Loyola College M.Sc. Statistics Nov 2003 Econometrics Question Paper PDF Download

LOYOLA COLLEGE (AUTONOMOUS), CHENNAI –600 034

M.Sc., DEGREE EXAMINATION – STATISTICS

THIRD SEMESTER – NOVEMBER 2003

ST-3950/S919 – ECONOMETRICS

12.11.2003                                                                                                           Max:100 marks

1.00 – 4.00

SECTION-A

Answer ALL questions.                                                                                   (10X2=20 marks)

 

  1. What is meant by a generalized least square estimator?
  2. Explain auto regressive process.
  3. What are lagged variables?
  4. What are the properties of OLS estimators of a linear model Y =u?
  5. What is multi collinearity?
  6. Explain specification error.
  7. What is the auto correlation?
  8. What are the reasons for auto correlation disturbances?
  9. What are the sources of non spherical disturbances?
  10. Explain the homoscedasticity property.

 

SECTION-B

Answer any FIVE questions.                                                                           (5X8=40 marks)

 

  1. Consider the linear Y =u with E (u) = 0 and E(uu!) = Prove that an unbiased estimate of  is given by  where r is the residual vector.
  2. Derive the MLE of the parameters of the linear regression model Y =
  3. Derive the variance – covariance matrix of the autocorrelated disturbance terms?
  4. Explain in detail the concept of multi cotnearity.
  5. Explain the effect of excluding the relevant variables is the linear model Y =
  6. Explain clearly the concept of hetroscedasticity property.
  7. Explain the concept of structural change.
  8. Write short notes on (i) dummy variables (ii) seasonal adjustment.

 

SECTION-C

Answer any TWO questions.                                                                           (2X20=40 marks)

 

  1. For the general linear model Y =u, derive the least square estimator and

find Var  .

  1. a) State and prove gauses Markov theorem.
  2. b) Derive the test procedures to test the linear hypothesis H:Rb = S for the general linear

model.

  1. a) What are the properties of OLS estimators under Non spherical disturbances?
  2. b) Explain the Drubin – Watson test to test for auto correlation. (8+12)
  3. a) Explain cochrane – orcutt iterative estimation procedure used in the presence of

autocorrelated disturbance.

  1. b) Describe the ALMON Lag model to estimate the parameters of a distributed Lag

model.                                                                                                              (10+10)

 

 

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