Youth Aspirations and the Future of Work

A Review of the Literature and Evidence

Drew Gardiner

Dr Micheline Goedhuys

Introduction

“The aspirations of young people are essential to their human capital investment, educational choices and labour market outcomes.”

Poverty, despair and precariousness are commonly understood to deprive young people of significant opportunities, experiences and even freedom. The effects of poverty can extend beyond economic opportunities and deprive young people of their aspirations and leave psychological scars. And especially in the context of the massive current and future changes in labour markets around the world, a vitally important question is whether it is possible to enhance the beliefs and aspirations of young people – even those most economically marginalized – in a way that helps them overcome what life throws in their path? The answer is that, if it is possible to influence beliefs and aspirations in such a way as to lead to higher levels of labour market attainment, then appropriate policies can be developed.

As confirmed by recent trends analysis, young people in particular remain disadvantaged in the labour market. The transition from school to work is increasingly difficult, with the latest data putting the global youth unemployment rate at 13.6 per cent in 2020. Three out of four young workers are employed in the informal economy, especially in the developing parts of the world. Informal employment is one of the main factors behind a high incidence of working poverty among young people. According to International Labour Organization (ILO) estimates, more than a fifth of young people are not in employment, education or training, three-quarters of whom are women.

Compounding this situation is the fact that the world of work is changing rapidly, with technological and climate change altering the conditions of production and labour markets undergoing substantial shifts. The transformation of employment relations, expanding inequalities and economic stagnation greatly hamper the achievement of full employment and decent work for everyone.

If young people are to benefit from the changing nature of the world of work, they need to be prepared, both in terms of skills attainment and level of ambition and aspiration. The aspirations of young people are essential to their human capital investment, educational choices and labour market outcomes. When realistic aspirations combine with an individual’s sense of agency and a belief that change can occur through their own effort, and given the pathways and tools to support achievement, success can be the outcome.

Understanding aspirations is important when developing effective employment policies. If the career aspirations and life goals of youth are not considered, employment policies aiming to “match” skills with labour market opportunities may continue to fail young people.

This report was undertaken as part of the ILO Future of Work project and aims to (i) review the literature on the concepts and drivers of aspirations; (ii) develop a conceptual framework that relates labour market conditions to aspirations; (iii) map the existing survey-based evidence on the aspirations of youth worldwide; and (iv) provide insights into how to improve data collection, research and evidence-based policy-making related to young persons aspirations.

In particular, the objectives of this report are to:

review the literature discussing the concepts of aspirations, beliefs, expectations, and the relations between them;
understand the drivers and determinants of youth aspirations;
provide a conceptual framework on how labour market policies and shocks affect aspirations;
identify existing data sets and survey questions measuring aspirations and related concepts in the world of work;
identify gaps in the evidence and provide recommendations for future aspirations data collection;
formulate recommendations for aspirations-sensitive employment policies.

This review is structured as follows: section 2 provides information on the methodologies used to identify and select the relevant literature and data sources. Section 3 develops a theoretical framework based on scientific studies into the concept and determinants of aspiration. Section 4 turns to the world of work and highlights the current important challenges impacting youth aspirations worldwide. After presenting an overview of the survey-based data sources covering youth career aspirations and related concepts in section 5, section 6 presents key evidence of aspirations, mapping the global trends in youth aspirations as labour markets change. Section 7 concludes with recommendations for data collection and for the development of interventions that take account of aspirations in order to produce better labour market outcomes.

This work was undertaken by a group of researchers at UNU-MERIT, Maastricht, the Netherlands, coordinated by Micheline Goedhuys of UNU-MERIT and Drew Gardiner of the ILO. The researchers and co-authors to this report include Alison Cathles, Chen Gong, Michelle González Amador and Eleonora Nillesen. The research took place from 25 November 2018, until 30 April 2019. The review was presented at ILO Geneva, on 19 April 2019, Employment Seminar Series #26 on “Aspirations and the Future of Work: Global Evidence”.

Methodology of the study

The sections into which this review is divided each has its own scope and objectives and therefore different search techniques were applied to identify the most relevant literature. To develop the concept of aspirations, in section 2, we first look at early academic discussion of aspirations and the economy, and then expand on its conceptualization by revisiting classic papers in Psychology and its application in current literature on Behavioural Economics. We further divide section 2 into subsections to facilitate an easy flow of ideas, from (a) the concept of aspirations (how they differ from beliefs and expectations, how they might be biased and how they might fail); to (b) what shapes and drives aspirations (poverty, policy shocks, role models, community structures and peers’ networks); and finally to (c) the effectiveness of aspirations (results from empirical studies on aspirations and policy implications).

The papers used in this review were identified through a systematic search using Google and Google Scholar; EBSCO (EconLit); SpringerLink; Maastricht University Library; and Elsevier for the period 1998 to 2018, as well as revisiting some classics from 1966, 1977 and 1981. The keywords used to identify the relevant papers included, but were not limited to: aspirations, aspirations formation, aspirational failure, aspirational bias, adolescents’ aspirations, aspirations and educational outcomes, aspirations and labour market outcomes, occupational outcomes and choices, drivers of aspirations, role models, social interactions and aspirations, hope and aspirations, capacity to aspire, aspirations and economic change.

For section 4, which addresses challenges in the labour market, we build on the existing reports published by the International Labour Office, such as the World Employment and Social Outlook series, in order to identify some of the most salient evolutions within the labour market that directly affect aspirations. This is complemented by a selection of recent academic publications identified through searches of EBSCO, Cambridge Journals, EconPapers, Google Scholar and SpringerLink for the period 2000–18. Search strings included, but were not limited to: future of work, youth labour market outcomes, education job mismatch, labour market policy, working condition, NEET, and variants thereof, alone and in combination with aspirations. We imposed as an additional criteria that a paper had to have been published in a leading journal or have been cited at least 30 times if published before 2010. The literature sections and literature references from the studies selected were also investigated, so as to complement the list of studies compiled with any additional relevant works we may have missed in the systematic review.

To map aspirations and the labour market outcomes for youth (sections 5 and 6), an initial list of surveys was provided by the ILO. This was then expanded in the following ways. If a report from the initial list mentioned another survey or report containing data from focus groups or interviews, it was checked and, if found to be relevant, added to the list of literature. A few other sources were identified through a systematic search in Google, Google Scholar, the Maastricht University Library (which houses numerous databases and e-journals) and the websites of the following international organizations whose data is open to the public: Eurostat, the ILO, the OECD, UNESCO and the World Bank. The following keywords were used: “survey”, “data”, “interview”, “focus group” plus “youth aspiration” and variants, such as “young people”. The Global Entrepreneurship Monitor (GEM) was not found via this search, but instead added because of potential indicators of interest.

We first searched the databases looking for (i) type of indicators; (ii) accessibility of indicators at country level or in a more disaggregated form, either as data or from reports; (iii) country coverage; (iv) years covered; (v) representativeness of the underlying sample; and (vi) target group. Based on this outcome, we extracted countries (including emerging ones, such as the BRICS countries, developed and developing countries) and indicators (related to perceptions, aspirations and expectations, and drivers regarding technological change, employment and education) in order to identify data trends across different geographical regions.

The concept and determinants of aspirations

3.1 Understanding aspirations

Aspirations are the driver of an individual’s life path and well-being. The idea that aspirations are proxies for human choice and determinants of socioeconomic outcomes is not new to the social sciences. Ever since the landmark examination of aspirations in Kurt Lewin’s Principles of Topological Psychology (1936), social psychologists have been concerned with the concept and its effects on an individual’s actions and interactions in society. The field of sociology introduced the notion of aspirations as a determinant of educational and occupational attainment as early as the 1960s. Career aspirations can drive choices in education, job-seeking efforts and, consequently, salaries. Today, there is a renewed interest in the role played by aspirations in lifetime outcomes and in how they shape social development. Through the work of anthropologist Arjun Appadurai and economist Debraj Ray, there has been substantial research on how aspirations affect the lives of individuals and why they are at the core of efforts at socioeconomic development. It is at the intersection between the study of aspirations and development policy action that this analysis investigates youth aspirations within a changing world of work.

Appadurai and Ray posited the notion that aspirations are unevenly distributed across society and that people born into poverty, among other structural disadvantages, are less likely to aspire to make significant changes in their lives. This results in low human capital investment and hinders the social mobility efforts that policy tries to promote. Appadurai (2004) defines aspirations as a “capability”; that is, the capacity to aspire is the ability to navigate social life and align wants, preferences, choices and calculations with the circumstances into which a person is born. However, as a navigational ability, the capacity to aspire is not distributed evenly: individuals born into less privileged backgrounds will have a more limited social frame within which to explore what is possible than their more privileged counterparts.

Ray (2006) has contributed to an understanding of the capacity to aspire by introducing the concept of “aspirations failure”. For Ray, the capacity to aspire can be measured as the distance between where you are and where you want to go. How great this distance is, the extent of the “aspiration gap”, determines whether aspirations can be a true motivator of change during the life course or whether there is instead a likelihood of aspirations failure through a lack of capacity to aspire. If the gap is too small, then a person will fail to aspire to significant change in their life; conversely, if the gap is too large, a person will fail to turn aspirations into action. Moreover, setting unrealistic aspirations might decrease the motivation to see them fulfilled. Thus, the relationship between aspiration and action is shaped like an inverted U: aspirations that are either too low or too high will yield limited action, whereas reasonable aspirations will motivate effort and produce action.

Dalton, Ghosal and Mani (2016) explained this phenomenon further by introducing aspirations failure as a “behavioural bias”, something to which all people, regardless of background, can be susceptible. In their view, individuals can fail to recognize the adaptive, dynamic mechanism in operation between effort exerted and aspirations. Aspirations spur effort and motivate action, but the level of effort a person chooses to exert will influence their future aspirations through realized outcomes. This dynamic has an especially detrimental effect on individuals confronted with a tremendous number of external constraints; for instance, only limited or non-existent material resources. Because poverty is the biggest external constraints, people who are poor must exert greater effort to achieve the same result as those who are not poor. Failing to account for this susceptibility in the design of socioeconomic development policies can result in a low take-up of opportunities or their being missed entirely.

Acknowledging the relevance of aspirations to development efforts, Lybbert and Wydick (2018) investigated how aspirations can be realized and become positive outcomes. They turned to Snyder’s (2002) theory of hope1 to explain how to arrive at successful aspirations. First, individuals need to set a goal for the future (an aspired position). Second, they need to have the necessary agency to carry out the steps required to attain that goal. Third, they need to visualize pathways to achieving that goal, such as access to the cognitive or material tools necessary for their journey.

When what a person aspires to for the future is aligned with what they believe can be achieved, given their circumstances and through their own effort (Dalton, Ghosal and Mani, 2016; Bandura, 1993), then aspirations become analogous to expectations and successful outcomes more likely. Therefore, whereas aspirations afford a dimension for preferences, expectations are the product of experiential perceptions, such that they become more context specific. Through this framework, the inverse U-shaped relationship between aspirations and action propounded by Ray can be better understood as the proposition: if aspirations that are either too low or too high discourage motivation, then there is a peak to be found where aspirations meet expectations towards the top of the inverse U curve. By designing policies and programmes that help recipients visualize the potential pathways to achieving their goals, development efforts can productively mobilize the motivating power of aspirations.

In line with Appadurai’s notion that the capacity to aspire is defined by social frames, Bandura (1977) had earlier investigated how social experiences shape how we behave in society. Social learning, either by the setting of personal boundaries through social norms or by imitating role models, determines how we behave and what we believe to be attainable for ourselves. Bandura introduced another component of cognitive and social learning, namely, “self-efficacy”, or, the belief in one’s capacity to succeed in any given situation. Self-efficacy is shaped by personal experiences and an important driver of aspirations (Bandura et al., 2003).

Bandura’s ground-breaking study of the capacity to aspire finds an echo in Amartya Sen’s “capability approach”. Sen (1985) proposed a framework in which human development is centred on an individual’s person’s capabilities and the real opportunities presented to that individual to do what they have reason to value (Robeyns, 2016). Not unlike Appadurai’s and Ray’s conceptions of aspiration formation, Sen posited that opportunities are not solely dependent on an individual’s choices but also on their social circumstances (Drèze and Sen, 2002). However, Sen conceived social circumstance as being what a society could provide for its citizens in terms of structures, as opposed to the cognitive roadmap envisioned by Appadurai and Ray. Together, they provide a larger picture of the phenomenon: an individual’s capacity to aspire to, say, productive work, is contingent upon their own experiences (Dalton, Ghosal and Mani, 2016), what they learn from society and what society can provide for them. The latter two are of particular interest for policy, because they mean that work aspirations are shaped by a person’s experience with, assessment of and expectations about the labour market institutions and policies operative in their society.

Aspirations require further investigation, because they tell us about the well-being of individuals and something about the cooperative nature of the recipients of development policies and social programmes. If people believe they have the ability to bring about meaningful change in their lives through effort (Lybbert and Wydick, 2018; Dalton, Ghosal and Mani, 2015; Bandura, 1993), and that they have the necessary avenues and pathways to change, be it naturally through social circumstances (Ray, 2006; Appadurai, 2004; Bandura, 1977) or by design through policy (Lybbert and Wydick, 2018), then they are likely to accept the opportunities offered to them through policy interventions.

3.2 What shapes aspirations?

The empirical literature defines aspirations as forward-looking behaviour. Aspirations capture the personal desires of individuals (preferences and goals), their beliefs about the opportunities available to them in society (opportunities and pathways) and their expectations about what can be achieved through their own effort in an uncertain future (self-efficacy and agency)2 (Favara, 2017; Ross, 2016; Dalton, Ghosal and Mani, 2016; Bernard et al., 2014; Bernard and Taffesse, 2014; Bernard et al., 2011). This working definition has allowed policy and development researchers to disentangle the mechanisms by which the circumstances in which we live affect aspirations formation and the extent to which an updating of aspirations results in improved outcomes.

Through the frameworks developed by Appadurai (2004) and Ray (2006), aspirations are understood as being socially determined: our perception of what is available to us in society is greatly influenced by what others around us think and do. The behaviour of our immediate social network is a reference that informs our own behaviour (Bogliacino and Ortoleva, 2013). For example, in a review of risk preferences and social interactions, Trautmann and Vieider (2012) demonstrated that risk-taking behaviour changes together with aspirations when subjects are placed into peer groups where they suddenly find themselves at risk of losing what they have. Peer frame, or peer structure, is perceived by subjects as a social reference point, which changes aspirations and, consequently, risk-taking behaviour and actions. Similarly, studying a sample of Chinese workers, Knight and Gunatilaka (2012) observed their income aspirations evolve positively over time together with those of their peer frame. Favara (2017) was able to show that the aspirations of children and adolescents mirror those of their parents and that these are revised over time to adapt to social expectations.

