Nonfarm Payrolls vs Unemployment Rate
Nonfarm Payrolls and Unemployment Rate are related concepts in AP Economics that students often mix up. Nonfarm payrolls measure the net change in jobs on employer payrolls outside farming, reported monthly by the Bureau of Labor Statistics. The unemployment rate is the percentage of the labor force that is jobless and actively looking for work: unemployed divided by labor force, times 100. Here is how they compare side by side.
Nonfarm payrolls come from the establishment survey, a monthly count of jobs at businesses and government agencies that leaves out farm work, the self-employed, unpaid family workers and private household employees. The headline is the net change from the previous month, so it sets hiring against separations rather than counting gross hires. Payrolls are a coincident indicator, since employment moves broadly in step with output rather than ahead of it. The same release carries the household survey, which produces the unemployment rate, and the two can disagree because they count different units: payrolls count jobs, so one person holding two jobs appears twice, while the household survey counts people. Each month's payroll estimate is revised in the two following reports, so a first print is a draft rather than a final figure.
The unemployment rate is the percentage of the labor force that is currently unemployed and actively seeking employment. It is calculated by dividing the number of unemployed workers by the total labor force and multiplying by 100. The unemployment rate is an important economic indicator, as it helps to measure the health of the labor market and the overall economy. A high unemployment rate can have negative effects on the economy, while a low unemployment rate can be beneficial for economic growth and stability.
Nonfarm Payrolls vs the Unemployment Rate: Two Surveys in One Report
| Nonfarm Payrolls | Unemployment Rate | |
|---|---|---|
| Who gets asked | Employers, from their payroll records | Households, by interview |
| What is counted | Jobs, so one person holding two of them counts twice | People, each counted once however many jobs they hold |
| Left out by design | Farm work, the self-employed and unpaid family workers | Nobody in the civilian population aged 16 and over |
| Shape of the number | A net change in jobs, quoted in thousands | A percentage of the labor force |
| Revisions | Revised in later months as more payroll records arrive | Not normally revised, apart from updated seasonal factors |
| What makes it look better | Employers adding jobs | Fewer people jobless, or job seekers giving up and leaving the labor force |
| Sample size | A large employer sample, so the monthly figure is comparatively steady | A much smaller household sample, so the monthly figure is noisier |
A month can add half a million jobs and still print a higher unemployment rate
The two headline figures in the monthly jobs report come from different surveys, so they can move in opposite directions in the same month without either being wrong. Work through an illustrative economy. The labor force is 160.0 million, with 152.0 million employed and 8.0 million unemployed, giving a rate of 8.0 divided by 160.0 times 100, or 5.0 percent. Over the next month employers add 500,000 jobs and the household survey records the same gain in people employed. At the same time 900,000 people who had not been looking start searching, so they enter the labor force. Employment rises to 152.5 million and the labor force rises to 160.9 million, which leaves 8.4 million unemployed. The rate becomes 8.4 divided by 160.9 times 100, or about 5.2 percent. Hiring was strong and the rate still went up. This pattern is common early in a recovery, when news of hiring pulls people who had stopped searching back into the count, and their return raises the denominator faster than the new jobs shrink the numerator. The reverse case is just as instructive: a month with almost no hiring can print a lower rate if enough job seekers give up, since /glossary/discouraged-workers sit outside the labor force entirely. Practice the rate arithmetic at /calculate/unemployment-rate.
Counting jobs and counting people are not the same exercise
Payrolls count positions on company books; the household survey counts individuals. If 100,000 people each pick up a second job, payrolls rise by 100,000 while the number of people employed is unchanged and the unemployment rate does not move at all. Run it the other way and the gap opens again. A wave of people setting up on their own account shows up as employment in the household survey and not at all in payrolls, because the self-employed have no employer filing a payroll record. Farm work and unpaid family work sit outside payrolls too. The surveys also differ in precision. The employer sample is far larger, which is why the payroll figure is treated as the better read on the pace of hiring, while the household count of employment jumps around and works better as a rate than as a level. That is also why the unemployment rate is the number written into policy discussions and into rules of thumb such as Okun's law, since a percentage of the labor force can be set against a benchmark like the natural rate. Neither survey is a correction of the other, and analysts read them together. /macro/unemployment-inflation shows where each one enters the standard model.
Frequently asked questions
Can nonfarm payrolls rise while the unemployment rate also rises?
Yes, and it happens most often when people who had stopped looking for work start searching again. Those returning workers count as unemployed the moment they resume searching, so the labor force grows faster than employment does. The result is solid job growth alongside a higher rate.
Why do the payroll survey and the household survey disagree?
They disagree because one counts jobs at businesses and the other counts employed people at home, and the two definitions cover different groups. Multiple jobholders inflate payrolls relative to household employment, while the self-employed, farm workers and unpaid family workers appear only in the household figures. Sampling error in the smaller household survey widens the gap in any given month.
Which number is the better read on the labor market?
Payrolls give the cleaner monthly signal on hiring, while the unemployment rate gives the better signal on slack. The payroll figure comes from a much larger sample and is quoted as a change, so it tracks momentum. The rate is what gets compared with the natural rate to judge whether the economy is above or below full employment.
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