ETF5200 - Applied time series econometrics - 2019

6 points, SCA Band 3, 0.125 EFTSL

Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Business and Economics

Organisational Unit

Department of Econometrics and Business Statistics

Chief examiner(s)

Professor Jiti Gao

Coordinator(s)

Professor Jiti Gao

Unit guides

Offered

Caulfield

  • First semester 2019 (Evening)

Prerequisites

ETC3200, ETF3300, ETC3410, ETF5320, ETC5341 or equivalent.

Synopsis

Presents newly developed econometric methodology in model building and model evaluation in general. Recent literature on assessing business time series properties, non-linear time series models, multiple cointegration, impulse response function and variance decomposition is introduced. Examples in business, economics and finance will be drawn to illustrate the application of techniques covered in this unit.

Outcomes

The learning goals associated with this unit are to:

  1. test the properties of economic and financial time series under various conditions such as structural breaks and asymmetric assessment due to business cycles
  2. test if the modelling framework for the relationship between variables should be linear or nonlinear
  3. test for the existence of long run relationship and if it is nonlinear and stable
  4. conduct multivariate framework time series analysis based on vector auto regression
  5. test for the presence of multi-long run relationships and estimate the vector auto regressive model.

Assessment

Within semester assessment: 40% + Examination: 60%

Workload requirements

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

See also Unit timetable information