An Economist Compared Tesla’s U.S. and China Factories — and the Result Shocked Everyone

It’s not just “cheap labor.” A head-to-head look at real output, wages, and statistical blind spots reveals why “Made in China” keeps winning

Why is so much of the physical world still stamped “Made in China”?

A lot of people answer instantly: “Because labor is cheap.”

That may have been true 20 years ago. But today, China’s manufacturing output is often cited at around 30% of the global total, far ahead of the U.S. at roughly 16%. If you still think it’s only wages, you’re missing the real mechanism.

Recently, economist Weijian Shan did something straightforward: he used Tesla — one of the rare companies with near-parallel “gigafactory-style” production footprints in both China and the United States — to run a hard, physical-output productivity comparison.

The result surprised many people.

Tesla’s “Tale of Two Cities”

Tesla’s Shanghai factory and its Fremont, California factory are often described as “sibling” plants. They use similar technology and production logic, and they build the same core models (Model 3 and Model Y). That makes them unusually close to a clean “experiment” for comparing manufacturing performance across China and the U.S.

Here’s the headline comparison:

Shanghai factory

• ~20,000 workers
• Nearly 1,000,000 vehicles were produced in 2024
• ~50 vehicles per worker per year

Fremont factory

• also ~20,000 workers
• about 560,000 vehicles annually
• ~28 vehicles per worker per year

Under almost identical hardware constraints, Shanghai’s physical output per worker appears to be roughly twice Fremont’s.

The More Uncomfortable Part: The Cost Math

Now add wages:

• A Shanghai Tesla worker is cited at roughly 14,000–15,000 per year.
• A U.S. Tesla worker is cited at approximately $82,500 per year.

So you get:

• ~2× output (physical units)
• at around 17% of the wage cost

That implies the advantage isn’t just “2×.” When you combine physical productivity and wages, the labor cost-performance ratio is roughly 8× to 14×.

And the argument goes further: that advantage compounds through the supply chain — batteries, motors, components — where scale effects and ecosystem maturity can amplify the gap. The article notes that by November 2025, Shanghai had produced 5 million battery packs, highlighting how “system efficiency” matters as much as the factory line itself.

A few years ago, Tesla reportedly even transferred people from Shanghai to Silicon Valley specifically to improve efficiency.

If Tesla were a one-off, it wouldn’t prove much. But similar patterns show up in other industrial sectors.

Shipbuilding

By 2025, China is expected to hold 60%–84% of global shipbuilding orders, up from 44% in 2020.

If you compare volumes:

• China (2024): ~1,700 ships
• U.S.: fewer than five commercial ships per year

If you compare physical output efficiency (gross tonnage per worker):

• Large Chinese groups (e.g., CSSC) cited at 40 million gross tons with ~300,000 workers → 133 gross tons/worker
• A U.S. yard like Huntington Ingalls (focused more on military vessels) cited at 2–3 million gross tons with ~40,000 workers → 50–75 gross tons/worker

That’s framed as 2×–3× output per worker. Combined with wage differences, the overall cost-effectiveness gap is estimated at 7×–10×.

Steel

In 2025, China’s steel output is cited at about 955 million tons, while the U.S. is mentioned around 80 million tons. On physical output per worker, the article claims China’s integrated mills produce about 3.2× more per worker (roughly 1,000 tons vs 300–400 tons).

Even with U.S. tariff protection raising prices by ~75% (as cited in the article), the overall cost-effectiveness is argued to remain around 15×–20×.

Solar

China is cited as producing ~80% of global solar panels, with 2025 exports up 73% amid falling prices. Output per worker is framed as about 2× (China ~500 MW/person, U.S. ~250 MW/person).

By Q1 2025, U.S. capacity is cited at 51 GW, while China exceeds 1 TW. The article argues China’s TOPCon advantage over PERC further widens the gap.

Overall cost-effectiveness is claimed at 10×–15×.

Across cars, ships, steel, and solar, the core claim is consistent: in physical-output terms, China’s manufacturing labor productivity is not “low” — it’s often high, and it compounds with scale and supply-chain density.

The Weird “Productivity Paradox”

At this point, you might think: So China’s productivity must be the best in the world.

But here’s the paradox: if you pull up “official” international datasets (World Bank / IMF style comparisons), you’ll often see the opposite claim:

China’s labor productivity is only 15%–20% of the U.S.

(Old chart — use it as a rough reference.)

So what’s going on?

One side shows factory-floor output dominance. The other shows a huge “productivity gap.”

The “secret” sits in the statistics.

Productivity Is Usually Measured as Value Added, Not “Stuff Made”

International “labor productivity” is usually measured by value added rather than physical output.

A simple example: the iPhone.

Most of an iPhone’s profit — its “value added” — is captured by Apple and recorded in U.S. GDP: brand, design, R&D, marketing, distribution. The Chinese assembly operation earns only 3%–5% in thin margins.

So, on paper, you get a “manufacturer without factories” (Apple) showing enormous manufacturing value added, while the country physically assembling the product shows much less.

Some analyses argue that if you removed such “outsourced production” companies from U.S. manufacturing statistics, the reported U.S. manufacturing value added could drop by 30%–40%.

Price Distortions Matter, Too

Imagine the same car:

• In the U.S., because of tariffs, limited competition, and market structure, it sells for $45,000.
• In China’s hyper-competitive market, it sells for $35,000.

A statistician’s ledger might say:

• A U.S. worker “produced” $45,000 of output.
• A Chinese worker “produced” $35,000 of output.

Instantly, the U.S. looks far more “productive.”

But that’s not a difference in production efficiency — it’s a difference in market prices.

Why PPP Can Undervalue China’s Manufacturing Output

Economists use PPP (Purchasing Power Parity) to normalize for different local price levels. This works well for local services like haircuts or restaurant meals.

But manufacturing is globalized:

A Tesla plant in Shanghai buys chips, robots, aluminum, and equipment priced in global markets (often in dollars). And the cars it builds compete globally.

So using local cost-of-living adjustments to value globally tradable manufacturing output can artificially “press down” China’s output value in dollar terms.

PPP is good for comparing local services, but it can misfire when valuing globally competitive goods.

Why Shan’s Comparison Feels So “Unfair” — and So Revealing

This is why Shan’s approach is so blunt:

Ignore the money games. Ignore the accounting tricks. Don’t compare how much was sold for. Compare how much was physically produced.

And from that perspective, the conclusion is harsh: closing an 8×–14× cost-effectiveness gap is close to a “mission impossible” for many Western economies.

Even with large policy pushes — like the Inflation Reduction Act or the CHIPS Act — the challenge is not just that Chinese wages are lower. It’s that China’s manufacturing system is often described as:

• higher-throughput
• lower-cost
• faster to iterate
• deeply embedded in dense supply chains
• supported by infrastructure and engineering depth

That kind of gap doesn’t vanish with subsidies alone.

Meanwhile, China is also moving toward higher-value industries — AI, EVs, advanced batteries — while continuing to offshore lower-end manufacturing.

The Takeaway

China’s advantage is no longer “cheap labor.”

It’s a systems advantage built from:

• efficient labor and process discipline
• world-class supply-chain density
• mature infrastructure
• A massive engineering talent pool (China is often cited as producing far more STEM graduates than the U.S.)

So the next time you see “Made in China,” it may not mean what you think it means.

It’s not just a cost label.

It’s a story about efficiency, scale, and industrial organization — and it’s still evolving.