NO.PZ2024082801000009
问题如下：
Question An analyst is comparing the out-of-sample forecasting performance of an AR(1) model and an AR(2) model for monthly inflation rates. Which of the following metrics is the most appropriate for making this comparison?选项：
A.A. R2 B.B.Durbin–Watson statistic C.C.Root mean squared error解释：
A is Incorrect because a model's R2 measures how much of the variation in the dependent variable is attributable to the independent variable(s), not the relative difference in the out-of-sample forecasting performance between models.
B is Incorrect because a model's Durbin–Watson statistic tests whether the regression errors are serially correlated, not whether the out-of-sample forecasting performance of one model is better than that of another model.
C is Correct because, typically, we compare the out-of-sample forecasting performance of forecasting models by comparing their root mean squared error (RMSE), which is the square root of the average squared error. The model with the smallest RMSE is judged the most accurate.
RT
