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ECONOMETRIC ANALYSIS

EIE3003 ECONOMETRIC ANALYSIS
3 Credits

Pre-requisite EIA2006 Basic Econometrics

Learning At the end of the course, the students are able to:
Outcomes
1. estimate econometric models;
2. use econometric software and models for estimations, inference and
predictions;
3. evaluate the results from the applications of econometric analysis; and
4. draw valid conclusions from the results of the analysis.

Synopsis This course covers the classical regression model using matrix approach.
Diagnostic testing and problems of estimation (multicollinearity, heteroscedasticity,
and autocorrelation) are discussed in the context of the relaxation of classical
assumptions. Advanced topics on single-equation system cover independent and
dependent dummy variables as well as distributed lag and autoregressive models.
This course is taught using analytical and empirical approaches through the use of
statistical software.

th
References 1. Gujarati, D and D.C. Porter, 2009, Basic Econometrics, 5 ed., McGraw-Hill.
2. Stock, J.H., and M.W. Watson, 2007, Introduction to Econometrics, 2 ed.,
nd
Pearson.
nd
3. Wooldridge, J. M.2003. Introductory Econometrics: A Modern Approach, 2
ed., Thompson Learning.
4. Pyndick, R. S. & Rubinfeld, D. L. 1991. Econometric Models and Economic
rd
Forecasts, 3 ed., McGraw-Hill.

Soft Skills CS1, CS2
CT5

Assessment Continuous Assessment : 40%
Final Examination : 60%

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