Why I Want to Master 'Metrics

Sometimes words or sentences fly out of your mouth before you have a minute to think about them. Most of the time such rambling is rather meaningless ad hoc answers to questions or comments you weren't expecting. But other times, you surprise yourself with how true your words are, aka Freudian slip or simply a moment of clarity. 

The other week I had one of those. A friend of mine asked me why I was taking econometrics as one of my optional classes. For the love of everything holy, why would I voluntarily take more econometrics than I am required to (or, in my flatmate's snarky comment: "do you have a death wish"?)

The words that flew out of my mouth before I could stop them were: I want to be smart. And I instantly realized how true they were to me. In many economic disputes, most commonly policy debates, various topics of disagreement in in economic journals (as well as pub debates over economic matters), you sooner or later come across empirical claims of causality: minimum wages do not increase unemployment (or more recently, minimum wages raise the incomes of the poor); equal societies are more successful; access to Obamacare-style health insurance makes the poor healthier. And on and on and on. (For a test of this, try listen in on random semi-political discussion at your closest student union or pub, and measure the amount of time until somebody makes a reference to causality, one thing leading to another. My money is on "less than 5 minutes".)

Econometrics is the study of such causality, one of the most important ways to support or disprove claims of causal relations. In the introduction to their celebrated 2015 book, Mastering 'Metrics: The Path From Cause to Effect, Angrist & Pischke states the following: 

There is a mystical aspect to our work as well: we’re after truth, but truth is not revealed in full, and the messages the data transmit require interpretaion. (p. xi)

Truth empowers and truth can be clouded in deceptions and honest mistakes. My aspiration for wielding the tools of master econometricians isn't much different than my reason for studying economics in the first place; people much smarter than me (or less smart than me...) can get away with unsound causal assertions unless me or other critics have compelling reasons for why those causal assertions are mistaken. In this, econometrics is a particularly valuable tool. This is what I wrote back in September, reflecting on why the study of economics in generation is so essential for everyone:

as told to me by a minister in rural Costa Rica, the reason to know what's in the Bible is that if you don't, people will fool you, use you and trick you into believing things. Same goes with econ. If you don't grasp basic econ, living in any kind of modern society is pretty much doomed. Econ is the best roadmap there is to modern societies, characterised as they are by money finance, fractional reserve banking and extensive division of labour. People (particularly, but hardly limited to, politicians) will use you, trick you, fool you and your life will be much poorer because of it.

In an academic or ideological sense, I think it also applies for econometrics, but perhaps with less emphasis on why non-nerdy people in general need to study it. Besides, econometrics is one of the few useful skills an economics degree actually teaches you – why not take the full advantage of that teaching?

As a great companion to this class, I'm using Angrist & Pischke's entertaining book to help me along the way. All cred to them for incorporating Superman, Kung Fu and down-to-earth examples in their quest to make sense of 'metrics.