This course goes beyond the simple ordinary least squares regression model. The course covers: review of ordinary least squares, feasible least squares, instrumental variables estimation, panel data estimation, simultaneous equations models, nonlinear models (discrete choice, censored, and sample selection). Maximum likelihood estimator and introduction to generalised method of moments. Despite its name, the course is highly theoretical. The software of choice for the applied component is STATA, basic knowledge of which is required.

Upon Completion of the course, the students will know:

• Estimation techniques used in Micro-Econometrics such as OLS, NLS, and more generally Extremum (or M) estimators including their asymptotic properties.
• Be familiar with concepts such as selection, endogeneity, simultaneity and instruments.
• Be able to formulate methods to estimate causality in economic models.
• To be able to understand and read and present seminal paper(s) in applied micro-econometrics.
• Be prepared to identify and execute research question involving cross sectional and panel data.

(subject to change) There will be four compulsory homework assignments. Each will count 10% towards the final course grade. There will be one compulsory final examination at the end of the semester. It will count 60% towards the final course grade.

3 contact hours plus private study time.

At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with introductory level courses in Economics, Statistics and Econometrics

The software of choice for the applied part is STATA with which you should be familiar.

Recommended Texts:

Microeconometrics: Method and Applications by A. Colin Cameron and Pravin K. Trivedi.

Econometric Analysis of Cross Section and Panel Data by Jeffrey M. Wooldridge.

For further information please refer to course website