ETC3400 - Principles of econometrics

Leader: Professor Don Poskitt

Offered

Clayton Second semester 2007 (Day)

Synopsis

Econometric and statistical techniques serve as the tools of inductive inference, enabling us to assess the size and likelihood of possible errors, to decide whether discrepancies between theory and practice can be attributed to chance, and to judge the merits of predictions based on past observations. Despite this generality a collection of basic ideas and concepts form the core principles underlying much econometric and statistical analysis. This unit discusses these core principles. Topic headings: models and data tructures, the general linear model and associated inference, the likelihood principle, maximum likelihood distribution theory, likelihood based inference.

Objectives

The learning objectives of this unit are to:

• consolidate the basic ideas and concepts that form the core principles underlying much econometric and statistical analysis;
• develop an understanding of different types of models, variables and data structures;
• analyze the general linear model, the Gauss-Markov Theorem and associated techniques of inference;
• understand principles, estimation and asymptotic distribution theory of maximum likelihood estimation;
• develop principles and procedure underlying likelihood based inference.

Assessment

Written assignments: 40%
Examination (2 hours): 60%

Contact hours

Two 1-hour lectures and one 2-hour tutorial per week

Prerequisites

ETC2400 or ETC2410 or permission