**– Introduction to Econometrics**

What is econometrics? Why a separate discipline?, methodology of econometrics, types of econometrics, understanding econometric modeling, use of econometrics for social scientists and business executives, regression as main tool of econometrics.

**– Two Variable Regression Model**

Population regression function, the significance of the stochastic disturbance term, the sample regression function, the role of statistical packages for econometric study.

**– Estimation Two Variable Regression Model**

The method of ordinary least squares (OLS), the basic assumption underlying the method of OLS, the properties of least squares estimators: Gauss Markov Theorem,

Standard error of the estimates, estimator of the variance of the disturbance term, Coefficient of determination, some illustrative examples of the two variable regression models.

**– Classical Normal Linear Regression Model (CNLRM)**

Normality assumption of the disturbance term, why the normality assumption? properties of OLS estimators under normality assumption, the method of maximum likelihood (ML),

**– Two Variable Regression: **Interval Estimation and Hypothesis Testing

The chi-square, t distribution and F distribution, hypothesis testing, confidence interval approach & test of significance approach.

– Extensions of the Two Variable Linear Regression Model:

Regression through the origin, scaling and units of measurement, different functional forms of regression models (double log model, semi-log, reciprocal model and the logarithmic reciprocal model), interpretation of estimated parameters, measurement of elasticity.

**– Estimation of Multiple Regression Model**

The matrix approach to linear regression model, assumptions of classical linear regression model in matrix notation, OLS estimation, variance covariance matrix of the estimators, R. square and adjusted R square, hypothesis testing of equality of two regression coefficients, restricted least squares, testing for structural or parameter stability of regression models: the Chow test, testing the functional form of regression : choosing between linear and log-linear regression models, forecasting with multiple regression.

– Demonstration of Statistical Packages for Social Sciences (SPSS) / Econometric Views/STATA

2. Gujarati, D.N.:Basic Econometrics,4th Edition, McGraw Hill Publications,2003.

3. Pindyck, R.S., and D.L. Rubinfeld.: Econometric Models and Econometric Forecasts4th Edition, Irvin McGraw Hill, 1998.

4. Johnston, J.: Econometric Methods, 3rd edition, McGraw Hill, New York, 1984.

5. Kmenta, Jan: Elements of Econometrics, 2nd edition, Macmillan, New York, 1986.

6. Koutsoyiannis. A.: Introductory Econometrics, Harper & Row, New York, 1973.

7. Maddlala, G.S.: Introduction to Econometrics, John Wiley & Sons, New York, 1970.

8. Andrew M. Jones, Health Econometrics, University of York.