Burgernomics Full Research Note

Every six months, The Economist publishes a spreadsheet of hamburger prices, and every six months, economists, journalists, and policymakers actually pay attention to it. Earlier this year, the gap between Big Mac prices in the U.S. and China got cited directly in American tariff talks with Beijing. This past summer the index turned 40, and it’s still doing more or less the job it was built for.

01 — The BasicsWhat It Is, How It Works

In 1986, an Economist journalist named Pam Woodall needed a simple way to explain purchasing power parity (PPP) — the theory that exchange rates should adjust, over time, so an identical basket of goods costs the same everywhere once you convert into one currency. Real PPP baskets run into the thousands of items and are a nightmare to compare across countries. Woodall’s fix was to swap the basket for one near-identical product sold in around 120 countries: the McDonald’s Big Mac.

It’s a surprisingly good stand-in, as these things go. A Big Mac is standardized (with the odd local swap, like chicken instead of beef in India), it blends tradable ingredients with local labor and rent, and its global footprint gives the comparison a reach that few other single products could match.

The calculation is simple enough to do on the back of a napkin. Take a Big Mac’s local price, divide it by the U.S. price, and you get the exchange rate that would hold if the two currencies were at parity. Compare that to the actual market rate, and the gap tells you whether a currency looks over- or undervalued.

That’s the whole calculation. No regressions, no adjustments — just one price ratio held up against another.

As of July 2026, Switzerland and Uruguay sit at the overvalued extreme; Taiwan, India, and Indonesia sit at the undervalued one, with burgers running less than 40% of the U.S. price once converted. That lines up with reporting around the index’s 40th anniversary, which flagged Taiwan’s currency as undervalued by more than 60% on the raw measure.

02 — The TheoryPurchasing Power Parity and the Law of One Price

The Big Mac Index rests on the law of one price: in a frictionless market, with no shipping costs, taxes, or trade barriers, an identical good should sell for the same price everywhere once you express it in a common currency. If it doesn’t, arbitrage — buy where it’s cheap, sell where it’s dear — should close the gap over time.

PPP just applies that same logic to a whole price index instead of a single good. In practice it behaves more like a long-run tendency than a hard rule. Line up Big Mac–implied PPP against the far more comprehensive Penn World Table measure for the year 2000, and the two are correlated at 0.73 — a decent showing, considering one measure is built on hundreds of expenditure categories and the other is built on a sandwich.

Across the full run of Economist surveys from 1986 to 2003, though, straying from strict PPP was the norm rather than the exception. Only 8.7% of readings sat within 5% of parity, and just 17.9% within 10%. Some of the gaps were both large and stubborn — the Swiss franc overvalued by 70% against the dollar in 2003, the Chinese yuan undervalued by 56% that same year.

03 — The MechanismWhy It Deviates: The Balassa–Samuelson Effect

If departures from PPP were just noise, they’d cancel out over time. They don’t. Certain currencies sit persistently undervalued or overvalued for years on end — the Australian dollar and Thai baht undervalued through most of the 1990s and 2000s; the British pound and Danish krone overvalued for roughly the same stretch.

The leading explanation is the Balassa–Samuelson effect, sometimes called the Penn effect. Rich countries have more productive export sectors, and because workers can move freely between a country’s tradable and non-tradable industries, high wages in manufacturing end up pulling wages up everywhere else too — including at the local McDonald’s, which isn’t competing with anyone overseas.

Just how much? Parsley and Wei (2007) rebuilt the Big Mac’s cost structure ingredient by ingredient (as reported in Clements et al., 2012) and found labor alone accounts for 45.6% of the total — more than beef, cheese, and bread combined.

A Big Mac’s ingredients are tradable. By the time it reaches the counter, labour and rent dominate the price.

The wage numbers make the case better than any theory could. A McDonald’s crew worker earned $6.50 an hour in the U.S. in 2000, against $0.42 an hour in China. By 2026, Swiss fast-food workers were earning something like $28 an hour, versus about $15 in the U.S. — a gap that alone accounts for much of the price difference between a Swiss and an American Big Mac. None of that is currency misalignment. It’s the wage gap, wearing a currency costume.

