Question

A regression is estimated relating to earnings to years of schooling. The data related to
earnings for different individuals who have completed their university education i.e. 16
years of education and they have no further education has been collected.
Based on the given data, what OLS coefficient is expected to find.
a) The coefficient is positive and significant
b) The coefficient is negative yet insignificant
c) The slope of the OLS estimator is zero
d) As there is no variation in the data for the explanatory variable, the OLS slope
estimator would not be defined.​

Answer 1

Answer: Your answer is A one

Answer 2

The correct answer is option (d) As there is no variation in the data for the explanatory variable, the OLS slope  estimator would not be defined.

Explanation:

• Based on the given data, As there is no variation in the data for the explanatory variable, the OLS slope  estimator would not be defined.
• The OLS estimates are the intercept and slope that minimize the sum of the squared residuals.
• In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model.
• This method minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses predicted by the linear approximation.