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BLS nonfarm payrolls and benchmark-adjusted data.

Understanding the Lead Chart

Before discussing the December data, it is important to understand the lead chart.

As part of its monthly jobs reports, the BLS provides an adjustment series to normalize employment levels to match nonfarm payrolls

The experimental series is LNS16000000, “Employment Adjusted to CES Concepts“.

The BLS admits that it undercounted employment by 2 million, spread out over a number of years. Instead of parsing that out in the correct months, the BLS plowed the entire adjustment into January of 2025.

This makes all historical comparisons of numbers flawed. I was unaware an alternate data series correcting the errors existed until last month.

All my charts going forward will use the best data available, and that is the experimental series.

There is valid data on overall employment. However, there is no valid data on full vs parttime employment, on foreign born employment, etc.

Cheerleading Nonsense

There has been massive cheerleading of Trump all year on year-over-year jobs and especially foreign-born employment. It’s all nonsense.

Assuming there are no more negative revisions (and what is the likelihood of that), the year-over-year employment gain was just 610,000.

I expect the next benchmark revision to wipe that out. Thud!

Now, let’s move on to the Monthly Jobs Report from the BLS.

Initial Thoughts

After a two-month hiatus from the government shutdown with extrapolated or no data, the BLS has data to report.

As has been customary for well over a year, BLS monthly revisions are negative.

The BLS revised October lower by 68,000 and November by 8,000. There is every reason to expect more negative revisions.

The BLS comments, “Effective with the release of The Employment Situation for January 2026 on February 6, 2026, nonfarm payroll employment, hours, and earnings data from the establishment survey will be revised to reflect the annual benchmark process and updated seasonal adjustment factors.”

So we will have more benchmark revisions next month further invalidating historical data.

I will continue to use what the BLS refers to as “experimental data” in my charts because the official series data is admitted garbage, especially for year-over-year comparisons.

All household data is subject to bad sampling and poor response rates. Illegal immigrants are highly unlikely to be responding accurately to government data surveys, if responding at all.

Monthly Job Report Details

• Nonfarm Payroll: +50,000 to 159,526,000 – Establishment Survey
• Civilian Non-institutional Population: +183,000 to 274,816,000
• Civilian Labor Force: -46,000 to 171,495,000 – Household Survey
• Participation Rate: -0.1 to 62.4% – Household Survey
• Employment:+232,000 to 163,992,000 – Household Survey
• Unemployment: -278,000 to 7,503,000 – Household Survey
• Baseline Unemployment Rate: -0.1 to 4.4% – Household Survey
• Not in Labor Force: -229,000 to 103,321,000 – Household Survey
• U-6 unemployment: -0.3 to 8.4% – Household Survey

Nonfarm Payrolls Change by Sector

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Nonfarm Payrolls Change by Sector in Thousands

• Nonfarm Payrolls: +50
• Manufacturing: -8
• Construction:-11
• Leisure and Hospitality: +47
• Private Education and Health Care: +41
• Professional and Business Services: -9
• Information: 0
• Financial: +7
• Retail: -25
• Wholesale: -2
• Government: +13

Leisure and Hospitality, and private education and health (demographic related) were the only two strong sectors.

Monthly Revisions

• The change in total nonfarm payroll employment for October was revised down by 68,000, from -105,000 to -173,000
• The change for November was revised down by 8,000, from +64,000 to +56,000.
• With these revisions, employment in October and November combined is 76,000 lower than previously reported.

Part-Time Jobs

• Involuntary Part-Time Work: -146,000 to 5,341,000
• Voluntary Part-Time Work: -817,000 to 22,251,000
• Total Full-Time Work: +890,000 to 135,215,000
• Total Part-Time Work: -260,000 to 28,712,000
• Multiple Job Holders: +444,000 to 8,848,000

The above numbers never total correctly due to the way the BLS makes seasonal adjustments. I list them as reported.

Monthly data is to be taken with a huge dose of skepticism. Year-over-year comparisons are simply invalid. Data is so bad I may stop reporting

All of this is subject to bad sampling and poor response rates. Illegal immigrants are highly unlikely to be responding accurately to government data surveys, if responding at all.

Hours and Wages

This data is frequently revised.

• Average weekly hours of all private employees down by 0.1 at 34.2 hours.
• Average weekly hours of all private service-providing employees was flat at 33.2 hours.
• Average weekly hours of manufacturers fell 0.2 hours to 39.9 hours.

An overall decline or rise of a tenth of an hour does not sound line much, but with employment over 160 million, it’s more significant than it appears at first glance.

In a falling employment setup, hours of the remaining employees tend to rise, at least initially.

