Tag: MCQs Autocorrelation

MCQs Econometrics 3

Muhammad Imdad Ullah
Posted by Muhammad Imdad Ullah Posted on September 27, 2021 0 Comments on MCQs Econometrics 3
Posted in Advanced Statistics, Statistics Tagged , ,

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

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

1. Durbin and Watson have suggested a test to detect the presence of autocorrelation which is applicable to

 
 
 
 

2. If $\rho$ is zero, then there is

 
 
 
 

3. The log transformation is _____________ if some of the $Y$ and $X$ values are zero or negative.

 
 
 
 

4. If $d*<d_l$ then we

 
 
 
 

5. A system which has an infinite number of solutions has _______

 
 
 
 

6. Which combination of regressors might lead to perfect collinearity?

 
 
 
 

7. The existence of a perfect or near to exact linear relationship among some or all explanatory variables of a regression model is called

 
 
 
 

8. An assumption about underlying the d statistics “The explanatory variable $X$’s are non-stochastic or fixed in ____________”

 
 
 
 

9. The rule of thumb is if k is between 100 and 1000 then there is ____________ multicollinearity?

 
 
 
 

10. Zero tolerance or VIF equal to one indicate

 
 
 
 

11. In case of perfect multicollinearity, the OLS estimates are

 
 
 
 

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

 
 
 
 

13. In case of perfect or near to perfect multicollinearity, the OLS estimates are

 
 
 
 

14. Glejser test is similar to ________

 
 
 
 

15. In case of perfect multicollinearity, the $X’X$ is a ____________

 
 
 
 

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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