609731 research-article2015

NVSXXX10.1177/0899764015609731Nonprofit and Voluntary Sector QuarterlyGil-Lacruz et al.

Article

Youth Volunteering in Countries in the European Union: Approximation to Differences

Nonprofit and Voluntary Sector Quarterly 2016, Vol. 45(5) 971­–991 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0899764015609731 nvsq.sagepub.com

Ana Isabel Gil-Lacruz1, Carmen Marcuello-Servós1, and María Isabel Saz-Gil2

Abstract The reasons why people volunteer their time and services are of great interest and they have been the subject of academic research. This article helps identify some of the underlying reasons for the marked differences in youth volunteering among member states of the European Union. Our objective is to describe the similarities and differences in countries’ youth volunteer rates on individual and national levels. To this end, we identified individual and contextual factors and compared volunteer activities. We used data from the European Values Survey (EVS) for that purpose. As a methodological strategy, we carried out Logit models to estimate individual probabilities of working as a volunteer. The main result shows that social capital variables are the most relevant when young people decide to participate in voluntary activities. Keywords volunteering, youth volunteering, motivation, context, volunteer activities, European Union countries

Introduction Citizen participation is a global issue that takes various forms and is significant for both social policies and social welfare. Volunteering is a planned, non-obligatory, and contributory behavior that takes place over time and within an organizational context. 1University 2University

of Zaragoza, Zaragoza, Spain of Zaragoza, Teruel, Spain

Corresponding Author: María Isabel Saz-Gil, Business Management Department, Faculty of Social and Human Sciences, University of Zaragoza, Ciudad Escolar s/n, 44003 Teruel, Spain. Email: [email protected]

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It is a type of prosocial participation and probably the most important (Penner, 2004). Understanding youth volunteering and its dynamics is relevant because of its positive effects on adolescent development. Youth volunteering is also a strong predictor of adult volunteering (Atkins, Daniel, & Donnelly, 2005). The effect of youth volunteering is not merely palpable in the short term, it has enduring consequences (McFarland & Thomas, 2006; Youniss, McLellan, & Yates, 1997). Not only has a positive relationship been found between participation as a youth volunteer and civic engagement in adulthood (Hart, Atkins, & Donnelly, 2006; Metz, McLellan, & Youniss, 2003), but also that youth volunteers become adult volunteers at a far higher rate than the mean (Hall, Mckeown, & Roberts, 2001; Hart, Donnelly, Youniss, & Atkins, 2007). Stolle and Hooghe (2004) point out that behavior patterns in adolescence continue to develop during adulthood due to two mechanisms: (a) integration into relationship networks, which could become a source of recruitment for the future, and (b) development of civic attitudes as a permanent personality trait that continues into adulthood. Volunteering contributes to the formation of social and community identity (Marta, Pozzi, & Marzana, 2010), according to the role identity model of volunteering (Callero, Howard, & Piliavin, 1987; Marta, Manzi, Pozzi, & Vignoles, 2014). Promoting volunteering at earlier ages requires national and international organizations to pay attention to planning. The European Union (EU) has been placing emphasis on fostering youth volunteering for some time.1 Voluntary activities form a core part of the EU strategy to help young people address the challenges they face in their countries. They are an essential aspect of several EU programs. The results of Flash Eurobarometer 375 (2013) demonstrate that 44% of those surveyed had not participated in activities in any organization in the last year. Furthermore, although there were fewer differences observed among countries, they still persisted. Some studies have analyzed the difference in volunteering among European countries (Curtis, Baer, & Graff, 2001; Curtis, Graff, & Baer, 1992); they have shown that Nordic countries have much higher volunteer levels, whereas Mediterranean and Eastern European countries have the lowest (Sardinha, 2010; Voicu & Voicu, 2009). A variety of reasons account for volunteering variations among countries; these can be grouped into economic aspects, religious traditions, differences in democratic political systems, or the continuity of democratic stability (Curtis et al., 2001). Our objective was to describe the similarities and differences in countries’ youth volunteer rates on individual and national levels. We used data from the European Values Survey (EVS; 1999, 2008) for that purpose. This main contribution of the article is to research on youth volunteering. We identified individual factors (sociodemographic variables) and contextual factors (government expenditure on social concerns) and compared their effects on various volunteer activities. We established four sets of factors in this study: socio-demographic variables; membership of a nongovernmental association; values and attitudes and geographical contextual variables of various welfare areas, according to Esping-Andersen (Anglo-Saxon, Continental, Eastern, Nordic, and Mediterranean); and time contextual variables (1999 and 2008 waves). Given the dichotomous nature of the dependent variables (1 if volunteering, 0 if not), we carried out independent Logit estimations for each type of volunteer activity

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(SocialConscience, Professional, Leisure, and SocialJustice). We also repeated the estimations with different sets of independent variables to improve the robustness of the estimated parameters.

