Existing research argues that refugee inflows may increase the risk of domestic conflict, particularly civil war that, by definition, involves the state as an actor. However, many of the postulated mechanisms linking refugees to a higher risk of such conflict pertain to tensions with locals, which do not necessarily involve any grievances against government authorities. We contend that it is more likely to identify an association between refugees and non-state actor violence , that is, armed violence between organized non-state groups, neither of which pertains to the state. We also claim that the extent to which refugees are associated with a higher likelihood of non-state conflict depends on the capacity of governments to manage and mitigate risks. We report evidence that refugee populations can be linked to an increased risk of non-state conflict, as well as for a mitigating effect of state capacity on the risk of non-state conflicts in the presence of refugees. We do not find a clear effect of refugee populations on civil war, suggesting that the link depends on existing conflict cleavages relevant to mobilizing refugees or locals. Our research helps to shed light on the relevant security consequences of managing refugee populations. Despite the common arguments portraying refugees as security risks in developed countries, the risk of non-state conflict applies primarily to weak states that have been forced to shoulder a disproportionate burden in hosting refugees.

Introduction A large literature has emerged suggesting that refugees can be associated with a higher risk of violent civil conflict within hosting countries. Most of this research focuses on conventional civil war or on how refugees are likely to exacerbate tensions within countries that in turn are more likely to lead to violent disputes involving the state. For example, the ‘refugee-warrior thesis’ highlights how refugees in camps could be mobilized to participate in violent uprisings against a government, with the 1970 Black September uprising of Palestinian refugees in Jordan as the canonical example (see Zolberg, Suhrke & Aguayo, 1989). However, there are also many examples where refugee flows have not been associated with violent conflict at all, or where refugees may have been linked to other forms of violence, distinct from conventional civil war. In particular, numerous events involving violence are not initiated by refugees, are not directed at the state, and do not involve the government as an actor in any meaningful way (see also Gleditsch & Bartusevičius, forthcoming). In one of the largest contemporary refugee crises in South-East Asia, for example, an estimated 40,000 Rohingya have fled violent persecution in Myanmar and sought refuge in India by mid-2017. Many Rohingya in India have become victims of violent persecution from hostile local populations. In early 2017, the Jammu and Kashmir National Panthers Party in northwest India launched a series of demonstrations calling for the Rohingya to be expelled from the province. And beyond simply exerting voice or raising political demands, there have been many threats to use violence as well as reports of violent attacks against Rohingya refugees. However, these violent events do not fit the traditional definition of civil war or the template of the ‘refugee-warrior thesis’ (see Zolberg, Suhrke & Aguayo, 1989), which focus on security risks arising from refugees taking up arms against the government in response to marginalization and immiseration. Although some have voiced concerns over the potential for radicalization and recruitment among the Rohingya refugees, there is no evidence that these have joined insurgent groups in Kashmir and there appears to be little mobilization over the common Muslim religious identities shared between the Indian Muslims and the Rohingya. Moreover, the violence that has been perpetrated against Rohingya refugees is neither carried out nor implicitly endorsed by the government. The case of the Rohingya in India illustrates the need to look beyond the effects of refugees on conventional conflict and consider the possible implications for non-state violence, that is, violence between organized armed groups, neither of which pertains to the state (Melander, Pettersson & Themnér, 2016; Sundberg, Eck & Kreutz, 2012). Although different forms of (organized) violence may share some common underlying causes and can occur simultaneously (see e.g. Cunningham & Lemke, 2013), there are also important differences. Non-state conflict involves fighting among groups outside of and not affiliated with the state that are identified by shared communal identities, and are often fought over land distribution or access to natural resources, or are a result of socio-economic inequalities (Fjelde & Østby, 2014). Partially because of data availability, however, existing quantitative literature has largely tested theories about refugees and violence exclusively using data on conflict involving the state.1 Qualitative research has acknowledged other forms of violence more systematically. Onoma (2013), for example, contributes in significant ways to our understanding of the refugee–conflict nexus by focusing on refugees as victims of violence. In light of this, there has been a reported increase in threats against refugees in European countries that have hosted larger numbers of refugees from the Syrian civil war. However, in countries such as Germany, concerted efforts by the police have been undertaken against people suspected of planning violent responses, and there has been considerable investment in efforts to monitor social media and prevent the diffusion of such acts. In this article, we build on previous studies by, for example, Onoma (2013) on refugee populations and the risk of non-state violence and consider the potential mitigating influence of state capacity. We first take stock of the literature on the security implications of refugees and the dire predictions that some have derived from the current refugee crisis based on their interpretation of existing research. We then outline the key arguments giving reasons why refugees may be associated with a higher risk of non-state violence, as well as the mechanism through which governments can intervene and mitigate risks. We contend that the prospects for such state interventions, if supported by a sufficiently large amount of state capacity, can potentially moderate how refugee populations are associated with non-state conflict. We empirically test these claims, combining the Uppsala Conflict Data Program’s (UCDP) Non-State Conflict Dataset (Melander, Pettersson & Themnér, 2016; Sundberg, Eck & Kreutz, 2012) with data on refugee populations from the United Nations High Commissioner for Refugees (UNHCR) Population Statistics Reference Database.2 Our analyses show that a larger number of refugees can be associated with a higher non-state conflict risk, but not a higher risk of civil war, that is, state-based conflict. We also report evidence for the moderating effect of state capacity. Our research has important implications for scholarship and policy. On one hand, we improve our understanding of how postulated drivers of intrastate conflict are related to specific types of violence (or not), as we show that refugees are less likely to be related to ‘traditional’ civil wars in their destination country, but could be associated with intrastate violence among non-state actors. On the other hand, we also help clarify the Download Open in new tab Download in PowerPoint relevant security consequences of hosting refugees as well as why certain fears of widespread civil war are less likely to be borne out. Our findings provide insights that can inform policymakers and public responses to address the security implications stemming from refugee populations. In particular, they can help to develop a more adequate understanding of the relevant concerns and challenges to states in dealing with the serious refugee crisis playing out at the present time. Our analysis lends little support to the alarmist calls for restricting refugee access in developed countries on security grounds, and the risk of non-state conflict primarily applies to the developing countries that face a disproportionate impact of the current refugee crisis and also have the least capacity to cope with large refugee populations.

