1. To acquaint the students with the statistical concepts used in econometrics.
2. To estimate and interpret the simple and multiple linear regression models.
3. To acquaint the students with the estimation and use of various functional forms.
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. Time series, cross-section, pooled and panel data.
Nature of regression analysis.PRF and SRF.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.Choice of functional form. Regression through origin
Estimation of parameters; properties of OLS estimators; partial regression coefficients; goodness of fit - R2 and adjusted R 2; testing hypotheses – individual and joint.
1. Gujarati, D. N. and Porter, D.C., Essentials of Econometrics, McGraw Hill, International Edition. 4th Edition, 2010.
2. Dougherty, C., Introduction to Econometrics, Oxford University Press, 5th Edition, 2016.
3. Koutsoyiannis, A., Theory of Econometrics, Palgrave Macmillan, 2nd Edition, 2001.
1. Klein, Lawrence R. , An Introduction to Econometrics, Printice-Hall, Englewood Cliffs, NJ, 1962.
2. Walters, A. A. , An Introduction to Econometrics., Macmillan, 1968.
3. Smith, A. and Taylor, J. E., Essentials of Applied Econometrics, University of California Press, 2017.
4. Kmenta, J., Elements of Econometrics, Indian Reprint, Khosla Publishing House, 2nd Edition, 1997.