Consider a k-variables linear regression model, i.e., Y = X 1β1 + X 2 β2 + ε, Where, X1 is (N k1 ) , X 2 is (N k2 ) and k = k1 + k2 . As you may recall, adding columns to the X matrix (including additional regressors in the model) gives positive definite increase in R2. The adjusted R2 ( R 2 ) attempts to avoid this phenomenon of ever increase in R2. Show that the additional k2 number of variables (regressors) in this model increases R 2 if the calculated F-statistic in testing the joint statistical significance of coefficients of these additional regressors (β2 ) is larger than one.
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