Likewise, exposure to people outside of our immediate social network can have a positive impact on aspiration formation. With reference to Bandura, Bernard et al. (2014) discussed the relevance of role models in the formation of an individual’s perception of what is feasible in their environment; for instance, through the construction of mental models and choice sets. Role models have to be people with whom we can identify socially and whose stories produce a vicarious experience that generates emotions strong enough to spur a willingness in us to change our status quo. By providing new information about what can be achieved in the circumstances we find ourselves, role models update our beliefs and change aspirations and motivations for the better (Lybbert and Wyddick, 2018; Bernard et al., 2014; Beaman et al., 2012; Chiapa, Garrido and Prina, 2012; Nguyen, 2008; Bandura, 1977).

Bernard et al. (2014) and Riley (2018) both tested the effect produced by the exposure of adults and secondary school children to relatable role models and found a relationship wherein they positively affect behaviour. For Bernard et al., adults change how they allocate time in response to aspirational changes; for example, less leisure time means more time at work and increased investment in the education of children. In Riley’s study, Ugandan secondary school children performed better in a mathematics exam after exposure to positive role models.

If new information about what can be achieved in the system in which we live is important, so too is our perception of that system. The study by O’Higgins and Stimolo (2015) provides an example. Using two-shot trust games with random, anonymous matching, they were able to demonstrate that trust is lowest when confronted by unemployment or precariousness and that it varies across job market structures. Bernard et al. (2014) found the same phenomenon, namely, a large proportion of poor, rural households in Ethiopia exhibited signs of holding fatalistic beliefs and having low aspirations and low self-efficacy. Poverty, precariousness and other strenuous circumstances and their opposite, relative richness and safe environments in which to live (Knight and Gunatilaka, 2012; Stutzer, 2004), certainly affect the type of future-oriented behaviour we choose, through the impact they have on our perception of the choices available to us and our ability to contest or alter the circumstances in which we find ourselves (Favara, 2017; Dalton, Ghosal and Mani, 2016; Appadurai, 2004).

Schoon and Parsons (2002) demonstrated this by looking at the effect the relevance of educational credentials had on two different cohorts’ aspirations and adult occupational outcomes. They found that when the socio-historical context makes academic credentials more relevant for employment, the younger generation raises its academic aspirations and consequently has better occupational outcomes. Echoing these results, Lowe and Krahn (2000) compared two Canadian youth cohorts and found that occupational aspirations increased in the later cohort to match the opportunities presented by trends in the country’s service-based economy.

Finally, some studies suggest that early interventions are desirable for raising expectations and aspirations. Gorard, See and Davies (2012) documented a series of studies looking at aspirations and expectations, stability over time and effect on educational outcomes. For example, Goodman et al. (2011) found that expectations reported at age 14 were the best predictor of the score gap between low- and high-income students and therefore encouraged policy-makers and education workers to start raising students’ aspirations as early as primary school level. Lin et al. (2009) found that expectations reported in grade seven (approximately age 12) were positively correlated with academic progress in grade eleven. In the same vein, Beal and Crocket (2010) and Liu (2009) observed self-reported aspirations from grade seven to nine and from grade ten until the end of high school and found they remained mostly stable and were reliable predictors of educational outcome. However, knowing that aspirations appear to be formed during early adolescence does not preclude programmes from targeting older youth cohorts. On the contrary, this finding suggests that aspirations are constant motivators in life and should be approached early and continue to be engaged throughout the life course.

3.3 The malleability of aspirations through policy interventions

As our understanding of aspirations in the context of policy and development improves, we see research gradually turn from aspiration formation to how to increase aspirations. Natural and field experiments centred on the concept of aspirations and the individual’s ability to imagine a brighter future for themselves have important implications for policy. Mainly, they demonstrate that the success of policy efforts can be partially secured by engaging the people who they directly affect.

Perhaps the most famous natural experiment on the topic, undertaken by Beaman et al. (2012), used a gender quota policy in West Bengal to illustrate how exposure to positive role models raises educational and career aspirations and improves outcomes for young girls. In 1998, state policy-makers introduced a gender quota for village councils. Some villages were asked to reserve at least one seat for women, some at least two seats; other villages were asked not to reserve any seats at all. Thanks to this design, Beaman et al. were able to study what happened to the cohorts of girls exposed to councilwomen in their villages compared to those who were not. From the time of implementation in 1998 until the first round of data collection in 2007, they observed that exposure to women role models increased primarily the occupational aspirations of the adolescent girls and their parents, with fewer parents wanting their girls to be housewives, and improved educational outcomes.

Both Chiapa et al. (2012) and García, Harker and Cuartas (2016) designed field experiments in which they combined a social programme with exposure to career role models and social leaders. Chiapa and co-authors observed what effect a Mexican conditional cash transfer programme, PROGRESA, had on educational outcomes. They were able to demonstrate that PROGRESA, as a social programme, raised the aspirations of parents for their children for at least one-third of a school year. When comparing persons who had received the cash transfer and were exposed to health-care professionals, Chiapa and co-authors found that educational aspirations extended for half a school year longer than it did among those parents who had received the cash transfer but were not exposed to role models. They also found a positive correlation between parental aspirations and students’ educational attainment (Favara, 2017; Chiapa, Garrido and Prina, 2012).

García, Harker and Cuartas (2016) observed the effect a conditional cash transfer programme, Familias en Acción, had on the educational aspirations of parents and adolescents. They found that the improvement in educational outcomes after the transfer can be partly explained by the increase in aspirations achieved through the exposure of beneficiary parents to social leaders and professionals who shared with them information about local returns to education and the other benefits of schooling. Glewwe, Ross and Wydick (2015) also found that combining a mechanism that relaxes financial constraints with exposure to role models enhances both aspirations and educational attainment rates. Through a child sponsorship programme, they showed that a role model’s impact is greatest in the early stage of exposure. Similarly, Wydick, Glewwe and Rutledge (2013, 2017) found that a child sponsorship programme not only increases participants’ educational attainment, but also enhances their labour market outcomes, measured as the probability of obtaining while-collar employment in adulthood.

In another natural experiment, Kosec and Hyunjung Mo (2017) documented what happens to aspirations when confronted by a natural disaster (i.e. extreme rainfall). As expected, natural disasters have the effect of abruptly changing the perception of safety in the environment and lower aspirations. However, they also found that government social protection programmes can blunt the negative social effect of natural catastrophes. Their study is evidence of the crucial role the state has to play in first shaping and then maintaining a positive outlook on our environment and the circumstances in which we find ourselves.

Another is the study by Ross (2016) of the National Rural Employment Guarantee Act (NREGA) programme in India. Initiated in 2006, the NREGA programme guarantees poor households one hundred days of salaried, low-skill employment in any financial year, should they want it. The stability this provides raised the aspirations of parents and adolescents and is associated with higher educational attainment and an increased probability of being employed full time.

Bernard et al. (2014) and Macours and Vakis (2014) designed experiments to observe the effects (i.e. social network effects) peers have on aspirations and outcomes. The one carried out by Bernard et al. (2014) focused on enhancing the aspirations of microcredit borrowers through exposure to role models via a video documentary. This was shown to enhance both the level of aspirations and actual, future-oriented behaviour (such as saving, and time spent on leisure and work). Interestingly, they found that positive peer dynamics (peers included friends, spouses, and so on) further boosted the positive effect of the video. In their turn, Macours and Vakis (2014) chose to observe the effect of social interactions on aspirations by randomly assigning leaders and beneficiaries to lending groups in a microcredit scheme. They found that positive peer dynamics, promoted by more optimistic group leaders, promoted a positive outlook on the future and the probability of on-time repayment.

Judging from the insights generated by the natural and field experiments described, there seems to be a consensus that it is possible to manipulate the conditions under which aspirations are shaped and that the aspirations of individuals matter equally as much for successful policy and social programmes as they do for life outcomes.3 When policies assist in aligning individuals’ educational and work aspirations with the pathways to achieving them, they are more likely to be successful than when such aspirations are ignored. For example, programmes that provide experiential information on how to integrate into the labour market plus a financial aid scheme are more likely to elicit a positive response from the target population than programmes that do not. Programmes tend to miss their mark when they fail to acknowledge that resource scarcity is sometimes more than just financial but can also be a lack of the type of social experiences that help recipients visualize the ways in which financial resources can be put to good use. Labour market policies thus benefit from a holistic design; one that includes role models (who generate vicarious experiences) in combination with skills development and other career supporting interventions (e.g. financing schemes).

Based on insights from the literature and building on the conceptual framework developed by Boateng and Löwe (2018), Figure 3.1 encapsulates the determinants of aspiration formation: lived experiences (own and vicarious) and social context shape aspirations, both the commonly held aspirations shared by the larger age related cohort and those of the individual embedded therein. When the aspiration gap is too large, aspirations are no motivator of change, and there is the likelihood of aspirations frustration. If the gap is too small, there will be a failure to aspire to a significant change in life. When realistic aspirations combine an individual’s sense of agency and belief that change can be brought about through their own effort with the pathways and tools in support of that individual to achieve, success can be the outcome.

Figure 3.1: Developing and achieving aspirations

Labour market challenges and youth aspirations

Career aspirations typically drive individuals’ educational and occupational choices (Duncan et al., 1968; Ohlendorf and Kuvlesky, 1968; Kuvlesky and Bealer, 1967) and vice versa. Career aspirations are influenced by the immediate social context through the own or vicarious experiences acquired from peers, parents and successful role models (Bernard et al., 2014; Bogliacino and Ortoleva, 2013; Bandura, 1977).

In addition to financial remuneration, people aspire to various non-monetary elements related to work, including a healthy work–life balance, social protection, career development and flexibility. Labour market conditions and labour market trends can affect each of these components.

4.1 Labour markets and aspirations: conceptual framework

Career aspirations are influenced by the immediate social context, through own experiences or vicarious experiences acquired from peers, parents and successful role models (Bernard et al; 2014; Bogliacino and Ortoleva, 2013; Bandura, 1977).

4.1.1 Dimensions of occupational aspirations

Given the many differences in experiences, in availability of role models and in social norms and (local) labour markets, aspirations necessarily differ considerably across and within regions and countries (across rural and urban settings), and even between individuals across the different stages in life. Boateng and Löwe (2018) have described how in rural communities in Ghana, where the cocoa crop is regarded as the pride of the country, cocoa farmers are the most highly respected professionals, whereas in urban areas, respect is reserved exclusively for office workers and white-collar professionals. They also showed how aspirations change over the life course. They noted that most young people earn a living from doing ad hoc jobs: “The priority for most young people is to make ends meet and to be seen to be contributing to their immediate and extended families’ well-being and upkeep. In other words, the earning potential of various tasks and jobs was the key consideration for most young people.” This enables them to build up some savings in the medium term in order to raise a family. But for the longer term, they aspired to jobs that are less physically demanding, once passed middle age (Boateng and Löwe, 2018).

This example demonstrates that what people value about a job, and what they may realistically aspire to in the short, medium and long term, has many dimensions. An important one – if not the most important – is the financial remuneration for the work undertaken. Earning a decent income is what enables young people to develop aspirations for the longer term, such as raising a family, building up emergency savings and supporting the family’s well-being. However, besides financial rewards, other job characteristics and personal occupational preferences come into play: namely, the extent of social protection, the work–life balance, job flexibility, an aspired to technical skill level and learning opportunities, the presence of labour union representation, income stability and, last but not least, outspoken preferences for work in certain sectors (public or private; wage or self-employment; agriculture, manufacturing or services). What it is exactly that young people worldwide aspire to and find important in a job is an empirical question and varies according to individual preferences and the socio-economic and institutional environments in which they live.

4.1.2 Labour markets and realistic aspirations

The framework conceives three levels of aspiration – low, realistic and high – for a given set of skills. As previously discussed, aspirations and action can be seen to follow an inverted U shape, where realistic levels of aspiration are at the top of the arms of the U and most conducive to successfully aspired to outcomes.

Figure 4.1 Aspirations and labour markets

In figure 4.1, the diverse set of aspirational dimensions for a given set of skills is represented by the arrows. Each arrow represents a particular dimension (income), and aspirations can range from low to realistic to high. Individuals may develop strong aspirations in one particular dimension and weaker ones in another. To demonstrate the links between the different dimensions, take for instance, a person who is hoping to have an enjoyable work–life balance: their aspired to salary may be a little lower than for career-driven young people, for whom salary and career development goals will be strong but with less of a work–life balance. How people prioritize different aspirational dimensions is partly determined by preferences and socioeconomic environment and, again, the labour market.

Local labour market conditions influence the range of realistic aspirations and successful labour market outcomes, as represented by the darker colour (see figure 4.1). Yet, labour market conditions alter in response to the technological, social and economic forces that shape supply and demand, thereby shifting and potentially increasing or decreasing the range of realistic aspirations available. Technological change influences how production factors, such as capital and labour, relate to each other and determines the skills required from workers. Automation and robotization may replace workers with machines and drive low-skilled workers and increasingly medium-skilled ones out of the market, thereby decreasing the likelihood that low- and medium-skilled people will find another job, earn a decent income and work at the technical level to which they aspire. Hence, labour markets that are more challenging affect how large is the range of aspirations that individuals are likely to achieve.

Along with technological change, social forces may shape labour market conditions. A minimum wage structure, social protection and employer–employee relationships are largely the result of labour market policy interventions targeting the challenging evolutions in the labour market. Labour markets that are more flexible can fuel the aspirations of people who want to combine jobs with study, family or life quality, but they can depress aspirations in, say, the dimension of social protection or career development.

Hence labour market forces and labour market policies jointly determine how narrow or wide is the range of realistic aspirations for any given skills set. A limited range can motivate people to engage in education and skills development in order to open more perspectives, feeding into new future aspirations.

4.2 Labour market trends and their implications for aspirations

There are currently various labour market trends with the potential to affect aspirations. In particular, technological change, instigating robotization, automation and an increasing use of information and communication technology (ICT) in the workplace, is leading to non-standard forms of employment and new employer–employee relations. This may have many implications for what can realistically be aspired to in the various aspirational dimensions, including social protection and job flexibility. These evolutions in the labour market and their implications for aspirations are discussed in brief below.

4.2.1 Non-standard forms of employment

Over the past decades, one of the most prominent features of global labour markets has been the growth in non-standard forms of employment (NSE) (ILO, 2016). In contrast to nine-to-five wage work, NSE incorporates (1) temporary employment, (2) part-time and on-call work, (3) multi-party employment relationships and (4) disguised employment and dependent self-employment (ILO, 2016).

This evolution clearly broadens possibilities in terms of job flexibility or work-life balance, but narrows expectations for young people who aspire to a full-time wage job providing a decent and stable income. For most workers, employment in NSE is accompanied by job insecurity and even working poverty. In many low-income countries, NSE has come to dominate the labour market in the form of informal employment or employment in informal sectors.

