NEETs in Europe | Encyclopedia MDPI

NEETs in Europe: Comparison

Please note this is a comparison between Version 2 by Dean Liu and Version 1 by Carlos Pesquera Alonso.

The rates of young people Not in Education, Employment or Training (NEET) in the Mediterranean European Economic Area (MED EEA) are high. Hence, the European Union and national governments have developed and implemented different policies aimed to tackle the NEET situation.

NEET
Mediterranean European Economic Area
youth guarantee

1. Introduction

In the Mediterranean European Economic Area (MED EEA), the rate of young people Not in Education, Employment, or Training (NEETs) increased after the hit of the 2008 financial crisis (Boot et al. 2016). Although these levels have started to decrease in the area since the peak of that crisis, the recovery process was still ongoing when the COVID-19 pandemic stopped it (Eurostat 2022). Recent years have seen the implementation of a series of EU programs aiming for the employability of the younger segments of the population. The success of those programs is still debatable: part of this improvement may be a consequence of the policies implemented in the European Union, but their efficiency is questioned due to their limited success (Focacci 2020).

2. NEETs in Europe

Although the term NEET is relatively new, there are many policies focused on NEETs (Williamson 2002), and many researchers have already highlighted the importance of these policies to reduce the NEET rate. Following that argument, many countries, as well as the European Union, opted to develop NEET policies to solve the situation (Eurofound 2012b). Although these types of policies may include funds and different mechanisms, as well as strategies focused on reducing the NEET rate, they do not prevent the criticism about resource efficiency regarding their main tools which aim to solve the NEET situation (Rodríguez Soler and Verd 2018). Another highlighted point in this discussion is the range of policies that have an impact on improving the NEET situation. Authors such as Carcillo and Königs (2015) argue that there are policies, which are not NEET policies (e.g., social benefits or special education programs), that are important for the improvement of the NEET situation, especially when one considers the most vulnerable groups. In this context, the authors also remarked that differences in NEET rates are also influenced by different contextual factors, such as the national economic situation. In the European framework, the main NEET policy is the Youth Guarantee, developed after a 2013 European Council Recommendation. Immediately after its implementation started in the second quarter of 2014, there were authors who claimed that it lacked the level of resources needed to achieve its own recommendations (Escudero and López Mourelo 2015), that to achieve its goals, it should address other factors that were causing the NEET situation (Pastore 2015), and that it could provoke negative side effects (Cabasés Piqué et al. 2016). After several years of implementation, there is no clear conclusion concerning this policy. Many authors present findings that reveal that the policy is partially working (Focacci 2020), but it is still far away from achieving its goals. Others wrote about the adjustments that it experienced (Kraatz 2017), and the time and changes it needed to adapt to each context (Milana and Vatrella 2020). Research shows that the wider the range of people under a policy, the more difficult it is to adapt the policy to the profiles of the different subgroups (Lahera 2004)—and that more diversified social spending increases the probability of success of people in need (Cuadrado Roura et al. 2017). Hence, many, such as Eurofound (2012a) in its reports on NEETs, support the thesis that the more tailored to the target group a policy is, the higher the probability of its success will be. In order to achieve this ideal of an efficient tailored policy, authors such as Mascherini (2017) highlighted the value of public policy evaluation. The author showed that, regarding the NEET policy, the evaluation process helps to improve the flexibility and adaptability required to successfully achieve the needs of the diverse target group. In line with the intersectionality indicated by Gökşen and Öker (2017), women show a higher risk of not achieving labor integration when their age increases, or when the focus is solely on migrants. Other authors have remarked that women show greater participation in education, especially during adolescence, but less employability when they enter the labor market (Vancea and Utzet 2018), which is linked to different ideas concerning the role of women in society. Women may have a greater propensity to assume household duties, which translates into a factor that influences the disparity in NEET rates (Maguire 2018). Due to the age group, an important role that influences women and can become a barrier is motherhood. Studies for European countries with different levels of gender equality and NEET rates, such as Finland (Saloniemi et al. 2020) or Hungary (Szabó 2018), included the factor of care status in closing this gender gap. Despite the different approaches and reasons behind the policies existing in each country, the benefits, offered in the form of financial aid or maternity leave, favor that more women than men choose to care for their offspring. As a consequence, some women are left out of the labor and training markets. Regarding the characteristic of coming from another country, the first barrier that migrants face is related to how the concept of a migrant is socially understood (Brahic and Lallement 2020). Due to this social idea, being labelled as such may bear negative implications, even for those who were born in the country, but descend from people who were not. Being a migrant has real measurable effects—for example, on average, a lower educational level is reached (Borgna 2016). They may face extra barriers, such as not being fluent speakers of the local language or experiencing difficulties obtaining official recognition for their educational certifications, which results in ‘disqualification’ (Gökşen and Öker 2017). These are elements of vulnerability that, as highlighted by Gökşen and Öker, are reflected in the higher NEET rate for migrants. Another factor that affects them is the community in which they live. Living concentrated in residential areas or so-called ghettos can facilitate comfort in the case of language difficulties, by surrounding themselves with people who speak the same language. However, it is also linked to issues in educational and work integration. Checa Olmos et al. (2018) pointed out that certain dynamics of migrant labor integration caused these difficulties, and they can be transmitted over generations. These authors focused on the primary sector, since it is a space with a high relative percentage of migrant population. They showed that these levels of participation in the sector can be explained by the reduction of barriers such as language, unskilled manual work, the high irregularity of contracts, the physical burden of work, etc. There is also research signaling barriers that are not exclusive to NEET policies, and do not only affect the most vulnerable people. For example, the motivation of both users and the key informants that implement public policy, especially if the demotivation of public workers reaches high levels, is a relevant factor (de Simone et al. 2018). In the case of NEETs and more vulnerable groups, this motivational aspect may be related to low expectations. They can derive from a lack of confidence in their future, thinking that the economy is performing in a worse way, or that the solutions provided by the institutions are not useful, etc. (Cabasés Piqué et al. 2017). In particular, the migrant population may carry extra considerations (i.e., not knowing the institutions, being afraid of incompatibilities with other aid, or being in an irregular situation), as well as the social pressure and expectations regarding being older or a woman (Maguire 2018). Other difficulties may be related to the dissemination of programs (Cabasés Piqué et al. 2017), which implies that institutions need to inform and convince the target group to participate in the policy.

References

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