ETC5420 - Microeconometrics - 2018

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 Xueyan Zhao

Coordinator(s)

Professor Xueyan Zhao

Unit guides

Offered

Clayton

  • First semester 2018 (On-campus)

Prerequisites

Students must have passed ETC3400, ETC3410 or equivalent or be granted permission by the Chief Examiner to undertake this unit.

Prohibitions

ETC5420, BEX4420

Synopsis

This unit involves the analysis of micro-level cross-sectional and panel data to study the behaviour of individuals and other micro-units as decision makers. It studies the specification, estimation, inference and evaluation of a range of microeconometric models. These include models for discrete, count, duration, censored or truncated dependent variables and examine issues arisen from sample selection and endogenous treatment. The aim of the unit is also for students to gain hands-on experience and computation skills for analysing large scale micro datasets. The computing package used for the unit is STATA.

Outcomes

The learning goals associated with this unit are to:

  1. become familiar with typical features and structures of micro datasets
  2. be able to identify microeconometric models suitable for given micro datasets and given research objectives
  3. be able to specify, estimate, evaluate and analyse econometric models with dependent variables that are binary choices, multinomial discrete choices, durations, censored or truncated, using a given dataset
  4. be able to summarise and present key model results and measures of interest in tables and graphs
  5. be comfortable and proficient with the use of STATA software to manage and analyse large datasets
  6. have had hands-on experience with analysing several real world micro datasets in health, labour, finance and marketing research, through computing exercises and a written assignment.

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