Performance of migrants

In many developed countries, racial and ethnic minorities are paid, on average, less than the native white majority. While racial wage differentials are partly the result of immigration, they also persist for racial minorities of second and further generations. Eliminating racial wage differentials and promoting equal opportunities among citizens with different racial backgrounds is an important social policy goal. Inequalities resulting from differences in opportunities lead to a waste of talent for those who cannot reach their potential and to a waste of resources if some people cannot contribute fully to society.

Refugee migration has increased considerably since the Second World War, and amounts to more than 50 million refugees. Only a minority of these refugees seek asylum, and even fewer resettle in developed countries. At the same time, politicians, the media, and the public are worried about a lack of economic integration. Refugees start at a lower employment and income level, but subsequently “catch up” to the level of family unification migrants. However, both refugees and family migrants do not “catch up” to the economic integration levels of labor migrants. A faster integration process would significantly benefit refugees and their new host countries.

There is increasing global competition for high-skilled immigrants, as countries intensify efforts to attract a larger share of the world's talent pool. In this environment, high-skill immigrants are becoming increasingly selective in their choices between alternative destinations. Studies for major immigrant-receiving countries that provide evidence on the comparative economic performance of immigrant classes (skill-, kinship-, and humanitarian-based) show that skill-based immigrants perform better in the labor market. However, there are serious challenges to their economic integration, which highlights a need for complementary immigration and integration policies.

Over recent decades, Western countries have admitted many immigrants from non-traditional regions (e.g. Philippines, India, China), which has coincided with poor economic integration. Language proficiency is an important determinant of economic integration; in addition to being a component of human capital, it plays a key role in facilitating the transmission of other components of human capital. Examining the strengths and weaknesses of objective and subjective measures of language proficiency is crucial for good integration policy, as is understanding the relationship between these measures and earnings, a key indicator of economic integration.

Immigrants are widely perceived to be highly entrepreneurial, contributing to economic growth and innovation, and self-employment is often viewed as a means of enhancing labor market integration and success among immigrants. Accordingly, many countries have established special visas and entry requirements to attract immigrant entrepreneurs. Research supports some of these stances, but expectations may be too high. There is no strong evidence that self-employment is an effective tool of upward economic mobility among low-skilled immigrants. More broadly prioritizing high-skilled immigrants may prove to be more successful than focusing on entrepreneurship.

Immigrants contribute to the economic development of the host country, but they earn less at entry and it takes many years for them to achieve parity of income. For some immigrant groups, the wage gap never closes. There is a wide variation across countries in the entry wage gap and the speed of wage assimilation over time. Wage assimilation is affected by year of entry, immigrant skill, ethnicity, and gender. Policies that facilitate assimilation of immigrant workers provide support for education, language, and employment. Such policies can also reduce barriers to entry, encourage naturalization, and target selection of immigrants.

Canada, the US, and most Western countries are looking to STEM (science, technology, engineering, and mathematics) immigrants to boost innovation and economic growth. Canada in particular has welcomed many STEM immigrants over the past quarter of a century. In the US, there is an ongoing debate about whether the H–1B visa program is being used effectively to attract more STEM immigrants. Interestingly, significant differences exist between the two countries in earnings and likely the innovation activity of highly educated immigrants, which highlights the likely role of immigration policy in determining such outcomes.

Immigration is one of the most important policy debates in Western countries. However, one aspect of the debate is often mischaracterized by accusations that higher levels of immigration lead to higher levels of crime. The evidence, based on empirical studies of many countries, indicates that there is no simple link between immigration and crime, but legalizing the status of immigrants has beneficial effects on crime rates. Crucially, the evidence points to substantial differences in the impact on property crime, depending on the labor market opportunities of immigrant groups.

The use of anonymous job applications (or blind recruitment) to combat hiring discrimination is gaining attention and interest. Results from field experiments and pilot projects in European countries (France, Germany, the Netherlands, and Sweden are considered here), Canada, and Australia shed light on their potential to reduce some of the discriminatory barriers to hiring for minority and other disadvantaged groups. But although this approach can achieve its primary aims, there are also important cautions to consider.

Discrimination is a complex, multi-factor phenomenon. Evidence shows widespread discrimination on various grounds, including ethnic origin, sexual orientation, gender identity, religion or beliefs, disability, being over 55 years old, or being a woman. Combating discrimination requires combining the strengths of a range of anti-discrimination policies while also addressing their weaknesses. In particular, policymakers should thoroughly address prejudice (taste-based discrimination), stereotypes (statistical discrimination), cognitive biases, and attention-based discrimination.