Theoretical Framework The review of studies and statistics highlights differences in the level of volunteering in Europe; the Nordic countries have the highest volunteer levels, whereas the Mediterranean and Eastern European countries have the lowest levels (Curtis et al., 1992; Gil-Lacruz & Marcuello, 2013; Sardinha, 2010; Voicu & Voicu, 2009). Curtis et al. (2001) point out that volunteering differences among countries are a consequence of several factors: The development and economic growth of countries are related positively to involvement in voluntary organizations, as they entail an increase in people’s educational and income levels (Curtis et al., 1992); religious tradition affects volunteers based on their implicit civic attitudes (Inglehart & Baker, 2000; Verba, Schlozman, & Brady, 1995); the type of democratic organization is related to involvement in volunteering to the extent that it influences the structure of a country’s welfare state (Curtis et al., 1992; Esping-Andersen, 1998); and democratic stability and continuity are considered to be an important factor in involvement in voluntary organizations as they allow people freedom of speech and association (Curtis et al., 2001; Inglehart & Baker, 2000). Paxton (2002) analyzes the reciprocal nature between an increase in the activity of voluntary organizations and the consolidation and continuity of democracy in countries. The welfare state can promote volunteering through its influence on certain individual variables considered essential in participation: education and income (Verba et al., 1995). Concerning the provision of public services, the relationship between the State and voluntary organizations is complex, as the State plays an active role in developing and establishing them, and financial support is one of the mechanisms used (Putnam, 2003). Research that has examined the effects of State grants on voluntary organizations suggests that State support can crowd out private participation. However, the results are not conclusive as the majority of people are not aware of government subsidies for non-profit organizations (Horne, Johnson, & Van Slyke, 2005). The impact depends on the area of focus of the voluntary organizations and their stage of development (Brooks, 2000). Organizations also play an important role in the continuity of volunteering (Chacón, Vecina, & Dávila, 2007). Citizen participation is a result of a series of factors that are not mutually exclusive (Verba et al., 1995). Some affect an individual’s ability to participate, which is conditioned by economic and educational resources and time constraints; others represent people’s motivation to participate, which depends on the individual’s integration in the community, attitudes, and civic orientations. Finally, there are incentives to volunteer. Cnaan and Cascio (1999) identify three groups of variables: sociodemographic variables, personality traits and attitudes, and a set of variables they call situational. The volunteer process model of Omoto and Snyder (1995) analyzes the psychosocial factors affecting volunteering.

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As Gaskin (2004) has demonstrated, young people’s behavior, attitudes, and motivations change as they transition from adolescence to their twenties, and various factors affect them depending on their age (Garcia et al., 2014). Flanagan and Sherrod (1998) demonstrate that the period between 14 and 25 is one of great flexibility and openness, and there is a considerable margin to adopt influences. Nevertheless, young people aged between 15 and 24 mention lack of time as the main barrier to volunteering (Hall et al., 2001). Other research emphasizes that gender affects activities and use of time (Eccles & Barber, 1999; Raymore, Godbey, & Crawford, 1994). The studies by Sarre and Tarling (2010) demonstrate that girls and young women have a higher rate of involvement in formal volunteer activities than boys and young men. In general, girls and young women have a more prosocial behavior than boys and young men (Inglés et al., 2009). However, the study by Garcia et al. (2014) shows that males are more likely to become volunteers than females. Prior research (Wilson & Musick, 1999) has found that socioeconomic and educational levels are positively related to volunteering. Sarre and Tarling (2010) demonstrate that the formal volunteering of boys and young men is closely related to the socioeconomic status of their homes. Educational levels are considered to be a good predictor of volunteering (Gesthuizen & Scheepers, 2012). Concerning beliefs, civic orientations, and ideology, Hodgkinson (1995) posits that commitment and involvement are higher among those who actively practice religion and that the Judaeo-Christian teaching of helping strangers could explain this leaning toward commitment. However, other studies have found a relationship that is contingent on the type of organization in question (Yeung, 2004). In a broader sense, highly self-confident people are more likely to become involved in voluntary organizations (Uslaner & Conley, 2003). Furthermore, growth in post-materialist values increases the likelihood of people participating in voluntary associations (Inglehart, 2003), and community identity encourages volunteering (Pozzi, Marta, Marzana, Gozzoli, & Ruggieri, 2014). This research emphasizes the idea that the association sector is not actually monolithic but instead plural and diverse. The effects that participation in different types of organizations has on their members’ abilities and civic virtues vary (Stolle & Rochon, 1998). In general, expressive organizations or participation promotes more homogeneous networks, whereas instrumental participation furthers the diversity of contacts and is more heterogeneous (Bekkers, Völker, Van Der Gaag, & Flap, 2008). Instrumental organizations relate positively with political participation (Frisco, Muller, & Dodson, 2004; Stolle & Rochon, 1998), as instrumental groups focus on targets outside the group. The purposes of instrumental participation go beyond the mere enjoyment of participating and sociableness; they seem to indicate some social vocation that aims to influence public behavior based on certain values or the regulatory conditions they promote. In contrast, expressive organizations exist, above all, to allow their members to express themselves and meet their needs, and their structure and aims are more homogeneous (Glanville, 2004). These organizations offer entertainment, and their impact does not seem to last as long as the attitude of their members (Glanville, 2004; Metz et al., 2003).

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Database: EVS and Organization for Economic Co-Operation and Development (OECD) Health Data We combined data on individuals with national contextual data to conduct a crosssectional study. The sample comprised of 6,202 individuals from 18 to 29 years old living in 20 European countries for the years 1999 and 2008. The micro-data were obtained from the EVS (1999 and 2008) because its questionnaire includes questions on socioeconomic characteristics and volunteering. The explanatory variables we considered for individuals are as follows: sociodemographic (age, gender, marital status, employment status, educational level, place of residence, and population size), membership of a non-governmental association, values and attitudes (how important family, friends, leisure, politics, work, and religion are; the extent to which the individual trusts the Church, the health system, the education system, and social security), and the geographical contextual variables of the various welfare areas (Anglo-Saxon, Continental, Eastern Europe, Nordic, and Mediterranean) and time contextual variables (1999 and 2008 waves). Following the criterion of prior research (Esping-Andersen, 1998; Sardinha, 2010), we grouped the European countries into five welfare categories: (a) Nordic: Denmark, Iceland, Finland, and Sweden; (b) Anglo-Saxon: Ireland and Great Britain; (c) Continental: Germany, Austria, Belgium, France, and Holland; (d) Mediterranean: Spain, Italy, and Portugal; (e) Eastern European: Bulgaria, Czech Republic, Lithuania, Poland, and Romania. Along with the fictitious geographical variables (which identify countries and welfare systems), we defined fictitious variables for each wave (1999 and 2008) to calculate the fixed regional and time effects. The EVS considers voluntary participation in 14 volunteer activities. To simplify matters, we aggregated volunteering into four groups (Sardinha, 2010): (a) social conscience: local political actions, human rights, pacifist movements, environmental conservation, or animal rights; (b) professional: trade unions, political parties, or professional associations; (c) leisure: activities related to education, culture, youth employment, sport, or leisure; (d) social justice: welfare services for vulnerable population groups, the Church, women’s groups, or health centers. Volunteers in social justice or social conscience issues are thought to be motivated by helping others, so these are instrumental organizations, while volunteers in professional and leisure areas could have motives that are more intrinsic to their personality, in other words, they are expressive organizations. For the macro-data, we used OECD Health Data (2008). This database provided us with statistics and indicators for the European countries we studied for the 1999-2008 period. This database gives a wealth of instruments that transcend the health sector and provide an overview of countries’ economic and welfare situation (gross domestic product [GDP] per capita and public expenditure per capita).

