Local elected officials’ receptivity to refugee resettlement in the United States

Robert Shaffer; Lauren E. Pinson; Jonathan A. Chu; Beth A. Simmons

doi:10.1073/pnas.2015637117

New Research In

Contributed by Beth A. Simmons, September 28, 2020 (sent for review July 24, 2020; reviewed by Kirk Bansak and Donghyun Danny Choi)

Significance

The recent global surge in forcibly displaced persons has produced grave humanitarian consequences. This surge has prompted close scrutiny of public sentiment toward refugees in recipient countries. But less attention has been paid to local governments, despite the outsized influence they wield over refugee resettlement and well-being. We provide an experimental study of US local elected officials’ attitudes toward refugees seeking to settle in their communities. We find that local elected officials support a broad range of refugee groups, though they are most supportive of refugees whom they believe will contribute to the local economy and fit with community values. Our results offer guidance to advocates seeking to improve resettlement outcomes and a rejoinder to national-level suspicion toward refugee resettlement.

Abstract

Local leaders possess significant and growing authority over refugee resettlement, yet we know little about their attitudes toward refugees. In this article, we use a conjoint experiment to evaluate how the attributes of hypothetical refugee groups influence local policymaker receptivity toward refugee resettlement. We sample from a national panel of current local elected officials, who represent a broad range of urban and rural communities across the United States. We find that many local officials favor refugee resettlement, regardless of refugee attributes. However, officials are most receptive to refugees whom they perceive as a strong economic and social fit within their communities. Our study contributes to a growing literature on individual attitudes toward refugees by systematically examining the preferences of US local elected officials and offers unique insights into the views of this influential and policy-relevant group.

What factors lead local elected officials to support refugee resettlement in their communities? Local leaders’ attitudes toward refugees significantly influence refugee-resettlement outcomes. Sympathetic local elites can facilitate the social and economic transition for resettled refugees by easing access to social services and economic assistance. By contrast, less receptive local officials can impose hostile regulations or incite resident resentment (1, 2). Since newly settled refugees often rely on community assistance, these obstacles represent real barriers for successful resettlement.

Recent executive actions have expanded US local elected officials’ already-critical role in the refugee-resettlement process. In September 2019, President Donald Trump signed an executive order requiring the federal government to obtain consent from state and local governments before settling refugees in their jurisdictions. In the following months, local governments in North Dakota, Minnesota, Virginia, Colorado, and beyond voted on whether to consent to refugee resettlement (3 ⇓⇓–6). Due to legal challenges, the final status of the executive order is uncertain. However, regardless of outcome, the order highlights the importance of local policymakers throughout the resettlement process. Furthermore, these developments have global implications due to the United States’ prominent position in the refugee-resettlement ecosystem. Until 2018, the United States accepted the most refugees of any country (7), with more than 500 US cities accepting over 100 refugees from 2002 to 2018.

This article investigates the attitudes of local elected officials toward refugees, with a focus on how refugee-group attributes (e.g., educational attainment, religion, and region of origin) affect officials’ attitudes. While the US Refugee Admissions Program’s stated intent is humanitarian, an abundance of scholarship shows that members of the public favor refugees with particular attributes, such as language proficiency and in-group religious identity. We intervene in this literature by providing a large-scale study of local elected officials’ views on refugee resettlement. To do so, we fielded a conjoint survey experiment asking local elected officials to read pairs of randomly generated refugee-group profiles and recorded whether respondents were receptive to such groups settling in their communities. This design allowed us to build on existing knowledge while generating insights into the views of local elected officials, who exert a powerful influence over refugee-resettlement outcomes.

We find that many local elected officials support refugee resettlement, regardless of refugee characteristics. While substantial variation in preferences exists, approximately half of our respondents supported all refugee group profiles they considered, while approximately 1 in 10 opposed all such profiles (see also ref. 8). Though local officials in Democratic-voting counties supported more refugee groups on average, their counterparts in Republican-voting counties also supported over half of the profiles they viewed.

However, this overall pattern of support conceals important attribute-based differences in local officials’ attitudes toward refugees. Our experimental evidence shows that officials favor refugee groups that are better-educated, possess stronger English skills, are predominantly female, and identify as Christian. Local officials are also more likely to support refugees who are sponsored by a business, compared with refugees without sponsorship. Descriptive data from an open-ended follow-up question suggest that a plurality of respondents focus on refugees’ economic contributions, potentially eroding the stated humanitarian intent of the US resettlement program. Approximately 40% of respondents mentioned refugees’ economic contributions or local resource constraints, compared with approximately 25% who mentioned refugees’ social or cultural fit.

Our study encourages researchers to pay closer attention to the role of local governments in refugee resettlement. Though we caution against reorienting resettlement-policy discussions toward refugees’ economic contributions or social fit, our research provides guidance for both academics and refugee-resettlement stakeholders.

Policy Context

A refugee is “any person who is outside any country of such person’s nationality […] and who is unable or unwilling to return […] or unwilling to avail himself or herself of the protection of that country because of persecution or a well-founded fear of persecution on account of race, religion, nationality, membership in a particular social group, or political opinion” (9). Refugee resettlement in the United States is a multistage, multilevel process. Each year, the US government sets a cap for refugee admissions. Based on this cap, the United Nations High Commissioner for Refugees submits cases to the United States from a pool of approved applicants. Upon referral, potential refugees undergo an interview, security clearance, and assignment process. Successful applicants are paired with one of nine nongovernmental resettlement agencies, which coordinate with federal agencies on location selection and services.

Before 2019, US law required the Department of Health and Human Services’ Office of Refugee Resettlement to regularly consult state and local governments about the sponsorship process and geographic distribution of refugees prior to resettlement (10). Local governments have occasionally used this consultation process to voice grievances with resettlement decisions. For example, after the 2008 Financial Crisis, officials in Fort Wayne, Indiana, and Manchester, New Jersey, requested moratoria on refugee resettlement due to funding constraints and lack of economic opportunity (11). But formal state or local consent was not required for refugee resettlement.

More recently, local policymakers have assumed new, formal powers over refugee-resettlement decisions. In September 2019, President Trump issued an executive order directing the Secretaries of State and Health and Human Services to create a process for states and localities to provide written consent for the initial resettlement of refugees (12). Starting July 2020, the order directed federal agencies to resettle refugees only with the consent of both state and local governments, though the order allowed federal agencies to override local decisions to remain consistent with other federal laws. Refugee-resettlement agencies sued to block the order (13), which led to a preliminary injunction halting implementation (14 ⇓–16), and a subsequent appeal (17).* Nevertheless, more than 111 localities and 41 states gave written consent for refugee resettlement ahead of the injunction (18). Texas was the only state to refuse (19).

