UnitLevel 2Undergraduate

ETC2410 Introductory econometrics

Faculty of Business and Economics

ETC2410 Introductory econometrics is a level 2, 6-credit-point, undergraduate unit from the Faculty of Business and Economics, offered in 2026 in Semester 1 and Semester 2 at Clayton. It needs ETB1100, ETC1000, ETF1100, ETW1001, FIT1006, SCI1020, STA1010 or ETX1100 and unlocks 27 units, leading on to 41 units in all.

Credit points: 6
Offered in 2026: Semester 1, Semester 2; Clayton
Assessment: Exam 60%; and 2 other tasks
Workload: 144 hours; per semester

This is the 2026 handbook entry. See the 2027 entry.

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Requisites

Before ETC2410

Prohibitions

You can't enrol if you have passed any of these.

One of

Prerequisites

Pass these before you enrol.

One of

After ETC2410

27 units list ETC2410 as a prerequisite or corequisite.

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Enrolment rules

If you are enrolled in course B6001, B6003, B6014 or B6030, there is no prerequisite.

To be successful in this unit, background knowledge and application of maths is required at the equivalent of VCE Year 12 Higher level. You may have satisfied this by completing relevant prerequisite unit/s, or you have covered relevant topics in your final years of secondary study. You should self-assess your maths competency prior to enrolling in this unit.

Equivalent units

The same content under another code. Only one of them counts.

Overview

This unit introduces you 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.

Offerings in 2026

Teaching period	Campus	Mode
First semester	Clayton	Blended
Second semester	Clayton	Blended

Assessment

Quiz / Test
10%
Written
30%
Examination
60%

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

Learning outcomes

When you finish this unit, you should be able 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.

Workload and teaching

Seminars24 hours
Tutorials12 hours
Workshops12 hours
Teaching approachActive learning
Teaching approachProblem-based learning

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.

This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.

This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.

Learning resources

Required resources

It is very important to have hands on practice to understand the concepts. The software that we use (EViews) is available via the Monash virtual environment (MoVE). The instructions on how to use the MoVE will be provided in the first tutorial in the first week. EViews is also used in Time Series ETC3450 and Financial Econometrics ETC3460, and is used by many financial and government institutions. If you are proficient in any other statistical software (e.g. SAS, SPSS, STATA, R), you can use that instead, but then you should not expect the teaching team to answer your software related questions.

Technology resources

There may be an additional cost associated with purchasing a physical and/or virtual calculator. Specific details will be provided in the Learning Management System by commencement of Orientation week.

Where it fits

ETC2410 is part of 9 areas of study in the 2026 handbook.

Contacts

Chief Examiners: Associate Professor Didier Nibbering; Dr Akanksha Negi

Common questions

What are the prerequisites for ETC2410?

You need ETB1100, ETC1000, ETF1100, ETW1001, FIT1006, SCI1020, STA1010 or ETX1100 before you enrol. Enrolment rules also apply.

What can I take after ETC2410?

ETC2410 is a prerequisite or corequisite for 27 units, including ECX5479, ETC3400, ETC3410, ETC3450, ETC3460 and ETC3550. Those lead on to 41 units in all.

When is ETC2410 offered?

In 2026, ETC2410 runs in Semester 1 and Semester 2 at Clayton.

How much work is ETC2410?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does ETC2410 have an exam?

Yes. The exam is worth 60% of the final mark, alongside 2 other tasks.

Which majors and minors include ETC2410?

ETC2410 is part of Actuarial studies; Business analytics; Econometrics; Finance; and Financial and insurance mathematics, and 1 other area of study.

More details

Credit points: 6
Level: 2
Study level: Undergraduate
Faculty: Faculty of Business and Economics
Organisational unit: Department of Econometrics and Business Statistics

Type: Coursework
EFTSL: 0.125
Student contribution: SCA Band 4
Study abroad: Available
Handbook years: 2020 2021 2022 2023 2024 202520262027