Subject Code: HS7L005

Subject Name: Applied Econometric

L-T-P:     3-0-2

Credit:    4

Pre-requisite(s): None

Simple Linear Regression Model- Methods of Ordinary Least Squares – Assumptions and Properties of OLS Estimators –Standard Errors of Least Square Estimates - Test of Significance of the Parameter Estimates – Measure of Goodness of Fit: Classical Normal Linear Regression Model (CNLRM). Multiple Regression Analysis- The Three Variable Models: Notation and Assumptions – Meaning of Partial Regression Coefficients - OLS and ML Estimations of the Partial Regression Coefficient – R2 and Adjusted R2 , The Nature of Dummy Variables – ANOVA Models and ANCOVA Models –Use of Dummy Variables in Seasonal Analysis. Auto Correlation – Consequences of Auto Correlation – Tests and Solutions for the Case of Auto Correlation – Methods for Estimating the Auto Correlation Parameters, Multicollinearity – Tests for Detecting Multicollinearity – Remedial Measures, Practical Consequences of Multicollinearity, Heteroscedasticity- Detection of Heteroscedasticity- Remedial Measures- Method of Weighted Least Squares. The Nature of Qualitative Response Models: The Linear Probability Model- The Logit Model- Probit Model – Tobit Model – The Poisson Regression Model, Panel Data Regression Model. Simultaneous Equation Models: The Nature of Simultaneous Equation Models – Simultaneous Equation Bias – Identification Problem – Rules of Identification – Test of Simultaneity – Test  for Exogeneity - Recursive Models – Method of Indirect Least Square (ILS) – Two Stage Least Square (2SLS).

Text/Reference Books:

• Aigner, D. J., Basic Econometrics, Prentice Hall Publisher
• Dimitrios, Asteriou and Stephen G. Hall, Applied Econometrics: A Modern Approach Using Eviews and Microfit, Palgrave Macmillan, New York
• Gujurati, Damodar  N., Essential of Econometrics, McGraw-Hill, New York