IDEAS home Printed from https://ideas.repec.org/p/wyi/wpaper/002537.html

Global temperatures and greenhouse gases - a common features approach

Author

Listed:
  • Li Chen
  • Jiti Gao
  • Farshid Vahid

Abstract

We propose a common features approach and establish that global temperatures and greenhouse gases share a common trend without conditioning on the exact nature of their trends. We also find deterministic cycles in global temperature series with a period of 72 years whose amplitude is non-negligible compared to the warming effect caused by anthropogenic greenhouse gas emissions. We also explore the direction of causation in the co-trending relationship by establishing an error correction mechanism, which shows that greenhouse gas emissions do not respond to the equilibrium errors whereas the global temperature responds to equilibrium errors so as to maintain the co-trending relationship. Finally, we forecast future temperatures conditional on representative concentration pathways (RCP) of greenhouse gases considered by the intergovernmental panel on climate change (IPCC). Our forecasts show that the cyclical component could play a significant role in the next 30 years in such a way that would make the politics of effective emission control policy making more challenging.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:002537
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    3. Liang Chen & Juan J. Dolado & Jesús Gonzalo & Andrey Ramos, 2023. "Heterogeneous predictive association of CO2 with global warming," Economica, London School of Economics and Political Science, vol. 90(360), pages 1397-1421, October.
    4. Gadea-Rivas, Maria Dolores & Gonzalo, Jesús & Ramos, Andrey, 2024. "Trends in temperature data: Micro-foundations of their nature," Economics Letters, Elsevier, vol. 244(C).
    5. Anderson, Heather M. & Gao, Jiti & Turnip, Guido & Vahid, Farshid & Wei, Wei, 2023. "Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach," Energy Economics, Elsevier, vol. 125(C).
    6. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    7. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    8. Chen, Li & Xu, Xiu, 2025. "Testing for common trends and patterns in functional time series data," Economics Letters, Elsevier, vol. 254(C).

    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
    • 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

    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:wyi:wpaper:002537. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: WISE Technical Team (email available below). General contact details of provider: https://www.wise.xmu.edu.cn/english/ .

    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.