Consider the following regression model, y;=B1+B2Xi2+ ... +Bkxik+e; where E[e;|xj] = 0 and Varſe;|x) depends on the valu

[answerhappygod]

Consider The Following Regression Model Y B1 B2xi2 Bkxik E Where E E Xj 0 And Varse X Depends On The Valu 1 (192.3 KiB) Viewed 102 times

Consider the following regression model, y;=B1+B2Xi2+ ... +Bkxik+e; where E[e;|xj] = 0 and Varſe;|x) depends on the value of xj, 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. b. To fix the problem, we need to have an instrumental variable. O C. This problem implies that errors are correlated with one of (Xi2, ..., Xik): O d. If we assume var(e|x;) = 92, the confidence interval is not valid. *None of the above is correct. The OLS estimators of the coefficients in multiple regression will have omitted variable bias: O a. only if an omitted determinant of y, is a continuous variable. Obif an omitted varible is correlated with at least one of the regressors, even though it is not a determinannt of the dependent variable. oc only if the omitted variable is not normally distributed. dif an omitted determinant of Y; is correlated with at least one of the regressors. e if the degree of freedom is less than 50. Consider the following regression model Y = Bo+B1X1 +B2X2 + u where E[U|X1, X2]=0. Suppose X, and X2 are highly (but not perfectly) correlated. Then, O a.OLS estimators are biased. b.OLS estimators are not consistent OLS estimators will have large standard errors. d. One of X1, X2, or the constant should be dropped. Во cannot be interpreted as the population intercept. c. e