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New methods for forecasting inflation and its sub-components: application to the USA

  • Janine Aron
  • John Muellbauer

Forecasts are presented for the 12-month ahead US rate of inflation measured by the chain weighted personal consumer expenditure deflator, PC, and its three main components: non-durable goods, durable goods and services.� Monthly models are estimated for 1974 to 1999, and pseudo out-of-sample forecasting performance is examined for 2000-2007.� Alternative forecasting approaches for a number of different information sets are compared with benchmark univariate autoregressive models.� In general, substantial out-performance is demonstrated for the aggregate and components models relative to benchmark models.� The combination of equilibrium correction terms, which bring gradual adjustment of relative prices into the inflation process, and non-linearities, to proxy state dependence in the inflation process, is shown to contribute importantly to this out-performance.� There is also evidence that forecast pooling or averaging improves forecast performance.� The indirect forecasts constructed by weighting the three component forecasts are compared with the direct forecasts from the aggregate PC.� In most cases, the indirect method outperforms the direct method.� A key innovation is to compare standard AR or VAR methods of using an information criterion to select the large length, with a parameterization in which longer lags appear in parsimonious forms.� Another is to compare general unrestricted models with corresponding parsimonious models selected by Autometrics, Doornik (2008).

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File URL: http://www.economics.ox.ac.uk/materials/working_papers/paper406.pdf
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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 406.

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Date of creation: 01 Oct 2008
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Handle: RePEc:oxf:wpaper:406
Contact details of provider: Postal: Manor Rd. Building, Oxford, OX1 3UQ
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