Syllabus (ECONOMICS)
Course Type: MAJ-16
Semester: 8
Course Code: BECOMAJ16T
Course Title: Econometrics - II
(L-P-Tu): 5-0-1
Credit: 6
Practical/Theory: Theory
Course Objective:
Learning Outcome: Course Objective: To Provide Basic Knowledge in Data Handling with econometric methods. To empower the students in analyzing the data behaviour with econometric methods. To understand the data handling problems and econometric interpretation. To handle th
- Limited Dependent Variable Models: (12)
- Linear Probability Model
- Logit Model
- Probit Model
- Specification Issues in Binary Response Models
- Simultaneous Equation System: (1
- Forms of Simultaneous Equation System
- Identification Problem
- The concept of identification with economic examples. Observationally equivalent structure. Order and Rank Conditions
- Estimation Problem
- Consequences of estimating simultaneous equation system by OLS method.
- Unbiasedness and consistency of estimator-use of the concept of plim. Recursive system.
- ILS estimator with properties,
- IV estimator with properties,
- Basics of Time Series Econometrics: (12)
- Properties of time series,
- ACF and PACF - Some Useful Processes
- White Noise,
- Random Walks,
- MA Processes,
- AR Processes,
- ARMA Processes and
- ARIMA Processes
- ARIMA models- identification, estimation, diagnostic testing,
- Analysis of Time Series and Box-Jenkins Method, Barlett’s test, Box-pierce Q-test, Ljung-Box test, Unit Root Tests,
- Trend Stationary and Difference Stationary process,
- Forecasting- MA(1), ARMA(1,1) and ARIMA(1,1,0) processes, Seasonality
- Modeling with Trends: (12)
- Deterministic and stochastic trends,
- Removing the trend,
- Spurious Regression,
- Cointegration:
- General cointegrated system,
- Error correction model and tests for cointegration;
- Cointegration in single equations-
- Engle-Granger method,
- CRDW test,
- System estimation method – Johansen procedure
- Basics of Panel Data: (12)
- Sources and Types of Panel Data
- Pooled Estimator
- Random Effect Model
- Fixed Effect Model
- Fixed versus Random Effects Model & Hausmann Test
- Dynamic Panel
Reading References:
- Johnston, J., 1977 and 1984, Econometric Methods, 2nd and 3rd Editions, McGraw-Hill.
- Johnston, J. and Dinardo, J., 1997, Econometric Methods, 4th Edition, McGraw-Hill International Edition.
- Hamilton, J. D. ,1994, Time Series Analysis, Princeton University Press.
- Granger, C.W.J. and Newbold, P., 1977, Forecasting Economic Time Series, 2nd Edition, Academic Press.
- Greene, W.H., 1997, Econometric Analysis, 3rd Edition, Prentice Hall.
- Gujarati, D.N., 1995, Basic Econometrics, 4th Edition, McGraw-Hill, New Delhi.
- Enders, W., 2004, Applied Econometric Time Series, Wiley.
- Maddala, G.S., 1997, Econometrics, McGraw Hill, New York.
Basic Features
Undergraduate degree programmes of either 3 or 4-year duration, with multiple entry and exit points and re-entry options, with appropriate certifications such as:
- UG certificate after completing 1 year (2 semesters with 40 Credits + 1 Summer course of 4 credits) of study,
- UG diploma after 2 years (4 semesters with 80 Credits + 1 Summer course of 4 credits) of study,
- Bachelor’s degree after a 3-year (6 semesters with 120 credits) programme of study,
- 4-year bachelor’s degree (Honours) after eight semesters (with 170 Credits) programme of study.
- 4-year bachelor’s degree (Honours with Research) if the student completes a rigorous research project (of 12 Credits) in their major area(s) of study in the 8th semester.
Note: The eligibility condition of doing the UG degree (Honours with Research) is- minimum75% marks to be obtained in the first six semesters.
- The students can make an exit after securing UG Certificate/ UG Diploma and are allowed to re-enter the degree programme within three years and complete the degree programme within the stipulated maximum period of seven years.