US Income Percentile Calculator

Estimate where your annual income ranks among US households, using a lognormal distribution model calibrated to the Census Bureau's published median income and Gini index.

Quick Facts

Formula
percentile = Φ((ln(income) − ln(median)) / σ)
σ = √2 · Φ−1((Gini + 1) / 2), where Φ is the standard normal CDF.
Reference data
2024 median household income: $83,730
US Census Bureau, "Income in the United States: 2024" (Report P60-286); household Gini index 0.49.
Model
Lognormal approximation
A standard way to approximate an income distribution's shape from just its median and Gini index.

Your Results

Calculated
Income percentile
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Where you rank nationally
Top share
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Households estimated to out-earn you
Vs. reference median
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Multiple of the median income entered
Top 10% threshold
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Approx. income for the 90th percentile

Ready

Enter an income, reference median, and Gini index, then press Calculate.

How the US Income Percentile Calculator works

This tool answers a specific question: given an annual income, roughly what share of US households earn less — and what share earn more? Exact answers require the Census Bureau's raw survey microdata, which is not something a page of JavaScript can query in real time. Instead, this calculator uses the standard shortcut economists reach for when only summary statistics are available: it fits a lognormal distribution to the income data using two published numbers — the median household income and the Gini index (a 0-to-1 measure of income inequality) — and reads your percentile off that fitted curve.

The formula

A lognormal distribution means the natural log of income is normally distributed. Two parameters define it: μ (the mean of log-income) and σ (its standard deviation). Because the median of a lognormal distribution equals eμ, we get μ directly from the median you enter:

μ = ln(median income)

The Gini index of a lognormal distribution has a known closed form, G = 2Φ(σ/√2) − 1, where Φ is the standard normal cumulative distribution function. Solving for σ:

σ = √2 · Φ−1((G + 1) / 2)

Once μ and σ are known, your percentile is just the standard normal CDF applied to the standardized log-income:

percentile = Φ((ln(income) − μ) / σ) × 100

The calculator also inverts the same formula to report the income threshold for the 90th percentile: income90 = eμ + σ·Φ−1(0.90).

Where the default numbers come from

The calculator pre-fills a median household income of $83,730 and a Gini index of 0.49, both from the US Census Bureau's report "Income in the United States: 2024" (Report P60-286), based on the 2025 Current Population Survey Annual Social and Economic Supplement covering calendar year 2024 income for all US households. Both fields are editable — enter a different year's figures, a state-level median and Gini, or statistics for a different reference group (such as individual earners) if you have them, and the same formula applies.

Worked example

At the default settings, an annual income of $75,000 against a $83,730 median and 0.49 Gini index works out to roughly the 45th percentile — modestly below the midpoint, consistent with the income being below the median. Raising the income to $150,000 with the same reference statistics pushes the estimate to roughly the 73rd percentile, and $250,000 lands around the 88th percentile — illustrating how the lognormal curve compresses near the median and stretches out at higher incomes.

Why this is an approximation, not an exact lookup

Real income distributions are not perfectly lognormal — they tend to have a fatter right tail than the lognormal curve predicts, meaning this model can understate just how exclusive the very top percentiles (the top 1% or top 0.1%) actually are. It also treats "income" as a single number without adjusting for household size, region, or age, all of which real Census tables break out separately. Treat the result as a solid, transparent estimate of where you sit in the broad middle of the distribution, and treat estimates near the extreme tails as directional rather than precise.

Frequently Asked Questions

How does this calculator estimate my income percentile?
It fits a lognormal distribution to US household income using two published statistics: the median income and the Gini index (a standard measure of income inequality). From the Gini index it derives the distribution's spread (σ = √2 · Φ−1((Gini + 1) / 2)), then converts your income into a percentile with the standard normal cumulative distribution function applied to (ln(income) − ln(median)) / σ.
Why use a lognormal model instead of exact Census percentile tables?
Exact microdata percentile tables aren't published as a simple formula, so this calculator uses the lognormal approximation economists commonly use to model income distributions from just two summary statistics. It tracks the broad shape of US household income well for the middle of the distribution but is less precise at the extreme tails, such as the top 1%, where real income distributions are fatter-tailed than a lognormal curve.
What do the median income and Gini index inputs represent, and can I change them?
They're pre-filled with the US Census Bureau's most recently published figures for all US households (median household income and the household Gini index from the "Income in the United States" report). You can edit either field to model a different year, a different reference group, or your own state's figures, as long as you know that group's median income and Gini index.
Does this model household income or individual income?
By default it compares your entry against all US households using the household median and Gini index. To estimate an individual earner's percentile instead, replace the median and Gini index with the corresponding figures for individual earners — the underlying lognormal formula works the same way for either reference population.

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