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The association of economic and cultural capital with the NEET rate: differential geographical and temporal patterns

The association of economic and cultural capital with the NEET rate: differential geographical... Using data from 103 Italian provinces, we investigated the relationship between local/regional development, and NEET. We constructed an indicator of cultural capital and another of economic capital and we studied their relation with the NEET rate. Covariance Structure Analysis with Generalized Least Squares estimation was employed, consider- ing a three time-points retrospective model. Results indicate a consistent protective effect of the economic capital on the NEET rate, both in the short run (2 years) and in the medium run (10 years). However, this effect has been obtained in the Central provinces (at 2 and 10 years) and Southern provinces (at 10 years), but not in the North- ern provinces. A mediation analysis indicated that, historically, the cultural capital may partly mediate the effect of the economic capital. We did not detect a significant direct effect of the cultural capital on the NEET rate, which is strongly mediated by the action of the economic capital. Together, these results denote that the economic capital is a strong predictor of NEET, but not in very competitive economic areas. Keywords: Cultural capital, Economic capital, NEET, School dropout, Southern European welfare 1 Introduction we will investigate these issues using national retrospec- The individual trajectories of adolescent development, tive data. including educational attainment and participation in Contemporary European societies are, in general, char- the labor market, should be studied in conjunction with acterized by advanced and knowledge-based economies, the role of macro-level determinants, which may play a as well as by strong welfare systems and social services. top-down effect on teenagers’ behavior and interact with However, there is also high heterogeneity across and micro-level variables. This paper specifically investigates within countries (Mayer 2004), which makes important the role of economic and cultural capital on young peo- the study of macro-level variables for a deep understand- ple who are neither in employment nor in education or ing of social change and of youth transition to adulthood training (NEET)s. While being NEET reflects a multifac - (Buchmann and Kriesi 2011). It is particularly worth plac- torial phenomenon, whose main determinants have been ing the study of NEET in this high-level framework, since partially highlighted, the literature has paid less attention this may provide policy makers with a comprehensive to the role of the economic capital and of the cultural view on the risk factors involved in this phenomenon. wherewithal offered by a geographical area, as originally Indeed, governmental and international agencies, in par- operationalized by Di Maggio and Mohr (1985). Herein ticular the EU and its institutions, have long targeted this group of young people for intervention and monitoring. Such interest reflects the general objectives of the Lisbon strategy, ratified in 2000 by all Member States. However, *Correspondence: enrico.ripamonti@unimib.it Milan Center for Neuroscience, University of Milan-Bicocca, Piazza on current state of research, there is large heterogeneity dell’Ateneo Nuovo 1, 20126 Milan, Italy Full list of author information is available at the end of the article © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. 13 Page 2 of 17 E. Ripamonti , S. Barberis NEET rate Italy Europe (27) Spain France Germany 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Fig. 1 Time series indicators of the NEET rate in the 27 EU countries, and, nationally, in France, Italy, Germany, and Spain in methods and models followed in such interventions, #U u% = ∗ 100 without a clear and long-term strategy. #L To be included in the definition of #U a person must 1.1 NEE Ts in contemporary European societies not have a job, but, at the same time should be actively 1.1.1 Definition of NEET searching for a job (otherwise he/she would be classified The concept of NEET refers to young people who, since as out of L). While simple in principle, there is debate are not working and, at the same time, are not enrolled in the literature on the measurement of the labor force in school or other formative activities, are not accumu- (Battistin et  al. 2007) and of the unemployment rate lating human capital (Eurofound 2012). Thus, while cor - (Jones and Riddell 1999). The NEET rate has a slightly related to the construct of school dropout (Ripamonti more complicated definition. According to international 2018), NEETs reflect a more radical and extended form institutions (e.g., the International Labor Organization of vulnerability and social exclusion. The acronym NEET or Eurostat), the NEET rate (n%) can be defined as the was firstly used in the United Kingdom in the 1980s, but percentage of the population of a given age, group or sex became popular worldwide starting from 2010, when the who is not employed and not involved in further educa- European Union (EU) adopted the NEET rate as an offi - tion or training (Elder 2015): cial indicator to assess the youth conditions across EU countries. In Fig. 1 we show the time series of the NEET (#Y − (#YE + #YT)) n% = ∗ 100 indicator for the 27 EU countries, and, specifically, for #Y Italy, Spain, France, and Germany. Further graphs and where #Y indicates the number of youths, #YE the num- illustrations are presented in Additional file 1. ber of youths in employment, #YT the number of youths not in employment, but who are in education or train- 1.1.2 The youth unemployment rate and the NEET rate ing. It is worth placing the discussion on NEET and The youth unemployment rate (u % ) can be defined (e.g., unemployed youth in the larger framework of the theory in the Labor Force Survey) as the ratio between the num- of human capital (Becker 1962). Educational achieve- ber of unemployed young people (#U e.g., in the age ment is indeed a proxy of human capital, which affects range 15–24) and the total number of people in the same age range that make up the labor force ( # L = #U + #E, where E indicates the employed), namely (Blanchard At the numerator, where subtracting from #Y, young people that are both in et al. 2017): employment and in education or training simultaneously should not be dou- ble counted. 5101520253035 The association of economic and cultural capital with the NEET rate: differential geographical… Page 3 of 17 13 the economic capital and the economic development 1.1.4 Individu al factors related to NEET (Barro 1991). In the 2000s the economic theory under- NEETs may reflect the impossibility for young people lined the importance of non-cognitive skills (e.g., motiva- to attain the requirements of normative adult models. tion, leadership, initiative, goal-oriented attitude) in the In this regard, there are gender specificities as well as development of human capital (Heckman and Rubinstein personal characteristics to be kept into account. Young 2001). To increasing levels of human capital correspond girls show a more rapid transition to adulthood than increased salaries, and the differential in real wages young men (Malmberg and Trempała 1997). In addi- between skilled and unskilled workers, at least in the tion, while for young men the consequences of becom- US, has enlarged from 1970 to 2005 (Autor et  al. 2008). ing NEET may be mainly related to difficulties in the In addition, a past history of absence of high educational labor market, young women would also experience level and unemployment may also protect teenagers with negative psychological outcomes (Bynner and Parsons respect to the probability of future unemployment and 2002). Education is a second relevant factor associated transition through the NEET status (Narendranathan with NEET. Using data from the British Cohort Study, and Elias 1993). Young people with low levels of educa- it was  found that low instruction levels are likely to be tion have relevant difficulties to entry in the labor market associated with the NEET rate (Bynner and Parsons (Martin 2009). In Southern Europe, young people of all 2002). In the same cohort of young people it was shown educational levels may experience difficulties in finding a how uncertain occupational aspirations would be job and career instability (Brzinsky-Fay 2007). related to NEET (Yates et al. 2011). Health and mental health conditions may also be associated with the NEET status. For instance, actively searching for a job could be hampered by chronic dis- 1.1.3 NEET: A blurred concept orders such as suffering from chronic stress and fatigue In general, NEETs constitute a very heterogeneous (Lim et  al. 2016). In terms of mental health, long-term group of individuals, who, however, share an increased unemployment and loss of interest may lead NEETs to risk of social and labor market exclusion. The very con - a perception of generalized reduced self-efficacy, which cept of NEET has long been criticized, since it would implies resignation and inactivity (Jerusalem and Mit- denote a too general as well as fragmented category, not tag 1995). At the same time NEETs may experience adequate to represent the problems of young people in adverse psychological outcomes, like decreasing of transition to adulthood (Furlong 2006). Heterogene- self-estimate or self-efficacy (Heckhausen 2006), and ity refers to the fact that this category could virtually the very impossibility of actively choosing a different include, at the same time, young people who are not direction in life. If prolonged, the NEET state could employed and not at school but are proactively search- also determine in the young generations a condition of ing for an occupation, as well as people virtually stable protracted inertia and social disengagement (Maguire in their status, without putting in action proper efforts 2015). to ameliorate their condition. In the former group there Many psychological factors have to be discussed in are NEETs looking for their first job (having completed relation to NEET. First of all, motivation (Dietrich and or not the school with a certificate), and long-term Salmela-Aro 2013), which is a key factor to favor the unemployed young people. In the latter group there transition from school to work (Symonds et  al. 2019). are those who, as being long-term unemployed people, Motivation is strictly related to young people’s educa- have been discouraged to search for an occupation, as tional aspirations (Hegna 2014), future expectations well as young people who are temporarily in the NEET (Iovu et  al. 2018), and investing in active efforts in goal condition (e.g., to take care of children or parents). pursuit (Lechner et al. 2016), which are important deter- While, in general, the label “NEET” may capture young minant of educational choices and outcomes. The moti - people at risk of marginalization in contemporary soci- vational factor is a determinant of job search intensity, eties, there does not exist a shared operational defini - which is a very important variable in terms of the possi- tion underpinning this concept. In fact, scholars have bility of changing the NEET status (Vanoverberghe et al. defined the NEET phenomenon in very different ways 2008). and with reference to young people of different ages Motivation is a primary psychological dimension but (Yates and Payne 2006). If we consider NEETs as young should be studied in conjunction with other components people aged 15–29, such definition would cover three that, if activated, may protect the individual from becom- quite different developmental phases, namely late ado - ing NEET. In this regard, three important factors docu- lescence (15–17), emerging adulthood (18–24), early mented in the literature are given by goal attainability, adulthood (25–29) (Arnett 2006). i.e., the ability of self-monitoring one own’s objectives 13 Page 4 of 17 E. Ripamonti , S. Barberis (Nurmi et  al. 2002), the capacity of attributing priorities does not coincide with dropping out from high school, (Brannen and Nilsen 2002), and intrapersonal agency non-completion of school and entering the labor mar- (Graaf and Zenderen 2013). ket without qualifications is a strong determinant of Two classical concepts of general psychology, which transitioning through the NEET condition, especially have to be considered in connection to NEET and youth for women (Salvà-Mut et al. 2016). Basic school achieve- unemployment are coping styles and the locus of control. ments, in terms of literacy and numeracy skills, are a con- The coping style and the ability to cope with stress are a sistent protective factor with respect to the possibility protective factor in terms of completing education and of becoming NEET (Barth et  al. 2019; Kelly et  al. 2012). starting a job (Ngai et al. 2014). The internal locus of con - School is not only a matter of contents or competence, trol is the capacity of the individual to attribute internally but should actively help teenagers in finding their voca - the effect of behavior/conduct, which may play a role in tional specificity, which is an important factor in terms of relation to NEET and other developmental tasks of ado- job placement (Vogtenhuber 2014). lescence and of the emerging adulthood (Sharon 2016). There is a large amount of studies documenting the Career preparation, a factor related to the locus of con- important role of internships, extra-curricular activi- trol, predicts adolescents’ satisfaction and career success ties, investment on soft skills, and experiences like the (Hirschi 2010). However, having an internal locus of con- “gap year” in helping teenagers in the phase of transition trol seems a not sufficient condition for protecting young from school to work (Aguilar et  al. 2018; Sortheix et  al. people against becoming NEET for those living in dis- 2013; Stehlik 2010; Vanoverberghe et al. 2008). The litera - advantaged socio-economic conditions (Ng-Knight and ture has underlined the importance of the psychological Schoon 2017; Vancea and Utzet 2018). dimension of these paths, which should be perceived by the individual as an opportunity to ameliorate his/her 1.1.5 Familial and peer‑group related factors own outcome in the labor market (Taylor et  al. 2015). At a micro level, parental educational level as well as Important macro-level variables should be kept into parents’ support may have a protective effect on the risk account, since, at least in the EU countries, there is a cer- of becoming NEET, for both male and female teenag- tain variation in the real possibilities for young people to ers (Alfieri et al. 2015). NEETs are likely to live in a fam - invest in apprenticeships and internships (Lehmann et al. ily with one parent, and where parents are not working 2015). (Barham et al. 2009). The literature has shown how being A possible solution to contrast the NEET phenomenon NEET is associated with presence of poor or inadequate is given by starting a self-employed activity. While, as familial models and backgrounds (Robson and Team documented in a large study involving 11 EU countries, 2008), or to intergenerational influences (Bynner and this may protect young people from social exclusion Parsons 2002). At a macro level, being NEET is more fre- and unemployment (Dvoulety et  al. 2018), it could be quent in Southern than in Northern European countries, not achievable or realistic for the most frail and inactive with the former being characterized by a familialistic pro- segment of NEETs. In fact, given the personal and psy- tective welfare (Esping-Andersen 1990). As concerns the chological vulnerability of NEETs, it may be not easy for role of the group of peers, it is certainly a fundamental them, even with the help of formative programs or men- component of socialization in adolescent development, tors, to develop a specific business idea (Nabi et al. 2015). whose effect can go beyond familial factor (Harris 1995). There is also recent literature linking the role of the group 1.1.7 Contextual factors of peers with high school dropout (Ripamonti 2018). The level of poverty measured at community level has The role of the peer group and a constellation of nega - been proposed as a key variable to understand the mech- tive behaviors, like crime and violence, has been recently anism of social exclusion, indirectly favoring outcomes highlighted in Canadian NEETs (Henderson et al. 2017), like becoming NEET or school dropout (Harding 2003). while in Europe this specific issue, to our knowledge, has However, while associated with low socio-economic sta- been less studied. tus, the NEET condition is not exclusive of young people living in poverty or homeless (Thompson 2011). Indeed, 1.1.6 Organizational and work‑related factors being NEET may not be per se a matter of economic dis- There are some factors associated  with the NEET status advantage, but a signal of a developmental difficulty of that are related to the organizational and work environ- these teenagers in terms of adjusting their life trajectory ment. As to the school environment, recent research in the direction of adulthood (Chen 2011). A role of the from Nordic countries indicates that the excess risk for geographical context (living in rural and provincial ter- NEET can be attributed to teenagers’ poor performance ritories vs. cities and metropolises) has also been sug- at school (Berlin et  al. 2020). While becoming NEET gested, at least in terms of school completion (Swanson The association of economic and cultural capital with the NEET rate: differential geographical… Page 5 of 17 13 2004). Becoming NEET could be a consequence of the investigation) with scarce development of innovative increasing complexity of the EU labor market system policies connecting formative tracks with the possibility (Raffo and Reeves 2000). The presence and prevalence of finding a job, which may have reflected in high unem - of NEETs in the EU may also be linked to the special ployment rates in  the young generations (Breen 2005). needs of the local economy (e.g., request of low-skilled, Three labor market reforms (Treu in 1997; Biagi in 2003; low-paid workers) (Simmons 2008). At a local level, in an Poletti in 2014) have been approved in order to liberal- analysis conducted in the Austrian federal states, Bacher ize temporary jobs and to encourage companies hiring et  al. reported that expenditures for active labor market new employees. However, the side effect of these Jobs policy and other contextual factors can explain the geo- Acts is that the labor market has been made precarious, graphical difference in the NEETing rate (Bacher et  al. especially for young people (Barbieri and Scherer 2009). 2017). As a consequence, enterprises have been discouraged from investing in permanent training and specialization 1.1.8 Is NEET a choice? (Blanchard et  al. 2017). This may have led to the high Rarely, and for a very low percentage of the young popu- NEET rate that has been described in Italy in the last lation, becoming NEET has been described as a choice, 10–15 years. on a temporary or voluntary basis. These conditions include, for instance, the situation of temporary NEET 1.3 Cultural capital and education in which are teenage parents taking care of their children The dynamics underpinning a complex phenomenon like (Contini et  al. 2019), which should not be automatically NEET, reflecting scarce accumulation of human capi - deemed as negative (Simmons and Thompson 2011). tal, should be investigated also keeping into account the Hence, not all NEETs would be at the same risk of social putative role of macro-level variables, such as the eco- exclusion (Yates and Payne 2006). We remark that volun- nomic capital, the social capital, and the cultural capital, tary NEETs are counted in the official definition of NEET as well as their interaction with the micro level (Billari and contribute to the uncertainty and heterogeneity of 2004). To provide an example, not being employed or in the description of this phenomenon. a formative track could also be related to high-level vari- ables like living in familialistic cultures typical of South- 1.2 C ountry setting: Italy ern Europe, which in general provide strong support and In Italy the rate of NEETs, considering the age range protection to teenagers when they are not participating 15–29 years, was at 23.4% in 2018, with huge regional in the labor market (Kalmijn and Saraceno 2008). differences (ISTAT 2019): 15.6% in Northern provinces, Following the Weberian tradition, individuals do not 19.6% in Central provinces, and 33.8% in Southern prov- only belong to a certain social class (mainly reflecting inces (see the Additional file  1). It is worth putting the their position in the labor market), but also have a cer- investigation of the effect of economic/cultural capital tain status in the society, which reflects participation on NEET in the Italian context, which is characterized to a collectivity and is not just a constrained function by relevant geographical differences across the coun - of social class. In this context, the construct of cultural try in terms of both economic performance and welfare capital (Bourdieu 1986, 1984, 1970) refers to intellectual state. While the ISTAT has long highlighted the different and educational factors that could foster social mobil- NEET rate between Northern and Southern provinces, ity, beyond mere financial security or economic assets there is not extensive literature addressing the possible (economic capital), and beyond relation, group member- determinants of this gap, which is generally and primarily ship, support (social capital). In this paper we adopt the attributed to the territorial differences in the economic construct of cultural capital on a larger scale than that performance. In addition, Italian provinces have differ - originally proposed by Bourdieu, i.e., we measure the cul- ent history, cultural practices, and civic traditions (Put- tural capital developed in a certain geographical region nam et  al. 1994). Italy, like France and other Southern at an aggregated level (DiMaggio 1982). Indeed cultural European countries (Ferrera 1996), is characterized by capital can be conceived at a macro-system level (Ford a strong welfare system provided by the State. However, and Lerner 1992), in terms of the possibility offered to with the regionalization process following the 2001 Con- the population to participate and being involved in the stitutional reform, a rather marked variability in welfare society and in cultural activities (DiMaggio and Mohr regimes across Italian regions did emerge, especially as 1985). Bourdieu primarily described cultural capital at concerns the organization of vocational training. an individual or familiar level, as a factor contributing Italy is also a country with a highly regulated labor to the social reproduction at a macro-level, in terms, for market and, at least until 1997 (the first time-point instance, of intraclass difference; this has been opera - for the assessment of economic capital in the present tionalized also in the recent literature on educational 13 Page 6 of 17 E. Ripamonti , S. Barberis outcomes (Tramonte and Willms 2010). There is justifica - or Spain) than Germany or Nordic countries. Moreover, tion in the sociological literature to embrace a larger view in Southern European countries, like Italy, there is an of cultural capital from a multilevel perspective (Reay inter-regional gradient with Northern regions outper- 2004). This line of thinking can be attributed to Bourdieu forming Southern regions in terms of both the economic himself (Brubaker 1985), who differentiated between performance and the NEET rate (ISTAT 2019). While the embodied, objectified, and institutionalized cultural capi - association between the economic capital and the NEET tal (Bourdieu 1984), and to the sociologist Paul DiMag- rate has been reported at a descriptive level, the struc- gio, who clearly distinguished between cultural capital at tural mechanisms underlying these phenomena are far an individual level, and cultural capital at a macro level, in from being clarified. terms, for instance, of cultural goods produced by a soci- ety (DiMaggio 1991). Other authors have already adopted 1.5 Hypotheses the construct of cultural capital at an aggregate level and This paper aims to study putative protective factors on from a systemic perspective, for instance in the ecologi- the NEET rate through a large-scale and place-based cal literature (Berkes and Folke 1994), or in the economic approach, analyzing the role of macro level variables. We literature in terms of cultural assets (Throsby 1999). In pointed to clarify, at a detailed geographical level, the order to put cultural capital in the context of the pre- impact of both economic and cultural capital on becom- sent investigation, it is worth remarking that it has been ing NEET. A diachronic perspective  was employed, shown how, in Italy, this would be very heterogeneous assessing cultural capital, economic capital and the NEET across provinces (Ripamonti and Barberis 2018). Central rate at three different time points. First, we hypothesized provinces would attain the highest levels of cultural capi- that to high levels of cultural capital in a certain geo- tal, followed by Northern and Southern provinces. graphical area may correspond valuable cultural oppor- tunities offered to teenagers, and this might promote the 1.4 E conomic capital and education development of their cognitive and non-cognitive skills The economic capital, at different levels of aggregation, is (Heckman and Rubinstein 2001), thus protecting them an important predictor of educational attainment. Classi- from becoming NEETs. This prediction also follows from cal studies of developmental psychology and economics Ripamonti and Barberis (2018), who reported a protec- of education have documented that, in children, poverty tive effect of cultural capital on high school dropout, but and family income are associated with cognitive develop- with relevant differences across Italian provinces. Sec - ment and behavioral patterns (Duncan et  al. 1994). The ond, we assumed that living in areas characterized by human capital (Becker 1962) of parents, which is a proxy strong economic performance could have a protective of the economic opportunities for the family members, effect on the NEET rate, and we aim to clarify whether has been described as a protective factor for pupils in such putative effect is of direct type or may be mediated terms of school achievement and better social outcomes by cultural capital. Third, we aimed to investigate possi - (Brooks-Gunn et  al. 2006; Janosz et  al. 1997). Quality of ble mediation effects of cultural/economic capital on the home and of day care environments, which are strongly NEET phenomenon. correlated to the economic capital at an aggregate level, have also been described to be associated with cognitive 2 Methods abilities and language development (Broberg et  al. 1997; 2.1 Databases Burchinal et  al. 1996). Together, these findings highlight Data on the NEET rate (at aggregated level) from 103 the importance of assessing an adverse outcome such as Italian provinces were obtained from the database of the becoming NEET, keeping into account the specific back - “Rapporto BES” of the Istituto Nazionale di Statistica ground of the place where teenagers live, especially in (ISTAT 2019). This is an integrated and comprehensive terms of the economic performance. Indeed, the litera- data source on the performance of the Italian provinces ture has shown that the NEET phenomenon is intrinsi- that presents the main economic, social and environmen- cally related to the structural economic and labor market tal indicators of the country. In particular, the NEET indi- characteristics. In a study conducted in Ireland, it  was cator is the measure annually provided by the Institute in clearly demonstrated the connection of the economic the Labor Force Survey. From the ISTAT database we also recession of 2008 with the NEET rate, despite the general selected variables on the economic performance. Data on characteristics of this population were basically the same cultural capital have been obtained from the researches of the pre-crisis society (Kelly and McGuinness 2015). In on the Quality of Life in Italy yearly published by Il Sole this line, European statistical institutes have long under- 24 Ore, namely the leading and most authoritative Italian lined that the NEET rate is higher in countries with dif- economic newspaper. This database, which also adopts ficulties in the economic performance (e.g., Italy, Greece The association of economic and cultural capital with the NEET rate: differential geographical… Page 7 of 17 13 some of the ISTAT indicators, has been already described which is also transformed in the researches on the Qual- elsewhere (Ripamonti and Barberis 2018). ity of life in an employment score (EMP07). Four latent variables have been introduced, namely CUL97 and 2.2 M easures and latent variables CUL07, reflecting the cultural capital of a province in We considered the ISTAT time-point indicator for NEET 1997 and 2007; ECO97 and ECO07, describing the eco- in both 2009 and 2017. The indicator refers to the per - nomic performance of the Italian provinces in 1997 and centage of people aged 15–29 years. who are neither 2007, respectively. We collected information on four employed nor were in an education or training path, time-points (1997 and 2007 for the assessment of the cul- considering the total population in the same age range. tural/economic capital indicators; 2009 or 2017 for the As concerns cultural capital, we adopted a multidimen- outcome) since we aimed to disentangle short-run and sional perspective, taking into account different meas - medium-run (Blanchard et al. 2017) effects of economic/ ures that could be linked to the development of cognitive cultural capital on the NEET rate. and non-cognitive skills in young people (Ripamonti and Barberis 2018). For the first time-point (1997), we con -2.3 Data analysis sidered the following indicators: (i) the number of book- 2.3.1 D escriptive and spatial indicators shops (BOO97); (ii) the number of art, cultural, and free We calculated descriptive indicators (1st and 3rd quar- time associations (ASS97); (iii) the number of cinemas tiles, median, interquartile range, min and max) for the (CIN97). Measures for cultural capital in 2007 were: (i) variables under study. We used choropleth maps to attain the percentage of book sale index (BOO07); (ii) the num- a complete spatial view of the values taken by the statis- ber of art, cultural and free time associations (ASS07); tical units at a detailed geographical level. These maps (iii) the number of cinemas (CIN07). These measures were also used taking into account the Local Moran index are expressed with reference to a target population of (Moran 1948) in order to study spatial dependency and 100,000 inhabitants. Analyses were repeated (and shown local peculiarities (or cluster). The Local Moran index in the Additional file  1) inserting in the measurement belongs to a large class of statistical indicators known in model for cultural capital (iv) the average expenses pro the literature as Local Indicators of Spatial Association capite to participate in sport events in 1997 (SPO97); (LISA) (Anselin 1995) and provides estimates of spatial the sport index in 2007 (SPO07). We inserted a sport autocorrelation disaggregated to the level of the statisti- indicator in the operationalization of cultural capital, as cal units. this could represent a proxy of the possibilities offered to students, in a certain geographical area, to develop 2.3.2 Struc tural equation modeling their non-cognitive skills (Ripamonti and Barberis 2018). We calculated confirmatory Structural Equation Models Since results were very similar, herein we will present the (SEM) using Covariance Structure Analysis (Jöreskog more parsimonious model without adopting the sport 1970) through Generalized Least Squares estimation. indicator. Models were defined adopting the Linear Structural As to the economic performance, we used measures Equation Modeling (LISREL) terminology and notation. and proxies of wealth (income, added value, number of The relation between latent and manifest variables was enterprises) and of employment adopted, from the ISTAT of reflective type (Loehlin 1987); all analyses were  con - database, in the researches on the Quality of Life. In par- ducted on standardized variables. In the phase of model ticular, in 1997 the indicators were: (i) the income pro building, we took into account the values of the Akaike capite (INC97); (ii) the number of enterprises for every Information Criterion (AIC). Two types of modification 100,000 inhabitants (ENT97); (iii) the ratio between job indices have been considered: (i) Lagrange multipliers seekers and labor force, i.e., the unemployment rate, (LM, parameters having the largest LM indices would which is transformed in the researches on the Qual- most increase the model fit); (ii) Wald statistics (in order ity of life in an employment score for each province (the to eliminate the parameters that are not significant and higher the better performance) (EMP97). In 2007, we may be removed without virtually affecting the model fit). adopted the following indicators: (i) the added-value pro As to the error terms matrices, we initially constrained capite (INC07); (ii) the number of enterprises for every to zero all the extra-diagonal terms, and subsequently we 100,000 inhabitants (ENT07); (iii) the ratio between job unconstrained only those terms highlighted by LMs and seekers and labor force, as a proxy of unemployment, theoretically meaningful. We considered the following indicators of model assessment (Hu and Bentler 1999): (i) the ratio between the value of the Chi square statistic and For illustration see: https:// st. ilsol e24ore. com/ inclu des20 07/ speci ali/ quali ta- its degrees of freedom; (ii) the General Fit Index (GFI); della- vita/ scheda_ indice_ 9. shtml (only available in Italian); see also Ripamonti (iii) the Adjusted General Fit Index (AGFI); (iv) the Root and Barberis (2018). 13 Page 8 of 17 E. Ripamonti , S. Barberis Mean Square Residual (RMR); (v) the Root Mean Square NEE08) or after 5 years (2012, NEE12) from the last Error of Approximation (RMSEA). assessment of cultural and economic capital (2007). A third sensitivity analysis was performed to explore 2.3.3 Mediation analysis possible differential effects attributable to the eco - To evaluate how the effect of cultural capital and of eco - nomic capital, which contains two indicators of wealth nomic capital on NEET occurs in practice, we conducted (income/added value pro-capite and number of enter- a mediation analysis. Given the relatively low amount of prises) and one indicator of employment. The same literature on the interplay between cultural capital, eco- analyses already presented in the “Structural Equa- nomic capital, and NEET, we adopted an exploratory tion Modeling” subsection have been re-run, firstly by perspective in the mediation models. Thus, we consid - inserting in the economic capital indicator only the ered both the possibility that the economic capital could GDP/added value component, and secondly by insert- mediate a historical effect of the cultural capital, and vice ing only the employment component. versa. First, we estimated whether the economic capital could mediate the association between cultural capital and 3 Results NEET. Second, we estimated whether the cultural capital 3.1 Descriptive and spatial analysis could mediate the association between economic capi- From 2004 to 2018 the NEET rate increased in all Ital- tal and NEET. Taking economic capital in 2007 (ECO07) ian macro areas, but particularly in the Southern regions as a putative mediator, we aimed to disentangle the total and in the islands (Fig. 2). In addition, as indicated by the effect of cultural capital in 1997 (CUL97) on NEET in 2009 box plots shown in Fig. 2, in Southern regions and in the (NEE09) into a direct effect and an indirect effect that goes islands, data were much more scattered from the median through the mediation of the economic capital. This analy - value than in Northern and Central regions. sis was conducted using the product method (Baron and Choropleth maps showed an increasing trend between Kenny 1986), which is based on a decomposition of the Northern and Southern provinces in terms of the NEET total effect in a direct and indirect component, by calculat - rate (Fig.  3). As indicated by the values of the Local ing a regression model for the effect of CUL97 on NEE09 Moran index, in Southern provinces and in the two while adjusting for ECO07, and another regression model islands the levels of NEET are generally high and well assessing the effect of CUL97 on ECO07. Thus, the indi - clustered. Positive spatial autocorrelation has been found rect effect expressing the mediation component can be also in Northern-East provinces, but with associated calculated by taking the effect of CUL97 on ECO07 mul - much lower rates of NEETs than in Southern or Central tiplied by the effect of ECO07 on NEE09. We repeated the provinces. same analysis targeting cultural capital in 2007 (CUL07) as a putative mediator of the association between economic 3.2 Structural equations modeling capital in 1997 (ECO97) and NEET in 2009 (NEE09). In Fig. 4 we show the three time-points model adopted to Finally, we re-estimated both mediation models inserting assess the effect of cultural capital and economic capital NEE17 as an outcome measure. on the NEET rate. We firstly considered as an outcome measure the prevalence of NEET in 2009 (Model 1); sub- 2.3.4 Sensitivity analysis sequently we repeated the same analysis, but we inserted SEM work under the assumption of no unmeasured as outcome variable the prevalence of NEETs in 2017 confounding. To explore the possible impact of endo- (Model 2). We tested these models in all the Italian prov- geneity on our findings, we developed a delimited inces, and afterwards inserting only Northern, Central, simulation study. We inserted into the SEM previ- or Southern provinces. ously outlined (with the NEET rate in 2009 as outcome, Estimating Model 1 for the entire sample of the Ital- NEE09) a putative unmeasured confounder, obtained ian provinces, we obtained a fit value χ /df = 2.50 (see by simulating a vector of values from a Normal r.v. Table 1). mildly ( ρ = 0.30), moderately ( ρ = 0.60) or highly ( ρ The effect of the economic capital in 2007 = 0.80) correlated to both ECO07 and NEE09. We re- (ECO07) on the NEET rate in 2009 (NEE09) was estimated the models and we compared the coefficients significant considering all the Italian provinces with those obtained in the original models. A second (β =−0.81(0.12), t = −6.75, p < 0.0001) , and the Cen- sensitivity analysis was run to assess the robustness of tral provinces (β =−0.28(0.11), t = −2.54, p = 0.008) . the choice of the three time points in the SEM mod- In the sample of all the Italian provinces, we also els. In particular, we re-ran the same models already found an effect of the cultural capital in 1997 explained in the “Structural Equation Modeling” sub- (CUL97) on the economic capital in 2007 (ECO07) section, but inserting the NEET rate after 1 year (2008, (β = 0.36(0.07), t = 4.88, p < 0.0001) and of the The association of economic and cultural capital with the NEET rate: differential geographical… Page 9 of 17 13 Fig. 2 Descriptive analysis. Time series for the NEET indicator from 2004 to 2018 (first and last time point of the ISTAT database), and boxplots of the NEET rate in Northern-West, Northern-East, Central, Southern provinces, and islands in 2004 and 2018 economic capital in 1997 (ECO97) on the cultural capital but not in the Northern provinces. Again, we found in 2007 (CUL07) (β = 0.22(0.05), t = 4.18, p < 0.0001) ; a significant effect of the cultural capital in 1997 these results were replicated considering the subsamples (CUL97) on the economic capital in 2007 (ECO07) of Northern, Central, and Southern provinces. However, (β = 0.45(0.08), t = 5.49, p < 0.0001) , and of the eco- we did not obtain any significant finding as concerns the nomic capital in 1997 (ECO97) on the cultural capital in 2007 effect from cultural capital in 2007 (CUL07) to the NEET (CUL07) (β = 0.16(0.04), t = 3.49, p = 0.0005) in all the rate in 2009 (NEE09). Italian provinces; analogous patterns did emerge in the sub- Estimating Model 2 for the entire sample of the Ital- samples of Northern, Central, and Southern provinces. The ian provinces, it was attained a fit value χ /df = 1.35 relation between the cultural capital in 2007 (CUL07) and the (see Table  2). The relation from the economic capi - NEET rate in 2017 (NEE17) was never significant. Factor load - tal in 2007 (ECO07) to the NEET rate in 2017 (NEE17) ings for the measurement model are shown in Table 2. was significant in the entire sample of Italian provinces (β =−0.94(0.11), t =−8.54, p < 0.0001) , in the Central 3.3 Mediation analysis (β =−0.98(0.19), t = −5.15, p < 0.0001) and in the South- From SEM it emerged a protective effect of the eco - ern provinces (β =−0.81(0.24), t =−3.37, p = 0.0008) , nomic capital on the NEET rate. To better understand 13 Page 10 of 17 E. Ripamonti , S. Barberis Fig. 3 Spatial analysis. Distribution (above) and Local Moran index of autocorrelation (below) for the NEET rate in Italy in 2004 and 2018 how this effect occurs and the possible interplay of not significant, and for the 83% (Z = 7.70, p < 0.0001), it economic capital with cultural capital we conducted was attributable to the mediation component played by a mediation analysis using the product method. After the economic capital in 2007 (ECO07). We calculated having verified the absence of interaction between the another mediation model (having verified the same cultural capital in 1997 (CUL97) and the economic assumption of absence of interaction effects), insert - capital in 2007 (ECO07), we inserted the variable eco- ing the cultural capital in 2007 (CUL07) as a putative nomic capital in 2007 (ECO07) as a putative mediator mediator of the effect between the economic capital of the effect between cultural capital in 1997 (CUL97) in 1997 (ECO97) and the NEET rate in 2009 (NEE09) and the NEET rate in 2009 (NEE09) (CUL97 – > ECO07 (ECO97 – > CUL07 – > NEE09). Results pointed to 24% – > NEE09). The direct effect from the cultural capital (Z = 3.17, p = 0.001) of the effect due to the mediation in 1997 (CUL97) to the NEET rate in 2009 (NEE09) was component of the cultural capital in 2007 (CUL07), and the direct effect from the economic capital in 1997 (ECO97) to the NEET rate in 2009 (NEE09) was also 3 significant ( β =−0.36(0.06), Z =−5.52, p < 0.0001 ). Creating the quartiles of the CUL97 and ECO07 scores and inserting them as covariates in a multiple regression model with NEE09 as outcome measure. We repeated the same calculations inserting the NEET The association of economic and cultural capital with the NEET rate: differential geographical… Page 11 of 17 13 Fig. 4 Illustration of the three-points SEM (a similar model has also been estimated substituting NEE09, indicator for NEET in 2009, with NEE17, indicator for NEET in 2017) effect from the economic capital in 1997 (ECO97) to Table 1 Fit index for SEM considering all the Italian provinces (IT), and, separately, Northern (N), Central (C) and Southern (S) the NEET rate in 2017 (NEE17) was also significant provinces ( β =−0.41(0.07), Z =−5.91, p < 0.0001 ). To sum up, 2 cultural capital seems to play a weak (and statistically Model GFI AGFI RMR RMSEA χ /df non-significant) role on the NEET rate, and such rela - Model 1, IT 2.50 0.83 0.65 0.18 0.12 tion seems strongly mediated by the economic capital. Model 1, N 1.33 0.47 0.66 0.08 0.09 By contrast, in the medium term the economic capital Model 1, C 1.09 0.76 0.52 0.42 0.05 would play a consistent effect on the NEET rate, and such Model 1, S 1.24 0.73 0.44 0.22 0.08 effect seems partly mediated by the cultural capital. Model 2, IT 1.35 0.48 0.66 0.11 0.09 Model 2, N 0.96 0.47 0.64 0.22 0.01 3.4 Sensitivity analysis Model 2, C 3.28 0.38 0.32 1.15 0.26 We conducted a first sensitivity analysis, as described Model 2, S 2.07 0.75 0.50 0.08 0.18 in the Methods section, to assess the possible impact GFI: Global Fit Index; AGFI: Adjusted Global Fit Index; RMR: Root Mean Square of endogeneity on our models. In this regard we simu- Residual: RMSEA: Root Mean Square Error of Approximation lated (from Normal random variables), the presence of an unmeasured confounder in the SEM including all the Italian provinces. Three scenarios have been rate in 2017 (NEE17) as an outcome variable, and we evaluated, inserting a mild, moderate, or strong con- found that the economic capital in 2007 (ECO07) pos- founder, respectively. Results (see Table  3) indicate sibly mediated almost the 100% (Z = 7.32, p < 0.0001) of that both the relations from the economic capital in the effect of the cultural capital in 1997 (CUL97), while 2007 to the NEET rate in 2009 (ECO07 – > NEE09) and the direct effect of the cultural capital in 1997 (CUL97) from the economic capital in 2007 to the NEET rate on the NEET rate in 2017 (NEE17) was not significant. in 2017 (ECO07 – > NEE17) are robust with respect to The variable cultural capital in 2007 (CUL07) medi - the presence of a mild or of a moderate unmeasured ated about the 16% (Z = 2.42, p = 0.01) of the effect of confounder, but the statistical significance may not the economic capital in 1997 (ECO97), and the direct be confirmed in case of a strong confounder. While 13 Page 12 of 17 E. Ripamonti , S. Barberis Table 2 Factor loadings for the measurement model in all the Italian provinces. We report the estimate (SE) CUL97 ECO97 BOO97 0.79 (0.05)* ASS97 0.68 (0.07)* CIN97 0.95 (0.04)* INC97 1.16 (0.06)* EMP97 0.36 (0.11)* ENT97 0.99 (0.05)* CUL07 ECO07 BOO07 1.05 (0.22)* ASS07 0.95 (0.20)* CIN07 0.77 (0.18)* INC07 0.96 (0.01)* EMP07 0.91 (0.02)* ENT07 