In the ten years predating the Great Recession, Europe received twice as many immigrants (relative to the resident population) as the US and four to five times as many as Japan (OECD 2009). The main motivation for these flows was finding a job. In the US, research related to the effects of residential concentration of migrants on their economic and social integration is longstanding (e.g. Card and Rothstein 2007, Cutler and Glaeser 1997). But in Europe, notably in southern Europe, there is a very thin scientific literature on this issue, despite the highly controversial public debate.
In new research (Boeri et al. 2015), we explore the causal effect of the residential concentration of immigrants on their employment prospects. Our analysis is based on a new and unique survey carried out in 2009 in eight cities in northern Italy that is able to identify respondents’ exact residential location and which, thanks to a sampling strategy designed ad hoc, covers both legal and illegal immigrants.
Migrants who live in areas with a large share of non-Italians are less likely to be employed, compared with immigrants who reside in areas with a lower concentration of immigrants. The reduction in employment opportunities is remarkable – a 1% increase in the share of immigrants residing in the city block reduces the probability of being employed by two percentage points.
To establish a causal link between employment opportunities and block characteristics, residential location choices should not capture unobservable factors that may influence job market prospects. For example, low-ability migrants may be forced to live in highly segregated neighbourhoods, or the availability of public transport in some neighbourhoods may facilitate employability.
To address this issue, we use an instrumental variable, notably an observable neighbourhood characteristic that explains residential location but is not directly related to employment opportunities. Specifically, we use the building structure of the city block ten years before our survey, by linking our data with the Italian population census. The ratio of residential square metres per residential building in the block is our instrumental variable – it will be high in areas with large buildings, and low in areas with detached or semi-detached houses.
Discrimination in the housing market
Our strategy relies on discrimination in the housing market – migrants face more obstacles than natives in finding accommodation. If discrimination is motivated by preferences, then it means that natives, who form the vast majority of the supply side of the market, dislike close interactions with migrants. This implies that they will be more willing to rent or sell homes in areas where close interactions between natives and immigrants are less likely to take place.
Our main result, which is identified on the subgroup of immigrants whose choice of residential location is related to discrimination in the housing market, can be summarised as follows. If the share of migrants in a block were to rise from 15% to 25%, the employment rate of these migrants would fall from 88% to as low as 68%, depending on the model specification.
There are several mechanisms that could link the share of migrants in a block to employment opportunities. First of all, residents of ‘ghettos’ can be discriminated against in the labour market. Alternatively, neighbourhoods with a high share of migrants can be viewed as ‘launching pads’ because they may be helpful in building a network that can be useful in job search. But a high share of immigrants may impose negative congestion externalities if the job market is too crowded – in that case, a large share of illegal immigrants may displace workers from the informal hiring process, the only hiring process to which illegal immigrants have access.
It’s not neighbourhood discrimination
While our data do not allow us to distinguish which particular mechanism is behind our results, our findings lead us to conclude that there is little evidence of ‘redlining’ or neighbourhood-based discrimination in the labour market, since our results do not hold for Italians. The congestion externality hypothesis is instead supported by the fact that the negative effect of a large migrant share on employment is magnified by the presence of illegal immigrants in the block.
Our results have relevant policy implications. First of all, they suggest that housing policies should be focused on reducing the concentration of immigrants in cities. A second, perhaps less obvious, implication is that illegal status, and the concentration of individuals with illegal status, may impose a very high toll on the employment prospects of both legal and illegal immigrants. Thus, keeping a large share of illegal immigrants in a country may exert negative externalities on those migrants who have legal status.
References
Boeri, T, M De Philippis, E Patacchini and M Pellizzari (2015), “Immigration, Housing Discrimination and Employment”, Economic Journal 125(586): F82–F114.
Card, D and J Rothstein (2007), “Racial segregation and the black-white test score gap”, Journal of Public Economics 91(11–12): 2158–84.
Cutler, D M and E L Glaeser (1997), “Are ghettos good or bad?”, Quarterly Journal of Economics 112(3): 827–72.
OECD (2009), International Migration Outlook, Paris: OECD Publishing.