Descriptive Analysis The joint analysis of volunteer rates for people above the age of 18 (Figure 1) shows that, in general, for all country groups, leisure activities come first, closely followed

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Figure 1.  Volunteering ratios based on activity and geographical area (%): Above 18 years old. Source. European Values Survey 1999 and 2008. Data self-elaborated from EVS micro-data Note. Standard deviations are close to 0 and in any case less than 1%.

by social justice activities, except for Anglo-Saxon countries where social justice activities occupy the top place. Volunteering in professional or social conscience activities lags behind with substantially lower percentages. On analyzing the gap in volunteer rates among groups of countries, by the type of activity, the most remarkable difference in the leisure area is found between Nordic countries, with a rate of 19.5%, and Mediterranean countries, with a rate of 7.4%. In social justice activities, however, the most striking volunteering difference is observed in 15.3% of the Nordic countries compared with 7.1% of Eastern countries. Regarding social conscience, the most important difference is found between Anglo-Saxon countries with a rate of 6.4% and Eastern countries with a rate of 3.3%. In professional activities, the largest gap is found between Nordic and Mediterranean countries. There are no major differences in standard deviations for volunteering probabilities by groups of countries. It is interesting to note that volunteering differences between countries smooth out if we observe volunteer rates for young people aged between 18 and 29 in isolation (Figure 2), although the order of preferences remains constant. Among young people, therefore, the main volunteer activity is related to leisure, culture, sport, and free-time activities in general. Free-time activities are followed by social justice, social conscience, and professional activities. In general, young people from Nordic, Anglo-Saxon, and Continental countries have much higher volunteer rates, followed by young people from Eastern and Mediterranean countries. The volunteer gaps between geographical areas again differ based on the activities participated in. The most remarkable difference in the leisure area is between Nordic countries with a rate of 18.9% and Mediterranean group with a rate of 11.9%. The most marked difference in social justice

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Figure 2.  Volunteering ratios based on activity and geographical area (%): Between 18 and 29 years old. Source. European Values Survey 1999 and 2008 (own production). Note. Standard deviations are close to 0 and in any case less than 1%.

activities is between Anglo-Saxon and Eastern countries with rates of 10.2% and 5.2%, respectively. Regarding social conscience activities, the most important difference is found between Anglo-Saxon countries with a rate of 4.7% and Eastern countries with a rate of 3.9%. Finally, in professional activities, the largest volunteer gap between two of the groups is found between Nordic and Mediterranean countries with a difference of 3.2 points in favor of the former. However, the main result we wish to highlight is that geographical differences smooth out for younger population groups. Concerning voluntary participation in social conscience issues, younger respondents are less active than older people in Continental (3.6%-4.9%), Anglo-Saxon (4.7%-6.4%), and Nordic (4.6%-6.0%) countries; but the opposite is true for residents in Eastern (3.9%-3.3%) and Mediterranean (4.5%-3.6%) countries. Once again, there are no major differences in standard deviations for volunteering probabilities across groups of countries. The sample is distributed equally between men and women, and the mean age is 23.7 years. Table 1 highlights the mean of the variables we considered in this study. We know from the means shown in Table 1, for example, that 76.3% of the young European respondents are single and almost half live with their parents. For 59.2%, their main activity is work and 26.1% are studying. Unemployment affects 10.0% of these young people. Young Europeans value their family and friends above all else, followed by work and leisure. In contrast, the importance they give to politics and their region is limited. Table 2 shows national variables on economic figures that help us understand the differences among welfare systems. All these variables were measured in dollars (constant prices adjusted to purchasing power in 2000) and in per capita terms for

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Table 1.  Descriptive Statistics. Variables European value survey  SocialConscience  Professional  Leisure  SocialJustice  Age  Female  Male  Single  LiveParents  Works  Housewife  Student  Unemployed  Primary  Secondary  Tertiary  Population ≥ 500,000  SocialConscienceGroup  ProfessionalGroup  LeisureGroup  SocialJusticeGroup  FamilyImportance  FriendsImportance  LeisureImportance  PoliticsImportance  WorkImportance  ReligionImportance  ChurchTrust  HealthTrust  EducationTrust  SocialSecurityTrust OECD health data  GDP   PublicExpenditure: Work  PublicExpenditure: Unemployment   PublicExpenditure: Other

