00000nam##2200000za#4500 9.614934 CaOODSP 20211126112847 ta 150406|1999||||xxc||||| f|0| 0 eng|d 0-662-28177-2 1192-5434 CaOODSP eng n-cn--- FB3-2/99-13E Bank of Canada. The indicator models of core inflation for Canada / by Richard Dion. Ottawa - Ontario : Bank of Canada 1999. v, 20p. : references, tables ; 28 cm. Working paper 1192-5434 99-13 "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. 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 Softcover 99-41 1999-10-15 Inflation gcpds Forecasting gcpds Models gcpds Dion, Richard The indicator models of core inflation for Canada / (CaOODSP)9.571697 Working paper, 1192-5434 99-13 (CaOODSP)9.514622 99-13