January jobs: US labor market gaining back healthcare jobs


The US economy blew past expectations and added 353,000 non-farm payroll jobs to the labor market in January, previously expecting only 185,000. EY Chief Economist Gregory Daco indicates the importance of jobs growth in the healthcare sector: “We lost a lot of jobs during the COVID-19 pandemic. We’re getting these jobs back, very gradually, but that is an area that is structurally restrained where you see that progress be favorable.”

Sitting down with Yahoo Finance, Daco also comments on what Friday’s jobs data means for the Federal Reserve’s monetary policy and how generative AI could weigh on future jobs data.

For more expert insight and the latest market action, click here to watch this full episode of Yahoo Finance Live.

Editor’s note: This article was written by Luke Carberry Mogan.

Video Transcript

SEANA SMITH: Again, the US economy gaining 350,000 jobs in the month of January, blowing past the Street’s expectations, and the two prior readings on the jobs market, both revised to the upside. Wage growth, also, coming in much hotter than what the Street was forecasting.

But there is one key number that could be viewed as a bit of a disappointment. And that’s labor force participation. We want to bring in Greg Daco. He’s EY’s Chief Economist.

Greg, it’s great to have you here. So let’s first focus on labor force participation because we can take a look at those headline numbers, your immediate reaction would be, hey, this jobs market much, much hotter than what we had initially anticipated.

Does that labor force participation– the fact that we didn’t see a tick to the upside– does that maybe push a little bit of cold water on that initial reaction?

GREG DACO: Well, I think we always have to be a little bit careful and look at all of the data, not just the headline print in terms of payrolls. Payrolls were very strong. But we knew there was going to be some seasonality effect. I think that was part of the picture in terms of professional and business services. It was also part of the picture at the state and local level.

But when you look at some of the other readings, the labor force participation rate was steady. We also saw a notable decline in hours worked. And that brought hours worked back to their lowest since the pandemic. That is one area where we have to pay attention as well.

BRAD SMITH: And so as we think about where– and we just got the full sector breakdown, where people are still making their way back into the workforce. What is the most encouraging sector for us to continue to look at? Because there are some of the longer trends that we’ve seen in the leisure and hospitality recovery.

There’s some of the longer trends that we’ve been waiting for in health care as well. But if there’s one sector that sticks out that we can perhaps hang our hat on and say, it’s good that employers are making their way back in there. What is that?

GREG DACO: It’s health care.

BRAD SMITH: Yeah.

GREG DACO: Health care has been the key sector that has been structurally deficient in terms of labor supply. That’s one of the sectors that is still rising strongly. It has been the biggest contributor to job growth over the past six months. And that’s very positive because we lost a lot of jobs during the COVID pandemic.

We’re getting these jobs back very gradually. But that is an area that is structurally restrained, where you’re seeing that progress be quite favorable. I would note one more thing that is important to consider when we’re thinking about this labor market and what it means for the Fed, it is important to note that wage growth did accelerate. But it accelerated in the sectors, where you saw the strongest job growth.

Professional and business services– part of that was seasonal. So I think that might be pulled back in February. And then health care. And health care is that structurally restrained sector. So it’s pressure from one sector really that is outweighing the rest.

The key question is, do we get more productivity growth? And that would bring about non-inflationary growth, which is what the Fed wants.

SEANA SMITH: So maybe when you take a look at those very hot numbers, when it comes to wages, maybe it won’t be as problematic there than for the Fed or really just in terms of that getting inflation back to that 2% narrative. We have been talking about the Fed’s 2% target there.

Maybe a print like this won’t really complicate it to the degree that you would initially anticipate.

GREG DACO: Well, it does put the Fed in a bit of a difficult place. But remember, the Fed framed its statement with a negative tone. That’s very unusual for Fed policymakers to do that. We will not cut rates until we have greater confidence that inflation is sustainably at that 2% target, or moving towards that 2% target.

That’s very different than a positive statement. So they have the optionality there to hold off for a longer period of time, should the data necessitate a longer period.

BRAD SMITH: And then just lastly, while we have you here. You talk about productivity. A lot of people are trying to figure out what generative AI is going to do for productivity versus what humans are doing for productivity. How does that show up in the balance?

GREG DACO: Well, I think it’s going to take a bit of time before we actually see it in the numbers. But Gen AI is one of those technologies that will affect us very rapidly. It’s likely to be ubiquitous. We’re doing a lot of research on the economic impact of AI.

We think that about 2/3 of jobs in the US will likely be moderately to highly exposed. The third that remains is not necessarily going to be immune from Gen AI. But we’ll have some functions that are still exposed to AI.

I think we have to keep in mind that Gen AI in lifting productivity will help on the supply side and, also, alleviate some inflationary pressures by augmenting our capability to do our work.

SEANA SMITH: All right. Greg Daco, always great to have you, especially on a day like today. Thanks so much for joining us here in the studio.

GREG DACO: Thank you.



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