We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings. We use the following model to estimate the effect of a training program on annual earnings in 2018: ln(earn2018)=β0+β1train+β2ln(earn2016)+β3educ+β4exper+u where earn2018 = individual total annual earnings in 2018 in dollars train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise earn2016 = individual total annual earnings in 2016 in dollars educ = the individual's years of education exper = the individual's years of experience We find: ln(earn2018)^= 11.672 + 0.041train + 0.821ln(earn2016) + 0.037educ + 0.012exper (5.864) (0.019) (0.258) (0.013) (0.007) n=1278, R2= 0.048 Which of the following is the correct interpretation of the coefficient on earnings in 2016? a) For each additional 1% increase in earnings in 2016, average earnings in 2018 are expected to increase by approximately 0.821%, all else equal. b) For each additional 1% increase in earnings in 2016, average earnings in 2018 are expected to increase by approximately 82.1%, all else equal. c) Each additional 1% increase in earnings in 2016, is expected to increase earnings in 2018 on average by 0.821%.
We have a random sample of workers from a large firm. In 2017, the firm ran a training program. Some workers did the training program, others did not. The firm now wants to assess the effect of the training on earnings.
We use the following model to estimate the effect of a training program on annual earnings in 2018:
ln(earn2018)=β0+β1train+β2ln(earn2016)+β3educ+β4exper+u
where
- earn2018 = individual total annual earnings in 2018 in dollars
- train = a dummy variable that takes the value 1 if the individual worker did the training in 2017 and 0 otherwise
- earn2016 = individual total annual earnings in 2016 in dollars
- educ = the individual's years of education
- exper = the individual's years of experience
We find:
ln(earn2018)^= 11.672 + 0.041train + 0.821ln(earn2016) + 0.037educ + 0.012exper
(5.864) (0.019) (0.258) (0.013) (0.007)
n=1278, R2= 0.048
Which of the following is the correct interpretation of the coefficient on earnings in 2016?
a) For each additional 1% increase in earnings in 2016, average earnings in 2018 are expected to increase by approximately 0.821%, all else equal.
b) For each additional 1% increase in earnings in 2016, average earnings in 2018 are expected to increase by approximately 82.1%, all else equal.
c) Each additional 1% increase in earnings in 2016, is expected to increase earnings in 2018 on average by 0.821%.
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