What Difference Does a Negative Opinion Climate Make? Assessing Immigrants’ Low-Wage Risks in Times of Heightened Anti-Immigrant Attitudes

Welchen Unterschied macht ein negatives Meinungsklima? Eine Analyse des Niedriglohnrisikos von Migranten in Zeiten ausländerfeindlicher Einstellungen

Abstract

The paper argues that a negative opinion climate vis-à-vis immigrants increases the low-wage risks of second-generation immigrants. Analysing data from 18 waves of the German Socio-Economic Panel and using a matched case design, we provide strong support for this hypothesis. The findings complement studies of immigrants’ wages, bringing evidence for their sensitivity to contextual factors. They also complement recent findings from firm-level studies that found that the wage bias in cases of second-generation immigrants reflects the perception of competition between them and German workers.

Zusammenfassung

Dieser Beitrag argumentiert, dass ein negatives Meinungsklima gegenüber Einwanderern das Niedriglohnrisiko von Einwanderern der zweiten Generation erhöht. Eine Matching-basierte Analyse von Daten aus 18 Wellen des Sozio-oekonomischen Panels (SOEP) liefert deutliche Indizien für diese Hypothese. Im Einklang mit existierenden Studien über die Löhne von Migranten zeigen die Ergebnisse, dass kontextuelle normative Faktoren einen substanziellen Einfluss haben. Sie ergänzen auch Unternehmensstudien, die Lohnlücken von Einwanderern der zweiten Generation durch den wahrgenommenen Grad an Wettbewerb zwischen deutschen und nichtdeutschen Arbeitnehmern erklären.

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Notes

  1. 1.

    This has changed with the rise of the party Alternative für Deutschland, which received 12.6% of the votes in the 2017 federal election. However, as explained below, our empirical analyses focus on data from 1996 to 2013.

  2. 2.

    The SOEP was launched in West Germany with a random sample of the 1984 resident population (subsample A) and a stratified random sample of immigrants from the traditional guest-worker nations of Greece, Italy, the former Yugoslavia, Spain, and Turkey (subsample B). Other subsamples (C–M) were added later to address population changes and panel attrition. Two of these subsamples focus on immigration waves into Germany between 1984 and 1994 (subsample D) and between 1995 and 2013 (subsample M).

  3. 3.

    See employment status in the SOEP data documentation (SOEP 2014).

  4. 4.

    See migback in the SOEP data documentation (SOEP 2014).

  5. 5.

    We compute gross hourly wages as the ratio between monthly gross wage and weekly working hours multiplied by 4.2. This estimation depends on the reliability of weekly working hours provided by the respondents, and it may provide unrealistically low or high hourly wages. Therefore, the computed values were top- and bottom-coded at € 5 and € 50.

  6. 6.

    Economic: “If jobs are scarce, foreigners should be sent home.” Political: “One should deny foreigners any political activity.” Family: “Foreigners living in Germany should choose their spouses from among their own compatriots.”

  7. 7.

    All descriptive analyses are based on weighted data using the cross-sectional weights provided by SOEP. The weights control for different selection probabilities of the various subsamples (e.g., the oversampling of immigrants) and for different response and attrition rates (Pischner 2007). Weights are not available for sample D and hence, for some descriptive analyses, sample sizes may slightly differ from the ones mentioned in this section.

  8. 8.

    These scores are supplied with the SOEP data but include a high percentage of missing values. In these cases, we assign a status score of zero and control the missing data imputation with a dummy variable (named “imputation flag” in the estimation results).

  9. 9.

    In principle, these friends may also have a migration background, but this information is not available in the SOEP data.

  10. 10.

    Note that a FE model focuses on the within variance. Therefore, it cannot tell the absolute level of the dependent variable. However, it provides estimates on how low-wage probabilities deviate from natives when the corresponding independent variable (here: \(OC_{t}\)) is above or below its average. Therefore, at average opinion climate levels, the differences between both immigrant groups and natives were set to 0 in Table 3.

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Correspondence to Romana Careja.

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Careja, R., Andreß, H. & Giesselmann, M. What Difference Does a Negative Opinion Climate Make? Assessing Immigrants’ Low-Wage Risks in Times of Heightened Anti-Immigrant Attitudes. Köln Z Soziol 72, 265–288 (2020). https://doi.org/10.1007/s11577-020-00697-w

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Keywords

  • Competition theory
  • Immigrants’ life chances
  • Economic integration
  • Germany
  • SOEP

Schlüsselwörter

  • Wettbewerbstheorie
  • Lebenschancen von Immigranten
  • Ökonomische Integration
  • Deutschland
  • SOEP