Non-state violence, refugees, and state capacity Refugees and non-state violence As discussed above, most of the existing literature concentrates on violent conflict that directly targets the state either over control of the government or for territorial secession. We focus on how tensions between refugees and the local population could also lead to non-state violence in cases where conventional civil war may be less likely. Non-state conflict and refugees are plausibly linked through various mechanisms that relate to the costs on a host society (see also Savun & Gineste, 2017). These mechanisms may also suggest that refugees can become ‘targets’ of non-state violence. And in other cases, we might observe an increase in the risk of local groups fighting each other, where refugees themselves are not directly involved in violent conflict. In what follows, we provide an argument for the macro-level effect of refugees on non-state violence. The perceived economic burden placed by immigrants on the local population’s welfare seems to be one of the main drivers of hostility toward refugees (Preston, 2014). In fact, a larger refugee population can intensify existing problems associated with economic scarcity (Dancygier, 2010). This is consistent with the work of Homer-Dixon (2010), who contends that the likelihood of violence increases with scarce resources. Alternatively, as people migrate to other areas to escape resource scarcity, we may see clashes with native populations over resource access or the distribution of goods. Refugees also compete with locals over limited public services such as food assistance, housing support, or medical services. Indeed, the very presence of refugees may generate grievances and tensions between natives and the refugees – especially if the former see refugees as a threat or feel that refugees are depriving the local population of what is rightfully theirs (Chambers, 1986; Weiner, 1992; Savun & Gineste, 2017; Fjelde & von Uexkull, 2012).3 Overall, this discussion leads to the formulation of our first, unconditional hypothesis: Hypothesis 1: The risk of non-state violence increases with the number of refugees in a country. The mediating effect of state capacity Without ignoring the humanitarian and moral aspects of the plight of refugees, host states could experience difficulties in trying to manage or accommodate refugees, which may generate popular grievances and violence against refugees. It seems plausible that the negative externality accompanying hosting refugee populations will be more severe and the ability to control violence lower in weak states, that is, countries that are characterized by a low level of state capacity. In the following, we argue that state capacity mitigates the conflict-generating aspects of refugee populations. To this end, we focus on the administrative capacity of a high-capacity state to develop and disseminate information and (re-)distribute goods and services in an effective manner (see Hendrix, 2010). We see the strength of the bureaucratic apparatus as the most important aspect of state capacity; in particular, we look at the quality of public and civil service, including its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. Hence, we focus on the ‘economic capacity’ to provide public goods and, as a result, to reduce the grievances of the population rather than the ‘security capacity’ to deter violence directly. Particularly important for our purposes, Adamson (2006: 176) shows that refugees can ‘overwhelm a state’s capacity to provide public services and can lead to conflicts over resources’. Most of the world’s refugees are hosted in poor countries where already rather weak state institutions are put under additional pressure.4 In the words of Dowty & Loescher (1996: 47), ‘the cost falls disproportionately on nations least able to afford it, where the presence of large impoverished refugee populations further strains resources and perpetuates the poverty of the host nation. Refugees need water, food, fuel, and land; the environmental impact in already-marginal areas may be devastating. […] They require social services beyond those provided by international agencies, putting further strain on domestic structures that may already have been inadequate’. At the same time, Sundberg, Eck & Kreutz (2012) show that developing countries, in particular in Africa, see the largest number of non-state conflicts, suggesting that existing pressures on weak states are likely to increase as a large number of refugees can worsen the competition over already scarce resources. Although low-capacity states have limited ability to provide services or ensure sustainable livelihoods, they are particularly poorly suited to manage pressures arising from refugees. Not surprisingly, states ‘with high levels of institutional capacity are in a much better position to adapt to this new environment than are weak or failing states’ (Adamson, 2006: 176). We claim accordingly that the quality of state institutions is likely to play a major role in shaping and addressing possible tensions between refugees and locals, and preventing instances of non-state violence in the presence of large refugee populations. According to the IMF (2016), the impact of refugees on medium and long-term economic prospects hinges on how countries manage to integrate refugees in the labor market (see also Maystadt & Verwimp, 2014). Successfully addressing the challenges associated with refugees and responding to their needs effectively will be more difficult in societies with inadequate social welfare provision and no income support or unemployment benefits. All this depends on the quality and professionalism of the state apparatus – a key feature of our understanding of state capacity. Countries with more professional institutions are likely to be in a better position to minimize the negative social and economic aspects linked to refugee populations. In turn, this should reduce the risk of tensions between refugees and locals and the likelihood that this will foster non-state violence. As an illustrative example, consider how states differ in their ability to factor in the challenges associated with the arrival of refugees. According to the OECD (Organisation for Economic Co-operation and Development, 2015: 13), for example, European countries have long established introduction programs for refugees, generally related to language training, but also with a focus on labor-market integration, which is vital for ‘migrants’ economic independence, and a precondition for a positive economic impact of migration’. Nations with strong state capacity could even reap many benefits from access to a greater pool of skilled workers, which might promote technological innovation, stimulate economic growth, and redistribute gains to compensate potential losers. Immigrants are carriers of a variety of ideas and abilities, and the economic benefits of increased openness to immigration will tend to outweigh the economic costs, at least in the aggregate. Thielemann (2018) suggests here that when larger and more capable states accept large numbers of asylum seekers, they make a significant contribution to the provision of regional stability by reducing the scale of unregulated movement and stabilizing volatile situations. Ultimately, the degree to which organized non-state actors are involved in episodes of violence depends on the level of state capacity. In light of this discussion, although refugee flows can generate economic strains and pressures for violence, states with a high level of economic capacity can offer a sufficient level of public good provision and an effective economic and social integration so as to ensure peaceful cohabitation. Where the state is weak, however, there is little to prevent tensions between refugees and the local populations from emerging.5 We thus expect that any effect of refugee populations on a higher risk of non-state violence should be conditional on state capacity. Support for integration, access to social services, and better infrastructure can reduce the tensions between refugees and locals – and, thus, the risk of non-state violence. Hypothesis 2: State capacity conditions the effect of refugees on the risk of non-state violence.

