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ECON13-300: Advanced Econometrics


Many types of economic and financial data naturally occur as a series of data points in temporal order. Stock market indices are a classic example of such time series. Standard statistical methods are not appropriate for such data. This subject provides an introduction to time series econometrics with an emphasis on practical applications to typical economic and financial issues. Emphasis will be placed on determining when it is appropriate to use the various time series econometrics techniques and the use of appropriate software to conduct the analysis.

Subject details

FacultyBond Business School
Semesters offered
  • September 2022 [Standard Offering]
  • September 2023 [Standard Offering]
Study areas
  • Business and Commerce
Subject fees
  • Commencing in 2022: $3,950
  • Commencing in 2023: $4,050

Learning outcomes

1. Demonstrate the mathematical skills needed to derive autocorrelation functions to fit an appropriate univariate time series model. 2. Apply linear and non-linear univariate techniques of time series models for business forecasts. 3. Analyse the statistical significance of stationarity of time series through unit root tests. 4. Critically analyse the theoretical and technical knowledge of Vector Autoregressive Models and Vector Error Correction models to establish and differentiate both short and long run relationships between the variables. 5. Demonstrate the advanced knowledge of unit roots and cointegration in the context of panel data regression models. 6. Demonstrate the ability to produce a written report that communicates ideas clearly, cogently, and thoroughly, using a professional style and format. 7. Demonstrate the ability to work effectively with others to successfully complete a project.

Enrolment requirements

Requisites: ?


Assumed knowledge:

Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.

Assumed Prior Learning (or equivalent):

Restrictions: ?


Subject outlines

Subject dates

Standard Offering
Enrolment opens18/07/2021
Semester start13/09/2021
Subject start13/09/2021
Cancellation 1?27/09/2021
Cancellation 2?04/10/2021
Last enrolment26/09/2021
Withdraw – Financial?09/10/2021
Withdraw – Academic?30/10/2021
Teaching census?08/10/2021
Standard Offering
Enrolment opens17/07/2022
Semester start12/09/2022
Subject start12/09/2022
Cancellation 1?26/09/2022
Cancellation 2?03/10/2022
Last enrolment25/09/2022
Withdraw – Financial?08/10/2022
Withdraw – Academic?29/10/2022
Teaching census?07/10/2022