6 points, SCA Band 3, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Department of Econometrics and Business Statistics
- First semester 2018 (On-campus)
This unit presents econometric models and techniques that are widely used in modern applied econometrics. Emphasis is placed on models that address the special problems that arise when analysing microeconomic data, that is, data at the level of individual consumers, households and firms. The topics covered include modelling discrete dependent variables, modelling data sets that have both a cross-section and a time-series dimension and conducting inference in models in which the dependent variable is jointly determined with one or more of the regressors. The models taught in this unit are widely used in empirical work in economics, finance and marketing.
The learning goals associated with this unit are to:
- conduct statistical inference in statistical models with a binary dependent variable (LOGIT and PROBIT models)
- conduct statistical inference in statistical models with a limited dependent variable (TOBIT and Censored Regression models)
- conduct statistical inference in statistical models with one or more endogenous explanatory variables
- conduct statistical inference in a system of simultaneous equations
- conduct statistical inference on data that has a time series dimension.
Within semester assessment: 40% + Examination: 60%
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, 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