Time-Varying Parameters and the Out-of-Sample Forecasting Performance of Structural Exchange Rate Models
时变参数与结构汇率模型的样本外预测表现
Varying-parameter estimation techniques based on recursive application of the Kalman filter are used to improve the predictive performance of a class of monetary exchange rate models. I find that allowing estimated parameters to vary over time enhances the models' forecasting performance for the dollar–pound, dollar–mark, and dollar–yen exchange rates. Contrary to earlier results in the literature, ex-post forecasts for the dollar-mark rate compare favorably with those…