0.92 (0.02)* * Indicates a significant p-value as well as the relation from the economic capital in Table 3 Sensitivity analysis, examining the robustness of the 2007 to the NEET rate in 2012 (ECO07 – > NEE12) relations ECO07– > NEE09 and ECO07– > NEE17, when inserting (β =−1.14(0.13), t =−8.49, p < 0.0001). a mild, moderate or strong unmeasured confounder (UC) in the A third sensitivity analysis was run including in the model operationalization of the economic capital only the indicators of wealth (GDP/added value), without the β(SE) t p-value employment index. While the result was still in the ECO07– > NEE09 expected direction, neither the relation from the eco- Original − 0.81(0.12) − 6.75 < 0.0001 nomic capital in 2007 to the NEET rate in 2009 (ECO07 With mild UC − 0.89(0.16) − 5.45 < 0.0001 – > NEE09) (β =−0.35(0.87), t = −0.41, p = 0.68) With moderate UC − 0.97(0.22) − 4.40 < 0.0001 nor the relation from the economic capital in 2007 With strong UC − 0.00009(0.00007) − 1.33 0.18 to the NEET rate in 2017 (ECO07 – > NEE17) ECO07– > NEE17 (β =−0.40(0.42), t =−0.96, p = 0.33) proved sta- Original − 0.94(0.11) − 8.54 < 0.0001 tistically significant. A similar finding emerged With mild UC − 0.96(0.14) − 6.53 < 0.0001 when inserting only the indicator of the employ- With moderate UC − 1.07(0.23) − 4.50 < 0.0001 ment in the general population without the indica- With strong UC − 0.00002(0.0007) − 0.09 0.92 tors of wealth; the relationship was negative but not significant, neither in the short run (from the eco - nomic capital in 2007 to the NEET rate in 2009, ECO07 – > NEE09: β =−0.32(0.27), t =−1.16, p = 0.24 ) these results are worth reporting, the presence of a nor in the medium run (from the economic capital strong unmeasured confounder, i.e., a variable related in 2007 to the NEET rate in 2017, ECO07 – > NEE17: to both the economic capital in 2007 (ECO07) and the β =−0.01(0.53), t =−0.02, p = 0.98 ). Together, these NEET rate in 2009/2017 NEE09/NEE17 (with ρ ≥ 0.80 ) results indicate the importance of considering in the should be justified theoretically and proven empirically. measurement model describing the economic capital In a second sensitivity analysis we re-estimated the both the indicators of wealth and of employment in the SEM model for all the Italian provinces, inserting as general population. outcome variable the NEET rate in 2008 (NEE08) or the NEET rate in 2012 (NEE12). We obtained very similar results to those already presented in the “Struc-4 Discussion tural equations modeling” subsection. In particular, In contemporary European societies the new generations the relation from the economic capital in 2007 to the experience an unexpected condition of decline of their NEET rate in 2008 (ECO07 – > NEE08) was still sig- status and economic possibilities as compared with the nificant (β =−0.97(0.06), t = −15.14, p < 0.0001) previous generation. One of the phenomena testifying The association of economic and cultural capital with the NEET rate: differential geographical… Page 13 of 17 13 this dependence position is represented by NEETs, who of attained level of education, becoming NEET may indi- are a very heterogeneous group of teenagers and young cate a virtually stable (at least in the short run) vulner- people with marked and persistent difficulties in the tran - ability condition more deeply rooted than that implied sition from school to the labor market. For an improved by dropping out of high school. It should also be added organization and implementation of policies contrasting that in the present study and in Ripamonti and Barb- the NEET phenomenon it is important a deep under- eris (2018), following the definitions provided by Pub - standing of the determinants of this outcome, including lic Authorities and Statistical Institutes, two different the macro level antecedents. In this paper, we analyzed at age cohorts were considered (15–24 for school dropout, a detailed geographical level the relation among cultural including both early school leavers and non-completers capital, economic capital, and the NEET rate. The analy - of high school; 15–29 for NEET), which could also ses have been conducted in Italy, which is one of the EU explain part of the heterogeneity in the results. countries with the highest levels of NEETs, and also pre- An alternative possible explanation to the absence of sents with some structural weaknesses in its vocational direct effect of cultural capital on the NEET rate may rely system (Ballarino 2015), e.g., lack of investment on the on the definition of NEET provided by the ISTAT and dual apprenticeship system, which is a protective factor by other national statistical agencies, i.e., the percentage against NEET (Eurofound 2012). of people aged 15–29 (or 15–34) that are neither on a Results of the SEMs presented herein point to a protec- formative track nor employed. This definition potentially tive effect of economic capital on the NEET rate in the includes both unemployed young people who are non- short run (2  years), considering all the Italian provinces studying and are actively searching a job (as in the defi - and the Central provinces. The same protective effect nition of unemployment rate) and young people who are was found in the medium run (10  years) considering all not studying and are also out of the labor market (inac- the Italian provinces, the Central and the Southern prov- tive non-students). We may hypothesize that cultural inces. In addition, the economic capital strongly mediates capital can affect NEETs capacity to actively search for the effect of the cultural capital, which, as a direct effect, a job. Indeed, these young people could be motivated to is not significant. The cultural capital, by itself, does not find a job or a formative activity by experiencing an ani - play a direct protective role on the NEET rate, but may mate cultural environment. mediate the effect of the economic capital. Our results The mediation analysis also showed that, while there are in line with the hypothesis that the economic capital, does not seem to be a consistent direct protective effect at a macro level, affects the educational and labor market of cultural capital on the NEET rate, such relation is outcomes (Kelly and McGuinness 2015). In addition, as mediated by the economic capital. Thus, a province shown in the sensitivity analysis, both components of the with high levels of cultural capital would longitudinally economic capital considered in our analyses, i.e., wealth increase the likelihood to ameliorate its economic capital, and unemployment, are associated with the NEET rate. and this would reflect in a better outcome in terms of the u Th s, data  presented herein clearly point to  an increased NEET rate, both in the short and in the medium run. NEET rate in territories characterized by scarce economic Relevant geographical differences emerged in our performance. Our findings are in line with the previous analyses are also to be highlighted. Considering the literature, which highlights a correlation of the NEET rate subsample of Northern provinces, contrary to our pre- with the general unemployment rate and with the GDP diction, we did not identify any protective effect of the level (Eurofound 2012). This paper adds to previous stud - economic or cultural capital, neither in the short run ies a clear timing of the effects, as well as an analysis of nor in the medium run. High levels of both economic the role of economic capital (where both the components and cultural capital characterize these provinces. Thus, of wealth and general unemployment rate have to be kept a possible explanation of these negative results may into account) at a detailed geographical level. be in terms of a ceiling effect, i.e., an excellent perfor - It was a hypothesis of this article that of a putative mance with very low variation in a prediction variable, protective effect of cultural capital on NEET, following which may lead to hamper the possibility of captur- a similar finding already described for high school drop - ing a putative protective effect in the regression mod - out (Ripamonti and Barberis 2018). Differently from such els. It is also worth observing that  the Local Moran assumption, our findings did not indicate a direct protec - index indicates the presence of a certain heterogeneity, tive effect of cultural capital on the NEET rate. The dis - despite low values in magnitude, of the NEET indicator crepancy of results emerged herein with those reported in Northern-East provinces, but not in the Northern- in Ripamonti and Barberis (2018) could be explained in West provinces. terms of the different outcome considered in the two Another form of capital that could be linked to the studies. While non-completion of high school is a proxy NEET rate is given by social capital, which, following the 13 Page 14 of 17 E. Ripamonti , S. Barberis sociological tradition, could be operationalized in terms of young people with very different backgrounds and of connections, social networks, trust (Coleman 1988). developmental histories. Hence it may become diffi - While it would be worth investigating social capital as cult to program proper and individualized policies to a putative protective factor for NEET, it is also clearly deal with this phenomenon. The other side of the coin differentiated from the construct of cultural capital, as is that, thanks to the uncertainty degree underpinning originally underlined by Bourdieu (1994). Thus, introduc - the NEET definition, the NEET rate may allow to cap - ing social capital in this analysis would raise a quite dif- ture, at least at an aggregate level of analysis, particu- ferent research question, which we leave open for future larly vulnerable young people without a job but also research. Social capital could also help to better under- without the possibility of developing their human capi- stand the NEET phenomenon in the Northern provinces, tal in proper formative tracks. This frail segment of the where no significant effect of cultural or economic capital youth population would not be captured by the stand- did emerge. ard unemployment rates (Rosina 2015). In terms of timing of the effects, in this article we basi - Even though our analysis presents some limita- cally adopted an econometric viewpoint. In the eco- tions, we assume that understanding the role played nomic theory (Blanchard et  al. 2017) short-term effects by high-level variables may drive and provide guidance are those described in one or few years, while medium- on future research at a micro-level of analysis. At this term effects generally imply a timing of about a decade. stage, macro–micro link studies in all areas of research Both cultural and economic capital have been measured related to transition to adulthood, including becoming before the great recession of 2008. While it is interesting NEET, are still scarce (Buchmann and Kriesi 2011). A to observe that economic capital plays a protective effect second limitation is that we restricted our analyses to on NEET on both the short run and the medium run (but the assessment of the economic condition before the no effect has been described for cultural capital), results economic crisis of 2008, which relevantly weakened the should be carefully interpreted. Indeed, our analysis has economy of Southern European countries. Young peo- only 4 time points. We did not conduct a time-lagged ple and the youth labor market were disproportionately analysis with multiple time points, neither we considered affected by the consequences of the crisis (Bell and change scores of the NEET rate. These possibilities are Blanchflower 2011), as recently documented in terms open for future investigation using a more comprehen- of youth unemployment and employment trajectories sive data source as well as other longitudinal methods for in Spain (Verd et al. 2019). An evaluation of the effects data analysis, such as econometric panels. It is important of the great recession (2008 and the double-dip, 2012) to remark that in Southern provinces the protective effect in terms of the NEET rate, in relation with the eco- of the economic capital on the NEET rate was obtained nomic and cultural capital, could be a specific issue for only in the medium run scenario (i.e., after 10 years), but a future investigation. not in the short run scenario (i.e., after 2  years). These In conclusion, we found that the economic capital provinces are characterized by low levels of economic (considered in both dimensions of wealth and employ- performance and by marked spatial heterogeneity in the ment), independently of cultural capital and measured economic performance (Ripamonti and Barberis 2018), before the economic crisis of 2008, may protect young which, together, could imply that the beneficial effect of people from becoming NEET. Peculiar geographical a slow economic development on the young generation and temporal patterns did emerge, with the effect of the may be detectable only after a decade or longer. economic capital being particularly relevant in Italian A first limitation of this study is that of having only Central provinces, and in the Southern provinces only investigated the potential protective factors on the in the medium run scenario. Findings reported herein NEET rate at a macro-variable level, without studying indicate relationships among variables at a macro level, the  effect of the macro level on the micro  level, in dif - and should be complemented by future research at an ferent  cultural contexts (Rogoff 2003). In Italy, as well individual level. Our final message to policy makers is as in other EU countries, large administrative databases that investment in economic development, especially in on phenomena like NEET, at individual level, are still economic depressed areas like Southern Italy, may have under construction, and are not currently available on a beneficial effect on the NEET rate in the short and in a large scale. This problem also hampers the possibil - the medium run. The role of the economic capital may ity to properly address the heterogeneity issue in the be partly mediated by the cultural capital, which, how- NEET population. Heterogeneity represents one of the ever, does not seem to play an independent effect on main problems of using the NEET category (Furlong the NEET rate. Investment on culture and education 2006; Yates and Payne 2006) since it probably reflects cannot be isolated from investment on economic devel- the presence, under the same umbrella term (“NEET”), opment, and a multifactorial phenomenon like NEET The association of economic and cultural capital with the NEET rate: differential geographical… Page 15 of 17 13 European Perspective: A Comparative Analysis, pp. 181–208. Policy demands complex, differentiated, and multi-compo - Press, Bristol (2015) nent policies. Barbieri, P., Scherer, S.: Labour market flexibilization and its consequences in Italy. Eur. Sociol. Rev. 25, 677–692 (2009) Barham, C., Walling, A., Clancy, G., Hicks, S., Conn, S.: Young people and the Supplementary Information labour market. Econ. Labour Mark. Rev. 3, 17–29 (2009) The online version contains supplementary material available at https:// doi. 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Tramonte, L., Willms, J.D.: Cultural capital and its effects on education out - comes. Econ. Educ. Rev. 29, 200–213 (2010) Vancea, M., Utzet, M.: School-to-work transition: The case of Spanish NEETs. J. Youth Stud. 21, 869–887 (2018) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal for Labour Market Research Springer Journals