Description

M

SD

Volunteer in social conscience issues Volunteer in political and professional issues Volunteer in educational, sport, and leisure issues Volunteer in social justice issues Age Female Male Single Living with parents Worker Housewife Student Unemployed Primary education Secondary education University studies Residence in a place with more than 500,000 inhabitants Member of a non-governmental association engaged in social conscience issues Member of a non-governmental association engaged in professional and political issues Member of a non-governmental association engaged in educational, sport, and leisure issues Member of a non-governmental association engaged in social justice issues Considering family as an important aspect of life Considering friends as an important aspect of life Considering leisure as an important aspect of life Considering politics as an important aspect of life Considering work as an important aspect of life Considering religion as an important aspect of life Trusting the Church Trusting the health system Trusting the educational system Trusting the social security system

0.041 0.034 0.166 0.074 23.671 0.521 0.479 0.763 0.468 0.592 0.047 0.261 0.010 0.156 0.636 0.208 0.154

0.199 0.180 0.372 0.262 3.457 0.501 0.499 0.424 0.499 0.365 0.212 0.439 0.299 0.078 0.481 0.405 0.361

0.107

0.308

0.171

0.376

0.355

0.478

0.191

0.393

0.979 0.959 0.911 0.330 0.933 0.343 0.380 0.655 0.694 0.518

0.143 0.199 0.284 0.470 0.250 0.474 0.485 0.474 0.460 0.499

Per capita gross domestic product (adjusted to purchasing power) Per capita national public expenditure on work (adjusted to purchasing power of countries) Per capita national public expenditure on unemployment (adjusted to purchasing power of countries) Remaining per capita national public expenditure (adjusted to purchasing power of countries)

25,270.877

5,776,296

197.866

140,660

336.111

244,529

5,118.498

1,676.622

Note. We have also included geographical dummy variables (Nordic: Denmark, Iceland, Finland, and Sweden; Mediterranean: Spain, Italy, and Portugal; Anglo-Saxon: Ireland and Great Britain; Continental: Germany, Austria, Belgium, France, and Holland; Eastern: Bulgaria, Czech Republic, Lithuania, Poland, and Romania) and time dummy variables (1999wave and 2008wave). OECD = Organization for Economic Co-Operation and Development.

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Gil-Lacruz et al. Table 2.  Economic Variable Descriptors Based on Geographical Context in 2008. Public expenditure  

GDP per capita

Work

Unemployment

Other

Continental Anglo-Saxon Mediterranean Nordic Eastern

28,133.68 (53.66) 29,069.86 (107.78) 22,080.29 (68.39) 29,334.03 (80.19) 15,646.12 (94.64)

270.60 (1.50) 175.55 (2.61) 119.38 (0.59) 305.92 (4.96) 45.87 (0.58)

485.19 (4.38) 212.02 (3.45) 286.14 (3.79) 443.14 (6.72) 74.26 (0.84)

6,461.56 (15.42) 4,460.89 (40.40) 4,381.03 (26.81) 6,060.44 (32.98) 2,826.51 (15.38)

Source. Table self-elaborated from data of OECD Health Data, 2008 Note. Standard deviations in brackets. Variables measured in US Dollars (constant prices adjusted to purchasing power in 2000) and in per capita terms. GDP = gross domestic product.

2008. Nordic, Anglo-Saxon, and Continental countries generate the highest annual GDP per capita (around $28,000) (mean for the countries that are included in each geographical group), followed by Mediterranean countries (around $22,000) and Eastern European countries (around $16,000). Countries with a higher GDP per capita are in a better position to spend more government money per capita. While the total public expenditure of Anglo-Saxon countries and Mediterranean countries is similar, expenditure distribution shows large differences. Whereas in Mediterranean countries more government money is spent on unemployment, in Anglo-Saxon countries more public money is spent on work issues.

Empirical Framework The first approximation to the problem comprises independent estimations on the individual likelihood of working as a volunteer for each of the categories. Therefore, the dependent variables are dichotomous, adopting the value 1 (if there is volunteer activity) and 0 (if there is not). We employed Logit models for the estimation method, which comprises a discrete non-linear response model. We used tables to show the data valued in terms of elasticity (percentage variation of the dependent variable on modifying the independent variable by 1% keeping the other explanatory variables constant), so that the estimated parameters can inform us of both the meaning and intensity of the effects of independent variables.

P ( SocialConscience = 1 | x ) = G ( xβ1 ) , (1)



P ( Professional = 1 | x ) = G ( xβ2 ) , (2)



P ( Leisure = 1 | x ) = G ( xβ3 ) , (3)



P ( SocialJustice = 1 | x ) = G ( xβ4 ) , (4)

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where x represents the set of independent variables and β its associated parameters. The challenge consists of estimating β as realistically as possible. We repeated the estimations 3 times. The variables we included in Model 1 are as follows: sociodemographic (age, gender, marital status, employment status, educational level, place of residence, and population size), membership of a non-governmental association, values and attitudes (how important family, friends, leisure, politics, work, and religion are to individuals; the extent to which the individual trusts the Church, the health system, the education system, and social security), and the geographical contextual variables of the various welfare areas (Anglo-Saxon, Continental, East, and Mediterranean compared with Nordic) and time contextual variables (2008 compared with 1999). The variables for being a member of non-governmental groups and values and attitudes could introduce technical problems of endogeneity, for example, that the individual decides to become a member of an association and volunteer at the same time, or that variables determining the decision to volunteer also condition belonging to that group, among other casuistry. As these variables are conditioned by the environment, we repeated the estimations but changed these variables (Wooldridge, 2002). In Model 2, instead of considering individual variables, we took into account national means of individuals aged between 18 and 29. As social pressure could be more far-reaching, as the fact that adults volunteer could influence their children to do the same, in Model 3 we considered the national means of these variables for a population aged above 18. This choice not only reduces possible endogeneity but also controls social pressure. Finally, in Model 4, dummy regional variables inform us of the effect of those relevant variables that we did not control in the regression. Dummy regional variables could inform us on how welfare systems reinforce individual decisions to volunteer. Given the intensity and significance of geographical variables, we repeated the estimations for the last time and only for the best model of the above three. We included national economic information (GDP per capita and government expenditure per capita) in the set of explanatory variables.

