Q1.

Consider the following regression model, yi = B1 + B2x12+ ...+ Bxxix+ e; where Ele,| x;] = 0 and Var(e;| x.) depends on the value of x,, i.e., Var(e;] x;) # 02. Choose the correct statement. O a. To get around the problem, we often assume that e, is normally distributed. O b. To fix the problem, we need to have an instrumental variable. C. This problem implies that errors are correlated with one of (x;?, .., Xik) O d. If we assume Var(e;] x;) = 02, the confidence interval is not valid O e. None of the above is correct.In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, Iog(income), = 80 + 81 educ, + + u; where educ, is years of school of individual iand includes additional terms associated with other characteristics in the data set. When researcher B was carefully examining omitted factors in the error term Ui' she realised that unobserved factors such as moth/(mom and work ethic, would determine the income level and be correlated with the variable of interest GdUC," lf researcher B's conjecture regarding the unobserved factors is correct, then: A a. The OLS estimator 31 would not be computed. o b' The OLS estimator 81 would overestimate the effect on income, of EGUC,\" Il A c. The OLS estimator 81 would suffer imperfect multicollinearity. 'The OLS estimator 81 would have a large standard error. A '. ,' E. . A . . . . . ' The OLS estimator 81 would follow the Student t-dlstrlbutlon With n-k degrees of freedom, where k Is the number of coefficients to estimate in the model