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Does Hamilton's OLS Regression Provide a Better "Alternative" to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective

Author

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  • Viv B Hall
  • Peter Thomson

Abstract

Within a New Zealand business cycle context, we assess whether Hamilton's (H84) OLS regression methodology produces stylised business cycle facts which are materially different from HP1600 measures, and whether using the H84 predictor and other forecast extensions improves the HP filter's properties at the ends of series. In general, H84 produces exaggerated volatilities and less credible trend movements during key economic periods so there is no material advantage in using H84 de-trending over HP1600. At the ends, the forecast-extended HP filter almost always performs better than the HP filter with no extension which performs slightly better than H84 forecast extension.

Suggested Citation

  • 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.
    • Handle: RePEc:een:camaaa:2020-71
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    File URL: https://crawford.anu.edu.au/sites/default/files/2025-01/71_2020_hall_thomson.pdf
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    Cited by:

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    2. Lars-H. R. Siemers, 2024. "On the Hamilton-HP Filter Controversy: Evidence from German Business Cycles," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 367-409, November.
    3. Viv B. Hall & Peter Thomson, 2024. "Selecting a Boosted HP Filter for Growth Cycle Analysis Based on Maximising Sharpness," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(2), pages 193-217, July.
    4. Moura, Alban, 2024. "Why You Should Never Use the Hodrick-Prescott Filter. A Comment on Hamilton (The Review of Economics and Statistics, 2018)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 3, pages 1-17.
    5. Malikane, Christopher, 2024. "Traditional output dynamics: A structural perspective," Journal of Macroeconomics, Elsevier, vol. 82(C).
    6. Viv B. Hall & Peter Thomson, 2022. "A Boosted HP Filter for Business Cycle Analysis: Evidence from New Zealand's Small Open Economy," CAMA Working Papers 2022-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Ziwei Mei & Peter C. B. Phillips & Zhentao Shi, 2022. "The boosted HP filter is more general than you might think," Papers 2209.09810, arXiv.org, revised Apr 2024.
    8. Danila Ovechkin, 2026. "Estimation and forecasting with a Nonlinear Phillips Curve based on heterogeneous sensitivity between economic activity and CPI components," Bank of Russia Working Paper Series wps161, Bank of Russia.

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    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G01 - Financial Economics - - General - - - Financial Crises

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