Question

Use the following chart to answer the below questions. Each column represents a different regression equation in which only some of the potential variables are used. If there is no coefficient value in a specific column for a specific variable, that variable was not included. We are interested in what affects average hourly earnings, where: College 1 if worker went to college, 0 if they have a high school diploma Female 1 if worker is female (0 otherwise) Age- Age in years Northeast-1 if worker is from Northeast United States, 0 otherwise Midwest -1 if worker is from Midwest United States, 0 otherwise South 1 if worker is from Southern United States, 0 otherwise West 1 if worker is from Western United States, 0 otherwise We have 15 observations. ant variable: average hourly earnings Independant Variable College (Xi) Female (X2) Age (Xs) 8.31 8.32 3.85 3.81 8.34 3.80 0.52 0.18 1.23 0.43 2.05 0.51 Northeast (X) Midwest (Xs) South (%) Intercept Sumna SER 17.02 1.87 Statistics 9.79 9.68 9.67 0.162 0.180 0.182

Answer 1

Answer 3) Here x1, x2, x4, x5, x6 each assumes values 0 or 1. a) Notice that the first two regression equation does not have any regional effect. But in case of 3rd regression equation, there is positive effect of northeast, and negative effect of Midwest and south on the earning. This implies northeast people are more efficient in average hourly earnings. So, we may conclude, there is important regional effect on the earnings b) The west variable is omitted because it may not carry important significant effect on the earnings. If we include it, it may appear that average hourly earnings are increased or by a certain amount though, may not be significant enoug decreased