University of Technology Sydney

# 23931 Econometrics 2

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 2024 is available in the Archives.

Credit points: 6 cp

Subject level:

Result type: Grade and marks

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

### Description

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

### Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. Basic statistical properties of linear regression and other estimators Methods for dealing with different data (cross section as well as panel data, discrete choice or count data) Methods for policy evaluation and estimation of parameters that are subject to endogeneity bias

### Contribution to the development of graduate attributes

This subject develops advanced econometric treatment at the honors and Ph.D. level. The course covers advanced techniques that are used in modern empirical research. During the discussion of estimation strategies, concrete empirical examples are provided.

### Teaching and learning strategies

The subject will be taught using a combination of lectures and tutorials, which may include computer lab sessions. Tutorial sessions will include instruction on the use of econometric software packages, such as STATA, MATLAB, etc.

### Content (topics)

The content will be selected from the following areas:

• Foundations of statistics and econometrics.
• Estimation of linear or nonlinear models, which may include instrumental variables, GMM, Maximum Likelihood, etc.
• Panel data models and limited dependent variable models.
• Methods for policy evaluation. Endogeneity issues and the methods to deal with them.

### Assessment

#### Assessment task 1: Assignment (Individual)

Objective(s): This addresses subject learning objective(s): 1 and 3 25%

#### Assessment task 2: Assignment (Individual)*

Objective(s): This addresses subject learning objective(s): 2 and 3 25% *Note: Late submission of the assessment task will not be marked and awarded a mark of zero.

#### Assessment task 3: Final examination (Individual)

Objective(s): This addresses subject learning objective(s): 1, 2 and 3 50%

### Minimum requirements

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

### Required texts

There is no single textbook that covers all the topics discussed in this subject. Nevertheless, most of the lectures are based on

Joshua D. Angrist and Jorn-Steffen Pischke: "Mastering ‘Metrics: The Path from Cause to Effect", Princeton University Press, 2014 [to give you an intuition of the econometric approach]

Joshua D. Angrist and Jorn-Steffen Pischke: "Mostly Harmless Econometrics", Princeton University Press, 2008. [to give you a more formal description of the approach]

### Recommended texts

Some useful reading materials are:

Scott Cunningham Causal Inference: The Mixtape is a nice book, similar in style and content to what we cover in class. There's also some R and Stata code.

James Stock and Mark Watson: "Introduction to Econometrics", 4th edition, Pearson. (this book is more at an introductory level but can be helpful if you find some concepts too advanced)

Jeff Wooldridge: "Econometric Analysis of Cross Section and Panel Data" 2nd edition. MIT Press. (this book is more formal but very good if you want to focus on the properties of an estimator)