Econometrics

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.

MCQs about Multicollinearity, Dummy Variable, Selection of Variables, Error in Variables, Autocorrelation, Time Series, Heteroscedasticity, Simultaneous Equations, and Regression analysis

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

 Consistent estimation of model parameters low

 Consistent estimation of parameters complex

 Consistent estimation of parameters impossible

 Consistent estimation of parameters high

2. Which one assumption is not related to error in explanatory variables?

 $ Cov(u_i, \varepsilon_i) = 0 $

 $ Cov(u_i, w_i) = 0 $

 $ E(Z_i) =0 $

 $ Cov(Z, X_i) \ne 0 $

3. Which one is not the rule of thumb?

 Pair-wise correlation coefficients

 High $R^2$ but few significant t-ratios

 Biased regression

 Wider confidence intervals

4. Which of the following statements is true about autocorrelation?

 Consecutive values of Errors term or observations are correlated

 The conditional distribution of error terms is constant

 Regressors are correlated

 Consecutive errors or observations are uncorrelated

5. 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?

 Confidence band

 Sum of squared residuals

 P-value

 Confidence interval

6. The AR(1) process is stationary if

 $ \rho = 0 $

 $ | \rho | > 1 $

 $ \rho = 1 $

 $ | \rho | < 1 $

7. In a regression model with three explanatory variables, there will be _______ auxiliary regressions

 1

 2

 3

 4

8. What type of regression models a categorical variable based on one or more independent variables?

 Linear regression

 Coefficient regression

 Ordinary regression

 Logistic regression

9. For the presence and absence of first-order autocorrelation valid tests are

 Durbin-Watson $d$ and Durbin $h$ statistics

 Park and Glejser test

 All of the above

 White and Gold-Feld test

10. Which of the following actions does not make sense to struggle against multicollinearity?

 Add more regressors in the model

 None of these

 Decrease the number of regressors in the model

 Increase more observations

11. Heteroscedasticity can be detected by plotting the estimated $\hat{u}_i^2$ against

 $ \hat{Y}_i $

 $ Y_i $

 Both $ \hat{Y}_i$ and $X_i$

 $ X_i $

12. The value of Durbin Watson $d$ lies between

 $ -4$ and $4 $

 $ 0 $ and $1 $

 $ 0 $ and $\infty$

 $ 0 $ and $ 4 $

13. What technique models a categorical variable based on one or more independent variables?

 Link function

 Regression coefficients

 Loss function

 Logistic regression

14. What is a nonlinear function that connects or links a dependent variable to the independent variables mathematically?

 Regression function

 Loss function

 Link function

 Relationship function

15. Heteroscedasticity is more common in

 Cross-sectional data than time-series data

 Meta Data

 Panel data

 Time-series data than cross-Sectional data

16. Which of the following can indicate negative autocorrelation?

 All of the residuals are close to zero

 All alternating pattern in the residuals

 Complete randomness in the residuals

 A cyclical pattern in the residuals

17. Autocorrelation may occur due to

 Effect of Lagged Relationship

 Omitted variable specification bias

 Inertia

 Effect of Cobweb Phenomenon

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

 Close to zero

 Close to 1

 Close to $-1 $

 Lies between $-1$ and $+1 $

19. Choose a true statement about the Durbin-Watson test

 None of these

 $ DW$-test verifies autocorrelation only of the first order auto-regressive model

 $ DW \approx 0 $ means negative autocorrelation

 $ DW $-test verifies autocorrelation of any given order auto-regressive model

20. The _____ states that no two independent variables ($X_i$ and $X_j$) can be highly correlated with each other.

 No homoscedasticity assumption

 No normality assumption

 No linearity assumption

 No multicollinearity assumption

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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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