Suppose that all assumptions for ols are satisfied and estimate the following regression model: wagei = β0 + β1educi + ui , i = 1, . . , n. (5) where educ is the years of education which is included in the orginal dataset. report the value of βˆ 1 and its heteroskedasticity robust standard error. (b) we conjecture that location can also have an impact on the worker’s wage and it is potentially correlated with the worker’s education. we thus now estimate the following model, wagei = β0 + β1educi + β2urbani + ui , i = 1, . . , n. (6) urban is equal to 1 if the individual lives in urban area and equatl to 0 otherwise. report the value of βˆ 1 and its heteroskedasticity robust standard error. (c) how has your estimator of β1 changed compared to (a)? explain it by using your answer to equation (6). (d) does location have a significant effect on wage? if so, what is the significant level?