review chap4, 7,8

# review chap4, 7,8 - can you decide which models is the best...

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Chapter 4 1. What are the 2 conditions that lead to omitted variable bias? When is the slope coefficient positively (negatively) biased? 2. What is multicollinearity? What are the implications of perfect multicollinearity for OLS regression coefficients? What are the consequences of imperfect multicollinearity? 3. How can you test hypothesis about individual coefficients and joint hypotheses about multiple coefficients in a multiple regression model? 4. What is the distribution of F-statistic in the general case of heteroskedasticity? 5. What is the formula and the distribution of the F-statistic in a specific case of homoskedastic errors? What is the intuition behind this formula? Chapter 7 1. What is the interpretation of the slope coefficient in a linear-log, log-linear, and log-log regression models? How
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Unformatted text preview: can you decide which models is the best for your data? 2. What is the interpretation of the coefficient on the interaction term between the two dummy variables? When would you expect this model to describe the data well? 3. What is the interpretation of the coefficient on the interaction term between a dummy variable and a continuous variable? When would you expect this model to describe the data well? 4. What is the interpretation of the coefficient on the interaction term between the two continuous variables? Chapter 8 1. What is heteroskedasticity? 2. What are the consequences of heteroskedasticity? 3. How can heteroskedasticity be detected? 4. How can you correct for it?...
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## This note was uploaded on 11/20/2011 for the course ECON 420 taught by Professor Silous during the Spring '11 term at Emory.

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