Whether or not the executive order stands, the political debate surrounding the order highlights local officials’ influence over the refugee-resettlement process. Deliberation and votes on refugee resettlement by local elected officials reflect community priorities (3). When community priorities differ from the legal criteria for refugee admission, empowering local leaders to debate and vote on refugee resettlement could alter refugee-resettlement outcomes.

A Local Government Perspective on Refugees

Determinants of Officials’ Receptivity Toward Refugees.

In this study, we examine local elected officials’ attitudes toward refugee resettlement in their communities. We investigate two broad sets of factors that might lead to greater receptivity toward some refugee groups: economic/material and social/cultural factors. While these considerations are not mutually exclusive, and indeed often influence one another, they are useful to distinguish conceptually.

Beginning with economic and material considerations, we expect local elected officials to favor refugee groups that can participate in and contribute to the local economy (see, e.g., refs. 20 ⇓–22, for related findings).^† Local officials are particularly attuned to budgetary issues and economic constraints in their districts. We expect signals of employability and self-sufficiency to be especially attractive to resource-conscious officials. Refugee education, business sponsorship, language skills, and status as working-age adults are likely indicators of economic productivity, which should increase officials’ receptivity toward refugee groups with these attributes.

We also expect local elected officials to favor refugee groups that they view as a sociocultural fit for their communities. Whether because of in-group favoritism or out-group animus, existing scholarship reports that members of the public favor migrants with attributes associated with sociocultural proximity (see, e.g., refs. 20 ⇓–22, 25, and 26). In the context of our survey, refugees’ religion, religious sponsorship, language, gender/family composition, and age affect evaluations of sociocultural fit. Religion, in particular, is strongly associated with in-group moral principles and identity (27). Since Christianity is the majority religion in the United States, we predict that local elected officials will favor Christian-identifying refugees and refugees who are sponsored by faith-based organizations. Local officials should also favor English-speaking refugees, since English is both the dominant language and a strong signal of in-group belonging in the United States. Furthermore, local officials should be more inclined to support older and female migrants, compared with younger male migrants, since residents might associate an influx of young, male residents with a higher probability of criminal activity (25). This expectation also reflects conventional gender-based notions of vulnerability, which advocates and refugee-resettlement organizations have been known to replicate (28). An additional possibility is that local officials may prefer refugees originating from some regions compared to others, but we do not view this scenario as likely, once education, language skills, religion, and other demographic attributes are taken into account.^‡

Lastly, while these economic and social factors imply that local officials’ attitudes will depend on refugee-group attributes, there are also reasons to believe that officials will be indifferent to these traits. The legal definition of refugee status is based on a well-founded fear of persecution, rather than an individual’s ability to contribute materially or assimilate culturally. If local officials have internalized this legal designation, then they should be receptive overall toward refugees, and their level of receptivity should not significantly vary by refugee attributes.

Examining Elected Local Officials.

Our theoretical expectations draw from a substantial empirical literature on mass—as opposed to local official—attitudes toward refugees and immigrants more broadly. While officials clearly share some of their constituents’ concerns and attitudes, we should be wary about generalizing from the mass public to learn about officials’ attitudes toward refugee resettlement. (See ref. 29 as an example of the role of local governments in refugee settlement.) To be clear, our study does not attempt to test hypotheses about whether citizen and elite attitudes diverge, which is outside the scope of this study. Instead, in this section, we outline ex ante why scholars and policymakers cannot necessarily generalize from existing public-opinion scholarship to understand official attitudes.

First, local government officials represent jurisdictions, and rural, sparsely populated jurisdictions are more common than more densely populated ones. As a result, the average local official’s district is older, whiter, and poorer and has lower educational attainment compared to the overall US population. (See CivicPulse Omnibus Survey Reference Guide in SI Appendix and ref. 30, appendix B.) Furthermore, rural communities like those in our sample contain relatively homogeneous social networks (31), and local jurisdictions are more conservative, contain more Christian constituents (32)^§ , and are more ethnoracially homogeneous than the broader US public (31). Imbalances in political participation also lead to overrepresentation of white, wealthier, more educated, and older voters within these relatively rural and poorer districts (33 ⇓⇓–36). These demographic and turnout patterns likely bias officials’ attitudes toward those of their more politically engaged constituents, and away from a nationally representative sample of residents.

Second, owing to their professional responsibilities and experiences, local officials may differ systematically from the citizens they represent. Because they manage their governments’ personnel and budgets, local officials are likely to be acutely aware of the resource constraints their communities face. Since rural communities tend to face tight budget constraints (37), the average local government official might be more sensitive than ordinary citizens to refugees’ impacts on schools, public transportation, and other public goods. In sum, local leaders not only represent a different demographic than the general public, but they are also likely to consider a different set of factors when evaluating refugee policy.

We contracted with CivicPulse to deploy an online survey experiment to a sample of local government officials in the United States in April 2020. The University of Pennsylvania’s Institutional Review Board (IRB) determined that the survey was eligible for IRB exemption; respondents were recruited through email and volunteered their participation.^¶ CivicPulse invited a sample of local officials randomly drawn from the population of all US town, municipal, and county elected officials serving populations above 1,000. Geographically, our 574 respondents are divided across 48 states. More than 60% serve in municipalities, with the rest split almost equally between townships and counties (Table 1). The localities represented by officials in our sample are modestly larger, more urban, more educated, and less conservative than the average locality in the United States. (See CivicPulse Omnibus Survey Reference Guide in SI Appendix.) However, as with the true population of US localities, the average locality represented in our sample is still much less urban, less educated, and more conservative than the population of the United States as a whole. Individual respondents display a similar pattern. Compared with the American public, our sample of local government officials is conservative-leaning, with 39% of respondents self-identifying as conservative, 30% as moderate, and 29% as liberal; 66% received at least a college degree, and 69% identify as male, with an average of 12 years of experience in government. (See SI Appendix, section 1 for a full description of survey administration, sampling process, and sample demographics.)

View this table:

Table 1.

Demographics of localities represented by sample

Experimental Design

We used a paired conjoint design to identify the causal effects of group-level attributes on local elected officials’ receptivity toward refugee resettlement. (See SI Appendix, section 2 for question wording, survey delivery, design, and randomization.) Though officials are not provided with the demographic characteristics of potential refugee groups when voting to allow refugee resettlement, basic information about past and current refugees is publicly available and informs public discourse surrounding refugee-resettlement decisions. As a result, this design presents respondents with a hypothetical that closely resembles their real-world decisions, while allowing us to identify key concerns that underlie respondents’ preferences.

