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 2025 in Semester 1 and Semester 2 at Clayton. It needs ETB1100, FIT1006, ETC1000, SCI1020, ETF1100, STA1010, ETW1001 or ETX1100 and unlocks 28 units, leading on to 42 units in all.
- Credit points
- 6
- Offered in 2025
- Semester 1, Semester 2
- Clayton
- Assessment
- Exam 120%
- and 3 other tasks
- Workload
- 144 hours
- per semester
This is the 2025 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETC2410
Prerequisites
Pass these before you enrol.
- ETB1100Business statisticsNo reviews yet
- FIT1006Business information analysisNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- SCI1020Introduction to statistical reasoningNo reviews yet
- ETF1100Business statisticsNo reviews yet
- STA1010Statistical methods for scienceNo reviews yet
- ETW1001Introduction to statistical analysisNo reviews yet
- ETX1100Business statisticsNo reviews yet
Prohibitions
You can't enrol if you have passed any of these.
After ETC2410
28 units list ETC2410 as a prerequisite or corequisite.
- ETC3400Principles of econometricsNo reviews yet
- ETC3410Applied econometricsNo reviews yet
- ETC3450Applied time series econometricsNo reviews yet
- ETC3460Financial econometricsNo reviews yet
- ETC3550Applied forecastingNo reviews yet
- ETC3580Advanced statistical modellingNo reviews yet
- ETC5340Principles of econometricsNo reviews yet
- ETC5341Applied econometricsNo reviews yet
Show 20 more
- ETC5345Applied time series econometricsNo reviews yet
- ETC5346Financial econometricsNo reviews yet
- ETC5550Applied forecastingNo reviews yet
- ETC5580Advanced statistical modellingNo reviews yet
- ETF3200Applied econometricsNo reviews yet
- ETF3210Econometrics and statistics of the environmentNo reviews yet
- ETF3231Business forecastingNo reviews yet
- ETF3300Quantitative methods for financial marketsNo reviews yet
- ETF3500High dimensional data analysisNo reviews yet
- ETF3600Quantitative analysis of limited dependent variablesNo reviews yet
- ETF5231Business forecastingNo reviews yet
- ETF5320Applied econometricsNo reviews yet
- ETF5321Econometrics and statistics of the environmentNo reviews yet
- ETF5330Quantitative methods for financial marketsNo reviews yet
- ETF5500High dimensional data analysisNo reviews yet
- ETF5600Quantitative analysis of limited dependent variablesNo reviews yet
- ETW3420Time series forecasting: Principles and practiceNo reviews yet
- ETW3450Applied time series econometricsNo reviews yet
- ETW3481Econometric methods for financeNo reviews yet
- ETW3510Applied econometric methodsNo reviews yet
Enrolment rules
If students 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 2025
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | Blended |
| Second semester | Clayton | Blended |
Assessment
- Within semester assessment40%
- Examination60%
- Quiz / Test10%
- Written30%
- Examination60%
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
- Workshops12 hours
- Seminars24 hours
- Tutorials12 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 2025 handbook.
- ACTRLSTD02Core unitsActuarial studiesNo reviews yet
- ACTRLSTD07Additional actuarial studies unitsActuarial studiesNo reviews yet
- BUSANLMJ01Additional business analytics unitsBusiness analyticsNo reviews yet
- BUSANLYT09Additional business analytics unitsBusiness analyticsNo reviews yet
- ECONOMTR02Core unitsEconometricsNo reviews yet
- ECONOMTR05Core unitsEconometricsNo reviews yet
- FINANCE07Core unitsFinanceNo reviews yet
- FININMAT04Financial and insurance mathematics elective unitFinancial and insurance mathematicsNo reviews yet
- MTHFNDEC01Core unitsMathematical foundations of econometricsNo reviews yet
Contacts
- Chief Examiners
- Akanksha Negi
- Dr Didier Nibbering
Common questions
What are the prerequisites for ETC2410?
You need ETB1100, FIT1006, ETC1000, SCI1020, ETF1100, STA1010, ETW1001 or ETX1100 before you enrol. Enrolment rules also apply.
What can I take after ETC2410?
ETC2410 is a prerequisite or corequisite for 28 units, including ETC3400, ETC3410, ETC3450, ETC3460, ETC3550 and ETC3580. Those lead on to 42 units in all.
When is ETC2410 offered?
In 2025, 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 120% of the final mark, alongside 4 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.