[D]o Do inequalities decrease in the poorest countries when they open up to trade? There are in fact relatively few cross-national studies on this topic, reflecting a pattern we will see over and over again – trade economists have tended not to think about how the pie is shared, despite (or perhaps because?) Samuelson’s early warning that, in rich countries at least, trade could be done at the expense of workers.

There are exceptions, but not those that inspire confidence: A recent research report by two staff members found that countries that are close to many other countries, and therefore trade more, tend to be both richer and more equal. They ignore the fact that Europe is home to many small countries that trade a lot with each other, and these countries tend to be both richer and more equal, but probably not primarily because they exchange a lot.

Another reason to be skeptical of this rather optimistic conclusion is that it goes against what we know about many developing countries. Over the past three decades, many low- and middle-income countries have opened up to trade.

Strikingly, what happened to their income distribution in subsequent years almost always went in the opposite direction of what basic Stolper-Samuelson logic would suggest. The wages of low-skilled workers, who are abundant in these countries (and therefore should have been helped), have lagged behind those of their more skilled or more educated counterparts.

Between 1985 and 2000, Mexico, Colombia, Brazil, India, Argentina and Chile all opened up to trade by unilaterally reducing their tariffs at all levels. Over the same period, inequalities increased in all of these countries, and the timing of these increases seems to relate them to episodes of trade liberalization.

For example, between 1985 and 1987, Mexico massively reduced both the scope of its import quota regime and the average duty on imports. Between 1987 and 1990, blue-collar workers lost 15% of their salary, while their white-collar counterparts earned the same proportion. Other measures of inequality have followed suit.

The same pattern, liberalization followed by an increase in the earnings of skilled versus unskilled workers, along with other measures of inequality, has been observed in Colombia, Brazil, Argentina and India. Finally, inequalities exploded in China, gradually opening up from the 1980s and finally joining the World Trade Organization in 2001.

According to the World Inequality Database team, in 1978 the poorest 50% and the richest 10% of the population both won the same share of Chinese income (27%). The two shares started to diverge in 1978, with the poorest 50% taking less and less and the richest 10% taking more and more. In 2015, the richest 10% received 41% of Chinese income, while the poorest 50% received 15% 16.

Of course, correlation is not causation. Globalization in itself may not have caused the increase in inequality.

Trade liberalizations almost never take place in a vacuum: in all of these countries, trade reforms were part of a larger reform package. For example, the most radical liberalization of trade policy in Colombia in 1990 and 1991 coincided with changes in labor market regulations that aimed to significantly increase labor market flexibility. Mexico’s 1985 trade reform took place amid privatization, labor market reform, and deregulation.

As mentioned, India’s 1991 trade reform was accompanied by the removal of industrial licensing, capital market reforms, and a general transfer of power and influence to the sector. private. China’s trade liberalization was of course the cornerstone of the massive economic reform undertaken by Deng Xiao Ping, which legitimized private enterprise in an economy where it had been virtually banned for thirty years.

It is also true that Mexico and other Latin American countries opened up exactly as China was opening up as well, and therefore all faced competition from a more labor-intensive economy. of work. Perhaps that is what has hurt the workers in these economies.

So it is difficult to show anything definitive about trade by simply comparing countries, as growth and inequality can depend on so many different factors, with trade being only one of those ingredients, or even an effect. rather than a cause. There have, however, been some fascinating national studies that cast a shadow over the Stolper-Samuelson theorem.

Examining different regions within countries clearly reduces the number of potential things happening at the same time that might obscure the effect of trade; there is usually a single political regime, a common history and a common policy, which makes the comparisons more compelling. The problem is that the central predictions of trade theory, by their very nature, encompass all markets and regions of the economy, not just those where imports come in or exports take off.

In Stolper-Samuelson’s worldview, there is a unique salary for each worker with the same skills. A worker’s salary does not depend on their industry or region, only what they bring to the table. Indeed, the Pennsylvania steelmaker who loses his job due to foreign competition must immediately move wherever he can find a job, in Montana or Missouri, to tackle fish or make fisherman’s plates. After brief transitions, all workers with the same skills will earn the same pay.

If this were the case then the only legitimate benchmark for the impact of trade would be the economy as a whole. We wouldn’t learn anything by comparing workers in Pennsylvania to workers in Missouri or Montana, because they would all have the same pay.

Rather paradoxically, therefore, if we are to believe the hypotheses of the theory, it is almost impossible to test it, since the only impact that we observe is the impact at the country level, and we have just demonstrated the many pitfalls of comparisons between countries and countries. case studies.

However, as we have seen with migration, labor markets tend to be rigid. People don’t move even when labor market conditions suggest they should, and as a result wages are not automatically equalized across the economy. There are indeed many economies within a single country and it is possible to learn a lot by comparing them as long as the changes in trade policy affecting these sub-economies are not all the same.

Petia Topalova started from the idea that people can be stuck, both in a place and in a business line. His research investigated what happened in India after the massive trade liberalization of 1991. It turned out that even though we think of “liberalization of India”, there have been very different changes in the world. trade policy that affected different parts of the country.

Indeed, even if ultimately all the tariffs were brought down to roughly the same level, since certain industries were initially much more protected than others, there were much greater tariff reductions for certain industries.

In addition, India has more than 600 districts which differ greatly in terms of types of businesses. Some are mainly agricultural; others have steel mills or textile factories. Since different industries behaved differently, liberalization has led to very different tariff reductions in different districts.

Petia constructed, for each Indian district, a measure of the extent to which it was affected by liberalization. For example, if a district produced mainly steel and other industrial manufactures, the tariff of which rose from almost 100% to around 40%, she would say that that district has been heavily affected by liberalization. If another district was just growing grains and oilseeds, the prices of which hardly changed, it was hardly affected.

Using this measure of exposure, she looked at what happened before and after 1991. The national poverty rate fell rapidly in the 1990s and 2000s, from around 35% in 1991 to 15% in 2012. But, in this optimistic context, greater exposure to trade liberalization clearly slowed down poverty reduction – contrary to what Samuelson-Stolper theory would tell us, the more exposed a particular district was to trade, the slower the poverty reduction was in this district. In a later article, Topalova also found that the incidence of child labor also declined less in the more trade-prone districts than in the rest of the country.

The reaction to these articles in the economic profession has been surprisingly brutal. Topalova encountered a barrage of very hostile questions which seemed to imply that she had the wrong answer, even though her methods were correct. How could trade really increase poverty?

Theory tells us that trade is good for the poor in poor countries, so its data must have been wrong. Blackballed by the academic elite, Topalova eventually accepted a position at the IMF, who, somewhat paradoxically given that it was they who had pushed for massive liberalization in the first place, was more open-minded about her research than university community.

Her article was also rejected by the largest academic economic journals despite the fact that it ultimately inspired a literature devoted to debate: there are now many articles applying Topalova’s approach in other contexts and, incidentally, finding the same result, in Colombia, Brazil, and as we will see below, possibly in the United States. It wasn’t until a few years later that she got some justification from academic economists when her findings won the “Best Paper Award” for the American Economic Journal.

Extracted with permission from Good Economy for Tough Times: Better Answers to Our Biggest Problems, Abhijit V Banerjee and Esther Dufflo, Juggernaut.

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