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| 03132nam##2200349za#4500 |
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| 001 | 9.614934 |
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| 003 | CaOODSP |
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| 005 | 20211126112847 |
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| 007 | ta |
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| 008 | 150406|1999||||xxc||||| f|0| 0 eng|d |
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| 020 | |a0-662-28177-2 |
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| 022 | |a1192-5434 |
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| 040 | |aCaOODSP|beng |
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| 043 | |an-cn--- |
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| 086 | 1 |aFB3-2/99-13E |
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| 110 | 2 |aBank of Canada. |
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| 245 | 14|aThe indicator models of core inflation for Canada / |cby Richard Dion. |
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| 260 | |aOttawa - Ontario : |bBank of Canada |c1999. |
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| 300 | |av, 20p. : |breferences, tables ; |c28 cm. |
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| 490 | 1 |aWorking paper|x1192-5434|v99-13 |
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| 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. |
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| 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 |
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| 546 | |aRésumés en français |
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| 563 | |aSoftcover |
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| 590 | |a99-41|b1999-10-15 |
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| 690 | 07|aInflation|2gcpds |
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| 690 | 07|aForecasting|2gcpds |
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| 690 | 07|aModels|2gcpds |
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| 720 | 1 |aDion, Richard |
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| 776 | 0#|tThe indicator models of core inflation for Canada / |w(CaOODSP)9.571697 |
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| 830 | #0|aWorking paper,|x1192-5434|v99-13|w(CaOODSP)9.514622 |
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