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Terrorism and the integration of Muslim immigrants


We study the effect that a series of Islamist terrorist attacks across Europe in 2004–2005 had on the integration of Muslim immigrants. Using unique panel data that oversamples immigrants in the Netherlands, we show that, shortly after the attacks, Muslim immigrants’ attitudes toward integration worsened significantly compared to those of non-Muslim immigrants, with no evidence of a negative trend in the attitudes of Muslims prior to the attacks. While, in particular, low-educated Muslims became more geographically segregated and unemployed after the attacks, high-educated Muslims were affected most negatively in terms of their perceived integration. This decline in perceived integration is associated with a higher intention to permanently re-migrate to the country of origin.

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  1. See

  2. Detailed coverage of the 2005 London attacks can be found at the BBC website at

  3. With the exception of some terrorist conspiracies and threats, there were no high-profile terrorist attacks in Europe from September 11, 2001, to March 10, 2004 (Nesser 2008). According to the Global Terrorism Database (2012), the three attacks listed above were the most significant Islamist terrorism attacks in Europe. For extensive details on fundamentalist Islamic terrorism in Europe over this period, see Bakker (2006, pp. 3–4).

  4. This was also accompanied by a wave of increased xenophobic attitudes among locals. Data from the World Values Survey show that the share of the Dutch who would not like to have immigrants/foreign workers as neighbors jumped from about 10% in 2005 to around 20% in 2012. See:

  5. As the social integration process of foreign minorities takes generations, assessing changes in immigrants’ integration over a short period of time would prove difficult using traditional measures of integration such as language use, importance of religion, attitudes toward intra-marriage, etcetera. Integration attitudes, however, represent the basis of the integration process and could therefore capture the integration potential. Georgiadis and Manning (2013) show that immigrants who feel tolerated by natives are more likely to identify with the host country.

  6. Unlike Gautier et al. (2009), who studied the effect of terrorism on Muslim immigrants at the neighborhood level, we show changes in the geographic segregation of Muslims using data at the individual level. One advantage of our approach is the ability to study the heterogeneous effects of the impact of terrorism on Muslim immigrants.

  7. Some studies exploit exogenous shifts in natives’ ethnic preferences to study taste-based discrimination (e.g., Michaels and Zhi 2010; Moser 2012) and in-group preference (e.g., Shayo and Zussman 2011).

  8. The impact that large-scale fundamentalist Islamic terrorist attacks have on discrimination is not limited to the country in which the attacks take place. For example, Schüller (2016) shows that September 11 resulted in a significant increase in negative attitudes toward immigration and decreased concerns over xenophobic hostility among the native German population.

  9. In a similar vein, Miaari et al. (2012) showed that the second Intifada in 2000 increased job separation rate for Arab workers in Israel, relative to Jew workers.

  10. In addition to this strategic objective for terrorism, the literature discusses several other political objectives such as changing standpoints of governments (Kydd and Walter 2006), or switching political attitudes of locals leftwards (Gould and Klor 2010), in addition to economic objectives such as causing large movements of capital across countries (Abadie and Gardeazabal 2008).

  11. Goel (2010) estimates changes in perceptions of discrimination among Muslim-looking immigrants in Australia using a cross section of recently arrived immigrants, making it difficult to account for unobserved immigrant heterogeneity. In addition, the measures used in her study are limited to binary perceptions of intolerance and discrimination. Our study goes one step further, beyond perceptions of fair/unfair treatment, and assesses changes in immigrants’ feeling at ease with natives and attitudes toward living in the host country.

  12. The long period over which the data were collected is due to the difficulty in reaching the target groups (Dykstra et al. 2005, 2012).

  13. See the Statistics Netherlands website:

  14. The first eight items are used in the sociological literature as a measure of perceived acceptance by the host country (Huijnk et al. 2012). The scale for items (2), (5), (7), and (9) is reversed so that the higher the value, the better the outcome in terms of integration.

  15. We here follow the definition used in the literature (e.g., Steedman and McIntosh 2001) which defines the low educated as those who have lower secondary education or below, and the higher educated as those with upper secondary education or higher.

