Aim and Content of Course
This course aims to: (a) provide students with an introductory knowledge of applied econometrics; and (b) enable students to estimate and evaluate linear regression models using the econometrics software package called EViews 5. In the econometric analysis of any socio-economic phenomena, the creation of some sort of “model” is the usual starting point of any analysis. Econometric model building involves the following seven steps: (i) the specification of a theoretical model, (ii) data collection; (iii) the specification of a model for estimation; (iv) the estimation of unknown parameters; (v) hypothesis testing; (vi) model evaluation; and (vii) simulation and forecasting.
This course focuses on estimation using ordinary least squares (step (iv)) and hypothesis testing using the t and F tests (step (v)). Where possible, estimation and hypothesis testing techniques will be illustrated by empirical examples that use either cross-section or time series data. The emphasis in this course is not in proving propositions, but rather on the strong connection between the assumptions made about the components of the regression model and the results that can be obtained, and the various difficulties that arise when analyzing real data.
General comments about the course and prerequisities:
In order to understand the material in this course, it is extremely desirable that students have some previous knowledge of linear algebra, differentiation (including partial differentiation), and probability.
Instruction in the use of the econometrics software package, EViews5, will be given as part of this course. This course will strictly avoid the use of matrix algebra.
One of the purposes of econometrics is to test hypothesis suggested by other areas of economics, for example, microeconomics and macroeconomics. As a result, econometrics should not be considered in isolation, but as a complement to other subjects taught in the Faculty of Economics and the PCP program.
Grades in this course will be awarded on the basis of a student’s performance in an end-of-semester written exam, and two pieces of homework to be handed in during the semester. Some of the problems on each peice of homework will involve the using EViews 5 for estimating some econometric models and interpreting the results. In determining a student’s final grade, the results for the written exam and homework will be combined using the weights 80:20 or 100:0, whichever gives the more favorable result for the student concerned.