One of the most persistent economic narratives of 2021 and 2022 was that of missing workers. Many Americans seemed to have simply vanished from the labor force during the pandemic, leaving employers in a lurch.

• That's no longer the case, White House economists argue in a new post presenting evidence that labor supply has returned to its pre-pandemic trend.

Why it matters: It would be way less painful if the U.S. labor market were to come into a better, non-inflationary balance because labor supply increased, rather than labor demand decreased.

• And contrary to a widespread economic narrative of the last couple of years, that seems to be happening — as the Biden team seeks to emphasize.

State of play: There has been ample speculation about why labor supply was depressed in the aftermath of the pandemic, the White House Council of Economic Advisers notes.

• Maybe fear of COVID, or long COVID symptoms, kept people out of work. Maybe it was excess savings from the pandemic, or reassessment of life priorities, or a "collective loss of work ethic."

Nah. It increasingly looks as if it just took some time for potential workers to match up with jobs and return to the labor force.

By the numbers: The share of prime-age workers — those between 25 and 54 — who are part of the workforce is now a tick higher than it was before the pandemic: 83.1%, compared with 83.0% in February 2020.

• The overall participation rate is down (62.6%, from 63.3% in February 2020), but that is due to the Baby Boom generation retiring. It's on track with what forecasters at the Congressional Budget Office anticipated before the pandemic.
• Moreover, immigration rates surged in 2022 after a pandemic collapse, also adding to the supply of labor.

What they're saying: "The swift but lagged response of labor supply to surging demand suggests that with time workers do respond to favorable economic conditions," the White House economists write.

• "There are many plausible reasons that explain why this response is lagged. Most obviously, the job search process itself is not frictionless; it may take workers some time to find a good job," they wrote.
• "Also, if households adapted to the pandemic in ways that can take a while to unwind (such as giving up formal child care), this would delay the labor supply response to growing demand."

The bottom line: "There's still an inaccurate view that prime-age labor supply is depressed, that immigration is way down, and that labor force participation rates aren't back on trend following the pandemic shock to our economy," Ernie Tedeschi, the chief economist at the CEA, tells Axios.

• In fact, he said, tight labor markets "pull folks back into the workforce and, while we have more to do to break down barriers to entry, the 'missing worker' story doesn't quite apply anymore."

Attention fellow Federal Reserve watchers: ChatGPT can apparently read between the lines of crucial — and sometimes challenging-to-parse — communications from central bankers.

Why it matters: That is the upshot of a recent paper by two Fed staffers who ran several tests to determine whether the artificial intelligence tool could accurately decipher hawkish signals from dovish ones. According to their findings, the answer is yes.

How it works: Richmond Fed researchers Anne Lundgaard Hansen and Sophia Kazinnik randomly selected hundreds of sentences from Fed policy statements published between 2010 and 2020.

• Each sentence was assigned a label — like "hawkish" or "mostly dovish" or "neutral." The team then evaluated how the chatbot's classifications compared to those human classifications.

What they're saying: Hansen and Kazinnik found that GPT models "demonstrate a strong performance in classifying Fedspeak sentences." The researchers also said that the GPT "successfully justifies its classifications, and furthermore is very similar to the reasoning provided by a human reviewer."

• They found that GPT was better at the task than older language models, including a popular one introduced by Google in 2018.

Yes, but: The researchers warn that AI technology "may still misclassify sentences or fail to capture nuances that a human evaluator with domain expertise might capture."

• "Thus, while GPT models may not be able to fully replace human evaluators, they can serve as a highly valuable tool for assisting researchers and analysts in this domain."