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Econometrics 2014
Final Exam. Part A, July 14
Final Exam. Part A (5 points each, total 15 points)
1. Which of the following can cause OLS estimators to be biased?
(a) Heterosckedasticity
(b) Omitting an important variable
(c) Including irrelevant variables
(d) Multicollinearity
(e) The population error term is not normally distributed.
2. Which of the above (a)-(e) in question 1 can cause OLS t statistics to be invalid?
3. State whether the following statements are true, false, or uncertain.
(a) The intercept in a simple regression model is estimated by the sample mean of dependent
variable if the slope parameter is zero.
(b) There is a positive relationship between the variance of OLS estimators and the sample size.
(c) If a null hypothesis is not rejected, the hypothesis is true.
(d) The sum of residuals is always zero whatever the model form is.
(e) R2 or adjusted R2 is one of the good indicators to compare the models with different functional
forms like the log-log form vs. the level–log form.
a, b, c, e
(a) True, (b) False, (c) False or Uncertain, (d) True, (e) False