# Tag: MCQs Multicollinearity

## MCQs Econometrics-4

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

1. Autocorrelation may be the result of _____________

2. Collinearity or multicollinearity occurs whenever _________

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

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

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

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

7. What does a VIF of 1 mean?

8. The generalized least square estimators are also called:

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

10. If there is no overlapping between regressors then __________

11. If value of R-square between $X_2$ and $X_3$ approaches to 1 then ____________.

12. The term Heteroscedasticity means ________

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

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

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

16. If measurement errors are present only in dependent variable, then the estimate remains:

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

18. Autocorrelation is most likely occurred in ____________ data?

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## MCQs Econometrics 3

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 MCQs Econometrics test

Please go to MCQs Econometrics 3 to view the test

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.

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