The last twenty years have been good to tech nerds. When the floppy-looking Bill Gates came out with the personal computer many people might have thought it was a one-off success. Meanwhile, the smart money left engineering, got an MBA and a job in finance. It was the 90s and it seemed like the right thing to do.
Fast forward fifteen years and money was multiplying faster than starter yeast for Amish friendship bread in Silicon Valley. Apps, games, and whatever else they do with code were the gold that the smart techs were mining. And mining with a moral superiority that what they were bringing into existence was changing every facet of the economy. Those were glory days for math majors and engineers.
Mathematical techniques also became central in economic papers. Fancy statistics and linear regression models are used to demonstrate relationships between parties and their use of resources. Fast forward to the last five years and there’s this amazing mix of massive amounts of data, computers that can handle it in a timely manner, and mathematical tools to replicate theories.
But you don’t have people educated in the classics to help parse all the people represented in the data. Even recently I saw an analysis of real estate by zip code – zip code! I encourage you to drive the parameter of an area in your city identified by zip code. Do you see consistency in the properties which would suggest similar set? In my experience urban neighborhoods are not delineated by zip code or census track.
Going forward, the methods used to sort groups to obtain useful insights could be aided more by liberal arts majors than math majors.