Welcome to the Letter from the Chief Economist.
I feel like it’s rare to get economic news that’s almost entirely positive, but that’s how I felt with the federal JOLTS report yesterday. Openings went down by 1.1 million, while hires and separations were mostly flat and layoffs ticked up just a little.
Such a big drop in openings shows that the first cracks are beginning to open up as the labor market comes down from the historical tightness it’s shown over the past year. Those looking to hire aren’t showing the same eagerness as they were only a few months ago, but they aren’t willing to give up their existing workforce, either.
Everything in this data would suggest that employers have gone back to the drawing board, making thoughtful decisions about which positions they actually need to fill—and taking down any surplus job postings. And that sounds good to me, because we’re always in favor of a more deliberate talent strategy here at Lightcast. But more importantly, the low layoff rate shows the labor market is cooling without causing much damage in individual lives. Eliminating a job that nobody has filled yet hurts much less than eliminating a job someone holds.
All of this is good news for the Federal Reserve, too, as it keeps working to bring inflation down. We’re beginning to see the impact of its rate increases from this summer, and that policy seems to be working as expected.
But that doesn’t mean Fed Chair Jerome Powell is ready to wipe his hands and say “mission accomplished.” The main number he cares about is inflation, and until that comes down, interest rates will probably keep coming up; I would guess as much as 1.5% by February 2023. The only things I can see stopping that increase would be an unemployment rate above 4.5% or an inflation rate growing much more slowly—and we’re a long way off from both of those.
After the report went out yesterday morning, I went live with Lightcast Senior Economists Elizabeth Crofoot and Layla O’Kane to talk through our top takeaways and initial reactions, and you can catch up on that full discussion here. On Friday, my colleagues Rucha Vankudre and Ron Hetrick will have their own conversation about the monthly Employment Situation right after its release, and you can find that on the Lightcast LinkedIn page as well.
Lightcast Global Research: Digital Transformation in the UK
We have another research report out this week, and it’s one I’m very eager to share. According to Lightcast data, the number of UK job postings requesting artificial intelligence skills has more than tripled over the past decade, making the UK one of the global leaders in the field.
The new report—”Artificial Intelligence in the UK: The relevance of AI in the digital transformation of the UK labour market”— goes into detail about how the UK compares to other countries and also how individual regions in the UK compare to others, as well as which skills are being requested and growing in importance across the field. The research goes hand in hand with the UK government’s goal of seeing AI benefit all sectors and regions of the country and its economy.
What makes this report special compared to other projects we’ve done recently is the companion website. At aiskills.lightcast.io/heatmap, we and our partners at the visual storytelling firm Infogr8 have created an easy-to-use set of visualizations to explore and understand how and where AI is shaping the UK labo(u)r market. It’s a fun set of tools to play with.
The heatmap site and full report are here, and I’d encourage you to pay it a visit.
In The Papers
Thinking about this theme of artificial intelligence/machine learning reminded me of this paper from February of this year, written by Avi Goldfarb, Florenta Teodoridis, and yours truly: “Could Machine Learning Be a General Purpose Technology? A Comparison of Emerging Technologies using Data from Online Job Postings.”
We started with the idea of a “general purpose technology,” or GPT, defined as the major advances that fundamentally change the way human invention and innovation moves forward. Some of the best examples would be electricity and the internet.
But since those technologies have such broad application, it can be hard to empirically measure their impact. Our solution was to use job posting data: no technology can hope to advance to GPT status without a tremendous amount of human capital invested in its development. Since the Lightcast library of job postings is granular enough to show us what kinds of skills and job titles can be taxonomized and associated with the kinds of emerging technologies likely to become a GPT.
Looking at over 20 emerging technologies, ranging from blockchain to 3D printing to nanotechnology to virtual reality, we found that machine learning and associated fields led the pack and are most likely to become a GPT.
So as we keep thinking about how AI develops in the UK, we can also anticipate this technology continuing to grow in scale and importance all over the world, with the chance of becoming as indispensable to our day-to-day life as electricity and the internet. That’s what we see in the data, and I think it’s something to look forward to.
Until next week,
Lightcast Chief Economist