Leading Economic Indicators vs Nonfarm Payrolls
Leading Economic Indicators and Nonfarm Payrolls are two Economic Indicators & Data concepts in AP Economics that students often mix up. Leading economic indicators are data that tend to change before the overall economy does, helping forecast future activity. Nonfarm payrolls measure the net change in jobs on employer payrolls outside farming, reported monthly by the Bureau of Labor Statistics. Here is how they compare side by side.
Examples include stock prices, new building permits, manufacturing orders, and consumer expectations. Economists watch them to anticipate expansions or recessions. They contrast with lagging indicators, which confirm trends after the fact.
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.
Leading Indicators vs Nonfarm Payrolls: Which Bucket the Jobs Number Belongs In
| Leading Economic Indicators | Nonfarm Payrolls | |
|---|---|---|
| Position in the cycle | Chosen to move before output turns | Moves with output, so classed as coincident |
| What it counts | A composite of several forward-looking series | One count of filled jobs on employer payrolls |
| Units | Index points measured against a base period | A net change in jobs for the month |
| Why the timing differs | Orders, permits and claims commit a resource before production changes | Hiring and firing follow the demand that already appeared |
| Revision behavior | Rebuilt when its components are revised | Each month is revised twice as late payroll returns land |
| What a fall means | A warning about the coming quarters | Evidence a contraction is running now |
| Exam role | Forecasting the next phase of the business cycle | Measuring current labor market conditions |
Payroll employment is coincident, and the hidden third bucket is the real question
Nonfarm payrolls sits in the coincident group rather than the leading one, so any prompt pitting the two against each other is testing whether you know the classification has three buckets instead of two. Payrolls is a net figure. If employers make 520 thousand gross hires in a month against 465 thousand separations, the reported change is positive 55 thousand, and both sides of that subtraction were responses to conditions firms already faced. Hiring is slow and expensive, so a firm stretches the hours of the staff it has before adding anyone, which is why the average manufacturing workweek belongs in the leading group while the headcount does not. The same logic places new orders, building permits and first-time unemployment claims ahead of output, since each commits a resource before production changes. Payroll employment moves alongside output for the plain reason that the jobs exist in order to produce it, which is why standard coincident measures pair payrolls with industrial production and with income earned from work. For the labor series that genuinely leads, see /glossary/initial-jobless-claims.
Revisions make a coincident series behave like a lagging one while you are living through it
A payroll figure is published while returns are still arriving and is revised twice as late reports land, which quietly changes what the series is worth in real time. A first print of positive 55 thousand can settle at negative 20 thousand two months later, and revisions tend to run against you near turning points, because the firms slowest to report are disproportionately the ones in trouble. The consequence is awkward: a series classified as coincident becomes trustworthy only after enough time has passed that a confirming series would also have moved. Leading composites carry the mirror-image flaw, timely but noisy enough to dip for a month or two with no downturn behind it. The trap on exams is a table of series with an instruction to pick the earliest warning, and employment feels like the economy, so students choose payrolls. A second trap treats payrolls and the jobless rate as one measurement. They come from separate surveys, one of employers and one of households, and the rate is conventionally classed as lagging while payrolls are coincident, so both can rise in the same month. Work the rate itself at /calculate/unemployment-rate.
Frequently asked questions
Are nonfarm payrolls a leading indicator?
No. Payroll employment is classed as coincident, meaning it turns at roughly the same time as output rather than ahead of it. Firms hire after demand appears and cut after it disappears, so the headcount records the cycle instead of anticipating it. The labor series that do lead are first-time unemployment claims and the average manufacturing workweek, both of which move before anyone is hired or dismissed.
Which jobs number moves first in a downturn?
Weekly hours usually go first, since a firm facing softer orders trims overtime before it trims people. First-time unemployment claims move next, because a layoff is filed in the week it happens. Payroll employment follows, and the unemployment rate later still, partly because discouraged workers stop searching and are no longer counted as unemployed at all.
Why can payrolls and the unemployment rate rise in the same month?
Different surveys, different denominators. Payrolls counts filled jobs reported by employers, while the unemployment rate compares jobless people who are actively searching against the whole labor force measured in a household survey. If 100 thousand jobs are added while 150 thousand people start looking for work, employment and the rate climb together, which signals returning confidence rather than a contradiction in the data.
Live Business Cycle graph. Drag the curves, or open the full version.
Related comparisons
Get AP Econ exam tips in your inbox
Occasional emails with study tips, new interactive graphs, and exam-season reminders. Free, no spam.
No spam. Unsubscribe anytime. Read our privacy policy.
Keep track of what you have studied
A free EconLearn account adds progress tracking, your quiz history, and achievements. Studying here is free either way, and there is nothing to pay for as a student.
Create a free accountAlready have one? Sign in
Last updated