A white-collar worker in Shanghai earning 15,000 RMB per month may have a standard of living that far exceeds that of a middle-class individual in New York earning $6,000 per month—this phenomenon reflects two completely different economic statistical systems.

From a macro data perspective, the per capita GDP of the United States approaches $80,000, more than eight times that of China. However, when examining production-side data, the situation reverses: China's steel production is 12 times that of the US, electricity generation is 2.2 times higher, and automobile production exceeds three times. Comparisons on social media are even more intuitive—spending 2,000 RMB in China on food, clothing, housing, transportation, and medical care often provides a more fulfilling life experience than spending $3,000 in the US.

The key lies in the fact that these two countries use entirely different GDP calculation methods. China primarily uses the "production approach," which counts tangible goods and services produced. The US employs the "expenditure approach," including financial transactions, virtual rent, and various service expenditures within the GDP framework, often with overestimated pricing for these services.

The most typical example is in healthcare. US healthcare spending accounts for nearly 18% of GDP, with per capita medical costs 23 times higher than in China, yet ordinary people's medical experience and accessibility are actually worse. These inflated costs are included in economic data, pushing up overall GDP without corresponding improvements in actual living quality—essentially a numbers game rather than genuine prosperity.

This "virtual inflation" created by statistical differences is being re-examined through blockchain and cryptocurrency assets. The transparency of on-chain data and the value anchoring mechanisms may provide new reference dimensions for distorted economic measurements.