1. One of Eric Weinstein’s catch-phrases is the DISC, which I think stands for the Distributed Information Suppression Complex.
2. Recently, I was asked if I want to contribute some sections to a guide for college students of first-year economics. In looking at the guide, I was reminded of my frustrations with mainstream economics. The GDP factory. The failure to appreciate intangible factors. The failure to incorporate the business problems posed by the Internet into mainstream courses. My seemingly hopeless moonshot to overthrow neoclassical economics. My attempt with Specialization and Trade that fell with a thud. etc.
3. One idea that I extracted from Jeffrey Friedman’s turgid prose is that the economics profession probably selects for those who believe in and desire technocratic power. That seems to me what drives the DISC in economics. It leads to things like Raj Chetty’s project.
A central part of Opportunity Insights’ mission is to train the next generation of researchers and policy leaders on methods to study and improve economic opportunity and related social problems. This page provides lecture materials and videos for a course entitled “Using Big Data Solve Economic and Social Problems,” taught by Raj Chetty and Greg Bruich at Harvard University.
Gosh, if you were to just link data from tax returns, credit bureaus, and Google searches, imagine how well “seeing like a state” could work. Ugh.
4. Unfortunately, I am Bill. Let me tell you the story of Bill. In 1990, I was promoted to a low-level management position in charge of five people inside Financial Research at Freddie Mac. One of the staff I inherited was Bill. Bill was a very bright guy, the sort who is called a “computer genius” by people who are intimidated by computers, and even by some who are not intimidated. He was older, in his fifties, with the title of “economist” but doing the work of a glorified research assistant. Bill had bounced around different departments at Freddie Mac, as one supervisor would unload him for his performance issues and another would pick him up for his potential and background.
Bill was very popular with the other staff. When they had a gnarly problem in SAS or with installing new software on a PC (this was a challenge in those days), he would help. Unfortunately, he found these problems so interesting that he would gladly drop whatever assignment you gave him in order to work on the tech issues. So if he was supposed to run a report that I needed for a meeting with top management the next day, I could not count on him to do it. He was very distractable.
One day, he distractedly wandered through the tape library for Freddie Mac’s mainframe computers. I have no idea why. He pulled down a tape and, lo and behold, he found data that had been missing for years. It was data from loans that were originated in the late 1970s and early 1980s. The data was no longer needed for processing the loans, but it was priceless for research purposes. We could now correlate default rates to data from loan applications, such as the original loan-to-value ratio.
I soon hired another research assistant, Sudha. She was far from brilliant, and her computer skills were weak, but she was meticulous and organized. The other staff, who loved Bill, resented Sudha, especially because Bill always ended up doing the work for Sudha’s memos. But when I left my position, my replacement soon said to me, “Now I understand what you were doing. You needed Sudha in order to get Bill’s projects done.”
So I am Bill. I am distractable. That is who I am. That is where I live. Being distractable perhaps enables me to discover insights. But it also is a weakness. If I were like Bryan Caplan, I would spend several years delving deeply into a topic and come out with a compelling book. Maybe somebody needs to find a Sudha to pair with me.