Consider the following regression model: log(y) = β0 + β1x1 + β2x12 + β3x3 + u. This model will suffer from functional form misspecification if _____.
A. β0 is omitted from the model
B. u is heteroskedastic
C. x12 is omitted from the model
D. x3 is a binary variable
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A regression model suffers from functional form misspecification if _____.
A. a key variable is binary.
B. the dependent variable is binary.
C. an interaction term is omitted.
D. the coefficient of a key variable is zero.
Which of the following is true?
A functional form misspecification can occur if the level of a variable is used when the logarithm is more appropriate.
B. A functional form misspecification occurs only if a key variable is uncorrelated with the error term. .
C. A functional form misspecification does not lead to biasedness in the ordinary least squares estimators.
D. A functional form misspecification does not lead to inconsistency in the ordinary least squares estimators.
Which of the following assumptions is needed for the plug-in solution to the omitted variables problem to provide consistent estimators?
A. The error term in the regression model exhibits heteroskedasticity.
B. The error term in the regression model is uncorrelated with all the independent variables.
C. The proxy variable is uncorrelated with the dependent variable.
D. The proxy variable has zero conditional mean.
Which of the following is true of Regression Specification Error Test (RESET)?
A. It tests if the functional form of a regression model is misspecified.
B. It detects the presence of dummy variables in a regression model.
C. It helps in the detection of heteroskedasticity when the functional form of the model is correctly specified.
D. It helps in the detection of multicollinearity among the independent variables in a regression model.
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