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Econometric

Total questions: 50

Worksheet time: 28mins

Name
Class
Date
1.

Econometrics is a combination of

a)

Economics + statistics

b)

Economics + mathematics

c)

Economics+Mathematics + statistics

d)

None of the above

2.

Econometrics is pioneered by...

a)

Gold Berger

b)

Jan Tibergen

c)

Samuelson

d)

Ragnar Frisch

3.

Econometrics is helps for policy making.

a)

Strongly agree

b)

Agree

c)

Disagree

d)

No one above

4.

TOOL OF ECONOMETRICS ...

a)

Correlation

b)

Substraction

c)

Regression

d)

Addition

5.

Data collected for a variable over a period of time is called:

a)

Panel data

b)

Pooled data

c)

Time series data

d)

Cross-sectional data

6.

In an econometric model if relevant variables are excluded and irrelevant variables are included then it is said to be a ...

a)

simultaneity bias

b)

specification unbias

c)

specification bias

d)

none of the above

7.

............. is a set of elements taken from a population according to certain rules.

a)

population

b)

sample

c)

statistic

d)

element

8.

Data collected at a point in time is called...

a)

Cross- sectional data

b)

Time series data

c)

Pooled data

d)

Panel data

9.

Regression analysis is concerned with estimating...

a)

The mean value of the dependent variable

b)

The mean value of the explanatory variable

c)

The mean value of the correlation coefficient

d)

The mean value of the fixed variable

10.

The dependent variable in regression analysis is assumed to be

a)

known values

b)

constant

c)

non Stochastic

d)

stochastic

11.

y= bo + b1x or y = a + bx, the regression line…

a)

Scatterplot

b)

Linear Model (line of best fit)

c)

Correlation Coefficient

d)

Re-expression or transformation

12.

In regression models, errors are ___.

mistakes

the other factors affecting Y (T)

the explained factors

the explanatory factors

a)

the explained factors

b)

the explanatory factors

c)

mistakes

d)

the other factors affecting Y

13.

Regression analysis is concerned with the study of the dependence of:

a)

Two known variables

b)

Explanatory variables on one or more dependent variables

c)

Dependent variables on one or more explanatory variables

d)

Both explanatory and dependent variables on other

14.

REGRESSION WAS INTRODUCED BY

a)

Dalton

b)

Malthus

c)

Kendell

d)

Francis Galton

15.

Linear regression model is ...

a)

linear in parameters and must be linear in variables

b)

linear in parameters and may not be linear in variables

c)

non linear in parameters and must be linear in variables

d)

linear in explanatory variables but may not be linear in parameters

16.

In regression analysis, the values are fixed for the ...

a)

Explanatory variables

b)

Dependent variables

c)

All variables

d)

None of the variables

17.

Independent variable is…

a)

Predictor

b)

Intercept

c)

Response

d)

Residual

18.

In OLS regression, the task is to minimize ___

a)

Total Sum Squares

b)

Regression Sum Squares

c)

Residual Sum Squares

d)

Unexplained Sum Squares

19.

Which of the following represents true observed values?

a)

Y=α+β⋅X

b)

Yi​=hatα+hatβ⋅Xi​+hatui​

c)

Yi​=α+β⋅Xi​+ui​

d)

Yi​=hatα+hatβ⋅Xi

20.

One of the properties of OLS estimators is ...

a)

Linear

b)

Unbiased

c)

Minimum Variance

d)

All of the above

21.

An equation is linear if ...

a)

plotting the function in terms of X and Y generates a straight line

b)

plotting the function in terms of X and Y generates a curve

22.

The explanatory variable in regression analysis are assumed to be ...

a)

Non stochastic

b)

Constant

c)

Stochastic

d)

Known values

23.

studying the dependence of a variable on only a single explanatory variable is known as ...

a)

One Variable regression analysis

b)

Two variable regression analysis

c)

Three variable regression analysis

d)

Multiple regression analysis

24.

Numerical values of the parameters of the model are estimated with the help of ...

a)

Mathematics

b)

Economic statistics

c)

Inferential statistics

d)

None of them

25.

____________________ is the constant or intercept term; it indicates the value of Y when X equals 0

a)

β0

b)

β1

26.

An equation is linear if …

a)

Plotting the function in terms of X and Y generates a curve

b)

Plotting function in terms of X and Y generates straight line

27.

OLS stands for…

(a)  

28.

A method for finding the equation of a line that minimizes the sum of squared residuals…

a)

Form

b)

Least Squares

c)

Scatterplot

d)

Association

29.

The scatter plot shows the number of books read by students in Mrs. Hall’s English class and their final grades. Which statement represents the best description about the line of best fit?

a)

The more books students read, the higher their English grade.

b)

The more books students read, the lower their English grade.

c)

The fewer books students read, the higher their English grade.

d)

No relationship exists between the number of books students read and their English grades.

30.

What type of regression would you use for this data?

a)

Quadratic

Linear (T)

Radical

Exponential

b)

Linear

c)

Radical

d)

Exponential

31.

The number in front of the variable…

a)

Exponent

b)

Base

c)

Correlation

d)

Coefficient

32.

A good model has high values in which of the following?

a)

t-statistics 

b)

F statistics 

c)

Standard Error of Betas

d)

Standard Error of Regression

e)

 R2R^2   

33.

Proportion of variation in the dependent variable explained by variation in the independent variable...

a)

R

b)

 R2R^2  

c)

residual

d)

intercept

34.

A method to choose the omitted variable is:

a)

time series analysis

b)

omitted variable analysis

c)

expected bias analysis

d)

correlation analysis

35.

Omitted variable bias also known as:

a)

systematic error

b)

specification error (T)

c)

error term

d)

unbiasedness

36.

Tick the symbol for Error term

a)
b)
c)
d)
37.

Testing overall significance of a model could be done by...

a)

t test

b)

F test

c)

chi square test

d)

Wald test

38.

Stochastic variables are:

a)

Deterministic values

b)

Non-random value

c)

Imply causation

d)

Have probability distribution

39.

Observed value minus predicted value of the response variable…

a)

Residual

b)

Explanatory Variable

c)

Intercept

d)

Lurking Variable

40.

The locus of the conditional means of Y for the fixed values of X is the...

a)

Conditional expectation function

b)

Population Regression Line

c)

Intercept line

d)

Linear Regression Line

41.

Under least square procedure larger the ui larger is the...

a)

Standard error

b)

Regression error

c)

Explained sum of squares

d)

Squared sum of Residuals

42.

The residual is ___

a)

y-ȳ​

b)

y-hat ȳ

c)

hat y- ȳ​ ​

d)

estimates the error

e)

is estimated by the error

43.

The probability of rejecting the null hypothesis when it is true is called...

a)

Level of confidence

b)

Level of significance

c)

Power of test

d)

None of the above

44.

The choice of one tailed or two tailed test depends upon...

a)

Null Hypothesis

b)

Alternative Hypothesis

c)

Both

d)

None

45.

The value of R2 lies between ...

a)

-1 and 0

b)

-1 and 1

c)

0 and 1

d)

None of the above

46.

The correlation coefficient (r) is only used for linear regressions.

a)

True

b)

False

47.

The residual value can be calculated by subtracting: "predicted y - observed y"

a)

True

b)

False

48.

The least-squares regression line will always pass throught the ordered-pair (mean of x, mean of y).

a)

True

b)

False

49.

 Υ=β0 + β1X1\Upsilon=\beta_0\ +\ \beta_1X_1  This form of the OLS reggression line is also called the ...

(a)  

50.

 R2 R^2\   = SSE/SST = 1 - SSR/SST is define as ...



(a)