Hourly Earnings

This data is also frequently revised. Here are the numbers as reported this month.

Average Hourly Earnings of All Nonfarm Workers rose $0.12 to $37.02. A year ago the average wage was $35.68. That’s a gain of 3.8%.

Average hourly earnings of Production and Nonsupervisory Workers rose $0.03 to $31.76. A year ago the average wage was $30.67. That’s a gain of 3.6%.

Those gains are reportedly beating inflation. But that’s nonsense too because the CPI does not count property taxes or homeowners’ insurance in its calculations.

Unemployment Rate

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Unemployment rate seasonally adjusted, data from BLS, chart by Mish

Alternative Measures of Unemployment

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Table A-15 is where one can find a better approximation of what the unemployment rate really is.

• The official unemployment rate is 4.4 percent.
• U-6 is much higher at 8.4 percent.

Both numbers would be way higher still, were it not for millions dropping out of the labor force over the past few years.

Some of those dropping out of the labor force retired because they wanted to retire. Some dropped out over Covid fears and never returned. Still others took advantage of a strong stock market and retired early.

The rest is disability fraud, forced retirement (need for Social Security income), and discouraged workers.

Birth Death Model

Starting January 2014, I dropped the Birth/Death Model charts from this report.

The birth-death model pertains to the birth and death of corporations not individuals except by implication.

For those who follow the numbers, I retain this caution: Do not subtract the reported Birth-Death number from the reported headline number. That approach is statistically invalid.

Birth-Death Methodology Explained

I gave a detailed explanation of the model and why the usual calculation is wrong in my June 8, 2024 post How Much Did the BLS Birth-Death Adjustment Pad the May Jobs Report?

I repeat, do not subtract the birth-death number from the headline number.

Household Survey vs. Payroll Survey

• The payroll survey (sometimes called the establishment survey) is the headline jobs number. It is based on employer reporting.
• The household survey is a phone survey conducted by the BLS. It measures employment, unemployment and other factors.

If you work one hour, you are employed. If you don’t have a job and fail to look for one, you are not considered unemployed, rather, you drop out of the labor force.

Looking for job openings on Jooble or Monster or in the want ads does not count as “looking for a job”. You need an actual interview or send out a resume.

These distortions artificially lower the unemployment rate, artificially boost full-time employment, and artificially increase the payroll jobs report every month.

The BLS payroll reports smack of oversampling large employers and undersampling small employers where jobs have been trending lower.

Expect Negative Revisions

On September 9, 2025 I commented New QCEW Data Indicates More Big Negative Revisions Coming to Job Reports

The discrepancy between jobs reports and quarterly data widens again.

It’s based on highly accurate QCEW data that I expect negative benchmark revisions next month.

Understanding the Enormous BLS Job Report Errors

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For a full explanation of the lead chart, please see my December 18, 2025 post Understanding the Enormous BLS Job Report Errors, What Really Happened?

Four things: Immigration, Birth-Death Model, Response Rates, Sampling.

Incredibly Bad Standard Numbers

Many people are reporting unbelievable year-over-year numbers, then attributing the improvement to Trump.

For example, on the Benchmark adjusted chart, Employment in November 2025 was 163,741,000 and November of 2024 was 161,661,000. That’s supposedly a gain of 2.08 million.

But that entire gain occurred in January of 2025 when the BLS threw the whole adjustment into a single month.

Foreign-Born Employment Nonsense

The numbers in my charts are seasonally adjusted. Foreign born employment is not adjusted, compounding comparison errors.

And we have no BLS revised data for foreign born employment. So, all such foreign and US-born comparisons with BLS data remain garbage.

A second major problem with foreign-born employment is the BLS makes no distinction between US citizens who were foreign born and genuine foreign workers.

How Fast is the US Shedding Foreign-Worker Jobs?

On December 11, 2025 I asked How Fast is the US Shedding Foreign-Worker Jobs?

Think carefully.

Foreign-born includes US citizens.

There is one more big issue. Since there is widespread disbelief in BLS numbers, why are we supposed to believe this set of BLS numbers?

Are Illegal immigrants suddenly responding to BLS household surveys?

It’s really sad to see a parade of people challenging every BLS report for years, suddenly become believers that that we created 2 million jobs in a single month in January of 2025, all of them US born.

Final Thoughts

As noted, we are working with highly revised monthly data then potentially huge benchmark revisions.

Those annual benchmark revisions, despite being the BLS best estimates, are considered “experimental”. It’s ass backward.

My lead chart is a better approximation of what’s really happening than you can find elsewhere.

Next month we have more annual benchmark revisions that will not be posted to the official data series. Expect more negative revisions.

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