Own-account workers (self-employed without employees) made up over a third of all global employment in 2018 (ILO, 2019). Surveys show that in Europe individuals who are self-employed are often motivated to be so for positive reasons, such as autonomy and a better work–life balance, and that they are generally well remunerated. However, there are also negative motivations driving people into self-employment; increasingly, employers like to work on an ad-hoc basis with professionals who are self-employed in order to flexibly match the size of their workforce to the business cycle in anticipation of fluctuations in demand (Eurofound, 2018).

Hence, non-standard jobs are also associated with increased fragility and precariousness. They are hit hard by negative demand shocks and may not benefit equally from the social security system, including pension and unemployment benefits, and they tend to be found amoung youth in particular (O’Higgins, 2017; Chandy, 2017; Bruno et al., 2014; Gontkovičová et al., 2015). Being in NSE reduces the possibility of receiving on-the-job training and gaining from professional guidance, which can have a negative effect on career development (ILO, 2016). In addition, young workers who are informally employed have a higher risk of being in and out of employment, which could discourage them aspiring to a higher employment achievement (Beyer, 2018). In some cases, hardship for youth in entering job markets and securing stable employment may lead to frustration and drive them into being inactive (Arpaia & Curci, 2010).

4.2.2 Technological change and demand for work

The influence of technological change on the demand for labour and its impact on the aspirations of youth is another cause for concern. Technological change may entail automation, replacing people by machines. Concern about robotization and automation was at the centre of academic and policy debates following the publication of Frey and Osborne’s (2013) influential paper revealing that around 47 per cent of 702 occupations examined in the United States are at risk of replacement by computerization. Subsequent research, mainly in OECD countries, has confirmed what Frey and Osborne found, but gone on to demonstrate that technological advance may also create a considerable proportion of new occupations for the young. “Jobs at risk” should not therefore be equated to expected net employment losses, because the adoption of new technologies is a slow process, so not all the “jobs at risk” will disappear in the short term. Workers thus may have time to adjust to the changing labour environment by switching tasks and educations while new technologies progress and diffuse.

Irrespective of its potential magnitude or speed of impact, “skill-based technological change” is certain to alter the set of employable skills needed in the future. The massive use of computer-controlled machinery has tended to make workers performing routine manual tasks redundant (Autor, Levy, & Murnane, 2003). The US and UK labour markets have polarized, with growing employment in high-tech, high-income jobs, on the one hand, and low-income manual jobs on the other hand (Goos, Manning, & Salomons, 2009). Displacement is no longer a concern for medium-skilled employment only, but is also moving into the higher skilled employment segment (Autor, 2015). Jobs are increasingly tending to have cognitive, interactive and ICT-components. Therefore, highly skilled workers in complex fields will be more capable of getting secure employment (Castro Silva & Lima, 2017; Lowry, Molloy, & McGlennon, 2008). Youth that lack ICT or technology-related skills could be penalized in future labour markets. Especially the manufacturing sector – the traditional springboard for youth career transitions in developing and middle-income countries – which might not be able to offer sufficient positions to youth lacking ICT skills.

Additionally, the impact of technology on jobs and workers will be clearly uneven across countries. It will depend on a country’s level of development, its adaptation to new technologies and how well the labour force is prepared for the changes technology brings (Acemoglu & Autor, 2011; ILO, 2017a). Through foreign direct investment, technology diffuses rapidly. For a limited time, young labour market entrants in less developed countries might remain exempted from the influence of frontier technology, but they will need to adapt to the technology-driven world eventually (ILO, 2017a). In South Africa, for example, the IT-enabled services sector is growing fast, providing jobs for an increasingly large pool of medium-skilled workers conducting business processing services, such as administrative, legal and after sales services for large foreign customers’ firms (Keijser, 2019). In Ethiopia, evidence shows that foreign firms have increasingly sought skilled workers, but where export activity is involved there was a higher demand for unskilled workers, due to the country’s comparative advantage still being its low-cost labour (Haile et al., 2017). More jobs is desirable for a country with a youth bulge ready to enter the labour market, but the effect of technology on occupations’ skills and wages may differ between countries and may serve to either reduce or reinforce social exclusion for disadvantaged youth. These evolutions will ultimately be reflected in the beliefs, experiences and social networks of the young people developing aspirations, and hence influence what can realistically be achieved by young people equipped with a particular skills set.

4.2.3 IT-enabled opportunities and social protection

Technological change has also spurred the expansion of a range of more flexible working arrangements. Especially digital innovation decentralizes the unit of economic activity from corporations to individuals, affording workers more chances to participate in labour markets as entrepreneurs (Chandy, 2017).

The growing gig (platform) economy is fuelling the growth of various types of flexible employment and self-employment (De Stefano, 2016; Katz & Krueger, 2019). This may take the form of crowd work, whereby work is posted on Internet platforms to the “crowd” and customers and contractors can then manage it through either a digital platform (ILO, 2019) or “work-on-demand via apps”, with examples such as Uber, Airbnb, TaskRabbit. This may serve to free people from geographical restrictions and create more flexible job opportunities for all.

Nevertheless, this all comes at the risk of weak social protection related to NSE, as described above (Smith & Leberstein, 2015). The growing group of “platform workers” is not contractually employed by customers, so their status is one of legal uncertainty in the labour market. The flexibility of employment can be a sword that cuts both ways; it grants working autonomy but can also isolate workers and weaken their bargaining power (Codagnone, Abadie, & Biagi, 2016). In the long run, the platform employment may endanger income stability, increase unemployment and exclude workers from social security coverage.

The heterogeneous effects of technological change on global labour markets creates uncertainty for the future of work, which brings more challenges to the youth of today than previously experienced by their parents’ generation. As indicated in the preceding section, young people are starting careers in diverse forms of unstable and insecure employment (ILO, 2017a). Meanwhile, while young people still associate the ideal job with aspects of more traditional forms of employment, such as a good salary, career development opportunities and social protection, they are also increasingly open to greater flexibility in their job and a good work–life balance. In many parts of the world, the gap between career aspirations and labour market reality is widening, to a point that it may hurt young people’s chances of employment. A recurrent issue is youth in developing countries aspiring to a decent formal job in the public sector where job offers are in decline, often leading to unemployment, as seen in a study on Ethiopia (Mains, 2012). Therefore, in order to help youth mobilize their aspirational strength, we need to better understand their aspirations in life and at work. This includes what they value most in their work, what they aspire to for the future and how these aspirations can be aligned with future job or career development perspectives through policy interventions that help them develop the right skills set for the aspired to positions and which cushion labour market shocks. This calls, in the first place, for a survey of the existing empirical evidence of (drivers of) aspirations of youth around the world to help identify evidence gaps and contribute to the development of better evidence-based labour market policies.

Measuring youth aspirations in the world of work: an overview of existing surveys and indicators

Recent surveys focusing on youth (or sub-populations of youth) have included questions about aspirations or goals for the future, about what they value in a job or career, and about their beliefs and worldviews. While these surveys did not have as a primary objective collecting evidence of youth aspirations in the labour market, many touch on particular aspects or dimensions of youth (career) aspirations. They are therefore a good starting point when considering the methodologies applied so far and for bringing together for a first time in a systematic overview the evidence on youth aspirations.

Subsection 5.1 provides a brief overview of the surveys selected, drawing on the information presented in Appendix A. Subsection 5.2 describes how the surveys have been operationalized according to aspirations, expectations, or beliefs or values that contribute to shaping or driving aspirations. Detailed examples of questions taken from different surveys are presented in Appendix B as illustrative of the similarities and differences between the survey instruments reviewed for this study. The next section (section 6) presents the evidence.

5.1 Data sources: discussion of data sources, coverage, target groups

Eighteen surveys were identified with relevant indicators for various dimensions of youth (labour market) aspirations. The surveys selected have all been conducted within the last ten years and many within the last three. They do, however, differ widely from one another and this makes comparisons sometimes difficult. For instance, the number of countries covered, the number of respondents and the mode of delivery varies considerably between surveys. Modes of delivery include online, SMS messaging, face-to-face surveys and Computer Assisted Personal Interview (CAPI). Surveys that use the Internet to collect responses are able to reach respondents in more countries than otherwise.

To give a brief overview, Figure 5.1 plots the country coverage and number of respondents. Where a survey is thought to have been conducted only online, then the data point is represented by a blue circle. Where the survey has been conducted via other means (e.g. in person or via telephone or SMS messaging), perhaps in addition to online delivery channels, the data point is represented by a blue diamond.

Figure 5.1 Sources of data: country coverage and number of respondents

Note: ASEAN Transform: ASEAN in Transformation; PwC: PricewaterhouseCoopers; SWTS: School-to-Work Transition Survey. This figure does not include all the surveys; for example, the preliminary report for the Youth Speak Survey conducted by AIESEC reports neither the number of countries nor the mode of survey delivery.

Source: Authors’ elaboration, based on information provided in the reviewed reports on the number of countries and respondents.

The most important difference between the surveys selected is the target population. A majority targets youth populations, but the exact age range varies; indeed, some even target entire populations, including adults. The population surveyed is often further restricted beyond just the target age range. Restrictions may occur by default; for instance, due to the channels or modes of delivery by which a survey reaches potential respondents. For example, the ASEAN Youth and Future of Work survey (see more details in Appendix A, table 2) collected responses via online e-commerce or gaming platforms. Restrictions are explicit when the survey’s declared aim is to solicit responses from youth with specific characteristics (i.e. students); for example, Deloitte (see more details in Appendix A, table 5) surveyed millennials with a university degree who were employed full-time (mostly in large, private sector companies).

Both these types of restriction are potential sources of bias, if the idea is to generalize about the entire youth population (or all millennials),4 and limit our ability to compare the evidence across surveys. The opinions held by millennial respondents to Deloitte’s survey about the impact Industry 4.0 might have on their jobs, could systematically differ from those of millennials with no university degree and who are unemployed. Online e-commerce and games platform users may be systematically more optimistic (for example) about whether technology is likely to increase jobs than youth without access to the Internet. Clearly, the findings of such studies are only representative for the more restricted population of youth targeted.

A study by the United Nations Development Programme (UNDP) (see more details in Appendix A, table 15) set up 64 polling sites to interview youth in Armenia, aiming to yield a nationally representative youth sample. This was the sole study we found where a nationally representative sample was obtained. The World Values Survey collects responses from 60 countries and has made strenuous efforts to obtain a representative sample of each country’s population, but it does not exclusively target youth. Results from the World Values Survey can be filtered by age group to ascertain the responses by youth (aged 18–29). This feature might be useful in some cases, for example, to compare how youth feel about a particular topic with respect to other age groups, but a potential downside is that the questions and survey instrument are not specifically tailored to young people.

In Appendix A, table 1 through table 18 summarize information about the year the survey was conducted, the number of countries, the target age group, number of respondents and restrictions (by default or explicit) on the sample population. Each table includes a statement describing the objective of the survey; a statement describing the mode of survey delivery; and a short discussion about the survey’s respondents. The sources of information used to describe each survey come from either the survey itself, the documentation supporting the survey or reports written about the results of the survey.

5.2 Indicators of work-related aspirations

This subsection discusses the operationalization of indicators with reference to the specific questions put to respondents by the different surveys (presented in Appendix B.). Questions are classified into question groups, depending on the dimension measured (ability, beliefs/perceptions, desire/values, drivers and perceptions thereof, e.g., labour market perceptions), as discussed in the literature.

The state-of-the-art in terms of the current theoretical and empirical literature on aspirations has been covered earlier by section 3. Naturally, concepts must be operationalized in order to be measured in social science research.5 Therefore, in the review of survey questions that measure aspirations, the distinction between different dimensions of aspirations has been isolated and amplified. In theoretical section 3 above, aspirations are characterised as “the personal desires of individuals (preferences and goals), their beliefs about the opportunities available to them in society (opportunities and pathways) and their expectations about what can be achieved through their own effort in an uncertain future (self-efficacy and agency)”.

We identify survey questions that tackle the first dimension, which we call the “goal dimension of aspirations”, including career goals and the related “desired values and characteristics of jobs (or careers)”. “Expectations” are defined as a concept related to aspirations, in that it combines goals and preferences, on the one hand, with pathways and agency on the other. We identify questions that fit this description. We further identify questions assessing pathways and opportunities, or a lack thereof, by selecting those questions that ask for “perceived obstacles to achieving aspirations”. We distinguish between these perceived obstacles from perceptions and beliefs about technology, and from general perceptions about the world.

We were unable, however, to identify in the above mentioned surveys any questions that could be used as a measure of “self-efficacy and agency”.

5.2.1 The goal dimension of aspirations

In accord with the notions set forth in section 3 based on the theory of hope, we have classified the questions in Appendix B, table 1 as ones that operationalize the aspired to goals. Many of the questions are phrased in a way that asks individuals about their preferences or ideal sector of work or type of organization as an occupational or career aspired to goal.

Response choice varies between surveys. While many ask young people similar questions about their preferred sector of work or job, the response choices yield different kinds of information. For example, some surveys offer relatively broad responses categories for preferred sector of work, while others classify sectors in a more detailed way. To illustrate this variation, Appendix B presents the response choices in table 2 that correspond to the questions presented in table 1.

The desired/preferred job characteristics dimension is closely linked to the aspirations literature stating that aspirations capture the personal preferences of individuals (along with beliefs about the opportunities available to them in society, and expectations as to what can be achieved through their own effort in an uncertain future). In the context of work, this translates into survey questions which ask youth about what characteristics their ideal jobs would have (or similar phrasing). We assume this to be an underlying driver leading young people to form aspirations of working for a particular type of organization, or in a particular sector, hence preferred job characteristics and aspired to goals are interlinked. See Appendix B, table 3 for examples of survey questions related to a respondent’s desired or preferred job characteristics.

5.2.2 Expectations

As explained earlier in section 3, when what we aspire to for our future (aspirational goals) is aligned with what we believe can be achieved given the right circumstances (opportunities), and through your own effort, aspirations become analogous to expectations. Most of the questions in Appendix B, table 4 actually contain the word ‘expectations’ in relation to career goals, or ask respondents what they think will take place.

By asking youth about perceived obstacles to getting a job, answers reveal perceived limitations or constraints to achieving the goal of getting a job, reflecting a perceived lack of opportunity. In the context of youth and the future of work, this question may serve to highlight an important gap between aspirational goals and successful outcomes.

Youths’ assessment of the value of education, apprenticeships and particular labour market opportunities might also have an affect on aspirations achievement. Examples of survey questions that operationalize this notion are presented in Appendix B, table 5.

5.2.3 Perceptions/beliefs about technology

There is a fierce debate and a wide range of opinions regarding how new technologies are likely to affect employment opportunities. These range from a deep fear that jobs (or tasks within jobs) will be destroyed to a more general technological optimism that, ultimately, new technologies will create new jobs. Digitalization, automation and robotization are predicted to change the very nature of how we work. This is an important issue for all groups of people, but perhaps of most concern for today’s youth, who are either new to or entering the labour market. That said, young people have been exposed to some of today’s technologies from a younger age than older generations and may be more comfortable and competent with technology and therefore not feel as threatened by these new technologies as perhaps are older generations (see the earlier discussion in subsection 4.3). Examples of survey questions asking youth about their perceptions regarding technology and its implications are presented in Appendix B, table 6.

