11. Testing multiple exclusion restrictions with the F test and R-squared figures Suppose your friend Alex needs your assistance testing five exclusion restrictions in a multiple linear regression model at the 95% level. Specifically, his null hypothesis is that B6 ,..., ₁0 are all equal to 0, after controlling for the independent variables ₁,..., 5. The original, unrestricted model consisted of 10 population slope parameters, ₁ ,..., B10, plus an intercept parameter Bo and was estimated using a random sample of 420 observations. You ask Alex for the residual sum of squares from the restricted and unrestricted models. He says he lost those figures, but he did save the R-squared values. The R-squared for the unrestricted model is 0.237, while the R-squared for the restricted model is 0.234. Since the unrestricted model has degrees of freedom, while the restricted model has degrees of freedom, you know that the number of exclusion restrictions must be q= reject fail to reject Note: The critical value for the F-distribution, at the 95% level, is 2.6. he should the null hypothesis that After computing the F-statistic, you advise Alex that because the F-statistic is B6..... B10 are jointly insignificant.