expanded by Freeman (1994), who considered 51 countries and relied on indirect productivity indicators, such as the average schooling of the population, and its urbanization rate. According to Freeman's results, a third of the variance in average wages in manufacturing could be ascribed to those indirect productivity indicators, and another third to differences in purchasing power parities. Using a broader sample, Rodrik (1999) showed that a strong relationship existed between wages and productivity in the manufacturing sector. Rodrik also showed that the outcome depended on the political regime, as wages are higher (other things equal) in more democratic countries.

While these studies do not directly deal with globalization, they all suggest that its effect on wages should be positive. To begin with, they all reveal that a strong association exists between wages and productivity at the country level. It is generally accepted that productivity grows faster in more open economies (see, for instance, Sachs and Wamer, 1995; and Sala-i-Martin, 1997). Therefore, wages can be expected to grow faster too. In addition, both Freeman and Rodrik include the ratio of foreign trade to GDP among the explanatory variables in their regressions. The coefficient multiplying this ratio reflects the direct impact of openness on wages, not its indirect impact through productivity levels. That coefficient turns out to be positive in all the specifications in both studies. It is statistically insignificant in the study by Rodrik, but highly significant in the study by Freeman.

The hypothesis that wages grow faster in more open economies is supported by figure 1, which was constructed using wage data from dozens of occupations in 70 countries. The wage data were originally collected by the International Labor Office through its October Survey, and subsequently standardized in a comparable format by Freeman and Oostendorp (2000). The October Survey, conducted since 1924, has rarely been used for research purposes, because the raw data in it suffer from comparability problems. Occupations (e.g., bricklayer, teacher) are defined quite precisely. But depending on the country and occupation, the raw data may refer to wages or to earnings. The reported figure may be minimum, a maximum, an average, a median or other indicators. Figures can also refer to men, women or both. And the reference period can be the hour, the day, the week or the month, among others. Freeman and Oostendorp recalibrated these data so as to make them comparable, by assuming a stable relationship between different wage measures. The data used in figure 1 correspond to the average monthly wages of men, in current U.S. dollars.

The 70 countries considered in figure 1 are classified in three groups, using the approach proposed by Dollar and Kraay (2001). The first group, which is by far the largest, is made of countries that are not yet fully integrated with international markets. The two other groups, much smaller, are composed of industrial countries, which have been open for quite a long time, and of "recent" globalizers. These groups comprise 14 and 13 countries respectively. Figure 1 reports the growth rate of the average wage between the 1980s and the 1990s, for the largest common set of occupations across all 70 countries. This growth rate is highest for the recent globalizers, and lowest for the nonglobalizers. Therefore, the results reported in figure 1 suggest that openness is good for workers.

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