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The indicator models of core inflation for Canada / by Richard Dion. : FB3-2/99-13E

When there is uncertainty about estimates of the margin of unused capacity in the economy, examining a range of inflation indicators may help in assessing the balance of risks regarding the outlook for inflation. This paper tests a wide range of observable variables for their leading-indicator properties with respect to core inflation, including: commodity prices, cost indicators, measures of capacity pressures in labour and product markets, and components of the consumer price index (CPI) itself. After a preliminary screening of indicators using Granger causality tests, estimated bivariate indicator models generate post-sample static forecasts one quarter ahead and two quarters ahead over the period 1995 (Q1). A ridge regression technique is used to optimally combine selected bivariate forecasts into multivariate forecasts. The root-mean-squared errors of both the bivariate and multivariate forecasts are compared with those of benchmark models -- a Phillips curve, an autoregressive model, and two naive models.--Abstract

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publications.gc.ca/pub?id=9.614934&sl=1

Renseignements sur la publication
Ministère/Organisme
  • Bank of Canada.
TitreThe indicator models of core inflation for Canada / by Richard Dion.
Titre de la série
  • Working paper 1192-5434 99-13
Type de publicationMonographie - Voir l'enregistrement principal
Langue[Anglais]
FormatTexte matériel
Autres formats offertsTexte numérique-[Anglais]
Note(s)
  • "When there is uncertainty about estimates of the margin of unused capacity in the economy, examining a range of inflation indicators may help in assessing the balance of risks regarding the outlook for inflation. This paper tests a wide range of observable variables for their leading-indicator properties with respect to core inflation, including: commodity prices, cost indicators, measures of capacity pressures in labour and product markets, and components of the consumer price index (CPI) itself. After a preliminary screening of indicators using Granger causality tests, estimated bivariate indicator models generate post-sample static forecasts one quarter ahead and two quarters ahead over the period 1995 (Q1). A ridge regression technique is used to optimally combine selected bivariate forecasts into multivariate forecasts. The root-mean-squared errors of both the bivariate and multivariate forecasts are compared with those of benchmark models -- a Phillips curve, an autoregressive model, and two naive models."--Abstract.
  • Résumés en français
Information sur la publication
  • Ottawa - Ontario : Bank of Canada 1999.
ReliureSoftcover
Descriptionv, 20p. : references, tables ; 28 cm.
ISBN0-662-28177-2
ISSN1192-5434
Numéro de catalogue
  • FB3-2/99-13E
Numéro de catalogue du ministère99-13
Descripteurs
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