What You Love; What You Are Good At

Several discussions I had throughout today has brought me into this funk that I am in right now. But first, let me regale you with a tale of yonder. In my university years, I concentrated my study on two ‘streams’ of economics – the microeconomic ‘stream’ and the econometric ‘stream’. In the microeconomic stream, I did stuff like experimental economics, game theory and the like – you know, micro stuff. In the econometrics stream, I did stuff that had to do with data analysis. I love both streams. Then I graduated, and found a job.

The job mainly focused on the data analysis part of things – I have gone on to gain experience in all sorts of data analysis, from linear regression to support vector machines. I think I am good at it – I cannot be too sure after today. The new stuff I had to learn and pick up came fairly easily to me. PRML? No problem – consumed in about a week’s worth of baths (twice a day), and committed to memory. Heck, I even implemented some of the cutting edge machine learning algorithms ┬álike sparse coding at work.

So far, it’s about 3 years since my last course in the microeconomics stream. A discussion amongst colleagues today required my expertise (or lack thereof) in game theory. I could provide enough resources on the game theory end of things. But I decided to come home and do some research on the problem anyway to see how I could better improve the algorithms discussed. Lo and behold, my knowledge in that area is very spotty, and I had to wikipedia a lot of the concepts for refreshers.

This depresses me.

Why? You see, my one true love in economics had always been Consumer Theory, and the behind-the-scenes of it – you know, budget sets, convexity, clopen sets, the lot – but it’s really hard to find a well paying job that involves these theories directly, short of getting a PhD and being an academic. Money was always an issue for me – my parents aren’t wealthy people and I can’t thank them enough for struggling so I could do a degree with a not-so-high-paying job. Doing a PhD meant getting a post-graduate degree like a Masters before being able to do a PhD (which may or may not be sponsored). So the plan was to work and save up enough cash to do a post-grad degree that will eventually lead to a PhD.

So, thankfully enough, I had the presence of mind to do something that could potentially feed me as well – data analysis, a.k.a econometrics.

But this becomes a self-fuelling cycle of positive reinforcement. The more I worked in data analysis, the proficient I became at it, but that came at the cost of not remembering as much of what I love to do. Just before I wrote this blog post, I was combing through my bibliography of hundreds of papers on the Core and auction theory. I remember the gist of most of those papers, but a lot of key concepts I was once familiar with, I had to reacquaint through wikipedia.

Oh well, doing what you’re good at makes you only better at it. To excel in something you love, you must do it too. Lesson learned. May I be good enough to eventually do that PhD.

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