Fundamentals of Econometrics

Course ID
FG 202
Level
Undergraduate
Program
BBA (FIA)
Semester
Second
Credits
6.0
Paper Type
Generic Elective
Method
Lecture & Tutorial

Unique Paper Code: 61015920

This course provides a comprehensive introduction to basic econometric concepts and techniques. It covers estimation and diagnostic testing of simple, multiple regression models, panel data models, and dummy variable regression with qualitative response regression models.

Learning Outcomes:

At the end of the course, students should be able to:

  • Understanding of basic econometries and its assumptions and impact of violations of classical assumptions
  • Interpretation of functional forms of regression model
  • Understanding of Panel data regression models, stochastic regressors and the method of instrumental variables
  • Understanding of models using dummy variable and Qualitative Response Regression Models.

Course Contents

Unit I
Unit II
Unit III
Unit IV

Unit I (2 Weeks)

Introduction to management; Evolution of management thought: Scientific, Administrative, Human Relations and Systems approach to management; Management functions and Managerial roles.

References:
Stephen P. Robbins & Mary Coulter, Management. 13th Ed. Pearson[Chapter 1]
Kaul Vijay Kumar, Business Organization & Management – Text and Cases, Pearson[Chapter 23]

Unit II (3 Weeks)

Planning: Importance and types of plans, planning process, MBO; Decision making: process, types, concept of bounded rationality; Control: process and types; Principles of organizing: common  organizational structures, Departmentalization: types of departmentalization, Delegation & Decentralization: Factors affecting the extent of decentralization, Process and Principles of delegation.

References:
Stephen P. Robbins & Mary Coulter, Management. 13th Ed. Pearson[Chapter 2,8,10,18]

Unit III (3 weeks)
Panel data regression models – the importance of panel data, Pooled OLS regression of charity function, the fixed effects least squares dummy variable (LSDV) model, Limitations of the fixed effects LSDV model, the fixed effect within group (WG) estimator, the random effects model (REM) or error components model (ECM), fixed effects model vs. random effects model and properties of various estimators. Stochastic regressors and the method of instrumental variables- the problem of endogeneity, the problem with stochastic regressors, reasons for correlation between regressors and the error term and the method of instrumental variables (2SLS).

References:
Gujarati, N. Damodar. Basic Econometrics. New Delhi: McGraw Hill. [Chapter 16]
Gujarati, N. Damodar. Econometrics by Examples. New Delhi: McGraw Hill. [Chapter 17 and 19]

Unit IV (3 weeks)
Dummy variables: Intercept dummy variables, slope dummy variables, Interactive dummy variables, Use of Dummy Variables to model qualitative/Binary/Structural changes, Other Functional Forms, Qualitative Response Regression Models or Regression Models with Limited Dependent Variables – Use of Logit, and Probit Models

References:
Gujarati, N. Damodar. Basic Econometrics. New Delhi: McGraw Hill. [Chapter 9 and 15] Gujarati, N. Damodar. Econometrics by Examples. New Delhi: McGraw Hill. [Chapter 3 and 8]

Additional Information

Text Books


Christopher Dougherty. Introductory Econometrics. Oxford University Press.
Gujarati, N. Damodar. Basic Econometrics. New Delhi: McGraw Hill.
Gujarati, N. Damodar. Econometrics by Examples. New Delhi: McGraw Hill.

Additional Readings


Pindyck, Robert S. and Daniel L. Rubinfeld Econometric Models and Economic Forecasts. Singapore: McGraw Hill.
Ramanathan, Ramu (2002). Introductory Econometrics with Applications (5th ed.). Thomson South Western

Teaching Learning Process

Class room lecture, Case study discussion, Numerical Problem solving, Class presentation on the assigned topic by students individually or in group, Workshop, Tutorials, Role play

Assessment Methods

Internal evaluation of 25% marks
a. Attendance 5% marks
b. Two internal evaluations by the teacher with 10% marks each out of which one must be a class test and other may be another test or home assignment or presentation. Faculty may take more than two assignments and (or) tests but total will be only 20% marks.
End term University Exam of 75% marks

Keywords

Dummy variables, random effects model or error components model multicollinearity, heteroscedasticity, autocorrelation

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