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Unformatted text preview: Econ 103 UCLA, Fall 2010 Problem Set 3 Due: Thursday, October 21 in hardcopy at the beginning of class Note: Please attach the “Homework Cover Page” from Classweb to the front of your home work. Part 1: True or False and explain briefly why. 1. The assumption that E ( u i  X i = x i ) = 0 says that the expected value of u i changes depending on the value of X i . 2. If Cov ( X i ,u i ) > , then the OLS estimator ˆ β 1 will tend to be higher than β 1 . 3. Consider an omitted variable V i that is negatively correlated with X i . Also suppose that V i positively affects Y i . Then the OLS estimator ˆ β 1 is negatively biased. 4. Suppose you run a regression and obtain the estimate ˆ β 1 = 3 . 4 . STATA tells you that the tstatistic for the null hypothesis that β 1 = 0 is equal to 1.7. This implies that SE ( ˆ β 1 ) is equal to 2. 5. In the regression model Y i = β + β 1 Female i + β 2 Education i + u i , β 1 represents the intercept for females. 6. In the regression model Y i = β + β 1 Female i + β 2 Education i + β 3 Education i · Female i + u i , β 2 + β 3 represents the return to education for females. 7. Under perfect multicollinearity, the OLS estimator cannot be computed. 8. The Adjusted R 2 can be used to compare models with different numbers of regressors. 9. The overall regression Fstatistic tests the null hypothesis that all slope coefficients are zero. 10. If you reject a joint null hypothesis that a group of regressors have no effect on the dependent variable using the Ftest, then a series of individual ttests will reject as well....
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This note was uploaded on 10/23/2010 for the course STATISTICS 2 taught by Professor Ramirez during the Winter '09 term at USC.
 Winter '09
 Ramirez

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