Theoretical frameworks are essential for deciphering the complexities of our world. They enable us to interpret our surroundings and make informed predictions about future events. Consider theory as a pair of glasses: the right pair enhances clarity, while the wrong one distorts reality. No glasses? You’re left squinting at the blurry chaos of life.
Currently, one of the most pressing issues in economic discourse is the trade policy promulgated by the Trump Administration, which appears to be anchored in fundamentally flawed theoretical assumptions—or worse, a lack of any coherent theory at all. To add insult to injury, the administration seems oblivious to basic, verifiable facts, such as Trump’s overinflated assertion regarding the U.S. trade deficit with China being $1 trillion, when in reality it is closer to $300 billion. I must admit, I would have more confidence in central planners if they could at least nail the fundamentals.
This article aims to serve as a corrective lens, clarifying some of the prevailing misconceptions. Of course, for the die-hard True Believers, these insights may fall on deaf ears; this discussion is intended for those genuinely interested in understanding trade theory.
International trade operates under the same principles as domestic trade. Whether you’re negotiating with Bret in Boston, Brad in Baton Rouge, or Bobby in Berlin, the fundamental rules remain unchanged. Specifically, consumers operate on the margins when making buying and selling decisions. They choose to buy a good when the marginal cost of producing it exceeds the marginal benefit of purchasing it. In simpler terms, they will buy when it’s cheaper to do so and produce when it’s more economical to make it. Similarly, they will sell when the marginal cost of production is lower than the marginal benefit of selling the good, or when they can secure a higher price than the cost of production.
David Ricardo‘s foundational model of comparative advantage has consistently demonstrated its relevance across both individual and international trade contexts. While more sophisticated models have emerged (like the Heckscher-Ohlin Standard Trade Model, Stolper-Samuelson theorem, and others), we will stick to Ricardo’s simple framework, as these elaborations do not alter the core logic.
Given that individuals make decisions at the margins, we should anticipate that patterns of international trade will mirror these marginal considerations. Thus, a nation typically imports goods that it is relatively inept at producing (i.e., low-productivity goods/services) and exports what it is relatively proficient at producing (i.e., high-productivity goods/services). Furthermore, since wages correlate with productivity, we can expect lower wages in import-competing industries and higher wages in export-oriented sectors. And indeed, this is what the data illustrates.
In a report for the Peterson Institute for International Economics, J. Bradford Jensen and Lori G. Keltzer demonstrate that the majority of jobs “at risk” from trade are concentrated in sectors characterized by low productivity and wages. Conversely, sectors that exhibit the highest productivity and wages are predominantly exporters (refer to figures 4 and 7). While these data may be somewhat dated (the report dates back to 2008), I have been actively updating the statistics; the overarching trends remain unchanged.
Because trade patterns adhere to a logical framework rather than randomness, we should not expect job losses resulting from trade to be arbitrary. Protectionist advocates often imply that trade-related job losses are random, citing average wage figures, or that firms selectively offshore their most productive sectors, focusing solely on high-productivity industries. However, the reality is that job losses primarily occur in low-wage sectors, while gains happen in high-wage industries.
Consequently, any jobs “saved” through tariffs will predominantly be those low-productivity positions, potentially at the expense of more productive roles. Take the textile industry as a case study. Textile manufacturing in the U.S. faces intense competition from abroad. According to the Bureau of Labor Statistics, textile workers earn an average of $17.78/hour, which is merely 54.4% of the national average of $32.66. In contrast, oil and petroleum extraction workers—one of our key export sectors—earn an average of $28.39/hour (not including managerial roles). Tariffs may preserve some low-productivity jobs, but they often do so at the cost of higher-productivity employment opportunities. (Yes, I recognize that the industries cited are at opposite ends of the productivity spectrum, but the principle remains valid.)
As trade evolves, it’s inevitable that some textile workers may face layoffs. What are their options? Are they fated to rely on public assistance indefinitely? After all, their skills may no longer align with market demands—an issue economists refer to as “structural unemployment.” The reality is: likely not. Even low-productivity service jobs offer wages comparable to those in low-end manufacturing. For instance, food preparation workers earn approximately $17.32/hour and retail sales associates make about $17.05/hour. While this represents a decrease for former textile workers, these wages are fairly comparable. If they were not reliant on welfare while in textiles, they might not be in gainful employment in retail or food service either. This also assumes the worker doesn’t seek retraining. With new skills that meet market demands, they can actually raise their earning potential.
Life unfolds at the margins, and thus, adjustments in trade will manifest similarly. Sound theory equips us to anticipate the diverse impacts of tariffs and helps us discount unlikely outcomes.
To close, let me share a personal anecdote from my graduate studies:
While enrolled in Robin Hanson’s Law & Economics course (ECON 841), part of our assessment involved presenting an original research paper. I developed what I believed to be an exceptionally clever model. The mathematics were flawless, and the presentation was visually appealing. However, upon my presentation, Dr. Hanson posed a single question: “This is intriguing, but where’s the economics?” With that one simple query, my model crumbled. I was at a loss. The math was precise, the logical flow impeccable, but it ultimately lacked explanatory power. It boiled down to little more than a “what if?” scenario. That day, I gleaned two crucial lessons: 1) to avoid future embarrassment, I must ensure that my work is grounded in robust theory, and 2) give anyone enough assumptions, and they can substantiate any claim they desire.
Robust theory shields us from misguided perceptions. Conversely, flawed theories—regardless of their mathematical elegance or the number of esoteric symbols involved—can lead us astray.
