Introduction to Panel Data Analysis 2026 (Melbourne)

This course is designed for people familiar with panel data, including how to clean data and set it up for analysis, but now want to understand various statistical and econometric techniques that take full advantage of the panel nature of the data.

The topics covered in the course include:

• Longitudinal descriptive statistics, such as cross-wave correlations, conditional means and transition probabilities

• Regression analysis, including using pooled data, or cross-sectional techniques using lagged data

• Instrumental variables in panel data

• First-differences

• Second- (and longer) differences

• Fixed effects

• Random effects

• Binary response models

• Categorical response models

• Difference-in-differences

Data from the HILDA Survey will be used during the course and participants will be required to apply for, and be approved to use, the General Release 22 datasets prior to the course. The course will take several published papers using the HILDA Survey data with a view to reproducing some of the estimates presented by the authors. The course will be taught in Stata.

Course Instructor

The course will be presented by Professor Robert Breunig, who is a researcher at the Crawford School of Public Policy at the Australian National University. His primary applied research interests are in analysing individual and firm behaviour, evaluating government tax and transfer programs and analysing large data sets.

Pre-requisites

To participate in this course, you will need to:

• Have completed the Getting Started: Analysing HILDA with Stata course or have experience with the HILDA Survey data and be familiar with Stata

• Be familiar with regression theory

• Apply for and be approved to use HILDA General Release 22

• Have HILDA General Release 22 accessible from your laptop

• Have Stata (Version 14 or above) on your computer (student licenses can be provided if needed)

Cost (inc GST)

$1760 Standard
$1260 Masters or PhD student

Places are limited. Registrations close 5pm Friday 13 November 2026 unless all places are taken earlier. Cancellations after this will not be refunded.

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