By Katherine Marshall
Full article in PDF
Economic downturns tend to have a greater impact on youth compared to core-age workers. Youth unemployment tends to be higher and job stability and quality tend to decline—factors that can hinder a timely transition from school to work (Quintini and Martin 2006). Downturns can thus impede youths’ entry into well-matched career jobs and may have long-term effects on their well-being (Bell and Blanchflower 2010).
A suite of well-established indicators are used to assess the labour market performance of youth, including the employment rate, unemployment rate and long-term unemployment rate. During the late 1990s, a number of European countries and the Organisation for Economic Co-operation and Development (OECD) began publishing another indicator, the NEET rate—the proportion of all youth who are Not in Education, Employment, or Training. The term was coined in Britain after reports that an increasing number of older teenagers were leaving school and remaining jobless for long periods (Social Exclusion Unit 1999).
Concern was raised that NEET youth would become discouraged, disengaged and socially excluded. A British study showed that certain 'at-risk' youth were more likely to enter a NEET state and were subsequently more likely to have a poor labour market experience, depression, early parenthood and poor housing (Bynner and Parsons 2002). In reaction to this trend, programs and policies were developed in Britain to reduce the number of youths in a NEET state (Yates and Payne 2006). The phenomenon was not limited to Britain, as one study found that more than 10% of youth from age 15 to 24 in Italy, Greece, France and Spain were in a continual state of NEET for 5 years (Quintini and Martin 2006).
The term NEET has become a standard concept in Europe. However, some research has shown that while youth unemployment and NEET rates track closely in many countries, there are mixed or opposite correlations in others (Quintini and Martin 2006; Martin 2009). It is also argued that the term NEET has a distinctly negative connotation and that “it is important to note that even when youth NEET rates are very high, this may be generated by choices (e.g., travel, leisure), or by non-economic constraints (e.g., military conscription)” (Quintini and Martin, p. 11). Indeed travel, or unpaid work like parental leave or volunteering, should not be construed as detrimental behaviour. However, the exact activities of NEET youth not in the labour force are usually not known. Despite some conceptual difficulties with NEET, the argument has been made that publishing the indicator helps raise awareness of the potential vulnerability of some youth (Furlong 2006).
The OECD presents NEET and sub-NEET category rates (by unemployed and not in the labour force) for most member countries, including Canada. However, relatively little research has examined NEET youth in Canada. Is this relatively new indicator relevant to the situation of Canadian youth? Using the same OECD definition and data source—the Labour Force Survey—this study presents trends in NEET rates for Canada and other OECD countries (see Data sources and definitions). This is followed by a detailed examination of the characteristics of Canadian NEET youth, either unemployed or not in the labour force (NILF), with a focus on determining the activities of the latter group.
Note that the OECD calculates its NEET rates based on 'youth' age 15 to 29. In Canadian statistics, youth generally refers to the 15- to 24-year-old age group. This article follows the OECD convention, to maintain overall consistency with the NEET concept.
Germany had the lowest percentage of youth who were neither in education nor employed (11.6%) and Italy the highest (21.2%). Looking at NEET subcategories, 5.7% of Canadian youth were unemployed and 7.6% were not in the labour force (NILF). Similar to the other selected G7 countries, the overall NEET rate was lowest among teenagers and highest among the 25- to 29-year age group. In addition to the NEET rates, other related indicators include the duration of unemployment for NEET youth looking for work, and the reasons for not being in the labour force for the remaining NEET youth.
The OECD series further divides unemployed youth into those who have been searching for a job for less or more than six months. Although there is no standard definition of long-term unemployment, demarcations of longer than 6 or 12 months are often used (Dubé and Dionne 2005). Prolonged periods of unemployment can lead to financial hardship and lower levels of psychological well-being (Dubé 2004; Machin and Manning 1998).
