-Error in the variable: Properties of OLS under measurement error, Measurement error in dependent variable, measurement error in independent variable, Missing data and Outlying observation (solution for measurement error)
-Simultaneous Equation Models: The nature of simultaneous equation model, Simultaneity bias, IV estimator and its properties , Concept of identification and conditions for identification,Two Stage Least Square (2SLS), Statistical inference with IV estimator,Testingendogeneity and over identifying restriction, 2SLS and heteroskedasticity,
-Binary outcome model and Regression with Truncated and Censored Dependent Variable : Logit and Probit Models for Binary Response, The ‘Tobit’ Model for Corner Solution Responses, The Poisson Regression Model, Censored and Truncated Regression, Sample Selection Corrections
-Time Series Model: The Nature of Time Series Data, Classical Linear Regression Assumptions of Time series, Stationary and Weakly Dependent Time Series, Uni-variate Model (AR, MA and ARIMA models) , Vector Auto Regressive (VAR) Models: Reduced VAR, Recursive VAR and Structural VAR and Co-integrating Regression analysis.
-Basian Approach in Econometrics

1 Introductory Econometrics: A Modern Approach- Jeffery M. Wooldridge
2 Econometrics Analysis- William H. Green
3 Andrew M. Jones, Health Econometrics, University of York.
4 Pindyck, R.S., and D.L. Rubinfeld.: Econometric Models and Econometric Forecasts4th Edition, Irvin McGraw Hill, 1998.
5 Johnston, J.: Econometric Methods, 3rd edition, McGraw Hill, New York, 1984.
6 Griffiths, William E., R. Carter Hill and George G. Judge: Learning and Practicing Econometrics, John Wiley & Sons, New York, 1993.
7 Maddlala, G.S.: Introduction to Econometrics, John Wiley & Sons, New York, 1970.