Earned Income Proxy
Estimate consumer wage momentum from jobs, hours, and pay
- Difficulty
- Easy
- Time to result
- ~days to results
- Steps
- 5
- Confidence
- 99%
The Earned Income Proxy reduces a sprawling monthly employment report to three drivers of total wage income: how many people work, how many hours they work, and what they earn per hour. Combine those inputs to estimate total wages, then monitor the month-over-month change. Yardeni's mechanism links labour data to consumption: wages drive the consumer to a large extent, so a stronger proxy can foreshadow stronger retail sales even when the headline payroll number disappoints. The framework avoids treating one employment headline as the whole story. It deliberately checks whether changes in hours or hourly pay offset a weak jobs count, producing a more direct view of the income flow available to support spending.
Origin
Edward Yardeni described the Earned Income Proxy as the focused calculation his team used to cut through the monthly employment-data release.
Core principles
- 01Focus on the variables that determine aggregate wages
- 02Combine employment quantity, working time, and wage rates
- 03Use income momentum to anticipate consumer activity
How to run it
- 1
Count workers
Take the reported number of people working as the first input to aggregate wage income.
Pro tip Keep the release vintage consistent when comparing months.
Watch out Do not stop at the headline payroll change.
- 2
Measure working time
Add the average number of hours worked so the estimate reflects changes in labour utilization.
Pro tip Look for hours offsetting an apparently weak employment count.
- 3
Add the wage rate
Include the hourly wage to capture changes in what each hour of work earns.
Pro tip Read wage changes alongside jobs and hours rather than in isolation.
- 4
Estimate total wages
Combine workers, hours, and hourly wages into a total-wage proxy.
Pro tip Preserve the calculation in a monthly series.
Watch out The proxy is an earned-wage measure, not all household income.
- 5
Read the change
Calculate the month-over-month movement and use it as a directional signal for consumer spending.
Pro tip Compare the result with the next retail-sales release to calibrate its usefulness.
Watch out One month's movement can be noisy.
In the wild
Yardeni recalled a month when the payroll number disappointed, but hours and wages lifted the Earned Income Proxy by about 0.7 percent month over month. That broader wage calculation proved a useful harbinger of retail sales coming in better than expected.
→ The proxy detected consumer-income strength that the payroll headline obscured.
Common mistakes
Using payrolls alone
A disappointing jobs count can conceal stronger hours or wages and therefore understate aggregate earned-income momentum.
Treating the proxy as total income
The calculation estimates wages; it does not capture every source of household purchasing power.
Is it for you?
Best for
It is best for analysts who need a focused monthly read on household earned-income momentum.
Not ideal for
It is not ideal as a complete measure of household purchasing power because it does not by itself include taxes, transfers, wealth, or credit.
From the transcript
“we calculate something called the earned income proxy”
“how many people are working, how many hours are they working, and what's their wage”
“the earning income proxy was up like zero point seven percent”
From the episode
Interview With Edward Yardeni: Masters in Business (Audio)