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The Smoothing of Time Series

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  • Frederick R. Macaulay

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Suggested Citation

  • Frederick R. Macaulay, 1931. "The Smoothing of Time Series," NBER Books, National Bureau of Economic Research, Inc, number maca31-1, March.
    • Handle: RePEc:nbr:nberbk:maca31-1
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    Cited by:

    1. Estela Bee Dagum & Alessandra Luati, 2002. "Global and local statistical properties of fixed-length nonparametric smoothers," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 313-333, October.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Harding, Don, 1997. "The Definition, Dating and Duration of Cycles," MPRA Paper 3357, University Library of Munich, Germany.
    10. 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.
    11. 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.
    12. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    13. Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    14. Hackl, Peter & Westlund, Anders H., 1995. "On price elasticities of international telecommunication demand," Information Economics and Policy, Elsevier, vol. 7(1), pages 27-36, April.
    15. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Hackl, Peter & Westlund, Anders H., 1996. "Demand for international telecommunication time-varying price elasticity," Journal of Econometrics, Elsevier, vol. 70(1), pages 243-260, January.
    21. Proietti, Tommaso & Luati, Alessandra, 2009. "Low-Pass Filter Design using Locally Weighted Polynomial Regression and Discrete Prolate Spheroidal Sequences," MPRA Paper 15510, University Library of Munich, Germany.
    22. Ryan Greenaway-McGrevy, 2013. "A Multivariate Approach to Seasonal Adjustment," BEA Working Papers 0100, Bureau of Economic Analysis.
    23. 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.

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