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ETC5341 · Applied econometrics

Official Handbook

2026 Handbook6 credit pointsLevel 5Department of Econometrics and Business Statistics

Last checked: 23 Aug 2026 UTC

Overview

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.

Offerings

CampusTeaching periodMode
ClaytonFirst semesterActivities scheduled as a mix of on-campus and online activities (BLENDED)

Assessment

The Handbook lists an examination for this unit.

#AssessmentTypeWeightHurdle
11 - ExerciseExercise40%
22 - ExaminationExamination60%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

prohibitions

  • ETC3410 — Applied econometrics
  • ETF3200 — Applied econometrics
  • ETF5320 — Applied econometrics
  • ETW3510 — Applied econometrics for behavioural modelling

Joined by OR.

prerequisite

  • ETC2410 — Introductory econometrics
  • ETC3440 — Introductory econometrics
  • ETF2100 — Introductory econometrics
  • ETF5910 — Introductory applied econometrics
  • ETW2510 — Statistical modelling for decision making
  • ETC5241 — Introductory econometrics

Joined by OR.

Learning outcomes

  1. conduct statistical inference in statistical models with a binary dependent variable
  2. conduct statistical inference in statistical models with one or more endogenous explanatory variables
  3. conduct statistical inference in a system of simultaneous equations
  4. conduct statistical inference on data that has both a time series and a cross section dimension
  5. interpret the results of econometric analysis of data in context
  6. describe the role of econometrics as it applies to the analysis of data.

Workload

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. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

ActivityDuration
Tutorials12 hours
Workshops12 hours
Seminars24 hours

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