MCQs Econometrics Statistics 4

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

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

1. Which of the following could be used as a test for autocorrelation up to third order?

 
 
 
 

2. The generalized least square estimators are also called:

 
 
 
 

3. The Durbin-Watson d test has no__________ for the rejection of the null hypothesis.

 
 
 
 

4. Which of the following is an indication of the existence of multicollinearity?

 
 
 
 

5. What does a VIF of 1 mean?

 
 
 
 

6. Which of the following is an indication of the existence of multicollinearity?

 
 
 
 

7. One can test the pure randomness of residuals from

 
 
 
 

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

 
 
 
 

9. If the value of R-square between $X_2$ and $X_3$ approaches 1 then _________.

 
 
 
 

10. Which one of the following is not a plausible remedy for near multicollinearity?

 
 
 
 

11. If there is no overlapping between regressors then __________

 
 
 
 

12. One can test the pure randomness of residual from _______

 
 
 
 

13. Collinearity or multicollinearity occurs whenever _________

 
 
 
 

14. The presence of heteroscedasticity does not destroy the _______________ of OLS estimators.

 
 
 
 

15. Autocorrelation is most likely occurred in ____________ data?

 
 
 
 

16. Robust standard errors are the ones that are corrected by __________.

 
 
 
 

17. Autocorrelation may be the result of _____________

 
 
 
 

18. If measurement errors are present only independent variable, then the estimate remains:

 
 
 
 

19. The term Heteroscedasticity means ________

 
 
 
 

20. If we omit a relevant variable from the model ___________

 
 
 
 

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.

MCQs Econometrics Statistics

  • Which one of the following is not a plausible remedy for near multicollinearity?
  • Which of the following could be used as a test for autocorrelation up to third order?
  • If we omit a relevant variable from the model ———-
  • Autocorrelation may be the result of ———-
  • One can test the pure randomness of residual from ———-
  • The term Heteroscedasticity means ———-
  • Collinearity or multicollinearity occurs whenever ———-
  • If there is no overlapping between regressors then ———-
  • What does a VIF of 1 mean?
  • Autocorrelation is most likely occurred in ———- data?
  • If measurement errors are present only independent variable, then the estimate remains:
  • The presence of heteroscedasticity does not destroy the ———- of OLS estimators.
  • The Durbin-Watson d test has no ———- for the rejection of the null hypothesis.
  • If the value of R-square between $X_2$ and $X_3$ approaches 1 then ———-.
  • Which of the following is an indication of the existence of multicollinearity?
  • The generalized least square estimators are also called:
  • Robust standard errors are the ones that are corrected by ———-.
  • In the case of multicollinearity, the confidence interval tends to be much ———-, leading to the acceptance of a zero null hypothesis.
  • Which of the following is an indication of the existence of multicollinearity?
  • One can test the pure randomness of residuals from

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, or 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.
MCQs Econometrics Statistics

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