APPLIED ECONOMETRICS USING EVIEWS-II

Paper Code: 
GECO 405
Credits: 
2
Periods/week: 
3
Max. Marks: 
100.00
Objective: 

The course will enable the students to

     1 To acquaint the students with the use of software EViews to detect the violation of assumptions of the regression model.

     2.To describe the use of EViews for estimating models with dummy independent variables.

 Course Outcomes (COs). 

Course Outcomes (at course level)

Learning and teaching strategies

Assessment Strategies 

 
 

On completion of this course, the students will:

CO206. Demonstrate the various methods of detecting the problems of multicollinearity, heteroscedasticity, autocorrelation and specification error using EViews.

CO207. Estimate and interpret models comprising of dummy variables.

CO208. Learn how to use statistical software , like EViews, in controlling the problems related with violation of OLS assumptions.

CO209. Learn how to use the qualitative values in cause-effect related phenomenon.

CO210. Be trained about practical knowledge related with interpretation of empirical  results for policy formulation 

Approach in teaching. Interactive Lectures, Discussion and Demonstration.

 

Learning activities for the students.

Practice modules and Assignments.

Practical File Preparation, Assignments, Semester end examinations.

 

 

9.00
Unit I: 
Multicollinearity Detection of the problem of multicollinearity.   
 
 
9.00
Unit II: 
Heteroscedasticity Detection of the problem of heteroscedasticity.
 
s.   
9.00
Unit III: 
Serial correlation Detection of the problem of serial   correlation
 
 
9.00
Unit IV: 
Specification error   Omitted variable and redundant variable tests.
 
 
Unit V: 

Qualitative (dummy) independent variables Illustration of the uses of dummy variable

ESSENTIAL READINGS: 
  1. Bhaumik, S. K. ,Principles of Econometrics. A Modern Approach Using EVIEWS. Oxford University Press, 1st Edition, 2015.

 

REFERENCES: 
  1. Asteriou, D. and Hall, S. G. Applied Econometrics . A modern Approach Using EVIEWS and MICROFIT. Palgrave Macmillan, 1st Edition, 2007.

E RESOURCES

  • Chow, G.,’Use of Dummy Variables in Testing for Equality between Sets of Coefficients in Two Linear Regressions. A Note’, American Statistician, 24(1), 50-52, 1970.

 

  • Mason, R. L. Gunst, R. F. and Webster, J. T., ‘Regression Analysis and   Problems of Multicollinearity’, Communications in Statistics A, 4(3),  277-292, 1975.
  • Kumar, T. k., ‘Multicollinearity in regression Analysis,’ Review of Economics          and Statistics, 57, 365-366, 1975.
  • Park, R. E., ‘Estimation with Heteroscedastic Error Term’, Econometrica,      34(4), 888, 1966.
  • Glejser , ‘A new Test for Heteroscedasticity,’ Journal of the American Statistical       Association, 64, 316-323, 1969.
  • Breusch, T. and Pagan, A., ‘A Simple test for Heteroscedasticity and Random            Coefficient Variation,’Econometrica, 47, 1287-1294, 1979.
  • Durbin, J. and Watson, G. S., ‘Testing for Serial Correlation in Least Squares      Regression,’Biometrika, 38, 159-171, 1951.

 

JOURNALS

  • Theoretic and Applied Econometrics: http://www.ectap.ro/

 

Academic Year: 
2023-24
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