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23932 Econometrics 3

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2019 is available in the Archives.

UTS: Business: Economics
Credit points: 6 cp
Result type: Grade and marks

There are course requisites for this subject. See access conditions.


This subject provides the advanced econometrics and its empirical application at the PhD level.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. Apply advanced econometric techniques that impose minimal functional form assumptions on the model that is being estimated
2. Apply methods that allow for heterogeneity in policy response among individuals. Methods that deal with set identification, structural auction models and econometric for games
3. Apply methods for high dimensional modelling and big data analysis

Contribution to the development of graduate attributes

This subject covers advanced econometric techniques to address identification issue of causal relationship when analysing experimental and non-experimental data (analysis of randomized control trials; instrumental variables; differences in differences approach) and heterogeneity in effect. Empirical papers will serve as examples. Applications will include topics in labour economics, economics of education, and others.

Teaching and learning strategies

The subject will be taught using a combination of lectures and tutorials, which may include computer lab sessions.

Content (topics)

  • Identification
  • Randomized Experiments
  • Instrumental variables
  • Differences in Differences
  • Quantile regression
  • Policy evaluation, treatment effects
  • Structural methods using expectations data
  • Expectations Formation
  • Empirics of Rational inattention models
  • Econometrics of peer effects


Assessment task 1: Assignments (Individual)


This addresses subject learning objective(s):

1, 2 and 3

Weight: 70%

Approximately 1000 words each

Assessment task 2: Final examination (Individual)


This addresses subject learning objective(s):

1, 2 and 3

Weight: 30%

20 minutes

Minimum requirements

Students must achieve at least 50% of the subject’s total marks.

Recommended texts

There is no required textbook in this course. Students will read selected chapters from books listed on References. The details will be provided by the instructor.

Other resources

A list of additional readings will be provided during the course.