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Demography
Published in: Demography 3/2019

17-04-2019

Natives’ Attitudes and Immigrants’ Unemployment Durations

Authors: Sekou Keita, Jérôme Valette

Published in: Demography | Issue 3/2019

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Abstract

In this study, we investigate how the attitude of natives—defined as the perceived trustworthiness of citizens from different countries—affects immigrants’ labor market outcomes in Germany. Evidence in the literature suggests that barriers to economic assimilation might be higher for some groups of immigrants, but the role of natives’ heterogeneous attitudes toward immigrants from different countries of origin has received little attention. Using individual-level panel data from the German Socio-Economic Panel covering the years 1984 to 2014, we apply survival analysis methods to model immigrants’ unemployment durations. We find that lower levels of trust expressed by natives toward the citizens of a given country, measured using Eurobarometer surveys, are associated with increased unemployment durations for immigrants from this country. We show that this result is not driven by origin-specific unobserved heterogeneity and that it is robust to different specifications and alternative explanations.
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Appendix
Available only for authorised users
Footnotes
1
See Riach and Rich (2002), Zschirnt and Ruedin (2016), and Bertrand and Duflo (2017) for extensive reviews of the literature on field experiments on discrimination.
 
2
Ethnic penalties refer to a strong relationship between ethnicity and gaps in labor market outcomes (such as wages, job quality, or employment dynamics) that cannot be explained by demographic and other human capital variables.
 
3
In this context, performing refers to a choice rather than to productive ability. One can think of a level of effort required by the contract that can be only imperfectly observed by the employer. The worker then chooses to exert the level of effort that maximizes his or her utility, which can be below the effort required by the contract.
 
4
The contract might not be enforced for several reasons. For example, if effort cannot be perfectly observed, proving that the worker did not exert the level of effort stated in the contract might be impossible or too costly for the employer.
 
5
Reducing the arrival rate of job offers has two opposite effects. On the one hand, the unemployment duration of discriminated workers decreases because they become less picky and reduce their reservation wage. On the other hand, the lower expected number of opportunities to leave unemployment increases immigrants’ unemployment duration. Under relatively weak conditions, the latter effect dominates (van den Berg 1994).
 
6
Still, we also present suggestive correlations between trust and individuals’ annual labor earnings in the online appendix, Table A6.
 
7
We use the version v.32, accessible at https://​doi.​org/​10.​5684/​soep.​v32 (Goebel et al. 2018).
 
8
Two difficulties arise from GSOEP calendar data. First, individuals may report several activities for the same month, which implies overlapping spells. Second, the number of activities has marginally changed over time to include more categories. We provide a detailed explanation of how we address these two problems in the online appendix.
 
9
Before 1995, Eurobarometer surveys were exclusively administered to German citizens. From 1995 onward, they were also administered to EU citizens. For these waves, we drop all observations from respondents who are not German citizens.
 
10
One might expect that the opinion of German citizens with a migration background could induce a bias in our measure of trust. The potential influence of this on our results is limited because only 12 % of Germans had a migration background in 2017, and this share was even lower in the decades that constitute our period of analysis. Moreover, because some employers are also likely to have a migration background, a measure including German citizens with migration background is probably closer to the level of trust that immigrants actually face in the labor market.
 
11
We suspect unemployment spells above this threshold to be potentially artificial (due to early retirement for example). Nonetheless, such instances correspond to less than 1 % of the total observations, and all results are robust to the inclusion of unemployment spells above this threshold.
 
12
Interruptions of unemployment spells (for training or maternity leave for instance) are considered as right-censored spells. Table A9 in the online appendix shows that our results are robust when recoding these short leaves as unemployment.
 
13
Our tables report coefficients rather than exponentiated coefficients (hazard ratios). The difference is that coefficients must be compared with 0 instead of 1.
 
