Coming soon
ECONOMETRICS-II
- 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 appraise 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 |
CO63: Students willunderstand the meaning and applications of dummy variables. CO64:Students willanalyze the estimation of panel data regression models. CO65: Students willinterpret 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 independent variable(s) - ANOVA models, dummy variable trap, ANOVA model with interaction dummy, ANCOVA models, comparing two regressions - Chow test and dummy variable approach.
Models with Dummy Dependent Variable
Linear Probability Model, Logit Model, Probit Model, 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.
Time Series Econometrics-Important concepts
Stochastic process, stationary stochastic process, white noise stochastic process, random walk(with and without drift), unit root stochastic process, sources of non-stationarity, spurious regression problem.
Graphical approach, Autocorrelation function and Correlogram, Unit root test, Dickey-Fuller test, Augmented Dickey-Fuller test, Phillips-Perron test.
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.
Causality tests
Granger Causality test and Sims Causality test.
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.
