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Tutorial 1: Stata application of linear regression The University of Queensland ECON7360
Instructor: Rigissa Megalokonomou
Problem I: Simple regression and marginal effect
Using the data in WAGE2.dta to estimate a simple regression explaining monthly salary (wage) in terms of IQ score (IQ).
(1) Find the average salary and average IQ in the sample. What is the sample standard deviation of IQ? (IQ scores are standardized so that the population’s average is 100 with a standard deviation equal to 15.)
(2) Estimate a simple regression model where an one-point increase in IQ changes wage by a constant dollar amount. Use this model to find the predicted increase in wage if IQ increases by 15 points.
(3) Now, estimate a model where each one-point increase in IQ has the same percentage effect on wage. If IQ increases by 15 points, what is the approximate percentage increase in predicted wage?
2 Problem III: Multiple regression and Omitted Vari- able bias
Use the data set in WAGE2.dta for this problem. As usual, be sure all of the following regressions contain an intercept.
(1) Run a simple regression of IQ in educ to obtain the slope coefficient.
(2) Run the simple regression of log(wage) on educ, and obtain the slope coefficient.
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(3) Run the multiple regression of log(wage) on educ and IQ, and obtain the new slope coefficients.
3 Problem III: Multiple regression and Inference
Use the data set in WAGE2.dta for this problem. As usual, be sure all of the following regressions contain an intercept.
(1) Consider the standard wage equation:
log(wage) = β0 + β1educ + β2exper + β3tenure + u
State the null hypothesis that another year of general workforce experience has the same effect on log(wage) as another year of tenure with the current employer.
(2) Find the 95% confidence interval for educ, exper and tenure.
(3) Consider a model where the return to education depends upon the amount of work
experience:
Find the 95% confidence interval for educ*exper. What is the return of another year of
log(wage) = β0 + β1educ + β2exper + β3(educ ∗ exper) + u education, while holding exper fixed?
(4) Using the estimation model in (3), state the null hypothesis that the return to education does not depend on the level of exper. Test this hypothesis.
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