Leader: Associate Professor Gael Martin

Offered

Clayton Second semester 2008 (Day)

Synopsis

This unit provides a formal treatment of the core principles underlying econometric and statistical analysis, with particular focus given to likelihood-based inference. Topics covered include the likelihood principle and maximum likelihood estimation; minimum variance unbiased estimation; maximum likelihood asymptotic distribution theory; likelihood-based hypothesis testing; and quasi-maximum likelihood inference. The theoretical developments are supplemented by numerical results produced using computer simulation. Consideration is also given to the numerical optimization techniques used to implement likelihood-based procedures in practice.

Objectives

The learning objectives of this unit are to:

The learning objectives of this unit are to:

• consolidate the core principles underlying econometric and statistical analysis;
• understand and implement the technique of maximum likelihood estimation and develop an appreciation of the associated asymptotic distribution theory;
• understand and implement likelihood-based hypothesis testing and quasi-maximum

• develop the skills needed to demonstrate and explore theoretical sampling properties using computer simulation.

Assessment

Within semester assessment: 40%
Examination (2 hours): 60%

Contact hours

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

Prerequisites

ETC2400 or ETC2410 or permission