04 — The FixThe GDP-Adjusted Index

In 2011, The Economist started publishing a second version of the index that tries to strip the Balassa–Samuelson effect out — by fitting a regression line between local Big Mac prices and GDP per person, then checking how far each country’s actual price sits above or below what its income alone would predict.

For years, the magazine never quite explained the math clearly enough. A 2017 paper by O’Brien and Ruiz de Vargas cleared up the main point of confusion: the published “adjusted” percentage is a currency’s misvaluation against a basket of every currency in the survey, not against the dollar specifically. Their worked example, using July 2015 data, makes the distinction concrete:

Read the published percentages as bilateral figures and you’ll get it backward. Whether the adjustment is worth the trouble is a fair question, though — and the answer, tested against actual two-year currency moves for 36 currencies between 2011 and 2013, is that the GDP-adjusted index landed closer to the real outcome 73.7% of the time, with a noticeably smaller average error (22.5% against 34.2% for the raw index).

A technical footnote

A 2025 paper by Kunkler pushes this a step further, and it’s worth a moment even if you’re not planning to run the numbers yourself: every one of these figures depends on which currency you use as the reference point. Swap the dollar for a basket of only developed-market currencies, and the “correct” figure for the dollar’s overvaluation drops from around 36% to around 9%. Which currencies you’re comparing against moves the answer almost as much as the method you use.

05 — Other FrictionsTrade Barriers and Market Pricing

Even a flawless PPP measure would diverge from reality for reasons that have nothing to do with currencies at all.

Trade barriers. Japan’s beef tariffs ran as high as 70% before 1991, which inflated local Big Mac prices regardless of what the yen was doing.

Taxes. When Canada introduced a 7% national sales tax in 1991, its Big Mac price rose to match — narrowing the apparent undervaluation of the loonie without the two economies actually moving any closer to real parity.

Pricing to market. McDonald’s doesn’t always pass exchange-rate swings straight through to the till. It charges whatever the local market will bear.

06 — Real WorldThe China Yuan Debate

No currency gets more attention on this index than the yuan, which has read as undervalued against the dollar in every single survey since the early 1990s. As of July 2026, that gap stood at around 37% on the raw measure.

This split between the two lines is exactly what keeps the “currency manipulator” argument alive. On the raw index, the $5.79-versus-$3.52 U.S.–China Big Mac gap was cited in a 2025 U.S. trade policy memo as evidence for tariff action. Once the GDP adjustment accounts for China’s lower income level, though, the picture moves a lot closer to fair value — sometimes flipping entirely. Some economists push back harder still: a rival “Mini Mac Index,” built on iPad minis (which, unlike burgers, can actually be shipped across a border and resold), put the yuan’s undervaluation at just 3.7% — a fraction of the Big Mac figure.

07 — When the Index Becomes the StoryArgentina and Currency Crises

In 2011, The Economist pointed out that Argentina’s Big Mac inflation — 19% a year — was running far ahead of the government’s official rate of 10%, the widest such gap of any country in the survey. Reporting afterward suggested Argentina’s own commerce secretary had pressured local franchises to keep Big Mac prices artificially low, specifically to make the country’s reading look better than it was. Once international scrutiny made that too costly to keep up, prices jumped 26% in mid-2012.

As a predictor of currency crises, the raw index has a pretty poor track record. Across five historical crises — Mexico in 1994, Asia in 1997, Russia in 1998, Brazil in 1999, Argentina in 2002 — the local currency usually read as undervalued, not overvalued, right before the crash. Argentina’s 2002 devaluation is the one clear exception: once the dollar peg broke, the peso snapped from near-parity to a 68% undervaluation within a single survey, which says less about the index’s predictive power and more about how slowly local prices catch up to a sudden currency shock.

