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
Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.614934&sl=1
Ministère/Organisme | Bank of Canada. |
---|---|
Titre | The indicator models of core inflation for Canada / by Richard Dion. |
Titre de la série | Working paper1192-543499-13 |
Type de publication | Série - Voir l'enregistrement principal |
Langue | [Anglais] |
Format | Papier |
Autres formats offerts | Électronique-[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. |
Reliure | Softcover |
Description | v, 20p. : references, tables ; 28 cm. |
ISBN | 0-662-28177-2 |
ISSN | 1192-5434 |
Numéro de catalogue |
|
Numéro de catalogue du ministère | 99-13 |
Descripteurs | Inflation Forecasting Models |