Survey respondents first read a short prompt, which included a definition of the term “refugee,” and then viewed two randomly generated refugee-group profiles, labeled group A and group B. These profiles consisted of one randomly selected value for each of seven theoretically relevant attributes that might affect a local government official’s receptivity toward refugee-group resettlement: education, sponsorship status, language skills, religion, gender/family makeup, age, and region of origin. Respondents then indicated whether they were receptive to either group, group A only, group B only, or neither group settling in their community. We coded the responses to this question as a binary variable—Refugee Group Receptivity—which took a value of one if a given refugee group profile or “either group” was chosen and zero for other responses.^# We repeated this process two additional times, yielding three total paired-conjoint tasks for each respondent.

Compared with other immigration conjoint surveys (e.g., refs. 21, 24, and 38), our design is parsimonious. We chose this design to optimize for our specific target population and policy scenario. Since local elected officials are difficult to contact and time-constrained, we were limited in both the number of responses we could collect and the number of tasks we could ask of each individual. And, since we asked respondents to consider groups of refugees rather than individuals, including some standard conjoint attributes in our experiment would have presented respondents with an implausible hypothetical. We discuss our specific choices in more detail in SI Appendix, section 2, but we chose a design that respects respondents’ time and real-world policy experience, while allowing us to build on existing research.

Results

Conjoint Findings.

Our survey reveals that elected local officials generally support a broad range of refugee profiles (39). Of the 534 respondents who answered all three paired-profile questions, 51% indicated that they would accept any of the six profiles that they were presented with, compared with less than 13% who were unwilling to accept any of the six profiles. The remaining 36% of respondents varied substantially, with a roughly even distribution over the remaining set of values. (See SI Appendix, section 3 for further details.) Given the relatively conservative individual- and district-level demographics of our sample, this finding is noteworthy and offers a rejoinder to national-level opposition to refugee resettlement.

Fig. 1 reports the effect of each attribute value on the respondent’s probability of being receptive to a refugee group—the average marginal component effect (AMCE).^∥ Estimates were drawn from a regression model in which Refugee Group Receptivity was regressed on indicator variables for each level of each refugee group attribute, with baseline categories excluded and SEs clustered by respondent.**

Fig. 1.

Estimated effects of refugee profile attributes on local leaders’ refugee group receptivity. Dots mark point estimates, and lines indicate cluster-robust 95% CIs for the AMCE of each attribute value on the probability that respondents were receptive to a particular refugee group. The comparison category’s AMCE is the difference in the probability of receptivity between that category and the baseline category in parentheses (observations = 3,324; respondents = 574). NGO, nongovernmental organization.

We found strong evidence that US local government officials are more receptive to refugees with a greater potential for a positive economic impact. First, local officials were significantly more receptive to potential refugee groups with higher levels of education. Respondents were 7.7 and 8.3 percentage points more likely to support refugee groups with a high-school education and at least some college, respectively, compared with refugee groups with no formal schooling. This relationship may suggest that respondents view more educated refugees as more likely contributors to the local economy. Second, local elected officials were 7.9 percentage points more likely to support refugee groups sponsored by a regional or local business compared to refugees with no sponsor, which suggests that respondents were likely prioritizing economic integration for refugees. Direct sponsorship from a business group is likely associated with employment opportunities.^††

We also found evidence that local officials were more likely to support refugees they believe will integrate more easily into their communities. First, respondents were 9.6 percentage points more likely to support Christian refugees settling in their communities compared with Muslim refugees, which was the single largest effect we identified. While officials preferred agnostic refugees to Muslim refugees (3.4 percentage points more), this difference is not statistically significant at the 0.05 level. This finding suggests that respondents may hold in-group preferences for Christian refugees rather than out-group animus directed specifically at Muslim refugees, though future work should investigate this possibility further.^‡‡

Second, local officials were 4.4 and 8.8 percentage points more likely to support refugee groups primarily consisting of families and single women, respectively, compared with the baseline group of single men. This difference likely results from a perception that single men are more likely to participate in socially disruptive behavior (see also ref. 25). The support for family groups over single men suggests that respondents were focused on the societal fit of the group’s composition, rather than the potential fiscal burden of families alone.^§§

Local elected officials were also 5.8 and 4.8 percentage points more likely to support refugee groups with fluent or broken but functional English skills, compared with a baseline of very little to no English. Since officials likely associate refugees’ English proficiency both with refugees’ sociocultural fit and their ability to participate in the local economy, we cannot definitively associate this finding with a particular mechanism. However, officials clearly preferred English speakers to non-English speakers, even when refugees’ English skills were imperfect.

Local officials did not appear to possess a significant preference with respect to refugee age or regional origin. The null result with respect to age may be due to the age cutoff we used in our study. Since adults above or below age 40 can plausibly be within prime economic productivity years, if respondents prioritize refugee economic contributions, they may be roughly indifferent between these two categories (see, e.g., ref. 21). By contrast, our null result on regional origin may be due to respondent political knowledge. Holding all other attributes constant, local officials may not have sufficient information about specified regional groupings to express a preference.^¶¶

Open-Ended Responses.

We concluded our survey with an open-ended question, in which we asked local elected officials to identify the most important issues to consider when assessing how a group of refugees might settle into their community. Of the 574 respondents who answered at least one conjoint question, some 439 (76%) offered at least some response to this question. Since open-ended responses are necessarily unstructured, any analysis of their contents is exploratory by nature. However, examining open-ended responses can reinforce the findings we described in the previous sections and reveal the logic that underlies them.

To summarize our open-ended data, we nonexclusively coded each response based on two sets of categories. The first set consisted of our seven conjoint attributes. The second set consisted of four abstract categories: Economy, Social/Cultural, Immigration Process, and Public Order. These categories represented the four most prominent themes we identified by reading a sample of open-ended responses. All responses were double-coded, with disagreements adjudicated by a third coder. (See SI Appendix, section 4 for definitions, examples, intercoder reliability, and per-attribute summary statistics.)

The marginal histograms in Fig. 2 illustrate that respondents most frequently identified refugee language skills as a key area of concern, followed by education and sponsorship status. These three attributes reaffirmed the set of influential attributes identified in the conjoint portion of the survey. Surprisingly, gender/family group makeup and religion were not frequently mentioned, despite their effect in the conjoint portion of the survey. One possible explanation for this divergence is social-desirability bias. Though some respondents may be wary of primarily Muslim or male refugee groups, they may be more willing to express this preference in the conjoint portion of the survey than in an open-ended response (41).

Fig. 2.

Frequency and correlation of descriptive categories in open-ended responses. Counts of each attribute are shown in marginal histograms. Cell hues denote correlation between attribute pairs (n=574). See SI Appendix, section 4 for visualizations of attribute counts and cooccurrences. Imm., immigration; lang., language.