Results We will use the structured order of the previous section to explain the results. Table 3 considers the estimations of the probability of volunteering only taking individual variables into account. One of the main results is that being a member of a nongovernmental group positively reinforces participation as a volunteer in that organization and, in general, also in other types of activities, with the only exception that belonging to a professional group reduces the likelihood of participating in social justice activities. The geographical differences of this model are also relevant. We are being cautious about these estimations at the moment, as being a member of nongovernmental groups can introduce technical problems of endogeneity that appear as high and significant parameters for the affected variables and reduce the effect and significance of the variables. This could explain both belonging to the group and voluntary participation (e.g., educational level).

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Gil-Lacruz et al. Table 3.  Voluntary Work Determinants: Model 1 (Logit: dx / dy). Social conscience Ln(Age) Femalea Male Single LiveParents Worksa Housewife Student Unemployed Primarya Secondary Tertiary Secondary&Student Tertiary&Student Population ≥ 500,000 SocialConscienceGroup ProfessionalGroup LeisureGroup SocialJusticeGroup FamilyImportance FriendsImportance LeisureImportance PoliticsImportance WorkImportance ReligionImportance ChurchTrust HealthTrust EducationTrust SocialSecurityTrust Nordica Mediterranean Anglo-Saxon Continental Eastern 1999Wavea 2008Wave Pseudo-R2 (%) Probability estimation (%) aReference

0.0051 — −0.0010 0.0016 −0.0043** — −0.0042 0.0083 0.0007 — −0.0023 −0.0049* −0.0030 0.0063 −0.0008 0.2599*** 0.0003 0.0067*** 0.0033 0.0029 0.0029 −0.0038 0.0017 −0.0005 −0.0004 0.0005 −0.0006 −0.0047** 0.0006 — 0.0138*** 0.0319*** 0.0015 0.0110* — 0.0013 37.71 4.10

Professional

Leisure

Social justice

−0.0020 — 0.0021* −0.0007 −0.0018 — −0.0004 0.0058 0.0042 — 0.0018 0.0038 −0.0014 −0.0034 0.0001 0.0048** 0.1967*** 0.0022* 0.0008 −0.0040 −0.0017 −0.0034 0.0042*** −0.0013 −0.0005 0.0006 −0.0006 0.0003 −0.0004 — 0.0137*** 0.0172*** 0.0038** 0.0147*** — 0.0005 37.67 3.60

0.0649*** — 0.0199*** 0.0104 0.0106 — 0.0075 −0.0010 −0.0049 — 0.0035 0.0090 0.0135 0.0013 −0.0216*** 0.0150* −0.0006 0.4173*** 0.0191*** 0.0173 0.0175 −0.0182 0.0033 0.0011 0.0067 0.0137** 0.0047 −0.0056 0.0012 — 0.0237* 0.0512** 0.0043 0.0391*** — 0.0011 34.63 17.59

−0.0142 — −0.0069** 0.0007 −0.0100*** — −0.0044 0.0059 −0.0051 — 0.0005 0.0050 −0.0009 0.0008 0.0033 0.0456*** −0.0069** 0.0130*** 0.2768*** −0.0052 −0.0108 0.0033 0.0030 0.0001 0.0205*** 0.0027 −0.0043 −0.0028 0.0037 — 0.0454*** 0.0557*** 0.0194*** 0.0330*** — 0.0021 36.81 7.82

variable. So as not to lengthen the table, we have only given this where there are three or more values involved, for example, 2008Wave must be interpreted in relation to 1999Wave. ***, **, and * indicate that the explanatory variables are significant at 1%, 5%, and 10%, respectively.

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In Table 4, we substituted the individual variables on being a member of nongovernmental groups, importance of different areas of life, and trust in institutions by youth means (excluding self-observation). The most relevant results include two main aspects. On one hand, being a member of non-governmental groups reinforces the decision to participate voluntarily in their activities, but the complementary effect is diluted by other activities. On the other, socioeconomic variables concerning individuals gain explanatory power. For example, single people are more likely to participate as volunteers in social conscience and leisure activities. Being a student and attaining a higher educational level reinforce voluntary participation. As social pressure can stem not only from similar-aged peers but can also be influenced by other people, we repeated estimations with means for the population above 18. Although this model (Table 5) provides us with data similar to those of the previous model, it allows us to observe that pressure from individuals of the same age is greater than the pressure exerted by the general population. We selected Model 2 to continue with the empirical development due to both the significance analysis of the variables (p value) and the joint significance test (greater pseudo-R2 and fewer gaps between estimated and actual probabilities). Finally, Table 6 considers the macro-variables in the estimation of the probabilities of volunteer rates. With reference to socioeconomic variables, age reinforces volunteering in professional and leisure-time activities, although over the years, the upward trend has slowed down. Men are more inclined to volunteer in professional and leisure activities, while there is a higher percentage of female volunteers in social justice activities. Being single reinforces the decision to volunteer in social conscience and leisure activities, and living with parents also has a negative impact on professional and social justice activities. Being a housewife or unemployed reduces the probability of volunteering compared with being in work, while being a student seems to reinforce it. Educational level reinforces voluntary activities, especially leisure-time activities. The results for being a member of non-governmental associations are robust, so that higher percentages of young people affiliated to a group reinforce their own activity. The attitudes of the younger population seem more relevant than the trust they place on institutions to consolidate their volunteer rates. Placing importance on political activity reinforces volunteer decisions in social conscience and professional activities, whereas placing importance on work curbs the decision to become a volunteer. Placing importance on religion promotes social justice issues but also professional activities. One of the most important results provided in this table is that considering macroeconomic variables has made the contextual variables of the welfare systems lose statistical significance. The larger the individual’s purchasing power (GDP per capita), the less likely they are to volunteer for social justice issues. More public expenditure on employment issues reduces volunteering in leisure and professional issues, whereas more government expenditure on unemployment issues promotes all volunteer activity. The same can be said of government expenditure on other items. All increases/ decreases are smoothed out as the economic items rise (all the effects in absolute value are less than 1).

