Explaining access to citizenship in Europe: How citizenship policies affect naturalization rates

Abstract

In Europe, a variety of national policies regulate access to citizenship. This article analyses how citizenship policies affect naturalization rates among immigrants. Our analysis confirms that favourable citizenship policies positively affect naturalization rates, especially among first-generation immigrants with more than 5 but fewer than 20 years of residence. However, most variation is explained by other factors. Immigrants from poor, politically unstable, and non-EU countries are more likely to be a citizen of their European country of residence. Other important predictors of the citizenship status of immigrants are language, years of residence (first generation), and age (second generation). Explanations of naturalization rates in Europe should not only take into account institutional conditions but also include other destination and origin country factors and individual characteristics of immigrants.

Keywords

Citizenship cross-national comparison Europe immigration migration policies naturalization

Introduction

Citizenship acquisition is often seen as a crucial step in the process of integrating immigrants into host societies. Within the European Union (EU), access to national citizenship is particularly important because, since the Maastricht Treaty, it provides access to EU citizenship and thus access to free movement rights. Although increasingly more precise comparative information is available on the differences in citizenship policies across European states (Bauböck et al., 2006; Goodman, 2010; Vink and De Groot, 2010a, 2010b) and their historical and political origins (Brubaker, 1992; Howard, 2009; Janoski, 2010), we know relatively little about the systematic effects of these comparative differences. As Franchino (2009: 414) has observed, the link between citizenship policy output and outcome is an important factor to consider because ‘politicians adopt the former but are ultimately concerned with the latter’. In this article, we investigate the effect of citizenship policies on citizenship acquisition and analyse the question of why some immigrants who are resident in Europe are more likely than others to be a citizen of their country of residence.

Observers noted 25 years ago that ‘the social science literature on the naturalization process is weak and few statistically valid generalizations can be made about the effect of specific cultural, economic, political, or familial variables on naturalization’ (DeSipio, 1987: 402). Today, when reviewing the existing literature on the naturalization of immigrants, it is evident that the literature has progressed significantly, but mostly within the context of North American immigration (see for example, Chiswick and Miller, 2008; Jones-Correa, 2001; Mazzolari, 2007; North, 1987; and Yang, 1994, on the USA; DeVoretz and Pivnenko, 2004, on Canada; and Bloemraad, 2002, on Canada and the USA). European studies are mostly single case studies and often focus more on the effects of naturalization (see for example, Bevelander and Veenman, 2006, on both the causes and the socioeconomic consequences of naturalization in the Netherlands; Steinhardt, 2008, on the economic impact of naturalization in Germany; Ersanilli and Koopmans, 2010, on the sociocultural consequences of the naturalization of Turks in France, Germany, and the Netherlands). Other studies have described the available national statistics and data sets on citizenship acquisition (see for example, Reichel, 2010; Waldrauch, 2006). We know of no comparative analysis using micro data to explain immigrant naturalization across European countries.

Our study is important in terms of exploring a phenomenon that has been under-studied in the European context, where immigrant naturalization has a different dynamic than in classic settler states such as Australia, Canada, and the United States. Moreover, we develop a novel comparative approach to analyse naturalization rates in a context where there are significant differences between states in terms of citizenship policies. In this article we use a pooled data set on first- and second-generation immigrants resident in 15 European countries. We test a series of hypotheses on the determinants of citizenship status derived from the social science literature on immigrant naturalization. By applying a logistic multilevel analysis to measure country of origin effects, destination country effects, and the effects of individual-level characteristics, we use a double comparative research design that is suited to analysing the importance of macro-level factors related to the countries of residence (see Van Tubergen et al., 2004). We use the terms ‘destination country’ and ‘origin country’ to refer to, respectively, the country of residence of first- and second-generation immigration and either the country of birth of the first generation or the country of birth of the parents of the second generation.

Theory and hypotheses

Virtually all empirical research on the question of what explains immigrant naturalization applies what DeVoretz (2008: 682) terms an ‘ad hoc approach’: a collection of explanations, formulated at both individual and country level, in the absence of a formal model that motivates immigration citizenship acquisition. DeVoretz (2008: 692) is right to note that such an approach carries the danger of providing a ‘weak rationale and ambiguous arguments on the direction of the effects of the … variables’. Yet, as we said in the introduction, most of these variables have been developed and tested in a North American context and their application to a European context is a novelty. We present here a first large-scale comparative and explanatory analysis of immigrant citizenship acquisition in the European context. Therefore, rather than testing a possibly more cohesive but restricted model, we favour an eclectic model in order to take on board as many variables as possible of those that have been tested in the relevant literature.

We now discuss the existing literature and the hypotheses that we will test in the empirical part of the article, categorizing them into three groups: macro-level explanations that focus on the destination country and on the origin country, and micro-level explanations that focus on the individual characteristics of the immigrants. Within these three groups of explanations, we focus on legal and formal, socioeconomic, cultural, and resource perspectives (see Bloemraad, 2002, for a related but somewhat different typology of explanations). For each of the hypotheses we indicate in parentheses at which level they are formulated: destination country, origin country, or individual level.

Legal/formal perspective: Institutional conditions

The first group of explanations can be summarized under the heading ‘national citizenship laws matter’. Citizenship laws vary greatly between countries and thus may well explain differences in terms of naturalization rates between similar immigrant groups. Typically, we see important differences between ‘immigration countries’, such as Canada and the United States, and most European countries. In the North American context, birth in the territory gives automatic access to citizenship to the second generation and naturalization is seen as a natural part of the integration process that follows immigration. In most European countries, by contrast, citizenship acquisition has for a long time been dominated by descent-based transmission from one generation to the next and therefore was never very accessible to immigrants. However, within Europe we also see a large variety of policies that regulate access to citizenship (see for example, Bauböck et al., 2006; Brubaker, 1992; Janoski, 2010; Vink and De Groot, 2010a).

Aspects of citizenship laws that influence the ‘accessibility’ of citizenship are ius soli birth right, residence requirements, dual citizenship toleration, language and integration requirements, fees, and administrative discretion. One might hypothesize, like many politicians in destination countries who aim to either facilitate or restrict access to citizenship for immigrants, that citizenship laws have an important influence on citizenship acquisition by immigrants (H1a). For second-generation immigrants, regulations that imply automatic or facilitated access to citizenship for persons born on the territory of a state, independently of the citizenship of their parents, may be expected to increase the chance of having destination country citizenship (H1b).

