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Unformatted text preview: Mehmet Soytas Applied Econometrics I, Summer, 2009 Wednesday, May 27, 2009 (due: Wednesday, June 03, 2009) Homework Assignment 3 1. State whether the following statements are TRUE or FALSE (Provide an explanation in either case). a. When there are omitted variables in the regression, which are determinants of the dependent variable, then the OLS estimator is biased if the omitted variable is correlated with the included variable. b. Imagine you regressed earnings of individuals on a constant, a binary variable (&Male¡) which takes on the value 1 for males and is 0 otherwise, and another binary variable (&Female¡) which takes on the value 1 for females and is 0 otherwise. Because females typically earn less than males, you would expect the coe¢ cient for Male to have a positive sign, and for Female a negative sign. c. When you have an omitted variable problem, the assumption that E ( u i j X i ) = 0 is violated. This implies that the OLS estimator is no longer consistent. d. You have to worry about perfect multicollinearity in the multiple regression model because OLS estimates will be always upward biased. e. In the multiple regression model, the least squares estimator is derived by minimizing the sum of squared errors. f. One of the least squares assumptions in the multiple regression model is that you have random variables which are &i.i.d.¡This stands for independently and identically distributed. g. Omitted variable bias will always be present as long as the regression R 2 < 1 : h. The following OLS assumption is most likely violated by omitted variables bias: E ( u i j X i ) = 0 : i. In the multiple regression model Y i = & + & 1 X 1 i + & 2 X 2 i + & 3 X 3 i + u i , the OLS estimators are ob-...
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This note was uploaded on 07/02/2009 for the course ECON 1150 taught by Professor Staff during the Summer '08 term at Pittsburgh.
- Summer '08