5.2.4 General perceptions/beliefs about the world

Appendix B, table 7 highlights examples of survey questions capturing general perceptions about the world and future possibilities that might help shape aspirations. The framework developed earlier in subsection 3.3 describes how aspirations are developed and achieved and how lived experiences and social messages and beliefs feed into aspiration formulation.

Youth aspirations and the world of work: Global evidence

The global trends in young people’s career aspirations as revealed in the data are discussed in this section. Indicators of aspirations or sub-dimensions thereof (specifically, perceptions of labour market challenges, most valued characteristics of a job) are presented and then data is compared by region and by gender.

Data from the Global Shapers Survey is used as a basis for the analysis. The Global Shapers Survey targets young people (aged 18–35) and has one of the most extensive country coverages (191 countries) from among the surveys reviewed for this report. In total, there were 24,766 respondents. Responses were collected via online and offline channels, together with some workshops designed for a wider range of respondents. However, despite attempts to increase its reach, the Survey makes no claim to representativeness. The Survey collected background information (including on gender) and grouped questions into themes such as “values, outlook, and workplace”. The data also contain information about a respondent’s region. For these reasons, the data from this survey was used to explore the sub-dimensions of aspirations, together with expectations and the perceptions of youth regarding whether technology is likely to create or destroy jobs in the various regions around the world.

6.1 Regional trends

Figure 6.1 presents data from two important sub-dimensions of aspirations, namely desired/valued job characteristics and perceived obstacles to job prospects. Young people were asked: “What are your most important criteria when considering job opportunities?” and “What are your biggest concerns about your job prospects when you apply for a new job?” Respondents were allowed to choose up to three of the answers listed. Responses are disaggregated according to gender.

In Asia, salary and financial compensation is ranked first by young women in this region, whereas growth and career advancement ranked top for young men. Women value the opportunity to travel internationally more than do men and young women and men both have lack of experience and too much competition as their two biggest concerns when applying for a job. But, a greater percentage of young women indicate discrimination by employers as being a concern than do young men.

The most striking finding for Europe and Central Asia is that, in contrast to every other region in the world, youth did not rank salary and financial compensation as the most important criterion for a job. More young women identified sense of purpose and impact on society together with work–life balance as being more important than salary and financial compensation when considering a job. More young men chose salary and compensation, but sense of purpose and impact on society ranked second. Like their counterparts in Asia, young men and women in Europe worry about lack of experience and too much competition. In Europe, more women than men cite discrimination by employers and not enough jobs as concerns.

In North America, similarly to Europe, more young women than young men nominated sense of purpose and impact on society as important to them, but in North America a greater proportion of young women cited flexibility and autonomy as important. Consistent with other regions, young men and women both worry about lack of experience and competition, but more also identify lack of social networks and luck as factors when applying for jobs.

In Latin America and the Caribbean, salary and financial compensation and growth and career advancement topped the chart for young women and young men alike, but greater proportions of women chose sense of purpose and impact on society and flexibility as of importance. While lack of experience and competition are again the biggest concerns, many more youth nominated there being not enough jobs as a major concern than in other regions.

In Middle East and North Africa, while salary and financial compensation and growth and career advancement ranked top for both young women and young men, a larger proportion of women valued a work–life balance, which is not surprising considering household duties tend to be assigned to women in this region. Both young women and young men cited discrimination by employers as the biggest concern when applying for jobs. This may be gender discrimination or segregation, following the observation that particular jobs are reserved for particular sexes. Furthermore, both young women and men indicated that there are not enough jobs available.

In Sub-Saharan Africa, a large proportion of young men cited training and development as the most crucial criteria when considering job opportunities and discrimination by employers as a major concern, while women cited “sense of purpose” as the third most desired job characteristic. All youth in every region were most worried about lack of experience when applying for jobs, and in sub-Saharan Africa it is no different.

Figure 6.1. Top five valued job characteristics and concerns in job applications amongst young people (18-35 years), 2017, by region

Sources: Own elaborations based on Global Shapers Survey (2017).

Notes: Respondents could select up to 3 out of 10 responses, hence totals do not add up to 100 per cent. The 11 responses for “Most important criteria when considering job opportunities” were (i) company culture/quality of colleagues (ii) dynamic and growing enterprise, (iii) product/service quality, (iv) opportunity to travel internationally, (v) reputation of company/social status, (vi) flexibility/autonomy (working hours, location), (vii) work-life balance, (viii) training and development, (ix) sense of purpose/impact on society, (x) growth / career advancement, (xi) salary/financial compensation. The 11 responses for “Biggest concerns about job prospects when applying for a job” were (i) lack of language skills, (ii) lack of presentation/soft skills, (iii) luck plays a big role, (iv) geographical constraints, (v) good jobs don’t get advertised, (vi) lack of friend/mentor network, (vii) not enough jobs, (viii) lack of right education/skills, (ix) discrimination by employers, (x) too much competition, (xi) lack of experience. Respondents from East Asia and the Pacific and South Asia have been combined in panels showing Global Shapers Data

To summarize the findings from this analysis: if we plot the percentage of youth who selected salary and financial compensation as one of the three most important criteria when choosing a job by the level of human development in their country, an inverse relationship can be seen. That is, the lower the human development index, the greater the proportion of youth who nominate salary as one of the three most important criteria when considering a job opportunity.

We can contrast this relationship with the inverted U-shaped relationship found when opportunity to travel internationally is plotted by human development category. In the lowest and highest human development categories, international travel is cited less often than it is in countries in the mid-to-high range of human development. This finding accords intuitively with a hierarchy of needs perspective: once financial needs are met, other interests and needs can begin to emerge. In countries with the highest level of human development, there may simply be less incentive to travel abroad to seek opportunity.

Figure 6.2. Different important job criteria, by human development category

Source: Own elaborations based on Global Shapers Survey (2017)

Notes: The y-axis is different in each panel, although both span 5 percentage points, there is a far greater proportion of respondents (in all human development categories) who selected ‘Salary / financial compensation’ as one of the three most important job criteria. This would be evident from studying figure 6.1 above.

6.2 Technological change and jobs

The Global Shapers Survey, like many other surveys reviewed in this report, asks young people about their perceptions regarding whether technology is creating or destroying jobs. Figure 6.3 gives a regional overview of responses to the question: “In your opinion, technology is…”. Possible answers were: creating jobs, or destroying jobs, or NA.

Figure 6.3. Perceptions of the influence of technology on job creation, 2017, by region (18-35 years)

In Asia, youth were overwhelmingly positive about technology creating jobs, which supports evidence found in other surveys conducted in countries in the ASEAN region. In Europe, youth are much less optimistic about technology creating jobs than their counterparts in Asia and North America. The only other region where only 60 per cent of youth believed that technology is creating jobs is sub-Saharan Africa. The youth most optimistic about technology creating jobs are in North America. In Latin America and the Caribbean, a relatively high percentage (70 per cent) of youth in the region believed the same. In the Middle East and North Africa region, 66 per cent of the youth were optimistic that technology is creating jobs.

It is possible that differences might arise, because of the different age groups surveyed; considering the rapid rate of change of today’s technology, the age range across the surveys selected (18–35 years of age) spans a long time-horizon. Nevertheless, generally speaking, there was not too much difference between 5 sub-age groups with regards to the opinions they held about whether technology is likely to create or destroy jobs. Interestingly, the youngest sub-age group (18–21 years of age) had the smallest fraction of respondents (64 per cent) that thought technology creates jobs. In fact, the results for ages 27–30 were exactly the same as for ages 31–35 (68 per cent thought that technology creates jobs). Ages 22–26 were almost as optimistic (67 per cent).

Making use of the background information collected by the Survey, we explored further how the answers about technology changed depending on employer or sector of employment in figure 6.4. Only 60 per cent of young people who were unemployed believed that technology is creating jobs, whereas 71 per cent of people working for either non-governmental organizations (NGOs) or international organizations believed this to be true. There is no marked difference apparent between unemployed youth and other youth who are employed in different sectors as regards the opinion they hold about this question. It is important to note that there are fewer respondents who are unemployed vis-à-vis the number of respondents who are students or working in the private sector, so we ought to be cautious and not draw too strong conclusions about unemployed youth.

Figure 6.4. Young people’s opinions about whether technology is creating or destroying jobs, by employer or employment/student status, 2017 (18-35 years)

Source: Own elabouration based on Global Shapers Survey (2017)

Using the World Values Survey, in figure 6.5 we juxtapose the viewpoints of people regarding whether the world is either better or worse off because of technology with the percentage of respondents who had never used a personal computer. The map in the left-hand panel illustrates survey respondents’ sentiments as to whether the world is better off because of science and technology. The response scale was from 1 (a lot worse off) to 10 (a lot better off). The lowest mean for any given country is a 5.87 and the highest 8.87. Most countries are in some shade of yellow to green, indicating a country mean of 8 or above. So, generally speaking, people are quite positive about the world being better off because of science and technology. The map in the centre panel is about how frequently respondents used a personal computer. Countries in green had among the highest proportion of people who had never used a personal computer; the maximum was in Zimbabwe, where this was true of 72.4 per cent of respondents. Countries in red had a very small proportion of people who had never used a personal computer; the smallest was in the Netherlands, where it was true of only 1.7 per cent of respondents. The right-hand panel shows a scatter plot for these two indicators. Clearly the range of responses for perceptions regarding science and technology is far smaller than the one for the percentage of respondents who have never used a personal computer. The correlation between the two indicators is very low, almost zero (0.04).

We ran a similar exercise for the percentage of respondents who said that their job was mostly manual and found that for those countries where respondents’ job tasks are mostly manual there is a 0.3 correlation with the perception that the world is better off because of science and technology. This is still a relatively low correlation coefficient, but not as negligible as the correlation between use of a personal computer.

As an illustrative example, let us consider India. Despite the fact that the vast majority of respondents in India considered the world to be better off because of science and technology, 59.3 per cent reported that they have never used a personal computer, and almost 18 per cent indicated that the nature of their tasks at work was mostly manual. This does not mean that people in India should not be optimistic about science and technology. The ICT industry in India has afforded many opportunities in the country and cell phone technology has increased access to finance. But, if almost 60 per cent have never used a personal computer and 18 per cent have manual jobs, it does call into question whether people in India are equipped with the basic computer skills necessitated by technological change and future labour market trajectories.

Figure 6.5. Perceptions of technology, juxtaposed with actual personal computer use

Source: World Values Survey, 2010–14 (6th Wave). Online analytics for the maps and own elaboration using World Values Survey data for the scatter plot.

6.3 Aspiration gaps and aspiration failures

The 2017 report Youth Aspirations and the Reality of Jobs in Developing Countries from the Organisation for Economic Co-operation and Development (OECD) is based on the harmonization and analysis of data from 32 school-to-work transition surveys conducted by the ILO in developing and transition countries in Africa, Asia, Europe and Latin America and the Caribbean from 2012 to 2015 (OECD, 2017). It pointed to the mismatch between youth aspirations and projected labour demand being alarmingly pronounced in a number of the countries surveyed. The job characteristics valued by youth are also difficult to ascertain in many countries. This led the OECD to caution that a wide gap between aspirations and reality is likely to result in lower levels of motivation and productivity, thus increasing frustration at the same time as it decreases well-being, and could even lead to social unrest (ibid., p. 14).

The OECD’s findings are summarized in Figure 6.6, which highlights the discrepancies between what youth aspires to and actual employment. This point must be considered carefully, especially in developing country contexts where the absolute lack of opportunity for work is a binding constraint. In a chilling case, described in an ILO report on “The Future of Work We Want” in Latin America and the Caribbean, a young participant told workshop facilitators that (paraphrasing), “if you help us find work, we can eat, and if we can eat, we can think”. That participant was subsequently shot dead by a neighbour in his villa for playing music too loudly (ILO, 2017, p. 73). It cannot be over emphasized that social and labour market conditions are a prerequisite for dreams and aspirations.

What the OECD found from the School-to-Work Transition Survey (SWTS) data is that students in the countries surveyed overwhelmingly aspired to work in the public sector. Across countries, this was the case for an average of 57 per cent of those surveyed. This is at odds with the fact that only 17 per cent of young workers were employed in the public sector at the time of the survey (which includes state-owned enterprises, international organizations, NGOs and public companies). Similarly, in most countries, more youth expressed a desire to work in the private sector or self-employment or for a family business than actually do. Another risky mismatch is that the high percentages of students who desired high-skilled work will most likely be unable to fulfil those aspirations (even tertiary students), given the current labour market trajectories (ibid., p. 13).

Figure 6.6. Young people’s (18-29 years) aspirational gaps, by region, country and sector of activity

Source: OECD (2017). OECD’s calculations based on SWTS 2012–15 data.

Notes: The figure shows the difference in the share of young students in the country who say they want to work in that sector and the actual employment of young people in that sector. Within each region, countries are sorted by the difference between reality and desire (aspirational gaps). 1Data for El Salvador are urban only and 2data for Montenegro, Togo and Viet Nam are missing sample weights.

The OECD offers several policy recommendations to curb the mismatch between young people’s labour market aspirations and reality. The first is to provide youth with information about labour market prospects to help guide their career choices. Indeed, around 33 per cent of respondents to the Citi and Ipsos survey said that if they “knew where to find information about job opportunities”, it would make it easier to find a job. Yet, the most cited need of around 48 per cent of respondents was “more on-the-job-experience” (Citi and Ipsos, 2017).

While the OECD analysis gives some information about aspirational gaps, we only see the mismatch for a broad classification of sectors (public and private) and it would be instructive to have an analysis based on economic sector of employment or actual occupations. For example, an analysis conducted by Education and Employers together with the United Kingdom’s Commission for Employment and Skills and B-live found the aspirations of people aged 15–16 to have “nothing in common” with actual and projected demand in the workforce (as cited by Chambers et al., 2018).

Figure 6.7 is excerpted from the Drawing the Future publication produced by Education and Employers (Chambers et al., 2018) and shows the occupational aspirations of youth aged 15–16 mapped against projected demand in the labour market (2010–20).

Figure 6.7 Aspirational gaps based on occupations, young people (15–16-year-olds) in the United Kingdom, 2010–20

Source: Excerpted from Chambers et al., 2018

Chambers et al. noted that these findings raise a major concern about the extent of the gap between jobs that actually existed (or were projected to exist) and what young people aspired to do and related this to a lack of information. The Office of National Statistics in the United Kingdom published a blog in September 2018 expressing a similar concern. They found that the top five dream jobs for young people aged 16–21 in 2011–12 did not align with the proportion of persons aged 22–29 in those occupations in 2017.