H1a: Immigrants are more likely to have destination country citizenship in countries with a citizenship law that makes citizenship relatively accessible.

H1b: Second-generation immigrants are more likely to have destination country citizenship in countries where birth in a country provides automatic or highly facilitated access to citizenship.

Scholars have also underlined the importance of administrative procedures (North, 1987) as well as institutional environments (Bloemraad, 2002). Given that the in-depth research required to analyse such factors goes beyond the scope of our survey approach, we do not include a separate hypothesis that captures these important dynamics.

We control for the age of immigrants (first and second generation), years of residence (first generation), and gender to filter out effects that are related to individual characteristics of the immigrant rather than to the policy of the destination country. First, given that the institutional context in countries receiving migration generally favours long-term over short-term immigrants with regard to citizenship acquisition, the duration of residence of first-generation immigrants can be expected to have a strong impact on the chances of being naturalized. Secondly, given that the institutional context in all European countries favours descent-based transmission of citizenship over other ways of acquiring citizenship, we also control for situations where one of the parents was born in the destination country. Third, Yang (1994: 472) observes gender bias and finds that women are more likely to naturalize. He argues that naturalization helps women to free themselves from repressive marriages or occupations: citizenship provides autonomy.

Moving from receiving country to sending country, scholars have noted that the citizenship laws in countries of origin also matter, particularly with regard to the toleration of dual citizenship (Chiswick and Miller, 2008; Jones-Correa, 2001). Whereas in some countries the voluntary acquisition of another citizenship either leads to automatic loss or may cause the withdrawal of the citizenship of origin, in others such provisions on loss of citizenship do not exist or are restricted to naturalized citizens. In order to maintain links with their emigrant community, also with a view to income from remittances, many countries, particularly in Latin America, have abolished such loss provisions. We expect toleration of dual citizenship in sending countries to have a positive effect on immigrant citizenship acquisition in destination countries (H2).

H2: Immigrants from countries that accept dual citizenship are more likely to have destination country citizenship.

Socioeconomic perspective: Push and pull factors

Although formal/legal explanations undoubtedly have an intuitive plausibility, in the sense that the legal framework ultimately determines whether or not an individual may have access to citizenship, there are good reasons to look beyond mere institutional conditions. Acquiring destination country citizenship is a deliberate choice both for first-generation and for second-generation immigrants and is often not an automatic fact, certainly not in Europe where most countries at best provide some form of facilitated access to citizenship for persons born on the territory of a country (Vink and De Groot, 2010b). Scholars have argued that the perceptions of immigrants of the costs and benefits as well as the meaning of naturalization are conditioned by their socioeconomic environment (Yang, 1994: 456). We expect these perceptions to be influenced by the socioeconomic context of both the sending country and the destination country. From an economic perspective, one may expect push and pull factors to have a significant impact on the decision by immigrants on whether or not to naturalize and these would in general be summarized as follows: the less attractive it is to return to the country of origin and the more attractive it is to stay in the country of destination, the more likely it is that an immigrant will naturalize. In order to test this general push–pull hypothesis, we break it down into five empirically measurable expectations.

With regard to push factors, we look at the economic and political situation in origin countries. Following Jasso and Rosenzweig (1986: 303), we expect immigrants from less developed countries of origin to be more likely than those from more developed countries to naturalize (H3a). The rationale behind this hypothesis is that citizenship confers not only political rights but also a secure residence status and diplomatic protection, and for immigrants from less developed countries the comparative benefits of citizenship of a European state will be far greater than they are for immigrants from more developed states. We hypothesize, along similar lines, that immigrants from politically less stable countries are more motivated to acquire the citizenship of their country of residence (H3b). Thirdly, we also hypothesize that immigrants from non-EU member states (‘third-country nationals’) have a stronger interest in citizenship of a European country than do those for whom citizenship of a member state of the EU or of an associated European Free Trade Association (EFTA) state, such as Iceland, Norway, or Switzerland, would provide relatively little in terms of substantive benefits of citizenship (H3c).

H3a: Immigrants from less developed countries are more likely to have destination country citizenship.

H3b: Immigrants from politically unstable countries are more likely to have destination country citizenship.

H3c: Immigrants from non-EU/EFTA member states are more likely to have destination country citizenship.

With regard to pull factors, our argumentation partly follows the same line of reasoning. We hypothesize, in line with neoclassical migration theory (Harris and Todaro, 1970), that immigrants are more likely to aspire to citizenship of economically stronger countries than of economically weaker (H4a). Given that all European countries included in our analysis are stable democracies, we do not hypothesize that political stability makes a difference. Rather, with regard to pull factors, we expect that the attractiveness of citizenship of a destination country is a function of net migration rates. Following Yang (1994: 456), our hypothesis is that citizenship of a country with comparatively high immigration becomes comparatively less attractive (H4b). The positive argument underlying this hypothesis is that, in a country with high immigration, immigrants may already have sufficient networks in which they can function well without having to integrate fully in the host society. The negative argument is that in a country with high immigration – certainly in the European context, where immigration is not as strongly embedded in national self-perception as it is in the North American context – immigrants may experience more antagonistic sentiments from the native population rather than encouragement to become a full member of the new host society. We agree, however, that in the latter case one could argue the opposite: immigrants might experience more antagonistic feelings from the native population in countries with lower net migration rates (where immigration is less ‘normal’) and in such countries governments might also be less encouraging towards immigrants acquiring citizenship.

H4a: Immigrants are more likely to have destination country citizenship in economically stronger countries.

H4b: Immigrants are more likely to have destination country citizenship in countries with a lower net migration rate.

Cultural perspective: Attitudes towards citizenship

A third strand of explanations highlights the importance of culture rather than economy (see Bernard, 1936, for an early work). These explanations focus on cultural similarity between destination country and country of origin, which reduces the difficulty for immigrants to integrate and ‘fosters their cultural adaptation to the host society’ (Yang, 1994: 458). Colonial relations, in particular, may be expected to enhance such cultural similarity, in terms of using the same language and having a common history and, sometimes, similar traditions. There is, of course, a wide variety of postcolonial constellations and in the cases of India and the UK or Cape Verde and Portugal the expectation of cultural similarity may be more realistic than in other cases of postcolonial relations. We also included countries that once belonged to the same political entity, such as Austria, Hungary, and the Czech Republic, or Norway and Sweden. Overall, we expect these historical ties to have a positive influence. We thus hypothesize that being from a former colony will increase the chance of citizenship acquisition in the destination country (H5).