As implied by their professional responsibilities, local officials most frequently mentioned economic concerns in their open-ended responses (marginal histograms in Fig. 2). Nearly half of all open-ended comments contained language categorized as Economy, while approximately one-third were categorized as Social/Cultural. Since these categories are broad, the specific concerns within most of these categories varied substantially. For example, some 60% of respondents who raised economic concerns cited availability of jobs in their community, while 29% mentioned suitability of housing, transportation, or other physical infrastructure. A smaller number of respondents also referenced language assigned to the Immigration Process and Public Order categories, which suggests that these categories were less central to respondents’ attitudes.

Open-ended responses also allow us to explore context for our experimental findings. As the heatmap in Fig. 2 shows, mentions of education and sponsorship were most highly correlated with our Economy category, which suggests that some respondents evaluated these categories primarily through their association with refugees’ perceived economic contributions. By contrast, language-skill mentions were not strongly correlated with any of our abstract categories. This finding suggests that language plays a more complex role, which spans respondents’ perceptions of refugee contributions to the local economy, the social/cultural milieu, and public order.

Subgroup Analyses.

We also examined whether local officials’ refugee receptivity preferences differed by their counties’ partisanship, their own levels of interaction with non-Americans, and their localities’ populations. (We follow refs. 13 and 42 and use marginal means to compare subgroups instead of AMCEs. See SI Appendix, section 3 for subgroup variables, marginal mean plots, and F-test results for each subgroup.) First, we compared officials by whether their jurisdiction is located in a county that voted for Donald Trump in the 2016 Presidential election. We observed significant differences—ranging from 7.9 to 22.8 percentage points—between the two groups of respondents on every attribute level, with officials in Republican-voting areas exhibiting a lower level of support across all attributes. Officials in Republican-voting counties also expressed stronger preferences toward refugee-group religion and education. These respondents were more than 13 percentage points more likely to support Christian refugees compared to Muslim refugees and refugees with education at a high-school level or above compared to those with no formal education. By comparison, officials in Democratic-voting counties did not significantly discriminate based on refugees’ religious or educational backgrounds.

Second, local government officials who interact more frequently with non-US citizens were significantly more receptive to all attribute levels than officials who interact infrequently, with per-level differences ranging from 6.7 to 18.3 percentage points. This finding aligns with prior research, suggesting that personal interaction with immigrants moderates preferences (42). Third, officials in more populous localities expressed more support for most refugee-group attribute levels than officials in less-populous localities, though not all differences were significant.

Implications

Our analysis of local government officials’ receptivity toward refugees offers two primary conclusions. First, in line with the stated humanitarian focus of the US Refugee Admissions Program, we find that many local elected officials are supportive of refugee resettlement, regardless of refugee group attributes. Approximately half of all local policymakers favored refugee admission for all profiles viewed, and almost all favored refugee admission for at least some types of refugee groups. This pattern was strongest among officials in Democratic-voting counties, but officials in Republican-voting counties still supported over half of all refugee-group profiles they viewed. While our study focuses on the attitudes of local officials, future research should connect these results to more qualified patterns of support expressed by members of the general public (see, e.g., ref. 43).

One possible explanation for this limited level of attribute-based discrimination is social-desirability bias. However, if local officials are concerned with the social acceptability of their answers in an anonymous survey, they are also likely to modulate their positions in public-facing policy discussions. Though the answers to our survey might potentially overestimate respondents’ “sincere” support for refugee admissions, they provide a reasonable representation of respondents’ publicly expressed beliefs.

Second, we find that local policymakers are concerned with refugees’ ability to both fit with local values and participate in the local economy. This pattern is stronger among officials in Republican-voting than Democratic-voting constituencies on at least some attributes, including education and religious background, but is present among both groups. We cannot adjudicate decisively between respondents’ motives, on average, for preferring refugees with particular attributes. Such preferences could reflect apprehension toward refugees or concern for community capacity to provide refugees with essential resources. But, descriptive data from our open-ended follow-up question suggest that officials may be more strongly motivated by refugees’ perceived economic contributions than by refugees’ perceived community fit. This result matches our theoretical expectations regarding the relative importance of economic issues to local elected officials, though future experimental work should further investigate these mechanisms.

Local officials are crucial to refugee resettlement, and yet their attitudes have been understudied. Based on our findings, emphasizing business-sponsorship programs, skill development, language training,^## and explicit financial support to local communities likely represent high-impact public-engagement strategies for refugee-resettlement stakeholders seeking to bolster refugee acceptance. When federal or state funding for these programs is not available, refugee-resettlement agencies may find less-expensive interventions more sustainable, such as placing refugees to optimize employment opportunities (45) or highlighting how refugees make a positive net fiscal impact across levels of government.

We emphasize that concerns about economic contribution and community fit are neither legal nor normative reasons for rejecting refugees, who are eligible for resettlement once the United States determines that their claim of persecution in their home or other country is well-founded. Engagement strategies that focus on these factors should not undermine the humanitarian purposes of the US refugee resettlement program, which is designed to resettle the most vulnerable. We do not contest a robust right to apply for refugee status or seek asylum in the United States or any other country. However, our results do reveal policy-relevant information about the attitudes of an understudied and increasingly important group of refugee-resettlement gatekeepers. Overall, we find that officials across the political spectrum are receptive to a broad range of refugee groups, which offers a timely rejoinder to suspicion toward refugee resettlement prevalent in national US politics.

Data Availability.

The data reported in this paper have been deposited in the Harvard Dataverse (DOI: 10.7910/DVN/U9IWNR) (39).

Acknowledgments

We thank Sarah Bush, Amanda Cellini, Dan Hopkins, Yosaku Horiuchi, Michael Hotard, Erik Lin-Greenberg, Lama Mourad, Marianne Potvin, Stephanie Schwartz, Maraam Dwidar, the participants of the Perry World House and Browne Center seminars, and two reviewers for their helpful comments. This report does not represent the views of CivicPulse. This project was funded by Perry World House and the Carnegie Corporation of New York Grant G-F-18-56213 (575502) (to B.A.S.) and does not represent the views of either institution. All mistakes remain our own.

Footnotes

↵¹To whom correspondence may be addressed. Email: simmons3{at}law.upenn.edu or rbshaffer0{at}gmail.com.