Figure 6.8 Aspirational gaps in the United Kingdom: top five jobs that persons aged 16–21 wanted and the employment of persons aged 22–29 in 2017

Source: United Kingdom Office for National Statistics blog, available at: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/youngpeoplescareeraspirationsversusreality/2018-09-27

A study conducted in Switzerland in 2010 found that around 80 per cent of young people in grade seven (aged 13–15) who were predominantly non-college bound had at least one realistic career aspiration (Hirschi, 2010). The Swiss education system is a dual system whereby around two-thirds of students go into vocational education and training in grade nine. The study asked 252 students to name the vocational education or training or the school they were considering after grade nine. Students could list as many options as they wanted (Hirschi, 2010). Due to the particular structure of the Swiss education system, it was possible for the author to build a measure of how realistic was this aspiration. This analysis is quite distinct from the studies conducted in the United Kingdom, but one interesting difference stems from students being allowed to mention as many aspirations as they wanted. For all but 20 per cent of respondents, at least one of those mentioned was realistic. This suggests that the way in which responses are solicited can yield different “matches” with reality; if a young person can list multiple career aspirations, what are the chances that at least one is consistent with labour market demand? This is a different question from the one analysed by the Office of National Statistics and Education and Employers in the United Kingdom.

The OECD’s second recommendation for reducing aspirational gaps is the promotion of entrepreneurship for young people who possess a high degree of entrepreneurial potential. According to the OECD’s report, youth identified self-employment and working for a family business as desirable, when through choice or because their family needed help (OECD, 2017). However, it is known that entrepreneurship in many developing countries is typically undertaken through necessity rather than choice therefore promoting more innovative types of entrepreneurship is crucial. Acs et al. (2008) have argued that positive perceptions of the opportunities available in the environment where one lives and about one’s own entrepreneurial capabilities drives people into opportunity entrepreneurship, a mechanism that clearly corresponds to the drivers of aspiration formation as described earlier in section 3. Box 6.1 presents the results of a recent study on differences between entrepreneurial attitudes and a country’s level of early-stage entrepreneurial activity.

Box 6.1 Entrepreneurial attitudes and entrepreneurship

Beynon et al. (2016) took a sample of 54 countries from the Global Entrepreneurship Monitor 2011 survey to analyze four country-level entrepreneurial attitudes and assess their role in driving Total early-stage Entrepreneurial Activity (TEA), which has been related to a strong business culture and growth. Entrepreneurial attitudes are defined in the table below.

Definitions of variables used in analysis
Variable	Description
Perceived opportunities	Percentage of 18–64 age group who see good opportunities to start a firm in the area where they live
Perceived capabilities	Percentage of 18–64 age group who believe they have the necessary skills and knowledge to start a business
Fear of failure	Percentage of 18–64 age group who with positive perceived opportunities who indicate that fear of failure would prevent them from setting up a business
Entrepreneurial intention	Percentage of 18–64 age group who intend to start a business within three years
Total early-stage Entrepreneurship Activity (TEA)	Percentage of 18–64 age group who are either a nascent entrepreneur or owner-manager of a new business

Source: Excerpted from Beynon et al., 2016.

The authors found that for a majority of countries high TEA levels of entrepreneurship related most to entrepreneurial intention, perceived capabilities and lack of fear of failure, rather than perceived entrepreneurial opportunity (with intention).

The results from this study, coupled with findings from Acs et al. (2008), suggest that stimulating entrepreneurship requires helping young people build skills, beliefs in capabilities and self-efficacy, and the desire to engage in entrepreneurial activity. In this sense, the OECD’s proposed recommendation to stimulate entrepreneurship programmes by boosting access to financial services and business development services might be more complete if it also promotes socio-emotional skill building.

6.4 The broader set of aspirations

Some of the survey literature on the broad life goals of youth indicates that work may not be their top priority. This notion was underscored during an interview held by the authors with representatives of UNI Global Union, who emphasized that youth aspirations of today may be different from those of previous generations. Today’s youth “work to live, rather than live to work”. Work/career may not be the most important goal in a young person’s life. Work might more often be regarded as a means to an end (i.e. to provide for family), whereas in previous generations everything was geared towards career development. Young people may aspire to aspirations that are more collective (i.e. greater care for the planet, environment and climate; resurgence of socialism among millennials), rather than to individual aspirations. Youth may be wary of rhetoric about change (i.e. from large companies and politicians) and desire actual change (via grassroots protests and demonstrations). Pre-market conditions and social responsibilities may be a bigger priority than is employment for some youth. That said, it was pointed out that many youth in many countries need work just to survive.6

Figure 6.9, excerpted from a report of the preliminary results from a YouthSpeak survey by the global student organization AIESEC, seems to corroborate this notion. Globally, youth indicated that family, purpose in life, love and friends, were motivating factors that ranked higher than financial reward or achievement.

Figure 6.9. What motivates youth today? (top 3 answers)

Source: YouthSpeak survey by AIESEC.

Generally speaking, the analysis presented in this section supports the notion that different groups of youth may respond differently to questions about technology, job preferences and the obstacles to getting a job. It is therefore very important to calibrate results from surveys that have more restrictive samples of generally highly educated employed youth (such as Deloitte Millennials and PricewaterhouseCoopers), since they might not capture the voices of youth who are less educated and not employed. Specifically, in the case of technology, it may be important for surveys to calibrate respondents’ perceptions and aspirations with questions that measure expectations about achieving aspirations and about actual use of and familiarity with new technologies. For example, Orlik (2017) argues that some people working in occupations most likely to be affected by digitalization are not necessarily aware of the acute need to reskill and upskill.

Conclusions and recommendations

7.1 Recommendations for data collection

Recent surveys focussed on youth aspiration tend to ask young people about their goals in terms of (a) ideal sector of work, or (b) ideal occupation. These data collection efforts have been important, because without them, little would be known about what type of work young people aspire to and what matters to them in a job or career (OECD, 2017). Of equal importance, as reported by the OECD, is whether existing labour market conditions live up to youth aspirations. There are risks on either side, as described in section 3 of this report. Aspirations that are either too low or too high risk aspiration failure, leading to frustration. It is crucial to balance within the same survey questions about aspirations with questions that assess reality.

The following recommendations are informed by an in-depth review of the research design of youth-focused surveys and structured as advice for researchers planning projects in this area.

Draw a sample from youth not in employment, education or training to compare their answers with those engaged in education or work . Many surveys reviewed used a restricted sample population of youth, either by default or explicitly, and solicited responses from youth who were employed or in school. These youth may have systematically differed from youth not employed or in education or training. One strategy could be to follow the example of the Young Lives survey7 and sample young people from groups of interest, including those not working or in education or training. Regional differences emerged in the analysis of trends around the world from among the 18 surveys reviewed. Drawing a larger sample of youth not in employment, education or training does not necessarily imply targeting only developing countries. Comparing the aspirations of such youth in different regions and countries may yield interesting insights.
Consider the target age group for this kind of research carefully . While most of the 18 surveys reviewed for this report were about youth, a more recent study asked more than 20,000 children aged 7–11 to draw a picture of the job they wanted when they grow up (Chambers et al., 2018). This revealed that social background already influences aspirations at age 7. Relevant questions for policy-makers are: What age is the right age to intervene, if the goal is to help shape aspirations? And, are there fundamental differences between aspirations formed at a young age? Are they more deeply rooted and more difficult to reshape than aspirations in later years, or is it the other way around?
Include questions in survey instruments that self-assess the probability of achieving goals . In general, when surveys asked youth about their aspirational goals, they were not asked to self-assess the chances of achieving those aspirations. Some of the surveys asked youth about concerns when applying for jobs (or about obstacles to finding a job), but this is not the same as explicitly asking young people to evaluate their chances of achieving a particular aspiration. One exception was the UNDP’s survey in Armenia, in which people were asked to assess the probability of fulfilling their top goals. This self-evaluation could be introduced via direct (as does the UNDP survey) and/or indirect questions.
Include self-assessment of digital and technical skills as part of any survey asking questions about technology. The surveys reviewed tended to ask youth a variety of questions about beliefs or general perceptions of the world around them. When youth were asked whether technology creates or destroys jobs, this question should have been complemented with questions about the respondents’ digital and technical skills and capabilities. Collection of this information would be useful, because under almost any future scenario of work, generic digital technology will become increasingly important. Collecting information about digital skill sets to complement young people’s perceptions will yield results that are more actionable for policy and programme design.
Introduce additional questions about current activity or occupational status and personal and/or family characteristics. The surveys reviewed often did not include enough information about current job and personal and/or family characteristics within the same instrument. Because almost all recent survey data on this topic use nationally representative samples, using the data to analyse the role that aspirations have in labour market outcomes is challenging.
Complement online surveys with mechanisms for reaching youth without access to the Internet. Modes of survey delivery could inadvertently exclude youths who do not use the Internet. To reach more youth respondents in a cost-effective way, many recent surveys have been conducted online. While this may yield a larger number of responses, it may also introduce bias.

7.2 Recommendations for employment policy

Youth can be influenced. We have argued, based on the literature presented in section 3, that youths’ aspirations are malleable. When policies align youth educational and work aspirations with the pathways to achieving them, they are more likely to be successful than when aspirations are ignored. Therefore, it is clear that employment policies should be geared towards supporting young people in their aspirations through allowing them to visualize their prospects and by providing the tools necessary to realizing the goals to which they aspire.

This report makes the following recommendations:

Career counselling with monitoring may be a good mechanism for relaying information about the types of jobs available in a given labour market, helping to raise aspirations among aspirations-poor youth and re-align aspirations that are unlikely to be achieved to more realistic alternatives. Although youth – particularly disadvantaged youth – are often targeted by active labour market policies (ALMPs), success varies regionally, possibly because in some contexts youth aspirations have not been taken into consideration. Intake interviews by psychologists to determine the aspirations and potential of young jobseekers, followed by individual assistance programmes to develop a career trajectory for the individual job seeker, combined with the identification of possible additional training needs and the provision of training (see Technical and soft skills training below), are needed in such cases.8 If career counsellors are primed with information about the current trends and aspirations of youth, or lack thereof, career guidance will prove more effective and tailored to the constraints they face. If career counselling comes equipped with an understanding of the prevailing goals and attitudes of youth towards work with respect to (for example) other life goals, and if the counsellors have up-to-date information about labour market prospects and trajectories, such job assistance programmes may well increase matches. Moreover, this may be more effective than simple job search training, when the prevailing labour market conditions are unfavourable and jobs are just not available. Job search training is also only effective at the expense of crowding out other jobseekers.

Technical and soft skills training are important in reducing young people’s lack of opportunities in the labour market. This may partly be within the scope of employment policies; for instance, when counselling re-orientates jobseekers towards vocational training or towards training curricula for jobs in high demand. One of the policy recommendations suggested in discussion with UNI Global Union is that universal access to reskilling and upskilling should be provided. Digitalization is changing jobs and the nature of jobs and of work rapidly. Policies need to facilitate reskilling and upskilling at different points along a career trajectory. The impact of technology may necessitate earlier and more systematic intervention; for example, unemployment services and career guidance during the transition from school to work. New skill accelerators known as “coding bootcamps” combine traditional vocational style training with rigorous “bootcamp” style coursework and have been found to be very successful in teaching advanced digital skills to people with no background in computer science. These coding bootcamps offer a very new form of digital skills training and could be a resource for other types of labour market training programmes (ITU, 2018).

Perhaps of equal importance is the development of soft skills (i.e. social and communication skills, belief in one’s own capability, attitudes). We find evidence for this in the literature on aspirations and in the entrepreneurship literature. In many countries, the sectors and occupations to which young people aspire do not exist in sufficient quantities. If young people are going to be path-breaking and create new opportunities where previously they did not exist, then soft skills will be a core component of such endeavours.

Entrepreneurship education and promotion is another important policy domain in the alignment of youth aspirations to labour markets when formal jobs are scarce. The entrepreneurial career is often one overlooked by youth, or else not desired. Stevenson and Lundström (2007) describe how entrepreneurship can be stimulated by (i) fostering people’s motivation to start a business, (ii) providing support for entrepreneurial skills development and (iii) supporting entrepreneurial opportunity.

By motivating young people through entrepreneurship promotion efforts, including awards programmes, entrepreneurship events and media campaigns to highlight the social value of entrepreneurship and raise greater awareness of entrepreneurship as a career option, entrepreneurship can become an aspirational (career) goal. Entrepreneurial skills development should be provided through the introduction of entrepreneurship education in schools at the various levels of education, building entrepreneurial know-how at a younger age. Employment policies can expand on this, relaxing the constraint that a lack of skills and experience puts on young people. Facilitating business coaching and mentoring, start-up guidance, business plan development support and access to business networks can all help people gain the skills necessary to succeed. Finally, supporting the search for start-up and seed funding, incubators and other business development services can help young people take effective action.

Box 7.1 Good practice example in positively influencing aspirations

Ganbina, Australia

Ganbina is Australia’s most successful indigenous school-to-work transition programme. It is founded on the belief that the exploration into successful employment begins at a very young age and continues throughout adolescence. The complex and limited connection to family and community can have a negative influence on youth’s educational attainment and further on in the future of their work. Among all underprivileged youth in Australia, indigenous children are the most severely disadvantaged in both education and employment, with many hailing from family backgrounds where long-term generational unemployment and welfare dependency are common. Because of this, these children lack the positive role models and the support they need to build and achieve aspirations.

To help young generations build self-confidence and career aspirations, Ganbina adopted a unique approach in which a team of trained mentors supports indigenous youth from the ages of 6 to 25 years, to ensure they gain the education, skills and life experiences they need to unlock their full potential. They work closely with the participants’ families, school teachers, vocational training organizations, universities, prospective employers and indigenous groups, to deliver a variety of practical programmes which help the young participants get the best education, explore different career options, raise career aspirations and make a successful transition from study into employment.

Ganbina has helped many youth get accepted into university, with professional certificates in different fields. Seventy-six per cent of Ganbina participants aged 25–34 are employed, versus 51 per cent nationally in Australia.

Taylah, a student at the University of Melbourne stated that “without Ganbina, I definitely would not be at university now. It made me realise I could do it, and so that changed my life”, “They helped me get through high school, apply to uni, organize accommodation and scholarships to help pay for my fees.”

Further information can be found: http://www.ganbina.com.au/

Role models in youth programmes . A recent study conducted into young people’s aspirations in Ghana argues that “Aspiring is a skill that not all young people have developed and so needs to be taught by youth programmes. Young people need to be encouraged to think about their future in a way that is both realistic and stretches them” (Boateng and Lowe, 2018, p. 30). The social context in which aspirations are shaped is indeed important and positive narratives, examples and role models with which young people can identify should be considered in any intervention among aspirations-poor youth (see, for example, the experience of Ganbina in Australia described in box 7.1). Labour market policies benefit by having a holistic design that includes role models (who generate vicarious experiences) in combination with skills developments and other career support interventions (e.g. financing schemes). Programmes that provide experiential information on how to integrate into the labour market, and have a financial scheme to aid in this, are more likely to elicit a positive response from its target population, as it helps visualize the different ways in which financial resources can be put to good use.

