Why the classics in economics matter: In “Capitalism, Socialism, and Democracy” (1942), Joseph Schumpeter was ahead of his time when he argued that the expansion of higher education would lead to the emergence of an underemployed academic precariat. Schumpeter suggested that capitalism could sow the seeds of its own destruction through the growth of intellectuals critical of it. Universities, as hubs of thought, could balance this by fostering innovation and entrepreneurial thinking. #Innovation #HigherEd

Sure. Here are some notes and a thread on VAR and SVAR models:
github.com/andreachello/A… x.com/arcamachoX/sta… 1. VAR* and SVAR** models both help us with analyzing multivariate time series in econometrics.

*VAR: Vector Autoregression.
**SVAR: Structural VAR.

A thread about conformal prediction, an important statistical concept that can help development economists and economists in general that are interested in causal inference and related concepts: Conformal prediction is a method of producing predictions that are accompanied by validity guarantees, meaning that they are valid under any distribution of the data.

🧵1/ Does causality have a color? In this .@DevEconX paper, we use graphs to model data or systems, and diagonal Ramsey numbers to estimate causal effects. What are diagonal Ramsey numbers and how can they help us with causal impact? Let’s find out! developmenteconomicsx.com/wp-content/upl…
🧵2/ Diagonal Ramsey numbers are a concept from graph theory that measure how large a graph has to be to guarantee that it contains a monochromatic subgraph of a given size. Ramsey numbers been used in macro, theory, and elsewhere, but not causal inference.

Until now.

Another thread on classic industrial R&D labs. Bell Labs was the birthplace of information theory. Nine Nobel prizes(!) and four Turing awards(!!). I’m mostly quoting this neat new .@Nature article on how they operated with actual quotes.

nature.com/articles/s4225… Riordan attributed the success of Bell Labs to the “combination of stable funding and long-term thinking”

But there were other ingredients articulated in 1950 by Mervin Kelly, director of Bell Labs.

While not perfect, I’ve long found this tech sector space endlessly fascinating, and am convinced of the significant need for far more collaboration between economics and computer science and across the board.

There are interesting contexts and implications. This is not the first time in history that private industry has been crucial to social impact. During the Second World War Raytheon played a pivotal role in supplying game-changing radar to the Allied powers.

Academia to industry in 5 steps:
1. LinkedIn profile with research methods+software keywords
2. Search for your universities
3. Add alums/folks in firms
4. DM, start conversations
5. Find a job ad for their workplace and ask for referral
#altac 1. Find (e.g) tech research scientists with backgrounds similar to yours and make your profile mimic theirs. Keywords: Stata, R, programming, data science, AI, teaching, economics, etc.

Thread to document a little of what I’ve read about innovative industrial research:

The history of Nobel prizes awarded to scientists in the private sector(!), yields some interesting correlations: In each case, in some area on the forefront of innovation and technology, the three necessary factors tend to be industrial motivation, basic science, and stellar results.