Research design Data, dependent variables, and methodology We constructed a time-series cross-section dataset containing all countries between 1989 and 2015, using the country-year as the unit of analysis. The time period is determined by the data availability for our variables. A central aspect of our theoretical argument is that many of the mechanisms through which refugees are meant to increase the risk of conflict include tensions with locals. But this does not entail clear grievances against the state authorities as such, especially if local populations see refugees as responsible. An implication of this claim is that refugee populations are likely to be associated with non-state conflict, but not necessarily with a higher likelihood of a full-scale civil war involving the host country’s government as a belligerent. Against this background, in a first step, we conduct an empirical analysis where we jointly model peace, non-state conflict, and civil war as separate outcomes in a multinomial logistic regression framework. The goal of this analysis is to show that there may not be a significant or substantive influence of refugees on civil conflict as the outcome, at least in the absence of a cleavage for mobilization exacerbated by refugee inflows. After having established this finding, we then concentrate on non-state conflict as the outcome with logistic regression models. The first dependent variable for the multinomial regression analysis codes for each country-year whether there was no conflict at all (0; we use this outcome value as the baseline category), non-state conflict (1), or civil conflict (2). Our data source for value 1 of that item (and the binary dependent variable described below) is the UCDP Non-State Conflict Dataset (Sundberg, Eck & Kreutz, 2012; Melander, Pettersson & Themnér, 2016), which defines non-state conflicts as ‘the use of armed force between two organized armed groups, neither of which is the government of a state, which results in at least 25 battle-related deaths in a year’. Organized groups are defined either formally or informally. The former refers to ‘any nongovernmental group of people having announced a name for their group and using armed force against another similarly formally organized group’. The latter comprises ‘any group without an announced name, but that uses armed force against another similarly organized group, where there is a clear pattern of violent incidents that are connected and in which both groups use armed force against the other’. The Non-State Conflict Dataset excludes incidents of one-sided violence, where organized groups use violence against unorganized civilians.6 Moreover, violence by unorganized individuals, such as hate crimes against refugees and riots by refugees or local populations, are not included as they do not meet the group criterion and are spontaneous rather than organized.7 However, note that the data are not limited to formal organizations but also include ‘informally organized groups […] without an announced name, […] who use armed force against another similarly organized group’, and cover ‘communal violence […] between very broad categories of identification’, with the codebook citing the case of Hindus vs. Muslims in India as an example. We see non-state conflict onset in about 2.7% of the 5,118 observations in our sample. The data on civil conflict (value 2 of the nominal dependent variable) are taken from Gleditsch et al. (2002) and Themnér & Wallensteen (2012), and we employ the 25 battle-deaths threshold to define onsets. We convert the recorded instances of non-state or civil conflicts since 1989 to binary variables indicating the onset of (at least) one non-state or state-based conflict in a given country-year. Since we focus on onset, we drop all ongoing conflict years from the analyses, and a country with past conflict only enters the analysis in the first non-conflict year (following the definitions above). In turn, we use this information to construct the nominal variable for the multinomial regression analysis. Note that non-state violence onset and civil conflict onset occurred in 13 observations at the same time, while there are 68 cases in which ongoing non-state conflict and ongoing civil-conflict years overlap. We drop these country-years to ensure that the categories of the dependent variable for the multinomial regression are mutually exclusive. The outcome variable for our second set of analyses is binary and we use logistic regression models as a result. This dichotomous dependent variable comprises all onsets of non-state violence, regardless of whether these overlap with state-based civil conflict onsets or incidence. The standard errors in either the multinomial regression or the logit models are clustered by country to control for potential differences in the variance between states. Explanatory variables Our argument focuses on refugee populations, state capacity, and the interaction of these two variables as we expect the latter to moderate the effect of the former on the risk of, particularly, non-state actor conflict. First, for refugee populations, we rely on the UNHCR Population Statistics Reference Database. These data provide information on the number of different ‘population types’ per country year. We concentrate on refugees, persons in refugee-like situations, and asylum-seekers as the relevant population types, and calculate the total number of these groups in a country-year. Internally displaced persons or returnees are excluded from our measure, since these subpopulations are likely to differ in important ways from those populations we focus on. Based on the raw data from the UNHCR, we replaced missing observations by zeros and we added the value of 1 