Author contributions: L.E.P. and J.A.C. led on initial project development; R.S., L.E.P., J.A.C., and B.A.S. contributed to research design; J.A.C. led on design of the questionnaire; R.S. programmed the survey; R.S., L.E.P., and J.A.C. contributed to pilot and final data collection; R.S. and L.E.P. analyzed data; R.S. and L.E.P. led on writing the manuscript; and R.S., L.E.P., J.A.C., and B.A.S. all shaped the research, analysis, and writing.
Reviewers: K.B., University of California San Diego: and D.D.C., University of Pittsburgh.
The authors declare no competing interest.
↵*The Trump administration has since noted to the Fourth Circuit that the executive order does not provide a veto to local governments since it provides a “mechanism for the Secretary [of State] to resettle refugees in nonconsenting jurisdictions” (16).
↵^†Alternatively, local elected officials may be more skeptical of refugees who may compete for their constituents’ jobs. However, ref. 23 reports that fears of individual-labor competition have a limited influence over perceptions of potential migrants. We, therefore, view this possibility as unlikely.
↵^‡Members of the American public express little preference for migrants of any specific ethnicity or national origin (20), though results from Europe are more mixed (contrast refs. 21 and 24).
↵^§As of 2019, approximately two-thirds of Americans identified as Christian, with higher rates in rural and suburban communities overrepresented in our sample (31).
↵^¶This study qualifies for exemption to human subjects review under 45 CFR 46 101(b) (2). The University of Pennsylvania’s Human Subject Committee granted exemption on March 30, 2020 (UPenn HSC Protocol 842736). Prior to the receipt of the data, this design was registered with Evidence in Governance and Politics (20200417AC).
↵^#This design also acknowledges the set of preferences respondents are likely to possess. When asked whether they are receptive to two refugee groups, local elected officials can express opposition, support regardless of group attribute, or selective support for refugees with certain attributes. Our design offers all of these options, rather than forcing a relative choice between profiles.
↵^##Notably, less than half of all arriving refugees in the United States speak any English (44).
↵**The average marginal treatment effect of each component is identifiable under a set of assumptions likely to hold in a typical conjoint experiment (38). In addition, see SI Appendix, section 3 for the AMCE results table and marginal means results.
↵^∥All in-text results are based on unweighted models. In SI Appendix, section 1, we discuss this choice further. In SI Appendix, section 3, we present an alternative model that includes locality-level demographic weights as a robustness check.
↵^††Business sponsorships are not currently part of the refugee-resettlement process in the United States. However, we included the option in our profile design, since other countries, including Canada, allow for private sponsorship.
↵^‡‡Ref. 40 similarly finds that Americans favor humanitarian action to save Christian over Muslim victims of war as a result of in-group preference.
↵^§§This finding may also stem from our focus on refugee groups instead of individuals. Respondents may be particularly wary of groups consisting of largely single men, especially in cases where the hypothetical group is larger.
↵^¶¶As shown in SI Appendix, section 3, as a robustness check, we pooled all non-Middle East regions to compare whether there is a systematic bias against refugee groups from the Middle East. The difference between the Middle East and non-Middle East categories is not statistically significant at the 0.05 level. However, in the weighted version of the analysis presented in SI Appendix, section 3, respondents do show a statistically significant and lower level of support for refugee groups from the Middle East.
This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2015637117/-/DCSupplemental.

