**Subject Code/Name:** ECOM20001 Econometrics 1 (Renamed - previously known as Introductory Econometrics)

**Workload:** 2 x 1 hr lectures and 1 x 1 hr tutorials a week

**Assessment:** - 3 x Assignments (15% total)

- Tutorial (5%)

- Weekly Quiz (10% total)

- Exam (70%)

**Lectopia Enabled:** Yes, with screen capture.

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

**Textbook Recommendation:** *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.

**Lecturer(s):** David Byrne

**Year & Semester of completion:** 2020 Semester 1

**Rating:** 5 out of 5

**Your Mark/Grade:** H1 (95)

**Comments: ** 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.

**Content**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

**Software**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'.

**Assessments**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.

**Econometrics 1 vs Quantitative Methods 2**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)

**Final Thoughts**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.