**Major:** Mathematical foundations of econometrics This major used to be referred to as the econometrics major, but there will be a change to that next year to accommodate for a more specialised version of the major that does not have significant overlap with actuarial science and business analytics, both under Monash’s Department of Econometrics and Business Statistics.

There has been quite a bit of change compared to the past, namely the inclusion of ECC3840, MTH3051 and MTH3140 which would certainly benefit individuals who seriously want to pursue academic work.

**First Year Subjects:**ETC1010 – Introduction to data analysis (elective)

**Second Year Subjects:** ETC2410 – Introductory econometrics

ETC2440 – Mathematics for economics and business

ETC2520 – Probability and statistical inference for economics and business

ECC2000 – Intermediate microeconomics (elective)

ECC2010 – Intermediate macroeconomics (elective)

**Third Year Subjects:**ETC3400 – Principles of econometrics

ETC3410 – Applied econometrics

ETC3450 – Applied time series econometrics

ECC3430 – Financial mathematics under uncertainty (elective)

MTH3251 – Financial mathematics (elective)

ECC3840 – Mathematical economics (elective)

ETC3460 – Financial econometrics (elective)

ETC3580 – Advanced statistical modelling (elective)

MTH3051 – Computational mathematics (elective)

MTH3140 – Real analysis (elective)

**Year of completion:** 2020 (under the econometrics major)

**Rating:** 4 out of 5

**Comments:** **Background of the major:**A lot of people don’t know what econometrics is, or might think of it as a mere subset of economics as a discipline. Well, that’s half true. Econometrics, I’d argue is a separate discipline, and deals with statistical methods for inference in non-experimental data.

There are 2 main reasons as to why we apply statistical methods differently compared to other fields (such as the natural sciences):

1) The data within economics/finance requires our own judgement to identify cause and effects of certain variables (e.g. does high GDP growth result in high employment? Or the other way around? Who knows. Maybe they affect each other like a cycle).

2) We want to test economic/financial theory and that often comes with very structurally complex systems, more so than applied research in the natural sciences. For example, how would one quantitatively analyse entire tax structures on the economy?

So there you have it, in a nutshell, it’s just a set of statistical tools (that overlap with the broader field of statistics, a lot) used to analyse non-experimental data. With this, we hope to verify, or quantify the effects of different variables or systems for economic/financial theory.

In your second year, you will build upon essential skills required in research in econometric theory or applied econometrics, and that includes an introduction to the discipline + some other prerequisites (theoretical mathematics, probability and statistics, and some knowledge on microeconomics and macroeconomics if you do choose the economics units).

As with the actuarial program, the third year in the econometrics major will provide you with more specific theoretical and practical underpinnings of econometrics. One would argue that the major itself is mostly theory. Broadly, you will encounter topics in:

1) Econometric and economic theory (ETC3400, ECC3840)

2) More underlying mathematical skills (MTH3051, MTH3140)

3) Financial mathematics and stochastic (random) processes (ETC3430, MTH3251, ETC3460)

4) Time series (ETC3450, ETC3460)

5) Applied econometrics and modelling (ETC3410, ETC3580, ETC1010)

**Personal experiences:**I enjoyed this major a lot, way more so than actuarial science. I guess it really fit my personality a lot, since I really liked reading and writing about economics and economic policy, particularly in healthcare when I started my undergraduate degree (obviously my interests have diversified since then). I was also always interested in venturing into academia as well, and I really think that this major only suits very specific people (those who want to get into academic research!). Most people who major in this are better off or would be happier doing something else.

If you really liked mathematics then you should try the mathematics majors at the science faculty, and if you really want to make it in corporate/data science, well you should undertake business analytics/data science and work on problem solving and soft skills.

Teaching is really a hit at miss in this major, there are a few units that definitely hit the sweet spot in teaching quality, and others, not so much. I would prefer the current structure, and would encourage people to do the more mathsy units if possible (MTH3251, MTH3140 are a must, MTH3051 less so because of bad teaching I guess). Definitely the units that involve R (ETC1010, ETC3410, ETC3580) for good grounding in programming. In many cases you will need to self-study some pre-requisite knowledge such as linear algebra or differential equations, but people get by I guess.

**Where I hope it would take me/where it has taken me:**With the exception of actuarial science I guess this is the most mathematical option you are going to get within the commerce faculties of all universities (including UniMelb) since Monash is the only Australian university with a dedicated econometrics department, and is highly ranked as well. Definitely super underrated in terms of research quality and output, which, only insiders in academia would know.

If your end goal is to be an academic in any business/economics domain, this major is definitely the place to start. Not only does it drill hard concepts specific to econometrics within you early, the Department of Econometrics and Business Statistics at Monash is on par with many top universities to publish material on good journals in the econometrics, operations research and social sciences field.

Monash is very well-connected with a diverse range of groups and institutes (SSA, ACEMS, QFRA, IIF, etc.) so you will definitely reap the benefits of doing academic research here. One field that’s pretty hot at the moment would be developing R tools and statistical programming in R, for which Monash also has very famous supervisors (Dianne Cook, Rob Hyndman).

From this major you can progress to an honours year/masters in econometrics, or even QTEM, which is like a pretty reputable applied masters course that spans a few countries. Pair this up with a business analytics/CS/data science major/degree, and you will definitely have a good place in academia should you do well in your studies.

I’m only beginning more academic research in and out of Monash and I have already noticed considerable benefits and advantages that econometrics at Monash provide already, so I’d give this a recommend if you’re interested in academic work.

With that being said though this major definitely falls short when it comes to good industry exposure (I think Monash is pretty weak on that in general), compared to the data science major, or even business analytics at other universities like Swinburne/Deakin. Do think twice if your goal is to go for industry positions, as this major will not prepare you for that too well.

Based on my own experience, I have never really used the econometrics part of my degree in industry, well aside from R. You’ll be qualified for most positions that are open for the economics major as well, or even quantitative roles outside of university, but do bear in mind that you will notice a lot of gaps in knowledge (e.g. financial knowledge or programming) that you will need to make up for compared to other students. Some companies (e.g. Frontier and Deloitte) have econometrics departments as well but that’s a minority.