This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

View Abstract

References

↵
1. M. Jones-Correa
, All Immigration Is Local: Receiving Communities and Their Role in Successful Immigrant Integration (Center for American Progress, Washington, DC, 2011).
↵
1. K. Ebert,
2. D. G. Okamoto
, Social citizenship, integration and collective action: Immigrant civic engagement in the United States. Soc. Forces 91, 1267–1292 (2013).
OpenUrl CrossRef
↵
1. A. T. Field
, Burleigh County OKs refugee resettlement after passionate testimony. Bismarck Tribune, 10 December 2019. https://bismarcktribune.com/news/local/bismarck/burleigh-county-oks-refugee-resettlement-after-passionate-testimony/article_ea486800-89eb-506e-bdd9-02ef38e6f5a6.html. Accessed 4 February 2020.
↵
1. G. Kaul,
2. T. Nehi
, How every Minnesota county has voted on refugee resettlement so far. Minnesota Post, 16 January 2020. https://www.minnpost.com/politics-policy/2020/01/how-every-minnesota-county-has-voted-on-refugee-resettlement-so-far/. Accessed 4 February 2020.
↵
1. E. Tyree,
2. V. Jones,
3. K. Baylor
, Appomattox Co. passes resolution refusing to become refugee sanctuary. WSET, 16 December 2019. https://wset.com/news/local/appomattox-co-to-vote-on-resolution-refusing-to-become-refugee-sanctuary. Accessed 4 February 2020.
↵
1. J. Aguilar
, Colorado communities welcome refugee resettlement. Denver Post, January 8, 2020. https://www.denverpost.com/2020/01/08/refugee-resettlement-colorado-trump-executive-order/. Accessed 4 February 2020.
↵
1. J. Radford,
2. P. Connor
, “Canada now leads the world in refugee resettlement, surpassing the U.S.” (Tech. Rep., Pew Research Center, Washington, DC, 2019).
↵
1. A. F. Williamson
, Welcoming New Americans?: Local Governments and Immigrant Incorporation (University of Chicago Press, Chicago, IL, 2018).
↵
8 USC §1101(a)(42)(A) (1965).
↵
8 USC §1522(a) (2)(A) (1980).
↵
1. A. Brown,
2. T. Scribner
, Unfulfilled promises, future possibilities: The refugee resettlement system in the United States. J. Migration Hum. Security 2, 101–120 (2014).
OpenUrl
↵
1. D. J. Trump
, Executive order 13888 of September 26, 2019, enhancing state and local involvement in refugee resettlement. Federal Register 84(190):52355–52356.
↵
1. J. Rose
, Advocates challenge Trump administration plan to let states and towns block refugees. NPR, 21 November 2019. https://www.npr.org/2019/11/21/781795867/advocates-challenge-trump-administration-plan-to-let-states-and-towns-block-refu. Accessed 19 April 2020.
↵
1. M. Jordan
, Judge halts Trump policy that allows states to bar refugees. New York Times, 15 January 2020. https://www.nytimes.com/2020/01/15/us/refugees-states-trump.html. Accessed 19 April 2020.
↵
1. S. Monyak
, Md. judge says Trump can’t let states refuse refugees. Law360 (2020). https://www.law360.com/articles/1234701/md-judge-says-trump-can-t-let-states-refuse-refugees. Accessed 19 April 2020.
↵
1. N. Dreid
, Gov’t tells Fourth Circ. refugee order gives states input not veto. Law360 (2020). https://www.law360.com/articles/1257128/gov-t-tells-4th-circ-refugee-order-gives-states-input-not-veto. Accessed 19 April 2020.
↵
1. M. Kunzelman
, Feds appeal Order blocking Trump refugee resettlement limit. Associated Press, 12 February 2020. https://apnews.com/article/f596690f189d2884779da2da12aa2e3ca. Accessed 19 April 2020.
↵
1. Lutheran Immigration and Refugee Service
, “Latest developments on refugee resettlement consent” (Tech. Rep., Lutheran Immigration and Refugee Service, Baltimore, MD, 2020).
↵
1. S. Monyak
, Texas is first to refuse refugees under Trump order. Law360 (2020). https://www.law360.com/articles/1233413/texas-is-first-to-refuse-refugees-under-trump-order. Accessed 19 April 2020.
↵
1. J. Hainmueller,
2. D. J. Hopkins
, The hidden American immigration consensus: A conjoint analysis of attitudes toward immigrants. Am. J. Polit. Sci. 59, 529–548 (2015).
OpenUrl CrossRef
↵
1. K. Bansak,
2. J. Hainmueller,
3. D. Hangartner
, How economic, humanitarian, and religious concerns shape European attitudes toward asylum seekers. Science 354, 217–222 (2016).
OpenUrl Abstract/FREE Full Text
↵
1. C. L. Adida,
2. A. Lo,
3. M. R. Platas
, Americans preferred Syrian refugees who are female, English-speaking, and Christian on the eve of Donald Trump’s election. PloS One 14, e0222504 (2019).
OpenUrl
↵
1. J. Citrin,
2. D. P. Green,
3. C. Muste,
4. C. Wong
, Public opinion toward immigration reform: The role of economic motivations. J. Polit. 59, 858–881 (1997).
OpenUrl CrossRef
↵
1. K. Clayton,
2. J. Ferwerda,
3. Y. Horiuchi
, Exposure to immigration and admission preferences: Evidence from France. Polit. Behav., doi:10.1007/s11109-019-09550-z (2019).
OpenUrl CrossRef
↵
1. D. G. Ward
, Public attitudes toward young immigrant men. Am. Polit. Sci. Rev. 113, 264–269 (2019).
OpenUrl
↵
1. D. D. Choi,
2. M. Poertner,
3. N. Sambanis
, Parochialism, social norms, and discrimination against immigrants. Proc. Natl. Acad. Sci. U.S.A. 116, 16274–16279 (2019).
OpenUrl Abstract/FREE Full Text
↵
1. B. Altemeyer
, Dogmatic behavior among students: Testing a new measure of dogmatism. J. Soc. Psychol. 142, 713–721 (2002).
OpenUrl CrossRef PubMed
↵
1. R. C. Carpenter
, “Women, children and other vulnerable groups”: Gender, strategic frames and the protection of civilians as a transnational issue. Int. Stud. Q. 49, 295–334 (2005).
OpenUrl CrossRef
↵
1. L. Mourad
, “Open borders, local closures: Decentralization and the politics of local responses to the Syrian refugee influx in Lebanon”, Doctoral dissertation, University of Toronto, Toronto, ON, Canada (2019).
↵
1. P. Mohanty,
2. R. Shaffer
, Messy data, robust inference? Navigating obstacles to inference with bigKRLS. Polit. Anal. 27, 127–144 (2019).
OpenUrl
↵
1. B. A. Lee,
2. G. Sharp
, Ethnoracial diversity across the rural-urban continuum. Ann. Am. Acad. Polit. Soc. Sci. 672, 26–46 (2017).
OpenUrl
↵
1. Pew Research Center
, “In U.S., decline of Christianity continues at rapid pace” (Tech. Rep., Pew Research Center, Washington, DC, October 17, 2019).
↵
1. J. Trounstine
, Representation and accountability in cities. Annu. Rev. Polit. Sci. 13, 407–423 (2010).
OpenUrl
↵
1. Z. Hajnal,
2. J. Trounstine
, Identifying and understanding perceived inequities in local politics. Polit. Res. Q. 67, 56–70 (2014).
OpenUrl CrossRef
↵
1. Z. Hajnal,
2. J. Trounstine
, What underlies urban politics? Race, class, ideology, partisanship, and the urban vote. Urban Aff. Rev. 50, 63–99 (2014).
OpenUrl CrossRef
↵
1. J. Hooker,
2. A. B. Tillery, Jr.
1. Z. L. Hajnal,
2. J. L. Trounstine
, “Race and class inequality in local politics” in The Double Bind: The Politics of Racial & Class Inequalities in the Americas, J. Hooker, A. B. Tillery, Jr., Eds. (American Political Science Association, Washington, DC, 2016).
↵
1. G. Propheter
, An exploration of revenue structure characteristics in rural municipalities. State Local Govern. Rev. 51, 46–56 (2019).
OpenUrl
↵
1. J. Hainmueller,
2. D. J. Hopkins,
3. T. Yamamoto
, Causal inference in conjoint analysis: Understanding multidimensional choices via stated preference experiments. Polit. Anal. 22, 1–30 (2014).
OpenUrl CrossRef
↵
1. R. Shaffer,
2. L. E. Pinson,
3. J. A. Chu,
4. B. A. Simmons
, “Replication data for: Local elected officials’ receptivity to refugee resettlement in the United States.” Harvard Dataverse. https://doi.org/10.7910/DVN/U9IWNR. Deposited 27 September 2020.
↵
1. J. Chu,
2. C. Lee
, Race, religion, and American support for humanitarian intervention (Stanford University, Stanford, CA, 2020).
↵
1. Y. Horiuchi,
2. Z. D. Markovich,
3. T. Yamamoto
, Does conjoint analysis mitigate social desirability bias? (MIT Political Science Department Research Paper No. 2018-05, Massachusetts Institute of Technology, Cambridge, MA, 2020).
↵
1. T. J. Leeper,
2. S. B. Hobolt,
3. J. Tilley
, Measuring subgroup preferences in conjoint experiments. Polit. Anal. 28, 207–221 (2020).
OpenUrl
↵
1. J. Ferwerda,
2. D. Flynn,
3. Y. Horiuchi
, Explaining opposition to refugee resettlement: The role of NIMBYism and perceived threats. Sci. Adv. 3, e1700812 (2017).
OpenUrl FREE Full Text
↵
1. R. Capps et al.
, The integration outcomes of U.S. refugees: Successes and challenges (Tech. Rep., Migration Policy Institute, Washington, DC, 2015).
↵
1. K. Bansak et al.
, Improving refugee integration through data-driven algorithmic assignment. Science 359, 325–329 (2018).
OpenUrl Abstract/FREE Full Text

Article Alerts

Email Article

Citation Tools

Request Permissions

Proceedings of the National Academy of Sciences: 117 (50)

Table of Contents

Submit

Article Classifications

Social Sciences
Political Sciences

[1] ↵
M. Jones-Correa
, All Immigration Is Local: Receiving Communities and Their Role in Successful Immigrant Integration (Center for American Progress, Washington, DC, 2011).

