The OLS estimators of the coefficients in a multivariate linear regression model will be unbiased and consistent if the following set of conditions holds A. expected value of the error term given the independent variables is zero, the variance of the error term does not depend on the values of the independent variables, the observations (Yi,X₁,1,X₁2,...,X) are i.i.d., large outliers are unlikely B. expected value of the error term given the independent variables is zero, the variance of the error term does not depend on the values of the independent variables, there is no perfect multicollinearity between the independent variables, the observations (Y₁X₁.1.X2,...,X) are i.i.d. C. expected value of the error term given the independent variables is zero, there is no perfect multicollinearity between the independent variables, the observations (Yi,Xi,1,Xi,2,...,Xik) are i.i.d., large outliers are unlikely D. the variance of the error term does not depend on the values of the independent variables, there is no perfect multicollinearity between the independent variables, the observations (Y₁, X₁,1,X₁,2,...,X) are i.i.d., large outliers are unlikely

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12. The OLS estimators of the coefficients in a multivariate linear regression model will be unbiased
and consistent if the following set of conditions holds
A. expected value of the error term given the independent variables is zero, the variance of
the error term does not depend on the values of the independent variables, the
observations (Yi,Xi,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikely
B. expected value of the error term given the independent variables is zero, the variance of
the error term does not depend on the values of the independent variables, there is no
perfect multicollinearity between the independent variables, the observations
(Y₁X₁,1X₁,2,...,Xik) are i.i.d.
C. expected value of the error term given the independent variables is zero, there is no
perfect multicollinearity between the independent variables, the observations
(Yi,Xi,1,Xi,2,...,Xik) are i.i.d., large outliers are unlikely
D. the variance of the error term does not depend on the values of the independent
variables, there is no perfect multicollinearity between the independent variables, the
observations (Yi,X₁,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikely
Transcribed Image Text:12. The OLS estimators of the coefficients in a multivariate linear regression model will be unbiased and consistent if the following set of conditions holds A. expected value of the error term given the independent variables is zero, the variance of the error term does not depend on the values of the independent variables, the observations (Yi,Xi,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikely B. expected value of the error term given the independent variables is zero, the variance of the error term does not depend on the values of the independent variables, there is no perfect multicollinearity between the independent variables, the observations (Y₁X₁,1X₁,2,...,Xik) are i.i.d. C. expected value of the error term given the independent variables is zero, there is no perfect multicollinearity between the independent variables, the observations (Yi,Xi,1,Xi,2,...,Xik) are i.i.d., large outliers are unlikely D. the variance of the error term does not depend on the values of the independent variables, there is no perfect multicollinearity between the independent variables, the observations (Yi,X₁,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikely
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