where ̈<sup>i</sup> t<sup>isa(timeandcountrydependent)binaryvariableequaltooneifthereis</sup> no data on the immigrants’ skill in country i, and equal to zero otherwise.

Shortcomings. Our methodology is imperfect and could be improved in many ways. However, we believe that our estimates can be reasonably used to examine the changes in the international distribution of migration rates, to test for the (push and pull) determinants of skilled migration. Let us discuss some shortcomings.

A ...rst limit of our analysis is that the set of receiving countries is restricted to OECD nations. Generally speaking, the skill level of immigrants in non-OECD countries is expected to be very low, except in a few countries such as South Africa (1.3 million immigrants in 2000), the Gulf countries (9.6 million immigrants in Saudi Arabia, United Arab Emirates, Kuwait, Barhain, Oman and Qatar), some Eastern Asian countries (4 million immigrants in Hong-Kong and Singapore only). According to their census data, about 17.5 percent of adult immigrants are tertiary educated in these countries (17 percent in Bahrain, 17.2 percent in Saudi Arabia, 14 percent in Kuwait, 18.7 in South Africa). Considering that children constitute 25 percent of the immigration stock, we estimate the number of educated workers at 1.9 million in these countries. The number of educated people in the rest of the world lies between 1 and 4 million (if the proportion of educated immigrants among adults lies between 2.5 and 10 percent). This implies that focusing on OECD countries, we should capture a large fraction of the world-wide educated immigration (about 85 percent). Nevertheless, we are aware that by disregarding non-OECD immigration countries, we probably underestimate the brain drain for a dozen of developing countries (such as Egypt, Sudan, Jordan in the neighborhood of the Gulf States, Namibia, Zimbabwe and other countries which send emigrants to South Africa, etc.).

Another point is that, by focusing on census and register data, our methodology does not capture illegal immigration for which systematic statistics by education level and country of origin are not available. Because illegal immigrants are mostly less educated, we obviously overestimate the average level of education of the immigrant population. Nevertheless, this limit should not signi...cantly distort our estimates of the migration rate of highly skilled workers.

Only taking into consideration the population aged 25 and over maximizes the comparability of the immigration population with the Barro and Lee data on educational attainment in source countries. It also excludes a large number of students who emigrated to complete their education. We cannot control for graduate students aged 25 and over completing their schooling<sup>7</sup> . Note that, in a limited number of OECD countries identi...ed below, we are unable to distinguish between young and adult immigrants.

A related problem is that we have no information on the age of entry. It is

> 7Carrington and Detragiache (1998) used data from the Institute of International Education to estimate the number of graduate students completing their schooling in the United States. We consider that some of these students aged 25 and over receive grants and can be considered as workers (researchers).

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