  16. An alternative approach is to compute the average effect size across items within the integration index, using seemingly unrelated regression for the 10 items to estimate the covariance of the effects and then calculating the mean effect size for the 10 items in a second step (Clingingsmith et al. 2009; Kling and Liebman 2004). Since we use a consistent number of observations across the 10 items of integration and there are no regression adjustments, the two approaches give identical results (Kling et al. 2007). Without a consistent number of observations, the results would remain very similar. The advantage of the average z-score index used in this paper is that it is much simpler to work with, especially when using panel data (Kling et al. 2007).

  17. The Breusch Pagan Lagrangian multiplier test rejects the null hypothesis and therefore suggests the use of random effects model over OLS.

  18. We acknowledge the potential for selection bias due to panel attrition in the dataset; of the 469 respondents for whom we have information on integration and background characteristics in the first wave, only 216 were also present in the second wave. To deal with the selection bias, we replicated the analysis after controlling for Mills ratio using a selection variable that equals one if the individual is observed in the two waves of the study as our dependent variable in the selection equation. As an exclusion restriction, we used a dummy variable that takes the value one if the number of missing items in the respondents’ answers to all the questions in the first wave is above the median and zero otherwise (Huijnk et al. 2012). This variable is used to satisfy the exclusion restriction, which is possible since the likelihood that a respondent will be absent from the second wave should be correlated with the number of questions the respondent did not answer in the first wave. (i.e., immigrants who answered fewer questions in the first wave should be more likely to drop out in the second wave). However, the number of missing answers should not be correlated with the timing of the terrorist attacks. The results (that can be obtained from the corresponding author) are similar to those shown in Table 1.

  19. We could not use wages here because our dataset does not contain a consistent measure of labor income across the two panel waves.

  20. To examine pre-trends, we also estimated a model in which we regress geographic segregation, unemployment, and working hours separately on the time of the interview during the first wave interacted with a Muslim dummy. We find no significant pre-trends in Muslim immigrants’ outcomes relative to non-Muslims.

  21. About 32% of the respondents (36% of Muslims and 30% of non-Muslims) witnessed a decline in their perceived integration across the two waves.

  22. The control variables shown are from the second wave. However, estimation results do not change when we control for the pre-attack levels of the control variables or the changes in the variables between the two waves. To capture any differences in the relationship between the change in perceived integration and the intention to permanently return to the native country between Muslim and non-Muslim immigrants, we have re-estimated the model controlling for the interaction between being a Muslim and the change in perceived integration. The coefficient of the interaction term shows no significant differences between the two groups, suggesting that the two groups of migrants do not respond differently to a decline in integration.


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We acknowledge the comments on earlier versions of our paper by two anonymous referees, Marion Collewet, Denis de Crombrugghe, Jan Feld, Stephen Machin, Alan Manning, Maria Paula Gerardino, Olivier Marie, Jeffrey Nugent, Jörn-Steffen Pischke, Nicolas Salamanca, and Maria Zumbuehl, as well as participants of the Economic Research Forum (ERF) 2013 conference in Kuwait, the 2013 “Migration: Global Development, New Frontiers” conference at UCL, the 16th IZA European Summer School in Labor Economics in Buch/Ammersee, Germany, the EALE, Conference in Ljubljana, Slovenia, and the CEP/LSE Labour Seminar in London School of Economics. The Netherlands Kinship Panel Study is funded by grant 480-10-009 from the Major Investments Fund of the Netherlands Organization for Scientific Research (NWO) and by the Netherlands Interdisciplinary Demographic Institute (NIDI), Utrecht University, the University of Amsterdam and Tilburg University.

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Correspondence to Ahmed Elsayed.

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Table 6 Descriptive statistics
Table 7 Difference-in-difference estimates of integration attitudes before and after the terrorist attacks
Table 8 Change in the integration of Muslim and non-Muslim immigrants after the terrorist attacks, FE model
Table 9 Change in the integration attitudes of Muslim and non-Muslim immigrants after terrorist attacks, separate estimations for each item in the integration index
Table 10 Change in the integration of Muslim and non-Muslim immigrants after the terrorist attacks excluding extremely high pre-attacks levels of integration
Table 11 Trends in integration before and after the attacks, OLS estimates

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Elsayed, A., de Grip, A. Terrorism and the integration of Muslim immigrants. J Popul Econ 31, 45–67 (2018).

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  • Terrorism
  • Integration
  • Muslim immigrants

JEL Classification

  • F22
  • J15
  • R23
  • Z13