The OECD NEET unemployment rates represent the number of unemployed or long-term unemployed as a percentage of the total youth population. This is a different calculation from the standard Labour Force Survey (LFS) unemployment and long-term unemployment rates, which represent these same populations as a percentage of the labour force (see Data sources and definitions). According to the data, the percentage of Canadian youth in long-term unemployment is relatively low compared with other OECD countries. In 2009, a year in the midst of the recent economic downturn, teenage long-term unemployment was virtually non-existent in Canada but ranged between 1.1% and 2.2% in all other OECD G7 countries (Chart A). Among youth over age 19, less than 1% were unemployed for more than six months in Canada, whereas for other countries the rates ranged from a minimum of 3.1% for United States (U.S.) youth age 20 to 24 to a maximum of 6.4% for Italian youth the same age. These findings confirm previous OECD research which found that Canada has consistently been among the few countries where youth have a “... very low incidence of long-term unemployment” (OECD 2010). Research into long-term unemployment has shown that North America generally has lower levels than most OECD countries (Machin and Manning 1998; Nickell 1997).
The reasons for youth being not in the labour force (NILF) are not available internationally but will be discussed later in the article for Canada.
The distribution of Canadian youth age 15 to 29 by education, employment and NEET status has changed over time. The overall NEET rate decreased from 22% in 1976 to 13% in 2011, mainly because of a decline in the NILF category for those age 20 to 24 and 25 to 29 (Table 2). This is a result of the influx of women into the labour force and out of the NILF category. In the years since 2008 and the start of the recent economic downturn, the NEET rate has been up by as much as 2 percentage points.
Since 1976, the percentage of youth attending school has steadily increased for all age groups—from 65% to 81% for those from age 15 to 19, 18% to 40% for those 20 to 24, and 7% to 13% for those 25 to 29. Over the past decade, there has also been a steady increase in the proportion of students age 15 to 24 who hold a job while attending school. This is particularly true for those age 20 to 24: since 2001, almost one-half of this group combine school and work.2 The high student employment rate may be linked to the relatively lower rates of long-term unemployment among Canadian youth. Many graduates will start looking for career employment with significant part-time work experience under their belt.
As the school attendance rate has risen, the percentage employed has fallen for both the younger age groups (15 to 19 and 20 to 24). Conversely, although the school attendance rate has increased for those age 25 to 29, the percentage employed has also increased from 65% in 1976 to 70% in 2011—again the result of the increasing employment rate of women.
In 1976, women accounted for 91% of NILF in the 25-to-29 age group compared with 67% in 2011. Furthermore, in 1976, among non-students, 41% of women were NILF versus 4% of men. In 2011, 14% of non-student women were NILF versus 7% of men (data not shown).
Following the recent downturn there have been small but significant decreases in the employment rates of students under age 20 and all non-students under age 30. At the same time, the overall NEET rate increased, as did the percentage of unemployed youth age 20 and over.
In 2011, 13% of youth age 15 to 29 (904,000 out of 6.8 million) were neither enrolled in school nor employed. The NEET population is equally divided between men and women (both with roughly 452,000) and most are older—79% of male NEET youth (355,000) are between the ages of 20 and 29, as are 85% of female NEET youth (382,000) (Chart B). While most older male NEET youth are unemployed (58% of those age 20 to 24 and 55% of those 25 to 29), most female NEET youth are not in the labour force (NILF) (65% of 20- to 24-year-olds and 70% of those 25 to 29). Since the type of NEET inactivity (unemployed versus NILF) varies considerably by age and sex, they will be analysed separately in the remaining sections.
Looking at all youth, 5.7% (391,000) were unemployed in 2011 (Table 3).3 This rate is lower than the standard unemployment rate because the denominator includes all youth, many of whom are not in the labour force—mainly students. This is why only a small percentage (3.1%) of all teenagers (15 to 19) are unemployed, since over 80% of them are in school. In absolute numbers, young men in their 20s account for more than one-half of unemployed NEET youth—200,000 out of 391,000.
The unemployed in relation to the labour force, or the LFS unemployment rate, is a better indicator of how non-student youth are doing in terms of finding employment. The LFS unemployment rate for 15- to 29-year-olds in 2011 was 11.8%. The rate was higher for teenage girls (18.7%), teenage boys (25.2%), men age 20 to 24 (15.7%), and those who had not graduated from high school (23.0%).
