IDEAS home Printed from https://ideas.repec.org/a/wly/envmet/v36y2025i1ne2846.html
   My bibliography  Save this article

Testing for galactic cosmic ray warming hypothesis using the notion of block‐exogeneity

Author

Listed:
  • Umberto Triacca

Abstract

In this article, we consider the notion of block‐exogeneity and establish a characterization of it. We use this characterization to propose a procedure to test for block‐exogeneity in a trivariate system. The proposed procedure has been applied to test the so‐called galactic cosmic ray warming hypothesis. The galactic cosmic ray warming hypothesis suggests the existence of an indirect solar influence on Earth's climate. Our results seem to imply that this hypothesis does not hold. In particular, we find that the global temperature is block‐exogenous with respect to both sunspot numbers (a measure of the solar activity) and galactic cosmic rays. This implies that the supposed indirect causal link from solar activity to temperature (through cosmic rays), postulated by the galactic cosmic ray warming hypothesis, does not appear to exist.

Suggested Citation

  • Umberto Triacca, 2025. "Testing for galactic cosmic ray warming hypothesis using the notion of block‐exogeneity," Environmetrics, John Wiley & Sons, Ltd., vol. 36(1), January.
    • Handle: RePEc:wly:envmet:v:36:y:2025:i:1:n:e2846
    DOI: 10.1002/env.2846
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/env.2846
    Download Restriction: no
    File URL: https://libkey.io/10.1002/env.2846?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    2. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    3. Rangan Gupta & Luis A. Gil-Alana & Olaoluwa S. Yaya, 2015. "Do sunspot numbers cause global temperatures? Evidence from a frequency domain causality test," Applied Economics, Taylor & Francis Journals, vol. 47(8), pages 798-808, February.
    4. Hassani, Hossein & Huang, Xu & Gupta, Rangan & Ghodsi, Mansi, 2016. "Does sunspot numbers cause global temperatures? A reconsideration using non-parametric causality tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 54-65.
    5. Robert Kaufmann & Heikki Kauppi & Michael Mann & James Stock, 2013. "Does temperature contain a stochastic trend: linking statistical results to physical mechanisms," Climatic Change, Springer, vol. 118(3), pages 729-743, June.
    6. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    7. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    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. Huang, Xu & Hassani, Hossein & Ghodsi, Mansi & Mukherjee, Zinnia & Gupta, Rangan, 2017. "Do trend extraction approaches affect causality detection in climate change studies?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 604-624.
    2. Tang, Chor Foon, 2008. "A re-examination of the relationship between electricity consumption and economic growth in Malaysia," Energy Policy, Elsevier, vol. 36(8), pages 3067-3075, August.
    3. Mohammad I. Elian & Khalid M. Kisswani, 2018. "Oil price changes and stock market returns: cointegration evidence from emerging market," Economic Change and Restructuring, Springer, vol. 51(4), pages 317-337, November.
    4. Evan Lau & Koon Po Lee, 2008. "Interdependence of income between China and ASEAN‐5 countries," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing Limited, vol. 1(2), pages 148-161, June.
    5. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    6. Malik, Zahra & Zaman, Khalid, 2013. "Macroeconomic consequences of terrorism in Pakistan," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1103-1123.
    7. Emre Aksoy, 2013. "Relationships between Employment and Growth from Industrial Perspective by Considering Employment Incentives: The Case of Turkey," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 74-86.
    8. Hian Teck HOON & Frank S T Hsiao & Mei-Chu Wang Hsiao, 2020. "FDI, Exports, and GDP in East and Southeast Asia — Panel Data versus Time-Series Causality Analyses," World Scientific Book Chapters, in: Development Strategies of Open Economies Cases from Emerging East and Southeast Asia, chapter 4, pages 81-129, World Scientific Publishing Co. Pte. Ltd..
    9. Ronald Kumar, 2014. "Exploring the role of technology, tourism and financial development: an empirical study of Vietnam," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2881-2898, September.
    10. Jonathan B. Hill, 2007. "Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money-income relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 747-765.
    11. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    12. Shahzad, Syed Jawad Hussain & Kumar, Ronald Ravinesh & Zakaria, Muhammad & Hurr, Maryam, 2017. "Carbon emission, energy consumption, trade openness and financial development in Pakistan: A revisit," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 185-192.
    13. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    14. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, December.
    15. Sinha, Dipendra, 2007. "Does the Wagner’s Law hold for Thailand? A Time Series Study," MPRA Paper 2560, University Library of Munich, Germany.
    16. Mongi Arfaoui & Bechir Raggad, 2023. "Do Dow Jones Islamic equity indices undergo speculative pressure? New insights from a nonlinear and asymmetric analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1582-1601, April.
    17. Aye, Goodness C. & Balcilar, Mehmet & Bosch, Adél & Gupta, Rangan, 2014. "Housing and the business cycle in South Africa," Journal of Policy Modeling, Elsevier, vol. 36(3), pages 471-491.
    18. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2014. "Housing and the Great Depression," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2966-2981, August.
    19. Azhar Khan, Muhammad & Zahir Khan, Muhammad & Zaman, Khalid & Naz, Lubna, 2014. "Global estimates of energy consumption and greenhouse gas emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 336-344.
    20. Basse, Tobias & Desmyter, Steven & Saft, Danilo & Wegener, Christoph, 2023. "Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors," International Review of Financial Analysis, Elsevier, vol. 89(C).

    More about this item

    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:wly:envmet:v:36:y:2025:i:1:n:e2846. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1180-4009/ .

    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.