The Commons · a hidden transfer everyone is in on
Who Really Pays for the Points
Credit-card rewards feel free. They are not free: they are funded by a fee baked into the price of everything, a fee the cashier charges you whether you pay with a rewards card, a debit card, or a fistful of twenties. A major 2026 study puts the yearly transfer at about $30 billion, flowing from people who pay cash and debit to people who pay with rewards cards, and it runs uphill, from poorer households to richer ones.
Here is the trick. When a store accepts a card, it pays an interchange fee: typically about 1.9% of the sale, most of which funds the cardholder's rewards. The store doesn't post two prices. It folds that cost into one shelf price that everyone pays. So the fee is already in the number on the tag before you decide how to pay. Pull out cash and you don't escape it; you just forfeit the rewards it was paying for.
Set your own numbers below. The one thing you operate is how you pay; everything recomputes from the same arithmetic the checker at the bottom re-runs offline.
How do you pay?
Markup baked into every price you pay
95 bps
= 1.90% fee × 50% card share of sales
Rewards you earn back
$0
cash earns nothing
Your net for the year: $24,000 of spending
You subsidize $228 to other people's rewards this year.
Groceries, gas, restaurants, online: anywhere a card is taken.
Flat-cash cards ≈1%. Premium travel cards clear 2%+ effective.
Study's typical figure is ~1.9%. Premium cards push it toward 3%.
Notice the break-even. You come out ahead only if your reward rate beats the markup: only if r > 0.95%. Below that line every shopper is paying more in hidden markup than they get back in points, and the difference is pure subsidy to whoever is above the line. That's why the game is stable: for you, individually, carrying the best rewards card is the rational move, which is exactly why nobody stops, and the transfer never unwinds.
The part that stings: paying cash doesn't get your money back
The intuitive escape ("fine, I'll just pay cash") mostly doesn't work. To recover the fee you'd need the store to charge you less for cash. Almost none do: in 2022 only about 3% of cash payments came with any discount (Atlanta Fed). So the cash user pays the full baked-in markup and gets nothing back: the worst seat in the house.
Twist 1 · you subsidize regardless
This is the reversal most explainers miss. "Rewards aren't free, someone pays" is only half of it. The other half: opting out by paying cash doesn't make you the one who stops paying. The fee is in the price either way; cash just strips off the rebate. The only way to stop subsidizing is for the whole equilibrium to change, not for you to reach for bills.
Which way it runs: uphill
If everyone used cards the same amount, the markup would wash out; you'd pay it and get it back. It doesn't wash out because card use rises steeply with income. Lower-income households pay cash far more often, so they pay the markup and collect fewer of the points it funds. In the Federal Reserve's 2024 diary, households under $25k paid cash for 24% of payments; households over $150k, just 9%. That gap is the engine of the regressive transfer.
Bars show each tier's yearly net at the current markup: red = pays in, green = collects. Direction is what's robust; the two endpoint cash shares (24% / 9%) are Fed-published, the middle three are interpolated between them and labelled below.
Twist 2 · the study's own $9.2B
The headline transfer runs cash-and-debit → rewards; the regressive slice, money crossing from households under $150k up to those above, is about $9.2 billion of the ~$30 billion, roughly 31% of it. The direction is the robust finding across the whole literature. The exact dollar total is the softest number on this page (see the check).
The honest haircut: it's smaller than a naïve model says
A crude version of this argument assumes everyone shops at the same store and pays the same fee. Reality is messier and it cuts against the alarm: cash-heavy shoppers sort toward lower-fee merchants (discount stores, cash-friendly corners), and merchant fees vary. The study finds this consumer sorting and fee heterogeneity shrink the transfer by about 25%: real, but nowhere near enough to erase it.
Twist 3 · smaller, not gone
Naming this is the difference between a scare and an answer. The 25% haircut is the study's own correction, and this page keeps it switched on by default. The transfer survives it, because sorting is partial and cash-heavy households still can't dodge every marked-up shelf.
Policy and product design already moved this
Two forces reshaped who wins. The 2010 Durbin Amendment capped debit interchange, and the study finds regulated-debit users lost about $9.6B in vanished rewards and free checking, a transfer from middle-income to higher-income households. Meanwhile premium cards grew from 15% of credit volume in 2006 to 60% by 2022, and their richer fees widened the gap: premium holders gained about $7.9B. Both the cap and the card were found regressive. The incidence isn't fixed by nature; it's shaped by rules and rewards, and it has moved before.
| who | net purchasing power | direction |
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The study's measured incidence, in basis points of purchasing power. These are the coefficients the calculator's per-user math is calibrated against; our simple μ = fee × share reproduces the cash line to within a basis point.
The check: every number, reconciled
Two kinds of number live on this page, and honesty means keeping them apart. The calculator's numbers (your markup, your net, the break-even) recompute live from μ = fee × share and net = rewards − markup. Press the button to re-run them and see them cross-check against the study's measured 96 bps cash loss. The aggregate numbers ($30B, $9.2B, the incidence table) are the 2026 study's measured estimates from proprietary merchant data; we don't re-derive them from four sliders; we reconcile them against public 2024 credit-purchase volume and against each other.
Free choices & uncertainties named:
- The $30B magnitude is one 2026 study's estimate and is contested by industry-aligned analysts (e.g. ICLE). Read it as "a major 2026 study estimates," not settled fact. The regressive direction is robust across the literature; the exact dollar total is the softest number here.
- Card share = 50% is a calibration: it's the value that makes the live markup match the study's measured 96 bps cash loss at a 1.9% fee. The study backs the markup out of merchant data; we back the share out of the markup.
- "Cash-and-debit" is a lump. Durbin-capped debit users subsidize less per dollar than cash users (−47 vs −96 bps), because regulated debit interchange is tiny. The study uses the combined bucket; we follow it, and show the split in the incidence table rather than hide it.
- Income-tier cash shares: only the endpoints (24% under $25k, 9% over $150k) are Fed-published 2024 figures. The three middle tiers are a monotone interpolation to illustrate direction, not measured values.
- This describes the equilibrium; it is not financial advice. "A rewards card is individually rational" is a statement about incentives, not a recommendation about your wallet.
Run it yourself: node research/cash-users-subsidize-credit-card-rewards/verify-cash-users-subsidize-credit-card-rewards.mjs
The model, in one paragraph: what's exact and what's assumed
The identity. Under full pass-through and a single posted price (the empirically normal case: only ~3% of cash sales get a discount), the fee a merchant pays on its card sales is spread across all sales as a markup μ = fee × (card share of sales). Every shopper pays μ on every dollar. A shopper's yearly net is rewards − markup: a cash or debit user earns no card rewards, so their net is exactly −μ × spend; a rewards cardholder nets (reward rate − μ) × spend, positive only when the reward rate clears the markup. This is a closed transfer: summed across everyone at a shared merchant it nets to zero, so every dollar a below-average card-user loses is a dollar an above-average one gains. That is the whole mechanism, and it's exact given the assumptions.
Assumed. Full pass-through of the fee into prices (the study's central case; pass-through under 100% shrinks the level but not the direction); a single posted price; and, for the calculator, a representative shopper using one method. Measured, not assumed (taken from the study): the −96 / −47 / +48 / +59 bps incidence, the ~25% sorting haircut, the $30B and $9.2B totals, and the Durbin and premium-card figures. Reconciled: $30B ÷ $6.14T of 2024 credit-purchase volume ≈ 49 bps average gain per credit dollar, which sits squarely between the study's +48 bps (basic) and +59 bps (premium). The pieces agree.