Applied Econometrics

Paper Code: 
25ECO 324 (A-P)
Credits: 
2
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 
  1. To acquaint the students with the basics of software EViews.
  2. To develop an understanding of the use of EViews for estimating simple and multiple linear regression models. 
  3. To appraise the students with the detection and remedial methods of multicollinearity, heteroskedasticity and autocorrelation problems with the help of software EViews.

 

Course Outcomes: 

Course Outcomes (COs):

Course

Learning outcome (at course level)

Learning and teaching strategies

Assessment Strategies 

Course Code

Course Title

25ECO 324 (A-P)

Applied Econometrics using EViews-I

(Practical)

Students will

CO103: examine the basics of EViews/ Stata software to estimate and interpret simple regression and examine the multiple regression models using EViews/ Stata software.

CO104:analyze different methods of detecting the problem of heteroscedasticity and autocorrelation and specification error in data using EViews/Stata

CO105: examine different methods of detecting the problem of multicollinearity in EViews/Stata software.

CO106: create a document related to different types of analysis using EViews/Stata software.

CO107: defend orally the findings of the analysis using EViews/Stata software.

CO108: contribute effectively in course-specific interaction.

 

Approach in teaching: Interactive Lectures, Discussion and Demonstration.

 

Learning activities for the students:

Practice modules and Assignments.

Practical File Preparation, Assignments, Semester end examinations.

 

12.00
Unit I: 
Simple Linear Regression Model

·       About EViews software package

·       Estimation of Simple Linear Regression Model

Presentation and interpretation of regression results

12.00
Unit II: 
The Multiple Linear Regression Model
  • Estimation of Multiple Linear Regression Model
  • Presentation and interpretation of regression results
  • Omitted Variable test, Redundant Variable test and Wald test of Coefficient Restrictions.

 

12.00
Unit III: 
Heteroscedasticity
  • Tests of heteroscedasticity
  • Estimation of White’s Heteroscedasticity-Consistent Standard Errors
  •  Weighted Least Squares Estimation.

 

12.00
Unit IV: 
Autocorrelation
  • The Durbin-Watson test, Breusch-Godfrey test, Estimation of model using Iterative Method, OLS regression with HAC Standard Errors.

 

12.00
Unit V: 
Multicollinearity
  • Tests for Multicollinearity- Correlation matrix, Computation of VIFs, Coefficient Variance Decomposition.

 

 

Essential Readings: 
  1. Bhaumik, S.K., Principles of Econometrics- A Modern Approach using EViews, Oxford University Press, 2015.

Cameron, A.C. &Trivedi, P.K.-Microeconometrics Using Stata, 2009. A Stata Press Publication, StataCorp LP, Texas

References: 

Suggested Readings:

 

  1. Gujarati, Damodar, N., Porter, Dawn C. and Pal, Manoranjan, Basic Econometrics,

McGraw-Hill Education, 2021.

  1. Dougherty, Christopher, Introduction to Econometrics, Oxford University Press, 2011.

E-Resources:

 

  • Data Set for Dougherty’s Book:

https://global.oup.com/uk/orc/busecon/economics/dougherty5e/student/datasets/

 

Journal:

 

  • Theoretic and Applied Econometrics

 

Academic Session: 
2025-26
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