# MCQs Econometrics Quiz 2

This quiz is about Econometrics, which covers the topics of Regression analysis, correlation, dummy variable, multicollinearity, heteroscedasticity, autocorrelation, and many other topics. Let’s start with the MCQs Econometrics Quiz.

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

1. The regression predictions are inefficient

2. Which one of the following is NOT an example of misspecification of functional form?

3. If we drop a relevant variable from the model

4. The generalized least square (GLS) is an efficient procedure that weights each squared residual by:

5. Which of the following is a consequence in case of imperfect multicollinearity?

6. Does the White General Heteroscedasticity test follow $\chi^2$ distribution with degrees of freedom?

7. The conditional variance of $Y_i (Var(u_i))$ conditional upon the given $X_i$ does not remain the same regardless of the values taken by the variable $X$ when the problem of ________ exists.

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

9. Which of the following tests is used to compare OLS estimates and WLS estimates?

10. If the calculated value of tolerance is equal to 1, then it is an indication of

11. Which of the following is an indication of the existence of multicollinearity in a model?

12. For the Durbin-Watson test:

13. Multicollinearity causes

14. Incorrect data transformation (ratio or difference, linear, log-linear) is also a source of

15. In GLS the weights assigned to each observation are _______ to its $\sigma_i$

16. In the case of multicollinearity, the confidence interval tends to be much ______, leading to the acceptance of the zero null hypothesis.

17. If $R^2$ between $X_2$ and $X_3$ approaches 1 (that is $r_{23}^2 \rightarrow 1$ ) then

18. In the case of homoscedasticity

19. Which of the following is true about autocorrelation?

20. Heteroscedasticity may _____________ the variance and standard errors of the OLS estimates.

An application of different statistical methods applied to the economic data used to find empirical relationships between economic data is called Econometrics.

Econometrics means “Economic Measurement”. Econometrics is the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of statistical inference.

Econometrics can also be defined as the empirical determination of economic laws. Econometrics can be classified as (i) Theoretical Econometrics and (ii) Applied Econometrics.

### (i) Theoretical Econometrics

Theoretical econometrics is concerned with developing appropriate methods for measuring economic relationships specified by econometric models. Theoretical econometrics leans heavily on mathematical statistics and must spell out the assumptions of methods (such as Least Squares), their properties, and what happens to these properties when one or more of the assumptions of the technique are not fulfilled.

### (ii) Applied Econometrics

In applied econometrics, the tools of theoretical econometrics are used to study special fields(s) such as production function, investment function, demand and supply function, portfolio theory, etc.

### Types of Econometrics Data

Different type of data is used in Econometrics. There are three important types of data for empirical analysis:

• Time Series Data
A time series data is a set of observations on the values that a variable takes at different times. The time series data may be collected at regular time intervals such as daily, weekly, monthly, quarterly, annually, etc.
• Cross-Sectional Data
Cross-sectional data are data on one or more variables collected at the same point in time. Cross-sectional data has a problem of heterogeneity.
• Pooled Data
Pooled data is a combination of both time series and cross-sectional data.

### Online MCQs Econometrics Quiz

• In the case of homoscedasticity
• In the presence of autocorrelation, the OLS estimates are no longer
• Which one of the following is NOT an example of misspecification of functional form?
• Which of the following tests is used to compare OLS estimates and WLS estimates?
• Incorrect data transformation (ratio or difference, linear, log-linear) is also a source of
• The conditional variance of $Y_i (Var(u_i))$ conditional upon the given $X_i$ does not remain the same regardless of the values taken by the variable $X$ when the problem of __________ exists.
• Which of the following is an indication of the existence of multicollinearity in a model?
• Which of the following is a consequence in case of imperfect multicollinearity?
• Heteroscedasticity may _________ the variance and standard errors of the OLS estimates.
• For the Durbin-Watson test:
• The regression predictions are inefficient
• Multicollinearity causes
• The generalized least square (GLS) is an efficient procedure that weights each squared residual by:
• In GLS the weights assigned to each observation are to its $\sigma_i$
• Does the White General Heteroscedasticity test follow $\chi^2$ distribution with degrees of freedom?
• If we drop a relevant variable from the model
• In the case of multicollinearity, the confidence interval tends to be much ________, leading to the acceptance of the zero null hypothesis.
• If the calculated value of tolerance is equal to 1, then it is an indication of
• If $R^2$ between $X_2$ and $X_3$ approaches 1 (that is $r_{23}^2 \rightarrow 1$ ) then
• Which of the following is true about autocorrelation?

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