A logistic regression model was used to control for the relationship between age, education, and other factors possibly linked to being unemployed and in the labour force. The findings confirm that compared with men age 25 to 29, both younger age groups of men were significantly more likely to be unemployed. The rate for young women in all age groups did not differ significantly from the rate for men age 25 to 29.4
Having a higher level of education significantly reduced the probability of being unemployed. For example, compared with youth with a high school diploma, those with a university degree were less than two-thirds as likely to be unemployed (with an odds ratio of 0.6). Research has shown that the pursuit of higher education is positively associated with higher employment rates among youth (Hango and de Broucker 2007).
Youth who were married and without children were also significantly less likely to be unemployed compared with single youth. Finally, after controlling for other factors, youth living at home had significantly higher odds (1.5 times) of being unemployed than those not living at home, possibly reflecting the difficulty of living on one's own without a job.
Of the 391,000 unemployed youth in 2011, 55,000 had been looking for work for more than six months. This figure represents 1% of all youth from age 15 to 29 and 14% of the unemployed in this age group. This population is too small for detailed analysis, but simple cross-tabulations show that the majority comprises older youth—88% are age 20 to 29 (49,000 out of 55,000). Of the long-term unemployed in their 20s, 66% are men (Table 4). Also, 54% of the long-term unemployed youth in their 20s have a high school diploma or less, compared with 47% of all 20- to 29-year-olds.5 Young men age 20 to 29 are more likely than women to have a high school education or less (51% versus 42%), and those with lower levels of education have fewer employment opportunities and higher rates of unemployment (Hango and de Broucker 2007; Martin 2009).
The larger portion of youth neither in education nor employment (NEET) are not in the labour force (NILF)—7.5% (513,000) of all those age 15 to 29. More young women are NILF than men, 9.1% (305,000) versus 6.0% (208,000) (Table 5). More than one-third (117,000 or 38.4%) of NILF women are married with children compared with 6.7% of NILF men (14,000). Since family status has a different effect for men and women, the NILF data are shown in detail by sex.
Again, it is instructive to examine NEET NILF youth excluding the student population. In other words, if a youth is not going to school, it is important to understand his or her relationship with the labour market. Excluding students, what are the characteristics of the not-in-the-labour-force youth population?
Among the non-student population, 10.3% of men and 16.9% of women are NILF. Excluding students and after controlling for other factors, being married with children significantly increases the likelihood of women being NILF (3.1 times) and decreases it by about one-half for men (0.6) compared to being single. One-third (33.2%) of non-student, young married women with children are not in the labour force, compared with 6.3% of their male counterparts. This suggests that many young mothers are, at least temporarily, out of the labour force to care for young children.
Similar to the unemployed, fewer teenage girls and boys are NILF, since most are still in school. However, among teenagers not in school, 1 in 4 girls and boys are NILF. Compared with non-student youth in their 20s, teenagers are significantly more likely to be not in the labour force (1.5 times for boys and 1.3 times for girls).
Excluding students and after controlling for other factors, youth with higher levels of education are less likely to be out of the labour force. For example, youth with less than a high school diploma had the highest percentage not in the labour force (24.1% of men and 42.3% of women) while those with a university degree had the lowest (4.6% of men and 8.4% of women). The probability of being NILF is also significantly higher for men and women who were born outside Canada.
Unlike the 6% of NEET youth who are unemployed and looking for employment, the main activity of NEET youth not in the labour force is less clear. This may be part of the reason there are negative connotations associated with NEET youth overall—that is, to not be in education, not be employed, and not be looking for employment implies inactive and unproductive behaviour that can lead to a negative or problematic state. “There is a widespread current perception that being ‘NEET’ (not in employment, education or training) presents a major risk for young people of becoming socially excluded” (Yates and Payne 2006, p. 329). However, before NEET NILF youth can be labelled as 'at-risk,' it is important to determine what they are doing.
The Labour Force Survey, the data source used for the OECD NEET indicator, does not ask about non-labour-market activities of youth who are NILF. Furthermore, no information is collected on the duration of NILF spells, which, similar to unemployment, could be a potential issue if the NILF activity is counterproductive or cause for concern. Another data source, however, the Youth in Transition Survey (YITS), can provide some information on the length of any NEET spell. Although the type of NEET spell is not known (unemployment or NILF), recent research on NEET using YITS has shown that almost 40% of youth had been NEET for 5 months or longer at least once over the 5 cycles of the survey but “few appear to be in a permanent state of detachment.” The overall conclusion from the study found "that there is not a large sub-class of young Canadians who have become permanently detached from the schooling system or labour market” (Drewes 2011).
