IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p277-d1016337.html
   My bibliography  Save this article

Global Temperature and Carbon Dioxide Nexus: Evidence from a Maximum Entropy Approach

Author

Listed:
  • Pedro Macedo

    (CIDMA—Center for Research and Development in Mathematics and Applications, Department of Mathematics, University of Aveiro, 3810-193 Aveiro, Portugal)

  • Mara Madaleno

    (Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
    Departamento de Economia, Gestão, Engenharia Industrial e Turismo (DEGEIT), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

Abstract

The connection between Earth’s global temperature and carbon dioxide (CO 2 ) emissions is one of the highest challenges in climate change science since there is some controversy about the real impact of CO 2 emissions on the increase of global temperature. This work contributes to the existing literature by analyzing the relationship between CO 2 emissions and the Earth’s global temperature for 61 years, providing a recent review of the emerging literature as well. Through a statistical approach based on maximum entropy, this study supports the results of other techniques that identify a positive impact of CO 2 in the increase of the Earth’s global temperature. Given the well-known difficulties in the measurement of global temperature and CO 2 emissions with high precision, this statistical approach is particularly appealing around climate change science, as it allows the replication of the original time series with the subsequent construction of confidence intervals for the model parameters. To prevent future risks, besides the present urgent decrease of greenhouse gas emissions, it is necessary to stop using the planet and nature as if resources were infinite.

