This course provides a comprehensive introduction to basic econometric concepts and techniques. It covers statistical concepts of hypothesis testing, estimation and diagnostic testing of simple and multiple regression models.
Nature, scope and methodology of econometrics;
Statistical concepts: Normal distribution; chi-square, t- and F-distributions; estimation of parameters; properties of estimators; testing of hypotheses: defining statistical hypotheses Type I and Type II errors; power of a test.
Nature of regression analysis; assumptions of Classical Linear Regression Model, estimation of model by method of ordinary least squares; properties of least square estimators; Gauss-Markov theorem.
Goodness of fit; tests of hypotheses; scaling and units of measurement; confidence intervals; Chow Test, forecasting.
Log-linear model, semilog models, reciprocal models and logarithmic reciprocal model.
Estimation of parameters; properties of OLS estimators; partial regression coefficients; goodness of fit - R2 and adjusted R 2; testing hypotheses – individual and joint.