Some NILF youth report wanting a job despite not searching for one. Among this group of NILF job-wanters, the LFS asks why they did not search for a job during the reference week. This information gives some insight into the main activity and current status of a portion of the NILF population. Of the 513,000 NILF youth, one-fifth (18%) reported wanting a job but stated they had not looked for one (Table 6). Some of the reasons for not searching reflect a somewhat negative situation, such as being discouraged and believing no work is available (1%), waiting for recall to a former job or for replies from employers (2%), and being too sick to search (2%). However, for the largest group (7%) of NILF youth wanting a job, the reasons for not job searching are not known.
Most of the youth not in the labour force did not report that they wanted a job (418,000)—82% overall, 77% of men and 84% of women. For about one-half of this population, the main activity could be identified, and with the exception of youth permanently unable to work because of illness or disability, their situation was not indicative of a detachment from work or school. For example, 26,000 (5%) youth had a job that was to start or re-start in the future, 34,000 (7%) were students at other schools (see Data sources and definitions), and 103,000 (20%) had no recorded activity but had children at home (97,400 were women). The latter group likely includes parents at home caring for children.
For the remaining 226,000 NILF youth without children and not wanting work (44%), there is no information about their main activity, presumed or otherwise. The General Social Survey (GSS) is another data source that can help determine the activity of NILF youth. The GSS asks all respondents a question about what their main activity was during the preceding week—providing a similar, but not exact, OECD definition of NEET youth (see Data sources and definitions). The GSS findings show a comparable youth NEET rate to that of the LFS. In 2010, 15% of youth age 15 to 29 reported their main activity to be neither in school nor employed (NEET) during the previous week6 (Table 7).
Of the NEET NILF youth identified in the GSS, 50% reported child care as their main activity, 10% household work, and 31% fell into categories too small to report, such as maternity leave, volunteering, and “Other – Specify.” If Other –Specify was reported, respondents were asked to specify their main activity and interviewers were to write down the answer. Common write-in answers included leisure, March or school break, and playing sports. Examples of specific answers included being on sabbatical, doing a practicum, renovating, relaxing, and unemployed.7 Although it is not possible to determine from the GSS whether the NILF youth wanted or did not want a job, the activity information suggests that few youth are idle.
Since the late 1990s, the OECD and some European countries have added the NEET indictor to their analysis of youth in the labour market—referring to the proportion of the population age 15 to 29 who are neither in employment nor education. NEET youth fall into two groups—either unemployed and actively looking for a job or not in the labour force (NILF).
The indicator emerged in the United Kingdom during a time of concern over disadvantaged youth becoming discouraged and at risk of social exclusion. Intervention policies were introduced to reduce NEET rates. Due to this history, the NEET indicator is associated with at-risk youth. Critique of the indicator suggests that not all NEET youth are at risk, and specifically targeting this group may come at the expense of others in greater need of policy interventions (Yates and Payne 2006; Roberts 2011).
Canada has had a NEET rate of between 12% and 14% over the past decade, which is relatively low compared with other G7 rates. In 2011, 13.3% of youth were NEET—5.7% unemployed and 7.5% NILF—with the remainder students (43.7%) or employed (43.0%). The unemployed, in relation to the labour force, revealed an under-30 unemployment rate of 11.8%.
Unemployment for youth is often an expected stage between finishing school and finding a job and is not necessarily detrimental, especially if it is short-term. Relative to other countries, Canada had low proportions of long-term unemployed youth, representing 1% of all youth and 14% of unemployed youth. Lower levels of education were significantly tied with higher rates of unemployment and long-term unemployment. Men under 25 were also more likely to be unemployed than young men age 25 to 29 or young women.
Among those not in the labour force, 18% reported wanting a job despite not having looked for one. Among the remaining 82% of NEET NILF youth who did not want a job, 5% had future work arrangements, 6% were permanently unable to work, 7% were non-traditional students, 20% had no known activity but had young children at home, and 44% had no known activity and no children at home. Based on corresponding GSS data, many youth in this latter “unknown” category report a wide range of unpaid activities.
