IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_10556.html
   My bibliography  Save this paper

Trends and Persistence in the Greenland Ice Sheet Mass

Author

Listed:
  • Guglielmo Maria Caporale
  • Luis Alberiko Gil-Alana
  • Laura Sauci

Abstract

This paper examines trends and persistence in the Greenland ice sheet mass by applying fractional integration methods to a dataset constructed by Mankoff et al. (2020) on ice discharge for seven different regions of Greenland. The adopted empirical framework encompasses a wide range of stochastic processes and is informative about their dynamic and long-run properties. The main finding is that significant changes have occurred in the behaviour of the series of interest in recent years; more specifically, although a deterministic trend is not present, ice discharge in the various regions of Greenland has become a non-stationary, explosive process, with shocks having permanent effects. It appears that, as a result of global warming, the ice mass loss in Greenland has already reached a tipping point and become an irreversible process.

Suggested Citation

  • Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Laura Sauci, 2023. "Trends and Persistence in the Greenland Ice Sheet Mass," CESifo Working Paper Series 10556, CESifo.
  • Handle: RePEc:ces:ceswps:_10556
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10556.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    2. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    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. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
    2. Aye, Goodness C. & Carcel, Hector & Gil-Alana, Luis A. & Gupta, Rangan, 2017. "Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016," Resources Policy, Elsevier, vol. 54(C), pages 53-57.
    3. Grassi, Stefano & Santucci de Magistris, Paolo, 2014. "When long memory meets the Kalman filter: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 301-319.
    4. Zied Ftiti & Slim Chaouachi, 2018. "What Can We Learn About the Real Exchange Rate Behavior in the Case of a Peripheral Country?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(3), pages 681-707, September.
    5. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    6. OlaOluwa S.Yaya & Pui Kiew Ling & Fumitaka Furuoka & Chinyere Mary Rose Ezeoke & Ray Ikechukwu Jacob, 2019. "Can West African countries catch up with Nigeria? Evidence from smooth nonlinearity method in fractional unit root framework," International Economics, CEPII research center, issue 158, pages 51-63.
    7. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    8. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.
    9. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, January.
    10. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Tripathy, Trilochan, 2020. "Volatility persistence in the Russian stock market," Finance Research Letters, Elsevier, vol. 32(C).
    11. Belbute, José M. & Pereira, Alfredo M., 2022. "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the National Dimension of the Policy Efforts to Meet IPCC Targets," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 47(1), pages 1-27, March.
    12. Ding, Liang & Luo, Yi & Lin, Yan & Huang, Yirong, 2021. "Revisiting the relations between Hurst exponent and fractional differencing parameter for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    13. Choi, Kyongwook & Zivot, Eric, 2007. "Long memory and structural changes in the forward discount: An empirical investigation," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 342-363, April.
    14. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Paul Johnson & Chris Papageorgiou, 2020. "What Remains of Cross-Country Convergence?," Journal of Economic Literature, American Economic Association, vol. 58(1), pages 129-175, March.
    16. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    17. C. Vladimir Rodríguez-Caballero & J. Eduardo Vera-Valdés, 2020. "Long-Lasting Economic Effects of Pandemics:Evidence on Growth and Unemployment," Econometrics, MDPI, vol. 8(3), pages 1-16, September.
    18. Giorgio Canarella & Luis Gil-Alana & Rangan Gupta & Stephen M Miller, 2021. "Persistence and cyclical dynamics of US and UK house prices: Evidence from over 150 years of data," Urban Studies, Urban Studies Journal Limited, vol. 58(1), pages 53-72, January.
    19. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    20. Monge, Manuel & Romero Rojo, María Fátima & Gil-Alana, Luis Alberiko, 2023. "The impact of geopolitical risk on the behavior of oil prices and freight rates," Energy, Elsevier, vol. 269(C).

    More about this item

    Keywords

    Greenland ice sheet mass; long memory; fractional integration; persistence; trends;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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:ces:ceswps:_10556. 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: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.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.