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A Framework for Forecasting the Components of the Consumer Price Index: application to South Africa

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  • Janine Aron
  • John Muellbauer
  • Coen Pretorius

Abstract

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.

Suggested Citation

  • Janine Aron & John Muellbauer & Coen Pretorius, 2004. "A Framework for Forecasting the Components of the Consumer Price Index: application to South Africa," CSAE Working Paper Series 2004-07, Centre for the Study of African Economies, University of Oxford.
    • Handle: RePEc:csa:wpaper:2004-07
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    File URL: https://ora.ox.ac.uk/objects/uuid:7936fc1a-1056-4027-ab30-0ab8aa909195
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    References listed on IDEAS

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    1. Weiss, Andrew A., 1991. "Multi-step estimation and forecasting in dynamic models," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 135-149.
    2. 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 657-684, November.
    3. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, January.
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    Cited by:

    1. 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.
    2. 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.

      More about this item

      JEL classification:

      • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
      • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
      • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
      • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
      • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
      • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
      • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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