Further Education: Social Mobility, Skills and Second Chances

For the past five years we have carried out a series of investigations with colleagues at the Education Datalab (Fischer Family Trust) that shed new light on the value of learning in Further Education (FE) in England, using matched ILR-WPLS administrative data (including, Thomson et. al., 2010; Buscha and Urwin, 2013; Bibby et. al., 2014; Cerqua and Urwin, forthcoming 2015a; 2015b; Bibby et. al., 2015; forthcoming 2015a; 2015b). This programme of analysis has uncovered good returns to learning at all levels of FE, and challenges the previous findings from survey-based studies that estimated insignificant, or even negative, returns to learning at Level 2 and below. There is a recognition that the ILR-WPLS administrative data overcomes many of the limitations faced by previous surveyed-based studies and in this latest of reports (below) we consider the role of Further Education in Social Mobility, Skills and Second Chances; with the CER Director, Professor Peter Urwin, providing an accompanying personal note of what he thinks the findings from this programme of work imply for policy.

We are very grateful to the Department for Business Innovation and Skills for access to the data and especially Adrian Jones, who has worked on development of the data for many years. We are also grateful to the Department for Education for data access.

Most of the reports produced in this programme of research have been commissioned by BIS (though this is not true of the latest report below), and we also thank the 157 Group for financial support.

Please note that the views expressed in this report, or any others as part of this series, are those of the authors, and are not necessarily supported by any of the funders of research.

 

Social mobility research

Dr Franz Buscha has been awarded a highly prestigious ESRC grant to examine trends in intergenerational mobility in England and Wales. Over a period of 18 months Franz will be working jointly with Professor Patrick Sturgis (Southampton) to analyse Census data to see how social mobility has developed since the 1970s. Their proposal was deemed excellent with a high potential for academic and policy impact and was strongly supported by the Sutton Trust and the Deputy Prime Minister’s Office.

Housing policy in high-density global cities: a cost benefit model of sub-market rental accommodation in Central London

Peter Urwin has been awarded an important contract by the Dolphin Square Foundation (DSF). DSF provides good quality, affordable homes for people in Central London whose work is particularly valuable to the local economy. The project will provide DSF with estimates of the costs and benefits of their approach to the supply of affordable housing (through rental agreements), compared to alternatives that exist in the market at present.

Working with HMRC

In providing Econometric support to staff in KAI (HMRC, 2010-2014) we have developed a deep understanding of the specific challenges faced by HMRC staff tasked with evaluation in the areas of, for instance, SDLT and Income tax; estimates of elasticity in models of Tobacco and Alcohol consumption; and we have also been involved in supporting HMRC staff to tackle the challenges they face in evaluating programmes aimed at SMEs, for instance, gauging the impact of Venture Capital Trusts (VCT) and the Enterprise Investment Scheme (EIS). In all of this we have supported staff in their interpretation of quantitative evaluation evidence to inform decisions over policy impacts.

We have also delivered the (very well received) sessions for senior HMRC staff on the Use of Evidence and Analysis in Decision-Making (2009). These sessions for senior HMRC staff were delivered across the country, in Manchester, Newcastle, Birmingham and London, with 94 percent of participants agreeing that the course was ‘very good’ or ‘good’. The discussions with operational staff, as well as those tasked with policy, have provided us with further insight into the workings of HMRC and the subject-specific knowledge required to effectively support development of evidence-based evaluation.