The unemployment rate in France is roughly six percentage points higher for African immigrants than for natives. In the US, the unemployment rate is approximately nine percentage points higher for black people than for white people. The gap between the minority (African immigrants or black people) and the majority (natives or white people) remains important even after controlling for individual attributes such as education, age or other demographic characteristics. The persistence of ethnic unemployment-rate gaps is a major policy concern, first in terms of equality of opportunities and second in terms of economic efficiency, since considerable resources are wasted for the economy if large groups cannot easily access to jobs. However, the causes of the gaps are still debated. In particular, it is not yet known whether it is ‘race’ or ‘space’ that is the key explanatory factor of the poor labour-market outcomes of many minorities (see Ellwood 1986). The spatial mismatch literature, initiated by Kain (1968), has indeed attempted to determine whether minority workers have worse access to the labour market or whether they face barriers in housing choice, making it difficult to locate close to job opportunities.
A clue may come from the observation of commute-time data by groups of workers. The data indicate that the Minority faces longer commute times to work, potentially reflecting a more difficult access to jobs. Table 1 shows that, in France, the difference between median commute times as a fraction of daily working time is 17 % (and 24% for the mean commute time).1
Table 1. Commute time in France as a fraction of standard daily working time (7.8 hours)
In the US, differences in commute time between black and white workers are similar to those in France. In addition, France and the US differ regarding job-related geographical mobility rates: they are higher for minority workers than for majority workers in France, and quite similar for white people and black people in the US.
Since several factors affect the equilibrium rate of unemployment of a given group, including not only productivity and job acceptance decisions but also geographical features such as geographical mobility, access to residential locations with good access to jobs and finally the ability to commute, it is hard to assess the respective role of each factor in the determination of ethnic unemployment rates. Unfortunately, it is difficult to find an appropriate natural experiment to properly decompose the respective role of each market (housing and labour market).
In a recent paper (Gobillon, Rupert and Wasmer 2013), we try to quantify the impact of spatial mismatch on the unemployment rate of ethnic groups. More precisely, we provide a methodology to assess this ‘dynamic spatial mismatch’ hypothesis, that is, the inter-temporal decisions of housing, commuting, job acceptance and quit. We build a tractable macroeconomic matching model meant to capture the relevant forces at work. It allows us to assess the importance of job-market factors and spatial factors. We model frictions on both the labour and housing markets whereas, in the literature, frictions are usually introduced in one market only; we calibrate the model to get quantitative results rather than giving only theoretical predictions; finally, we perform comparative statics to assess the contribution of job and spatial factors to the ethnic unemployment-rate gap.
Overall, although labour-market factors play a major role, spatial factors in France explain between 17% and 25% of the unemployment-rate gap between the minority and the majority, depending on the decomposition. The results appear to be robust to various alternative calibration parameters and correspond to an unemployment-rate difference between 1 and 1.5 percentage points, out of six percentage points. Decreuse and Schmutz (2012) find similar qualitative results as, in their study, spatial factors account for around 15% of the unemployment-rate gap. It is also consistent with Rathelot (2013) who studies the employment gap between French natives and second-generation Africans, and finds that between 63% and 89% of the employment gap remains after controlling for observable individual characteristics and location, which suggests that ethnic differences in access to the labour market play a major role and spatial factors a lesser role.
More work is needed to better understand the factors behind the ethnic differences in access to the French housing market. It appears that the different outcomes across ethnic groups in the housing market are less due to the minority receiving fewer housing offers, than to the minority receiving fewer good offers. That is, while the probability of housing offers can be the same for the minority and the majority, offers to the minority are for dwellings which are located farther away from jobs. This result is consistent with other papers on the French housing market emphasising a substantial degree of spatial mismatch and rising segregration (Bouvard et al. 2009).2
In the US, spatial factors also seem to play a role, and explain 1 to 1.5 percentage points of the difference in unemployment rates between black people and white people. However, this corresponds to only 10 to 17.5% of the total racial unemployment-rate gap because there is a larger absolute difference in unemployment rates.
It appears that differences in commuting distances account for a large fraction of the unemployment-rate gap. In France, a higher mobility of the minority partly compensates for the contribution of commuting differences to explaining the unemployment-rate gap.
Overall, labour-market factors still remain the main explanation for the higher unemployment rate of African immigrants in France and black people in the US, but understanding why minority workers face higher commute times should be further investigated, especially in France where studies are scarce .
More generally, we believe that our methodology can be replicated to address additional issues in which labour and housing markets interact in complex ways.
Bouvard, L, P-P Combes, B Decreuse, M Laouénan, B Schmutz and A Trannoy (2009), "Géographie du chômage des personnes d'origine africaine : une discrimination vis-à-vis des emplois en contact avec la clientèle?", Revue Française d'économie 23, 8-56.
Decreuse, B and B Schmutz (2012), “Residential mobility and unemployment of African immigrants in France : a calibration approach”, Annals of Economics and Statistics 107, 51–927.
Ellwood, D (1986), “The spatial mismatch hypothesis: Are there teenage jobs missing in the ghetto?” in Freeman, R, Holzer, H (eds.) The Black Youth Unemployment Crisis, University of Chicago Press, Chicago.
Gobillon L, P Rupert and E Wasmer “Ethnic Unemployment Rates and Frictional Markets”, CEPR Discussion Paper 9507, June 2013, forthcoming in the Journal of Urban Economics.
Kain, J (1968), “Housing segregation, negro employment, and metropolitan decentralization”, Quarterly Journal of Economics 82, 175–197.
Rathelot, R (2013), “Ethnic differentials on the labor market in the presence of asymmetric spatial sorting: Set identification and estimation”, Mimeo CREST.
Rupert P and E Wasmer (2012), “Time to move and aggregate unemployment”, Journal of Monetary Economics 59, 24–36.
1 Note also that these differences by ethnic group are unconditional, but they increase after controlling for education and demographic characteristics: the unconditional commute time difference is 9.9 minutes; the conditional difference is 11.6 minutes.
2 More precisely, Bouvard et al. (2009) argue that, in France, over the past several decades, employment in industrial sectors shrunk, and job centers moved away from social housing where migrants used to live. The sectoral employment shift lead jobs to appear in the service sectors, located in cities, where migrants may not have had access in terms of housing markets.