Contribution of each beta coefficient to the model's R2?

[PCA]

Does anyone know of a way to calculate this in EViews?

I am trying to find the individual contribution of each beta coefficient to the overall R2 of the model. In other words, if a model has 4 statistically significant explanatory variables, how much does each one of those contribute to the model as a whole?

[startz]

This is a good question, but unfortunately it doesn't have a unique answer unless the right hand side variables are uncorrelated.

[PCA]

Assuming they aren't correlated, is the only way to figure out their individual contribution to the R2 figure by stepping each variable into the regression one at a time?


Take a peek at the attachment picture - does that seem logical?

[startz]

If they're uncorrelated--which is unusual--you can just run separate regressions on each explanatory variable and use the R^2 from each.

[PCA]

Does EViews calculate the partial sum of squares or sequential sum of squares for variables?