before taking the natural logarithm of the total number of refugees to arrive at the final item, Refugees (ln) (mean value of 6.565; standard deviation of 4.495). The pairwise correlation between Non-state conflict and Refugees (ln) is 0.084 (p < 0.001). Second, although state capacity is a potentially multidimensional concept that is challenging to measure (see also Hendrix, 2010), we focus on state capacity pertaining to the strength and quality of the bureaucratic apparatus. Countries with an effective bureaucracy are most likely to be able to maintain, control, and sustain state services. Similarly, Fukuyama (2013) argues that measures of state capacity based on what the state produces are problematic and, instead, suggests that state capacity is best measured by looking at how governments function, specifically bureaucratic procedures, capacity, and autonomy. We capture this empirically by the Worldwide Governance Indicators (WGI), which report aggregate governance indicators for more than 200 countries in 1996–2015. These data are based on enterprise, citizen, and expert survey respondents in industrial and developing states, and further incorporate information from over 30 individual data sources (e.g. survey institutes, think-tanks, nongovernmental organizations, international organizations, or private sector firms). The specific variable we focus on, namely government effectiveness, is intended to capture perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. The WGI measure is widely used in the literature, but the temporal scope is limited in that data before 1996 are not available. To overcome this, we rely on an alternative indicator from the Political Risk Services Group’s (PRSG) International Country Risk Guide, which is based on expert assessments on a state’s bureaucratic quality and ranges in [0; 4]. According to the PRSG, ‘high points are given to countries where the bureaucracy has the strength and expertise to govern without drastic changes in policy or interruptions in government services. In these low-risk countries, the bureaucracy tends to be somewhat autonomous from political pressure and to have an established mechanism for recruitment and training. Countries that lack the cushioning effect of a strong bureaucracy receive low points because a change in government tends to be traumatic in terms of policy formulation and day-to-day administrative functions’. We combine the two variables by interpolating missing values of the WGI variable using information from the PRSG. The final variable, State capacity, is thus an interpolated version of the WGI item covering the period from 1989 to 2015, and its pairwise correlation with Non-state conflict is –0.091 (p < 0.001). It has a mean value of –0.028 with a standard deviation of 0.966. Note that refugees are present in countries of all levels of state capacity, with or without non-state conflict. Finally, we include a multiplicative interactive term between Refugees (ln) and State capacity to examine whether state capacity moderates the effect of refugees. With regard to the control variables, we consider a series of other covariates reflecting alternative influences leading to the outbreak of non-state conflict that are also plausibly associated with refugees and state capacity. First, taken from the World Bank Development Indicators, we control for a country’s mid-year total population, which counts all residents regardless of legal status or citizenship – however, refugees not permanently settled are included only in Refugees (ln). Second, we use an indicator for democracy based on the 21-point combined polity score from the Polity IV database, ranging from –10 to 10, with higher values reflecting states with more democratic institutions (Marshall & Jaggers, 2016). As this particular democracy measure might be endogenous to factional non-state conflict, we use the modified XPolity variable by Vreeland (2008). Since some work on regime type and civil war suggests that partly democratic countries are more prone to conflict than both full democracies and full autocracies (Hegre et al., 2001), we also include the square term of XPolity as well. Third, we consider the share of population in excluded ethnic groups, based on the Ethnic Power Relations (EPR) data (see Cederman, Wimmer & Min, 2010; Wimmer, Cederman & Min, 2009). According to the EPR data, included/excluded ethnic groups are defined by ethnicity and their access to power. Excluded groups (largely) lack access to executive power, that is, representation in the presidency, the cabinet, and senior posts in the administration, including the army. Ethnic groups are also excluded if they are discriminated, powerless, or have regional or separatist autonomy. For our specific question, ethnic exclusion and tensions might not only affect the risk of non-state conflict, but also the degree of state capacity and refugees’ self-selection into host societies: it is plausible that refugees may avoid fleeing to countries that have significant ethnic tensions manifested in political exclusion of ethnic groups. We use the normalized share of the population in excluded groups. Finally, to address temporal dependencies in the analysis using our nominal outcome variable, we calculate cubic polynomials based on the time elapsed (in years) since the last conflict onset (if any and however defined it may be, i.e. non-state conflict or civil conflict) following Carter & Signorino (2010). As the outcome variable for our second set of analyses differs from the multinomial regressions, we adjust the variables for temporal correction accordingly (i.e. the time elapsed since the last onset of non-state violence, its squared term, and this variable raised to the power of 3).