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Gil-Lacruz et al. Table 4.  Voluntary Work Determinants: Model 2 (Logit: dx / dy).

Ln(Age) Femalea Male Single LiveParents Worksa Housewife Student Unemployed Primarya Secondary Tertiary Secondary&Student Tertiary&Student Population ≥ 500,000 YMSocialConscienceGroup YMProfessionalGroup YMLeisureGroup YMSocialJusticeGroup YMFamilyImportance YMFriendImportance YMLeisureImportance YMPoliticsImportance YMWorkImportance YMReligionImportance YMChurchTrust YMHealthTrust YMEducationTrust YMSocialSecurityTrust Nordica Mediterranean Anglo-Saxon Continental Eastern 1999Wavea 2008Wave Pseudo-R2 (%) Probability estimation (%)

Social conscience

Professional

Leisure

Social justice

0.0228 — −0.0041 0.0083* −0.0161*** — −0.0201*** 0.0429** −0.0089 — 0.0026 0.0110 −0.0191** −0.0102 −0.0024 0.1072* −0.0691 0.0059 0.0275 0.9400*** −0.1650 −0.0086 0.0295 −0.4080*** 0.0594 −0.1579*** −0.1329** 0.1324** 0.0352 — −0.0076 −0.0333*** −0.0243 −0.0329*** — −0.0224*** 4.96 3.90

0.0333** — 0.0097*** 0.0021 −0.0088* — −0.0178*** 0.0145 −0.0051 — 0.0070 0.0335*** −0.0098 −0.0193*** −0.0045 0.0122 −0.0288 0.0358 0.0271 0.6216*** −0.2865* 0.0411 0.0426 −0.2256*** 0.0756** −0.1440*** −0.0579 0.0807 −0.0162 — −0.0241* −0.0279*** −0.0382** −0.0330*** — −0.0124* 6.71 3.48

0.0918** — 0.0633*** 0.0227* 0.0409*** — −0.0513*** 0.0729** −0.0595*** — 0.0436*** 0.1188*** −0.0171 −0.0561** −0.0540*** 0.1261 −0.2239*** 0.3461*** 0.0417 0.4985 −0.8307* 0.1816 0.0809 −0.1249 0.1176 −0.2268** −0.0492 −0.0836 −0.0263 — −0.1319*** −0.0572 −0.1302*** −0.1255*** — −0.0275* 6.80 17.51

0.0174 — −0.0234*** 0.0042 −0.0151** — −0.0147 0.0495* −0.0256*** — 0.0133 0.0403*** −0.0277* −0.0230 −0.0086 0.1545** −0.2674*** 0.0903* 0.1041* 0.7686*** −1.1111*** 0.2425*** 0.1036* −0.2932** 0.1308** −0.1872*** 0.0666 0.0769 −0.1661* — −0.0631*** −0.0560*** −0.1011*** −0.0865** — −0.0137 5.42 7.67

Note. YM: Young people mean (population between 18 and 29 years old). The observation for individuals has been discounted for this calculation. aReference variable. So as not to lengthen the table, we have only given this where there are three or more values involved, for example, 2008Wave must be interpreted in relation to 1999Wave. ***, **, and * indicate that the explanatory variables are significant at 1%, 5%, and 10%, respectively.

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Table 5.  Voluntary Work Determinants: Model 3 (Logit: dx / dy).

Ln(Age) Femalea Male Single LiveParents Worksa Housewife Student Unemployed Primarya Secondary Tertiary Secondary&Student Tertiary&Student Population ≥ 500,000 TMSocialConscienceGroup TMProfessionalGroup TMLeisureGroup TMSocialJusticeGroup TMFamilyImportance TMFriendImportance TMLeisureImportance TMPoliticsImportance TMWorkImportance TMReligionImportance TMChurchTrust TMHealthTrust TMEducationTrust TMSocialSecurityTrust Nordica Mediterranean Anglo-Saxon Continental Eastern 1999Wavea 2008Wave Pseudo-R2 (%) Probability estimation (%)

Social conscience

Professional

Leisure

Social justice

0.0210 — −0.0042 0.0063 −0.0134*** — −0.0202*** 0.0394* −0.0097 — 0.0043 0.0128 −0.0171* −0.0079 0.0036 0.2535*** 0.1259* −0.1250 −0.0067 −0.6251 −0.5037** −0.0105 −0.1940*** 0.3307*** −0.1632*** 0.1164** −0.0237 0.0157 −0.0584 — 0.0421 0.6873*** 0.0568 0.0023 — 0.0265*** 4.87 3.27

0.0317* — 0.0099*** −0.0004 −0.0074 — −0.0183*** 0.0131 −0.0048 — 0.0095 0.0399*** −0.0077 −0.0189*** −0.0010 0.0753 0.0598 −0.0451 0.0414 0.0443 −0.2284 −0.0187 −0.0287 0.0764 −0.0348 −0.0094 −0.0525 0.0205 0.0266 — −0.0009 0.0964 0.0028 −0.0058 — 0.0052 6.13 2.66