NILF youth not attending school had significantly lower levels of education than their counterparts in the labour force, after controlling for other factors. This suggests that some NILF youth may be having difficulty finding employment.
Canadian NEET youth have been shown to be a heterogeneous group with many in unemployment—likely to be short-term—and many others not in the labour force. However, this is not to say that there are not youth in the NEET category who are at risk of disengagement, like those experiencing long-term unemployment or those who would like a job but have given up looking because they do not believe any work is available.
The Labour Force Survey (LFS) is a monthly household survey that collects information on labour market activity from all persons 15 years of age and over. Respondents are also asked whether they are currently attending school and which type of school. The LFS employment and education information is used to create an indicator of youth who are neither in education nor employment (NEET), based on the Organisation for Economic Co-operation and Development (OECD) definition and methodology (see below).
The General Social Survey (GSS) is an annual household survey that collects information on a wide range of social trends and policy issues. Questions are asked of one household member age 15 or over and data collection takes place over the entire year. Each survey cycle asks about the main activity of the respondent during the past week. In order to gauge the regular activity of youth, all summer months are excluded from the calculations (May through August). All files include a set of bootstrap weights to help adjust for the survey design.
The target population is all individuals age 15 to 29, excluding those in the military. If the members of the military were to be included in the study they would be considered employed youth. Note that the OECD definition of youth is different from the standard for those age 15 to 24 generally used in the Canadian LFS.
The OECD NEET indicator is created from OECD and Eurostat databases, which are compiled from national labour force surveys. The data refer to the first three months of the calendar year (January, February, March), which is meant to exclude summer employment. Youth are divided into three main groups: those attending school in a regular educational system (whether part time or full time and whether they have a job while attending school); the employed (part time or full time and not attending school);, and those neither attending school nor employed (NEET). NEET youth are further categorized as unemployed (by duration of unemployment) or not in the labour force (NILF). Based on the OECD methodology, students attending “other” schools in Canada are not considered students in the indicator (OECD 2011).
Students are all individuals attending primary or secondary school, community college, junior college or Collèges d'enseignement général et professionnel (CEGEP), or university during the LFS reference week. For the purpose of this study, those attending other schools are not considered students. Examples of the other school category include personal interest courses that do not count towards a degree, certificate or diploma and credit courses that are employer-sponsored and employer-operated. In this study, 1% of all youth were attending some form of other school based on the OECD NEET definition, while roughly one-half were coded as employed youth and the remainder as NEET youth not in the labour force.
Employed youth are non-students who reported doing any work at a job or business or being temporarily away from their jobs during the interview period (the LFS reference week). For this study, employed students were classified in the student population.
Unemployed youth are non-students who, during the reference week, were without employment but were actively looking for work and were available to work, or were not actively looking for work but had been laid-off and expected to return to work, or had a new job to start within four weeks. The NEET unemployment rate refers to unemployed youth as a percentage of all youth, while the LFS unemployment rate refers to unemployed youth as a percentage of youth in the labour force (the employed plus the unemployed).
Youth Not in the Labour Force (NILF) refers to those who are neither employed nor unemployed and therefore not in the labour market. Normally students fall into the NILF category; however, for the purpose of analyzing NEET youth, students are not included in the standard NILF population and comprise their own “student” category. The NEET–NILF group can be further classified into those who reported wanting a job, despite not looking, and those who did not report wanting a job. A derived variable from the LFS lists the reasons why NILF youth wanted a job but did not search for one.
Youth are defined as living with parents when they are listed as the son or daughter of the reference person of the household. The reference person must be one of the adult household members who have responsibility for the care or support of the family. It is assumed that youth living at home are in households where one of the parents has been identified as the reference person. Youth who identify themselves as the reference person, spouse of the reference person, or other relative are classified as not living with parents.
In this study, 23% of youth were married (including common-law) and 77% were single (including 1% of youth who were widowed, separated or divorced).
When youth are recorded as the reference person or spouse of the reference person it is possible to determine whether they have their own children at home. The vast majority of married youth are coded as the reference person or spouse of the reference person (94%). Single-parent youth not living with their parents can also be identified but are not a focus of this study. It is not possible to determine whether youth living at home have their own children, however, 99% of youth living with their parents are single.
