Econometrics

Paper Code: 
STT 421
Credits: 
5
Contact Hours: 
75.00
Max. Marks: 
100.00
Objective: 

This course is meant for training the students in econometric methods and their applications. This course would enable the students in understanding the economic phenomena through statistical tools and economics principles.

 

Students will able to

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

 

Paper Code

Paper Title

STT-421

Econometrics

 

CO 84: Construct, test, and analyse and interpretate econometric models, using variables and relationships commonly found in studies of economic theory;

 

CO 85: Identify key classical assumptions in the field of econometrics, explain their significance, and describe the effects that violations of the classical assumptions can have.

 

CO 86: Use the least squares method in evaluating the relationship of one explanatory variable to the dependent variable and the relationships of multiple explanatory variable to the dependent variable

 

CO 87: Remove the problems of econometrics such as heteroscedasticity, auto correlation, multicollineraity.

 

CO 88: Able to make use of econometric models in your own academic work

Approach in teaching:

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

Learning activities for the students:

Assignments

Seminar

Presentation

Subject based  Activities

 

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

15.00
Unit I: 
UNIT I

Representation of Economic phenomenon, relationship among economic variables, the general linear model and its extensions, basic assumptions, Ordinary least squares estimation and prediction, generalized least square estimation and prediction.

 

15.00
Unit II: 
UNIT II

Heteroscedasticity, Auto-correlation: its consequences and tests (Durbin Watson test), Multicollinearity: problem, its implications and tools for handling the problem

 

15.00
Unit III: 
UNIT III

Linear regression and stochastic regression, instrumental variable estimation, autoregressive linear model, lagged variables, Distributed Lag models: Koyck’s Geometric Lag model

 

15.00
Unit IV: 
UNIT IV

Simultaneous equation model: Basic rationale, Consequences of simultaneous relations, Identification problem, Conditions of Identification, Indirect Least Squares, Two-stage least squares, K-class estimators, Limited Information and Full Information Maximum Likelihood Methods.

 

15.00
Unit V: 
UNIT V

Three stage least squares, Generalized least squares, Recursive models, SURE Models. Mixed Estimation Methods, use of instrumental variables, pooling of cross-section and time series data, Principal Component Methods.

 

Essential Readings: 
  • Croxton, F.E .& Cowden, DJ. (1979): Applied General Statistics, Prentice Hallof India.
  • Johnston, J. (1984): Econometric Methods. McGraw Hill.
  • Judge, G.C., Hill, R.C., Griffiths, W.E., Lutkepohl, H. & Lee, T.C. (1988):Introduction to the Theory and Practice of Econometrics, 2nd Ed.John Wiley.
  • Kmenta, J. (1986): Elements of Econometrics, 2nd Ed. University of Michigan Press.
  • Koop, G. (2007): Introduction to Econometrics, John Wiley.
  • Maddala, G.S. (2017): Introduction to Econometrics, 3rd Ed. John Wiley.
  • Pindyck, R.S. & Rubinfeld, D.L. (1998): Econometric Models and Economic Forecasts, 4th Ed. McGraw Hill.
  • Verbeek, M. (2008): A Guide to Modern Econometrics, 3rd Ed. John Wiley.
  • Judge, G.C., Hill, R,C. Griffiths, W.E., Lutkepohl, H. and Lee, T-C. (1988): Introduction to the Theory and Practice of Econometrics, Second Edition, John Wiley & Sons.
  • Kendall, M.G. and Stuart, A. (1968): The Advanced Theory of Statistics (Vol. III), Second Edition, Charles Griffin.
Academic Year: 
2021-2022
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