|
000
| 03461nam##2200349za#4500 |
|---|
| 001 | 9.571697 |
|---|
| 003 | CaOODSP |
|---|
| 005 | 20211126112845 |
|---|
| 007 | cr ||||||||||| |
|---|
| 008 | 150406|1999||||xxc|||||o f|0| 0 eng|d |
|---|
| 022 | |a1701-9397 |
|---|
| 040 | |aCaOODSP|beng |
|---|
| 043 | |an-cn--- |
|---|
| 086 | 1 |aFB3-2/99-13E-PDF |
|---|
| 110 | 2 |aBank of Canada. |
|---|
| 245 | 14|aThe indicator models of core inflation for Canada / |h[electronic resource]|cby Richard Dion. |
|---|
| 246 | 1 |aIndicator models of core inflation for Canada |
|---|
| 260 | |aOttawa - Ontario : |bBank of Canada |cSeptember 1999. |
|---|
| 300 | |a29p.|breferences, tables |
|---|
| 490 | 1 |aBank of Canada working paper|x1701-9397|v99-13 |
|---|
| 500 | |a"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. |
|---|
| 500 | |aThe 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. |
|---|
| 520 | 3 |aWhen 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 |
|---|
| 546 | |aRésumé en français. |
|---|
| 590 | |a11-20-Supp|b2011-09-29 |
|---|
| 690 | 07|aInflation|2gcpds |
|---|
| 690 | 07|aForecasting|2gcpds |
|---|
| 690 | 07|aModels|2gcpds |
|---|
| 720 | 1 |aDion, Richard |
|---|
| 776 | 0#|tThe indicator models of core inflation for Canada / |w(CaOODSP)9.614934 |
|---|
| 830 | #0|aWorking paper (Bank of Canada)|x1701-9397|v99-13|w(CaOODSP)9.504604 |
|---|
| 856 | 40|ahttp://publications.gc.ca|qPDF|s235 KB|uhttps://publications.gc.ca/collections/Collection/FB3-2-99-13E.pdf|y99-13 |
|---|