Loyola College B.A. Economics April 2006 Econometrics Question Paper PDF Download

LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

B.A. DEGREE EXAMINATION – ECONOMICS

AC 13

FOURTH SEMESTER – APRIL 2006

                                                             ST 4204 – ECONOMETRICS

 

 

Date & Time : 22-04-2006/9.00-12.00         Dept. No.                                                        Max. : 100 Marks

 

 

                                                            Section A

Answer all questions                                                                          ( 10 x 2 = 20 )

  1. What is the difference between a ‘Mathematical model’ and an ‘Econometric model’?
  2. Give any two properties of variance.
  3. Mention any two properties of OLS estimates.
  4. Let the sample space for a random experiment be S = {1, 2,…, 50}.Let A and B be two events defined on S with the event space A={all odd numbers between 1 to 50} and B={prime numbers between 1 to 50}.Are A and B independent?
  5. Give one example each for discrete and continuous random variable.
  6. What is meant by ‘Time series’ data? Give an example for the same.
  7. Interpret the following regression equation.

Y = 1.7 + 0.251X1 + 1.32X2

where  Y denotes the weekly sales( in ‘000’s)

X1 denotes the weekly advertisement expenditure

X2 denotes the number of sales persons.

  1. In a multiple regression model, the value of R2 is found to be 0.894.How would you interpret it?
  2. For a two variable regression model, the observed and estimated (under OLS) values of Y are given below:

Observed Y:    10         14        13        12        17

Estimated Y:    10         13        11        14        15

Calculate the standard error of the estimate.

  1. What is meant by ‘dummy variable’?

 

Section B

Answer any five questions                                                                 ( 5 x 8 = 40 )

  1. Define the following:
  1. Sample space
  2. Independent events
  3. Conditional probability
  4. Random variable
  1. If X is a random variable distributed as normal with mean 10 and variance 3  Find  a.) P(X<8)   b.) P(-1<X<5) c.) P(X>15)
  2. The following data relates to the family size(X) and family food spending(Y)

of 8 persons randomly selected from a small urban population.

Y: 40   50   50   70   80   100  110  105

X: 1      1     2     1     4      2      4      6

Assuming there is a linear relationship between Y and X, perform a regression of Y on X and estimate the regression coefficients. Also find the standard error of the estimate.

 

  1. Consider the following information from a 4 variable regression equation:

Residual sum of squares = 94;

Y = 10,12,14,9,7,8,2,22,4,12.

a.) Find TSS and ESS.

b.) Test the hypothesis that R2 = 0 at 5% level.

  1. Explain the concept of point and interval estimation with an example.
  2. Give the procedure for Chow’s test.
  3. Explain the ANOVA and ANCOVA models in regression analysis using

example.

  1. Consider the following data set:

Sample no.: 1  2           3          4          5

Y: 15 10        14        8          3

X: 1  2           3          4          5

Calculate the standard errors of the intercept and slope coefficients.

 

Section C

 

Answer any two questions                                                                 ( 2 x 20 = 40 )

 

  1. a.) Explain the different steps involved in an Econometric study.

b.) Mention the various assumptions in a Classical Linear Regression model.

(10 + 10 )

  1.  A bag contains three balls numbered 1, 2, 3 . Two balls are drawn at random , with replacement , from the bag. Let X denote the number of the first ball drawn and Y the number of the second ball drawn.
  1. Find the joint distribution of X and Y
  2. Find the marginal distributions of X and Y
  3. Find variance of X and variance of Y
  4. Are X and Y independent ?
  5. Calculate the correlation between X and Y

 

  1. a.) Explain the procedure for testing structural change using dummy

variables.

b.) Consider the following data on annual income (in 000’s $) categorized by

gender and age.

Income: 12         10       14       15        6       11       17

Gender:  0         1          1          0        0         1         1

Age:  1         1          0         1         0         0         1

where Gender = 1 if male; 0 if female

Age = 1 if less than or equal to 35; 0 if greater than 35.

Perform a regression of Income on Gender and age. Interpret the results.

What is the benchmark category for the above model?                        ( 8 + 12 )

  1. a) Explain the construction of 95% confidence interval for the slope

coefficient in a two variable regression model.

b.) Define the following:

1.) Standard error of the estimate

2.) Correlation coefficient

3.) Differential intercept

4.) Mutually exclusive events.

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