Casual review — Learnings from my decade old Econs Degree
I had the luck of graduating from the Economics Department from the National University of Singapore (NUS) twice, once in 2009 into a Lehman-less world as an undergrad, and another time in 2012, after completing my Master’s programme. Ask me what I wanted to study for my university degree before enrolment, and I would say “Business”! So I kid you not when I said luck played a huge part in where I ended up in NUS.
Given it has been 11 years since my graduation, I feel primed to do a review on some learnings from my NUS Economics days. This is a quick, no-holds bar review that reflects what has stuck to the core of my bones. There was no in-depth analysis, nor 5-day meditation retreats to extract out the essence of my NUS life into nuggets of life advice. The points came second nature to me, while the English took more out of me to construct. If you are still reading this and intend to continue, please treat this piece as casual exposition rather than any form of life advice.
Know your assumptions
In many fields, including Economics, it is always good to have your goal in mind. I, on the other hand, learned to be hypersensitive to the concept of “assumptions” from reading up to a 100 journal papers for my Master’s thesis. Rational agents. Convex utility functions. Hilbert spaces. Rational numbers (not to be confused with rational agents). It is common in Economics journals that before the authors set forth into any mental gymnastics, they do a very detailed checkpoint on where they are at first, and I learned to first seek those assumptions first before I seek to tear up the journal for myself. Bringing this to our real world, “knowing your assumptions” can be akin to “understanding the context of the discussion”, or “understanding what are these ideas built upon”. I realise in many situations, and especially in times of uncertainty, it has served me well to clarify everyone’s assumptions, so that we can get everyone to be one the same page to have a more fruitful discussion on what needs to be done next.
Necessary but insufficient conditions
Among the seas of equations in my level-5 Mathematical Economics class, certain English phrases pop up, and this is one. Many Economics proofs that only end up confirming certain conditions must hold true for certain phenomena to occur, but that these conditions may not always lead to the said phenomenon. In love, in careers, in life. It was only later in life that I realised the philosophical poetic-ness of this statement. It made me realise that it is pointless to hold any emotional grudges on any rewards that I felt I deserved because I did my work. The real world, and Economics, doesn’t work that way. Appreciating necessary but insufficient conditions was one way for me to learn how to try my best, but still, be willing to let go.
There is always “error” in your Econometrics models
Econometricians call them “errors”, but intuitively, these are unaccounted variables that have an influence in your model’s estimations. And while we can try to account for all the harsh realities of our lives, we can never fully account for them. Just as how we will always have that “error” parameter in our Econometrics models. “Errors” do happen. Don’t bastardise the word or bastardise yourself for having errors once a while in your life. We train, we tune, we test, and we adapt. We learn from them. Just as we get our models to do as well. That’s the beauty of life.
Focus beyond pure rational, numbered optimisations
In the 1970s (I think?), the world was introduced to Behavioral Economics (or Economists were introduced to the world of real humans). It was a relief to finally realise purely optimising on convex utility functions is actually irrational when one looks deep into the souls of humanity. Money is important, but there things, money cannot (directly) buy. Time with your loved ones. An overseas exchange. Expanding your mind. Appreciating your life’s blessings. As convenient and scientific it is to harmonise decision makings into seemingly objective utility functions to optimise, many hard decisions in life don’t have that strong, consistent, rational (convex function) utility to compare across. Life is messy, and unfortunately, using complicated models doesn’t make it simpler.
We don’t know our utility functions
Economics 101, we do our dy/dx to optimise our utility functions. Interestingly, I got to realise that this textbook assumption (literally) is actually harder to achieve for most of us, because most of us don’t even know what our utility function looks like! What kind of career do you want? Do you really want to relocate to another country? Is your right career banking, or baking? What do you want your future to look like? And do you know that your utility function can change, which means you will have to dynamically optimise your life decisions on the fly?
It was very late into my undergrad life that I realised I had to figure out what my utility function(s) are. I went for a summer programme, picked up Japanese, before dropping it to learn another language called Python, so that I could potentially speak to computers. I was never sure if I could use Python for anything, but I know I had to test out my utility functions. Even till this day, I test different ideas and concepts, such as “Can I create an app to better view the books I want to borrow from the Singapore libraries? [article here]”. Nothing beats trying and testing things for myself to truly understand what I want and can do. I have, unfortunately, that little faith in knowing what I truly want, without really testing it for myself, haha…
Conclusion
I hope this random chatter is something interesting for existing college students who are thinking about the time they are spending for their university degrees. The knowledge you learn will be important, either directly or indirectly. And beyond that, there will be other interesting nuggets of learnings that you may be able to gather, if you are willing to take some time to evaluate them.
Lastly, I hope this weird exposition was an interesting to any who made to make it all the way down here! I am an Economics major turned freelance analytics consultant, with an interest in an array of humanities and hard science topics. If you managed to reach to the end of this article, I would love to connect with like-minded individuals like you on Linkedin!
