- Publications and Research
|Author(s)||Ali Dib, Mohamed Gammoudi, Kevin Moran|
|Date of publication||March 2006|
The authors document the out-of-sample forecasting accuracy of the New Keynesian model for Canada. They estimate their variant of the model on a series of rolling subsamples, computing out-of-sample forecasts one to eight quarters ahead at each step. They compare these forecasts with those arising from simple vector autoregression (VAR) models, using econometric tests of forecasting accuracy. Their results show that the forecasting accuracy of the New Keynesian model compares favourably with that of the benchmarks, particularly as the forecasting horizon increases. These results suggest that the model could become a useful forecasting tool for Canadian time series. The authors invoke the principle of parsimony to explain their findings.
|Bank topic index||Topics: Business fluctuations and cycles; Econometric and statistical methods; Economic models|
|JEL classification||E32, E37, C12|