Logistic regression models were used to examine the probability of being unemployed in the labour force and the probability of not being in the labour force within the non-student population. Multicollinearity diagnostic tests were run for all models. Since it is not possible to use the LFS variance estimation program to take the complex survey design into account for regression models, a more conservative level of statistical significance (<.001) was set to ensure reliable results. Coefficients of variation were produced for all other LFS estimates using the jackknife estimation program with significance levels set at <.01.
Bell, David N.F. and David G. Blanchflower. 2010. Young People and Recession: A Lost Generation? Economic Policy: 52nd Panel Meeting, October 22-23, 2010. University of Stirling, Stirling, Scotland. Centre for Economic Policy Research. 36 p. (accessed May 10, 2012).
Bynner, John and Samantha Parsons. 2002. “Social exclusion and the transition from school to work: The case of young people not in education, employment, or training (NEET).” Journal of Vocational Behavior. Vol. 60, no. 2. April. p. 289-309. (accessed May 10, 2012).
Drewes, Torben. 2011. NEETs in Canada. Presented at the 2011 Socio-Economic Conference, September 26–27 in Gatineau. Peterborough, Ontario. Trent University. p. 26.
Furlong, Andy. 2006. “Not a very NEET solution: Representing problematic labour market transitions among early school-leavers.” Work, Employment and Society. Vol. 20, no. 3. p. 553-569.
Hango, Darcy and Patrice de Broucker. 2007. Education-to-Labour Market Pathways of Canadian Youth: Findings From the Youth in Transition Survey. Statistics Canada Catalogue no. 81-595-MIE – No. 054. Culture, Tourism and the Centre for Education Statistics Research Paper. Ottawa. 80 p. (accessed May 10, 2012).
Machin, Stephen and Alan Manning. 1998. The Causes and Consequences of Long-Term Unemployment in Europe. No. 400. London.Centre for Economic Performance, London School of Economic Performance and Political Science. 41 p. (accessed May 10, 2012).
Marshall, Katherine. 2010. “Employment patterns of postsecondary students." Perspectives on Labour and Income. Vol. 11, no. 9. September. Statistics Canada Catalogue no. 75-001-XIE. (accessed May 10, 2012).
Martin, Gary. 2009. “A portrait of the youth labor market in 13 countries, 1980–2007." Monthly Labor Review. Vol. 132, no. 7. July. p. 3-21. (accessed May 10, 2012).
Nickell, Stephen. 1997. “Unemployment and labor market rigidities: Europe versus North America." The Journal of Economic Perspectives. Vol. 11, no. 3. Summer. p. 55-74. (accessed May 10, 2012).
Organisation for Economic Co-operation and Development. 2011. "Annex 3: Sources, Methods and Technical Notes. Chapter C: Access to Education, Participation and Progression." Education at a Glance: OECD Indicators 2011. 32 p. (accessed May 10, 2012).
Quintini, Glenda and Sébastien Martin. 2006. Starting Well or Losing Their Way? The Position of Youth in the Labour Market in OECD Countries. OECD Social, Employment and Migration Working Papers. No. 39. Paris. Organisation for Economic Co-operation and Development. OECD Publishing. 72 p. (accessed May 10, 2012).
Roberts, Steven. 2011. “Beyond ‘NEET’ and ‘tidy’ pathways: Considering the ‘missing middle’ of youth transition studies.” Journal of Youth Studies. Vol. 14, no. 1. February. p. 21-39.
Social Exclusion Unit. 1999. Bridging the Gap: New Opportunities for 16–18 Year Olds Not in Education, Employment or Training. Presented to Parliament by the Prime Minister by Command of Her Majesty. London.Her Majesty’s Stationery Office (HMSO). 123 p. (accessed May 10, 2012).
Yates, Scott and Malcolm Payne. 2006. “Not so NEET? A critique of the use of ‘NEET’ in setting targets for interventions with young people.” Journal of Youth Studies. Vol. 9, no. 3. July. p. 329-344.
Katherine Marshall is with the Labour Statistics Division. She can be reached at 613-951-6890 or email@example.com.