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Forecasting South African Inflation

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  • GEOFFREY WOGLOM

Abstract

This paper looks at what variables are useful for forecasting inflation starting in 1990. I show that the output gap, a measure of real economic conditions, does seem to provide useful information for forecasting inflation. This is good news for the Reserve Bank, since the primary way that the Reserve Bank tries to affect future inflation is through real economic conditions. In addition, short‐term interest rates and import price inflation also seem to provide useful information. The most accurate of these forecasts suggests a root mean square forecast error of 1–2 per cent for 1‐year ahead inflation, which is within the Reserve Bank's current target range.

Suggested Citation

  • Geoffrey Woglom, 2005. "Forecasting South African Inflation," South African Journal of Economics, Economic Society of South Africa, vol. 73(2), pages 302-320, June.
    • Handle: RePEc:bla:sajeco:v:73:y:2005:i:2:p:302-320
    DOI: 10.1111/j.1813-6982.2005.00019.x
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    Cited by:

    1. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
    2. repec:ipg:wpaper:2014-471 is not listed on IDEAS
    3. Stan du Plessis & Ben Smit & Federico Sturzenegger, 2007. "Identifying aggregate supply and demand shocks in South Africa," Working Papers 11/2007, Stellenbosch University, Department of Economics.
    4. Patrick T. Kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2016. "Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2412-2427, June.
    5. 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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