Global M2 Money Supply: Four Economies or 159?

Global M2 money supply has no single figure, because “global” means a different country set to every tracker that publishes one. StreetStats and MacroMicro sum four major central banks and get $102.66 trillion (MacroMicro, 2026-06) to $103.28 trillion (StreetStats, June/July 2026), both checked 2026-08. We sum 159 of the 185 economies we track and get $144.41 trillion, newest row 2026-06. The four banks are the Fed, the ECB, the PBoC and the BoJ. Neither total is wrong. They answer different questions, and this page works out which question is which.

Four Economies or 159? What “Global M2” Means Here

StreetStats defines its own metric plainly: “the M2 values of the four largest global economies (U.S., China, Euro Zone, and Japan)… converted to U.S. dollars.” MacroMicro’s series carries the same scope under a longer name, “World - Major Central Bank M2 Money Supply.” Both are an aggregate money supply figure for the same four USD-converted economies. Google’s AI Overview for this exact query lands on “roughly $103.1 trillion” and cites both of them among its sources (checked 2026-08). That figure sits between the two and matches neither.

Four economies does include China. That settles a fan-out question directly: yes, both incumbent aggregates count China, and so does ours. China is the single largest component of our $144.41 trillion total — $42.64 trillion (2024), 29.5% of the sum.

Our aggregate isn’t four economies — it’s an all-country sum. It’s 159 of the 185 we track: every economy publishing a broad-money series we can source and convert to USD. Twenty-six rows sit outside it, and they are not one category. Twenty-four carry no World Bank exchange rate at all: the 20 euro-area members, whose money is the Euro Area series rather than their own, plus Anguilla, Montserrat, the Eastern Caribbean Currency Union and the West African Economic and Monetary Union. Two more we drop deliberately: the IMF’s separate euro-area row, which would count the ECB series twice, and Somalia, whose shilling series converts to $71,961 (2025-03) because the country runs on dollars and the national-currency series is only what’s left over.

That’s the country-set lever, and it’s the largest one. Adding 155 more economies to the four-economy base adds $40.30 trillion — 27.9% of our world total. That’s not bigger central banks printing more. It’s counting economies the “major central bank” aggregate never includes: India ($3.57T, 2026-04), Brazil ($2.80T, 2026-05), South Korea ($3.14T, 2025-10) among them.

Why Do Global Liquidity Charts Disagree With Each Other?

Four levers move a “global money supply” figure, and none of the four is an error.

Country set. Four economies against 159 — the biggest lever, covered above.

Aggregate definition. “M2,” “M3” and “broad money” are not one instrument list. StreetStats publishes its boundary: M2 in all four countries, currency in circulation through non-institutional money-market funds (checked 2026-08). MacroMicro’s series page gives the four banks and their units, not the inclusion rule (checked 2026-08). Ours blends IMF broad-money series, ECB M3 for the Euro Area, and World Bank backfills — comparable measures, not identical inclusion rules country by country.

FX method. A dollar-denominated total moves whenever the dollar moves, independent of any central bank. We use the World Bank’s period-average rate. StreetStats uses the spot rate for its headline figure, and a three-year average for its constant-FX variant. Three conventions, three different answers — from the same underlying money.

Vintage. Every world total sums observations taken on different dates. Ours spans 2008-05 to 2026-06 across 159 economies; StreetStats’ four-economy figure mixes June and July 2026 readings inside one headline number.

The next two sections size the FX and vintage levers with our own numbers, not with a claim.

The Four-Economy Cross-Check: Our Data Against Their Method

Restrict our own dataset to the same four economies StreetStats and MacroMicro track. Sum them: United States $30.68 trillion (2025-12), China $42.64 trillion (2024), Euro Area $19.90 trillion (2026-06), Japan $10.89 trillion (2026-02). The total is $104.12 trillion. That’s 1.4% above MacroMicro’s $102.66 trillion (2026-06) and 0.8% above StreetStats’ $103.28 trillion, both checked 2026-08.

Different sources, different FX conventions, different observation dates per row — and the four-economy sum still lands within 1.5% of both incumbents. That agreement is the useful finding. The country-set lever, not sourcing quality, explains most of the gap between any “major central bank” total and a full world sum. The remaining $40.30 trillion between our four-economy figure and our $144.41 trillion world total comes from the other 155 economies. It’s not a better or worse method.

Growth splits wider than the level does. MacroMicro’s four-economy aggregate grew 8.13% year over year to 2026-06. Weight each of our four economies by its USD value and apply its own year-over-year rate (United States 6.0% at 2025-12, China 6.8% at 2024, Euro Area 4.0% at 2026-06, Japan 0.3% at 2026-02), and the same four come to 5.37%. Those rates are computed in local currency, so no exchange-rate move sits inside them; MacroMicro’s aggregate is USD-converted, so one does. The two figures also don’t share a window: ours mixes the four vintages just listed, theirs is a clean twelve months to June 2026. The 2.76-point gap measures the method, not the money.

The cross-check carries its own vintage warning inside it, too. Our four-economy figure already mixes a 2024 China reading with 2025 and 2026 readings for the other three. That’s the exact problem the next section describes — present in our own numbers before it’s present in the world total.

