Econometrics

Test your knowledge with these Econometrics MCQs with Answers, covering autocorrelation, heteroscedasticity, multicollinearity, and OLS assumptions. The Econometrics Quiz is perfect for students, researchers, econometricians, and data scientists. Let us try Econometrics MCQs with Answers Quiz now.

Online Econometrics MCQss with Answers

1. Multicollinearity causes

 Low R-squares

 Insignificant t-ratios

 None of these

 Biased Coefficient estimates

2. Heteroscedasticity may —————– the variance and standard errors of the OLS estimates.

 Not affect

 Highly affect

 Minor affect

 Affect

3. Autocorrelation may occur due to

 Effect of Cobweb Phenomenon

 Inertia

 Omitted variable specification bias

 All options

4. An assumption underlying the $d$ statistics is that “The explanatory variables $X$’s are non-stochastic or fixed in —————-“.

 None of the these

 Repeated sampling

 Cluster sampling

 Simple random sampling

5. What does a VIF of 1 mean?

 There is near or high multicollinearity

 There is perfect multicollinearity

 There will be no multicollinearity

 Not at all

6. Heteroscedasticity is more common in

 Cross-sectional data rather than time series data

 Panel Data

 Meta Data

 Time-series data than cross-sectional data

7. If we omit a relevant variable from the model

 The disturbance variance $\sigma^2$ is incorrectly estimated

 Heteroscedasticity

 Autocorrelation

 The disturbance variance $\sigma^2$ is correctly estimated

8. The value of $d$ lies between

 0 and 4

 –4 and 4

 0 and $\infty$

 0 and 2

9. If a Durbin-Watson statistic takes a value close to zero, what will be the value of the first-order autocorrelation coefficient?

 Close to –1

 Close to zero

 Lies between –1 and +1

 Close to 1

10. Collinearity or multicollinearity occurs whenever

 There is a close, non-linear relationship among the independent variables

 The dependent variable is highly correlated with the independent variables

 The explanatory variables are highly orthogonal

 There is a close linear relationship among the explanatory variables

11. If the calculated value of tolerance is 1, then there is an issue of

 Perfect multicollinearity

 No multicollinearity

 Low multicollinearity

 None of these

12. If the value of R-squared between $X_2$ and $X_3$ approaches to 1 then

 VIF approaches to infinity

 There is no effect on VIF

 VIF approaches to zero

 VIF becomes zero

13. A system which have an infinite number of solutions has

 Less variables than equations

 Equal number of variables and equations

 None of these

 More variables than equations

14. If $d*<d_l$ then we

 Accept $H_0$ of no autocorrelation

 Problem of Heteroscedasticity

 Reject $H_0$ of no autocorrelation

 Problem of collinearity

15. The term heteroscedasticity refers to

 The variance of the dependent variable is not constant

 The errors have non-zero mean

 The variance of the errors is not constant

 The errors are not linearly independent of each other

16. The AR(1) process is stationary if

 $r = 0$

 $r = 1$

 $|r| > 1$

 $|r| < 1$

17. In case of homoscedasticity

 $E(u_i^2 ) = n \times p$

 $E(u_i^2) = 0$

 $E(u_i^2 ) = \sigma^2 = Var(u_i^2)$

 $E(u_i^2 ) ≠ \sigma^2 = Var(u_i^2)$

18. Zero tolerance value indicates

 Perfect multicollinearity

 Low multicollinearity

 Near to Perfect multicollinearity

 No multicollinearity

19. In the presence of autocorrelation, the OLS estimates are no longer

 All of these

 Consistent

 Efficient

 Unbiased

20. When measurement errors are present in the explanatory variable(s), they make

 Consistent estimation of model parameters low

 Consistent estimation of parameters impossible

 Consistent estimation of parameters complex

 Consistent estimation of parameters high

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Question 1 of 20

Online Econometrics MCQs with Answers

• An assumption underlying the $d$ statistics is that “The explanatory variables $X$’s are non-stochastic or fixed in —————-“.
• The term heteroscedasticity refers to
• Zero tolerance value indicates
• A system which have an infinite number of solutions has
• If we omit a relevant variable from the model
• When measurement errors are present in the explanatory variable(s), they make
• If $d*<d_l$ then we
• If a Durbin-Watson statistic takes a value close to zero, what will be the value of the first-order autocorrelation coefficient?
• Heteroscedasticity is more common in
• Autocorrelation may occur due to
• The AR(1) process is stationary if
• Heteroscedasticity may —————– the variance and standard errors of the OLS estimates.
• The value of $d$ lies between
• In case of homoscedasticity
• In the presence of autocorrelation, the OLS estimates are no longer
• What does a VIF of 1 mean?
• Multicollinearity causes
• If the calculated value of tolerance is 1, then there is an issue of
• If the value of R-squared between $X_2$ and $X_3$ approaches to 1 then
• Collinearity or multicollinearity occurs whenever

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The Post is about Online MCQs Econometrics. The MCQS Econometrics Quiz contains 20 multiple-choice questions on heteroscedasticity, multicollinearity, auxiliary regression, multiple regression, autocorrelation, and regression diagnostics. Let us start with the Online MCQs Econometrics quiz.

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Online MCQs Econometrics with Answers

• In a regression model with three explanatory variables, there will be ————– auxiliary regressions
• The AR(1) process is stationary if
• The value of Durbin Watson $d$ lies between
• Which of the following actions does not make sense to struggle against multicollinearity?
• Autocorrelation may occur due to
• Which of the following can indicate negative autocorrelation?
• Which one is not the rule of thumb?
• Heteroscedasticity can be detected by plotting the estimated $\hat{u}_i^2$ against
• If a Durbin Watson statistic takes a value close to zero what will be the value of the first-order autocorrelation coefficient?
• Which of the following statements is true about autocorrelation?
• When measurement errors are present in the explanatory variable(s) they make
• Heteroscedasticity is more common in
• Which one assumption is not related to error in explanatory variables?
• For the presence and absence of first-order autocorrelation valid tests are
• Choose a true statement about the Durbin-Watson test
• What technique models a categorical variable based on one or more independent variables?
• What is a nonlinear function that connects or links a dependent variable to the independent variables mathematically?
• What type of regression models a categorical variable based on one or more independent variables?
• In a linear regression model, what is the area surrounding the regression line that describes the uncertainty around the predicted outcome at every value of X?
• The ————- states that no two independent variables ($X_i$ and $X_j$) can be highly correlated with each other.

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