This course is the second part of a optional two-course sequence. This part is to be taught in Semester IV following the first part in Semester III. The objective of this sequence is to acquaint the students with advanced econometric topics.
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.