0.0880** — 0.0629*** 0.0190 0.0416*** — −0.0510*** 0.0705** −0.0577*** — 0.0480*** 0.1215*** −0.0121 −0.0524** −0.0466*** 0.0908 −0.3196** 0.5174*** 0.0894 1.6114* −0.8259* 0.0291 0.0768 −0.2263 0.0991 −0.1885 −0.1974** −0.0826 0.1236 — −0.1349*** −0.0746 −0.1230** −0.1254*** — −0.0160 6.85 15.07

0.0109 — −0.0234*** −0.0011 −0.0126* — −0.0142 0.0461* −0.0246*** — 0.0159 0.0488*** −0.0230 −0.0216 −0.0067 0.1697 −0.1707* −0.0560 0.1490*** 0.8469 −0.5117* 0.0600 0.1541** −0.4083*** 0.1311 −0.1451* −0.0335 −0.0303 0.1051 — −0.0484* −0.0558*** −0.0684* −0.0526** — −0.0233** 4.56 6.52

Note. TM: Total mean (population below 18 years old). The observation for individuals has been discounted for this calculation. aReference variable. So as not to lengthen the table, we have only given this where there are three or more values involved, for example, 2008Wave must be interpreted in relation to 1999Wave. ***, **, and * indicate that the explanatory variables are significant at 1%, 5%, and 10%, respectively.

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Gil-Lacruz et al. Table 6.  Voluntary Work Determinants: Model 2B (Logit: dx / dy).

Ln(Age) Femalea Male Single LiveParents Works Housewife Student Unemployed Primary Secondary Tertiary Secondary&Student Tertiary&Student Population ≥ 500,000 YMSocialConscienceGoup YMProfessionalGroup YMLeisureGroup YMSocialJusticeGroup YMFamilyImportance YMFriendImportance YMLeisureImportance YMPoliticsImportance YMWorkImportance YMReligionImportance YMChurchTrust YMHealthTrust YMEducationTrust YMSocialSecurityTrust Ln(GDP) Ln(PublicExpenditureWork) Ln(PublicExpenditureUnemployment) Ln(PublicExpenditureOther) Nordica Mediterranean Anglo-Saxon Continental Eastern 1999Wavea 2008Wave Pseudo-R2 (%) Probability estimation (%)

Social conscience

Professional

Leisure

Social justice

0.0225 — −0.0041 0.0087* −0.0151*** — −0.0189*** 0.0381* −0.0090 — 0.0047 0.0146 −0.0179** −0.0093 0.0006 0.0889* −0.0659 0.0314 −0.0233 0.2643 0.3202 0.0481 0.1352* −0.2817** 0.0598 0.0361 −0.0043 0.0886 −0.1019 −0.0153 −0.0424 0.0640*** 0.0522*** — 0.0735 0.0277 −0.0049 0.1566 — −0.0126 6.15 4.26

0.0345** — 0.0094*** 0.0025 −0.0083* — −0.0172*** 0.0144 −0.0054 — 0.0069 0.0338*** −0.0099 −0.0193*** −0.0036 0.0106 −0.0149 0.0370 0.0056 0.3887 −0.0105 0.0606 0.1091* −0.2465** 0.0903** −0.0817 −0.0125 0.0698 −0.0737 −0.0330 −0.0182** 0.0316*** 0.0163 — −0.0067 −0.0144 −0.0260 −0.0116 — −0.0048 7.07 3.69

0.0860** — 0.0628*** 0.0231* 0.0415*** — −0.0511*** 0.0673** −0.0601*** — 0.0511*** 0.1320*** −0.0154 −0.0528** −0.0480*** 0.1211 −0.1230 0.4111*** −0.0171 −0.7735 0.4134 0.0982 0.1469 0.1282 0.1262 0.1229 0.0473 −0.1455 −0.0952 −0.1255 −0.0758*** 0.0967*** 0.1912*** — −0.0209 0.2461 −0.0553 0.1004 — −0.0095 7.23 18.21

0.0188 — −0.0234*** 0.0063 −0.0150** — −0.0135 0.0486* −0.0268*** — 0.0115 0.0382*** −0.0279* −0.0244 −0.0096 0.1310* −0.1414* 0.0681 0.1199* 0.4214 −0.5531* 0.1293 0.1253 −0.3212* 0.1107** −0.0775 0.0706 0.0356 −0.1565* −0.1108* −0.0076 0.0338* 0.0628** — 0.0029 0.0373 −0.0368 −0.0273 — −0.0029 5.69 7.09

Note. YM: Young people mean (population between 18 and 29 years old). The observation for individuals has been discounted for this calculation. aReference variable. So as not to lengthen the table, we have only given this where there are three or more values involved, for example, 2008Wave must be interpreted in relation to 1999Wave. ***, **, and * indicate that the explanatory variables are significant at 1%, 5%, and 10%, respectively.

