More Evidence China Has Surpassed Us

It turns out our GDP figures have been cooked.

The Map Still Isn’t the Territory

In a post earlier this week (China Has Surpassed Us), I wrote about how the size of China’s real economy dwarfed America’s.

Patrick Fitzsimmons’s new piece in Palladium explains why the scoreboard number misleads: GDP (especially “real value-added” by industry) is constructed in ways that can make industrial decline look like progress. It’s worth reading.

What Fitzsimmons Adds

• The stat that flatters decline. Policymakers lean on “real value-added” to claim U.S. manufacturing is near records. Fitzsimmons shows how heavy use of deflators and “quality adjustments” can create paper growth even when unit volumes and domestic content stagnate or fall.

• Why the math breaks intuition. Chain-weighting plus quality adjustments often raise today by pushing yesterday down, yielding implausible surges in “real” output for sectors like chips and autos despite weak physical throughput.

• Less glamorous gauges say otherwise. If you look at BEA real gross output, the Fed’s industrial production index, or BLS real sectoral output, U.S. manufacturing per capita is well below late-1990s/early-2000s peaks.

• Dollar rankings ≠ capacity rankings. Nominal value-added rewards higher prices and IP rents; a country producing far more units at lower prices (and with deeper domestic content) can still “look” smaller in value-added terms.

Bottom line: clever accounting ≠ the factory floor. The map brightens while the shop lights dim.

Why This Strengthens “China Is Already Bigger”

If the U.S. counts a lot of high-price services and IP rents, while China counts a lot of high-volume production at lower margins, GDP will understate China’s operational economy. Add three wedges:

1. Price-level wedge: Lower Chinese prices compress value-added per unit, masking real throughput.

2. Domestic-content wedge: U.S. “output” often embeds imported guts; China’s supply chains run deeper at home.

3. Services overweight: U.S. GDP leans on sectors that don’t translate into strategic, reproducible industrial capacity.

Stack those, and the physical economy you can see—ships launched, transformers installed, wafers started, cells produced—already tilts toward China.

Note the Turn: Early U.S. Reindustrialization Moves

As I wrote in How Trump May Have Solved America’s Fiscal Dilemma, the Trump administration has taken steps that could start bending the curve back toward capacity.

Recent reporting points to additional moves in that direction (including potential federal stakes in critical-minerals players) and even trial-balloon talk of large Chinese investment in exchange for tariff relief. None of that is a panacea—but it rhymes with the thesis that capacity, not accounting, wins.

Why Both Washington and Beijing Still Understate China

Different incentives, same obsfucation:

• Washington: Narrative management (“record manufacturing”), asset-price and dollar optics, and deflator choices that goose “real” growth all reduce pressure to make hard industrial investments now.

• Beijing: Lowering the temperature abroad (sanctions/tariff risk), keeping a lid on domestic expectations amid property and LGFV strains, and avoiding a bigger geopolitical target all argue for sandbagging headline boasts.

So you get bilateral under-reporting of the true size of China’s machine—one side to save face, the other to save room to maneuver.

How We’re Positioned

This is why one of our core themes is Reindustrialization—the picks-and-shovels of a capacity comeback.

We’ve been betting on companies positioned to benefit from a U.S. rebuild: power equipment, critical materials, heavy electrification, enabling software/hardware, and logistics. If you’re new here, this primer lays out the framework: Reindustrialization / Embodied AI / Energy.

And the payoff isn’t just theoretical. We booked several winners this week from trades aligned with these themes:

Stocks or Exchange Traded Product.

1. Iris Energy (IREN 6.84%↑). Bought for $10.45 on 11/15/2024; sold (a quarter) at $51.47 on 10/3/2025. Profit: 392%

Options

1. Calls on Clearpoint Neuro (CLPT 19.34%↑). Bought for $5.10, as part of a 3-leg combo on 9/26/2025; sold (half) for $6.50 on 10/2/2025. Profit: 28%.

2. Put spread on Joby Aviation (JOBY -3.19%↓). Entered at a net credit of $1, as part of a 4-leg combo, on 8/11/2025; exited at a net debit of $0.20 on 10/3/2025. Profit: 80%.¹

3. Put spread on Robinhood Markets (HOOD -1.91%↓). Entered at a net credit of $1.83, as part of a 4-leg combo, on 9/5/2025; exited at a net debit of $0.25 on 10/2/2025. Profit: 86%.²

4. Call spread on Centrus Energy (LEU 0.01%↑). Entered at a net debit of $3.12, as part of a 4-leg combo, on 8/13/2025; Exited at a net credit of $8 on 10/2/2025. Profit: 156%.

5. Call spread on Iris Energy (IREN 6.84%↑). Entered at a net debit of $2.14 on 7/24/2025; exited at a net credit of $8 on 10/3/2025; Profit: 274%.

6. Call spread on Tesla (TSLA -0.50%↓). Entered at a net debit of $2 on 11/4/2024; exited at a net credit of $8 on 9/29/2025. Profit: 300%.

1

On premium; profit on max risk (width of spread) was 40%.

2

On premium; profit on max risk was 50%.

No losers this week; our losers tend to cluster at big options expiration days, since we usually exit our winners before expiration.

What To Measure Next

If we want clarity, stop laundering vibes through GDP and start tracking:

• Unit counts and domestic-content shares in strategic categories (transformers, wafers, cells, ships, machine tools).

• Throughput capacity (wafer starts, GW of cells/turbines, dwt of ships) and time-to-ramp.

• Supply-chain depth onshore and time-to-recover from shocks.

• Energy and logistics baselines (refining, grid additions, port/rail ton-miles).

Bottom line: Fitzsimmons shows why the map flatters us. The visible terrain still says China’s operational economy is already larger. The encouraging news is that U.S. policy is edging toward capacity-first moves—and we’re positioned in names that stand to benefit if that continues. The faster we scale those moves—and measure the right things—the sooner our map will start to match the territory.