This is important in forecasting models, because fewer independent variables must be predicted to develop the ultimate forecast for a "smaller" model.
A) Estimation
B) Smoothing
C) Parsimony
D) Volume
E) Preference

Question

Quizplus · Accepted Answer

Parsimony in forecasting models refers to the principle of using the smallest number of independent variables necessary to achieve an accurate forecast. A parsimonious model is simpler and requires fewer variables to be predicted, making the forecasting process more straightforward and potentially more accurate.

This Is Important in Forecasting Models, Because Fewer Independent Variables