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A Framework for Forecasting the Components of the Consumer Price

  • Janine Aron

    (Centre for the Study of African Economies)

  • John Muellbauer

    (Nuffield College, University of Oxford)

  • Coen Pretorius

    (South African Reserve Bank, Pretoria, South Africa)

Inflation is a far from homogeneous phenomenon, but this fact is ignored in most work on consumer price inflation. Using a novel methodology grounded in theory, the ten sub-components of the consumer price index (excluding mortgage interest rates, or CPIX) for South Africa are modeled separately and forecast, four quarters ahead. The method combines equilibrium correction models in a rich multivariate form with the use of stochastic trends estimated by the Kalman filter to capture structural breaks and institutional change. This research is of considerable practical use for monetary policy, allowing sectoral sources of inflation to be identified. Aggregating the forecasts of the components with appropriate weights from the overall index, potentially indicates the gains to be made in forecasting the idiosyncratic sectoral behaviour of prices, over forecasting the overall consumer price index.

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Paper provided by EconWPA in its series Development and Comp Systems with number 0409054.

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Length: 63 pages
Date of creation: 28 Sep 2004
Date of revision:
Handle: RePEc:wpa:wuwpdc:0409054
Note: Type of Document - pdf; pages: 63
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  1. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
  2. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  3. Janine Aron & John Muellbauer, 2004. "Construction of CPIX Data for Forecasting and Modelling in South Africa," Development and Comp Systems 0409056, EconWPA.
  4. Janine Aron & John Muellbauer, 2002. "Interest Rate Effects on Output: Evidence from a GDP Forecasting Model for South Africa," Economics Series Working Papers WPS/2002-04, University of Oxford, Department of Economics.
  5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  6. Chevalier, Judith A & Scharfstein, David S, 1996. "Capital-Market Imperfections and Countercyclical Markups: Theory and Evidence," American Economic Review, American Economic Association, vol. 86(4), pages 703-25, September.
  7. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  8. Michael F. Bryan & Stephen G. Cecchetti, 1999. "Inflation And The Distribution Of Price Changes," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 188-196, May.
  9. Marvin J. Barth III & Valerie A. Ramey, 2002. "The Cost Channel of Monetary Transmission," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 199-256 National Bureau of Economic Research, Inc.
  10. Janine Aron & John Muellbauer, 2000. "Personal and Corporate Saving in South Africa," World Bank Economic Review, World Bank Group, vol. 14(3), pages 509-544, September.
  11. Christopher A. Sims, 1996. "Macroeconomics and Methodology," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 105-120, Winter.
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  13. Zellner, Arnold & Chen, Bin, 2001. "Bayesian Modeling Of Economies And Data Requirements," Macroeconomic Dynamics, Cambridge University Press, vol. 5(05), pages 673-700, November.
  14. Johannes Fedderke & Chandana Kularatne & Martine Mariotti, 2007. "Mark-up Pricing in South African Industry," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 16(1), pages 28-69, January.
  15. Janine Aron & John Muellbauer, 2000. "Inflation and output forecasts for South Africa: monetary transmission implications," CSAE Working Paper Series 2000-23, Centre for the Study of African Economies, University of Oxford.
  16. repec:cup:cbooks:9780521632423 is not listed on IDEAS
  17. Janine Aron & John Muellbauer, 2000. "Financial Liberalization, Consumption and Debt in South Africa," Economics Series Working Papers WPS/2000-22, University of Oxford, Department of Economics.
  18. Clements, Michael P & Hendry, David F, 1996. "Multi-step Estimation for Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 657-84, November.
  19. Zellner, Arnold & Tobias, Justin, 2004. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12371, Iowa State University, Department of Economics.
  20. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  21. Weiss, Andrew A., 1991. "Multi-step estimation and forecasting in dynamic models," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 135-149.
  22. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  23. Antoni Espasa & Rebeca Albacete, 2004. "Econometric Modelling For Short-Term Inflation Forecasting In The Emu," Statistics and Econometrics Working Papers ws034309, Universidad Carlos III, Departamento de Estadística y Econometría.
  24. repec:cup:macdyn:v:5:y:2002:i:05:p:673-700_03 is not listed on IDEAS
  25. J.W. Fedderke & E. Schaling, 2005. "Modelling Inflation In South Africa: A Multivariate Cointegration Analysis," South African Journal of Economics, Economic Society of South Africa, vol. 73(1), pages 79-92, 03.
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