Loyola College M.A. Economics Nov 2006 Applied Econometrics Question Paper PDF Download

             LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034  M.A. DEGREE EXAMINATION – ECONOMICS

AN 27

THIRD SEMESTER – NOV 2006

         EC 3875 – APPLIED ECONOMETRICS

 

 

Date & Time : 06-11-2006/9.00-12.00         Dept. No.                                                       Max. : 100 Marks

Part  – A

 

Answer any FIVE questions in about 75 words each.                  (5 x 4 = 20 marks)

  1. What is meant by coefficient of determination?
  2. What is the confident interval for ‘β’ in a regression model?
  3. Suppose the hypothesis to be tested are

β2 + β3 = 0

β4 = 1

β5 = 0

Express that in the form Ho: Rβ = γ

  1. Define BLUE.
  2. What are the different kinds of time series analysis?
  3. What are the reasons to include error term in the model?
  4. What do you mean by panel data? Give an example.

Part – B

Answer any FOUR questions in about 300 words each.            (4 x 10 = 40 marks)

  1. Complete the following ANOVA based on a regression model

Source                   df        SS        MSS    F

Regression             –           800      –           –

Error                      45        –           –           –

Total                      49        1200                 .

Also obtain (i) Sample size           (ii) Adjusted R – square

  1. Explain the method used for testing a linear restriction.
  2. Explain the method of converting the Coub-Douglas function as a linear model. How will you test the linear hypothesis in that model.
  3. Explain Hansens test for stability.
  4. Discuss the practical problems posed by the distributed lag model in the direct application of OLS.
  5. Analyze the lagged case in time series regression model.
  6. Verify that the sampling variance depends not only on the disturbance variance but also on the sampling values of the explanatory variables.

Part – C

 

Answer any TWO questions in about 900 words each.              (2 x 20 = 40 marks)

  1. Given Y = family food spending, X1 = income, X2 = family size
Family 1 2 3 4 5 6 7 8 9 10
Y 40 50 50 70 80 100 110 140 160 200
X1 100 150 100 300 200 400 300 300 850 300
X2 1 1 2 1 4 2 4 6 1 8
  1. Explain tests of structural change in detail.
  2. Examine the various cases of panel data models.
  3. Obtain the variance-covariance matrix for correlated error term over time and bring out its consequences.

 

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Loyola College M.A. Economics Nov 2010 Applied Econometrics Question Paper PDF Download

LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.A. DEGREE EXAMINATION – ECONOMICS

THIRD SEMESTER – NOVEMBER 2010

    EC 3811 / 3875  – APPLIED ECONOMETRICS

 

 

 

Date : 09-11-10                 Dept. No.                                        Max. : 100 Marks

Time : 9:00 – 12:00

PART A

 

Answer any FIVE  of  the following questions:-                                                                      [ 5×4=20 marks]

 

  1. What is meant by structural break or structural change?
  2. Distinguish between probit and logit techniques.
  3. What is meant by count R2?
  4. What is censored regression?
  5. Define a ‘Random Walk Model’.
  6. What is cointegration?
  7. Distinguish between ‘ARCH’ and ‘GARCH ‘ models .

 

PART B

Answer any FOUR of the following questions:-                                                                   [4X10=40 marks]

 

  1. Outline the procedure for testing ‘Linear Equality Restrictions’.
  2. Explain the idea behind ‘Linear Probability Model.
  3. Outline Recursive Residual Test of model stability.
  4. Explain the Probit model as an alternative to LPM.
  5. Briefly explain the Error components Model in panel data regression.
  6. Explain the procedure of Box-Jenkins methodology.
  7. Discuss the estimation aspects of an ARIMA model.

 

PART C

Answer  any  TWO  of the following questions:-                                                                 [ 2X20=40 marks]

 

  1. Discuss the possibilities of panel data models under LSDV approach.
  2. Evaluate the tests of stationarity.
  3. Discuss the approaches to economic forecasting based on time series data.
  4. Explain the Arch and GARCH models in measuring volatility in financial time series.

 

 

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