Question

For the (estimated) linear regression model

log(Income_i) = 0.4 + 0.5 Education_i + e_i

• Income_i is an individual's income (in thousands of dollars)
• Education_i is an individual's education (in years)

How do we interpret the coefficient on education?

Group of answer choices

A)A 1-year increase in education is associated with a 50% increase in income (holding all else constant).

B)A 1-year increase in education is associated with a $500 increase in income (holding all else constant).

C)The correct answer is not given.

D)A 1-year increase in education is associated with a 5% increase in income (holding all else constant).

Answer 1

The Log-linear regression model:

log(Income_i) = 0.4 + 0.5 Education_i + e_i

Dependent variable = Income

Independent variable = Education

The dependent variable is in log

The independent variabl is linear.

The coefficient of independent variable (i.e., Education) is 0.5.

In case of Log -Linear regression model, one unit change in independent variable will lead to (100 * Coefficient of independent variable) percent change in dependent variable.

So,  A 1-year increase in education is associated with a 50% (i.e., (100 * 0.5)% increase in income (holding all else constant)

Answer: Option (A)