Q1 Productivity: Ignore the Quarterly Chop—Trend Favorable for Inflation
Nonfarm labor productivity growth nearly stalled out in the first quarter. Output per hour worked increased at an annualized rate of 0.3%, a sharp slowdown from the prior quarter’s 3.5% rise. Robust hiring and soft real GDP growth over Q1 presaged the outturn.
This is not the first time productivity growth has eased considerably in Q1 and undershot expectations. The pattern follows weaker-than-expected output and stronger-than-expected job growth in the first three months of the year.
These seasonal dynamics have obscured the view of productivity’s sequential growth rates at the turn of the calendar, thus we often look to annual comparisons to gauge the underlying trend. Relative to Q1-2023, labor productivity is up 2.9%, or the strongest annual gain in three years. The year-ago change has steadily ticked higher over the past four quarters, indicating a solid pace of expansion. For context, labor productivity expanded at a 1.5% average annual rate during the 2007-2019 business cycle.
U.S. Department of Labor and Wells Fargo Economics
Amid the softer gain in productivity and another strong quarter for hourly compensation growth (+5.0% annualized), unit labor costs (ULCs) picked up to a 4.7% annualized rate in the first quarter. Unit labor costs can be viewed as the productivity-adjusted cost of labor, making it a useful gauge of the extent to which the nominal pace of compensation growth is problematic (or not) for the Fed’s 2% inflation objective.
While today’s reading is on its own yet another unfriendly print for the Fed’s efforts to corral inflation, the jump is reminiscent of the first quarters of 2022 and 2023 when ULCs also leapt, hinting at the possibility of residual seasonality in both productivity and compensation data.
Taking a slightly longer view shows a less worrying picture. Over the past year, unit labor costs are up 1.8%. Smoothing out the inherent choppiness of this report’s data a little more and looking at the year-ago change in the four-quarter average of ULCs also shows the inflationary pressure coming from labor costs continues to subside. While, overall, labor costs are still making it difficult for inflation to return to 2% on a sustained basis, the improving trend in productivity is supportive of inflation resuming its downward path ahead.
Ed Yardeni:
Unit labor costs (ULC) is simply hourly compensation divided by productivity. It is the most important measure of the underlying inflation rate in the labor market and is highly correlated with the CPI inflation rate when both are measured on a y/y basis (chart). ULC inflation was actually down to 1.8% y/y during Q1, suggesting that consumer price inflation could fall to 2.0% in coming months.
Inflation is generally higher than ULC. Headline inflation (used by Ed above) is higher than ULC growth 68% of the times and by 0.3% on average (same median). So +2.1% headline inflation.
Core inflation is higher than ULC 75% of the times since 1958 and by 1.3% on average (same median, see below chart). On that basis, with ULC up 1.8%, the probabilities are that core CPI will be +3.1%.
Core PCE inflation is higher than ULC 62% of the times since 1958 and by 1.2% on average (same median, see below chart). On that basis, with ULC up 1.8%, the probabilities are that core PCE will be +3.0%.
The Treasurys Market Is Getting Squeezed From All Sides Inflation and deficits are lifting yields and jarring the stock market
(…) The government funds spending on Social Security, the military and other areas in part by selling bonds at regular auctions. As Washington has run up larger budget deficits in the wake of the pandemic, those auctions have ballooned, drawing warnings that Wall Street might struggle to absorb the debt.
Few investors fear a failed auction, an unlikely scenario that could potentially trigger prolonged market turmoil. Still, many worry that tepid demand could rattle markets and hurt the economy. Those fears intensified after a series of weak auctions this past month drove Treasury yields higher. Demand improved somewhat at recent auctions. But more outsize issuance is coming soon.
The Treasury Department said Wednesday that it would sell roughly $1 trillion of bonds in total from May to July, keeping its auction sizes steady. The plan maintains an approach started after weak auctions late last year, when Treasury eased market pressures by shifting issuance toward short-term debt. At the time, the Fed also signaled a pivot toward easier monetary policy, with hopes for imminent rate cuts reassuring investors about the strategy.
