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A Note On The Trimmed Mean Measure Of Core Inflation In South Africa

Author

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  • Zelda Blignaut
  • Greg Farrell
  • Victor Munyama
  • Logan Rangasamy

Abstract

This paper constructs and analyses the properties of a trimmed mean inflation rate for South Africa. Based on an analysis of the distributions of the consumer price index component price changes, a measure is constructed that provides an estimator of core inflation, which may be particularly useful to policymakers in an inflation‐targeting environment. The trimmed mean estimator focuses on the price movements of individual components that have a strong bearing on the current and future trend of the headline inflation rate, allowing monetary policy to be directed at the persistent or underlying sources of inflationary pressures.

Suggested Citation

  • Zelda Blignaut & Greg Farrell & Victor Munyama & Logan Rangasamy, 2009. "A Note On The Trimmed Mean Measure Of Core Inflation In South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(4), pages 538-552, December.
  • Handle: RePEc:bla:sajeco:v:77:y:2009:i:4:p:538-552
    DOI: 10.1111/j.1813-6982.2009.01230.x
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    References listed on IDEAS

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    1. Mark A. Wynne, 2008. "Core inflation: a review of some conceptual issues," Review, Federal Reserve Bank of St. Louis, vol. 90(May), pages 205-228.
    2. Robalo Marques, Carlos & Duarte Neves, Pedro & Morais Sarmento, Luis, 2003. "Evaluating core inflation indicators," Economic Modelling, Elsevier, vol. 20(4), pages 765-775, July.
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    5. Janine Aron & John Muellbauer, 2004. "Construction Of Cpix Data For Forecasting And Modelling In South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 72(5), pages 884-912, December.
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    7. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins II, 1997. "Efficient Inflation Estimation," NBER Working Papers 6183, National Bureau of Economic Research, Inc.
    8. Jonathan Kearns, 1998. "The Distribution and Measurement of Inflation," RBA Research Discussion Papers rdp9810, Reserve Bank of Australia.
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    10. Stephen G. Cecchetti, 1997. "Measuring short-run inflation for central bankers," Review, Federal Reserve Bank of St. Louis, issue May, pages 143-155.
    11. Ivan Roberts, 2005. "Underlying Inflation: Concepts, Measurement and Performance," RBA Research Discussion Papers rdp2005-05, Reserve Bank of Australia.
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    13. Janine Aron & John Muellbauer, 2004. "Construction Of Cpix Data For Forecasting And Modelling In South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 72(5), pages 884-912, December.
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    Cited by:

    1. Franz Ruch & Stan du Plessis, 2015. "SecondRound Effects from Food and Energy Prices an SBVAR approach," Working Papers 7008, South African Reserve Bank.
    2. Franz Ruch & Dirk Bester, 2013. "Towards a Measure of Core Inflation using Singular Spectrum Analysis," South African Journal of Economics, Economic Society of South Africa, vol. 81(3), pages 307-329, September.
    3. Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2016. "Analyzing South Africa’s inflation persistence using an ARFIMA model with Markov-switching fractional differencing parameter," Journal of Developing Areas, Tennessee State University, College of Business, vol. 50(1), pages 47-57, January-M.
    4. Stan Plessis & Gideon Rand & Kevin Kotzé, 2015. "Measuring Core Inflation in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 527-548, December.
    5. Stan du Plessis, 2014. "Targeting core inflation in emerging market economies," Working Papers 23/2014, Stellenbosch University, Department of Economics.
    6. Franz Ruch & Mehmet Balcilar & Rangan Gupta & Mampho P. Modise, 2020. "Forecasting core inflation: the case of South Africa," Applied Economics, Taylor & Francis Journals, vol. 52(28), pages 3004-3022, June.

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