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Optimal HP filtering for South Africa

Author

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  • Leon du Toit

    (Department of Economics, Stellenbosch University)

Abstract

Among the various methods used to identify the business cycle from aggregate data, the Hodrick-Prescott filter has become an industry standard – it ‘identifies’ the business cycle by removing low-frequency information, thereby smoothing the data. Since the filter’s inception in 1980, the value of the smoothing constant for quarterly data has been set at a ‘default’ of 1600, following the suggestion of Hodrick and Prescott (1980). This paper argues that this ‘default value’ is inappropriate due to its ad hoc nature and problematic underlying assumptions. Instead this paper uses the method of optimal filtering, developed by Pedersen (1998, 2001, and 2002), to determine the optimal value of the smoothing constant for South Africa. The optimal smoothing constant is that value which least distorts the frequency information of the time series. The result depends on both the censoring rule for the duration of the business cycles and the structure of the economy. The paper raises a number of important issues concerning the practical use of the HP filter, and provides an easily replicable method in the form of MATLAB code.

Suggested Citation

  • Leon du Toit, 2008. "Optimal HP filtering for South Africa," Working Papers 07/2008, Stellenbosch University, Department of Economics.
    • Handle: RePEc:sza:wpaper:wpapers55
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    File URL: https://www.ekon.sun.ac.za/wpapers/2008/wp072008/wp-07-2008.pdf
    File Function: First version, 2008
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    Citations

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    Cited by:

    1. Harun Alp & Yusuf Soner Baskaya & Mustafa Kilinc & Canan Yuksel, 2011. "Turkiye Icin Hodrick-Prescott Filtresi Duzgunlestirme Parametresi Tahmini," CBT Research Notes in Economics 1103, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    2. Leon du Toit, 2009. "Economic Crises, Stabilisation Policy and Output in Emerging Market Economies," Working Papers 20/2009, Stellenbosch University, Department of Economics.
    3. Yiming Liu & Longxin Wang & Yunsong Jia & Ziwen Li & Hongju Gao, 2021. "Dynamic Influence Ranking Algorithm Based on Musicians’ Social and Personal Information Network," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    4. Harun Alp & Yusuf Soner Baskaya & Mustafa Kilinc & Canan Yuksel, 2012. "Stylized Facts for Business Cycles in Turkey," Working Papers 1202, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Cobus Vermeulen, 2023. "The inherent uncertainties in output gap estimation a South African perspective," Working Papers 11051, South African Reserve Bank.
    6. Byron Botha & Eric Schaling, 2020. "Commodity Prices and Policy Stabilisation in South Africa," Working Papers 10225, South African Reserve Bank.
    7. Johannes W. Fedderke, 2022. "Identifying steady‐state growth and inflation in the South African economy, 1960–2020," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 279-300, September.
    8. Adél Bosch & Steven F. Koch, 2020. "The South African Financial Cycle and its Relation to Household Deleveraging," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 145-173, June.

    More about this item

    Keywords

    Hodrick-Prescott filter; Spectral analysis; Ideal filtering; Optimal filtering; Distortionary filtering; Business cycles; MATLAB;
    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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