UNDERSTANDING INEQUALITIES IN THE LABOUR MARKET PROF ROBERT RAESIDE DR VALERIE EGDELL DR HELEN GRAHAM EMPLOYMENT RESEARCH INSTITUTE EDINBURGH NAPIER UNIVERSITY SDS Research Symposium, Edinburgh Napier University, 16 March 2016

Workshop overview  Labour market inequalities: key trends  Young people seeking work  Access to job related training  Demand side issues and future job trends  Implications for policy and practice

 Young people have always been more likely to be unemployed, but the gap has widened over the last decade Labour market inequalities: key trends Unemployment rate in Scotland, by age group, Source: ONS Regional labour market statistics: HI11 Headline indicators for Scotland allabourmarket/february2016

 The gap between male and female unemployment widened after the recession, although it is narrowing Labour market inequalities: key trends Unemployment rate in Scotland, by gender, Source: ONS Regional labour market statistics: HI11 Headline indicators for Scotland allabourmarket/february2016

 Unemployment is associated with area deprivation, although it is also itself an indicator of deprivation Labour market inequalities: key trends Unemployment rate in Scotland, by area deprivation, Source: Local Area Labour Markets in Scotland - Statistics from the Annual Population Survey Jan-Dec 2013: Web Tables - 15% Most Deprived Areas

 Those with a minority ethnic background are somewhat more likely to be unemployed Labour market inequalities: key trends Unemployment rate in Scotland, by ethnic background, Source: Annual Population Survey data, obtained via Nomis

 There is a strong association between qualification holding and employment, and the gap has widened over the last decade Labour market inequalities: key trends Employment rate in Scotland, by qualification level, Source: Local Area Labour Market in Scotland - Statistics from the Annual Population Survey 2014: Web Tables - Local Authority

Looking at young people seeking work  Photovoice research with young people engaged in employment support programmes.  Young people want to find work, and often have a specific job in mind. However, they may feel a pull to accept any job that comes along.  They may feel disadvantaged in the job market compared to others; excluded due to forces beyond their control.  They may not feel that employers are willing to give them a chance - employers do not offer them opportunities because they lack experience.  They do not feel that school gives them the right skills for finding work. Not all are able to undertake work experience opportunities at school.  Some felt that attending the programmes had opened up their eyes to the opportunities available to them. Source project: SocIEtY (Social Innovation – Empowering the Young for the Common Good). Funding: The research leading to these results has received funding from the European Union's Seventh Framework Programme FP7 under grant agreement n° See for project outputs:

“You hear everybody moan about I haven’t got a job, I don’t know what I am meant to do, like I am going to be on the dole. Well you’re like if you actually sat down like and figured out what you wanted and decided and made like a life plan. I don’t even have a life plan but...” (Young female) “They have been telling us careers and that I didn’t even know, I knew you could do, but I didn’t think that I could do with my qualifications and everything. They’re kind of helping us get a bigger range” (Young female)

“That’s what it was meant to be, something from here you were, where you wanted to be, and how you’d get there or something like that... [Photograph 1 is] where I was... And [Photograph 2] is where I want to go” (Young male)

Access to job related training (I)  Labour Force Survey, 2000 to 2014  “In the 3 months since [date] have you taken part in any education or any training connected with your job or a job that you might be able to do in the future?”  The first step of the analysis was to look at the training patterns for different age groups (16-19, 20-24, 25-49, and 60+) over the 15 year period  Then we built statistical models to find out what factors might affect participation in training  Look into the trend of change with the factors over the 15 year period Full report available: Chen, T. et al. (2015) Job-related training in the UK from 2000 to 2014: Insights from the LFS. In: Report on the Quantitative Case Studies. SocIEtY: Social Innovation - Empowering the Young for the Common Good. Report to the European Commission

Access to job related training (II)  The young and middle-aged groups showed a similar general pattern of the proportion receiving training rising ( ), falling ( ) and rising ( ) and falling ( ) again. The pattern among the older age groups (50-59 and 60+) differs with the proportion receiving training increasing, with almost no large fluctuations.  Factors associated with a higher likelihood of receiving training included: holding higher levels of qualification and spending longer in full-time education; working full-time; working in the public administration, education and health industries; working in a professional or associate professional occupation; working for a larger employer; having fewer dependent children in the household; and being unmarried.  Younger age groups are more likely to have undertaken training, even after controlling for other factors that might influence the likelihood of training.  But there is evidence that the proportion of young being trained has reduced during the Great Recession and the youngest group 16 to 19 is most affected.  There is also some evidence that older workers are getting proportionately more training.  Consequences of denying training lead to failure to develop talent.

Demand Side  Skill inflation  Employment policies – incurs risk averseness  Demand for experience  Outsourcing – especially low skilled work  End of careers  Technology  Minimum wage

Future Jobs Frey, C. B. and Osborne, M. A. (2013) The Future of Employment: How Susceptible are Jobs to Computerisation? Bakhshi, H. et al. (2015) Creativity Vs Robots, NESTA,

20 years from now? Not Pretty – Bill Gates  Skills lost to Bots  Population ageing  UK response – four scenarios 1. Force flexibility - business as usual 2. The great divide – have and have nots 3. Skills activism 4. Innovation adaption  Safer jobs – creativity – knowledge intensive  Low skill – caring – but expensive  Future might level the inequalities playing field Yet huge gender imbalance regarding women in computing – less than 20% of computer science degrees awarded to women – even lower proportion in computer science management roles.

Implications for policy and practice  How should policy address these inequalities in the labour market?  How can you address these inequalities in the labour market in your own professional practice?  What challenges might there be in addressing these inequalities in the labour market in policy and practice?  How will inequalities be effected by future pressures on jobs?

Prof Robert Raeside: Dr Valerie Egdell: Dr Helen Graham: Follow us on Twitter: Contacts