Conclusion A central claim of our research is that high-intensity forms of organized political violence are unlikely to be linked to refugees. Lower-intensity forms of violence seem, ex-ante and if anything, more plausibly linked to refugee populations, and we should also focus on types of conflict that do not see the state as the central actor. Our article extends existing work on refugees and conflict by analyzing the implications for non-state conflict. The main argument is that refugees can – directly or indirectly – be associated with non-state forms of violence, but primarily when state institutions are weak. The presence of refugees results in social and economic challenges that weak states are less prepared to take measures necessary to prevent (see also Chambers, 1986). The moderating influence of state capacity is important, as developing and emerging countries host the most refugees and suffer disproportionately. Indeed, our results run completely counter to the security rationale cited for efforts to restrict refugee inflows in the USA and many European countries. A key implication of our analysis is that the risk of non-state conflict remains low despite high inflows when hosting states have high capacity. The relevant security implications arise in low-capacity, developing countries. In part as a result of the problems of achieving a proportionate global burden-sharing and the reluctance of many developed countries to accept refugees (Bauböck, 2018), UNHCR estimates indicate that as many as 84% of the world’s refugees are hosted in developing countries least prepared to deal with the challenges. If fleeing and fighting are potential substitutes (Okamoto & Wilkes, 2008), efforts to crackdown on opportunities for refugees or asylum institutions risk exacerbating conflicts and their devastating impact in the countries of origin, with potentially worse consequences for neighboring states. Hence, our results should also not be interpreted as evidence in favor of exclusionary policies in low-capacity states against refugees from neighboring countries, as limits to opportunities for asylum can exacerbate neighboring conflict and generate even more severe transnational security challenges from conflicts. The link between state capacity and non-state conflict from hosting refugees may seem to have largely negative policy implications, in that many states hosting refugees lack the capacity to implement measures that could be effective in mitigating the risks of violence. However, state capacity is not just determined by domestic forces, and resources from outside a country can also be important to compensate for limited domestic capacity. Many European nations have developed better settlement services for refugees over the course of the recent crisis, and some of this capacity could, at least in principle, be transferred to vulnerable countries hosting refugees closer to ongoing conflicts. Third-party assistance that can raise host countries’ capacities may help these to address the difficulties in trying to manage the arrival of refugees in a way that does not undermine local service provision and generate popular grievances, before tensions arise and the risk of non-state violence increases. For this to happen, states must be less concerned with burden shirking, and steer more foreign assistance and development aid to state-capacity-building measures in receiving nations (also Chambers, 1986). Several avenues for future research might emerge out of our work. Since previous research has paid limited attention to the multidimensional character of state capacity (Fukuyama, 2013; Migdal, 2001), disaggregating our measure of state capacity based on bureaucratic quality may be helpful. Studying how a more differentiated measure of state capacity plays out with respect to authority and legitimacy might also be an effort worth making (see also Tikuisis & Carment, 2017), and we believe that shedding more light on the willingness and opportunity aspects of state capacity can significantly improve our understanding of how state capacity mediates the security implications of refugee flows. Our current state-capacity measure combines states’ willingness to use their resources with the possibilities they have at their disposal. However, in some cases, a government may actually have the