One single-country gap is sharp enough to name directly rather than average away. StreetStats reports China’s M2 at $52.99 trillion (June 2026, current-rate USD conversion). Our own figure is $42.64 trillion (2024, World Bank period-average conversion). That’s a $10.34 trillion, 24.3% gap on the same country, from an eighteen-month vintage difference and a different FX convention stacked together. Neither figure is fabricated — both need a stated method before “how much” means anything.

What the FX Method Does to the Number

We convert every currency at the World Bank’s PA.NUS.FCRF, the period-average annual rate, matched to each observation’s year. That’s an average, not a snapshot: it smooths a full year of currency movement, and lags the spot rate by design. A currency that weakened sharply in the second half of a year won’t show that weakness fully in our conversion until the following year’s average catches up.

StreetStats makes the opposite trade-off for its headline figure, converting at the current exchange rate. Its Global M2 rises or falls with the dollar in real time. Its “Global Total (No FX)” variant holds the exchange rate at a three-year average instead, specifically to separate money creation from exchange-rate effects. Over the three months to June 30, 2026, the two versions diverged. The dollar-denominated total grew 1.54% (z=-0.12). The constant-rate total grew 1.15% (z=-0.87) — a 0.39-point gap on the same underlying money.

That gap is worth taking apart, because it doesn’t point where the obvious indicator does. Weight the four local-currency three-month changes StreetStats publishes by its own June 2026 country totals and the result is 1.14% — its constant-rate 1.15%, within a rounding step. So the whole 0.39 points is currency, not money creation. Yet StreetStats also reports the DXY dollar index up 1.23% over that same quarter, and calls the move “relatively small” (checked 2026-08). A stronger dollar should hold the USD-denominated total below the constant-rate one. Here it did the reverse, because DXY doesn’t track the yuan, and China is 51.3% of StreetStats’ own four-economy total ($52,986B of $103,276B, June 2026).

That’s exactly why MacroMicro and StreetStats each publish a constant-FX version as its own document, not a footnote: MacroMicro’s fixed-exchange-rate series and StreetStats’ “Global Total (No FX)”, both checked 2026-08. We publish no equivalent, and the reason is the same method question this whole page is about. Our conversion rests on the World Bank’s PA.NUS.FCRF, a period-average annual rate. We hold no historical monthly FX series. Holding a rate fixed across a monthly aggregate of 159 economies requires one, so a constant-FX total from us would rest on a rate we invented rather than a rate we sourced. For that view — the “global liquidity index” version of the question — use StreetStats’ “Global Total (No FX)” (checked 2026-08) and read the four levers above against it. Knowing which lever a chart moved matters more than owning a copy of every chart.

The Mixed-Vintage Problem: Every World Figure Is a Mosaic

Our 159 summed observations run from 2008-05 (Panama) to 2026-06. Only 20 of those rows actually read 2026-06. Eighty-five fall somewhere in 2026, and ten predate 2020. A full breakdown of the spread lives on the world-total page. The point for this page is narrower. A single “as of” date attached to any world total describes that total’s freshest row, not its whole composition.

The FX conversion carries a second, quieter version of the same problem. A period-average annual rate means a “2026-06” observation is converted using the full-2026 average rate, not the June spot rate. The money figure and the exchange rate applied to it don’t share one vintage, even on a single row. That’s a deliberate trade-off for stability, stated here rather than left for a reader to discover.

StreetStats’ own headline number shows the mosaic in miniature. Three economies read as of June 2026, Japan as of July 2026 — summed into one figure dated to the day StreetStats last updated the page. A labeled mixed-date total beats no total — the same choice every world figure on this page, ours included, has to make.

Global M2, the Liquidity Cycle, and Bitcoin

A common trading thesis rests on a risk-asset correlation: global M2 leads Bitcoin specifically, after a lag. The published leads don’t agree either. newhedge.io runs a “Bitcoin vs Global M2 10-Week Lead” chart (checked 2026-08), while the r/Bitcoin thread below it argues over a three-month one. One commenter there set out the mechanism (new money takes time to reach risk assets, so M2 moves first), then closed the door on it himself: “Correlation ≠ causality so this is just one of many metrics that point in the ‘number go up’ direction” (u/SgtMicky, r/Bitcoin, 2025-05-13). Another asked the question the charts skip: “Can anyone explain how the 3 month lead is calculated? Is it estimated?” (u/manugd, r/Bitcoin, 2025-05-13). We hold no Bitcoin or asset-price data ourselves, so we can’t test any specific lead — 10 weeks, three months or otherwise. We won’t attach a number to it we can’t stand behind. What we can say: the four-versus-159 country-set question applies to any “global M2” chart making that claim. Check which aggregate it’s using before trusting the correlation. The full M2-versus-Bitcoin comparison covers those correlation claims on its own page.

The Level and Year-on-Year Views, and the One We Don’t Publish

This page carries no ranking of its own. Two documents do, one metric each, each with its own dataset. The level view carries the $144.41 trillion total and ranks the economies inside it by USD value, every row dated. The year-on-year view ranks the same set by growth instead — the “is global M2 increasing” question, without the level’s dollar-sign noise. Its headline is the 6.51% value-weighted rate across the 157 summed economies that carry a year-earlier comparison. There is no third, constant-FX view, for the annual-rate reason given above.

For the plain-English total, see how much money is in the world. For every row’s source, see the 185-economy methodology. For the full ranking, see every country compared.

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