[2] M. Jones-Correa

[3] ↵
K. Ebert,
D. G. Okamoto
, Social citizenship, integration and collective action: Immigrant civic engagement in the United States. Soc. Forces 91, 1267–1292 (2013).
OpenUrl CrossRef

[4] K. Ebert,

[5] D. G. Okamoto

[6] ↵
A. T. Field
, Burleigh County OKs refugee resettlement after passionate testimony. Bismarck Tribune, 10 December 2019. https://bismarcktribune.com/news/local/bismarck/burleigh-county-oks-refugee-resettlement-after-passionate-testimony/article_ea486800-89eb-506e-bdd9-02ef38e6f5a6.html. Accessed 4 February 2020.

[7] A. T. Field

[8] ↵
G. Kaul,
T. Nehi
, How every Minnesota county has voted on refugee resettlement so far. Minnesota Post, 16 January 2020. https://www.minnpost.com/politics-policy/2020/01/how-every-minnesota-county-has-voted-on-refugee-resettlement-so-far/. Accessed 4 February 2020.

[9] G. Kaul,

[10] T. Nehi

[11] ↵
E. Tyree,
V. Jones,
K. Baylor
, Appomattox Co. passes resolution refusing to become refugee sanctuary. WSET, 16 December 2019. https://wset.com/news/local/appomattox-co-to-vote-on-resolution-refusing-to-become-refugee-sanctuary. Accessed 4 February 2020.

[12] E. Tyree,

[13] V. Jones,

[14] K. Baylor

[15] ↵
J. Aguilar
, Colorado communities welcome refugee resettlement. Denver Post, January 8, 2020. https://www.denverpost.com/2020/01/08/refugee-resettlement-colorado-trump-executive-order/. Accessed 4 February 2020.

[16] J. Aguilar

[17] ↵
J. Radford,
P. Connor
, “Canada now leads the world in refugee resettlement, surpassing the U.S.” (Tech. Rep., Pew Research Center, Washington, DC, 2019).

[18] J. Radford,

[19] P. Connor

[20] ↵
A. F. Williamson
, Welcoming New Americans?: Local Governments and Immigrant Incorporation (University of Chicago Press, Chicago, IL, 2018).

[21] A. F. Williamson

[22] ↵
8 USC §1101(a)(42)(A) (1965).

[23] ↵
8 USC §1522(a) (2)(A) (1980).

[24] ↵
A. Brown,
T. Scribner
, Unfulfilled promises, future possibilities: The refugee resettlement system in the United States. J. Migration Hum. Security 2, 101–120 (2014).
OpenUrl

[25] A. Brown,

[26] T. Scribner

[27] ↵
D. J. Trump
, Executive order 13888 of September 26, 2019, enhancing state and local involvement in refugee resettlement. Federal Register 84(190):52355–52356.

[28] D. J. Trump

[29] ↵
J. Rose
, Advocates challenge Trump administration plan to let states and towns block refugees. NPR, 21 November 2019. https://www.npr.org/2019/11/21/781795867/advocates-challenge-trump-administration-plan-to-let-states-and-towns-block-refu. Accessed 19 April 2020.

[30] J. Rose

[31] ↵
M. Jordan
, Judge halts Trump policy that allows states to bar refugees. New York Times, 15 January 2020. https://www.nytimes.com/2020/01/15/us/refugees-states-trump.html. Accessed 19 April 2020.

[32] M. Jordan

[33] ↵
S. Monyak
, Md. judge says Trump can’t let states refuse refugees. Law360 (2020). https://www.law360.com/articles/1234701/md-judge-says-trump-can-t-let-states-refuse-refugees. Accessed 19 April 2020.

[34] S. Monyak

[35] ↵
N. Dreid
, Gov’t tells Fourth Circ. refugee order gives states input not veto. Law360 (2020). https://www.law360.com/articles/1257128/gov-t-tells-4th-circ-refugee-order-gives-states-input-not-veto. Accessed 19 April 2020.

[36] N. Dreid

[37] ↵
M. Kunzelman
, Feds appeal Order blocking Trump refugee resettlement limit. Associated Press, 12 February 2020. https://apnews.com/article/f596690f189d2884779da2da12aa2e3ca. Accessed 19 April 2020.

[38] M. Kunzelman

[39] ↵
Lutheran Immigration and Refugee Service
, “Latest developments on refugee resettlement consent” (Tech. Rep., Lutheran Immigration and Refugee Service, Baltimore, MD, 2020).

[40] Lutheran Immigration and Refugee Service

[41] ↵
S. Monyak
, Texas is first to refuse refugees under Trump order. Law360 (2020). https://www.law360.com/articles/1233413/texas-is-first-to-refuse-refugees-under-trump-order. Accessed 19 April 2020.

[42] S. Monyak

[43] ↵
J. Hainmueller,
D. J. Hopkins
, The hidden American immigration consensus: A conjoint analysis of attitudes toward immigrants. Am. J. Polit. Sci. 59, 529–548 (2015).
OpenUrl CrossRef

[44] J. Hainmueller,

[45] D. J. Hopkins

[46] ↵
K. Bansak,
J. Hainmueller,
D. Hangartner
, How economic, humanitarian, and religious concerns shape European attitudes toward asylum seekers. Science 354, 217–222 (2016).
OpenUrl Abstract/FREE Full Text

[47] K. Bansak,

[48] J. Hainmueller,

[49] D. Hangartner

[50] ↵
C. L. Adida,
A. Lo,
M. R. Platas
, Americans preferred Syrian refugees who are female, English-speaking, and Christian on the eve of Donald Trump’s election. PloS One 14, e0222504 (2019).
OpenUrl

[51] C. L. Adida,

[52] A. Lo,

[53] M. R. Platas

[54] ↵
J. Citrin,
D. P. Green,
C. Muste,
C. Wong
, Public opinion toward immigration reform: The role of economic motivations. J. Polit. 59, 858–881 (1997).
OpenUrl CrossRef

[55] J. Citrin,

[56] D. P. Green,

[57] C. Muste,

[58] C. Wong

[59] ↵
K. Clayton,
J. Ferwerda,
Y. Horiuchi
, Exposure to immigration and admission preferences: Evidence from France. Polit. Behav., doi:10.1007/s11109-019-09550-z (2019).
OpenUrl CrossRef

[60] K. Clayton,

[61] J. Ferwerda,

[62] Y. Horiuchi

[63] ↵
D. G. Ward
, Public attitudes toward young immigrant men. Am. Polit. Sci. Rev. 113, 264–269 (2019).
OpenUrl

[64] D. G. Ward

[65] ↵
D. D. Choi,
M. Poertner,
N. Sambanis
, Parochialism, social norms, and discrimination against immigrants. Proc. Natl. Acad. Sci. U.S.A. 116, 16274–16279 (2019).
OpenUrl Abstract/FREE Full Text

[66] D. D. Choi,

[67] M. Poertner,

[68] N. Sambanis

[69] ↵
B. Altemeyer
, Dogmatic behavior among students: Testing a new measure of dogmatism. J. Soc. Psychol. 142, 713–721 (2002).
OpenUrl CrossRef PubMed

[70] B. Altemeyer

[71] ↵
R. C. Carpenter
, “Women, children and other vulnerable groups”: Gender, strategic frames and the protection of civilians as a transnational issue. Int. Stud. Q. 49, 295–334 (2005).
OpenUrl CrossRef

[72] R. C. Carpenter

[73] ↵
L. Mourad
, “Open borders, local closures: Decentralization and the politics of local responses to the Syrian refugee influx in Lebanon”, Doctoral dissertation, University of Toronto, Toronto, ON, Canada (2019).