08 — The ResearchTwo Academic Verdicts on the Bias

A biased-but-workable signal. A University of Western Australia study by Clements, Lan, and Seah ran the most thorough academic stress-test of the index to date, drawing on every Big Mac price The Economist published for 24 major currencies between 1994 and 2008 — 360 country-year observations in total.

What they found was a bias that’s both real and oddly stable. Mispricing was statistically significant in 20 of the 24 currencies; only Argentina, Chile, Japan, and South Korea couldn’t be told apart from “correctly priced” across the full sample. What’s more striking is that the direction of the mispricing barely budged from year to year — the Australian dollar, Chinese yuan, Hong Kong dollar, Malaysian ringgit, Polish zloty, Russian rouble, Singapore dollar, and Thai baht were undervalued in every single year from 1994 to 2008; the British pound, Danish krone, and Swiss franc were overvalued in every year. A formal test of whether one year’s mispricing predicts the next produced a chi-square statistic of 211.9, against a 5% critical value of just 3.8 — about as decisive a rejection of “these are independent readings” as you’ll find, and the dependence holds out to roughly a 12-year horizon.

A bias this consistent can actually be corrected for, and that’s where the index earns its keep. A “bias-adjusted” version — one that tracks a currency’s mispricing against its own historical average, rather than the raw number at face value — shows real mean reversion, strongest at a five- to six-year horizon, with half-life estimates running from about 3.5 to 7.3 years depending on the specification. Tested against the industry-standard “random walk” benchmark, which just forecasts no change at all, the raw index loses at every horizon from one to fourteen years. The bias-adjusted version flips that: it beats the random walk at every horizon beyond a year.

Despite enormous analytical effort, no model of currency direction has reliably beaten a coin toss. — Alan Greenspan, 2004, as cited in Clements, Lan, & Seah (2012)

Set against that bar — and for the cost of well under $10 a year in data — the bias-adjusted index earns its place as a genuine, cheap forecasting tool. The paper also traces how a gap closes once it does. Setting aside four economies with major hyperinflation or currency-redenomination episodes during the sample period (Argentina, Brazil, Poland, Russia), it’s the exchange rate that does almost all of the adjusting, not years of elevated inflation.

Interest in the underlying idea has grown to match. Tracking business-press coverage, Clements, Lan, and Seah found mentions of “purchasing power parity” growing roughly 25% a year across three decades, and mentions of the “Big Mac Index” specifically growing roughly 32% a year — a growth rate matched among major economic topics only by “foreign direct investment.”

A caution on how fragile that “significance” can be

Fujiki and Kitamura (2003) took The Economist’s full 1986–2002 dataset — 34 economies, 406 observations — and tested whether PPP holds once you control for the Balassa–Samuelson effect. Their answer: it depends, a lot, on which statistical model you use, which years you include, and which countries you treat as outliers. The full unbalanced panel rejects the standard PPP restriction outright under a pooled model; a random-effects model comes closer to supporting it, but even that conclusion flips once Russia’s 1998 crisis data or Argentina’s 2002 currency-board collapse get added or dropped.

Put the two papers together and they land in roughly the same place, just from different directions: the raw index overstates its own precision, careful correction recovers something real, and that something is more fragile — and more dependent on how you slice the data — than any single headline number lets on.

09 — CaveatsLimitations, in Brief

One product, not a basket. A single item can’t replicate a full price index.

Uneven coverage. McDonald’s has limited African presence, which is why the regional “KFC Index” exists.

Local status effects. McDonald’s is a budget option in some markets and a bit of a treat in others.

Corporate pricing strategy. High-volume, low-margin in one country; higher-margin in the next.

Slow price adjustment. Local prices tend to lag exchange-rate shocks by months, sometimes years.

10 — The Genre It SpawnedBurgers Have Imitators Too

The KFC Index (Africa), the Mini Mac Index (iPad minis, courtesy of the Council on Foreign Relations), the Starbucks Tall Latte Index (Wall Street Journal, 2004), and Bloomberg’s IKEA Billy Bookcase Index have all tried to patch one weak point or another in the original. None has really displaced it. Forty years on, the Big Mac is still the reference point every imitator gets measured against.