H5: Immigrants from former colonies or former parts of the same political entity are more likely to have destination country citizenship.

One variable that has been noticeably absent in the literature on the naturalization of immigrants, as far as we can see, is religion. Yet, at least within the specific context of European host societies, the religious background of immigrants is nowadays a ‘hot potato’, particularly as regards the integration of Muslims in Europe (see for broader discussions, Modood et al., 2006; Pauly, 2004). With regard to access to citizenship, in a country such as the Netherlands citizenship tests include, for instance, questions about gay marriage and church–state relations that at least raise the suggestion of being a litmus test for immigrants with a specific religious background. As Van Oers observes (2009: 128): ‘Applicants for naturalisation even need to feel Dutch’. This arguably raises the bar for immigrants with a specific religious background and it is clear that in these cases, when discussing the religious background of immigrants, Islam is the main issue.¹ We expect this to have a negative effect on citizenship acquisition rates (H6a). Furthermore, although one might expect that Muslim identity loses force over immigrant generations, and thus its potentially problematic effect on citizenship acquisition, the theory of segmented assimilation expresses a more pessimistic view on the integration of, particularly, the second generation (Portes and Zhou, 1993; Thomson and Crul, 2007). Faced with racial and ethnic discrimination and lower than expected employment success, we would expect the Muslim second generation in particular to be less integrated and thus also to be less likely to have citizenship of their country of residence (H6b).

H6a: Muslim immigrants are less likely to have destination country citizenship.

H6b: Second-generation Muslim immigrants are less likely to have destination country citizenship.

Resource perspective: Skills

Finally, individual characteristics, such as language competence, education, and employment, can influence citizenship acquisition both by shaping the motivations for naturalization and by affecting their eligibility for citizenship. Jasso and Rosenzweig (1986: 305) observe that, for the USA, ‘coming from a country in which English is an official language facilitates naturalisation, for which knowledge of the English language is a requirement’. Yang (1994: 468) confirms these findings. Furthermore, immigrants – like anyone else – have to invest in their education, and those with higher education will thus have invested more. They will therefore be more strongly motivated to make use of the employment opportunities they have based on their education and, with a view to returns from employment, be more inclined to do so in the destination country than in the origin country. Investing in education is a sign that they are committed to integrating in society. Finally, successful economic adaptation to the host society, by way of employment, increases immigrants’ commitment (Yang, 1994: 455). We hypothesize that speaking the language of the destination country (H7a), higher education (H7b), and employment (H7c) have a positive effect on citizenship acquisition.

H7a: Immigrants who speak the destination country’s language at home are more likely to have citizenship of that country.

H7b: Immigrants with higher education are more likely to have destination country citizenship.

H7c: Employed immigrants are more likely to have citizenship of their country of residence.

Data and measurement

We use the second and third waves of the European Social Survey (ESS) for our analysis. The first wave of the ESS is not usable for our purposes because it does not include information on the country of origin of second-generation immigrants. The data were assembled in the years 2004–5 for the second wave and 2006–7 for the third wave (Jowell and the Central Coordinating Team, 2005, 2007). From the 24 countries included in the ESS we selected only the 15 countries that have been stable democracies and independent states for several decades: Austria, Belgium, Germany, Denmark, Finland, Spain, France, the United Kingdom, Greece, Ireland, Luxembourg, the Netherlands, Norway, Portugal, and Sweden. We exclude Italy because it is not included in the third wave of the ESS. We include Norway in our data set because, although it is not a member state of the EU, its status as an associated state provides access to free movement rights that are virtually equal to those of European Union citizens. We do so because we are interested in integration processes over a long period of time in a stable, democratic setting. In order to enhance comparability with studies on immigration and naturalization in the USA and Canada, we aim to exclude as much as possible the influence of changing borders and state formation.

The pooled ESS data set of the remaining 15 European countries contains 6465 immigrants of 15 years and older. We classify respondents as immigrants if they or at least one of the parents were born outside the survey country. Respondents who were born outside the survey country but whose parents were born in the survey country are classified as natives. We do not expect them to be different from natives in the destination country. If both parents were born in the same country, this country is categorized as the country of origin. If the parents were born in different countries, we use the country that matches the language spoken at home. In all other cases, the country of birth of the mother is used (see Fleischmann and Dronkers, 2007, for a similar approach). For first-generation immigrants, that is, respondents who were themselves born outside the survey country, their country of birth is used as the country of origin.

A problem with the use of country of birth for the measurement of immigrant status is the changing national borders in Europe during the 20th century and at the beginning of the 21st century. Owing to changes in political boundaries after 1918 (the restructuring of Central and Eastern Europe, including Turkey) and 1945 (the annexation of some formerly German territory by Poland), and owing to the subsequent displacement of large populations, an unknown number of ‘indigenous’ persons are measured as being born outside their country. One can argue that, by failing to make a distinction between genuine migrants and border changes, we overestimate the number of better-integrated immigrants. At the same time, this potential defect highlights a conceptual problem in defining an immigrant: for how many generations must an East Prussian live in Germany before he/she is no longer considered a foreigner (see Kossert, 2008)?

One other important point to keep in mind when using the ESS for comparative analyses is that the ESS is not specifically designed to include first-generation immigrants. Because participation requires language proficiency, the first-generation immigrants who are in the sample need to speak the language of the destination country, which means that there is selectivity as to the kind of immigrants included in the sample.² If first-generation immigrants are willing to participate in a survey, they are likely also to have a legal status in the survey country. However, because our target population is the group of reasonably well-integrated immigrants who have the potential to naturalize, this bias towards legal and reasonably integrated immigrants in the ESS is less problematic for the specific purposes of this study.