The association of economic and cultural capital with the NEET rate: differential geographical and temporal patterns

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Abstract

Using data from 103 Italian provinces, we investigated the relationship between local/regional development, and NEET. We constructed an indicator of cultural capital and another of economic capital and we studied their relation with the NEET rate. Covariance Structure Analysis with Generalized Least Squares estimation was employed, consider- ing a three time-points retrospective model. Results indicate a consistent protective effect of the economic capital on the NEET rate, both in the short run (2 years) and in the medium run (10 years). However, this effect has been obtained in the Central provinces (at 2 and 10 years) and Southern provinces (at 10 years), but not in the North- ern provinces. A mediation analysis indicated that, historically, the cultural capital may partly mediate the effect of the economic capital. We did not detect a significant direct effect of the cultural capital on the NEET rate, which is strongly mediated by the action of the economic capital. Together, these results denote that the economic capital is a strong predictor of NEET, but not in very competitive economic areas. Keywords: Cultural capital, Economic capital, NEET, School dropout, Southern European welfare 1 Introduction we will investigate these issues using national retrospec- The individual trajectories of adolescent development, tive data. including educational attainment and participation in Contemporary European societies are, in general, char- the labor market, should be studied in conjunction with acterized by advanced and knowledge-based economies, the role of macro-level determinants, which may play a as well as by strong welfare systems and social services. top-down effect on teenagers’ behavior and interact with However, there is also high heterogeneity across and micro-level variables. This paper specifically investigates within countries (Mayer 2004), which makes important the role of economic and cultural capital on young peo- the study of macro-level variables for a deep understand- ple who are neither in employment nor in education or ing of social change and of youth transition to adulthood training (NEET)s. While being NEET reflects a multifac - (Buchmann and Kriesi 2011). It is particularly worth plac- torial phenomenon, whose main determinants have been ing the study of NEET in this high-level framework, since partially highlighted, the literature has paid less attention this may provide policy makers with a comprehensive to the role of the economic capital and of the cultural view on the risk factors involved in this phenomenon. wherewithal offered by a geographical area, as originally Indeed, governmental and international agencies, in par- operationalized by Di Maggio and Mohr (1985). Herein ticular the EU and its institutions, have long targeted this group of young people for intervention and monitoring. Such interest reflects the general objectives of the Lisbon strategy, ratified in 2000 by all Member States. However, *Correspondence: enrico.ripamonti@unimib.it Milan Center for Neuroscience, University of Milan-Bicocca, Piazza on current state of research, there is large heterogeneity dell’Ateneo Nuovo 1, 20126 Milan, Italy Full list of author information is available at the end of the article © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. 13 Page 2 of 17 E. Ripamonti , S. Barberis NEET rate Italy Europe (27) Spain France Germany 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Fig. 1 Time series indicators of the NEET rate in the 27 EU countries, and, nationally, in France, Italy, Germany, and Spain in methods and models followed in such interventions, #U u% = ∗ 100 without a clear and long-term strategy. #L To be included in the definition of #U a person must 1.1 NEE Ts in contemporary European societies not have a job, but, at the same time should be actively 1.1.1 Definition of NEET searching for a job (otherwise he/she would be classified The concept of NEET refers to young people who, since as out of L). While simple in principle, there is debate are not working and, at the same time, are not enrolled in the literature on the measurement of the labor force in school or other formative activities, are not accumu- (Battistin et  al. 2007) and of the unemployment rate lating human capital (Eurofound 2012). Thus, while cor - (Jones and Riddell 1999). The NEET rate has a slightly related to the construct of school dropout (Ripamonti more complicated definition. According to international 2018), NEETs reflect a more radical and extended form institutions (e.g., the International Labor Organization of vulnerability and social exclusion. The acronym NEET or Eurostat), the NEET rate (n%) can be defined as the was firstly used in the United Kingdom in the 1980s, but percentage of the population of a given age, group or sex became popular worldwide starting from 2010, when the who is not employed and not involved in further educa- European Union (EU) adopted the NEET rate as an offi - tion or training (Elder 2015): cial indicator to assess the youth conditions across EU countries. In Fig. 1 we show the time series of the NEET (#Y − (#YE + #YT)) n% = ∗ 100 indicator for the 27 EU countries, and, specifically, for #Y Italy, Spain, France, and Germany. Further graphs and where #Y indicates the number of youths, #YE the num- illustrations are presented in Additional file 1. ber of youths in employment, #YT the number of youths not in employment, but who are in education or train- 1.1.2 The youth unemployment rate and the NEET rate ing. It is worth placing the discussion on NEET and The youth unemployment rate (u % ) can be defined (e.g., unemployed youth in the larger framework of the theory in the Labor Force Survey) as the ratio between the num- of human capital (Becker 1962). Educational achieve- ber of unemployed young people (#U e.g., in the age ment is indeed a proxy of human capital, which affects range 15–24) and the total number of people in the same age range that make up the labor force ( # L = #U + #E, where E indicates the employed), namely (Blanchard At the numerator, where subtracting from #Y, young people that are both in et al. 2017): employment and in education or training simultaneously should not be dou- ble counted. 5101520253035 The association of economic and cultural capital with the NEET rate: differential geographical… Page 3 of 17 13 the economic capital and the economic development 1.1.4 Individu al factors related to NEET (Barro 1991). In the 2000s the economic theory under- NEETs may reflect the impossibility for young people lined the importance of non-cognitive skills (e.g., motiva- to attain the requirements of normative adult models. tion, leadership, initiative, goal-oriented attitude) in the In this regard, there are gender specificities as well as development of human capital (Heckman and Rubinstein personal characteristics to be kept into account. Young 2001). To increasing levels of human capital correspond girls show a more rapid transition to adulthood than increased salaries, and the differential in real wages young men (Malmberg and Trempała 1997). In addi- between skilled and unskilled workers, at least in the tion, while for young men the consequences of becom- US, has enlarged from 1970 to 2005 (Autor et  al. 2008). ing NEET may be mainly related to difficulties in the In addition, a past history of absence of high educational labor market, young women would also experience level and unemployment may also protect teenagers with negative psychological outcomes (Bynner and Parsons respect to the probability of future unemployment and 2002). Education is a second relevant factor associated transition through the NEET status (Narendranathan with NEET. Using data from the British Cohort Study, and Elias 1993). Young people with low levels of educa- it was  found that low instruction levels are likely to be tion have relevant difficulties to entry in the labor market associated with the NEET rate (Bynner and Parsons (Martin 2009). In Southern Europe, young people of all 2002). In the same cohort of young people it was shown educational levels may experience difficulties in finding a how uncertain occupational aspirations would be job and career instability (Brzinsky-Fay 2007). related to NEET (Yates et al. 2011). Health and mental health conditions may also be associated with the NEET status. For instance, actively searching for a job could be hampered by chronic dis- 1.1.3 NEET: A blurred concept orders such as suffering from chronic stress and fatigue In general, NEETs constitute a very heterogeneous (Lim et  al. 2016). In terms of mental health, long-term group of individuals, who, however, share an increased unemployment and loss of interest may lead NEETs to risk of social and labor market exclusion. The very con - a perception of generalized reduced self-efficacy, which cept of NEET has long been criticized, since it would implies resignation and inactivity (Jerusalem and Mit- denote a too general as well as fragmented category, not tag 1995). At the same time NEETs may experience adequate to represent the problems of young people in adverse psychological outcomes, like decreasing of transition to adulthood (Furlong 2006). Heterogene- self-estimate or self-efficacy (Heckhausen 2006), and ity refers to the fact that this category could virtually the very impossibility of actively choosing a different include, at the same time, young people who are not direction in life. If prolonged, the NEET state could employed and not at school but are proactively search- also determine in the young generations a condition of ing for an occupation, as well as people virtually stable protracted inertia and social disengagement (Maguire in their status, without putting in action proper efforts 2015). to ameliorate their condition. In the former group there Many psychological factors have to be discussed in are NEETs looking for their first job (having completed relation to NEET. First of all, motivation (Dietrich and or not the school with a certificate), and long-term Salmela-Aro 2013), which is a key factor to favor the unemployed young people. In the latter group there transition from school to work (Symonds et  al. 2019). are those who, as being long-term unemployed people, Motivation is strictly related to young people’s educa- have been discouraged to search for an occupation, as tional aspirations (Hegna 2014), future expectations well as young people who are temporarily in the NEET (Iovu et  al. 2018), and investing in active efforts in goal condition (e.g., to take care of children or parents). pursuit (Lechner et al. 2016), which are important deter- While, in general, the label “NEET” may capture young minant of educational choices and outcomes. The moti - people at risk of marginalization in contemporary soci- vational factor is a determinant of job search intensity, eties, there does not exist a shared operational defini - which is a very important variable in terms of the possi- tion underpinning this concept. In fact, scholars have bility of changing the NEET status (Vanoverberghe et al. defined the NEET phenomenon in very different ways 2008). and with reference to young people of different ages Motivation is a primary psychological dimension but (Yates and Payne 2006). If we consider NEETs as young should be studied in conjunction with other components people aged 15–29, such definition would cover three that, if activated, may protect the individual from becom- quite different developmental phases, namely late ado - ing NEET. In this regard, three important factors docu- lescence (15–17), emerging adulthood (18–24), early mented in the literature are given by goal attainability, adulthood (25–29) (Arnett 2006). i.e., the ability of self-monitoring one own’s objectives 13 Page 4 of 17 E. Ripamonti , S. Barberis (Nurmi et  al. 2002), the capacity of attributing priorities does not coincide with dropping out from high school, (Brannen and Nilsen 2002), and intrapersonal agency non-completion of school and entering the labor mar- (Graaf and Zenderen 2013). ket without qualifications is a strong determinant of Two classical concepts of general psychology, which transitioning through the NEET condition, especially have to be considered in connection to NEET and youth for women (Salvà-Mut et al. 2016). Basic school achieve- unemployment are coping styles and the locus of control. ments, in terms of literacy and numeracy skills, are a con- The coping style and the ability to cope with stress are a sistent protective factor with respect to the possibility protective factor in terms of completing education and of becoming NEET (Barth et  al. 2019; Kelly et  al. 2012). starting a job (Ngai et al. 2014). The internal locus of con - School is not only a matter of contents or competence, trol is the capacity of the individual to attribute internally but should actively help teenagers in finding their voca - the effect of behavior/conduct, which may play a role in tional specificity, which is an important factor in terms of relation to NEET and other developmental tasks of ado- job placement (Vogtenhuber 2014). lescence and of the emerging adulthood (Sharon 2016). There is a large amount of studies documenting the Career preparation, a factor related to the locus of con- important role of internships, extra-curricular activi- trol, predicts adolescents’ satisfaction and career success ties, investment on soft skills, and experiences like the (Hirschi 2010). However, having an internal locus of con- “gap year” in helping teenagers in the phase of transition trol seems a not sufficient condition for protecting young from school to work (Aguilar et  al. 2018; Sortheix et  al. people against becoming NEET for those living in dis- 2013; Stehlik 2010; Vanoverberghe et al. 2008). The litera - advantaged socio-economic conditions (Ng-Knight and ture has underlined the importance of the psychological Schoon 2017; Vancea and Utzet 2018). dimension of these paths, which should be perceived by the individual as an opportunity to ameliorate his/her 1.1.5 Familial and peer‑group related factors own outcome in the labor market (Taylor et  al. 2015). At a micro level, parental educational level as well as Important macro-level variables should be kept into parents’ support may have a protective effect on the risk account, since, at least in the EU countries, there is a cer- of becoming NEET, for both male and female teenag- tain variation in the real possibilities for young people to ers (Alfieri et al. 2015). NEETs are likely to live in a fam - invest in apprenticeships and internships (Lehmann et al. ily with one parent, and where parents are not working 2015). (Barham et al. 2009). The literature has shown how being A possible solution to contrast the NEET phenomenon NEET is associated with presence of poor or inadequate is given by starting a self-employed activity. While, as familial models and backgrounds (Robson and Team documented in a large study involving 11 EU countries, 2008), or to intergenerational influences (Bynner and this may protect young people from social