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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| Department/Agency | Bank of Canada. |
|---|---|
| Title | The indicator models of core inflation for Canada / by Richard Dion. |
| Variant title | Indicator models of core inflation for Canada |
| Series title | Bank of Canada working paper1701-939799-13 |
| Publication type | Series - View Master Record |
| Language | [English] |
| Format | Electronic |
| Electronic document | |
| Other formats | Paper-[English] |
| 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. |
| Publishing information | Ottawa - Ontario : Bank of Canada September 1999. |
| Description | 29p.references, tables |
| ISSN | 1701-9397 |
| Catalogue number |
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| Subject terms | Inflation Forecasting Models |