The dependent variable of our analysis is destination country citizenship. Respondents in the ESS are asked whether they have citizenship of the country where the survey is being carried out. Unfortunately, they are not asked in which year they acquired that citizenship (for example, after how many years of residence) and they are also not asked how they acquired it (for example, whether automatically by birth or by naturalization). Those data would allow us to measure the effects of changing citizenship policies in destination countries. Regrettably, respondents are also not asked whether they have another citizenship (for example of their country of origin or their parents’ country of origin). Hence we do not know the percentage of immigrants with two or more citizenships in destination countries. Table 1 shows the percentages of first- and second-generation immigrants per destination country who are citizens of that country.³

Table 1.

Immigrants with destination country citizenship

	First generation	Second generation	Total
	Percent	Percent	Percent	N
France	61.2	99.0	82.9	691
Sweden	70.4	96.6	82.4	704
Netherlands	68.8	96.9	82.1	274
United Kingdom	61.3	99.7	79.6	603
Austria	60.0	95.8	79.5	351
Denmark	54.0	98.1	77.9	299
Germany	60.3	90.9	74.0	758
Belgium	49.0	89.2	71.7	590
Ireland	36.0	100.0	68.4	152
Norway	44.5	93.1	64.7	312
Greece	33.0	100.0	64.6	367
Finland	20.0	100.0	58.6	58
Portugal	31.8	90.9	51.5	231
Spain	18.7	92.1	37.2	301
Luxembourg	12.4	74.8	36.5	784
Average / Total	46.9	93.5	68.7	6475

Source: Unweighted data from the second and third waves of the European Social Survey.

Table A1 in the web appendix provides descriptive information about the independent variables that we used in this analysis.⁴ With regard to the macro characteristics of destination countries, we collected indicators of the citizenship policy and of the socioeconomic characteristics of each of the 15 destination countries.

Our main indicator for citizenship policy comes from the Migrant Integration Policy Index (MIPEX). MIPEX is a measurement of the different policies towards the integration of migrants for 28 states, including the 25 EU member states (see H1a). Higher scores represent more inclusive migrant integration policies on a scale from 0 to 100. We use only the subscale for ‘access to nationality’ from the second edition of MIPEX (hereafter ‘MIPEX Access’). The scores for this subscale are based on the following criteria: eligibility, conditions for acquisition, security of status, and dual nationality (see Niessen et al., 2007, for details).

In addition to this general citizenship policy indicator, we also use a separate indicator to capture ius soli policies. All countries that have a form of automatic ius soli citizenship acquisition for everybody born in that country (Ireland, Portugal, the UK) or highly facilitated access for second-generation immigrants at a later age (France, Belgium, Italy, the Netherlands, Spain) are coded 1; the other countries are coded 0 (see H1b).⁵

Gross Domestic Product (GDP) per capita is an indicator of the economic wealth of the destination country (see H4a); we use OECD data from 2005. The ‘net migration rate’ of a destination country is the difference between immigration to and emigration from a country per 1000 persons of the population per year (see H4b); we use 2007 data from the CIA World Fact Book. Table A2 (web appendix) summarizes the descriptive statistics for all destination countries.

With regard to the macro characteristics of origin countries, we use data on whether the citizenship of countries of origin is lost automatically upon voluntary acquisition of another citizenship for the variable ‘dual citizenship’ (see H2). Where citizenship is lost automatically, we code this as 0 and where citizenship is not lost automatically, but can be renounced after acquiring another citizenship, or where it cannot be lost at all, we code this as 1. We use the Dutch Ministry of Justice’s extensive and yearly updated list of provisions in all UN member states, with October 2001 as the reference date (Ministerie van Justitie, 2001).

To gauge the level of development (see H3a) we use the Human Development Index (HDI). The HDI is a composite measure of the development level of a country that includes not only GDP but also factors in indicators of life expectancy and education levels. We use it in order to avoid categorizing countries as developed when their economic wealth is not reflected in overall life expectancy and education (for example, countries that are heavily dependent on oil revenues). Data from the Human Development Report 2007/2008 are used. We recode this index in such a way that a high score means a higher developmental level.

The second origin country indicator is political stability (see H3b), for which we use the Kaufmann Index. This assesses the probability that the government in office will be overthrown in the near future by unconstitutional or violent means (Kaufmann et al., 2006). Using 7–11 components, the indicator ranges from −2.5 to +2.5 owing to standardization. Higher scores indicate greater political stability.

For the variable ‘EU15/EFTA’ (see H3c), we use a dummy and code as 1 all 15 countries that were a member state of the EU before 2004 plus the 3 countries that were associated with the EU through the European Economic Area. All other countries of origin are coded 0 for this variable.

The final origin country indicator is a historical characteristic that might indicate easier access to citizenship of the country of destination, namely ‘former colony or territory’ (see H5). If the country of origin was a former colony or territory of the country of destination, this might promote citizenship in the country of destination.⁶ Table A3 (web appendix) summarizes the descriptive statistics per country of origin.

All included individual variables and their coding are self-evident and directly derived from the ESS. With regard to the religious background of respondents, we use information on the religious group to which the respondent says he or she belongs. In this analysis we use only the dummy variable ‘Islam’ (see H6a) and the interaction term ‘Islam * second generation’ (see H6b) to capture whether a respondent is an adherent of the faith of Islam.

‘Minority language’ is a dummy that measures whether the respondent speaks a language at home other than one of the official languages of the country of residence (see H7a). For ‘education’, the educational level of the immigrants was originally measured on the ISCED-97 seven-point scale, but unfortunately the measurement of education in the UK forces us to reduce this to four dichotomous variables (see H7b). We collapsed the categories of ‘less than primary’ and primary education; higher secondary and ‘post-secondary non-tertiary’ education; and the first and second stages of tertiary education. The fourth dummy is ‘lower secondary education’.⁷ Regarding ‘employment status’, we use the following six ESS categories: unemployed, no work, retired, housework, student, occupational status (see H7c). ‘Occupational status’ is the category that indicates that the respondent has a remunerated occupation. ‘No work’ is different from ‘unemployed’ in that the first category does not involve actively looking for employment.

As control variables we use data on whether one of the parents was born in the destination country, age of the respondent, gender, and years of residence (the latter only for first-generation immigrants). For the number of years of residence we collapsed the categories ‘recently arrived’ and ‘less than 6 years’ into one category ‘less than 6 years’. The other categories – 6–10, 10–20, and more than 20 years of residence – are given by the ESS questionnaire.