exclusion Parsons 2002). At a macro level, being NEET is more fre- and unemployment (Dvoulety et  al. 2018), it could be quent in Southern than in Northern European countries, not achievable or realistic for the most frail and inactive with the former being characterized by a familialistic pro- segment of NEETs. In fact, given the personal and psy- tective welfare (Esping-Andersen 1990). As concerns the chological vulnerability of NEETs, it may be not easy for role of the group of peers, it is certainly a fundamental them, even with the help of formative programs or men- component of socialization in adolescent development, tors, to develop a specific business idea (Nabi et al. 2015). whose effect can go beyond familial factor (Harris 1995). There is also recent literature linking the role of the group 1.1.7 Contextual factors of peers with high school dropout (Ripamonti 2018). The level of poverty measured at community level has The role of the peer group and a constellation of nega - been proposed as a key variable to understand the mech- tive behaviors, like crime and violence, has been recently anism of social exclusion, indirectly favoring outcomes highlighted in Canadian NEETs (Henderson et al. 2017), like becoming NEET or school dropout (Harding 2003). while in Europe this specific issue, to our knowledge, has However, while associated with low socio-economic sta- been less studied. tus, the NEET condition is not exclusive of young people living in poverty or homeless (Thompson 2011). Indeed, 1.1.6 Organizational and work‑related factors being NEET may not be per se a matter of economic dis- There are some factors associated  with the NEET status advantage, but a signal of a developmental difficulty of that are related to the organizational and work environ- these teenagers in terms of adjusting their life trajectory ment. As to the school environment, recent research in the direction of adulthood (Chen 2011). A role of the from Nordic countries indicates that the excess risk for geographical context (living in rural and provincial ter- NEET can be attributed to teenagers’ poor performance ritories vs. cities and metropolises) has also been sug- at school (Berlin et  al. 2020). While becoming NEET gested, at least in terms of school completion (Swanson The association of economic and cultural capital with the NEET rate: differential geographical… Page 5 of 17 13 2004). Becoming NEET could be a consequence of the investigation) with scarce development of innovative increasing complexity of the EU labor market system policies connecting formative tracks with the possibility (Raffo and Reeves 2000). The presence and prevalence of finding a job, which may have reflected in high unem - of NEETs in the EU may also be linked to the special ployment rates in  the young generations (Breen 2005). needs of the local economy (e.g., request of low-skilled, Three labor market reforms (Treu in 1997; Biagi in 2003; low-paid workers) (Simmons 2008). At a local level, in an Poletti in 2014) have been approved in order to liberal- analysis conducted in the Austrian federal states, Bacher ize temporary jobs and to encourage companies hiring et  al. reported that expenditures for active labor market new employees. However, the side effect of these Jobs policy and other contextual factors can explain the geo- Acts is that the labor market has been made precarious, graphical difference in the NEETing rate (Bacher et  al. especially for young people (Barbieri and Scherer 2009). 2017). As a consequence, enterprises have been discouraged from investing in permanent training and specialization 1.1.8 Is NEET a choice? (Blanchard et  al. 2017). This may have led to the high Rarely, and for a very low percentage of the young popu- NEET rate that has been described in Italy in the last lation, becoming NEET has been described as a choice, 10–15 years. on a temporary or voluntary basis. These conditions include, for instance, the situation of temporary NEET 1.3 Cultural capital and education in which are teenage parents taking care of their children The dynamics underpinning a complex phenomenon like (Contini et  al. 2019), which should not be automatically NEET, reflecting scarce accumulation of human capi - deemed as negative (Simmons and Thompson 2011). tal, should be investigated also keeping into account the Hence, not all NEETs would be at the same risk of social putative role of macro-level variables, such as the eco- exclusion (Yates and Payne 2006). We remark that volun- nomic capital, the social capital, and the cultural capital, tary NEETs are counted in the official definition of NEET as well as their interaction with the micro level (Billari and contribute to the uncertainty and heterogeneity of 2004). To provide an example, not being employed or in the description of this phenomenon. a formative track could also be related to high-level vari- ables like living in familialistic cultures typical of South- 1.2 C ountry setting: Italy ern Europe, which in general provide strong support and In Italy the rate of NEETs, considering the age range protection to teenagers when they are not participating 15–29 years, was at 23.4% in 2018, with huge regional in the labor market (Kalmijn and Saraceno 2008). differences (ISTAT 2019): 15.6% in Northern provinces, Following the Weberian tradition, individuals do not 19.6% in Central provinces, and 33.8% in Southern prov- only belong to a certain social class (mainly reflecting inces (see the Additional file  1). It is worth putting the their position in the labor market), but also have a cer- investigation of the effect of economic/cultural capital tain status in the society, which reflects participation on NEET in the Italian context, which is characterized to a collectivity and is not just a constrained function by relevant geographical differences across the coun - of social class. In this context, the construct of cultural try in terms of both economic performance and welfare capital (Bourdieu 1986, 1984, 1970) refers to intellectual state. While the ISTAT has long highlighted the different and educational factors that could foster social mobil- NEET rate between Northern and Southern provinces, ity, beyond mere financial security or economic assets there is not extensive literature addressing the possible (economic capital), and beyond relation, group member- determinants of this gap, which is generally and primarily ship, support (social capital). In this paper we adopt the attributed to the territorial differences in the economic construct of cultural capital on a larger scale than that performance. In addition, Italian provinces have differ - originally proposed by Bourdieu, i.e., we measure the cul- ent history, cultural practices, and civic traditions (Put- tural capital developed in a certain geographical region nam et  al. 1994). Italy, like France and other Southern at an aggregated level (DiMaggio 1982). Indeed cultural European countries (Ferrera 1996), is characterized by capital can be conceived at a macro-system level (Ford a strong welfare system provided by the State. However, and Lerner 1992), in terms of the possibility offered to with the regionalization process following the 2001 Con- the population to participate and being involved in the stitutional reform, a rather marked variability in welfare society and in cultural activities (DiMaggio and Mohr regimes across Italian regions did emerge, especially as 1985). Bourdieu primarily described cultural capital at concerns the organization of vocational training. an individual or familiar level, as a factor contributing Italy is also a country with a highly regulated labor to the social reproduction at a macro-level, in terms, for market and, at least until 1997 (the first time-point instance, of intraclass difference; this has been opera - for the assessment of economic capital in the present tionalized also in the recent literature on educational 13 Page 6 of 17 E. Ripamonti , S. Barberis outcomes (Tramonte and Willms 2010). There is justifica - or Spain) than Germany or Nordic countries. Moreover, tion in the sociological literature to embrace a larger view in Southern European countries, like Italy, there is an of cultural capital from a multilevel perspective (Reay inter-regional gradient with Northern regions outper- 2004). This line of thinking can be attributed to Bourdieu forming Southern regions in terms of both the economic himself (Brubaker 1985), who differentiated between performance and the NEET rate (ISTAT 2019). While the embodied, objectified, and institutionalized cultural capi - association between the economic capital and the NEET tal (Bourdieu 1984), and to the sociologist Paul DiMag- rate has been reported at a descriptive level, the struc- gio, who clearly distinguished between cultural capital at tural mechanisms underlying these phenomena are far an individual level, and cultural capital at a macro level, in from being clarified. terms, for instance, of cultural goods produced by a soci- ety (DiMaggio 1991). Other authors have already adopted 1.5 Hypotheses the construct of cultural capital at an aggregate level and This paper aims to study putative protective factors on from a systemic perspective, for instance in the ecologi- the NEET rate through a large-scale and place-based cal literature (Berkes and Folke 1994), or in the economic approach, analyzing the role of macro level variables. We literature in terms of cultural assets (Throsby 1999). In pointed to clarify, at a detailed geographical level, the order to put cultural capital in the context of the pre- impact of both economic and cultural capital on becom- sent investigation, it is worth remarking that it has been ing NEET. A diachronic perspective  was employed, shown how, in Italy, this would be very heterogeneous assessing cultural capital, economic capital and the NEET across provinces (Ripamonti and Barberis 2018). Central rate at three different time points. First, we hypothesized provinces would attain the highest levels of cultural capi- that to high levels of cultural capital in a certain geo- tal, followed by Northern and Southern provinces. graphical area may correspond valuable cultural oppor- tunities offered to teenagers, and this might promote the 1.4 E conomic capital and education development of their cognitive and non-cognitive skills The economic capital, at different levels of aggregation, is (Heckman and Rubinstein 2001), thus protecting them an important predictor of educational attainment. Classi- from becoming NEETs. This prediction also follows from cal studies of developmental psychology and economics Ripamonti and Barberis (2018), who reported a protec- of education have documented that, in children, poverty tive effect of cultural capital on high school dropout, but and family income are associated with cognitive develop- with relevant differences across Italian provinces. Sec - ment and behavioral patterns (Duncan et  al. 1994). The ond, we assumed that living in areas characterized by human capital (Becker 1962) of parents, which is a proxy strong economic performance could have a protective of the economic opportunities for the family members, effect on the NEET rate, and we aim to clarify whether has been described as a protective factor for pupils in such putative effect is of direct type or may be mediated terms of school achievement and better social outcomes by cultural capital. Third, we aimed to investigate possi - (Brooks-Gunn et  al. 2006; Janosz et  al. 1997). Quality of ble mediation effects of cultural/economic capital on the home and of day care environments, which are strongly NEET phenomenon. correlated to the economic capital at an aggregate level, have also been described to be associated with cognitive 2 Methods abilities and language development (Broberg et  al. 1997; 2.1 Databases Burchinal et  al. 1996). Together, these findings highlight Data on the NEET rate (at aggregated level) from 103 the importance of assessing an adverse outcome such as Italian provinces were obtained from the database of the becoming NEET, keeping into account the specific back - “Rapporto BES” of the Istituto Nazionale di Statistica ground of the place where teenagers live, especially in (ISTAT 2019). This is an integrated and comprehensive terms of the economic performance. Indeed, the litera- data source on the performance of the Italian provinces ture has shown that the NEET phenomenon is intrinsi- that presents the main economic, social and environmen- cally related to the structural economic and labor market tal indicators of the country. In particular, the NEET indi- characteristics. In a study conducted in Ireland, it  was cator is the measure annually provided by the Institute in clearly demonstrated the connection of the economic the Labor Force Survey. From the ISTAT database we also recession of 2008 with the NEET rate, despite the general selected variables on the economic performance. Data on characteristics of this population were basically the same cultural capital have been obtained from the researches of the pre-crisis society (Kelly and McGuinness 2015). In on the Quality of Life in Italy yearly published by Il Sole this line, European statistical institutes have long under- 24 Ore, namely the leading and most authoritative Italian lined that the NEET rate is higher in countries with dif- economic newspaper. This database, which also adopts ficulties in the economic performance (e.g., Italy, Greece The association of economic and cultural capital with the NEET rate: differential geographical… Page 7 of 17 13 some of the ISTAT indicators, has been already described which is also transformed in the researches on the Qual- elsewhere (Ripamonti and Barberis 2018). ity of life in an employment score (EMP07). Four latent variables have been introduced, namely CUL97 and 2.2 M easures and latent variables CUL07, reflecting the cultural capital of a province in We considered the ISTAT time-point indicator for NEET 1997 and 2007; ECO97 and ECO07, describing the eco- in both 2009 and 2017. The indicator refers to the per - nomic performance of the Italian provinces in 1997 and centage of people aged 15–29 years. who are neither 2007, respectively. We collected information on four employed nor were in an education or training path, time-points (1997 and 2007 for the assessment of the cul- considering the total population in the same age range. tural/economic capital indicators; 2009 or 2017 for the As concerns cultural capital, we adopted a multidimen- outcome) since we aimed to disentangle short-run and sional perspective, taking into account different meas - medium-run (Blanchard et al. 2017) effects of economic/ ures that could be linked to the development of cognitive cultural capital on the NEET rate. and non-cognitive skills in young people (Ripamonti and Barberis 2018). For the first time-point (1997), we con -2.3 Data analysis sidered the following indicators: (i) the number of book- 2.3.1 D escriptive and spatial indicators shops (BOO97); (ii) the number of art, cultural, and free We calculated descriptive indicators (1st and 3rd quar- time associations (ASS97); (iii) the number of cinemas tiles, median, interquartile range, min and max) for the (CIN97). Measures for cultural capital in 2007 were: (i) variables under study. We used choropleth maps to attain the percentage of book sale index (BOO07); (ii) the num- a complete spatial view