Introductory Econometrics

By Prof. Deb Kumar Chakraborty   |   Dibrugarh University
Learners enrolled: 566
This course provides a comprehensive introduction to basic econometric concepts and techniques. It covers statistical concepts of hypothesis testing, estimation and diagnostic testing of simple and multiple regression models. The course also covers the violations of the assumptions of OLS, the consequences of and tests for misspecification of regression models along with errors in variables. The specific objectives of the course are:
To analyse the nature and scope of Econometrics
To define hypothesis and process of hypothesis testing.
To define the implications of the assumptions of OLS
To discuss the violations of assumptions.
To discuss specification bias and errors in variables

Course Status : Ongoing
Course Type : Core
Duration : 12 weeks
Start Date : 30 Jan 2023
End Date : 30 Apr 2023
Exam Date :
Enrollment Ends : 15 Mar 2023
Category :
  • Humanities and Social Sciences
Credit Points : 4
Level : Undergraduate

Page Visits

Course layout

Week 1:
Module 1: Nature and Scope of Econometrics
Module 2: Models, Aims and Methodology of Econometrics
Module 3: Basic Statistical Concepts
Module 4: Estimate and Estimator, Point vs. Interval Estimation

Week 2:
Module 5: Properties of Estimators
Module 6: Probability Distributions
Module 7: Uses of Probability Distributions in Econometrics

Week 3:
Module 8: Hypothesis I
Module 9: Hypothesis II
Module 10: Type I and Type II Errors

Week 4:
Module 11: Power of a Test
Module 12: Tests for Comparing Parameters from two Samples

Week 5:
Module 13: Simple Linear Regression Model
Module 14: Stochastic Specification

Week 6:
Module 15: Ordinary Least Squares
Module 16: BLUE, The Gauss Markov Theorem, Goodness of fit
Module 17: k-variable linear regression model, Dummy variable

Week 7:
Module 18: Violations of Classical Assumptions
Module 19: Heteroscedasticity, Problem and Consequences

Week 8:
Module 20: Heteroscedasticity- Detection, Alternative Methods of Estimation.
Module 21: Autocorrelation, Sources and Consequences
Module 22: Tests of Autocorrelation

Week 9:
Module 23: Autocorrelation-Remedial Measures
Module 24: Multicollinearity-Problem and Consequences
Module 25: Detection of multicollinearity

Week 10:
Module 26: Multicollinearity- Remedial Measures
Module 27: Multicollinearity- Remedial Measures (contd.)
Module 28: Specification bias

Week 11:
Module 29: Omission of Relevant Variables
Module 30: Inclusion of Irrelevant Variables
Module 31: Test for Specification Bias

Week 12:
Module 32: Errors in Variable

Books and references

1. Gujarati, D.N. and Porter, D.C., Essentials of Econometrics, McGraw Hill.
2. Dougherty, C., Introduction to Econometrics, Oxford University Press.
3. Jan Kmenta, Elements of Econometrics, Indian Reprint, Khosla Publishing House.
4. Maddala, G.S., Introduction to Econometrics, Wiley India.
5. Studenmund, A.H., Using Econometrics-A Practical Guide, Pearson
6. Johnston, J. and Dinardo, J., Econometric Methods, McGraw-Hill 

Instructor bio

Prof. Deb Kumar Chakraborty

Dibrugarh University
Prof. Deb Kumar Chakraborty is Professor of Economics and Dean, Faculty of Social Sciences at Dibrugarh University, Dibrugarh. With more than twenty years of teaching experience at Post Graduate level, his areas of interest are Econometrics, Applied Macroeconomics, Industrial Economics and Regional Economics

Course certificate

1. Internal Assessment : 30%
2. External Assessment: 70%

Note 1. Internal Assessment includes Assignments to be submitted online by the learners, Interactions with the learners and time to time online MCQs

Note 2. External Assessment includes end-term examinations.

Minimum 40% in each would be required to pass the course and get completion certificate.

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