Question

Suppose a researcher, using data on the number of years of education a person has received and their annual earnings (in thousands of dollars) from 200 people, estimates the OLS regression: earnings = β₀ + β₁(education).

What does β₁ represent?

a. Intercept
b. Slope
c. Error term
d. R-squared value

Answer 1

In the given OLS regression, β1 represents the slope, indicating the expected change in annual earnings for each additional year of education.

Step-by-step explanation:

In the context of the OLS regression equation earnings = β₀ + β₁(education), the term β1 represents the slope of the regression line. The slope indicates how much the dependent variable, which in this case is annual earnings, is expected to increase for each additional year of education, holding all other factors constant. This coefficient provides insight into the relationship between the number of years of education and annual earnings.

Given the equation, we can notate the slope as β1, denoting the expected change in earnings (measured in thousands of dollars) for each additional year of education received. The slope is a crucial part of the regression analysis as it quantifies the relationship between education and earnings.