Computer Exercise - 3

Description: This computer exercise is meant to help you learn 1 ) how to perform hypothesis testing and 2) the difference between individual significance and joint significance of the estimated coefficients in a multiple regression model.

1. Check out the description of all the relevant variables in this exercise.
2. Estimate the following wage equation, using the dataset wage 2.wf1.
   \(\text { lwage }=\alpha+\beta_{1} \text { age }+\beta_{2} e d u c+\beta_{3} \text { exper }+\beta_{4} \text { feduc }+\beta_{5} \text { meduc }+\beta_{6} u r b a n+\beta_{7} i q+u\)
   Assume two-sided alternatives and a \(5 \%\) significance level for all the following tests.
3. Test the significance of the coefficient for father's education feduc, \(\beta_{4}\) : write down the null hypothesis and interpret your test results. (Hint: After estimating the regression equation, go to View \(\rightarrow\) Coefficient Tests \(\rightarrow\) Wald-Coefficient Restrictions...)
4. Test the significance of the coefficient on mother's education meduc, \(\beta_{5}\) : write down the null hypothesis and interpret your test results.

Finally, test the joint significance of \(\beta_{4}\) and \(\beta_{5}\) : write down the null hypothesis and interpret your test results.

Are \(\beta_{4}\) and \(\beta_{5}\) individually significant at the \(5 \%\) level? Are they jointly significant at the \(5 \%\) level? What conclusion would you draw?

Price: $13.19

Solution: The downloadable solution consists of 8 pages, 519 words.
Deliverable: Word Document