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Abstract
Many young people have short spells of unemployment during their transition from school to work; however, some often get trapped in unemployment and risk becoming long-term unemployed. Much research has been undertaken on the factors that influence unemployment risk for young people during their school-to-work transition. However, very little is known about the factors associated with long-term unemployment (LTU) risk for those youths who become unemployed. This article attempts to fill this gap in the literature by identifying the characteristics associated with young peoples’ LTU risk in Ireland. The research, which is conducted using multivariate statistical analysis, uses a combination of unemployment register data and information gathered from a specially designed claimant questionnaire that was issued to all jobseekers making an unemployment benefit claim between September and December 2006. The results indicate that factors such as a recent history of LTU, a lack of basic literacy/numeracy skills and low levels of educational attainment, all have a significant impact on the likelihood that young people will remain unemployed for 12 months or more. A number of attributes are gender-specific, such as the presence of children, additional welfare benefits and spousal earnings for females and apprenticeship training and participation in a public sector job creation scheme for males. Comparisons with the characteristics associated with older welfare claimants LTU risk reveal some interesting difference between younger and older unemployed individuals.
Notes
2. Defined as those aged 15–24 years of age.
3. As a percentage of total unemployment.
6. No empirical support has been identified for institutional factors (for example, wage-bargaining institutions, union density and the extent of youth activation and training measures) having an impact on youth unemployment risk during the school-to-work transition phase (Müller and Gangl Citation2003). However, Breen (Citation2005), using data from 27 OECD countries, found that, in general, youth unemployment was higher in labour markets that had legislation that restricted employers in their ability to dismiss workers. Using a panel of 19 OECD countries, Jimeno and Rodriguez-Palenzuela (Citation2002) also found that labour market institutions (the unemployment benefit system, extent of active labour market policies, wage determination, the tax wedge and employment protection legislation), along with demographic and macroeconomic variables, had a positive impact on youth unemployment. Unfortunately, we do not have the data to investigate the impact of structural factors, such as economic sector or type of contract of previous employment, on young peoples’ LTU risk in this paper, but we are hoping to collect these data in future data-sets so that the issue can be looked at in future research.
7. Some descriptive analyses have been undertaken on youth LTU. For example, based on labour force survey data from 25 countries, the OECD (Citation2005) found that there are wide differences across countries in the proportion of young adults who are long-term unemployed and that this cross-country discrepancy appears to be related to educational attainment (see also Quintini and Martin Citation2006). Russell and O'Connell (Citation2001) have looked at the factors that influence the transition from unemployment to work among young people but not specifically the characteristics associated with LTU risk. Malmberg-Heimonen and Julkunen (Citation2006) analysed the impact of immigrant status on the exit routes from unemployment among longer-term unemployed youths but they did not address the question of what initially determines if a young unemployed person becomes long-term unemployed.
8. Alhawarin and Kreishan (Citation2010) did not find that education had a strong effect in predicting LTU in Jordan, and Livanos (2007) obtained a similar result for Greece.
9. Some research exists on the determinants of unemployment risk (see, for example, Arai and Vilhelmsson Citation2004, Thapa Citation2004) but less on the factors associated with becoming long-term unemployed.
10. Recent research for Ireland suggests that the positive relationship between education and earnings/employment continued to hold for 2000–2007 (Voitchovsky et al. Citation2012), and more recent descriptive data would suggest that this positive relationship continues.
11. Persons unemployed as a percentage of all persons in the population.
12. Persons unemployed as a percentage of all persons in the population.
13. The CE scheme, which is Ireland's main public sector job creation programme, is operated by the national employment and training agency FÁS. The scheme is designed to help long-term unemployed and other disadvantaged individuals to get back to work by offering part-time and temporary placements in jobs based within local communities.
14. JA and JB are Ireland's two unemployment benefits. JA is a means-tested payment and JB is based on social insurance contributions.
15. Checks undertaken on the survey non-respondents (using data from the Live Register) to ensure that they did not differ significantly from those who answered the questionnaire revealed that both samples were almost identical: a slightly higher proportion of non-respondents were non-Irish but the difference was minor and we are confident that our sample is representative of the total unemployment benefit claimant population.
16. We made two adjustments to our initial leaver sample: (1) individuals whose JA or JB claims were closed at the end of the 65-week period but who moved across to alternative benefits were redefined as stayers and (2) individuals who had exited the Live Register by week 65 but who had accumulated 52 weeks or more of unemployment duration were redefined as stayers because they met the criteria for LTU. One adjustment was also made to the stayer sample: any claimant who had left the Live Register for a substantial period (i.e. for more than six weeks) during the 65-week observation period was redefined as a leaver.
17. Logit and probit models.
18. The pattern of results from the probit model is consistent with those of a Cox Proportional Hazard model (results available from the authors).
19. Data available from the authors on request.
20. County controls are included in each model: the results are not presented here but are available from the authors on request.
21. The spousal earnings and CE scheme results need to be interpreted with caution as the number of observations on which each coefficient is estimated is quite small.
22. Males are the reference category.
23. Results for the older claimant probit models, both male and female, are available from the authors on request.
24. Older male and female claimants are the respective reference categories in each model.