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Discussion The results of the first model, which exclusively considers individual variables, show that being male significantly and positively affects being a volunteer in leisure and professional organizations, while its significance is negative in social justice organizations. This suggests that males opt for organizations that are more expressive, while females lean toward instrumental organizations. This result, also present in other estimated models, may be because girls and young women, as posited in other studies (Inglés et al., 2009), have demonstrated significantly higher levels of prosocial behavior than boys and young men, and these differences widen with age. This enables us to qualify the results of other studies (Roker et al., 1999; Sarre & Tarling, 2010), which show that females have a higher participation rate in formal volunteer activities; Valor-Segura and Rodríguez-Bailón (2011) demonstrate a university student volunteer profile with a mean age of 21 to 22 and more women than men. Cruce and Moore (2007) observed additional differences regarding students’ academic majors and their likelihood of volunteering. Our result highlights the importance of considering the type of organization. The results of the model also show that volunteering in a specific work domain is positively influenced by being a member of a non-governmental organization with similar aims. The results coincide with those arrived at by other research, which points out that belonging to extensive social networks, being a member of several organizations, and having prior experience as a volunteer increase the possibility of becoming a volunteer (Haski-Leventhal & Bargal, 2008; Wilson & Musick, 1999). These results can be explained by the social learning theory (Bandura, 1977) and the role identity model of volunteering (Callero et al., 1987). Concerning ideological and attitudinal factors, they have often been associated with helping behavior (Ruiter & De Graaf, 2006; Valor-Segura & Rodríguez-Bailón, 2011). The results show that ideological values, such as trust in religion, have a positive significance for becoming a volunteer in social justice organizations. Trust in the Church2 encourages volunteering in leisure activities and the importance of politics affects volunteering in professional activities. After analyzing the second model, in which individual variables are replaced by youth means (excluding self-observation), being a member of non-governmental organizations significantly and positively affects the decision to volunteer in organizations in which the same activity is performed. This could result from organizations explicitly asking their members to volunteer, a direct request that is highly effective (Smith, 1994) because they know the work this type of organization performs (McAdam & Paulsen, 1993) and they have friends and a large support network in the organization (Smith, 1994). Young people also learn how to behave through modeling (Bandura, 1977; García, Marcuello, & Saz, 2015). The assessed importance of friends has a negative effect on volunteering, except in social conscience activities, whereas the assessed importance of family has a positive significance on volunteering, except in leisure activities. Individuals’ age might determine this result. The oldest of the young people, at a stage in their lives when they are

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more aware of the importance of family and social problems, represent the group that is more likely to volunteer. The younger group is less likely to volunteer, however. This might stem from them investing more time in their education and in developing their own human capital. They are also at a stage when they pay more attention to their friends than to their family members. In this second model, socioeconomic variables related to individuals gain explanatory power, which is in line with previous research (Verba et al., 1995). According to these authors, for example, people with a high socioeconomic status are more likely to volunteer because they have more verbal, writing, and social skills, which give them more confidence to reach out to others and make them more desirable as volunteers. The third model, in which youth means are replaced by the national means of the variables for a population above 18, highlights that the significance of the demographic variables of the first model and the socioeconomic variables of the second model is similar. It also shows that, among young people, peer pressure from individuals of the same age is more influential than the pressure older people exert. Finally, in the fourth model, which considers macro-variables in the estimation of the probabilities of the volunteer rate, we observe that the results for the socioeconomic variables are the same as those for the previous models. A higher level of education positively affects volunteering, as does being single (García et al., 2014). The results for being a member of non-governmental associations are the same as in the previous models. Once we introduce macro-indicators, the dummy variables identifying welfare systems lose explanatory power. National economic indicators are important determinants of country welfare systems. Voluntary participation in national economic programs that have government money spent on them is significant. It is worth noting that more government expenditure on unemployment issues encourages all volunteer activity in all organization types, while public expenditure on employment is not an incentive for volunteering. One explanation for these results is that government expenditure on unemployment3 affects people with fewer economic resources (Verba et al., 1995). In general, young people are more vulnerable to precarious economic conditions than adults, so unemployment benefits might have more impact on their welfare than public expenditure on employment. In short, we conclude that the results of this research are in line with those obtained in previous studies. Although an individual’s socioeconomic characteristics are relevant when deciding to participate in voluntary activities, variables related to grouping in non-governmental associations and attitudes relating to different areas of life exert more pressure. Our work demonstrates that, although individual variables are relevant for analyzing volunteer rates, population information on behavior and attitudes must also be taken into account. The social pressure young people place on each other is greater than the social pressure stemming from the general population. Consequently, if specific population groups need to be addressed, actions focused only on them might be the answer. Finally, the macroeconomic figures characterizing the countries’ welfare systems help us understand contextual differences. Stimulating certain economic items, for example, specific government expenditure on unemployment, can strengthen youth

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volunteer decisions. The influence and effects of public expenditure and other environmental factors should be studied in greater detail. For example, further research is needed to understand who benefits and why from different types of government expenditures along with their associated targets and externalities. Acknowledgments The authors gratefully thank the anonymous Nonprofit and Voluntary Sector Quarterly (NVSQ) referees and the NVSQ editor for their helpful comments and suggestions.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors are grateful the financial support to the European Social Fund and to Aragonese Regional Government for this research.

Notes 1. The European Voluntary Service is an integral part of the Youth in Action Programme of Commission of the European Communities, 2009 (200 final). See Schizzeretto & Gasperoni (2001) and Walther (2006). 2. The questionnaire by the European Values Survey includes a specific question about individual trust in a list of institutions. The only religious institution included in the questionnaire is the Church. We assume that the term Church refers to a congregation of believers for all religions. 3. Active and passive unemployment policies affect people’s economic and educational resources.

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Author Biographies Ana Isabel Gil-Lacruz is an empirical health economist at Zaragoza University (Spain) and a member of the Wellbeing and Social Capital Studies Group (http://www.unizar.es/bycs/ miembros15b.htm). She has been recently working in the projects sponsored by the National Institute of Health of the United States and by the Spanish Association of Health Economics. Carmen Marcuello-Servós is a senior lecturer at the University of Zaragoza and a coordinator of the Third Sector’s Social and Economic Research Group (http://www.unizar.es/geses). Her research interest includes non-profit economics and management, social capital, Corporate Social Responsibility, and health economics. María Isabel Saz-Gil is a lecturer at Business University of Zaragoza (Spain) and a member of the Third Sector’s Social and Economic Studies Group (http://www.unizar.es/geses), which takes part and collaborates with different research networks.