00000nam##2200000za#4500 9.571705 CaOODSP 20211126112845 cr ||||||||||| 150406|1999||||xxc|||||o f|0| 0 eng|d 1701-9397 CaOODSP eng n-cn--- FB3-2/99-3E-PDF Bank of Canada. Forecasting GDP growth using artificial neural networks / [electronic resource] by Greg Tkacz and Sarah Hu. Ottawa - Ontario : Bank of Canada January 1999. 33p. figs., graphs, references, tables Bank of Canada working paper 1701-9397 99-3 "In this paper, the authors wish to determine whether the forecasting performance of such variables can be improved using neural network models. The main findings are that, at the 1-quarter forecasting horizon, neural networks yield no significant forecast improvements. At the 4-quarter horizon, however, the improved forecast accuracy is statistically significant. The root mean squared forecast errors of the best neural network models are about 15 to 19 per cent lower than their linear model counterparts. The improved forecast accuracy may be capturing more fundamental non-linearities between financial variables and real output growth at the longer horizon."--Abstract. The ISBN (0-662-27537-3) and ISSN (1192-5434) for the print edition have been incorrectly copied in this electronic publication. In this paper, the authors wish to determine whether the forecasting performance of such variables can be improved using neural network models. The main findings are that, at the 1-quarter forecasting horizon, neural networks yield no significant forecast improvements. At the 4-quarter horizon, however, the improved forecast accuracy is statistically significant. The root mean squared forecast errors of the best neural network models are about 15 to 19 per cent lower than their linear model counterparts. The improved forecast accuracy may be capturing more fundamental non-linearities between financial variables and real output growth at the longer horizon.--Abstract Résumé en français. 11-20-Supp 2011-09-29 Gross national product gcpds Forecasting gcpds Models gcpds Tkacz, Greg Hu, Sarah Forecasting GDP growth using artificial neural networks / (CaOODSP)9.614702 Working paper (Bank of Canada) 1701-9397 99-3 (CaOODSP)9.504604 http://publications.gc.ca PDF 200 KB https://publications.gc.ca/collections/Collection/FB3-2-99-3E.pdf 99-3