Abstract
To what extent does exposure to immigration condition the types of immigrants citizens are willing to admit? Extending the conjoint approach adopted by Hainmueller and Hopkins (Am J Pol Sci 59(3):529–548, 2015), this study investigates whether the admission preferences of French natives vary based on personal exposure to immigration, as proxied by local demographics and self-reported social contact. Methodologically, we propose and apply new methods to compare attribute salience across different subgroups of respondents. We find that although an inflow of immigrants into respondents’ municipalities has a limited influence on how French natives evaluate prospective immigrants, social contact with immigrants matters. Specifically, French natives who do not frequently interact with immigrants are significantly less favorable toward immigrants from non-western countries, and more favorable toward immigrants from western countries. In contrast, natives who report frequent social interactions with immigrants place less weight on nationality as a criterion for immigrant admission. Although scholars have noted an increasing consensus in immigration attitudes across developed democracies, our findings suggest that individual experiences with immigration condition preferences for immigration policy at the national level.
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Notes
In our conjoint experiment, we asked respondents to assess hypothetical immigrants for admission. In the “Study Design” section, we argue that the attributes we include in our analysis reflect important aspects of immigration policy preferences.
Iyengar et al. (2013) and Hainmueller and Hangartner (2013) could be considered exceptions. However, the number of attributes included in Iyengar et al.’s vignette is relatively small, and each attribute only takes on one of two levels. In the case of Hainmueller and Hangartner (2013), the authors use observational data, which limits their ability to make a causal interpretation of the relevance of various immigrant attributes.
For a comprehensive review of studies that explore public attitudes toward immigration, see Hainmueller and Hopkins (2014).
See Hopkins (2018) for a similar argument in the American context.
This experiment received approval from the Committee for the Protection of Human Subjects at Dartmouth College (STUDY00030745).
This sample size is within the range of published studies that use fully randomized conjoint analysis in political science (e.g., Ballard-Rosa et al. 2016; Bechtel and Scheve 2013; Teele et al. 2018), and exceeds that of Hainmueller and Hopkins (2015). Our conjoint experiment includes two profiles per task and ten tasks. Therefore, the resulting number of observations in our data set is nearly 30,000—2 profiles \(\times\) 10 pairs \(\times\) 1500 respondents.
For our analyses that use demographic data based on respondents’ postal code, we excluded four respondents who entered an invalid postal code.
The French versions of the attributes and levels are shown in Tables A.2 and A.3 in the Supplementary Materials.
We use the same baseline categories as Hainmueller and Hopkins (2015). The only exception is for the country of origin attribute. We changed the levels (countries) for this attribute to suit the French context (following Hainmueller and Hopkins 2015, the top 10 sending countries for immigrants), and chose China as the baseline. Note that India is used by Hainmueller and Hopkins (2015).
Specifically, if a hypothetical immigrant had a high-skilled profession (e.g., “Doctor,” “Research scientist,” “Financial analyst,” “Professor,” or “Computer programmer”), their education level was higher than “Two-year degree.” If their profession was “Nurse,” their education level was higher than “High school.” Additionally, if a hypothetical immigrant’s country of origin was in the EU (i.e., “Portugal,” “Spain,” “Italy,” or “United Kingdom”), their prior trips to France did not include the following levels: “Visited once before on a tourist visa,” “Visited many times before on a tourist visa,” or “Entered France once without legal authorization.” This is because EU nationals can move freely across European borders, and their reason for immigrating cannot be “Escape political or religious persecution.” After a soft launch of our study, we noticed a coding error that prevented some of these cross-attribute constraints from working properly, and fixed it. For our analysis, we therefore exclude conjoint tasks with at least one profile that includes a highly unlikely combination. The number of tasks excluded from analysis is 332, which is only 2.2% of all 15,000 (\(=\) 1500 respondents \(\times\) 10 tasks per respondent) tasks.
Following another suggestion from Hainmueller and Hopkins (2015), we also implemented one constraint on the attribute ordering such that the profession, job experience, and job plans attributes always appeared together, in that order (although the location of this block of attributes among other attributes was randomized across respondents).
Before these questions, respondents answered two additional questions about public transportation and the education system in France, which served as “distractors.” By asking demographic and attitudinal questions about several different topics after exposing respondents to the conjoint tasks, we sought to reduce the likelihood that responses to the next set of questions would be impacted by the treatment.
The survey concluded with an opportunity for respondents to provide written comments or feedback, and a debriefing statement about the nature of the study.
In Schmid et al.’s (2014) study of neighborhood diversity and trust, this question reads, “How often, if at all, do you have brief everyday encounters with people from ethnic minority backgrounds, which might involve exchanging a couple of words, for example, in corner shops, buying a paper and so on?”
In the General Social Survey, this question pertains to American race relations and reads, “During the last few years, has anyone in your family brought a friend who was a (Negro/Black/African-American) home for dinner?” (Smith et al. 2017, p. 365).
