What to Make of January’s Jobs Boom

US jobs boomed in January. But, like many data points today, the reaction to that boom was largely mixed, with competing camps arguing over whether the data portend good or bad things for the US economy ahead. In our view, though, it is a mistake to read too much into January’s better-than-expected numbers, as jobs won’t tell you much about where the economy is headed.

January nonfarm payrolls rose 517,000, well above consensus estimates of 185,000, while the 3.4% unemployment rate was the lowest since May 1969.^[i] Many headlines pointed out January’s jobs gains were broad based, seemingly more than offsetting high-profile Tech layoffs. Of 14 major sectors, only two—Utilities and Information (which houses Tech)—lost jobs on a monthly basis.^[ii] Leisure and hospitality (128,000) was the biggest gainer, led by food services and drinking places (98,600).^[iii] January also got a boost from the government sector, as a strike involving 36,000 University of California workers ended.

The far bigger-than-expected figures led many pundits to recalibrate their earlier views. Some now argue all the recent recession chatter was flat wrong, with the US economy buoyed by the strong and resilient labor market. But a large contingent worries the jobs data are actually bad news, suggesting the strength may spur the Fed to tighten more and send rates higher on concerns that still-tight labor markets will keep prices elevated.

Still others, interestingly, implied January’s stronger-than-expected stemmed in part from calculation quirks, e.g., “updated seasonal adjustment factors.” The US Bureau of Labor Statistics (BLS) applies its seasonal adjustment methodology to account for expected variations in hiring and layoffs based on the time of year. (e.g., retailers adding help for the holidays.) The agency relies heavily on the past three years to determine the expected seasonal change and calculates its factors each month based on most recent data.

Based on the reaction to the latest numbers, though, some seem to think BLS overcorrected with its seasonal adjustments—e.g., there were fewer-than-usual post-holiday layoffs, which may have boosted nonfarm payrolls—and the most recent calculations injected an error into January’s read. The implication: There is no way jobs numbers can be this strong in today’s economic environment, so some of it must be a calculation issue.

That is possible, as no methodology is perfect—and economic data are always subject to some error. But in our view, this doubt speaks more to skeptical sentiment than cooked numbers. Consider: The BLS updates its seasonal adjustments regularly. If this is indeed a methodology problem, January’s nonfarm payroll change would probably be subject to a large revision frequently. This happened with the BEA’s preliminary GDP estimates—despite their best efforts to account for seasonality, GDP growth would often slow or even contract in Q1 and speed up in Q2.^[iv] However, the last decade suggests January’s revision to nonfarm payrolls doesn’t stand out relative to the average monthly revision for the year. (Exhibit 1)

Exhibit 1: Revisions Between Monthly Estimates in Nonfarm Payroll Changes, 2010 – 2019

Source: BLS, as of 2/8/2023. Numbers represent thousands of persons. Revisions are between first estimate and third estimate of monthly change in nonfarm payrolls.  

Now, it is possible the BLS applies a big revision to January 2023’s number. But that update would be old news to stocks—they have long since moved on from January’s hiring decisions and are looking forward. Yet that hasn’t stopped many from fretting over the jobs report’s future implications—particularly for potential Fed action and a potential recession. The former operates on longstanding misperceptions surrounding central banks’ macroeconomic impact and, particularly, the relationship between inflation and employment. Besides the futility in trying to predict what central bankers will do in reaction to any data, history shows monetary policy’s impact on jobs is limited, and there is little actual evidence tight labor markets boost wages and drive up inflation generally. Other factors, including the economic cycle and political and regulatory matters, factor more heavily into businesses’ willingness to hire or lay off workers. And, as Nobel laureate Milton Friedman taught, wages typically follow inflation.

On recession, always remember: Employment data are late-lagging—so whether jobs numbers are strong or weak, they won’t tell you whether a downturn is coming. They tell you more about what businesses have already endured. Hiring employees is a big investment of time and money, and the decisions around employment can be very emotional. Businesses aren’t likely to make major changes unless they absolutely have to—for instance, they generally hire because the business can’t meet customer demand without more employees. Or, they typically lay people off to cut expenses after a downturn is well underway. So you can’t draw many forward conclusions from the actions.

Recent Tech layoffs are kind of a case in point. First, note, the industry isn’t representative of the labor market (or economy at large)—the Information industry comprises about 2% of total nonfarm payrolls.^[v] But also, after booming in 2020 and 2021—and adding many jobs as a result—the Tech sector led 2022’s bear market down. Many Tech firms did see previously hot growth rates cool some. So it isn’t that shocking that they cut payrolls in response after adding hugely. But again, that likely says more about the conditions these businesses already endured than what is to come.

This doesn’t mean we think investors should ignore jobs data, which are chock-full of interesting information about industry and labor trends. But from an investing perspective, we think they are useful for what they say about sentiment than anything about the US economy’s prospects going forward. The acknowledgement of the resilience—and fretting over the Fed’s activities—point to some ongoing improvement in moods, though skepticism persists.