As far as immigration is concerned, the ’Worst-case’e¤ect is essentially equal to zero for all countries whereas the ’Best-case’e¤ect is positive everywhere. The largest gains are obtained for Singapore (+3.7%), Australia (+2.6%), Canada (+1.9%) and the UK (+1.7%). The opposite picture emerges with regard to emigration. The ’Best-case’e¤ect is essentially equal to zero for all countries whereas the ’Worst-case’e¤ect is negative everywhere. The largest losses are obtained for the UK (-1.3%), Portugal (-1.1%), Poland (-0.9%), Singapore and South Africa (-0.8%), Greece and Canada (-0.7%). For EU15 as a whole the best case scenario for immigration implies a gain around 0.5% of non movers’wages. On the other hand the worst-case scenario implies a loss from emigration also around -0.5% of non movers’ wage.

# 5 Simulated e¤ects: extensions wage

The parametrization of our model re‡ects di¤erent results on the impact of immigration, schooling externalities, and the substitutability between highly educated and less educated workers. However our analysis of the wage e¤ects of immigration can be seen as somewhat optimistic. First, our database may not capture illegal immigration to the OECD countries, which is widely believed to be low-skill intensive. Second, it assumes that highly educated immigrants are homogeneous across origin countries and contribute the same skills as native highly educated workers to the destination labor markets. Finally, we did not include yet the potential congestion e¤ects of immigration on the labor market of receiving countries, nor did we examine the short-run e¤ects accounting for sluggish adjustment of physical capital to immigrants. This section deals with those issues and extends our robustness analysis.

## 5.1 Accounting for undocumented immigrants

By focusing on census data, our database fails to record undocumented immigrants in most countries, for whom systematic statistics by education level and country of birth are not available. An exception is the United States where demographic evidence indicates that most residents, regardless of legal status, are identi...ed in the census. However, other host countries provide no accurate data about the size and educational status of undocumented migrants. In their recent report, Kovacheva and Vogel (2009) estimate the size of irregular migrant populations in the European Union and in selected member states. Annex 1 of their paper provides lower and upper bounds for the proportion of undocumented in the immigrant population in 2002.<sup>13</sup> Data are available the for the 10 European countries in our sample - Belgium (11-18%), France (9-15%), Germany (14-20%), Greece (42-63%), Italy (53-75%), Netherlands (11-26%), Portugal (18-89%), Spain (8-29%), Sweden (1.7-2.5%), and the U.K. (11-21%).

Figure 6 gives the e¤ect of immigration on average wages when illegal immigration is taken into account where the ’Lower Bound’and ’Upper Bound’scenarios use the proportions listed above. Although there may be some instances of highly skilled undocumented migrants (such as those overstaying their H-1B visas in the United States), the majority of undocumented migrants are believed to be low-skilled. Hence, we make the two extreme assumptions that

> 13See http://irregular-migration.hwwi.net/Stock_estimates.6170.0.html.

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