A. The bottom half of PhD Economists are not being trained in the data science/Big Data side of analysis increasingly needed
B. There is less demand for Theory-sided Economists over computationally trained ones
The whole profession was basically centered around putting a dollar amount on risk.
For example, lets say I give you a chance of either taking $1k now, or playing a game where you have 1 in 10 chance to win $200k. What would you do? The right answer is "sell" the risk to someone. For example, on the average, if I "buy" the game from 10 people, at a price of $10k each, I can realistically win twice what I spend.
Repeat that over x number of steps and more complex games, and that is what the PhDs worked on in terms of pricing.
For most of the time it worked ok. In a few instances (most notably the Gaussian Copula that was a large reason for the subprime house market crisis in 2007) it didn't.
The problem is that now, its impossible to predict whether orange man is going to throw a hissy fit and cause the market to go up or down, or if large investors are going to artificially prop up stock like they did with Tesla.
As the article indicates, a huge portion of the market for hiring PhDs is directly or indirectly dependent on federal funding. Universities are freezing hiring and reducing PhD cohort sizes, institutions like the IMF and World Bank are in crisis, and US government agencies have been reducing staff sizes. There was hope that the tech industry would provide another big source of jobs for PhD economists, but that hasn't panned out.
Source: the article, and my wife works in the UChicago economics department.
PhDs werent dealing with stock prices either. Nobody was trying to predict the stock market. The goal was to price volatility and sell volatility to the end party that would actually roll the dice.
Shortly before this debt time-bomb went off, Trump magically showed up tweeting in support of the company and alluded to a deal getting pulled off with GM. [] Of course, this ended up being spun off as Lordstown motors, a company that has failed horribly, including Hindenburg Research publishing a video of one of the few trucks they had literally catching on fire on the road while the CEO was simultaneously claiming they had hundreds of millions of dollars in solid orders (later fined by the SEC for that and barred from being an executive of a company for N years).
I still don't understand how Trump magically got involved with this penny stock at the 11th hour, but I can tell you I feel something very fishy happened there.
https://www.cnbc.com/2019/05/08/trump-tweet-sends-penny-stoc...
The man scammed his own supporters twice with crypto scams. He, of course, is not at all opposed to market manipulation or other types of financial scams
Speaking as someone who has attended 3 economics Ph.D. defenses in the past two years.
It was called statistics
The practice of working with huge datasets manipulated by computers is valuable enough that you need separate training in it.
I don't know what's in a modern stats degree though, I would assume they try to turn it into DS.
Like with most other academic fields, there is no clear separation between data science and neighboring fields. Its existence as a field tells more about the organization of undergraduate education in the average university than about the field itself.
The Finnish term for CS translates as "data processing science" or "information processing science". When I was undergrad ~25 years ago, people in the statistics department were arguing that it would have been a more appropriate name for statistics, but CS took it first. The data science perspective was already mainstream back then, as the people in statistics were concerned. But statistics education was still mostly about introductory classes of classical statistics offered to people in other fields.
essentially, provided you were at a right place in a right time, you could get a BSc in it
"The whole damn field is turning into a bunch of Data Monkeys"
Referring to the rise of CS and DS minded economists in the field. His top student was a computer science major...
Political economists are explicitly less interested in the quantitative side of economics - which is why they call themselves political economists.
Thus, the comment about data makes a lot of sense, and isn't evidence of what is going on with economists
The point of hiring an economics PhD in industry is largely not because they learnt something but because it's a strong and expensive signal.