necessary resources, but simply lack the willingness to invest them. Second, it would be interesting to expand the analysis of non-state conflict to other forms of political violence in varying degrees of organization and the relationship between them, as well as variation in intensity and severity. One-sided violence, hate crimes, and violence by paramilitary and militia groups could all be interesting alternatives we should study. In addition, non-state actor violence may well be associated with state-based civil conflict in that the former may increase the risk of the latter or that the latter positively influences the onset of non-state conflict. Our multinomial regression analysis assumes that these two alternatives are unrelated to each other at the point of onset, but there may be more complex relationships between one type of conflict and the risk of others over time that are worthy of further investigation. A full analysis of the relationship between different forms of violence goes beyond the scope of this article, but we provide a preliminary analysis based on a simultaneous-equations model in the Online appendix. This suggests some evidence that non-state conflict may deter refugees and that states with lower state capacity may receive more refugees, but there is little evidence for a clear relationship from non-state conflict to civil war. Finally, our outcome variable in its present form cannot determine whether refugees are the source or the target of violence – or not directly involved in violence at all. This is in line with our theory, and the specific propositions we consider do not require that refugees must be the target or source of non-state violence. However, Onoma (2013) and Cuellar (2006) provide case studies indicating that refugees are often targeted in civil wars. Moreover, parts of our theoretical discussion and the Rohingya illustration also show that refugees frequently become targets of non-state violence in weak states because of the actual or perceived negative externalities they pose. Stigmatizing refugees seems therefore even more misleading, and victims should indeed not be blamed, but the lack of coding of targets in conflict in current data prevents a more thorough analysis. Hence, additional coding efforts to distinguish between refugees as the source or target of violence are necessary. Savun & Gineste (2019), Gineste & Savun (2019), and Polo & Wucherpfennig (2017) have begun to pursue this promising avenue of research; in addition, Fisk (2014) provides spatially disaggregated conflict and refugee data in 26 African countries for 2000–10, while Shaver & Zhou (2017) have compiled geo-coded data on UNHCR refugee sites for 1989–2008. We conclude that no state is inherently unable to deal with refugees, and there is no automatic link between hosting more refugees and a higher likelihood of political violence. Our evidence helps to clarify the consequences that can be anticipated and what policies could be enacted. If governments are concerned about tensions in countries affected by the humanitarian impact of refugee crises and migration, efforts should be made to strengthen state capacity and the ability to integrate refugees into the local economy (see also Savun & Gineste, 2017). Blaming refugees for heightened security risks or simply closing borders to people in need of asylum entails large humanitarian consequences and can be counterproductive. It is unlikely that people will stop fleeing conflict and persecution, and efforts to close borders are likely to increase the burden on weaker states and force refugees to seek more risky routes with a high loss of life. We recognize the significant challenges to asylum systems, as host states need to mobilize resources to minimize the difficulties they could be experiencing in trying to manage the arrival of refugees so that the provision of public goods is not undermined and grievances among the local population are not generated. In many countries, the scale of the current refugee crisis leaves existing systems for accommodating and processing refugees under severe strain. But failing to implement comprehensive and well-tailored policies to strengthen receptive and processing capabilities and to support integration efforts will make refugee flows more costly for host societies in the long run.

