Objective:     The purpose of this course is to provide an introduction to regression, econometric and time series methods and to show how these methods can be used for exploring economic behavior. The course combines theory and application and emphasizes practice with statistical software.

Lecturer:     Dr C. Sukume

Lecture Hours: Wednesday 11-12, Thusday 8 - 9

Practical Hours: Friday 8 - 9; 10 - 12

Office Hours: Monday mornings and afternoons

Texts:

*Hu, T-W      Econometrics: An Introductory Analysis, 2nd Ed Baltimore:     University Park Press,
            1982

Gujarati, D.N. Basic Econometrics. McGraw - Hill, Toronto, 1988.

Wonnacott, R.J. and T.H. Wonnacott, Econometrics, Wiley, N.Y.

Maddala, G.S. Introduction to Econometrics, McMillan, 1988.

Matridakis, S. et al, Forecastine Methods and Applications, Wiley 1983.

Term 1

I. Introduction
      A.  The nature of Econometrics
      B.  Application in business and government

II.  Review of statistical inference
      A.  Probability
      B.  Random variable
C.  Estimation
      D.  Hypothesis testing

III.  Regression Methods
      A.  Simple Regression
            1.  Assumption of least squares analysis
            2.  The least square model and estimation
            3.  Properties of least squares model
            4.  Statistical inference in regression, summary     statistics
     B. Multiple Regression
            1.  Generalization to multiple regression
            2.  Use of summary statistics in multiple regression
            3.  Functional forms in regression analysis
            4. Dummy variables and other ad hoc methods

 Term 2
 IV.  Applications: Econometrics Analysis of Production, Supply and Demand

      A. The identification Problem
      B.    Production Functions
           1.  Specification
           2.  Estimation and interpretation
      C.    Supply Functions
           1.  Specification
           2.  Estimation and interpretation
      D.    Demand Function
           1.  Specification
           2.  Estimation and interpretation
      E.    Treating violation of least squares assumptions
           1.  Serial correlation
           2.  Heteroscedasity
           3.  Multi collinearity

V.   Analysis of Economic Time Series (Term 2 and 3)
A.    Reduced Form and Price Forecasting Equation
      B.    Smoothing Procedures
      C.    Decomposition of Trend, cycle, season and random elements
      D.    Box - Jenkins methods
           1.  Specification
           2.  Diagnostic Checking and Forecasting
      E.    Short-run and long-run effects: dynamic analysis
      F.    Evaluating Forecasting accuracy.

Term 3
VI. Revision