Takeaways from Senate Hearing on Recent Bank Failures and the Potential Effects of AI on Economic Growth/Productivity
Today the US Senate Banking Committee held a hearing about recent bank failures with regulators from the Federal Reserve. Here were the highlights from the 2.5-hour hearing.
The Fed’s stress test, which is an analysis conducted under hypothetical scenarios designed to determine whether a bank has enough capital to withstand a negative economic shock, will be enhanced to ‘uncover a variety of channels of contagion’.
Shouldn’t the stress test be detecting potential contagion issues in the first place???
The Fed will propose ‘a long-term debt requirement’ for big banks that aren’t designated as global systemically important (also known as GSIBs), ‘so that they have a cushion of loss-absorbing resources’
The FDIC will on May 1 lay out options for potential changes to deposit-insurance coverage, which is now capped at $250,000.
The SVB bank run was on track to be way larger than initially realized.
On March 10th, “The bank let us know that they expected the outflow to be vastly larger based on client requests and what was in the queue. A total of $100 billion was scheduled to go out the door that day.”
Note that depositors ultimately withdrew ~$42 billion from the bank that day.
After the collapse of SVB, the FDIC received two bids for its purchase. However, one of the bids was turned down because the board of the bank that made the offer did not vote to approve the transaction. The second bid was considered by the regulators to be more costly for the FDIC than liquidating the bank, so they proceeded with the liquidation process.
The recent buzz in technology has all been about ChatGPT, GPT-4, DALL-E, and other generative AI. I was curious about how AI in general could boost economic growth/productivity in an economy where both have been gradually decelerating.
After combing through many academic papers and research reports, here’s what I found.
There are three main ways that AI will impact economic growth:
Productivity gains from businesses automating processes.
Productivity gains from businesses augmenting their existing labor force with AI technologies.
Increased consumer demand resulting from the availability of personalized and/or higher-quality AI-enhanced products and services.
So how will AI affect the labor market?
Goldman finds that roughly 2/3rds of US occupations are exposed to some degree of automation by AI, and that of those occupations which are exposed, most have a significant - but partial - share of their workload (25-50%) that can be replaced.
25% of current work tasks could be automated by AI in the US, with particularly high exposures in administrative (46%) and legal (44%) professions and low exposures in physically-intensive professions such as construction (6%) and maintenance (4%).
Fewer jobs in emerging markets are exposed to automation than in developed markets, but 18% of work globally could be automated by AI on an employment-weighted basis.
The share of AI job postings among all job postings in 2021 was greatest for machine learning skills (0.6% of all job postings), followed by artificial intelligence (0.33%), neural networks (0.16%), and natural language processing (0.13%). Machine learning jobs are at 3x the level, and artificial intelligence jobs are at around 1.5x the level they each reached, respectively, in 2018.
How would AI affect productivity and economic growth?
Academic papers suggest that workers at early AI-adopting companies experience higher labor productivity growth following AI adoption. Estimates generally imply a 2%-3% increase in productivity per year.
While many workers could be displayed by AI automation, it’s expected that they will eventually be reemployed in new occupations that emerge from AI adoptions or in response to higher labor demand generated by higher productivity.
This has plenty of precedents. As Goldman notes, For example, information technology innovations introduced new occupations like webpage designers, software developers, and digital marketing professionals, but also increased aggregate income and indirectly drove demand for service sector workers in industries like health care, education, and food services.”
Economists from the NBER have found that technological innovation that initially displaces workers actually drives employment growth over a long time horizon.
60% of workers today are employed in occupations that did not exist in 1940, implying that over 85% of employment growth over the last 80 years is explained by the technology-driven creation of new positions.
How much investment is expected to go into AI?
US and global private investment in AI totaled $53 billion and $94 billion respectively, each up more than 5x in real terms from five years ago.
Per Goldman, if investment continues to increase at the more modest pace that software investment grew at during the 90s, US investment in AI could approach 1% of US GDP by 2030.
Per PWC, AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption side effects.
Per Stanford, among companies that disclosed the amount of funding, the number of AI funding rounds that ranged from $100 million to $500 million more than doubled in 2021 compared to 2020, while funding rounds that were between $50 million and $100 million more than doubled as well.
Companies attracted significantly higher investment in 2021, as the average private investment deal size in 2021 was 81.1% higher than in 2020.
However, the number of newly funded AI companies continues to drop, from 762 companies in 2020 to 746 companies in 2021—the third year of a decline that started in 2018. Consolidation.
Most AI investment has been in the United States, which has 3x more private investments than the next country, China.
https://www.sciencedirect.com/science/article/pii/S0164070421000458
https://realinvestmentadvice.com/the-no-landing-scenario-and-ufos
https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf
https://aiindex.stanford.edu/wp-content/uploads/2022/03/2022-AI-Index-Report_Master.pdf
https://www.nber.org/system/files/working_papers/w30389/w30389.pdf