Coming soon
ECONOMETRICS-II
Course Objectives:
The objectives of this course are-
- To acquaint the students with the use of dummy variable and panel data in econometric research and estimation of autoregressive and distributed lag models.
- To develop an understanding of the use of testing of stationarity, granger causality tests and forecasting with ARIMA models.
- To acquaint the students with the construction, identification, estimation and interpreting of simultaneous equations models.
Course Outcomes (COs):
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Course |
Outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Paper Code |
Paper Title |
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ECO 424(A-T) |
Econometrics-II |
CO64: Understand the meaning and applications of dummy variables. CO65: Acquire knowledge about estimation of panel data regression models. CO66: Analyse time series data and the estimation of various models based on time series data. |
Approach in teaching: Interactive Lectures and Discussions.
Learning activities for the students: Practice Modules and Assignments. |
Class activity, Assignments and Semester end examinations. |
Definition, Simple Regression Model with Dummy variable, interaction dummy, comparing two regressions(Chow test), Models with Dummy Dependent Variable- Linear Probability Model, Logit Model, Probit Model, Comparison between Logit and Probit Models, problem of disproportionate sampling, Measuring goodness of fit- Effron’s R2 and McFadden’s Pseudo R2, Examining the overall significance of regression.
Definition and Specification, Geometric Lag Approach, Estimation of Geometric Lag Model- The Koyck Method, Adaptive Expectations Model, Partial Adjustment Model, Almon’s Polynomial Lag Model.
Definition, usefulness and types, Panel Data Models- Constant Coefficients Model, Fixed-Effects Model, Random Effects Model, The Hausman Test.
Important concepts- stochastic process, stationary stochastic process, white noise stochastic process, random walk(with and without drift), unit root stochastic process, Tests for stationarity- Graphical approach, Autocorrelation function and Correlogram, Unit root test, Dickey-Fuller test, Augmented Dickey-Fuller test, Phillips-Perron test, Sources of non-stationarity, limitations of unit root test, Spurious regression problem.
Cointegration and Error Correction Mechanism- Engle-Granger cointegration test and ECM, ARIMA Forecasting- Box-Jenkins Methodology, Vector Autoregressive Model- Specification, estimation, forecasting, Vector Error Correction Model, merits and demerits of VAR
Causality tests- Granger Causality test and Sims Causality test
ARCH Model and GARCH model
Meaning , features and examples, OLS estimation ignoring simultaneity, Structural and reduced form equations, Identification problem- Rules and application, Estimation of Simultaneous Equations System- Indirect Least Squares and Two-Stage Least Squares.
Bhaumik, S.K., Principles of Econometrics- A Modern Approach using EViews, Oxford University Press, 2015.
