Question

Causal relationships are potentially useful for which component of a time series?

Short answer

Answer

Casual relationships forecasting involves using independent variables other than time to predict future demand.

Step-by-step solution

Definition of forecast errors

In casual relationship forecasting, to be worthy of forecasting, any variable must be a number one indicator.

For example, we will expect that an extended period of rain will increase sales of umbrellas and raincoats. The rain causes the sale of rain gear. This can be a causal relationship, where one occurrence causes another.

Implications do forecast errors have for the statistical forecasting models

All forecast contains some errorswhether the model is simple or sophisticated because the forecast is a prediction of the long run supported by past data. Forecast errors are often caused by changes in conditions that generated the past data.

As an example, an economic recession could change the demand certainly of unnecessary products.

Fact that every forecast models have some error, regardless of what a forecaster does, they will not predict all events within the future which can cause demand to fluctuate.