Replication data The dataset and do-file for the empirical analysis in this article, along with the Online appendix, can be found at http://www.prio.org/jpr/datasets.

Acknowledgments We thank the special issue editors, Alex Braithwaite, Idean Salehyan, and Burcu Savun, as well as three anonymous reviewers for useful comments and suggestions. We are also grateful to Faten Ghosn, Arzu Kibris, Adam Lichtenheld, John McManus, and participants at the workshop ‘Political, Economic, Social, and Legal Aspects of Hosting Migrants and Refugees’, Istanbul, 4–8 July 2017, supported by the British Council Newton Fund (grant number: RLWK6-261786650), as well as audiences at seminar presentations at the Universities of Mannheim and Warwick for their valuable feedback.

ORCID iD

Tobias Böhmelt https://orcid.org/0000-0002-7661-8670 Kristian Skrede Gleditsch https://orcid.org/0000-0003-4149-3211

Notes 1

In a recent exception, Fisk (2018) explores violence against civilians in refugee-populated communities. She finds that refugee populations positively correlate with civilian victimization, particularly in areas with larger self-settled populations, i.e. those living among the local population who do not have official legal status as refugees (see also Fisk, 2019). 2

Available Online at http://popstats.unhcr.org/en/time_series. 3

The Online appendix elaborates on the underlying, micro-level implications of this macro-level framework. 4

This is stressed in a report from the Brookings Institution, available Online at https://www.brookings.edu/wp-content/uploads/2017/01/global_20170109_foresight_africa.pdf. 5

Note that in countries with high levels of state capacity, social services provided through government funding are also targeted at native communities, which significantly reduces concerns over locals having limited access to public services. 6

Although the UCDP also collects data on one-sided violence by non-state actors, we show in the Online appendix that these are largely confined to actors involved in a state-based civil conflict. Hence, although we could see one-sided violence by organized non-state actors against refugees, such events will not be systematically captured by existing data, largely limited to situations with ongoing or recent civil conflict. Evaluating one-sided violence against refugees would also benefit from information on victims to assess whether refugees are specifically targeted. Although we see more one-sided violence by governments against civilians outside civil war (Savun & Gineste, 2019), governments are unlikely to have incentives to target refugees unless they perceive a high risk of organized violence, which would suggest a higher risk of civil conflict. 7

See Savun & Gineste (2017) on refugee riots and Koopmans & Olzak (2004) on hate crimes. 8

Our results for civil war are not directly comparable to Salehyan & Gleditsch (2006), though. We do not impose their suggested scope restriction to refugees from neighboring countries, while Salehyan & Gleditsch (2006) do not consider an interaction between refugees and state capacity. Our main purpose here is not to examine the more specific conditions under which refugees can increase the risk of civil war, but rather the more direct relationship to non-state conflict. 9

Available Online at: https://www.hrw.org/world-report/2017/country-chapters/lebanon.