Question

Suppose we are estimating an OLS regression where our y-variable is an individual's wages and our explanatory variables are: X1 = years of education, X2 = years of work experience, X3 = IQ. We generate our results and want to test whether the impact of a year of education on wages is significantly different from the impact of a year of work experience. What will the null hypothesis be for this test?

A-β1≠β2
B-β1=β2
C-It is not possible to test for this unless we add an interaction term to our model
D-β1≠0,β2≠0
E-β1=β2=0

Answer 1

The null hypothesis for testing the impact of education and work experience on wages in an OLS regression is that the coefficients for the education and work experience variables are not equal in the population.

Step-by-step explanation:

The null hypothesis for testing whether the impact of a year of education on wages is significantly different from the impact of a year of work experience in an OLS regression is option A: A-β1≠β2. This hypothesis assumes that the coefficients for the years of education (β1) and years of work experience (β2) are not equal in the population. By testing this hypothesis, we are examining whether the two explanatory variables have different effects on wages.