The steps I took into making my Master’s Thesis in Economic Analysis can be summed up as: 1. Identifying an economic problem, 2. Identifying the data needed to solve the problem, 3. Gathering the data and cleaning it, 4. Exploration of the data, 5. Modelling the data (statistical modelling, predictive modelling, you name it), 6. Communicating the findings, tying it back to how it solves the economic problem asked in step 1.
Extremely similar, a data scientist needs to have a good business understanding, then the data understanding, gathering the data, EDA (Exploratory Data Analysis), Modelling (Machine Learning) and communication of the results. Similar? I say very.
The title of the article asks you to not let “them” fool you. Who “them” is, is irrelevant. Just don’t let anyone fool you. Economics is not a “dry, theoretical and qualitative” field, not anymore and probably never was. It has all reasons to be part of STEM, in that it not only covers the ‘S’ and ‘M’, but the inclusion of the ‘T’ in Economics academic degrees is growing steadfastly.
The Science aspect of STEM in my opinion, should not limit itself to physical, biological, life and natural sciences — but should include social sciences as well. I’ll tell you why. Mathematics is a key component in STEM, and is so in Data Science, and definitely so in Economics. Some of the concepts of Mathematics crucial to an Economist are differential calculus, geometry, matrix & linear algebra. But, if I haven’t proven my point properly yet, read further for you to see me vindicated.
Data is now everywhere. Without data, there is no solution that can be accepted because data is unquestionably right, and you can eliminate the entire debate of “how can I trust you?”. Data is like God, or like your PT Teacher (drawing from experience — basically something/someone you’re afraid of). Using data to solve problems is the norm now, and economists did this since the 19th century. Its what we were introduced to as “empirical studies” — using historical data to prove a point, or some pulled-a-rabbit-out-of-the-hat kind of theory.
Ideas are just a block of rock. It is with data, that you can sculpt Christ the Redeemer, put it on top of a mountain and make it into a functioning business model. Data Scientists are naturally expected of this, and well before, so were Economists. To end this section, if a scientist can be defined as someone who “observes, measures and communicates”, you gotta include economists in the lot. Anthropology, sociology, economics, behavioral sciences and psychology are often grouped, and yes, all of them are STEM too.