Miressa Beyene

1. The curve showing the possibilities of production of desired good is known as: A. indifference curve B. production possibility curve C. revealed preference curve D. none of these Answer: B 2. Which one of the following definition of Economics is associated with the name of Lionel Robbins? A. welfare definition B. scarcity definition C. growth definition D. wealth definition Answer: B 3. A hypothesis is tested by: A. the realism of its assumptions B. the lack of realism of its assumptions C. its ability to predict accurately an outcome that follows logically from the assumptions D. none of these Answer: C 4. In a free enterprise economy, the problems of what, how and for whom to produce are solved by : A. a planning committee M c q M a t e .

1. The curve showing the possibilities of production of desired good is known as: A. indifference curve B. production possibility curve C. revealed preference curve D. none of these Answer: B 2. Which one of the following definition of Economics is associated with the name of Lionel Robbins? A. welfare definition B. scarcity definition C. growth definition D. wealth definition Answer: B 3. A hypothesis is tested by: A. the realism of its assumptions B. the lack of realism of its assumptions C. its ability to predict accurately an outcome that follows logically from the assumptions D. none of these Answer: C

A. reject a false null hypothesis B. reject a true null hypothesis C. do not reject a false null hypothesis D. do not reject a true null hypothesis 3. What is the meaning of the term "heteroscedasticity"? A. The variance of the errors is not constant B. The variance of the dependent variable is not constant C. The errors are not linearly independent of one another D. The errors have non-zero mean 4. What would be then consequences for the OLS estimator if heteroscedasticity is present in a regression model but ignored? A. It will be ignored B. It will be inconsistent C. It will be inefficient D. All of a),c), b) will be true. 5. Which one of the following is NOT a plausible remedy for near multicollinearity? A. Use principal components analysis B. Drop one of the collinear variables C. Use a longer run of data D. Take logarithms of each of the variables 6. What will be the properties of the OLS estimator in the presence of multicollinearity? A. It will be consistent unbiased and efficient B. It will be consistent and unbiased but not efficient C. It will be consistent but not unbiased D. It will not be consistent 7. A sure way of removing multicollinearity from the model is to A. Work with panel data B. Drop variables that cause multicollinearity in the first place C. Transform the variables by first differencing them D. Obtaining additional sample data 8. Autocorrelation is generally occurred in A. Cross-section data B. Time series data C. Pooled data D. None of the above 9. The regression coefficient estimated in the presence of autocorrelation in the sample data are NOT A. Unbiased estimators B. Consistent estimators C. Efficient estimators D. Linear estimators 10. In the regression function y=β o + β 1 x +c A. x is the regressor B. Y is the regressor C. x is the regress and D. none of these 11. The coefficient of determination, r2 shows A. Proportion of the variation in the dependent variable Y is explained by the independent variable X