Finally, our method of analysis needs to take into account the nested structure of our data because respondents are nested in countries of destination as well as countries of origin. For this reason we use multilevel analysis. As the two levels of country of origin and country of destination are not hierarchically nested, we use a cross-classified model that makes it possible for respondents to be nested both in countries of origin and in countries of destination (Van Tubergen et al., 2004). Given the dichotomous nature of our dependent variables (respondents either do or do not have destination country citizenship), we apply logistic multilevel analysis.

Results

Our main findings are summarized in Table 2. Model 1 is an empty model, without characteristics of individual immigrants, destination country, or origin country variables, which provides a benchmark for the variance in citizenship status of immigrants that remains to be explained (−2 log-likelihood = 7295). We can see that the majority of the non-individual-level variance is at the level of the destination country and not that of the origin country. This means that there are more differences in citizenship acquisition by immigrants between destination countries than between origin countries. However, this is partly spurious. As soon as we control for the individual characteristics in Model 2, there is also substantial variation at the origin level. This indicates that the individual characteristics of immigrants (for example, age) are related with country of origin variables (for example, economic development). In Model 1, these individual characteristics ‘neutralize’ variation between the countries of origin. For instance, the individual characteristics of immigrants from less developed origin countries (they are younger and have arrived more recently and thus are less likely to obtain citizenship) neutralize the variance of the macro characteristic of the origin countries (immigrants from less developed countries are more likely to obtain citizenship). In such a case, individual and macro-level variables have opposite effects on obtaining destination country citizenship.

Table 2.

Logistic multilevel analysis of determinants of destination country citizenship: Unstandardized coefficients (and standard errors)

	Model 1	Model 2	Model 3	Model 4	Model 5
Individual characteristics
Minority language (at home)		−0.43** (0.09)	−0.52** (0.10)	−0.46** (0.10)	−0.58** (0.10)
One parent born in destination country		1.89** (0.15)	2.06** (0.14)	1.91** (0.15)	2.09** (0.14)
Age/10		0.01 (0.04)	0.03 (0.04)	0.01 (0.04)	0.03 (0.04)
Second generation^a		0.08 (0.30)	0.42 (0.29)	0.17 (0.31)	0.45 (0.31)
Age/10 * second generation^a		0.32** (0.07)	0.28** (0.07)	0.28** (0.07)	0.26** (0.07)
Years of residence (first generation)^a
0–5 years		−2.35** (0.15)	−2.79** (0.16)	−2.46** (0.16)	−2.81** (0.17)
6–10 years		−1.35** (0.14)	−1.75** (0.15)	−1.48** (0.15)	−1.80** (0.16)
10–20 years		−0.57** (0.12)	−0.82** (0.13)	−0.64** (0.12)	−0.80** (0.13)
Gender (female)		0.06 (0.08)	0.09 (0.08)	0.06 (0.08)	0.08 (0.08)
Education^b
Only primary		−0.06 (0.13)	−0.16 (0.13)	−0.07 (0.13)	−0.14 (0.13)
Lower secondary		−0.08 (0.12)	−0.14 (0.12)	−0.08 (0.12)	−0.11 (0.12)
Higher secondary		0.02 (0.10)	0.04 (0.10)	0.07 (0.10)	0.09 (0.11)
Employment status^c
Unemployed		0.09 (0.14)	0.09 (0.15)	0.14 (0.15)	0.12 (0.15)
Housework		0.04 (0.13)	0.04 (0.13)	0.11 (0.13)	0.12 (0.14)
Student		0.29** (0.14)	0.36** (0.14)	0.34** (0.14)	0.37** (0.15)
Retired		0.34** (0.16)	0.44** (0.16)	0.41** (0.16)	0.50** (0.16)
Occupational status		0.11 (0.09)	0.10 (0.09)	0.12 (0.09)	0.11 (0.09)
Islam		0.24 (0.15)	0.25 (0.15)	0.25 (0.16)	0.22 (0.15)
Islam* second generation^a		−0.29 (0.28)	−0.75** (0.29)	−0.45 (0.29)	−0.79** (0.31)
Origin country
Former colony or territory			0.25 (0.17)		0.22 (0.18)
Human Development Index			−0.73** (0.25)		−0.69** (0.25)
Kaufmann Index			−0.24** (0.08)		−0.23** (0.08)
Dual citizenship			−0.26* (0.14)		−0.26* (0.14)
EU15/EFTA			−1.66** (0.18)		−1.71** (0.18)
Destination country
Net migration rate				−0.17** (0.06)	−0.21** (0.06)
GDP per capita/1000				0.04 (0.09)	0.13 (0.09)
MIPEX Access* 10				0.12** (0.05)	0.12** (0.05)
Ius soli				−0.15 (0.18)	−0.21 (0.17)
Ius soli* second generation^a				0.28 (0.22)	0.22 (0.21)
Constant	0.67** (0.06)	0.71** (0.24)	1.27** (0.27)	0.45 (0.41)	0.58 (0.43)
Destination variance	0.86** (0.11)	0.76** (0.13)	0.77** (0.13)	0.73** (0.13)	0.65** (0.12)
Origin variance	0.02 (0.05)	0.40** (0.13)	0.00 (0.05)	0.43** (0.13)	0.01 (0.05)
−2 log-likelihood	7295	1390	154	1343	31

Source: Unweighted data from the second and third waves of the European Social Survey.

Notes: N_immigrants = 6475; N_origin = 156; N_destination = 15.

Reference category: first generation (> 20 years’ residence).

Reference category: tertiary education.

Reference category: no work.

Significant at .05 level; ** Significant at .01 level.

Model 2 of Table 2 shows the coefficients of the individual characteristics. Given the strong decrease in the log-likelihood, individual characteristics are far more important than the macro features for explaining the citizenship of immigrants. First we look at the control variables. The results show that first-generation immigrants with more than 20 years of residence are more likely than those with fewer years of residence to have destination country citizenship. Compared with the reference category of first-generation immigrants with more than 20 years of residence, second-generation immigrants are not more likely to have destination country citizenship. In other words, residence matters. For the second generation, age matters: the older the immigrant, the more likely he or she is to naturalize. Finally, if one of the parents was born in the destination country this significantly increases the likelihood of citizenship of the destination country.

