At present the centre offers four different certificate courses in online mode. The following table contains the name of the courses and the corresponding instructor.
No. | Name of Course | Instructor |
1. | Advanced Economic Theory | Dr. Rajit Biswas and Dr. Chandril Bhattacharyya |
2. | R. Package | Dr. M. Parameswaran |
3. | Financial Econometrics | Dr. Srikanta Kundu |
4. | Game Theory | Dr. Thiagu Ranganathan |
**Behavioral Economics is now included as an optional course in MA in Applied Economics. Hence it is not going to be offered as certificate course.
The outline of each course and the eligibility to attend the course is given below:
Advanced Economic Theory
Course Outline:
- Social Choice Theory- Basics, Mayes theorem Arrow’s Impossibility Theorem
- General Equilibrium Theory- Existence, Uniqueness and Stability of Competitive equilibrium, First and Second Welfare Theorems, Introduction to DSGE.
- Ricardian vs Non Ricardian Economies.
- Endogenous Growth Theory
- Knowledge Accumulation
- Productive public expenditure
- R&D
No. of classes: 10-12 lecture (one hour)
Expected Time: During second semester for the MA-I students. Exact date will be announced after the exam of the first semester.
References:
- Microeconomic Theory by Mascollel, Whinston and Green
- Game Theory by Osborne
- Economic growth by Robert J. Barro and Xavier Sala-i-Martin
Eligibility: Student who got at least 50% marks in their basic microeconomic course in MA-I programme.
R Package
Course Outline:
- Introduction – overview of features and elements.
- Vectors and vector operations
- Matrices and Arrays
- Lists
- Dataframes
- Factors and tables
- R programming structures
- Object oriented Programming
- Graphics
- Econometrics and statistics using R
- Linear regression
- Time series applications: unit root testing, cointegration,
- structural break
- Kemeny’s aggregation and ranking
- Computing Herfindhal index of industry concentration
- Coding cointegration breakdown test of Andrews andKim (2006)
- 6 Coding geographical agglomeration Ellison-Glaeser Index of Ellison and Glaeser (1997)
No. of classes: 10 lecture (one hour)
Expected Time: From 19th January 2021.
References:
Eligibility: Students who have a B.A/B.Sc./B.Com degree with basic knowledge in Statistics/Econometrics.
Financial Econometrics
Course Outline: This course covers econometric and statistical methods as applied to finance. Topics includes-
- Asset returns and efficient markets hypothesis
- Linear time series and dynamics of returns
- Discrete time volatility models (ARCH/GARCH) of returns
- Leverage effect and asymmetric GARCH models
- Capital asset pricing Model (CAPM) and GARCH-in-mean
- Multivariate time series and volatility Models
- Efficient portfolios and Global CAPM
- Nonlinear econometric model and their applications
- Markov switching models
- State space model and Kalman filter
No. of classes: 10-15 lecture (one hour)
Expected Time: From 15th February 2021.
References:
- Time series Analysis by Hamilton.
- Nonlinear time series in Empirical Finance by Frances and Van Dijk.
- Analysis of financial time series by Ruey S. Tsay
Eligibility: Students who attended the MA-I Econometric course with knowledge in basic time series (ARIMA modeling)
Financial Econometrics
Course Outline: This course covers econometric and statistical methods as applied to finance. Topics includes-
- Asset returns and efficient markets hypothesis
- Linear time series and dynamics of returns
- Discrete time volatility models (ARCH/GARCH) of returns
- Leverage effect and asymmetric GARCH models
- Capital asset pricing Model (CAPM) and GARCH-in-mean
- Multivariate time series and volatility Models
- Efficient portfolios and Global CAPM
- Nonlinear econometric model and their applications
- Markov switching models
- State space model and Kalman filter
No. of classes: 10-15 lecture (one hour)
Expected Time: From 15th February 2021.
References:
- Time series Analysis by Hamilton.
- Nonlinear time series in Empirical Finance by Frances and Van Dijk.
- Analysis of financial time series by Ruey S. Tsay
Eligibility: Students who attended the MA-I Econometric course with knowledge in basic time series (ARIMA modeling)
Game Theory
Course Outline: The Course will introduce the core concepts of Game Theory and its applications. Game theory and game theoretical thinking are essential for analyzing various situations in business, politics, and everyday life. The current course will deal with some of the important concepts of game theoretical thinking. It will delve Static and Dynamic Games with complete and incomplete information. We will deal with the following equilibrium concepts – Nash Equilibrium, Sub Game Perfect Equilibrium, Bayesian Nash Equilibrium, and Perfect Bayesian Equilibrium
- Introduction to the Course: Games, Players, Strategies, and Equilibrium
- Nash Equilibrium
- Mixed Strategies
- Sequential Games and Repeated Games
- Games with Incomplete Information – Static Games
- Games with Incomplete Information – Dynamic Games
- Auctions
No. of classes: 10 lecture (one hour)
Expected Time: From 15th February 2021.
References:
- Tadelis, Steven. Game theory: an introduction. Princeton University Press, 2013.
- Gibbons, R. S. (1992). Game theory for applied economists. Princeton University Press.
- Avinash Dixit, Susan Skeath, and David Reiley. (2012). Games of Strategy. Viva-Norton Student Edition. Third Edition.
Eligibility: Any Social science student having B.A. degree is eligible to attend the course.