[74] L. Mourad

[75] ↵
P. Mohanty,
R. Shaffer
, Messy data, robust inference? Navigating obstacles to inference with bigKRLS. Polit. Anal. 27, 127–144 (2019).
OpenUrl

[76] P. Mohanty,

[77] R. Shaffer

[78] ↵
B. A. Lee,
G. Sharp
, Ethnoracial diversity across the rural-urban continuum. Ann. Am. Acad. Polit. Soc. Sci. 672, 26–46 (2017).
OpenUrl

[79] B. A. Lee,

[80] G. Sharp

[81] ↵
Pew Research Center
, “In U.S., decline of Christianity continues at rapid pace” (Tech. Rep., Pew Research Center, Washington, DC, October 17, 2019).

[82] Pew Research Center

[83] ↵
J. Trounstine
, Representation and accountability in cities. Annu. Rev. Polit. Sci. 13, 407–423 (2010).
OpenUrl

[84] J. Trounstine

[85] ↵
Z. Hajnal,
J. Trounstine
, Identifying and understanding perceived inequities in local politics. Polit. Res. Q. 67, 56–70 (2014).
OpenUrl CrossRef

[86] Z. Hajnal,

[87] J. Trounstine

[88] ↵
Z. Hajnal,
J. Trounstine
, What underlies urban politics? Race, class, ideology, partisanship, and the urban vote. Urban Aff. Rev. 50, 63–99 (2014).
OpenUrl CrossRef

[89] Z. Hajnal,

[90] J. Trounstine

[91] ↵
J. Hooker,
A. B. Tillery, Jr.
Z. L. Hajnal,
J. L. Trounstine
, “Race and class inequality in local politics” in The Double Bind: The Politics of Racial & Class Inequalities in the Americas, J. Hooker, A. B. Tillery, Jr., Eds. (American Political Science Association, Washington, DC, 2016).

[92] J. Hooker,

[93] A. B. Tillery, Jr.

[94] Z. L. Hajnal,

[95] J. L. Trounstine

[96] ↵
G. Propheter
, An exploration of revenue structure characteristics in rural municipalities. State Local Govern. Rev. 51, 46–56 (2019).
OpenUrl

[97] G. Propheter

[98] ↵
J. Hainmueller,
D. J. Hopkins,
T. Yamamoto
, Causal inference in conjoint analysis: Understanding multidimensional choices via stated preference experiments. Polit. Anal. 22, 1–30 (2014).
OpenUrl CrossRef

[99] J. Hainmueller,

[100] D. J. Hopkins,

[101] T. Yamamoto

[102] ↵
R. Shaffer,
L. E. Pinson,
J. A. Chu,
B. A. Simmons
, “Replication data for: Local elected officials’ receptivity to refugee resettlement in the United States.” Harvard Dataverse. https://doi.org/10.7910/DVN/U9IWNR. Deposited 27 September 2020.

[103] R. Shaffer,

[104] L. E. Pinson,

[105] J. A. Chu,

[106] B. A. Simmons

[107] ↵
J. Chu,
C. Lee
, Race, religion, and American support for humanitarian intervention (Stanford University, Stanford, CA, 2020).

[108] J. Chu,

[109] C. Lee

[110] ↵
Y. Horiuchi,
Z. D. Markovich,
T. Yamamoto
, Does conjoint analysis mitigate social desirability bias? (MIT Political Science Department Research Paper No. 2018-05, Massachusetts Institute of Technology, Cambridge, MA, 2020).

[111] Y. Horiuchi,

[112] Z. D. Markovich,

[113] T. Yamamoto

[114] ↵
T. J. Leeper,
S. B. Hobolt,
J. Tilley
, Measuring subgroup preferences in conjoint experiments. Polit. Anal. 28, 207–221 (2020).
OpenUrl

[115] T. J. Leeper,

[116] S. B. Hobolt,

[117] J. Tilley

[118] ↵
J. Ferwerda,
D. Flynn,
Y. Horiuchi
, Explaining opposition to refugee resettlement: The role of NIMBYism and perceived threats. Sci. Adv. 3, e1700812 (2017).
OpenUrl FREE Full Text

[119] J. Ferwerda,

[120] D. Flynn,

[121] Y. Horiuchi

[122] ↵
R. Capps et al.
, The integration outcomes of U.S. refugees: Successes and challenges (Tech. Rep., Migration Policy Institute, Washington, DC, 2015).

[123] R. Capps et al.

[124] ↵
K. Bansak et al.
, Improving refugee integration through data-driven algorithmic assignment. Science 359, 325–329 (2018).
OpenUrl Abstract/FREE Full Text

[125] K. Bansak et al.

Main menu

User menu

Search

New Research In

Local elected officials’ receptivity to refugee resettlement in the United States

Significance

Abstract

Policy Context

A Local Government Perspective on Refugees

Determinants of Officials’ Receptivity Toward Refugees.

Examining Elected Local Officials.

Experimental Design

Results

Conjoint Findings.

Open-Ended Responses.

Subgroup Analyses.

Implications

Data Availability.

Acknowledgments

Footnotes

References

Citation Manager Formats

Article Classifications

You May Also be Interested in

Similar Articles

Articles

PNAS Portals

Information

Main menu

User menu

Search

New Research In

Physical Sciences

Featured Portals

Articles by Topic

Social Sciences

Featured Portals

Articles by Topic

Biological Sciences

Featured Portals

Articles by Topic

Local elected officials’ receptivity to refugee resettlement in the United States

Significance

Abstract

Policy Context

A Local Government Perspective on Refugees

Determinants of Officials’ Receptivity Toward Refugees.

Examining Elected Local Officials.

Experimental Design

Results

Conjoint Findings.

Open-Ended Responses.

Subgroup Analyses.

Implications

Data Availability.

Acknowledgments

Footnotes

References

Citation Manager Formats

Sign up for Article Alerts

Article Classifications

Jump to section

You May Also be Interested in

Similar Articles

Articles

PNAS Portals

Information