The indicator models of core inflation for Canada / by Richard Dion. : FB3-2/99-13E-PDF
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=9.571697&sl=1
Ministère/Organisme | Bank of Canada. |
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Titre | The indicator models of core inflation for Canada / by Richard Dion. |
Variante du titre | Indicator models of core inflation for Canada |
Titre de la série | Bank of Canada working paper1701-939799-13 |
Type de publication | Série - Voir l'enregistrement principal |
Langue | [Anglais] |
Format | Électronique |
Document électronique | |
Autres formats offerts | Papier-[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. The catalogue number (FB3-2/99-13E), ISBN (0-662-28177-2), and ISSN (1192-5434) for the print edition have been incorrectly copied in this electronic publication. Résumé en français. |
Information sur la publication | Ottawa - Ontario : Bank of Canada September 1999. |
Description | 29p.references, tables |
ISSN | 1701-9397 |
Numéro de catalogue |
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Descripteurs | Inflation Forecasting Models |