14
Age and years since migration are defined at the beginning of the unemployment spell in order to avoid the collinear variation of these two variables with duration. Other variables, such as marital status, assistance, and number of children, are updated yearly. All covariate definitions and descriptive statistics are reported in Tables A1 and A3, respectively, in the online appendix.
 
15
Our main conclusions are robust to stratification by gender as well as to separating samples for men and women. These results are reported in Table A14 in the online appendix.
 
16
The Weibull model is preferable to the gamma, log-logistic, log-normal, and exponential models because of its lower AIC and BIC criteria.
 
17
Successive failures are assumed to be unordered and of the same type. In the baseline sample, 57 % experienced only one unemployment spell. Our results are robust to clustering at the origin-region level, as reported in Table A8 in the online appendix. Table A12 in the online appendix shows that our results are robust to controlling for past unemployment history.
 
18
Consistent with this mechanism, Table A11 in the online appendix shows that removing right-censored spells from the analysis leads to a dramatic increase in our estimated coefficient. Our results remain robust to the exclusion of left-censored spells.
 
19
The estimated shape parameter ln(ρ) in Weibull regressions is significantly positive, which means that the probability for immigrants of finding a job increases with time in unemployment.
 
20
We actually use 112 of the 165 possible origin-region pairs because migrants from some countries are not observed in all regions.
 
21
Unlike findings by Uhlendorff and Zimmermann (2014), our results are not exclusively driven by Turkish immigrants, the largest group of immigrants in Germany. The results with Trust and Trustor are robust to estimates excluding Turkish immigrants (available upon request).
 
22
Karlson et al. (2012) showed that unlike in linear models, the changes in coefficient of the variable of interest cannot be straightforwardly attributed to the inclusion of confounding variables. We take advantage of the fact that with their accelerated failure-time (AFT) metric, Weibull models can be seen as regular linear regression models, albeit with extreme values of residual terms. AFT models no longer model hazards (as parametric proportional hazard Weibull models do) but instead model the logarithm of the duration. Thus, using coefficients from Weibull in the AFT metric allows us to compare coefficients between models with different covariates. The results are perfectly equivalent in the two metrics given that βAFT = −βPH / ρ. The results with the AFT metric are available upon request.
 
23
Our results are also robust to the inclusion of years of education abroad. These results are reported in Table A13 in the online appendix. All our results with the education variable are also robust to the inclusion of more detailed categories, with separate groups for degrees specific to the German education system, such as vocational degrees.
 
24
The model also predicts that individuals with low and high levels of education have similar levels of ability regardless of the level of discrimination they face.
 
25
These two variables are computed irrespective of whether the immigrants had a long period of unemployment or inactivity. By definition, immigrants without prior work experience or first recorded spells are excluded from this analysis. The number of individuals in the sample is therefore reduced by roughly 30 % compared with our benchmark specification.
 
26
The 2SRI estimator corrects for the inconsistency of the estimated parameters obtained with the two-stage least squares (2SLS) method applied to nonlinear models. Although the 2SLS and the 2SRI share the same first-stage equation, the latter does not replace the endogenous variable by its predicted value but instead includes the first-stage residuals as additional regressors (Terza et al. 2008).
 
27
When included in our main specification as the explanatory variable, our instrument is not significant, supporting the validity of the exclusion restriction.
 
28
Figure A7 in the online appendix shows a strong and negative correlation between the variable Trust and the perceived discrimination variable. The correlation coefficient between the two variables is –.17 and is statistically significant at the 1 % level.
 
29
The index can be found online at http://​www.​mipex.​eu/​anti-discrimination.
 
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Metadata
Title
Natives’ Attitudes and Immigrants’ Unemployment Durations
Authors
Sekou Keita
Jérôme Valette
Publication date
17-04-2019
Publisher
Springer US
Published in
Demography / Issue 3/2019
Print ISSN: 0070-3370
Electronic ISSN: 1533-7790
DOI
https://doi.org/10.1007/s13524-019-00777-3

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