ETS2410 - Introductory econometrics - 2019

This unit introduces students to the empirical analysis of relationships between economic variables. The approach is based on linear regression theory and emphasises 'hands on' data analysis. Topics studied will include properties of least squares estimators, hypothesis testing, the choice of appropriate functional form, the use of dummy variables, issues around modelling survey data, and the problems of serial correlation, heteroscedasticity and multicollinearity.

The learning goals associated with this unit are to:

1. understand and derive the properties of ordinary least squares in summation and matrix notation
2. interpret, evaluate and apply inferential methods to multiple linear regression
3. understand the use and implications of data scaling, functional form and dummy variables in regression modelling
4. identify the presence of heteroscedasticity, adjust OLS standard errors and perform feasible GLS in regression models
5. understand issues related to modelling with time-series data.

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, 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