“Work is work, no matter the contractual arrangement.” This statement was made by representatives from UNI Global Union during an interview with the authors who noted the rise in non-standard forms of employment, a trend discussed in the literature in section 4. According to the UNI Global Union representatives, this has at least two implications. First, “post WWII” social protection schemes are outdated; if people are working under temporary contracts, they should still have the right to social protection (i.e. maternity leave, sick leave and retirement savings). Second, there may be a need to redefine what constitutes work; does, for instance, care of next of kin or family qualify as work? There has been a rise in the individualization of everything, from workers’ rights to student debt and market risk; perhaps redistribution and collective rights are more valued by young people as a consequence? Employment policies should address these questions in order to redefine work better and develop social protection schemes that are more inclusive of the increasingly large group of people working in NSE.

Involve youth in the policy-making process . In discussion with UNI Global Union, they underscored the need for the voices of diverse youth interest groups to be included in the policy-making process. This harkens back to the initial impetus for research on the aspirations of youth. There is a sentiment held by employers and the general public alike that the aspirations of millennials are somehow distinct and different from those of previous generations. It is in order to better understand these differences, should they exist, that research about youth is being conducted. It makes sense that the voices and differences of opinion among youth be heard and incorporated, otherwise any attempt at analysis could risk bias. If the right questions are not asked, or if questions are not asked in a way that makes sense to the young people surveyed, the answers elicited are not going to provide meaningful input for policy-making (or programme development) for youth.

Appendix A: Overview of each survey

Table A.1 ASEAN in transformation

Survey year(s)	Number of countries	Target age group	Number of respondents	Restriction on sample population: explicit or default
June 2015 and Jan. 2016	10	18–24 years (83.3% of sample)	2 747	University and technical and vocational education and training students expected to graduate between 2015 and 2017

Survey objective: The ILO Bureau for Employers’ Activities designed this survey to explore the challenges, changing goals and needs facing the ASEAN region’s new generation of workers and to further understand the dynamics of new technological trends in the region. The survey was conducted by partners in the region. A survey of 4,000 enterprises in the region was also conducted, but in this report we focus on the survey that targeted young students in the region (ILO, 2016, p. 1).

Mode of delivery: The students’ data were collected through an online survey.

Discussion of survey respondents: The respondents had to be students enrolled in either top-tier universities or vocational education and training. All students surveyed were expected to graduate between 2015 and 2017, and roughly 83 per cent of the respondents were between the ages of 18 and 24 years. The report ASEAN in Transformation (ILO, 2016) provides detailed methodology about how top-tier universities were selected. It is not clear how TVET institutions were selected.

Country coverage (10): Brunei Darussalam, Cambodia, Indonesia, Lao People’s Democratic Republic, Malaysia, Myanmar, Philippines, Singapore, Thailand, Viet Nam.

Table A.2 ASEAN Youth and the Future of Work

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2018

6

Under 35 years

64 000 (42 000 completed)

e-commerce or online game platform users

Survey objective: To gain insight about how youth in South-east Asia are feeling about their future employment prospects, the World Economic Forum partnered with SEA (a Southeast Asian internet company), in order to survey younger generations in the region (WEF and SEA, 2018, p. 2).

Mode of delivery: Online only. The survey was run in partnership with SEA, one of South-East Asia’s leading internet companies. Users of Shopee (an e-commerce platform) and Garena (an online games platform) across ASEAN were asked to fill in the survey online during July 2018.

Discussion of survey respondents: The respondents had to be 35 or younger and were mainly citizens of six ASEAN countries. Given the mode of delivery (i.e. via online games and e-commerce platforms) one could assume a pro-technology bias in the responses vis-à-vis people not using those platforms.

Country coverage (6): Indonesia, Malaysia, Philippines, Singapore, Thailand, Viet Nam.

Table A.3 Credit Suisse

Survey year(s)

Number of countries

Target age group

Number of respondents

Sample population: explicit or default

April and May 2018 (eighth since 2010)

4

16–25 years

4 021

Youth in four countries with access to the internet

Survey objective: Designed to gain insight and monitor young people’s lifestyles, communication styles, means of gathering information and views (i.e. what is considered “in” and “out”) over time. The survey has been conducted annually in Brazil, Switzerland and the United States since 2010 and in Singapore starting in 2013. The questionnaire was designed in Switzerland, but in order to ensure maximum comparability in the other countries the questionnaire was reviewed by local experts and adapted to adjust for any cultural differences or different political circumstances in the countries.

Mode of delivery: Online questionnaire. In Switzerland the survey was conducted by gfs.bern polling service. Ag Knowledgetech was commissioned to gather data in Brazil, Singapore and the United States.

Discussion of survey respondents: The survey collected 1,000 responses in Brazil, Singapore and the United States and 1,021 in Switzerland. The 2018 survey in Switzerland was weighted by language region and, “only a post-stratification weighting by age was additionally undertaken. In the United States, Brazil and Singapore, quota sampling was used, so weighting is not necessary (Credit Suisse Youth Barometer, 2018).

While in these three countries internet penetration rates are generally high, there are big differences between the countries. The International Telecommunications Unit (ITU, n.d.) reports the “Percentage of Individuals using the Internet” in the four countries in 2017 as follows: Brazil, 67 per cent; Singapore, 84 per cent; Switzerland, 94 per cent; United States, 75 per cent. These statistics are for the entire population, and while it might be safe to assume that youth might have a higher percentage of access, especially in Brazil, there may be some youth whose voices are not heard by this survey that was conducted exclusively online.

Country coverage (4): Brazil, Singapore, Switzerland, United States.

Table A.4 Citi and Ipsos, Pathways to Progress Global Youth Survey

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

Nov. 2016 and Jan. 2017

32

18–24 years

7 394

Youth in 45 cities with access to the internet

Survey objective: Citi Foundation commissioned Ipsos to conduct a survey to gauge economic prospects and pursuits of young people in 32 countries in 45 cities spread globally (Citi Foundation and Ipsos, 2017, p. 2).

Mode of delivery: Online.

Discussion of survey respondents: The respondents are youth aged 18–24, located in 45 large cities in 32 countries with access to the internet.

Country coverage (32): Argentina, Australia, Brazil, Canada, China, Colombia, Hong Kong, India, Indonesia, Israel, Japan, Kenya, Malaysia, Mexico, Morocco, Nigeria, Panama, Peru, Philippines, Poland, Republic of Korea, Russian Federation, Singapore, South Africa, Spain, Taiwan, Thailand, Turkey, United Arab Emirates, United Kingdom, United States, Viet Nam.

Cities surveyed in “Developed Markets”: Chicago, Cleveland, Dallas, Denver, Dubai, Hong Kong, Istanbul, London, Los Angeles, Madrid, Miami, Moscow, New York, San Francisco, Seoul, Singapore, St. Louis, Sydney, Taipei, Tampa/Jacksonville, Tel Aviv, Tokyo, Toronto, Warsaw, Washington, DC.

Cities surveyed in “Developing Markets”: Bangkok, Beijing, Bogotá, Buenos Aires, Casablanca, Guadalajara, Ho Chi Minh, Jakarta, Johannesburg, Kuala Lumpur, Lagos, Lima, Manila, Mexico City, Mumbai, Nairobi, New Delhi, Panama City, São Paulo, Shanghai. Data presented in the report were weighted to the local population 18–24 according to gender, age, household income and in the United States, ethnicity.

Table A.5 Deloitte Millennial Survey

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

Nov. 2017 and Jan. 2018

36

23–34 years

10 455

University degree and employed full time

Survey objective: The Deloitte 2018 Millennial Survey is the seventh annual survey. It builds upon the 2017 survey to ask respondents about their perceptions regarding changing opportunities and threats in world that is becoming more complex (Deloitte, 2018, p. 1).

Mode of delivery: Online questionnaire only. The report does not state how many questionnaires were distributed, or details about how responses were solicited.

Discussion of survey respondents: The respondents were born between January 1983 and December 1994 and are university graduates working full time. Respondents are predominantly employed in large private-sector companies.

Country coverage (36): Argentina, Australia, Belgium, Brazil, Canada, Chile, China, Colombia, France, Germany, India, Indonesia, Ireland, Italy, Japan, Malaysia, Mexico, Netherlands, New Zealand, Peru, Philippines, Poland, Republic of Korea, Russian Federation, Singapore, South Africa, Spain, Switzerland, Thailand, the Nordics (Denmark, Finland, Norway, Sweden), Turkey, United Kingdom, United States.9

Table A.6 European Social Survey

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2002–16 (every 2 years)

23 in 2016

15 and older

Varies by survey year and question

All persons 15 and over (no upper age limit)¹

Survey objective: The European Social Survey (ESS) is a cross-national survey of attitudes and behaviour. (ESS website, available from: www.europeansocialsurvey.org/about/faq.html)

Mode of delivery: Face-to-face computer-assisted personal interviews (CAPI) in all participating countries.

Discussion of survey respondents: Respondents 15 and older who are ¹residents within private households, regardless of their nationality, citizenship or language. According to the ESS website, all participating countries had to aim for a 70 per cent response rate and representative sample with a minimum “effective achieved sample size” of 1,500 or 800 in countries with populations of under 2 million.

Country coverage (23 in 2016): Austria, Belgium, Czechia, Estonia, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Russian Federation, Slovenia, Spain, Sweden, Switzerland, United Kingdom.

Table A.7 Gallup

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on population: explicit or default

2016

150+

None¹

Typically 1 000 per country

Nationally representative samples

Survey objective: The Gallup World Poll continually surveys residents in more than 150 countries. Gallup’s mission was to commit to collecting and disseminating the opinions and aspirations of people around the globe is essential to understanding our world (Gallup, 2016, p. 189).

Mode of delivery: When telephone coverage is 80 per cent of the population or if telephone surveys are commonly used, a 30-minute survey is conducted via telephone using random digit dialling (RDD). Face-to-face interviews that are about 1 hour long are conducted using an area frame in Central and Eastern Europe, parts of Latin America, the former Soviet Union countries, nearly all of Asia, the Middle East, and Africa. Gallup weights the World Poll samples to match national demographics and correct for unequal selection probability, nonresponse, and double coverage of landline and cellphone users when using both cellphone and landline frames.

Discussion of survey respondents: ¹The respondents are said to be nationally representative and therefore there is no targeted youth age group for the survey. It is also not possible to filter these responses by age using the online Gallup Analytics tool.

Country coverage (150+): A list of countries was not explicitly provided in the reports, or on the website.

Table A.8 Global Citizen Survey – Varkey Foundation

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on population: explicit or default

Sep. and Oct. 2016

20

15–21 years

20 088

Generation Z. Respondents who are members of global online research panels

Survey objective: To collect information about the attitudes, behaviours and experiences of Generation Z in 20 countries to capture an overview of their hopes, values and wellbeing (Broadbent et al., 2017, p. 1).

Mode of delivery: Members of global online research panels were emailed invitations to take part in the survey. The survey was not compulsory, but participants were financially compensated for their time if they took part in the survey.

Discussion of survey respondents: Respondents are a sub-age-group of youth (Generation Z) and are members of global online research panels. There is potential for bias, since there may be a selection issue for youth who are members of online research panels. Youth without access to the internet will naturally be excluded, due to the mode of delivery.

Country coverage (20): Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Israel, Italy, Japan, New Zealand, Nigeria, Republic of Korea, Russian Federation, South Africa, Turkey, United Kingdom, United States.

Table A.9 Global Shapers Survey (World Economic Forum)

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

March–June 2017

191

18–35 years

24 766

Youth aged 18–35

Survey objective: The Global Shapers Survey aims to capture the views and values of millennials worldwide: (1) how young people see the world (perception); and (2) what they want to do about it (action) (Global Shapers, 2017, pp. 5–6).

Mode of delivery: The survey was conducted in cities and mostly online by survey affiliates. Offline surveys were conducted in some cities and workshops were set up to increase access. The survey was available in 14 languages.

Discussion of survey respondents: Respondents are youth aged 18–35.

Country coverage (190): Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Aruba, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia (Plurinational State of), Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Cayman Islands, Central African Republic (CAR), Chad, Chile, China, Colombia, Comoros, Congo-Brazzaville, Costa Rica, Cote d'Ivoire, Croatia, Cuba, Curacao, Cyprus, Czechia, Democratic Republic of the Congo, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guam, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hong Kong, Hungary, India, Indonesia, Iran (Islamic Republic of), Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kosovo, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, North Macedonia, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Micronesia (Federated States of), Mongolia, Montenegro, Morocco, Mozambique, Myanmar (Burma), Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Puerto Rico, Qatar, Republic of Korea, Republic of Moldova, Romania, Russian Federation, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Sint Maarten (Dutch part), Slovakia, Slovenia, Somalia, South Africa, South Sudan, Spain, Sri Lanka, State of Palestine, Sudan, Suriname, Swaziland, Sweden, Switzerland, Syrian Arab Republic, Taiwan, Tajikistan, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Uganda, Ukraine, United Arab Emirates, United Kingdom, United Republic of Tanzania, United States, Uruguay, Vanuatu, Venezuela (Bolivarian Republic of), Viet Nam, the Occupied Territories of West Bank and Gaza, Yemen, Zambia, Zimbabwe.

Table A.10 ILO Survey on Youth and the Future of Work

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

April–June 2017

187

15–29 years

2 300 (1 700 were retained as valid responses)

Youth with access to the ILO’s Decent Work for Youth platform

Survey objective: Collect and link information about young people’s attitudes and aspirations to the actual employment situation of respondents (ILO, 2017b, p. 1).

Mode of delivery: Online, via ILO’s Decent Work for Youth platform via youth-led organizations with a focus on young activists from workers and employer’s organizations. Available in four languages: English, French, Spanish and Arabic.

Discussion of survey respondents: Respondents are between the ages of 15 and 29 with access to the ILO’s Decent work for Youth platform.

Country coverage (187): A list of countries was not explicitly provided in the reports.

Table A.11 Ipsos and Gates Foundation Goalkeepers Global Youth Outlook Poll

Survey year(s)

Number of countries

Target age group

Number of respondents

Sample population: explicit or default

Between 9 July and 22 August 2018

15

12–15 years (12–17 years in three countries)

40 506 (7 152 youth and 33 354 “adults”)

Ipsos claims representative samples in nine of the 15 countries¹

Survey objective: To ask people about their outlook regarding their personal lives, their communities’ challenges, and in which direction they think their country is headed.

Mode of delivery: In 12 of the 15 countries, the survey was conducted online. In three countries (India, Kenya and Nigeria), interviews were conducted face-to-face.

Discussion of survey respondents: Ipsos states that: ¹“In 6 of the 12 countries where interviewing was done online, internet penetration is sufficiently high to think of the samples as representative of the wider population within the age ranges covered: Australia, France, Germany, Great Britain, Sweden and the U.S. The three face-to-face countries are also nationally representative. Brazil, China, Mexico, Russia, Indonesia and Saudi Arabia have lower levels of internet penetration and so these samples should not be considered fully nationally representative, but instead to represent a more affluent, connected population. These are still a vital social group to understand in these countries, representing an important and emerging middle class” (Ipsos and Bill and Melinda Gates Foundation, 2018).

