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Measuring Core Inflation in South Africa

Author

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  • Stan Plessis
  • Gideon Rand
  • Kevin Kotzé

Abstract

Measures of core inflation convey critical information about an economy. They have a direct effect on the policymaking process, particularly in inflation-targeting countries, and are utilised in forecasting and modelling exercises. In South Africa, the price indices on which inflation is based have been subject to important structural breaks following changes to the underlying basket of goods and the methodology for constructing price indices. This paper seeks to identify a consistent measure of core inflation for South Africa using trimmed means estimates, measures that exclude changes in food and energy prices, dynamic factor models, and wavelet decompositions. After considering the forecasting ability of these measures, which provide an indication of expected second-round inflationary effects, traditional in-sample criteria were used for further comparative purposes. The results suggest that wavelet decompositions provide a useful measure of this critical variable.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:sajeco:v:83:y:2015:i:4:p:527-548
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    File URL: http://hdl.handle.net/10.1111/saje.12090
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    References listed on IDEAS

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    1. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2005. "A Core Inflation Indicator for the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 539-560, June.
    2. Amstad, Marlene & Fischer, Andreas M, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment," CEPR Discussion Papers 4627, C.E.P.R. Discussion Papers.
    3. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    4. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    5. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    6. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    7. Ramsey, James B. & Zhang, Zhifeng, 1997. "The analysis of foreign exchange data using waveform dictionaries," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 341-372, December.
    8. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    9. 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.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Baqaee, David, 2010. "Using wavelets to measure core inflation: The case of New Zealand," The North American Journal of Economics and Finance, Elsevier, vol. 21(3), pages 241-255, December.
    12. Logan Rangasamy, 2009. "Inflation Persistence And Core Inflation: The Case Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 430-444, September.
    13. Mick Silver, 2007. "Core Inflation: Measurement and Statistical Issues in Choosing Among Alternative Measures," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 163-190, May.
    14. repec:hal:journl:peer-00844811 is not listed on IDEAS
    15. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    16. 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.
    17. Ben S. Bernanke & Mark Gertler, 1999. "Monetary policy and asset price volatility," Economic Review, Federal Reserve Bank of Kansas City, vol. 84(Q IV), pages 17-51.
    18. 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.
    19. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 49-71, March.
    20. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    21. Logan Rangasamy, 2011. "Food Inflation In South Africa: Some Implications For Economic Policy," South African Journal of Economics, Economic Society of South Africa, vol. 79(2), pages 184-201, June.
    22. Marlene Amstad & Simon M. Potter, 2009. "Real time underlying inflation gauges for monetary policymakers," Staff Reports 420, Federal Reserve Bank of New York.
    23. 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.

      Citations

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      Cited by:

      1. Francis Leni Anguyo & Rangan Gupta & Kevin Kotzé, 2020. "Inflation dynamics in Uganda: a quantile regression approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 13(2), pages 161-187, May.
      2. Franz Ruch & Stan du Plessis, 2015. "SecondRound Effects from Food and Energy Prices an SBVAR approach," Working Papers 7008, South African Reserve Bank.
      3. Ladi R. Bala-Keffi & Donald G. Mbaka & Nuruddeen Usman, 2020. "Alternative Core Inflation Measures in Nigeria: An Examination," Applied Economics and Finance, Redfame publishing, vol. 7(4), pages 112-120, July.
      4. Mehmet Balcilar & Rangan Gupta & Kevin Kotzé, 2017. "Forecasting South African macroeconomic variables with a Markov-switching small open-economy dynamic stochastic general equilibrium model," Empirical Economics, Springer, vol. 53(1), pages 117-135, August.

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