As to the three individual skills variables, only speaking the language of the destination country at home increases the likelihood of having destination country citizenship (H7a). Educational level (H7b) and employment status (H7c) do not influence this chance significantly when looking at both first and second generations. As to the factor of religion, the analysis shows that, although Muslim immigrants are not less likely to naturalize (H6a), second-generation Muslims are less likely to naturalize than their non-Muslim counterparts (H6b). This provides tentative support for segmented assimilation theories.

In Model 3 we add the macro characteristics of the origin country.⁸ Development (H3a) and political stability (H3b) have a significant and negative effect, and so does coming from an EU15/EFTA country (H3c). However, coming from an EU15/EFTA country has a significant negative effect only when controlling for individual characteristics (see Table A5 of the web appendix). This is plausible because some of the individual characteristics that increase the probability of having destination country citizenship (for example, born in destination country; being a second-generation non-Muslim immigrant) are especially strong among immigrants from EU15/EFTA countries. Hence, if those characteristics are not controlled for, the EU15/EFTA effect is neutralized. Surprisingly, coming from a country where dual citizenship is allowed also has a negative effect on the likelihood of having destination country citizenship (see H2). Although this is in line with earlier findings by Yang (1994: 473–4), who had also originally hypothesized a positive effect, this outcome remains a bit of a puzzle. Yang suggests that immigrants may perceive dual citizenship as bearing more responsibilities rather than providing more benefits, but we do not find that explanation very convincing because immigrants from dual citizenship countries might normally also voluntarily renounce their citizenship of origin if they experience such ‘confusion about and difficulty in maintaining dual allegiance to both the country of origin and the host country’ (Yang, 1994: 474). We suggest an alternative hypothesis that immigrants from countries where voluntary acquisition of another citizenship leads to the automatic loss of the original citizenship are paradoxically in a better position. The reason is that officials in destination countries might not ask them to renounce their citizenship of origin because those new citizens would presumably lose their original citizenship automatically anyway. From that alternative perspective, immigrants from dual citizenship countries have to make a greater effort because they may need to explicitly renounce their citizenship of origin. This alternative hypothesis, however, would require further research into renunciation practices.

Each of these significant origin country characteristics has its own effect, which cannot be explained by its relationship with the other macro features. The predicting force of these characteristics of the origin countries is quite powerful, in particular that of the EU/EFTA variable, because they explain almost all of the remaining variance after controlling for the individual characteristics.

In Model 4 we look at the effect of the characteristics of the country of destination. Very importantly for the starting point of this article (the analysis of policy output and outcome), we do indeed find a significant and positive effect of the variable ‘access to nationality’, which we use to capture the main variation in citizenship policies across European countries (H1a). Although the change in log-likelihood indicates that the increase in explained variance between Models 2 and 4 is marginal (compared with the difference between Models 2 and 3), the positive effect of citizenship policy also holds when including it in the full model (Model 5). In substantive terms, this means that an increase of 10 points on the MIPEX Access indicator increases the chance of having destination country citizenship for immigrants by 13 percent.⁹

To analyse whether the effect of citizenship policy depends on the years of residence of immigrants, we added the interaction effects of ‘MIPEX Access * years of residence’ to Model 5 (see Table A6, web appendix). This additional analysis shows that first-generation immigrants with more than five years but fewer than 20 years of residence in particular are more likely to have destination country citizenship in countries with higher MIPEX Access scores. For first-generation immigrants with more than 5 and fewer than 10 years of residence, an increase of 10 points on the MIPEX Access score increases the chance of having destination country citizenship for immigrants by 25 per cent. For first-generation immigrants with ten to 20 years of residence the effect is 17 per cent. Figure 1 shows these combined chances of obtaining citizenship in destination countries with a very low, an average, and a very high MIPEX Access score for comparable first-generation immigrants with different durations of residence.

Figure 1.

Chances of obtaining destination country citizenship by comparable first-generation immigrants with different durations of residence in destination countries with low, average and high MIPEX Access scores. Source: ESS (unweighted second and third waves), based on Table A5 (web appendix).

Variables measured at the individual level, such as the ability to speak the language of the country of residence or the number of years of residence, are often formal or informal criteria for citizenship acquisition. Although the relevance of these factors as requirements for naturalization should be largely captured by our main institutional variable ‘MIPEX Access’, it is possible that individual variables (for example, language, years of residence) still reflect the importance of institutional-level factors. To analyse the relationship between individual and institutional variables, we have introduced interaction terms between these individual-level variables and ‘MIPEX Access’. We added these interaction terms to Model 5 and found that none of these interaction terms was significant, except the interaction terms with the different categories of years of residence (see also Table A6 in the web appendix). The absence of a significant interaction effect, for example for language (individual) and ‘MIPEX Access’ (institutional), means that, independent of institutional requirements, speaking the language of the destination country at home has a positive effect on the probability of having destination country citizenship. This suggests that, of the individual-level variables, only the variable ‘residence’ may reflect institutional-level characteristics.

With regard to citizenship acquisition, based on birth in the territory (ius soli) we find that there is a positive and significant effect of the interaction term ‘ius soli * second generation’ when included as a single variable in the model (see Table A5, web appendix). The effect weakens but still holds when controlling for individual variables such as ‘age’ and ‘second generation’. However, the effect disappears when controlling for other origin country and destination country variables (H1b). This means that the overall citizenship policy of a country (as measured by ‘MIPEX Access’) is empirically more important than its birthright policy (ius soli). There is no significant effect for ius soli or for the interaction term ‘ius soli * second generation’ when we omit the variable ‘MIPEX Access’ from Models 4 and 5. Our analysis thus shows why in countries such as Sweden, with weak ius soli policies but high MIPEX Access scores, naturalization rates among adult immigrants are high. For second-generation immigrants compared with the first generation with at least 20 years of residence, we find significant differences in naturalization rates only when the second generation grows older. In other words, whereas for first-generation immigrants residence matters, for the second generation the important factor is age.

‘GDP per capita’ has no independent effect (H4a) but the ‘net migration rate’ has a significant negative effect that cannot be explained by a relationship with the other macro features (H4b). On the whole, the predicting force of these characteristics of destination countries is quite poor because they explain little variance and, as a consequence, hardly improve the fit of our model (indicated by a small decrease in the log-likelihood). In other words, only two destination country characteristics (citizenship policy and the net migration rate) have a significant but empirically weak effect on immigrant citizenship status in Europe.