The majority of respondents to this survey are classified by Ipsos as “adults”, which they define as 16+ in all countries except the United States where it 18+. Around 500 respondents per country are youth, except in Saudi Arabia where around 200 respondents are youth. In most countries ISPOS considers youth to be ages 12–15, but in the United States, Kenya and Nigeria youth are defined as 12–17.

Country coverage (15): Australia, Brazil, China, France, Germany, India, Indonesia, Kenya, Mexico, Nigeria, Russian Federation, Saudi Arabia, Sweden, United Kingdom, United States.

Table A.12 MY World Survey

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2015

194

Any (possible to filter 16–30)

9 736 484 (5 274 181 are 16–30)

None

Survey objective: To engage citizens via a global survey to include citizens voices in official debates about the Sustainable Development Goals (SDGs) for the Post-2015 Development Agenda. Survey results (or “votes”) about priorities are meant to inform leaders (see United Nations, 2012, 2015).

Mode of delivery: MY World 2015 Survey had over 1,000 partners who worked to bring in votes from all countries and regions of the world. Votes were collected online, via text (SMS) or ballot and 80 per cent of the votes were collected offline. It was an honour system to vote only once.

Discussion of survey respondents: Respondents could be any age, although it is possible to filter the data by age group.

Country coverage (194): Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia (Plurinational State of), Bosnia and Herzegovina, Botswana, Brazil, Brunei Darussalam, Bulgaria, Burkina Faso, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Democratic People's Republic of Korea, Democratic Republic of the Congo, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran (Islamic Republic of), Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kuwait, Kyrgyzstan, Lao People's Democratic Republic, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia (Federated States of), Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Republic of Korea, Republic of Moldova, Romania, Russian Federation, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, State of Palestine, Sudan, Suriname, Swaziland, Sweden, Switzerland, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, United Republic of Tanzania, United States, Uruguay, Uzbekistan, Vanuatu, Venezuela (Bolivarian Republic of), Viet Nam, Yemen, Zambia, Zimbabwe.

Table A.13 PwC Millennials at work – Reshaping the workplace

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

August–October 2011

75 (most of the sample is from 24 listed countries)

31 or under

4 364

Graduated between 2008 and 2011. Most respondents were PwC recruits or employees

Survey objective: To provide insight into how recent graduates who are entering the workplace for the first time think about work, and how technology, globalization and other changes might affect how future businesses will operate (PwC, 2011, p. 2).

Mode of delivery: Online only. PwC commissioned Opinium Research to carry out the online survey.

Discussion of survey respondents: The sample of respondents is limited mostly to PwC recruits or employees. “PwC” refers to the network of member firms of PricewaterhouseCoopers International Limited (PwCIL); 1,706 of respondents were PwC graduate recruits or responded through PwC’s website. Overall, 1,470 PwC employees and 2,894 other graduates responded to the survey. The majority (75 per cent) of the respondents were employed or about to start a new job at the time they filled in the questionnaire. Very few (8 per cent) were unemployed. The rest were self-employed or returning to full-time education. Respondents were 31 or younger in 2011, but must have graduated between 2008 and 2011, so that provides a lower bound for the age of the respondents (assuming the vast majority of university graduates are 21 or older).

Country coverage (75, but most respondents are from the following 24 countries): Australia, Belgium, Brazil, Canada, China, France, Germany, Hong Kong, India, Ireland, Italy, Japan, Malaysia, Netherlands, Portugal, Romania, Russian Federation, South Africa, Spain, Switzerland, Turkey, United Arab Emirates, United Kingdom, United States; “Other countries (<30)”.10

Table A.14 School to Work Transition Survey (SWTS)

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2012–15

32

15–29 years

99 745

Young people aged 15–29¹

Survey objective: To collect labour market information on young people and background characteristics of those young people, and to identify features of labour market demand in developing countries (ILO, n.d.).

Mode of delivery: Implemented through individual countries’ National Statistics Office (NSO).

Discussion of survey respondents: Respondents are nationally representative of youth aged 15–29, ¹except in Colombia and El Salvador, where only urban areas are covered, and Brazil, where the data cover only 10 regions. The SWTS methodology module offered a variety of sampling strategies for participating countries to achieve nationally representative samples of youth aged 15–29.

Country coverage (32): Armenia, Bangladesh, Benin, Brazil, Cambodia, Colombia, Dominican Republic, Egypt, El Salvador, Jamaica, Jordan, Kyrgyzstan, Lebanon, Liberia, Madagascar, Malawi, Montenegro, Nepal, North Macedonia, Peru, Republic of Moldova, Democratic Republic of the Congo, Russian Federation, Serbia, Sierra Leone, Togo, Uganda, Ukraine, United Republic of Tanzania, Viet Nam, the Occupied Territories of West Bank and Gaza Strip, Zambia.

Table A.15 UNDP Armenia 2012 National Youth Aspirations Research Report

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2012

1

16–30 years

1 204

16–30-year-olds living in Armenia

Survey objective: To identify the aspirations and expectations of young people in Armenia, as well as their beliefs about the political, social and cultural life in Armenia (UNDP, 2012, p. 4).

Mode of delivery: 64 polling points, quantitative (semi-) structured face-to-face interviews with 16–30-year-olds and focus groups.

Discussion of survey respondents: Respondents are nationally representative of youth 16–30 years of age living in Armenia in 2012 (with a 2.9 per cent margin of error). A multi-stage sampling strategy was used.

Country coverage (1): Armenia.

Table A.16 World Values Survey

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

Sixth wave (2010–14)

60

18+ (possible to cross-tab answers for ages 18–29)

89 565

Nationally representative sample (no upper age limit)

Survey objective: A better understanding of global changes in values and beliefs, cultural norms and their stability or change over in different societies around the world (WVS Association, n.d.a).

Mode of delivery: Mainly face-to-face interview at respondent’s home or place of residence. Respondent’s answers could be recorded in a paper questionnaire or by CAPI.

Discussion of survey respondents: Respondents are nationally representative. Each country devised its own sampling strategy (more detailed information about sampling can be found at WVS Association, n.d.b.

Country coverage (60): Algeria, Argentina, Armenia, Australia, Azerbaijan, Belarus, Brazil, Colombia, Cyprus, Chile, China, Ecuador, Egypt, Estonia, Georgia, Germany, Ghana, Haiti, Hong Kong, India, Iraq, Japan, Jordan, Kazakhstan, Kuwait, Kyrgyzstan, Lebanon, Libya, Malaysia, Mexico, Morocco, Netherlands, New Zealand, Nigeria, Pakistan, Peru, Philippines, Poland, Qatar, Republic of Korea, Romania, Russian Federation, Rwanda, Singapore, Slovenia, South Africa, Spain, State of Palestine, Sweden, Taiwan, Thailand, Trinidad and Tobago, Tunisia, Turkey, Ukraine, United States, Uruguay, Uzbekistan, Yemen, Zimbabwe.

Table A.17 Young Lives: An International Study of Childhood Poverty, Round 4

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

2013–14 (Round 4)

4

19 years

3 382

Over-sample poor children/youth

Survey objective: Tracing the changing lives of 12,000 children over 15 years. The core research questions are about causes of poverty, its consequences, and means of inter-generational transmission (WB/ODID UK Guide to Young Lives Research, 2017).

Mode of delivery: Implemented by fieldwork teams who have undergone training, many fieldworkers worked with Young Lives for more than one round of fieldwork.

Discussion of survey respondents: The respondents are 19 years of age, but 12-year-olds are also surveyed in wave 4. The Young Lives survey has not been designed to be nationally representative, but rather to gain sufficient data for statistical analysis. Sentinel sites were selected non-randomly and rich areas were excluded. Children or youth in the right age range in the selected sites were sampled randomly. http://www.younglives.org.uk/sites/www.younglives.org.uk/files/GuidetoYLResearch-S5-Sampling.pdf

The child (or youth) questionnaire is complemented by a household questionnaire and a community questionnaire. It is a longitudinal study.

Country coverage (4): Ethiopia, India, Peru, Viet Nam.

Table A.18 Youth Speak: Global Youth Movement and Youth Insight Survey. (AIESEC)

Survey year(s)

Number of countries

Target age group

Number of respondents

Restriction on sample population: explicit or default

Launched on 9 October 2015

Unknown

16–30 (small percentage of responses younger or older)

160 231

None

Survey objective: Created by youth for youth, the survey is designed to ascertain what young people (globally) care about and gain insight into how they would like to be engaged (AIESEC, 2016, p. 8).

Mode of delivery: Not explicitly stated. Based on the YouthSpeak website (https://aiesec.org/youth-speak), it is assumed to be an online survey.

Discussion of survey respondents: The respondents are youth from different regions around the world. It is difficult to find detailed information about how the survey responses were solicited.

Country coverage (unknown): A list of countries was not explicitly provided in the reports. Regional data are presented in the preliminary results report as follows: Asia Pacific (57,959 respondents), Central and Eastern Europe (32,704 respondents), Latin America (25,974 respondents), Africa (16,393 respondents), Western Europe and North America (14,566), Middle East and North Africa (12,635 respondents).

Appendix B: Examples of survey questions

Table B.1 Examples of survey questions that measure the “goal” dimension of aspirations

Dimension measured	Survey question	Results presented	Source(s)
Aspired goals	What type of organization do you work for today? What type of organization would you like to work for in the future?	Report: Region and country	ASEAN Y&FoW
	In which economic sector would you ideally want to work when choosing your first employment?	Report: Gender, education level and field of study	ASEAN Transform
	If you had your preference, in which of the following would you prefer to work?	Data available and online analytical tool	World Values
	Could you please tell me the most important goal in your life?	Data available	SWTS
	Ideally, which of the following type of work would you prefer?	Data available	SWTS
	Ideally, in which sector do you want to work?	Data available	SWTS
	Each individual person has certain ideas that determine their life and behaviour. When you think about what you strive for in your life, how important are the following things for you personally?	Report	Credit Suisse
	What company would you like to work for the most, what would be your dream?	Report	Credit Suisse
	If you could have any job in the world, what would you want to do?	Report and tables	Ipsos/Gates Foundation
	What field would you most like to have a career in?	Report	Citi and Ipsos
	Do you agree or disagree with the following statement? My dream is to own my own business	Report	Citi and Ipsos
	Survey asked children (between 7 and 11 years old) to draw what they want to be when they get older and where they heard about that job (i.e. parents or someone else)	Report	Education and Employers

Source: Own elaboration using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.2 Examples of response choices that reflect different frameworks used to classify jobs

Survey question	Answer choices	Source(s)
What type of organization do you work for today? What type of organization would you like to work for in the future?	For a charity or social enterprise, start-up company, small and medium enterprise, big local company, my family business, foreign multinational company, for myself	ASEAN Y&FoW
In which economic sector would you ideally want to work when choosing your first employment?	ICT services, Financial or insurance services, Manufacturing, Education, RetailArts, entertainment or recreation, Human health or social work, Construction, Hotels or restaurants, Scientific or technical research, Other	ASEAN Transform
If you had your preference, in which of the following would you prefer to work?	(1) To work as an employee in the public sector, (2) To work as an employee in the private sector, (3) To be self-employed	World Values
Could you please tell me the most important goal in your life?	(1) Being successful in work, (2) Making a contribution to society, (3) Participating in local community affairs, (4) Upholding religious faith, (5) Having lots of money, (6) Having a good family life, (7) Having leisure time, (8) Having a lot of different experiences, (9) Finding purpose and meaning in life, (10) Building self-esteem and confidence, and finding personal fulfilment	SWTS
Ideally, which of the following type of work would you prefer?	(1) Start your own business, (2) Work for the government/public sector, (3) Work for a multinational corporation, (4) Work for a private company, (5) Work for a non-profit organization (6) Work for own/family farm, (7) Work for someone else’s farm, (8) Work for family business, (9) Not sure, (10) Do not wish to work, (11) Happy with current type of business/would not change, (12) Other	SWTS
Ideally, in which sector do you want to work?	(1) Agriculture, hunting, forestry and fishing, (2) Mining, (3) Manufacturing, (4) Electricity, gas and water supply, (5) Construction, (6) Wholesale and retail trade, repair, (7) Hotels and restaurants, (8) Transport, storage and communications, (9) Finance/insurance, (10) Real estate, renting and business activities, (11) Public administration and defence, (12) Education, (13) Health and social work, (14) Other community, social and personal services, (15) Private household service, (16) Happy with current sector/would not change, (17) Not sure, (18) Do not wish to work, (19) Other	SWTS
Each individual person has certain ideas that determine their life and behaviour. When you think about what you strive for in your life, how important are the following things for you personally?	Respondents could rate each response choice as either “extremely important”, “very important”, “fairly important”, “not that important”, “not important”, “not important at all”, “don’t know/no comment” to the following: honesty, having friends I can count on, loyalty, balancing leisure time and a career, having an exciting job, enjoying life to the full, being respected as a person, getting a good education and/or further training, tolerance, living and acting responsibly, living healthy, protecting the environment, being independent of other people, seeing as much of the world as possible, achieving set goals with hard work, having a family with children, imagination/creativity, helping disadvantaged people/work for charity, having a good career, gaining sexual experiences, to move the world with my actions, living according to my religious/spiritual values, being my own boss/being independent, having lots of money, looking good and being popular, being committed politically, living life in the city, having an interesting personal online profile	Credit Suisse
What company would you like to work for the most, what would be your dream?	From the report, it seems that the respondent listed the company itself and then the analysts aggregated responses to sector (in Switzerland they report the percentage of 16–25-year-olds who prefer the following sectors: Agriculture, Banking, Commerce, Construction, Crafts business, Government, Health, IT/tech sector, Luxury goods, Media, NGO/charity, Pharmaceuticals, Show business/culture, Teaching and education, Tourism/travel, Watches)	Credit Suisse
If you could have any job in the world, what would you want to do?	The list of job options was ~85 different choices. These are the jobs that received the top responses (as summarized in the report): Doctor, Engineer, Teacher, Lawyer, Business owner or entrepreneur, Pilot, Technology, Nurse, Football player, Gamer, Veterinarian, Actor or model, Military personnel Journalist, Director or manager	Ipsos/Gates Foundation
What field would you most like to have a career in?	Technology or Science, Arts or Entertainment, Professional Activities, Health Care, Government, Education, Internet Startup, Sales or Retail, Service, Construction or Manufacturing, Transportation	Citi and Ipsos
Do you agree or disagree with the following statement? My dream is to own my own business	Assumed response choice (yes/no)	Citi and Ipsos
Survey asked kids (between 7- and 11-years-old) to draw what they want to be when they get older and where they heard about that job (i.e. parents or someone else)	The first question is open ended, the children can draw anything they want. The survey asked a series of questions about how they heard about the job they drew (i.e. parents or other relative; TV, internet, or social media)	Education and Employers