Suggested Citation

  • Pedro Macedo & Mara Madaleno, 2022. "Global Temperature and Carbon Dioxide Nexus: Evidence from a Maximum Entropy Approach," Energies, MDPI, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:277-:d:1016337
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/277/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/1/277/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Glen P. Peters & Robbie M. Andrew & Tom Boden & Josep G. Canadell & Philippe Ciais & Corinne Le Quéré & Gregg Marland & Michael R. Raupach & Charlie Wilson, 2013. "The challenge to keep global warming below 2 °C," Nature Climate Change, Nature, vol. 3(1), pages 4-6, January.
    2. Costas Varotsos & Yuri Mazei & Elena Novenko & Andrey N. Tsyganov & Alexander Olchev & Tatiana Pampura & Natalia Mazei & Yulia Fatynina & Damir Saldaev & Maria Efstathiou, 2020. "A New Climate Nowcasting Tool Based on Paleoclimatic Data," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    3. Vladimir F. Krapivin & Costas A. Varotsos & Vladimir Yu. Soldatov, 2017. "The Earth’s Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability," IJERPH, MDPI, vol. 14(8), pages 1-19, August.
    4. Withey, Patrick & Johnston, Craig & Guo, Jinggang, 2019. "Quantifying the global warming potential of carbon dioxide emissions from bioenergy with carbon capture and storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    5. Vinod, Hrishikesh D. & Lopez-de-Lacalle, Javier, 2009. "Maximum Entropy Bootstrap for Time Series: The meboot R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i05).
    6. G. P. Peters & R. M. Andrew & J. G. Canadell & P. Friedlingstein & R. B. Jackson & J. I. Korsbakken & C. Quéré & A. Peregon, 2020. "Carbon dioxide emissions continue to grow amidst slowly emerging climate policies," Nature Climate Change, Nature, vol. 10(1), pages 3-6, January.
    7. Vinod, Hrishikesh D., 2006. "Maximum entropy ensembles for time series inference in economics," Journal of Asian Economics, Elsevier, vol. 17(6), pages 955-978, December.
    8. Greg H. Rau & Heather D. Willauer & Zhiyong Jason Ren, 2018. "The global potential for converting renewable electricity to negative-CO2-emissions hydrogen," Nature Climate Change, Nature, vol. 8(7), pages 621-625, July.
    9. Myles R. Allen & David J. Frame & Chris Huntingford & Chris D. Jones & Jason A. Lowe & Malte Meinshausen & Nicolai Meinshausen, 2009. "Warming caused by cumulative carbon emissions towards the trillionth tonne," Nature, Nature, vol. 458(7242), pages 1163-1166, April.
    10. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "On Spurious Causality, CO2, and Global Temperature," Papers 2103.10605, arXiv.org.
    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. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
    2. Vajjarapu, Harsha & Verma, Ashish, 2022. "Understanding the mitigation potential of sustainable urban transport measures across income and gender groups," Journal of Transport Geography, Elsevier, vol. 102(C).
    3. A. Talha Yalta, 2013. "The Dynamics of Road Energy Demand and Illegal Fuel Activity in Turkey: A Rolling Window Analysis," Working Papers 1304, TOBB University of Economics and Technology, Department of Economics, revised Jul 2013.
    4. Miroslav Plašil, 2011. "Potenciální produkt, mezera výstupu a míra nejistoty spojená s jejich určením při použití Hodrick-Prescottova filtru [Potential Product, Output Gap and Uncertainty Rate Associated with Their Determ," Politická ekonomie, Prague University of Economics and Business, vol. 2011(4), pages 490-507.
    5. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    6. Zeinab Zanjani & Pedro Macedo & Isabel Soares, 2021. "Investigating Carbon Emissions from Electricity Generation and GDP Nexus Using Maximum Entropy Bootstrap: Evidence from Oil-Producing Countries in the Middle East," Energies, MDPI, vol. 14(12), pages 1-22, June.
    7. H.D. Vinod, 2016. "New bootstrap inference for spurious regression problems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(2), pages 317-335, February.
    8. Maria Grazia Zoia & Gianmarco Vacca & Laura Barbieri, 2020. "Modeling Multivariate Financial Series and Computing Risk Measures via Gram–Charlier-Like Expansions," Risks, MDPI, vol. 8(4), pages 1-21, November.
    9. Hrishikesh D. Vinod, 2013. "Maximum Entropy Bootstrap Algorithm Enhancements," Fordham Economics Discussion Paper Series dp2013-04, Fordham University, Department of Economics.
    10. Aqil Khan & Mumtaz Ahmed & Salma Bibi, 2019. "Financial development and economic growth nexus for Pakistan: a revisit using maximum entropy bootstrap approach," Empirical Economics, Springer, vol. 57(4), pages 1157-1169, October.
    11. Arisara Romyen & Chukiat Chaiboonsri & Satawat Wannapan & Songsak Sriboonchitta, 2019. "Multi-Process-Based Maximum Entropy Bootstrapping Estimator: Application for Net Foreign Direct Investment in ASEAN," Economies, MDPI, vol. 7(3), pages 1-13, July.
    12. Yalta, A. Yasemin, 2013. "Revisiting the FDI-led growth Hypothesis: The case of China," Economic Modelling, Elsevier, vol. 31(C), pages 335-343.
    13. A. Talha Yalta, 2016. "Bootstrap Inference of Level Relationships in the Presence of Serially Correlated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 339-366, August.
    14. Yalta, A. Talha & Yalta, A. Yasemin, 2016. "The dynamics of fuel demand and illegal fuel activity in Turkey," Energy Economics, Elsevier, vol. 54(C), pages 144-158.
    15. Alptekin, Aynur & Broadstock, David C. & Chen, Xiaoqi & Wang, Dong, 2019. "Time-varying parameter energy demand functions: Benchmarking state-space methods against rolling-regressions," Energy Economics, Elsevier, vol. 82(C), pages 26-41.
    16. A. Talha Yalta, 2013. "Small Sample Bootstrap Inference of Level Relationships in the Presence of Autocorrelated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Working Papers 1301, TOBB University of Economics and Technology, Department of Economics.
    17. Galip Altinay & A. Talha Yalta, 2016. "Estimating the evolution of elasticities of natural gas demand: the case of Istanbul, Turkey," Empirical Economics, Springer, vol. 51(1), pages 201-220, August.
    18. Hrishikesh Vinod & Lekha S. Chakraborty & Honey Karun, 2014. "If Deficits Are Not the Culprit, What Determines Indian Interest Rates? An Evaluation Using the Maximum Entropy Bootstrap Method," Economics Working Paper Archive wp_811, Levy Economics Institute.
    19. A. Yasemin Yalta, 2011. "New Evidence on FDI-Led Growth: The Case of China," Working Papers 1107, TOBB University of Economics and Technology, Department of Economics.
    20. Zanjani, Zeinab & Soares, Isabel & Macedo, Pedro, 2023. "Investigating CO2 emissions from aviation in oil producing countries using a two-stage maximum entropy approach," Energy, Elsevier, vol. 278(PA).

    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:gam:jeners:v:16:y:2022:i:1:p:277-:d:1016337. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.