Model 5 contains all individual characteristics and the macro features of both origin and destination countries together. All three macro features of the origin countries and the two macro variables of the destination countries remain significant. The direction of the parameters of the macro variables hardly changes compared with those of Models 3 and 4. This shows that, in as much as there is a correlation between the macro variables in our model, these do not bias our results.

Discussion and conclusion

Does citizenship policy matter? The results of our analysis show that it does. Immigrants, especially those of the first generation with more than 5 but fewer than 20 years of residence, are indeed more likely to have citizenship of a country with a policy that makes citizenship relatively accessible. The importance of citizenship policy should, however, be qualified. First, for second-generation immigrants we do not find this positive effect of accessible citizenship policy. Second, with regard to citizenship laws in origin countries, where we hypothesized a positive effect of dual citizenship policies, we found a negative effect. Third, and more importantly, with regard to the relative explanatory power of the different variables that we tested, it is clear that legal/formal explanations that focus on institutional conditions provide the weakest explanation. The same holds for net migration rates in destination countries, which have a significant but empirically weak negative effect on citizenship acquisition rates.

Of greater empirical importance are three variables related to cultural and socioeconomic conditions in the countries of origin. Immigrants from poor or politically instable countries are more likely, and those from EU15/EFTA countries less likely, to become a citizen of their country of residence. These findings indicate that it matters much more where an immigrant comes from than where he or she is going.

Yet the largest variation in terms of whether first- and second-generation immigrants have citizenship of their country of residence is explained by individual factors. From a democratic perspective that finding may be seen as encouraging in the sense that it matters less where you come from, or where you are, than who and what you are. We find that adult second-generation immigrants and first-generation immigrants who have more than 20 years of residence, immigrants with one parent born in the destination country and retired workers and persons speaking the host country language at home are more likely to be a citizen of their country of residence. We find no significant effects for education and employment. With regard to cultural factors, we do find that second-generation Muslim immigrants are less likely to have host country citizenship than comparable non-Muslims immigrants (including immigrants who adhere to non-Christian religions such as Judaism, Hinduism, and Buddhism), although we find no significant effect of adherence to Islam for the first generation. The latter, somewhat pessimistic finding offers support for what in the literature is called the phenomenon of segmented assimilation, drawing attention to the social stratification factors that makes some immigrant groups susceptible to downward mobility (Portes and Zhou, 1993; Zhou, 1997).

We conclude with two important caveats. First, we use survey data in this article (compare also Bevelander and Veenman, 2006, for an analysis of survey data from the Netherlands), whereas most existing work so far has been done based on census data, particularly in the North American context (but see also Steinhardt, 2008, on Germany and Evans, 1988, on Australia). One clear downside of our survey approach is that we cannot follow a cohort approach, which would be possible had we used census data. Our data do not indicate, for example, the precise year of arrival in destination countries of first-generation immigrants. In general terms, our analysis provides a weak measurement of the time dimension of immigration. At the same time, whereas existing research on immigrant integration in European countries tends to focus on one or a few receiving countries and a few immigrant groups (see for example, Ersanilli and Koopmans, 2010, on Turks in France, Germany, and the Netherlands), our analysis provides a much more comprehensive picture of the full range of immigration groups.

Second, with regard to the significant ‘individual’ characteristics we observe, such as duration of stay and language skills, these might be the result of selective migration inflow and thus of variation in migration control between countries. Although we partly control for this potential effect by including origin country variables such as ‘former colony/territory’, measuring the effect of immigration policies on naturalization rates goes beyond the scope of this article. Further analysis is needed to analyse the relationship between immigration and naturalization policies more systematically.

Finally, our analysis suggests two broader conclusions. First, we show that the acquisition of citizenship by immigrants in Europe is partly, but not primarily, driven by legal characteristics. This has important consequences for political debates and citizenship theories, which too often focus only on the receiving end of the migration process and ignore the transnational dimension of migration and citizenship (see for notable exceptions, Bauböck, 1994; Bauböck and Faist, 2010; Fox, 2005). A comprehensive analysis of immigrant citizenship acquisition should thus take into account social, economic, and cultural features of destination and origin countries and of individuals. Second, when looking at the developing notion of European citizenship, our analysis indicates both the strength and the weakness of this status. Its weakness is shown by the diversity of the rules that determine, via national citizenship, access to this European status. In other words, for immigrants, becoming a European citizen depends, at least partly, on the member state in which they reside. The strength of the European status, however, is also highlighted because being a European citizen clearly makes a difference. At least from the point of view of individual European citizens residing in another member state, who are clearly less motivated to acquire another European citizenship, it matters more that one has citizenship of at least one member state than that one has citizenship of the member state of residence. That underlines the importance of the shared status.

Footnotes

Acknowledgments

Earlier versions of this article were presented at the University of Lille, the University of Grenoble, the University of Liege, the University of California, San Diego, and Maastricht University. We thank Rainer Bauböck, Thomas Faist, David FitzGerald, Jon Fox, Virginie Guiraudon, Rik Linssen, Dietmar Loch, Marco Martiniello, David Reichel, Ayelet Shachar and the anonymous reviewers for their comments and invitations to present work in progress. The web appendix of this article includes five tables with additional descriptive statistics and additional analysis, as well as the data file, the codebook, and a brief description of the data management procedures.

Notes

References

Bernard

(1936) Cultural determinants of naturalization. American Sociological Review 1(6): 943–953.

Bauböck

(1994) Transnational Citizenship: Membership and Rights in International Migration. Aldershot: Edward Elgar.

Bauböck

Faist

(eds) (2010) Diaspora and Transnationalism: Concepts, Theories and Methods. Amsterdam: Amsterdam University Press.

Bauböck

Ersbøll

Groenendijk

Waldrauch

(eds) (2006) Acquisition and Loss of Nationality. Policies and Trends in 15 European states. Volumes 1 & 2. Amsterdam: Amsterdam University Press.

Bevelander

Veenman

(2006) Naturalisation and socioeconomic integration: The case of the Netherlands. IZA Discussion Paper No. 2153.

Bloemraad

(2002) The North American naturalization gap: An institutional approach to citizenship acquisition in the United States and Canada. International Migration Review 36(1): 193–228.

Brubaker

(1992) Citizenship and Nationhood in France and Germany. Cambridge, MA: Harvard University Press.

