One of the sources of error in the RMSFE in the AR(1) model is
A) the error in estimating the coefficients $\beta _ { 0 } \text { and } \beta _ { 1 } \text {. }$
B) due to measuring variables in logarithms.
C) that the value of the explanatory variable is not known with certainty when making a forecast.
D) the model only looks at the previous period's value of Y when the entire history should be taken into account.

Question

One of the sources of error in the RMSFE in the AR(1) model is
A) the error in estimating the coefficients $\beta _ { 0 } \text { and } \beta _ { 1 } \text {. }$
B) due to measuring variables in logarithms.
C) that the value of the explanatory variable is not known with certainty when making a forecast.
D) the model only looks at the previous period's value of  Y  when the entire history should be taken into account.

Quizplus · Accepted Answer

The error in estimating the coefficients $\beta _ { 0 }$ and $\beta _ { 1 }$ can lead to inaccuracies in the forecast, contributing to the root mean square forecast error (RMSFE) in the AR(1) model.

One of the Sources of Error in the RMSFE in the AR(1)