Why the January Jobs Report May Disappoint, and Is Sure to Perplex

The January jobs report is arriving at a critical time for the U.S. economy. Inflation is rising. The pandemic is still taking a toll. And the Federal Reserve is trying to decide how best to steer the economy through a swirl of competing threats.

Unfortunately, the data, which the Labor Department will release on Friday, is unlikely to provide a clear guide.

A slew of measurement issues and data quirks will make it hard to assess exactly how the latest coronavirus wave has affected workers and businesses, or to gauge the underlying health of the labor market.

“It’s going to be a mess,” said Skanda Amarnath, executive director of Employ America, a research group.

Data for the report was collected in mid-January, near the peak of the wave of cases associated with the Omicron variant. There is no question that the surge in cases was disruptive: A Census Bureau survey estimated that more than 14 million people in late December and early January were not working either because they had Covid-19 or were caring for someone who did, more than at any other point in the pandemic.

But exactly how those disruptions will affect the jobs numbers is less certain. Forecasters surveyed by Bloomberg expect the report to show that employers added 150,000 jobs in January, only modestly fewer than the 199,000 added in December. But there is an unusually wide range of estimates, from a gain of 250,000 jobs to a loss of 400,000.

The Biden administration and its allies are bracing for a grim report, warning on Twitter and in conversations with reporters that a weak January jobs number would not necessarily be a sign of a sustained slowdown.

Economists generally agree. Coronavirus cases have already begun to fall in most of the country, and there is little evidence so far that the latest wave caused lasting economic damage. Layoffs have not spiked, as they did earlier in the pandemic, and employers continue to post job openings.

“You could have the possibility of a payroll number that looks really truly horrendous, but you’re pulling on a rubber band,” said Nick Bunker, director of economic research for the job site Indeed. “Things could bounce back really quickly.”

Still, the January data will be unusually confusing because Omicron’s impact will affect different particulars in different ways.

The number that usually gets the most attention, the count of jobs gained or lost, is based on a government survey that asks thousands of employers how many employees they have on their payrolls in a given pay period. People who miss work — because they are out sick, are quarantining because of coronavirus exposure or are caring for children because their day care arrangements have been upended — might not be counted, even though they haven’t lost their jobs.

Forecasting the impact of such absences on the jobs numbers is tricky. The payroll figure is meant to include anyone who worked even a single hour in a pay period, so people who miss only a few days of work will still be counted. Employees taking paid time off count, too. Still, the sheer scale of the Omicron wave means that absences are almost certain to take a toll.

The jobs report also includes data from a separate survey of households. That survey considers people “employed” if they report having a job, even if they are out sick or absent for other reasons. The different definitions mean that the report could send conflicting signals, with one measure showing an increase in jobs and the other a decrease.

Economists typically pay more attention to the survey of businesses, which is larger and seen as more reliable. But some say they will be paying closer attention than usual this month to the data from the survey of households, because it will do a better job of distinguishing between temporary absences and more lasting effects from Omicron, such as layoffs or postponed expansions.

But economists have also cautioned not to minimize the impact that even temporary absences from work could have on families and the economy, especially now that the government is no longer offering expanded unemployment benefits and other aid.

“There isn’t that much Covid relief funding sloshing about anymore, so absences from work may actually reflect a meaningful decline in income,” said Julia Pollak, chief economist at the employment site ZipRecruiter.

Even in normal times, January jobs data can be tough to interpret. Retailers, shippers and other companies every year lay off hundreds of thousands of temporary workers hired during the holiday season. Government statisticians adjust the data to account for those seasonal patterns, but that process is imperfect. January is also the month each year when the Labor Department incorporates long-run revisions and other updates to its estimates.

“January is a messy month as it is,” Mr. Amarnath said.

This year, it could be extra messy because the pandemic has disrupted normal seasonal patterns. The labor shortage led some companies to hire permanent workers instead of short-term seasonal help during the holidays; others may have retained temporary workers longer than planned to cover for employees who were out sick. If that results in fewer layoffs than usual, the government’s seasonal adjustment formula will interpret that continued employment as an increase.

Other numbers could also be deceptive. The unemployment rate, for example, could fall even if hiring slowed. That is because the government considers people unemployed only if they are actively searching for work, and the spike in Covid cases may have led some to suspend their job searches.

Data on average hourly earnings could also be skewed because it is based on the payroll data — people who aren’t on payrolls aren’t counted in the average at all. Low-wage workers were probably the most likely to be missing from payrolls last month, since higher-wage workers are more likely to have access to paid sick leave. That could lead to an artificial — and temporary — jump in average earnings when policymakers at the Fed are watching wage data for hints about inflation.

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