Chiswick

Miller

(2008) Citizenship in the United States: The roles of immigrant characteristics and country of origin. IZA Discussion Paper No. 3596.

Cohen

(1983) Applied Multiple Regression/Correlation Analysis in Behavioral Sciences. Hillsdale, NJ: Erlbaum.

10.

DeSipio

(1987) Social science literature and the naturalization process. International Migration Review 21(2): 390–405.

11.

DeVoretz

(2008) The economics of citizenship: A common intellectual ground for social scientists?. Journal of Ethnic and Migration Studies 34(4): 679–693.

12.

DeVoretz

Pivnenko

(2005) The economic causes and consequences of Canadian citizenship. Journal of Immigration and Integration 6(3–4): 435–468.

13.

Ersanilli

Koopmans

(2010) Rewarding integration? Citizenship regulations and the socio-cultural integration of immigrants in the Netherlands, France and Germany. Journal of Ethnic and Migration Studies 36(5): 773–791.

14.

Evans

MDR

(1988) Choosing to be a citizen: The time-path of citizenship in Australia. International Migration Review 22(2): 243–264.

15.

Fox

(2005) Unpacking ‘transnational citizenship’. Annual Review of Political Science 8: 171–201.

16.

Fleischmann

Dronkers

(2007) The effects of social and labour market policies of EU-countries on the socio-economic integration of first and second generation immigrants from different countries of origin. Working paper EUI-RSCAS 2007/19 (European Forum Series).

17.

Franchino

(2009) Perspectives on European immigration policies. European Union Politics 10(3): 403–420.

18.

Goodman

(2010) Naturalisation Policies in Europe: Exploring Patterns of Inclusion and Exclusion. Comparative Report, RSCAS/EUDO-CIT-Comp. 2010/7. San Domenico di Fiesole: EUDO Citizenship Observatory.

19.

Harris

Todaro

(1970) Migration, unemployment and development: A two-sector analysis. American Economic Review 60: 126–142.

20.

Howard

(2009) The Politics of Citizenship in Europe. New York: Cambridge University Press.

21.

Janoski

(2010) The Ironies of Citizenship: Naturalisation and Integration in Industrialized Countries. Cambridge: Cambridge University Press.

22.

Jasso

Rosenzweig

(1986) Family reunification and the immigration multiplier: U.S. immigration law, origin-country conditions, and the reproduction of immigrants. Demography 23(3): 291–311.

23.

Jones

(1996) Indicator and stratification methods for missing explanatory variables in multiple linear regression. Journal of the American Statistical Association 91: 222–230.

24.

Jones-Correa

(2001) Under two flags: Dual nationality in Latin America and its consequences for naturalization in the United States. International Migration Review 35(4): 997–1029.

25.

Jowell

and the Central Coordinating Team (2005) European Social Survey 2004/2005: Technical Report. London: Centre for Comparative Social Surveys, City University.

26.

Jowell

and the Central Coordinating Team (2007) European Social Survey 2006/2007: Technical Report. London: Centre for Comparative Social Surveys, City University.

27.

Kaufmann

Kraay

Mastruzzi

(2006) Governance matters V: Aggregate and individual governance indicators for 1996–2005. World Bank Policy Research Working Paper 4012.

28.

Kossert

(2008) Kalte Heimat. Die Geschichte der Deutschen Vertriebenen nach 1945. Munich: Siedler.

29.

Mazzolari

(2007) Dual citizenship rights: Do they make more and better citizens? IZA Discussion Paper 3008.

30.

Ministerie van Justitie (2001) Landenlijst naturalisatie oktober 2001. Tussentijds Berichten Nationaliteiten (TBN 2001/5). Staatscourant 180: 20–20.

31.

Modood

Triandafyllidou

Zapata-Barrero

(eds) (2006) Multiculturalism, Muslims and Citizenship: A European Approach. Abingdon: Routledge.

32.

Niessen

Huddleston

Citron

(2007) Migrant Integration Policy Index. Brussels: British Council and Migration Policy Group.

33.

North

(1987) The long grey welcome: A study of the American naturalization process. International Migration Review 21(2): 311–326.

34.

Pauly

(2004) Islam in Europe: Integration or Marginalization?. Aldershot: Ashgate.

35.

Portes

Zhou

(1993) The new second generation: Segmented assimilation and its variants among post-1965 immigrant youth. Annals of the American Academy of Political and Social Science 530(1): 74–98.

36.

Reichel

(2010) Measuring determinants and consequences of citizenship acquisition. Prominstat Working Paper No. 15.

37.

Steinhardt

(2008) Does citizenship matter? The economic impact of naturalizations in Germany. Centro Studi Luca D’Agliano Development Studies Working Papers No. 266.

38.

Thomson

Crul

(2007) The second generation in Europe and the United States: How is the transatlantic debate relevant for further research on the European second generation?. Journal of Ethnic and Migration Studies 33(7): 1025–1041.

39.

Van Oers

(2009) Justifying citizenship tests in the Netherlands and the UK. In: Guild

Groenendijk

Carrera

(eds) Illiberal Liberal States: Immigration, Citizenship and Integration in the EU Survey. Surrey: Ashgate, pp. 113–130.

40.

Van Tubergen

Maas

Flap

(2004) The economic incorporation of immigrants in 18 western societies: Origin, destination and community effects. American Sociological Review 69(5): 704–727.

41.

Vink

De Groot

(2010a) Citizenship attribution in Western Europe: International framework and domestic trends. Journal of Ethnic and Migration Studies 36(5): 713–734.

42.

Vink

De Groot

(2010b) Birthright Citizenship: Trends and Regulations in Europe. Comparative Report, RSCAS/EUDO-CIT-Comp. 2010/8. San Domenico di Fiesole: EUDO Citizenship Observatory.

43.

Waldrauch

(2006) Statistics on acquisition and loss of nationality. In: Bauböck

(eds) Acquisition and Loss of Nationality. Policies and Trends in 15 European States, Volume 1. Amsterdam: Amsterdam University Press, pp. 269–316.

44.

Yang

(1994) Explaining immigrant naturalization. International Migration Review 28(3): 449–477.

45.

Zhou

(1997) Segmented assimilation: Issues, controversies, and recent research on the new second generation. International Migration Review 31(4): 825–858.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.93 MB