of the values taken by the statis- ber of art, cultural and free time associations (ASS07); tical units at a detailed geographical level. These maps (iii) the number of cinemas (CIN07). These measures were also used taking into account the Local Moran index are expressed with reference to a target population of (Moran 1948) in order to study spatial dependency and 100,000 inhabitants. Analyses were repeated (and shown local peculiarities (or cluster). The Local Moran index in the Additional file  1) inserting in the measurement belongs to a large class of statistical indicators known in model for cultural capital (iv) the average expenses pro the literature as Local Indicators of Spatial Association capite to participate in sport events in 1997 (SPO97); (LISA) (Anselin 1995) and provides estimates of spatial the sport index in 2007 (SPO07). We inserted a sport autocorrelation disaggregated to the level of the statisti- indicator in the operationalization of cultural capital, as cal units. this could represent a proxy of the possibilities offered to students, in a certain geographical area, to develop 2.3.2 Struc tural equation modeling their non-cognitive skills (Ripamonti and Barberis 2018). We calculated confirmatory Structural Equation Models Since results were very similar, herein we will present the (SEM) using Covariance Structure Analysis (Jöreskog more parsimonious model without adopting the sport 1970) through Generalized Least Squares estimation. indicator. Models were defined adopting the Linear Structural As to the economic performance, we used measures Equation Modeling (LISREL) terminology and notation. and proxies of wealth (income, added value, number of The relation between latent and manifest variables was enterprises) and of employment adopted, from the ISTAT of reflective type (Loehlin 1987); all analyses were  con - database, in the researches on the Quality of Life. In par- ducted on standardized variables. In the phase of model ticular, in 1997 the indicators were: (i) the income pro building, we took into account the values of the Akaike capite (INC97); (ii) the number of enterprises for every Information Criterion (AIC). Two types of modification 100,000 inhabitants (ENT97); (iii) the ratio between job indices have been considered: (i) Lagrange multipliers seekers and labor force, i.e., the unemployment rate, (LM, parameters having the largest LM indices would which is transformed in the researches on the Qual- most increase the model fit); (ii) Wald statistics (in order ity of life in an employment score for each province (the to eliminate the parameters that are not significant and higher the better performance) (EMP97). In 2007, we may be removed without virtually affecting the model fit). adopted the following indicators: (i) the added-value pro As to the error terms matrices, we initially constrained capite (INC07); (ii) the number of enterprises for every to zero all the extra-diagonal terms, and subsequently we 100,000 inhabitants (ENT07); (iii) the ratio between job unconstrained only those terms highlighted by LMs and seekers and labor force, as a proxy of unemployment, theoretically meaningful. We considered the following indicators of model assessment (Hu and Bentler 1999): (i) the ratio between the value of the Chi square statistic and For illustration see: https:// st. ilsol e24ore. com/ inclu des20 07/ speci ali/ quali ta- its degrees of freedom; (ii) the General Fit Index (GFI); della- vita/ scheda_ indice_ 9. shtml (only available in Italian); see also Ripamonti (iii) the Adjusted General Fit Index (AGFI); (iv) the Root and Barberis (2018). 13 Page 8 of 17 E. Ripamonti , S. Barberis Mean Square Residual (RMR); (v) the Root Mean Square NEE08) or after 5 years (2012, NEE12) from the last Error of Approximation (RMSEA). assessment of cultural and economic capital (2007). A third sensitivity analysis was performed to explore 2.3.3 Mediation analysis possible differential effects attributable to the eco - To evaluate how the effect of cultural capital and of eco - nomic capital, which contains two indicators of wealth nomic capital on NEET occurs in practice, we conducted (income/added value pro-capite and number of enter- a mediation analysis. Given the relatively low amount of prises) and one indicator of employment. The same literature on the interplay between cultural capital, eco- analyses already presented in the “Structural Equa- nomic capital, and NEET, we adopted an exploratory tion Modeling” subsection have been re-run, firstly by perspective in the mediation models. Thus, we consid - inserting in the economic capital indicator only the ered both the possibility that the economic capital could GDP/added value component, and secondly by insert- mediate a historical effect of the cultural capital, and vice ing only the employment component. versa. First, we estimated whether the economic capital could mediate the association between cultural capital and 3 Results NEET. Second, we estimated whether the cultural capital 3.1 Descriptive and spatial analysis could mediate the association between economic capi- From 2004 to 2018 the NEET rate increased in all Ital- tal and NEET. Taking economic capital in 2007 (ECO07) ian macro areas, but particularly in the Southern regions as a putative mediator, we aimed to disentangle the total and in the islands (Fig. 2). In addition, as indicated by the effect of cultural capital in 1997 (CUL97) on NEET in 2009 box plots shown in Fig. 2, in Southern regions and in the (NEE09) into a direct effect and an indirect effect that goes islands, data were much more scattered from the median through the mediation of the economic capital. This analy - value than in Northern and Central regions. sis was conducted using the product method (Baron and Choropleth maps showed an increasing trend between Kenny 1986), which is based on a decomposition of the Northern and Southern provinces in terms of the NEET total effect in a direct and indirect component, by calculat - rate (Fig.  3). As indicated by the values of the Local ing a regression model for the effect of CUL97 on NEE09 Moran index, in Southern provinces and in the two while adjusting for ECO07, and another regression model islands the levels of NEET are generally high and well assessing the effect of CUL97 on ECO07. Thus, the indi - clustered. Positive spatial autocorrelation has been found rect effect expressing the mediation component can be also in Northern-East provinces, but with associated calculated by taking the effect of CUL97 on ECO07 mul - much lower rates of NEETs than in Southern or Central tiplied by the effect of ECO07 on NEE09. We repeated the provinces. same analysis targeting cultural capital in 2007 (CUL07) as a putative mediator of the association between economic 3.2 Structural equations modeling capital in 1997 (ECO97) and NEET in 2009 (NEE09). In Fig. 4 we show the three time-points model adopted to Finally, we re-estimated both mediation models inserting assess the effect of cultural capital and economic capital NEE17 as an outcome measure. on the NEET rate. We firstly considered as an outcome measure the prevalence of NEET in 2009 (Model 1); sub- 2.3.4 Sensitivity analysis sequently we repeated the same analysis, but we inserted SEM work under the assumption of no unmeasured as outcome variable the prevalence of NEETs in 2017 confounding. To explore the possible impact of endo- (Model 2). We tested these models in all the Italian prov- geneity on our findings, we developed a delimited inces, and afterwards inserting only Northern, Central, simulation study. We inserted into the SEM previ- or Southern provinces. ously outlined (with the NEET rate in 2009 as outcome, Estimating Model 1 for the entire sample of the Ital- NEE09) a putative unmeasured confounder, obtained ian provinces, we obtained a fit value χ /df = 2.50 (see by simulating a vector of values from a Normal r.v. Table 1). mildly ( ρ = 0.30), moderately ( ρ = 0.60) or highly ( ρ The effect of the economic capital in 2007 = 0.80) correlated to both ECO07 and NEE09. We re- (ECO07) on the NEET rate in 2009 (NEE09) was estimated the models and we compared the coefficients significant considering all the Italian provinces with those obtained in the original models. A second (β =−0.81(0.12), t = −6.75, p < 0.0001) , and the Cen- sensitivity analysis was run to assess the robustness of tral provinces (β =−0.28(0.11), t = −2.54, p = 0.008) . the choice of the three time points in the SEM mod- In the sample of all the Italian provinces, we also els. In particular, we re-ran the same models already found an effect of the cultural capital in 1997 explained in the “Structural Equation Modeling” sub- (CUL97) on the economic capital in 2007 (ECO07) section, but inserting the NEET rate after 1 year (2008, (β = 0.36(0.07), t = 4.88, p < 0.0001) and of the The association of economic and cultural capital with the NEET rate: differential geographical… Page 9 of 17 13 Fig. 2 Descriptive analysis. Time series for the NEET indicator from 2004 to 2018 (first and last time point of the ISTAT database), and boxplots of the NEET rate in Northern-West, Northern-East, Central, Southern provinces, and islands in 2004 and 2018 economic capital in 1997 (ECO97) on the cultural capital but not in the Northern provinces. Again, we found in 2007 (CUL07) (β = 0.22(0.05), t = 4.18, p < 0.0001) ; a significant effect of the cultural capital in 1997 these results were replicated considering the subsamples (CUL97) on the economic capital in 2007 (ECO07) of Northern, Central, and Southern provinces. However, (β = 0.45(0.08), t = 5.49, p < 0.0001) , and of the eco- we did not obtain any significant finding as concerns the nomic capital in 1997 (ECO97) on the cultural capital in 2007 effect from cultural capital in 2007 (CUL07) to the NEET (CUL07) (β = 0.16(0.04), t = 3.49, p = 0.0005) in all the rate in 2009 (NEE09). Italian provinces; analogous patterns did emerge in the sub- Estimating Model 2 for the entire sample of the Ital- samples of Northern, Central, and Southern provinces. The ian provinces, it was attained a fit value χ /df = 1.35 relation between the cultural capital in 2007 (CUL07) and the (see Table  2). The relation from the economic capi - NEET rate in 2017 (NEE17) was never significant. Factor load - tal in 2007 (ECO07) to the NEET rate in 2017 (NEE17) ings for the measurement model are shown in Table 2. was significant in the entire sample of Italian provinces (β =−0.94(0.11), t =−8.54, p < 0.0001) , in the Central 3.3 Mediation analysis (β =−0.98(0.19), t = −5.15, p < 0.0001) and in the South- From SEM it emerged a protective effect of the eco - ern provinces (β =−0.81(0.24), t =−3.37, p = 0.0008) , nomic capital on the NEET rate. To better understand 13 Page 10 of 17 E. Ripamonti , S. Barberis Fig. 3 Spatial analysis. Distribution (above) and Local Moran index of autocorrelation (below) for the NEET rate in Italy in 2004 and 2018 how this effect occurs and the possible interplay of not significant, and for the 83% (Z = 7.70, p < 0.0001), it economic capital with cultural capital we conducted was attributable to the mediation component played by a mediation analysis using the product method. After the economic capital in 2007 (ECO07). We calculated having verified the absence of interaction between the another mediation model (having verified the same cultural capital in 1997 (CUL97) and the economic assumption of absence of interaction effects), insert - capital in 2007 (ECO07), we inserted the variable eco- ing the cultural capital in 2007 (CUL07) as a putative nomic capital in 2007 (ECO07) as a putative mediator mediator of the effect between the economic capital of the effect between cultural capital in 1997 (CUL97) in 1997 (ECO97) and the NEET rate in 2009 (NEE09) and the NEET rate in 2009 (NEE09) (CUL97 – > ECO07 (ECO97 – > CUL07 – > NEE09). Results pointed to 24% – > NEE09). The direct effect from the cultural capital (Z = 3.17, p = 0.001) of the effect due to the mediation in 1997 (CUL97) to the NEET rate in 2009 (NEE09) was component of the cultural capital in 2007 (CUL07), and the direct effect from the economic capital in 1997 (ECO97) to the NEET rate in 2009 (NEE09) was also 3 significant ( β =−0.36(0.06), Z =−5.52, p < 0.0001 ). Creating the quartiles of the CUL97 and ECO07 scores and inserting them as covariates in a multiple regression model with NEE09 as outcome measure. We repeated the same calculations inserting the NEET The association of economic and cultural capital with the NEET rate: differential geographical… Page 11 of 17 13 Fig. 4 Illustration of the three-points SEM (a similar model has also been estimated substituting NEE09, indicator for NEET in 2009, with NEE17, indicator for NEET in 2017) effect from the economic capital in 1997 (ECO97) to Table 1 Fit index for SEM considering all the Italian provinces (IT), and, separately, Northern (N), Central (C) and Southern (S) the NEET rate in 2017 (NEE17) was also significant provinces ( β =−0.41(0.07), Z =−5.91, p < 0.0001 ). To sum up, 2 cultural capital seems to play a weak (and statistically Model GFI AGFI RMR RMSEA χ /df non-significant) role on the NEET rate, and such rela - Model 1, IT 2.50 0.83 0.65 0.18 0.12 tion seems strongly mediated by the economic capital. Model 1, N 1.33 0.47 0.66 0.08 0.09 By contrast, in the medium term the economic capital Model 1, C 1.09 0.76 0.52 0.42 0.05 would play a consistent effect on the NEET rate, and such Model 1, S 1.24 0.73 0.44 0.22 0.08 effect seems partly mediated by the cultural capital. Model 2, IT 1.35 0.48 0.66 0.11 0.09 Model 2, N 0.96 0.47 0.64 0.22 0.01 3.4 Sensitivity analysis Model 2, C 3.28 0.38 0.32 1.15 0.26 We conducted a first sensitivity analysis, as described Model 2, S 2.07 0.75 0.50 0.08 0.18 in the Methods section, to assess the possible impact GFI: Global Fit Index; AGFI: Adjusted Global Fit Index; RMR: Root Mean Square of endogeneity on our models. In this regard we simu- Residual: RMSEA: Root Mean Square Error of Approximation lated (from Normal random variables), the presence of an unmeasured confounder in the SEM including all the Italian provinces. Three scenarios have been rate in 2017 (NEE17) as an outcome variable, and we evaluated, inserting a mild, moderate, or strong con- found that the economic capital in 2007 (ECO07) pos- founder, respectively. Results (see Table  3) indicate sibly mediated almost the 100% (Z = 7.32, p < 0.0001) of that both the relations from the economic capital in the effect of the cultural capital in 1997 (CUL97), while 2007 to the NEET rate in 2009 (ECO07 – > NEE09) and the direct effect of the cultural capital in 1997 (CUL97) from the economic capital in 2007 to the NEET rate on the NEET rate in 2017 (NEE17) was not significant. in 2017 (ECO07 – > NEE17) are robust with respect to The variable cultural capital in 2007 (CUL07) medi - the presence of a mild or of a moderate unmeasured ated about the 16% (Z = 2.42, p = 0.01) of the effect of confounder, but the statistical significance may not the economic capital in 1997 (ECO97), and the direct be confirmed in case of a strong confounder. While 13 Page 12 of 17 E. Ripamonti , S. Barberis Table 2 Factor loadings for the measurement model in all the Italian provinces. We report the estimate (SE) CUL97 ECO97 BOO97 0.79 (0.05)* ASS97 0.68 (0.07)* CIN97 0.95 (0.04)* INC97 1.16 (0.06)* EMP97 0.36 (0.11)* ENT97 0.99 (0.05)* CUL07 ECO07 BOO07 1.05 (0.22)* ASS07 0.95 (0.20)* CIN07 0.77 (0.18)* INC07 0.96 (0.01)* EMP07 0.91 (0.02)* ENT07 0.92 (0.02)* * Indicates a significant p-value as well as the relation from the economic capital in Table 3 Sensitivity analysis, examining the robustness of the 2007 to the NEET rate in 2012 (ECO07 – > NEE12) relations ECO07– > NEE09 and ECO07– > NEE17, when inserting (β =−1.14(0.13), t =−8.49, p < 0.0001). a mild, moderate or strong unmeasured confounder (UC) in the A third sensitivity analysis was run including in the model operationalization of the economic capital only the indicators of wealth (GDP/added value), without the β(SE) t p-value employment index. While the result was still in the ECO07– > NEE09 expected direction, neither the relation from the eco- Original − 0.81(0.12) − 6.75 < 0.0001 nomic capital in 2007 to the NEET rate in 2009 (ECO07 With mild UC − 0.89(0.16) − 5.45 < 0.0001 – > NEE09) (β =−0.35(0.87), t = −0.41, p = 0.68) With moderate UC − 0.97(0.22) − 4.40 < 0.0001 nor the relation from the economic capital in 2007 With strong UC − 0.00009(0.00007) − 1.33 0.18 to the NEET rate in 2017 (ECO07 – > NEE17) ECO07– > NEE17 (β =−0.40(0.42), t =−0.96, p = 0.33) proved sta- Original − 0.94(0.11) − 8.54 < 0.0001 tistically significant. A similar finding emerged With mild UC − 0.96(0.14) − 6.53 < 0.0001 when inserting only the indicator of the employ- With moderate UC − 1.07(0.23) − 4.50 < 0.0001 ment in the general population without the indica- With strong UC − 0.00002(0.0007) − 0.09 0.92 tors of wealth; the relationship was negative but not significant, neither in the short run (from the eco - nomic capital in 2007 to the NEET rate in 2009, ECO07 – > NEE09: β =−0.32(0.27), t =−1.16, p = 0.24 ) these results are worth reporting, the presence of a nor in the medium run (from the economic capital strong unmeasured confounder, i.e., a variable related in 2007 to the NEET rate in 2017, ECO07 – > NEE17: to both the economic capital in 2007 (ECO07) and the β =−0.01(0.53), t =−0.02, p = 0.98 ). Together, these NEET rate in 2009/2017 NEE09/NEE17 (with ρ ≥ 0.80 ) results indicate the importance of considering in the should be justified theoretically and proven empirically. measurement model describing the economic capital In a second sensitivity analysis we re-estimated the both the indicators of wealth and of employment in the SEM model for all the Italian provinces, inserting as general population. outcome variable the NEET rate in 2008 (NEE08) or the NEET rate in 2012 (NEE12). We obtained very similar results to those already presented in the “Struc-4 Discussion tural equations modeling” subsection. In particular, In contemporary European societies the new generations the relation from the economic capital in 2007 to the experience an unexpected condition of decline of their NEET rate in 2008 (ECO07 – > NEE08) was still sig- status and economic possibilities as compared with the nificant (β =−0.97(0.06), t = −15.14, p < 0.0001) previous generation. One of the phenomena testifying The association of economic and cultural capital with the NEET rate: differential geographical… Page 13 of 17 13 this dependence position is represented by NEETs, who of attained level of education, becoming NEET may indi- are a very heterogeneous group of teenagers and young cate a virtually stable (at least in the short run) vulner- people with marked and persistent difficulties in the tran - ability condition more deeply rooted than that implied sition from school to the labor market. For an improved by dropping out of high school. It should also be added organization and implementation of policies contrasting that in the present study and in Ripamonti and Barb- the NEET phenomenon it is important a deep under- eris (2018), following the definitions provided by Pub - standing of the determinants of this outcome, including lic Authorities and Statistical Institutes, two different the macro level antecedents. In this paper, we analyzed at age cohorts were considered (15–24 for school dropout, a detailed geographical level the relation among cultural including both early school leavers and non-completers capital, economic capital, and the NEET rate. The analy - of high school; 15–29 for NEET), which could also ses have been conducted in Italy, which is one of the EU explain part of the heterogeneity in the results. countries with the highest levels of NEETs, and also pre- An alternative possible explanation to the absence of sents with some structural weaknesses in its vocational direct effect of cultural capital on the NEET rate may rely system (Ballarino 2015), e.g., lack of investment on the on the definition of NEET provided by the ISTAT and dual apprenticeship system, which is a protective factor by other national statistical agencies, i.e., the percentage against NEET (Eurofound 2012). of people aged 15–29 (or 15–34) that are neither on a Results of the SEMs presented herein point to a protec- formative track nor employed. This definition potentially tive effect of economic capital on the NEET rate in the includes both unemployed young people who are non- short run (2  years), considering all the Italian provinces studying and are actively searching a job (as in the defi - and the Central provinces. The same protective effect nition of unemployment rate) and young people who are was found in the medium run (10  years) considering all not studying and are also out of the labor market (inac- the Italian provinces, the Central and the Southern prov- tive non-students). We may hypothesize that cultural inces. In addition, the economic capital strongly mediates capital can affect NEETs capacity to actively search for the effect of the cultural capital, which, as a direct effect, a job. Indeed, these young people could be motivated to is not significant. The cultural capital, by itself, does not find a job or a formative activity by experiencing an ani - play a direct protective role on the NEET rate, but may mate cultural environment. mediate the effect of the economic capital. Our results The mediation analysis also showed that, while there are in line with the hypothesis that the economic capital, does not seem to be a consistent direct protective effect at a macro level, affects the educational and labor market of cultural capital on the NEET rate, such relation is outcomes (Kelly and McGuinness 2015). In addition, as mediated by the economic capital. Thus, a province shown in the sensitivity analysis, both components of the with high levels of cultural capital would longitudinally economic capital considered in our analyses, i.e., wealth increase the likelihood to ameliorate its economic capital, and unemployment, are associated with the NEET rate. and this would reflect in a better outcome in terms of the u Th s, data  presented herein clearly point to  an increased NEET rate, both in the short and in the medium run. NEET rate in territories characterized by scarce economic Relevant geographical differences emerged in our performance. Our findings are in line with the previous analyses are also to be highlighted. Considering the literature, which highlights a correlation of the NEET rate subsample of Northern provinces, contrary to our pre- with the general unemployment rate and with the GDP diction, we did not identify any protective effect of the level (Eurofound 2012). This paper adds to previous stud - economic or cultural capital, neither in the short run ies a clear timing of the effects, as well as an analysis of nor in the medium run. High levels of both economic the role of economic capital (where both the components and cultural capital characterize these provinces. Thus, of wealth and general unemployment rate have to be kept a possible explanation of these negative results may into account) at a detailed geographical level. be in terms of a ceiling effect, i.e., an excellent perfor - It was a hypothesis of this article that of a putative mance with very low variation in a prediction variable, protective effect of cultural capital on NEET, following which may lead to hamper the possibility of captur- a similar finding already described for high school drop - ing a putative protective effect in the regression mod - out (Ripamonti and Barberis 2018). Differently from such els. It is also worth observing that  the Local Moran assumption, our findings did not indicate a direct protec - index indicates the presence of a certain heterogeneity, tive effect of cultural capital on the NEET rate. The dis - despite low values in magnitude, of the NEET indicator crepancy of results emerged herein with those reported in Northern-East provinces, but not in the Northern- in Ripamonti and Barberis (2018) could be explained in West provinces. terms of the different outcome considered in the two Another form of capital that could be linked to the studies. While non-completion of high school is a proxy NEET rate is given by social capital, which, following the 13 Page 14 of 17 E. Ripamonti , S. Barberis sociological tradition, could be operationalized in terms of young people with very different backgrounds and of connections, social networks, trust (Coleman 1988). developmental histories. Hence it may become diffi - While it would be worth investigating social capital as cult to program proper and individualized policies to a putative protective factor for NEET, it is also clearly deal with this phenomenon. The other side of the coin differentiated from the construct of cultural capital, as is that, thanks to the uncertainty degree underpinning originally underlined by Bourdieu (1994). Thus, introduc - the NEET definition, the NEET rate may allow to cap - ing social capital in this analysis would raise a quite dif- ture, at least at an aggregate level of analysis, particu- ferent research question, which we leave open for future larly vulnerable young people without a job but also research. Social capital could also help to better under- without the possibility of developing their human capi- stand the NEET phenomenon in the Northern provinces, tal in proper formative tracks. This frail segment of the where no significant effect of cultural or economic capital youth population would not be captured by the stand- did emerge. ard unemployment rates (Rosina 2015). In terms of timing of the effects, in this article we basi - Even though our analysis presents some limita- cally adopted an econometric viewpoint. In the eco- tions, we assume that understanding the role played nomic theory (Blanchard et  al. 2017) short-term effects by high-level variables may drive and provide guidance are those described in one or few years, while medium- on future research at a micro-level of analysis. At this term effects generally imply a timing of about a decade. stage, macro–micro link studies in all areas of research Both cultural and economic capital have been measured related to transition to adulthood, including becoming before the great recession of 2008. While it is interesting NEET, are still scarce (Buchmann and Kriesi 2011). A to observe that economic capital plays a protective effect second limitation is that we restricted our analyses to on NEET on both the short run and the medium run (but the assessment of the economic condition before the no effect has been described for cultural capital), results economic crisis of 2008, which relevantly weakened the should be carefully interpreted. Indeed, our analysis has economy of Southern European countries. Young peo- only 4 time points. We did not conduct a time-lagged ple and the youth labor market were disproportionately analysis with multiple time points, neither we considered affected by the consequences of the crisis (Bell and change scores of the NEET rate. These possibilities are Blanchflower 2011), as recently documented in terms open for future investigation using a more comprehen- of youth unemployment and employment trajectories sive data source as well as other longitudinal methods for in Spain (Verd et al. 2019). An evaluation of the effects data analysis, such as econometric panels. It is important of the great recession (2008 and the double-dip, 2012) to remark that in Southern provinces the protective effect in terms of the NEET rate, in relation with the eco- of the economic capital on the NEET rate was obtained nomic and cultural capital, could be a specific issue for only in the medium run scenario (i.e., after 10 years), but a future investigation. not in the short run scenario (i.e., after 2  years). These In conclusion, we found that the economic capital provinces are characterized by low levels of economic (considered in both dimensions of wealth and employ- performance and by marked spatial heterogeneity in the ment), independently of cultural capital and measured economic performance (Ripamonti and Barberis 2018), before the economic crisis of 2008, may protect young which, together, could imply that the beneficial effect of people from becoming NEET. Peculiar geographical a slow economic development on the young generation and temporal patterns did emerge, with the effect of the may be detectable only after a decade or longer. economic capital being particularly relevant in Italian A first limitation of this study is that of having only Central provinces, and in the Southern provinces only investigated the potential protective factors on the in the medium run scenario. Findings reported herein NEET rate at a macro-variable level, without studying indicate relationships among variables at a macro level, the  effect of the macro level on the micro  level, in dif - and should be complemented by future research at an ferent  cultural contexts (Rogoff 2003). In Italy, as well individual level. Our final message to policy makers is as in other EU countries, large administrative databases that investment in economic development, especially in on phenomena like NEET, at individual level, are still economic depressed areas like Southern Italy, may have under construction, and are not currently available on a beneficial effect on the NEET rate in the short and in a large scale. This problem also hampers the possibil - the medium run. The role of the economic capital may ity to properly address the heterogeneity issue in the be partly mediated by the cultural capital, which, how- NEET population. Heterogeneity represents one of the ever, does not seem to play an independent effect on main problems of using the NEET category (Furlong the NEET rate. Investment on culture and education 2006; Yates and Payne 2006) since it probably reflects cannot be isolated from investment on economic devel- the presence, under the same umbrella term (“NEET”), opment, and a multifactorial phenomenon like NEET The association of economic and cultural capital with the NEET rate: differential geographical… Page 15 of 17 13 European Perspective: A Comparative Analysis, pp. 181–208. Policy demands complex, differentiated, and multi-compo - Press, Bristol (2015) nent policies. Barbieri, P., Scherer, S.: Labour market flexibilization and its consequences in Italy. Eur. Sociol. Rev. 25, 677–692 (2009) Barham, C., Walling, A., Clancy, G., Hicks, S., Conn, S.: Young people and the Supplementary Information labour market. Econ. Labour Mark. Rev. 3, 17–29 (2009) The online version contains supplementary material available at https:// doi. 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Published: Apr 28, 2021

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