Jobs Report Confuses: Payrolls Rise, Labor Force Shrinks
The latest jobs report from the Bureau of Labor Statistics (BLS) has presented a puzzling picture for the U.S. economy. While the report stated that 178,000 jobs were added in the past month and unemployment fell by 0.1%, other data points suggest a different reality.
Consumer confidence has hit a record low, with more people than ever believing jobs are hard to find. Companies are also signaling a cautious hiring approach, according to Indeed’s data.
This disconnect between the official job creation number and consumer sentiment is stark. In March, the same month the BLS reported adding 178,000 jobs, companies announced over 60,000 job cuts.
Weekly unemployment claims rose to 219,000, and the labor force itself shrank by 396,000 people. These figures contradict the headline job growth number, raising questions about the accuracy and interpretation of the widely cited statistic.
Understanding the Official Jobs Number
The number most often reported in headlines and cited by politicians is the total non-farm payroll count. This figure influences bond yields, Federal Reserve decisions, and political narratives about the economy’s health. However, this number may no longer reflect the lived experience of most Americans when they hear the term “jobs.” The BLS does not have real-time access to all payroll data; instead, it relies on two main surveys: the establishment survey and the household survey.
The Two Surveys: Establishment vs. Household
The establishment survey collects data from businesses about their payrolls, job titles, and locations. The household survey, on the other hand, asks individuals about their employment status, whether they are working, unemployed, or have lost their job.
In a healthy economy, these two surveys usually move in similar directions. For decades after World War II, the establishment and household numbers tracked each other closely, offering a consistent view of the labor market.
However, over the past decade, the gap between these two surveys has widened significantly, particularly since 2020. The San Francisco Fed has published research indicating this divergence is at its largest recorded level.
Essentially, the two surveys are now telling very different stories about the American labor market. The focus has remained on the establishment survey, which is structurally more likely to present a more optimistic outlook each month.
Why the Divergence? Three Key Problems
There are several reasons why the BLS data may not accurately reflect the current job market. The first issue is that the establishment survey counts payrolls, not people.
A single person holding multiple jobs or working across different locations can be counted multiple times. For example, a doctor working at a hospital, a private practice, and doing research could add three payrolls to the count, even though they are only one individual.
This was evident when 35,000 healthcare professionals returning from a strike were counted as new jobs. While technically true in terms of payrolls, it doesn’t represent new employment opportunities for 35,000 different people. This distinction is crucial when the household survey simultaneously reported 64,000 fewer people employed.
The second problem lies in the methodology of the establishment survey. Collecting accurate payroll data for the entire U.S. economy is incredibly complex.
The survey counts jobs by location, which makes it difficult to track remote workers or jobs that move between cities. As more work becomes location-independent, accurately assigning payrolls to a physical workplace and monitoring them month-to-month has become harder.
This difficulty contributes to large revisions in the data. Last year alone, the BLS revised down previously reported job gains by 800,000.
The survey’s methodology was designed for a time when most people worked in traditional office or factory settings, not for the modern, flexible workforce. The BLS also uses a “births and deaths” model to estimate business creation and closures, but this model is skewed by the rise of gig work, where a new Uber driver might be counted as a new “enterprise.”
The third and perhaps most significant problem is that the establishment survey misses a growing segment of the workforce entirely. It tends to count people in traditional W2 payroll jobs with established employers.
This excludes a large number of independent contractors, freelancers, consultants, and gig workers. These individuals are counted in the household survey, but if they lose work, their job losses are not reflected in the establishment survey’s payroll numbers.
When companies face economic downturns, they often cut contractors and freelancers first. These workers may not be eligible for unemployment benefits, so their job losses don’t immediately appear in unemployment claims. This can lead to situations where the labor force shrinks significantly, while the payroll number still appears to grow, as the two surveys capture increasingly different groups of workers.
Why the Flawed Number Persists
Despite its flaws, the payroll survey remains the primary source for monthly job data for two main reasons. First, it is fast, providing data quickly enough for the Federal Reserve and government to make timely decisions. Second, the payroll survey is considered more reliable than the household survey in some aspects.
Businesses are generally not motivated to inflate their payroll numbers for statistical purposes. In contrast, individuals might be less forthcoming in the household survey due to embarrassment or confusion about what constitutes an active job search.
The household survey also has its own timing issues. It captures data for the week containing the 12th of the month, meaning someone losing their job after the 13th would still be counted as employed for another month. Therefore, the household survey is not a perfect alternative, but it does capture a different, and arguably more representative, segment of the workforce.
Market Impact and Investor Considerations
The accuracy of these economic statistics is critical because they inform major policy decisions. Interest rate adjustments by the Federal Reserve, government stimulus debates, and foreign investment in U.S. Treasury bonds are all influenced by this data.
If the numbers appear artificially pessimistic or optimistic, they can lead to misguided policies and business decisions. Misinterpreting economic data can create a cycle of reduced hiring and consumer spending.
A lack of faith in economic statistics can erode confidence in the economy as a whole. While BLS economists are aware of these issues and have published research on them, changing the methodology in the U.S. is challenging. It could create data inconsistencies that markets dislike and require federal agencies to admit past reporting inaccuracies, which can be politically difficult, especially when facing potential budget cuts.
Each administration also has an incentive to maintain a data point that can be spun favorably. A monthly job number that fluctuates significantly can be politically convenient.
As a result, the methodology is likely to remain the same, leading to larger revisions and a widening gap between the headline statistic and the reality experienced by many workers. For the foreseeable future, the most quoted economic figure in the U.S. may continue to tell a story that fewer working people recognize.
Source: How Unemployment AND Employment Are Rising… At The Same Time (YouTube)