This question draws inspiration from the General Social Survey’s question, “Now I’m going to ask you some questions about people that you trust, for example good friends, people you discuss important matters with, or trust for advice, or trust with money. Some of these questions may seem unusual but they are an important way to help us understand more about social networks in America. Please answer the questions as best you can. How many people you trust are [race/ethnicity]?” (Smith et al. 2017, pp. 1963–1973), and from the Canadian Measure of Social Capital, which includes a similar version of this question in French (Franke 2005, p. 61).
Although we included a series of demographic, attitudinal, and “distractor” questions between the conjoint exercise and the questions used to construct our social contact index, we cannot definitively rule out the possibility that exposure to the conjoint profiles impacted responses to the social contact index questions. To address this concern, we ran analyses using each component of the index as an individual moderator. The question about sharing a meal with an immigrant is arguably the least subjective measure of immigrant interaction included in the index, and is therefore least likely to be subject to priming effects. As we describe in the next section, our results hold using this specification.
Leeper et al. (2018) also acknowledge this issue and, as we do, suggest using marginal means for subgroup comparisons in conjoint analysis.
The difference is almost significant for Morocco (\(p=0.057\)).
We note that low contact natives’ preferences against immigrants from non-western countries most likely does not reflect Islamophobic sentiments among this group. While the pattern of differences we observe suggests that low contact natives disfavor immigrants from the Muslim-majority countries of Algeria and Morocco, the differences are consistently insignificant for the other two majority-Muslim countries (i.e., Tunisia and Turkey).
When an attribute in conjoint analysis has many levels, it is possible to have one or two statistically significant coefficients purely by chance. To rule this out, we calculated, for each attribute-level, the p-value for testing the difference between the subgroups of respondents. We also calculated the p-values after the false discovery rate adjustment. The results, which are presented in the Supplementary Materials (Fig. B.2), confirm the robustness of our findings. After the adjustment, the attributes including at least one statistically significant level are the country of origin and application reason attributes. These results are consistent with our main findings presented in Fig. 3.
We observe a handful of additional significant differences regarding the job plans and application reason attributes, and we still observe significant differences in the same direction in terms of high and low contact respondents’ likelihood of selecting immigrants from Algeria, Portugal, and the UK. Respondents with no immigrant contact (score of 0) also select immigrants from Morocco and Turkey at a significantly lower rate than do respondents with some contact (score of 1–3).
To measure the component scores, we use the original (categorical or dichotomous) variables.
Our data do not indicate what the “unexplained” variation in our dependent variable—social contact—is. That said, after controlling for a range of key demographic and attitudinal variables, we are inclined to think that this variation correlates with each respondent’s frequency of interacting with immigrants.
We also tested whether the differences we observe between high versus low contact respondents are driven by differences in respondents’ education and ideology by subsetting our data to include respondents who are highly educated (holding a university degree) and those who are left-leaning (who scored lower than the midpoint on an 11-point ideology scale). Our findings are presented in Figs. B.10 and B.11 in the Supplementary Materials. The results for highly educated respondents are consistent with the main results: the country of origin attribute is highly salient. The results for left-leaning respondents show that the country of origin attribute is not statistically significant at the 0.05 level, but the point estimate remains similarly sized. This result is in part due to the relatively small number of respondents who are left-leaning.
Paralleling this analysis, the top panel of Fig. 4 shows the lack of statistically significant differences in salience between respondents in municipalities with an above- versus below-median immigrant influx from foreign countries. To test the robustness of these results, we first ran an OLS regression using immigrant flow as the dependent variable and the same set of independent variables used in the above noted regression analysis (the results of which are presented in Fig. 5). We then divided respondents into two groups based on the residuals—whether respondents live in a municipality with an above-median or below-median immigrant inflow. The results presented in Fig. B.12 in the Supplementary Materials support the findings.
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Earlier drafts of this paper were written as part of Clayton’s undergraduate Honors Thesis submitted at Dartmouth College, and presented at the 2018 Annual Meeting of the Midwest Political Science Association, the 2018 Annual Meeting of the Society of Political Methodology, the 2018 Annual Meeting of the American Political Science Association, and the Joint Conference of the 6th Asian Political Methodology Meeting and the 2nd Annual Meeting of the Japanese Society for Quantitative Political Science. We thank John Carey, Michelle Clarke, Dean Knox, Adeline Lo, James McCann, Benjamin Valentino, and Sean Westwood for their useful feedback. The complete replication package is available at https://doi.org/10.7910/DVN/2OOLD7.
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Clayton, K., Ferwerda, J. & Horiuchi, Y. Exposure to Immigration and Admission Preferences: Evidence from France. Polit Behav 43, 175–200 (2021). https://doi.org/10.1007/s11109-019-09550-z
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DOI: https://doi.org/10.1007/s11109-019-09550-z