Tham khảo tài liệu 'real estate modelling and forecasting by chris brooks and sotiris tsolacos_10', tài chính - ngân hàng, đầu tư bất động sản phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Forecast evaluation 299 Table Mean forecast errors for the changes in rents series Steps ahead 1 2 3 4 5 6 7 8 a LaSalle Investment Management rents series VAR 1 VAR 2 AR 2 Long-term mean Random walk b CB Hillier Parker rents series VAR 1 AR 2 Long-term mean Random walk forecast is made in 1Q97 for the period 2Q97 to 1Q99 . In this way forty-four one-quarter forecasts forty-four two-quarter forecasts and so forth are calculated. The forty-four one-quarter forecasts are compared with the realised data for each of the four methodologies. This is repeated for the two-quarter- three-quarter- . . . and eight-quarter-ahead computed values. This comparison reveals how closely rent predictions track the corresponding historical rent changes over the different lengths of the forecast horizon one to eight quarters . The mean forecast error the mean squared forecast error and the percentage of correct sign predictions are the criteria employed to select the best performing models. Ex ante forecasts of retail rents based on all methods are also made for eight quarters from the last available observation at the time that the study was written. Forecasts of real retail rents are therefore made for the periods 1999 quarter two to 2001 quarter one. An evaluation of the forecasts obtained from the different methodologies is presented in tables to . Table reports the MFE. As noted earlier a good forecasting model should have a mean forecasting error of zero. The first .
