopp & Dawei Li , 2021. "The Paris Climate Agreement and future sea-level rise from Antarctica," Nature, Nature, vol. 593(7857), pages 83-89, May.
- Christian Gourieroux & Joann Jasiak, 2022. "Nonlinear Fore(Back)casting and Innovation Filtering for Causal-Noncausal VAR Models," Papers 2205.09922, arXiv.org, revised Apr 2024.
- Clemen, Robert T. & Murphy, Allan H. & Winkler, Robert L., 1995. "Screening probability forecasts: contrasts between choosing and combining," International Journal of Forecasting, Elsevier, vol. 11(1), pages 133-145, March.
- Emir Shuford & Arthur Albert & H. Edward Massengill, 1966. "Admissible probability measurement procedures," Psychometrika, Springer;The Psychometric Society, vol. 31(2), pages 125-145, June.
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
- Wenju Cai & Guojian Wang & Agus Santoso & Michael J. McPhaden & Lixin Wu & Fei-Fei Jin & Axel Timmermann & Mat Collins & Gabriel Vecchi & Matthieu Lengaigne & Matthew H. England & Dietmar Dommenget & , 2015. "Increased frequency of extreme La Niña events under greenhouse warming," Nature Climate Change, Nature, vol. 5(2), pages 132-137, February.
- Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
- Corradi, Valentina & Swanson, Norman R., 2006.
"Predictive density and conditional confidence interval accuracy tests,"
Journal of Econometrics, Elsevier, vol. 135(1-2), pages 187-228.
- Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
- Christian Gouriéroux & Jean-Michel Zakoian, 2013. "Explosive Bubble Modelling by Noncausal Process," Working Papers 2013-04, Center for Research in Economics and Statistics.
- Corradi, Valentina & Swanson, Norman R., 2006.
"Predictive Density Evaluation,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 5, pages 197-284,
Elsevier.
- Valentina Corradi & Norman Swanson, 2004. "Predictive Density Evaluation," Departmental Working Papers 200419, Rutgers University, Department of Economics.
- Quandt, Richard E, 1974. "A Comparison of Methods for Testing Nonnested Hypotheses," The Review of Economics and Statistics, MIT Press, vol. 56(1), pages 92-99, February.
- Marc Hallin & Claude Lefèvre & Madan Lal Puri, 1988. "On time-reversibility and the uniqueness of moving average representations for non-Gaussian stationary time series," ULB Institutional Repository 2013/2017, ULB -- Universite Libre de Bruxelles.
- Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
- Breid, F. Jay & Davis, Richard A. & Lh, Keh-Shin & Rosenblatt, Murray, 1991. "Maximum likelihood estimation for noncausal autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 36(2), pages 175-198, February.
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Cited by:
- Ohtsuka, Yoshihiro & Oga, Takashi & Kakamu, Kazuhiko, 2010. "Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2721-2735, November.
- Geweke, John & Amisano, Gianni, 2010.
"Comparing and evaluating Bayesian predictive distributions of asset returns,"
International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
- Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.
- Christian Kascha & Francesco Ravazzolo, 2010.
"Combining inflation density forecasts,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
- Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
- Gianluca Cubadda & Alain Hecq & Elisa Voisin, 2023.
"Detecting Common Bubbles in Multivariate Mixed Causal–Noncausal Models,"
Econometrics, MDPI, vol. 11(1), pages 1-16, March.
- Gianluca Cubadda & Alain Hecq & Elisa Voisin, 2022. "Detecting common bubbles in multivariate mixed causal-noncausal models," Papers 2207.11557, arXiv.org.
- Gianluca Cubadda & Alain Hecq & Elisa Voisin, 2023. "Detecting Common Bubbles in Multivariate Mixed Causal-noncausal Models," CEIS Research Paper 555, Tor Vergata University, CEIS, revised 27 Feb 2023.
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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
NEP fields
This paper has been announced in the following NEP Reports:- NEP-DEM-2022-07-18 (Demographic Economics)
- NEP-ENV-2022-07-18 (Environmental Economics)
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