Source: Own elaboration using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.3 Examples of survey questions that measure desired/valued job characteristics

Dimension measured	Survey question	Results presented	Source(s)
Desired/preferred job characteristics	What characteristics would your ideal job have?	Report	Y&FoW ILO
	In general, how important are the following aspects when you are considering working at an organization? Please select each in order of their importance to you, from most important to least important	Report: aggregate	Deloitte Mil
	What are your most important criteria when considering job opportunities?	Data and report	G. Shapers
	When thinking about your current or future career, which ONE of the following is the most important?	Report	Global Citizen
	Which of the following work priorities would you currently prefer to choose?	Report	ASEAN Transform
	How important are the following factors in an employer?	Report	Credit Suisse
	You will see two companies that differ in various ways. Please select the company you like best. Scenario based question: “Respondents were presented with 2 fictional companies each with 5 different characteristics (randomly assigned between 3 options) along the following dimensions (economic, social, environmental, critical, and one in relation to the type of company). Young people then had to select the company they like best” (paraphrased from the Credit Suisse report).	Report	Credit Suisse
	Which of the following factors most influenced your decision to accept your current job?	Report	PwC

Source: Own elaborations using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.4. Examples of survey questions that measure expectations, probability of fulfilling aspirations and perceived obstacles to job prospects

Dimension measured	Survey question	Results presented	Source(s)
Expectations	Where do you see yourself 10 years from now? (sector of work)	Report	YouthSpeak AIESEC
	What best describes your current work and what are your expectations for [ten years in] the future?	Report	Y&FoW ILO
	How do you envision your future work life?	Report	Y&FoW ILO
	In your opinion, what is the outlook for your own future? At the present time, do you see the future …	Report	Credit Suisse
	Looking forward, do you think you will work ...?	Report	PwC
	Do you feel that you will be able to rise to the most senior levels with your current employer?	Report	PwC
	How many employers do you expect to have in your career?	Report	PwC
	Employment-related plans for the upcoming 3 years	Report	UNDP (Armenia)
	Plans for further education by place of residence	Report	UNDP (Armenia)
Dimension measured	Survey question	Results presented	Source(s)
Perceived chances of fulfilling aspirations	Estimates of the probability of fulfilment of their top goals by the young people in the upcoming three years	Report	UNDP (Armenia)
Dimension measured	Survey question	Results presented	Source(s)
Obstacles/lack of pathways or opportunity	What are your biggest concerns about your job prospects when you apply for a new job?	Data and report	G. Shapers
	What would make it easier to find a job?	Report	Citi and Ipsos
	Do you agree or disagree with the following statement? The education I want to achieve is beyond my financial means	Report	Citi and Ipsos

Source: Own elaborations using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.5 Examples of survey questions that measure assessment of opportunities (pathways)

Dimension measured	Survey question	Results presented	Source(s)
Assessment of opportunities (pathways)	Do you agree or disagree with the following statement? You need a university education to be successful	Report	Citi and Ipsos
	What do you see as the biggest benefit to studying in university/college?	Report	YouthSpeak AIESEC
	In your opinion, a person needs at least what level of education/training to get a decent job these days?	Data available	SWTS
	Which of the following qualities do you think is the most useful in finding a good job? (select one)	Data available	SWTS
	To what extent do you agree with the following statements about work, education and training? 5 choices on a Likert scale (completely agree, tend to agree, don't know/no comment, don't tend to agree, don't agree at all)	Report	Credit Suisse
	Do you agree or disagree with the following statement? Apprenticeships or internships are critical for career success	Report	Citi and Ipsos
	Do you agree or disagree with the following statement? There are not enough apprenticeships or internships in my city	Report	Citi and Ipsos
	Do you agree or disagree with the following statement? New or small businesses are not likely to succeed in my city	Report	Citi and Ipsos
	Do you agree or disagree with the following statement? My dream is to own my own business	Report	Citi and Ipsos

Source: Own elaborations using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.6 Examples of survey questions that measure perceptions of technology

Dimension measured	Survey question	Results presented	Source(s)
Perceptions of technology and jobs	Do you think that new technologies will create or destroy more jobs?	Report: regional	Y&FoW ILO
	Percent of respondents who have used online training and education courses	Report	ASEAN Y&FoW
	Percent of respondents who think technology will increase the number of jobs	Report	ASEAN Y&FoW
	Percent of respondents who think that technology will increase or reduce their earning power	Report	ASEAN Y&FoW
	What impact, if any, do you think Industry 4.0 might have on your job?	Report: aggregate	Deloitte Mil
	In your opinion technology is … [creating or destroying jobs]	Data and report	G. Shapers
	The services listed above are all part of the sharing economy. Sharing economy refers to the communal use of goods through sharing, swapping, lending, hiring or giving. The motto of the sharing economy is ‘using instead of owning’. Would you rate the sharing economy as being more negative (0) or positive (10) for you personally?	Report	Credit Suisse
	The sharing economy operates in particular via internet platforms or apps which are used for swapping and sharing things with others or for the communal use of items. Examples include Airbnb, RelayRides and Sharoo. Have you personally used a sharing economy service via an internet platform or app?	Report	Credit Suisse
	On an average day, how long do you use the following media for personal use? Please only list the approximate times in minutes per day for which you are active – (reading, viewing or writing entries yourself)	Report	Credit Suisse
	More emphasis on the development of technology (possible answers, excerpted from the codebook, range from “is a good thing” to “is a bad thing”)	Data available and online analytical tool	World Values
	Science and technology are making our lives healthier, easier, and more comfortable		World Values
	Because of science and technology, there will be more opportunities for the next generation		World Values
	Where do you see the use of technology most?	Report	YouthSpeak AIESEC

Source: Own elaborations using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Table B.7 Examples of survey questions that measure general perceptions/beliefs about the world

Dimension measured	Survey question	Results presented	Source(s)
General perceptions/beliefs about the world	Thinking about your future please indicate what you think is the most and least important to you from the list below?	Report	Global Citizen
	We have put together a list of very different things in life. Please judge whether these things are “in” or “out” in your personal circles and also what your own opinion of them is	Report	Credit Suisse
	Taking everything into account do you expect the overall economic situation in (your country) to improve, worsen or stay the same over the next 12 months?	Report	Deloitte Mil
	Taking everything into account do you expect the overall social/political situation in (your country) to improve	Report	Deloitte Mil
	Thinking about the world in general how do you feel about the future? Compared to your parents do you think you will be financially/materially better off	Report	Deloitte Mil
	Thinking about the world in general how do you feel about the future? Compared to your parents do you think you will be happier	Report	Deloitte Mil
	Do you agree or disagree with the following statement ... My generation is better off than my parents were	Report and tables	Ipsos/Gates Foundation
	In your opinion, what are the most serious issues affecting the world today?	Data and report	G. Shapers
	Welfare attitudes (many questions)	Data	ESS
	Which of these are most important for you and your family? (Choose 6 issues that matter most)	Website (myAnalytics)	MyWorld
	To what extent do the following make you hopeful of the future?	Report	Global Citizen
	To what extent do the following make you fearful for the future?

Source: Own elaboration using the questionnaires from the different survey instruments cited. Questions and answers are excerpted verbatim.

Literature list (by section and sub-section)

3 The concept and determinants of aspirations

3.1 Understanding aspirations

Appadurai, A. 2004. “The capacity to aspire: Culture and the terms of recognition”, in V. Rao and M. Walton (eds): Culture and public action (Stanford, CA, Stanford University Press).

Bandura, A. 1977. Social learning theory (Englewood Cliffs, NJ, Prentice-Hall).

—. 1993. “Perceived self-efficacy in cognitive development and functioning”, in Educational Psychologist, Vol. 28, No. 2, pp. 117–148.

—; Locke, E. 2003. “Negative self-efficacy and goal effects revisited”, in The Journal of Applied Psychology, Vol. 88, No. 1, pp. 87–99.

Bertrand, M.; Mullainathan, S.; Shafir, E. 2004. “A behavioral economics view of poverty”, in American Economic Review, Vol. 94, No. 2, pp. 419–423.

Dalton, P.; Ghosal, S.; Mani, A. 2016. “Poverty and aspirations failure”, in The Economic Journal, Vol. 126, No. 590, pp. 165–188.

Drèze, J.; Sen, A. 2002. India: Development and participation, 2nd edition (Oxford, Oxford University Press).

Lewin, K. 1936. Principles of topological psychology (New York, McGraw Hill).

Locke, E.; Latham, G. 2002. “Building a practically useful theory of goal setting and task motivation: A 35-year odyssey”, in American Psychologist, Vol. 57, No. 9, pp. 705–717.

Lybbert, T.J.; Wydick, B. 2018. “Poverty, aspirations, and the economics of hope”, in Economic Development and Cultural Change, Vol. 66, No. 4, pp. 709–753.

Ray, D. 2006. “Aspirations, poverty and economic change”, in A.V. Banerjee, R. Bénabou and D. Mookherjee (eds): Understanding poverty (Oxford, Oxford University Press).

Robeyns, I. 2016. “Capabilitarianism”, in Journal of Human Development and Capabilities, Vol. 17, No. 3, pp. 397–414.

Sen, A. 1985. “Well-being, agency and freedom: The Dewey lectures 1984”, in The Journal of Philosophy, Vol. 82, No. 4, pp. 169–221.

Snyder, C.R. 2002. “Hope theory: Rainbows in the mind”, in Psychological Inquiry, Vol. 13, No. 4, pp. 249–275.

3.2 What shapes aspirations?

Appadurai, A. 2004. “The capacity to aspire: Culture and the terms of recognition”, in V. Rao and M. Walton (eds): Culture and public action (Stanford, CA, Stanford University Press).

Beal, S.J.; Crockett, L.J. 2010. “Adolescents’ occupational and educational aspirations and expectations: Links to high school activities and adult educational attainment”, in Developmental Psychology, Vol. 46, No. 1, pp. 258–265.

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—.; Dercon, S.; Orkin, K.; Taffesse, A.S. 2014. The future in mind: Aspirations and forward-looking behaviour in rural Ethiopia, CSAE Working Paper 2014-16 (Oxford, Centre for the Study of African Economies). Available at: www.csae.ox.ac.uk/materials/papers/csae-wps-2014-16.pdf [17 June 2020].

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3.3 The malleability of aspirations through policy interventions

Bernard, T.; Dercon, S.; Orkin, K.; Taffesse, A.S. 2014. The future in mind: Aspirations and forward-looking behaviour in rural Ethiopia, CSAE Working Paper 2014-16 (Oxford, Centre for the Study of African Economies). Available at: www.csae.ox.ac.uk/materials/papers/csae-wps-2014-16.pdf [17 June 2020].

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—; Glewwe, P.; Prudencio, D.; Wydick, B. 2018. Developing educational and vocational aspirations through international child sponsorship: Evidence from Kenya, Indonesia, and Mexico (University of Minnesota). Available at: www.apec.umn.edu/sites/apec.umn.edu/files/cspaspire3.pdf [17 June 2020].

Wydick, B.; Glewwe, P.; Rutledge, L. 2013. “Does international child sponsorship work? A six-country study of impacts on adult life outcomes”, in Journal of Political Economy, Vol. 121, No. 2, pp. 393–436.

—; Glewwe, P.; Rutledge, L. 2017. “Does child sponsorship pay off in adulthood? An international study of impacts on income and wealth”, in The World Bank Economic Review, Vol. 31, No. 2, pp. 434–458.

4 Labour market challenges and youth aspirations

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5 Measuring youth aspirations in the world of work: An overview of existing surveys and indicators

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6 Youth aspirations and the world of work: Global evidence

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7 Conclusions and recommandations

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For Lybbert and Wydick, aspirations belong within the larger framework of “hope“, defined as a function of “aspirational hope” (aspirations) and “wishful hope” (dreams). “Hope” is the middle ground between what is ideal and what is feasible.

The first term is used mainly in the aspirations literature, the second, coined by the theory of “hope” and introduced into the aspirations literature by Lybbert and Wydick.

These results are in line with educational research that falls under the umbrella term “soft skills”. Personality traits and non-cognitive skills (soft skills), such as goals, motivation and other future-oriented behaviour, can be predictors of success in life (Heckman and Kautz, 2012) through the effect they have on decisions about schooling and the wage reward related to those schooling decisions (Heckman, Stixrud and Urzua, 2006).

Much of the reporting of these surveys appears under headlines such as ‘2018 Deloitte Millennial Survey: Millennials disappointed in business, unprepared for Industry 4.0’ which somehow imply that results based on a restricted sample population of employed university graduates working mostly in large companies can be generalized to all “millennials”.

This is more challenging when constructs (or abstract concepts) are multi-dimensional (Bhattacherjee, 2012). Aspirations are a multi-dimensional concept with many layers. In theory (and in reality) the formation of aspirations is shaped by a simultaneous feedback process in which own and vicarious experience, opportunities and social context, intermingle with preferences, psychological traits and ideas about expected outcomes, which evolve aspirations from one point in time to another. The concepts may be dynamic, but in this section it is necessary to pinpoint and articulate constructs that have been used to measure particular dimensions of aspirations.

Interview carried out on 19 February 2019 by UNU-MERIT researchers with UNI Global representatives visiting the ILO headquarters in Geneva.

Young Lives is an international panel study of childhood poverty that followed the lives of 12,000 children in Ethiopia, India (in the states of Andhra Pradesh and Telangana), Peru and Viet Nam over a 15-year period.

An example of such intervention was developed by the Tunisian National Employment Agency (ANETI). Its “Accompagnement” intervention was implemented as part of the FORSATI programme of the Ministry of Employment (MFPE) in 2017. The intervention comprised several steps, starting with collective and individual meetings between jobseeker and psychologists to determine whether youth had any idea about their professional future. Jobseekers were then classified into three groups: (i) young persons with no idea about their professional future, no view on the various options open to them and no idea how to link up to the labour market; (ii) those with a vague idea of what they wanted to do as a job; and (iii) those with a clear idea and the skills needed. The first group were to be supported by orientation counsellors in an individual trajectory, to help the young person develop ideas about the future. This could involve discussion about a choice between wage work or entrepreneurship. This intervention was fundamentally about raising aspirations and broadening options. The second group were to be assisted by counsellors to identify psychological and skills bottlenecks, implement a career plan and provide additional training to loosen those constraints. This support helped aspirations to be achieved by generating pathways. A last group was aided with job search assistance and training, introduction into professional networks, job search clubs and business coaching (ANETI, 2016, Manuel de procedures Programme Forsati Composante Accompagnement, Tunis).

The Nordics were grouped together by Deloitte, as were Malaysia, Singapore and Thailand. The number of responses from the grouped countries were in line with the number of responses from countries listed individually.

“Other countries <30” is excerpted from a bar chart showing responses per country in the report. It is assumed that this means less than 30 responses were from each country not explicitly named in the report.