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UNIT-II SIMPLE LINEAR REGRESSION MODEL - Specification – Assumptions – Least squares criterion – Ordinary least squares method of estimation.

UNIT-III PROPERTIES OF ESTIMATORS - Properties of good estimators – Small and large samples - Properties of OLS estimators in the classical linear regression model – Gauss Markov theorem (without proof)

UNIT -IV STATISTICAL SIGNIFICANCE OF ESTIMATORS - Testing of hypotheses – ‘t’ and ‘F’ tests - Confidence interval - Test of goodness of fit (R2) – Inference – Interpretation – Simple applications.

UNIT –V FUNCTIONAL FORMS OF MODEL - Linear trend - Double log – Semi log – Reciprocal – Polynomial forms

UNIT -VI MULTIPLE LINEAR REGRESSION ANALYSIS - Model – Assumptions – Estimation – Testing – R2 and adjusted R2 – Statistical inference – Interpretation – Partial correlation –Simple economic applications.

UNIT-VII MULTICOLLINEARITY - Definition – Reasons – Consequences – Tests – Remedial measures.

UNIT –VIII HETROSCEDASTICITY - Definition – Reasons - Consequences – Tests – Spearman’s rank correlation test - Goldfeld and Quandt test – Likelihood ratio test

UNIT -IX AUTO CORRELATION - Definition – Reasons – Consequences – First order auto regressive model – Durbin and Watson test – Remedial measures

UNIT –X DUMMY INDEPENDENT VARIABLE MODEL - Concept – Uses – Dummy variable trap – Estimation – Inference – Interpretation.

REFERENCE :

• Damodar Gujarati ‘Essentials of Econometrics’ Irwin Mcgraw Hill, Newyork, 1998.
• A Koutsoyiannis ‘Theory of Econometrics’ Palgrave, 1999.
• Robert S. Pindyck & Daniel L. Rubinfeld Econometric Models and Economic Forecasts’ Irwin Mcgraw Hill. Newyork – International Student Edition, 1998.