IDEAS home Printed from https://ideas.repec.org/p/ube/dpvwib/dp2308.html
   My bibliography  Save this paper

Forecasting Global Temperatures by Exploiting Cointegration with Radiative Forcing

Author

Listed:
  • Luca Benati

Abstract

I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a no change scenario, the most favorable median forecast predicts the land temperature anomaly to reach 5.6 Celsius degrees in 2100. Forecasts conditional on alternative paths for the JRF show that, given the extent of uncertainty, bringing climate change under control will require to bring the JRF back to the level reached in the early years of the XXI century. From a methodological point of view, my evidence suggests that previous cointegration-based studies of climate change suffer from model mis-specification.

Suggested Citation

  • Luca Benati, 2023. "Forecasting Global Temperatures by Exploiting Cointegration with Radiative Forcing," Diskussionsschriften dp2308, Universitaet Bern, Departement Volkswirtschaft.
    • Handle: RePEc:ube:dpvwib:dp2308
    as

    Download full text from publisher

    File URL: https://repec.vwiit.ch/dp/dp2308.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Benati, Luca, 2007. "Drift and breaks in labor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2847-2877, August.
    2. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    3. Kleibergen, Frank & van Dijk, Herman K., 1994. "On the Shape of the Likelihood/Posterior in Cointegration Models," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 514-551, August.
    4. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    5. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    6. Luca Benati, 2008. "Investigating Inflation Persistence Across Monetary Regimes," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(3), pages 1005-1060.
    7. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
    8. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    9. Hui Liu & Gabriel Rodriguez, 2003. "Human Activities and Global Warming: A Cointegration Analysis," Working Papers 0307E, University of Ottawa, Department of Economics.
    10. Hamilton, James D., 1986. "A standard error for the estimated state vector of a state-space model," Journal of Econometrics, Elsevier, vol. 33(3), pages 387-397, December.
    11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    12. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    2. Luca Benati & Thomas A. Lubik, 2021. "Searching for Hysteresis," Working Paper 21-03, Federal Reserve Bank of Richmond.
    3. Christian Aßmann & Jens Boysen-Hogrefe & Markus Pape, 2024. "Post-processing for Bayesian analysis of reduced rank regression models with orthonormality restrictions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 577-609, September.
    4. Benati, Luca, 2020. "Money velocity and the natural rate of interest," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 117-134.
    5. Issler, Joao Victor & Vahid, Farshid, 2001. "Common cycles and the importance of transitory shocks to macroeconomic aggregates," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 449-475, June.
    6. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    7. Chao, John C. & Phillips, Peter C. B., 1999. "Model selection in partially nonstationary vector autoregressive processes with reduced rank structure," Journal of Econometrics, Elsevier, vol. 91(2), pages 227-271, August.
    8. Guillermo Calvo & Carmen Reinhart & Carlos Végh, 1994. "La tasa de cambio real como meta de política: teoría y evidencia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 13(25), pages 7-50, June.
    9. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    10. Pan, Ming-Shiun & Liu, Y. Angela, 1999. "Fractional cointegration, long memory, and exchange rate dynamics," International Review of Economics & Finance, Elsevier, vol. 8(3), pages 305-316, September.
    11. Wei Yao & Weikun Zhang & Wenxiu Li & Penglong Li, 2022. "Measurement and Evaluation of Convergence of Japan’s Marine Fisheries and Marine Tourism," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    12. Chih-Chuan Yeh & Ching-Fang Chi, 2009. "The Co-Movement and Long-Run Relationship between Inflation and Stock Returns: Evidence from 12 OECD Countries," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 5(2), pages 167-186, July.
    13. MacDonald, Ronald & Molana, Hassan, 2004. "Can portfolio adjustments explain deviations of consumption from permanent income?: An empirical study of UK data," The North American Journal of Economics and Finance, Elsevier, vol. 15(3), pages 313-331, December.
    14. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587.
    15. Caporale, Guglielmo Maria & Hassapis, Christis & Pittis, Nikitas, 1998. "Unit roots and long-run causality: investigating the relationship between output, money and interest rates," Economic Modelling, Elsevier, vol. 15(1), pages 91-112, January.
    16. Evangelia Kasimati & Nikolaos Veraros, 2018. "Accuracy of forward freight agreements in forecasting future freight rates," Applied Economics, Taylor & Francis Journals, vol. 50(7), pages 743-756, February.
    17. Calvo, Guillermo A. & Reinhart, Carmen M. & Vegh, Carlos A., 1995. "Targeting the real exchange rate: theory and evidence," Journal of Development Economics, Elsevier, vol. 47(1), pages 97-133, June.
    18. Schumacher, Christian, 2002. "Forecasting Trend Output in the Euro Area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(8), pages 543-558, December.
    19. David B. Stephenson & Alemtsehai A. Turasie & Donald P. Cummins, 2023. "More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    20. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.

    More about this item

    Keywords

    Climate change; Bayesian VARs; cointegration; forecasting; conditional forecasts;
    All these keywords.

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:ube:dpvwib:dp2308. 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: Franz Koelliker (email available below). General contact details of provider: https://edirc.repec.org/data/vwibech.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.