Now rates might stay higher for some time, and the nonpartisan Congressional Budget Office forecasts the deficit will grow from 5.6% of U.S. gross domestic product to 6.1% in the next decade. Public debt is set to expand to $48 trillion from $28 trillion over that period. Few investors expect either party to push for sharp spending cuts after the November election.
Yields held steady after the Treasury’s announcement Wednesday, with investors saying it was widely expected. But Treasury also said that it likely wouldn’t have to increase auction sizes for “at least the next several quarters,” a longer period than some analysts anticipated. (…)
“In the past, the Fed hiked slowly and cut aggressively, but this time they hiked aggressively and will likely cut gradually,” said Jacobsen. “That isn’t lighting a fire under investors to get out of cash and into longer-term bonds.”
One force that could ease the strain: The Fed on Wednesday also said it would slow the pace at which it is reducing its bondholdings, which it had grown during the pandemic in an attempt to boost the economy. That, on the margin, should reduce pressure on the Treasury to issue bonds to investors because the central bank will need to buy more new Treasurys to keep its holdings from shrinking too quickly as some of its older bonds mature.
Some investors remain skeptical that the recent yield climb is being driven by bigger auctions, greater public spending or the onset of an era of higher interest rates.
Blake Gwinn, head of U.S. rate strategy RBC Capital Markets, said the recent Treasury selloff is rooted more in first-quarter data showing that the labor market remains tight and price pressures persist in parts of the economy.
“I don’t think what we’ve seen postpandemic suggests some new paradigm,” he said. “I think we’re just kind of getting back to normal.”
But, what is normal?
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The first chart plots 10Y Ts minus core inflation (CPI):
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This next chart swaps core CPI with inflation expectations per the Cleveland Fed calculations:
Inside the AI research boom
China leads the U.S. as a top producer of research in more than half of AI‘s hottest fields, according to new data from Georgetown University’s Center for Security and Emerging Technology (CSET) shared first with Axios. (…)
- Roughly 32% of AI research focused on computer vision, which grew 121% in those five years.
- Natural language processing — what large language models (LLMs) do in ChatGPT and other generative AI tools — accounted for another 11% of AI papers and grew 104%.
- Research in robotics grew slower than in vision and natural language processing — by just 54% — and made up about 15% of all AI research.
That tracks with the fact that anecdotally “a lot of the topics open in robotics have proven really hard to fix,” Arnold says. “At the same time, there has been very rapid progress in language tasks, for example.”
- And AI safety research made up just 2% of all research, despite growing 315% between 2017 and 2022.
The top five producers of sheer numbers of AI research papers in the world are Chinese institutions, led by the Chinese Academy of Sciences.
- The dominant narrative for years has been that while Chinese institutions generated the greatest quantity of papers, the quality of those papers wasn’t as high and research in the country largely came from applying fundamental advances made by researchers in the U.S., Europe and elsewhere.
- But when CSET researchers narrowed their analysis to highly cited papers, the Chinese Academy of Sciences was still the leader. Google is second, followed by China’s Tsinghua University, Stanford and then MIT.
At the country level, the U.S. had the top spot in producing highly-cited articles.
“China is absolutely a world leader in AI research, and in many areas, likely the world leader,” Arnold says, adding the country is active across a range of research areas, including increasingly fundamental research.
- The U.S. still has an edge on China in natural language processing. Google and Microsoft were the top organizations in this cluster of research.
- But researchers in China produce more papers on computer vision than other countries in the world. Tsinghua University was the top organization in the world on this topic. China’s strategic priorities for AI include autonomous vehicles, manufacturing, surveillance and other applications that require advances in computer vision.
- India — and three Indian institutions, including Chitkara University —was the top producer of AI applications for plant disease detection.
The data only account for research papers published in English and don’t capture scientific work in other languages. (…)
Data: Emerging Technology Observatory Map of Science. Chart: Axios Visuals
Research on robotics: check this guy out!! https://www.youtube.com/watch?v=AePEcHIIk9s