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Multi-sector inflation forecasting - quarterly models for South Africa

  • Janine Aron
  • John Muellbauer

Inflation is a far from homogeneous phenomenon, a fact often neglected in modeling consumer price inflation.� Using a novel methodology grounded in theory, the ten sub-components of the consumer price index (excluding mortgage interest rates), are modeled separately and forecast, four-quarters-ahead.� Equilibrium correction models in a rich multivariate form employ general and sectoral information, and take account of structural breaks and institutional changes.� Our methods allow for longer lags than conventionally considered in VARs, but in a parsimonious manner.� Sign priors are imposed on long-run effects and automatic model selection is used to select parsimonious models from more general ones.� The models throw light on sectoral sources of inflation, useful to monetary policy.� Data for 1979 to 2003 are used for model selection, and pseudo out of sample forecasting performance to the end of 2007 is examined.� Aggregating the weighted sub-component forecasts indicates gains are made over forecasting the overall index using these methods, and also substantial gains over forecasting using benchmark naive models.� To extend this work, including sectoral information such as an explicit treatment of tax policy, regulatory information and announced administred price rises, should further enhance these forecasting methods.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number WPS/2008-27.

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Date of creation: 01 Oct 2008
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Handle: RePEc:oxf:wpaper:wps/2008-27
Contact details of provider: Postal: Manor Rd. Building, Oxford, OX1 3UQ
Web page: http://www.economics.ox.ac.uk/
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  1. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  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 657-84, November.
  3. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  4. 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.
  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.
  6. 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.
  7. Janine Aron & John Muellbauer & Coen Pretorius, 2004. "A Framework for Forecasting the Components of the Consumer Price Index: application to South Africa," Economics Series Working Papers WPS/2004-07, University of Oxford, Department of Economics.
  8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  9. Christopher A. Sims, 1996. "Macroeconomics and Methodology," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 105-120, Winter.
  10. 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.
  11. repec:cup:cbooks:9780521634809 is not listed on IDEAS
  12. Weiss, Andrew A., 1991. "Multi-step estimation and forecasting in dynamic models," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 135-149.
  13. Janine Aron & John Muellbauer, 2008. "New methods for forecasting inflation and its sub-components: application to the USA," Economics Series Working Papers 406, University of Oxford, Department of Economics.
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