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Net-worth distributions, 2026 edition

The Wealth Ladder

How much it takes to reach the top 1%, the top 0.1% and the top 0.01% in twelve economies — and how many people stand on each rung above them, from everyday millionaires to billionaires.

Anchored to Knight Frank The Wealth Report 2026 (UHNWI, $30m+), UBS Global Wealth Report 2026 (millionaires, $5–100m cohort, mean and median wealth, Gini), and Forbes World's Billionaires 2026. All figures in US dollars, end-2025 valuations unless stated. Thresholds and centi-millionaire counts are model estimates derived from those anchors — see method.
57.5m
US-dollar millionaires worldwide
UBS, 56 markets, end-2025 · nearly 1m new in 2025
713,626
Ultra-high-net-worth individuals ($30m+)
Knight Frank 2026 · 89 new UHNWIs a day since 2021
≈110k
Centi-millionaires ($100m+), model estimate
Read off the straight line joining the $30m and $1bn anchors
3,110–3,428
Billionaires, depending on who counts
Knight Frank 3,110 · UBS 3,302 · Forbes 3,428 (Mar 2026)

Twelve countries, one shape

Each line is the number of people whose net worth exceeds the value on the horizontal axis. On log–log axes a pure Pareto (power-law) tail would be a straight line, and the shallower the slope, the fatter the tail. These lines are not quite straight. The bend sits exactly where one source hands over to the next (UBS below $30m, Knight Frank above), so it is at least partly a source artefact — though real wealth distributions curve too. That is why the tail exponent α quoted for each country is the slope of the $30m–$1bn segment only. Switch to 1 in N adults to compare countries of different size: 1 in 100 is the top 1%, 1 in 1,000 the top 0.1%.

Solid dots are published anchor points: UBS $1m+, UBS $5m+ (its $5–100m cohort plus the modelled $100m+ count), Knight Frank $30m+, Forbes $1bn+. Hollow dots are model points ($100m+ everywhere; $5m+ for Canada and India, where UBS publishes no cohort). Between dots the line is interpolated, so a hover readout between anchors is a model value, not a published one. Dashed verticals mark the top 1%, 0.1% and 0.01% of adults for the highlighted country — hover or tap a line to highlight it.

The ladder, country by country

Click a column heading to sort. Gold figures are published by the source named in the header; the rest are model estimates derived from those anchors. Knight Frank's own top-1% thresholds (published in its 2024 report, valued at end-2023) are shown alongside for comparison.

Asterisked values carry a note — hover them. Adults = population aged 20+, rounded (UN WPP 2024 medium variant). Mean and median wealth per adult from UBS 2026; China and India mean/median are UBS regional or prior-edition figures and are marked. Gini is UBS 2026 (wealth). Canada's millionaire count is UBS 2025 (no 2026 estimate published); its $5–100m cohort and India's are interpolated.

Country profiles

Small multiples on identical axes (1 adult in N above each net-worth level), so the shape of each country's tail is directly comparable. The ladder beneath shows what it takes to reach each percentile in that country, and how many people stand above each round-number threshold — as a count and as 1 adult in N. Gold figures are published anchors; the rest are model estimates. A tilde (~) marks a threshold below $1m, which the model reaches by extrapolating past its lowest anchor.

Method and sources

How the estimates are built

  1. For each country, take four published anchor points on the survival curve N(>x): the number of US-dollar millionaires (UBS 2026), the number of adults with $5–100m (UBS 2026, added to the modelled $100m+ count to give N(>$5m)), the UHNWI population with $30m+ (Knight Frank 2026) and the billionaire count (Forbes, March 2026, China including Hong Kong).
  2. Take the slope of the straight line joining the $30m and $1bn anchors in log–log space: α = ln(N₃₀ / N₁bn) / ln(1000/30). Two points always lie on a line, so this is a ratio between two published counts, not a statistical fit. It is the tail exponent α reported on each card and in the table. Published estimates of wealth-tail exponents mostly fall between about 1.3 and 1.7; lower values mean a fatter tail.
  3. Read the centi-millionaire count off that line: N(>$100m) = N₃₀ · (100/30)^−α.
  4. Between anchors, interpolate linearly in log–log space (piecewise Pareto). Thresholds for the top 1%, 0.1% and 0.01% are the net worth at which N(>x) equals that share of the adult population. Where that net worth is below $1m — China's top 1%, India's top 1% and 0.1% — the $1m–$5m slope is extended below the lowest anchor. That is an extrapolation into a region where a Pareto tail is known not to hold, so those figures (marked ~) are rough.
  5. Where UBS publishes no $5–100m cohort (Canada, India), N(>$5m) is interpolated between the $1m and $30m anchors.

Read the caveats

  • The three source houses use different methods. UBS models the whole distribution from national balance-sheet data and counts adults; Knight Frank's Wealth Sizing Model and Forbes count individuals from proprietary databases. Mixing them is a pragmatic choice, not a statistical one. Treat the percentile thresholds as indicative; ±20% is our own rough judgement of the uncertainty, not a computed error bar.
  • Knight Frank's published top-1% cut-offs (2024 report, end-2023 values) run above this model everywhere except the United States, even though they are two years older. The most likely reason is that UBS's balance-sheet method counts more millionaires than Knight Frank's database-driven Wealth Sizing Model, so the same rank lands at a lower net worth here. We have not reconciled the two; both are shown.
  • Centi-millionaire counts here use total net worth. Henley & Partners / New World Wealth define "centis" by liquid investable wealth and counted 30,450 worldwide in their 2025 report; Altrata's counts sit in between. The definition, not the arithmetic, explains most of the gap.
  • The very top of every distribution is fatter than a single Pareto line. Extending the US $30m–$1bn slope past $1bn would put the 400th-richest American near $1.8bn; the actual 2025 Forbes 400 cut-off was $3.8bn. Above $1bn the model is therefore not shown.
  • Currency: a weak dollar in 2025 inflated non-US figures measured in USD (the euro rose about 13% against the dollar over the year); Japan's yen weakness has the opposite effect.

Sources

  • Knight Frank, The Wealth Report 2026 (20th edition, March 2026): Wealth Sizing Model — UHNWI population by country, global billionaire count 3,110, UHNWI growth 2021–26. Top-1% thresholds from The Wealth Report 2024.
  • UBS, Global Wealth Report 2026 (June 2026): millionaires by market, adults with $5–100m, average and median wealth per adult, wealth Gini, financial-asset shares, 3,302 billionaires (April 2026).
  • Forbes, World's Billionaires 2026 (March 2026): 3,428 billionaires by country of residence, US 989, China 610 incl. Hong Kong, India 229, Germany 212.
  • Henley & Partners / New World Wealth, Centi-Millionaire Report 2025, and the 2025 Forbes 400, cited in the caveats only.
  • Source names appear for attribution only. This page is independent of, and not endorsed by, Knight Frank, UBS, Forbes, Henley & Partners or the United Nations; a handful of headline figures are quoted from each report, with the reasoning built on top being ours.
  • UN World Population Prospects 2024 for adult population; McKinsey Global Institute, Global Balance Sheet 2026, for cross-checks on household wealth per capita.

Reading the exponent

A Pareto tail with exponent α means that each time you multiply the wealth level by 10, the number of people above it falls by a factor of 10α. With α ≈ 1.5, ten times the money means about 32 times fewer people; with α ≈ 1.25 (India) only 18 times fewer — the top is proportionally heavier relative to the merely rich.