THE FACT THAT COULD NOT BE

Looking at different regions within countries clearly reduces the number of potential things going on at the same time that might obscure the effects of trade; there is usually a single policy regime, a shared history, and common politics, making the comparisons more convincing.

In the Stolper-Samuelson view of the world, there is one unique wage for every worker with the same skills. A worker’s wage does not depend on his sector or region, but only on what he brings to the table. This is because the steelworker in Pennsylvania who loses his job because of foreign competition should move immediately to wherever he can find a job, to Montana or to Missouri, to plating fish or making fisher-plates. After brief transitions, all workers with the same skills will earn the same.

If this were true, then the only legitimate object of comparison for learning about the impact of trade would be the entire economy. We would not learn anything by comparing workers in Pennsylvania with workers in Missouri or Montana because they would all have the same wage.

Rather paradoxically, therefore, if one believes the assumptions of the theory, it is almost impossible to test it, since the only impact one observes is what happens at the country level, and we just demonstrated the many pitfalls of cross-country comparisons and country case studies.

However, as we saw with migration, labor markets tend to be sticky. People do not move even when labor market conditions would suggest they ought to, and as a result wages are not automatically equalized across the economy. There are in effect many economies inside the same country and it is possible to learn a lot by comparing them, as long as the changes in trade policy affecting these subeconomies are not all the same.

One young economist, Petia Topalova, who was a PhD student at MIT at the time, decided to take this idea seriously, and to start from the premise that people may be stuck, both in a place and in a line of trade. In an important paper, she studied what happened in India after the massive trade liberalization of 1991.²⁰ It turned out that even though we think of “India liberalizing,” there were very different changes in trade policy that affected different parts of the country. This is because, even though eventually all the tariffs were brought down to more or less the same level, since some industries were much more protected than others to start with, there were much bigger reductions in tariffs for some industries. Moreover, India has over six hundred districts that differ enormously in the kinds of businesses they are home to. Some are mainly agricultural; others have steel plants or textile factories. Since different industries fared differently, the liberalization led to very different reductions in tariffs in different districts. Topalova constructed, for each Indian district, a measure of how much it was affected by liberalization. For example, if one district mainly produced steel and other industrial manufacturing products, whose tariff dropped from almost 100 percent to about 40 percent, she would say this district was strongly affected by liberalization. If another district just grew cereals and oilseeds, whose tariff essentially did not change, it was almost unaffected.

Using this measure of exposure, she looked at what happened before and after 1991. The national poverty rate dropped rapidly in the 1990s and 2000s, from about 35 percent in 1991 to 15 percent in 2012.²¹ But, against this rosy backdrop, greater exposure to trade liberalization clearly slowed poverty reduction. Contrary to what the Stolper-Samuelson theory would tell us, the more exposed a particular district was to trade, the slower poverty reduction was in that district.

The reaction to her findings in the economics profession was surprisingly brutal. Topalova ran into a barrage of very unfriendly comments suggesting she had the wrong answer, even if her methods were correct. How could trade actually increase poverty? The theory tells us trade is good for the poor in poor countries, so her data had to be wrong. Blackballed by the academic elite, Topalova finally took a job at the IMF, which, somewhat paradoxically given the IMF had pushed for the massive liberalization in the first place, was more open-minded about her research than the academic community.

Topalova’s paper was also rejected by the top economic academic journals despite the fact that it eventually inspired a literature dedicated to the debate. There are now many papers applying Topalova’s approach in other contexts and, incidentally, finding the same results in Colombia, Brazil, and, as we will see below, eventually the United States.²³ It was only several years later that she got some measure of vindication from academic economists when her findings won the Best Paper Award from the journal in which the paper had been published.