IDEAS home Printed from https://ideas.repec.org/h/nbr/nberch/9361.html
   My bibliography  Save this book chapter

The Smoothing of Economic Time Series, Curve Fitting and Graduation

In: The Smoothing of Time Series

Author

Listed:
  • Frederick R. Macaulay

Abstract

No abstract is available for this item.

Suggested Citation

  • Frederick R. Macaulay, 1931. "The Smoothing of Economic Time Series, Curve Fitting and Graduation," NBER Chapters, in: The Smoothing of Time Series, pages 31-42, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:9361
    as

    Download full text from publisher

    File URL: http://www.nber.org/chapters/c9361.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Shouvik Chakraborty, 2012. "Is Export Expansion of Manufactured Goods an Escape Route from Terms of Trade Deterioration of Developing Countries?," Journal of South Asian Development, , vol. 7(2), pages 81-108, October.
    2. Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
    3. Terence Mills, 2007. "A Note on Trend Decomposition: The 'Classical' Approach Revisited with an Application to Surface Temperature Trends," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(8), pages 963-972.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Hall, Viv & Thomson, Peter & McKelvie, Stuart, 2015. "On trend robustness and end-point issues for New Zealand’s stylised business cycle facts," Working Paper Series 3761, Victoria University of Wellington, School of Economics and Finance.
    6. Viv B Hall & Peter Thomson, 2020. "Does Hamilton’s OLS regression provide a “better alternative†to the Hodrick-Prescott filter? A New Zealand business cycle perspective," CAMA Working Papers 2020-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Wang, Shuai & Yu, Lean & Tang, Ling & Wang, Shouyang, 2011. "A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China," Energy, Elsevier, vol. 36(11), pages 6542-6554.
    8. Ingel, Anti & Shahroudi, Novin & Kängsepp, Markus & Tättar, Andre & Komisarenko, Viacheslav & Kull, Meelis, 2020. "Correlated daily time series and forecasting in the M4 competition," International Journal of Forecasting, Elsevier, vol. 36(1), pages 121-128.
    9. Hall, Viv & Thomson, Peter & McKelvie, Stuart, 2015. "On trend robustness and end-point issues for New Zealand’s stylised business cycle facts," Working Paper Series 18867, Victoria University of Wellington, School of Economics and Finance.
    10. Alexander Dokumentov & Rob J. Hyndman, 2022. "STR: Seasonal-Trend Decomposition Using Regression," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 50-62, April.
    11. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    12. Viv B. Hall & Peter Thomson & Stuart McKelvie, 2017. "On the robustness of stylised business cycle facts for contemporary New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 51(3), pages 193-216, September.
    13. Dagum Estela Bee & Luati Alessandra, 2004. "Relationship between Local and Global Nonparametric Estimators Measures of Fitting and Smoothing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-18, May.
    14. Alessandra Luati & Tommaso Proietti, 2011. "On the equivalence of the weighted least squares and the generalised least squares estimators, with applications to kernel smoothing," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(4), pages 851-871, August.

    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:nbr:nberch:9361. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.