Econ 262 Problem Set 2 Question 2022

Running head: PROBLEM SET 2 1
Econ 262 Problem Set 2
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PROBLEM SET 2 2
Question 1.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.938548
R Square 0.880872
Adjusted R
Square 0.874025
Standard Error 0.161936
Observations 93
ANOVA
df SS MS F
Significance
F
Regression 5 16.86961 3.373921 128.6612 1.1981E-38
Residual 87 2.281426 0.026223
Total 92 19.15103
Coefficients
Standard
Error t Stat P-value Lower 95%
Upper
95%
Intercept 7.843855 0.120248 65.23076 1.16E-75 7.60484952 8.082861
educ 0.016908 0.007887 2.143738 0.034844 0.00123145 0.032585
exp 0.004575 0.000188 24.39259 1.15E-40 0.00420241 0.004948
ln(months) 0.053937 0.017932 3.007872 0.00344 0.01829531 0.089579
male 0.175624 0.037881 4.63621 1.24E-05 0.10033163 0.250917
age -0.00075 0.001251 -0.59882 0.55085 -0.0032344 0.001737
Question 1a.
The adjusted R-squared shows that the independent variables could explain 88.09% of the
ln(salary) sources of variation. The adjusted R-squared is a better measure than r-squared
since it is adjusted for the number of independent variables in the model.
Question 1b.
H0: β(age) > 0, Ha: β(age) <= 0. When the p-value is less than α=0.05, the null hypothesis
should be rejected.
The results show that there is insufficient evidence to conclude (reject the null hypothesis)
that older workers are discriminated (β(age) = -0.00075 t (87) = -0.59882, p = 0.55085).
This shows that the average pay among older and younger workers is not significantly

PROBLEM SET 2 3
different. Also, the coefficient 95% confidence interval contains a zero, which support that
the salary difference is not statistically different (95% CI = [-0.0032344 0.001737]).
Question 1c.
First, we assess whether the experience coefficient is statistically significant. There is no
sufficient evidence to show that the coefficient is not statistically significant (β (exp) =
0.004575, t (87) = 24.39259, p < 0.05). This means that people with different age earn
differently. Therefore, Tammy earns more money than Bob based on experience.
Question 1d.
The β (months) coefficient is positive. This is an indication that as the number of months at
the company increases the salary is expected to increase. In this case, the salary is expected to
increase by exp(5%*0.053937) = exp(0.00269685) = 1.00270. Thus, the salary is expected to
increase by approximately $1.00.
Question 1e.
educ exp ln(months) male age
Average 12.50538 101.0344 2.509722 0.344086 40.42182
ln(salary) = 7.843855+ 0.016908(edu) + 0.004575(exp) + 0.053937(ln(month)) +
0.175624(male) - 0.00075(age)
ln(salary) = 7.843855+ 0.016908(12.50538) + 0.004575(101.0344) +
0.053937(2.509722) + 0.175624(0.344086) - 0.00075(40.42182)
ln(salary) = 8.683008615
salary = exp(8.683008615)
= $5,901.776081
The salary when the independent variables are at their average is $5,901.78.
Question 2
SUMMARY OUTPUT