Trade Wars Are Class Wars: How Rising Inequality Distorts the Global Economy and Threatens International Peace
Matthew C. Klein, Michael Pettis
A provocative look at how today’s trade conflicts are caused by governments promoting the interests of elites at the expense of workers Trade disputes are usually understood as conflicts between countries with competing national interests, but as Matthew C. Klein and Michael Pettis show in this book, they are often the unexpected result of domestic political choices to serve the interests of the rich at the expense of workers and ordinary retirees. Klein and Pettis trace the origins of today’s trade wars to decisions made by politicians and business leaders in China, Europe, and the United States over the past thirty years. Across the world, the rich have prospered while workers can no longer afford to buy what they produce, have lost their jobs, or have been forced into higher levels of debt.
Award History
1 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| Lionel Gelber Prize: International AffairsMajor | 2021 | Winner | Secondary source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
These suggestions did not meet the normal display threshold and are more likely to be wrong.
- China40%
- Europe38%
- United States38%
03 Suggested argument
Contemporary trade wars are often driven less by national interests than by domestic political choices that serve elites at the expense of workers and retirees, undermining economic welfare and international peace.
Model confidence 72%
04 Reading orientation
45 / 100 academicTrade / academic crossover
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 74%.