Answer Happy

Which statements are correct? If a new independent variable is added to a regression equation, the R2 increases only if the absolute value of the t statistic of the new variable is greater than one. A change in the unit of measurement of the dependent variable in a model does not lead to a change in the goodness-of-fit of the regression. When explanatory variables are not strictly exogenous, the Durbin Watson test for serial correlation is valid. Changing the unit of measurement of any independent variable, where log of the dependent variable appears in the regression affects only the intercept coefficient. In a multiple regression model, the OLS estimator is consistent if there is no correlation between the dependent variables and the error term. The variance of the slope estimator decreases as the error variance decreases. In presence of serial correlation, the OLS variance formula accurately estimates the true variance of the OLS estimator. In a simple linear regression model, wage = a +b*male+u, where male is a binary variable (1 if a person is male, and 0 otherwise), b measures the average wage of males. An advantage of first differencing a time-series is that it eliminates the possibility of spurious regression.