US Loses Up to $26 Billion in Annual Tariffs to Transshipped Goods, White House Reports

The United States is losing an estimated $19 billion to $26 billion in annual tariff revenue from goods illegally transshipped through third countries to evade U.S. import duties, according to a report released by the White House on Thursday. The document primarily identifies goods originating from China as the source of this trade circumvention.

Key Report Findings

The report, authored by White House trade and manufacturing adviser Peter Navarro, bases its tariff loss estimate on a "central case estimate" that $75 billion worth of goods are being transshipped into the U.S. annually. The document notes a wider potential range for the value of these goods, from $34 billion to $303 billion per year, based on various private sector and government estimates.

According to the report's central case, this level of tariff evasion displaces an estimated 450,000 U.S. jobs, both direct and indirect. The practice often involves minimally processing, relabeling, or repackaging Chinese-origin components in one of approximately 40 countries identified as having an elevated risk for facilitating illegal transshipments.

Shifting Trade Patterns

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The report argues that a sharp increase in imports from countries like Mexico and Vietnam correlates with a decline in direct imports from China, suggesting transshipment is a significant factor. U.S. Census Bureau data cited shows that imports from China fell to a 16-year low of $308.7 billion in 2025 following the implementation of U.S. tariffs. The report also noted that routing Chinese products through Mexico or Canada could potentially eliminate duties entirely under existing trade agreements.

As of the report's release, the Chinese embassy in Washington had not responded to a Reuters request for comment on the allegations.

Enforcement and Technology

To combat this issue, U.S. Customs and Border Protection (CBP) is deploying artificial intelligence tools to better detect suspected transshipments, the report states. These systems use learning models to analyze container markings, packaging patterns, and X-ray imaging to identify discrepancies between the declared and actual cargo. This technological push aims to enhance enforcement and recover lost tariff revenue.