ECOM20001: Econometrics 1

- 3 assignments (5% each)
- Tutorial participation (5%)
- weekly quizzes (1% each)
- Exam (70%)

A/Prof Dave Byrne

Multiple+sample exam, all with solutions.

5 out of 5

Introduction to Econometrics by Stock & Watson. However, Dave's slides are excellent and plenty sufficient and I didn't ever use the textbook.

- pre-recorded lectures (~2 hours)
- 1 one-hour tutorial

2021 Semester 1

95 H1

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- 3 x Assignments (15% total)
- Tutorial (5%)
- Weekly Quiz (10% total)
- Exam (70%)

Assignments: 3 group assignments spread throughout the semester worth 5% each. The assignments all require R and you would need to also submit an index page with all your codes at the end of the assignment. They're mostly maths/computing questions without much writing involved.

Exam: worth 70% and is hurdle like all FBE subjects. The exam is 2 hours long - 10 MCQ (section 1), 3 short answer (section 2) and 3 extended response questions (section 3).
Section 1 - mostly theory based, with some maths
Section 2 - mostly maths based, usually with at least one proof question
Section 3 - maths/computing based, including writing R pseudocode.

Weekly Quiz: 12 quizzes in total. Your 10 highest ones are counted. Worth 10% total.

Tute participation: I mean, this is the easiest 5% you'll ever get. Don't take it for granted. In our year, since it was the *Covid* semester where everything was online, Dave put this 5% to an entire new assignment where we had to write a full report and create an econometric regression model to analyse the effect of easing social distancing restrictions on the spread of Corona. Pray that you don't get anything like that.

If you are reading this, chances are you're trying to decide between Econometrics 1 and Quantitative Methods 2. I'll get to that at the end of the post. But first off, some disclaimers:

(i) I did this during the online semester, so our assessments were modified. I wrote this review without factoring in those changes to the best of my ability.

(ii) If you are noticing contradictions between my review and the previous two reviews in this thread, that is because this course was changed in 2018, but those reviews were from 2013 and 2017.

This subject may as well be renamed Regression 101 because that's the entire subject. The first week covers probability and statistics revision from QM1, the rest of the subject is wholly regression based. The topics are:
- Single linear regression
- Multiple linear regression
- Nonlinear regression
- Time series regression
- Regression application

Econometrics 1: Depth, quantitative, maths focus
Quantitative Methods 2: Breadth, qualitative, application focus

I highly recommend econ majors to do Econometrics 1 instead of QM2, as in 3rd year you MUST do at least one econometrics subject. If you did Econometrics 1, then the subjects you can choose from are:
- ECOM30002 Econometrics 2
- ECOM30003 Applied Econometrics Modelling
- ECOM30004 Time Series Analysis and Forecasting

But if you did QM2, the only subjects you can do are:
- ECOM30001 Basic Econometrics (which is essentially Econometrics 1)
- ECOM30002 Econometrics 2 (but only if you got H2A or above in QM 2)

As an arts major with a weak maths background and no prior experience in computing, I went into this subject feeling really unsure of whether I made the right choice of picking this over the renowned WAM-booster QM2. Econometrics 1 is quite a jump from QM1, and the first few weeks were challenging. But by the second half of the semester it easily became my most enjoyable subject. I absolutely loved this subject and highly recommend it to all Commerce and Arts (Economics) students.

Yes, with screen capture.

David Byrne

Yes, all exams from 2018 semester 1 are available, plus a sample exam.

5 out of 5

For this course, you must learn the programming language R (changed from the previous software Eviews). The additional packages used are 'AER', 'Stargazer', and 'ggplot2'.

Introduction to Econometrics, 3rd edition by Stock and Watson. It's not really required, and if you must get a textbook, then any that covers regression would do.

2 x 1 hr lectures and 1 x 1 hr tutorials a week

2020 Semester 1

H1 (95)

2 Short Answer-based assignments worth 10% each, Tutorial participation worth 5%, Mid-semester Test worth 0% or 10%, final exam worth 65% or 75%. Result is calculated using MST 10% and Exam 65%, then MST 0% and Exam 75%, and the higher mark is awarded. Assignments are largely just questions that test students' ability to apply knowledge (similar to QM1 assignments). They are reasonably simple if you've been paying attention. The exam is of appreciably greater difficulty.

Overall the subject is enjoyable insofar as it feels that what you are learning is useful. Initially much content is "repeated" from QM1 (basic probability, hypothesis testing and regression) albeit in greater detail. Those derivations that you "don't have to worry about, and just accept" in QM 1 are derivations that you need to commit to memory in this subject. The subject is almost entirely regression-based, but greater depth is achieved than the simple linear and multiple regression seen in QM1. Some time is devoted also to time-series analysis, and a few weeks are based upon troubleshooting a breakdown in the assumptions upon which simply regression analysis is based.

The content can become very dry, particularly in lectures, but if you enjoyed QM1 you will find Intro Ecom tolerable at least, and perhaps even interesting. The tutorials follow the standard format of pre-prep, going briefly through the pre-prep and then completing in-tute questions. The Mid-semester test and Assignments are quite simple, whereas the Exam is somewhat more demanding, placing greater emphasis on derivations and actual understanding of the underlying mathematics as opposed to simple application of methodology. Don't let it screw you over like it did me
It's worth noting that you will have to purchase/pirate and become reasonably familiar with the Eviews software. It isn't that difficult to use and fulfils a similar role to the Statistics Excel add-on does in QM1, but initially represents a small learning curve, and is required to complete assessments. Often eviews regression output is provided as part of assignment and exam questions with bits missing, so knowing what's where and how all the figures are inter-related is very helpful.

Yes, with screen capture.

Jenny Lye

Yes, three (if I recall correctly)

3.5 Out of 5

Text is not required. All examinable content is covered in lectures, though Principles of Economoetrics 4th ed., Hill, Griffiths & Lim is suggested.

2 x 1-hour lecture per week, 1 x 1-hour tutorial.

2013 SM2

75 H2A