Econometrics Midterm Exam with
100% Correct Answers
Consider the following regression equation: y=B1 + B2x1 + B2x2 + u . What does B1
imply?
- B1 measures the ceteris paribus effect of x1 on u.
- B1 measures the ceteris paribus effect of x1 on y.
- B1 measures the ceteris paribus effect of x1 on x2.
- B1 measures the ceteris paribus effect of y on x2. - Answer- - B1 measures the ceteris
paribus effect of x1 on y.
Which of the following is true of R2?
- R2 usually decreases with an increase in the number of independent variables in a
regression.
- R2 is also called the standard error of regression.
- A low R2 indicates that the Ordinary Least Squares line fits the data well.
- R2 shows what percentage of the total variation in the dependent variable, Y, is
explained by the explanatory variables. - Answer- - R2 shows what percentage of the
total variation in the dependent variable, Y, is explained by the explanatory variables.
What does the equation y(hat) = B0(hat) + B1(hat)X denote if the regression equation is
y= B0 + B1X1 + u?
- The explained sum of squares
- The population regression function
- The sample regression function
- The total sum of squares - Answer- - The sample regression function
Which of the following is assumed for establishing the unbiasedness of Ordinary Least
Square (OLS) estimates?
- The sample outcomes on the explanatory variable are all the same value.
- The regression equation is linear in the explained and explanatory variables.
- The error term has the same variance given any value of the explanatory variable.
- The error term has an expected value of 1 given any value of the explanatory variable.
- Answer- - The regression equation is linear in the explained and explanatory variables.
The error term in a regression equation is said to exhibit homoskedasticity if _____.
- it has the same variance for all values of the explanatory variable
- it has zero conditional mean
- it has the same value for all values of the explanatory variable
100% Correct Answers
Consider the following regression equation: y=B1 + B2x1 + B2x2 + u . What does B1
imply?
- B1 measures the ceteris paribus effect of x1 on u.
- B1 measures the ceteris paribus effect of x1 on y.
- B1 measures the ceteris paribus effect of x1 on x2.
- B1 measures the ceteris paribus effect of y on x2. - Answer- - B1 measures the ceteris
paribus effect of x1 on y.
Which of the following is true of R2?
- R2 usually decreases with an increase in the number of independent variables in a
regression.
- R2 is also called the standard error of regression.
- A low R2 indicates that the Ordinary Least Squares line fits the data well.
- R2 shows what percentage of the total variation in the dependent variable, Y, is
explained by the explanatory variables. - Answer- - R2 shows what percentage of the
total variation in the dependent variable, Y, is explained by the explanatory variables.
What does the equation y(hat) = B0(hat) + B1(hat)X denote if the regression equation is
y= B0 + B1X1 + u?
- The explained sum of squares
- The population regression function
- The sample regression function
- The total sum of squares - Answer- - The sample regression function
Which of the following is assumed for establishing the unbiasedness of Ordinary Least
Square (OLS) estimates?
- The sample outcomes on the explanatory variable are all the same value.
- The regression equation is linear in the explained and explanatory variables.
- The error term has the same variance given any value of the explanatory variable.
- The error term has an expected value of 1 given any value of the explanatory variable.
- Answer- - The regression equation is linear in the explained and explanatory variables.
The error term in a regression equation is said to exhibit homoskedasticity if _____.
- it has the same variance for all values of the explanatory variable
- it has zero conditional mean
- it has the same value for all values of the explanatory variable
