“Applications of the NPD in Academic Research: Some Examples from the Centre for the Economics of Education” Joan Wilson, CEE, CEP, IoE DCSF, York, Friday September 21st 2007

What is the Centre for the Economics of Education (CEE)? A multidisciplinary centre with 3 partners: Centre for Economic Performance at LSE (CEP); Institute for Fiscal Studies (IFS); Institute of Education (IoE). Conduct research into the field of the economics of education using the latest techniques of empirical analysis. Consider research problems relating to all stages of the education sequence. Areas we work in: returns to education; adult learning; link between family background & educational attainment; early years education; segregation between schools; pupil mobility; and ICT use in education. Most recent focus of the Centre: using new sources of administrative data to understand the processes governing achievement in schools. Headed by Professor Stephen Machin (Research Director at the CEP, Affiliated to the IFS, and Professor of Economics at UCL).

Past CEE Projects Using the NPD (1) School Choice and School Competition “Choice, Competition and Pupil Achievement” (Stephen Gibbons, Stephen Machin and Olmo Silva, July 2006) Distinction is made between the two concepts of choice and competition. Assess whether pupils in Primary schools in England with a wider range of school choice achieve better academic outcomes than those for whom choice is more limited. Consider whether Primary schools facing more competition perform better than those in a more monopolistic situation. Find little evidence of a link between choice and achievement. Only for Voluntary Aided schools, which have more freedom in managing their governance and admission practices, is there some evidence of a positive causal link between competition and pupil achievement.

School Choice and School Competition (cont.) “Are Schools Drifting Apart? Intake Stratification in English Secondary Schools” (Stephen Gibbons and Shqiponje Telhaj, December 2006) Consider social segregation in schools. Assess whether policies that expand families’ freedom to choose amongst schools encourage divergence or convergence in the types of pupil different schools admit. Address segregation or stratification of schools along lines of pupil ability, using data on the population of pupils entering Secondary school in England from 1996 to Find that almost nothing has changed over these years in terms of the way pupils of different age-11 abilities are sorted into different Secondary schools. Past CEE Projects Using the NPD (2)

Current CEE Projects Using the NPD (1) School Quality and House Prices “What Do Parents Want From a School? Evidence from Housing Prices” (Stephen Gibbons, Stephen Machin and Olmo Silva) Assess the influence of school quality on house prices. Construct de-facto school catchment areas using information on pupil home addresses and school attendance. Linkage to property price data to provide accurate estimates of the housing costs associated with admission to each school in England. Measure the way these housing costs change with school characteristics, geographically and over time, so as to unpick the key components of school quality that are valued by home-buyers. Questions: Do families who want to gain access to high ‘quality’ schools have to pay a house price premium? Does this house price premium reflect preferences for high academic performance or the desire by some families to ‘segregate’? (i.e. is the premium related to a school’s ethnic/social composition?)

Current CEE Projects Using the NPD (2) Higher Education Participation “Widening Participation in Higher Education” (Alissa Goodman, Stephen Gibbons, Stephen Machin, Sandra McNally, and Anna Vignoles)  The expansion of higher education in the UK has meant that a far larger proportion of young people are going to university.  Previous CEE research suggests that this expansion has largely benefited better off students.  Understanding the factors driving higher education participation and the barriers to participation is an important social policy question.  Examine the importance of being near to a learning institution, in terms of encouraging participation post-school and specifically in higher education.  Question: Do poor students who live near a university have a greater chance of attending university?

Current CEE Projects Using the NPD (3) Mobility “Geographical Mobility, Pupil Mobility and Child Outcomes” (Joan Wilson) Pupil mobility refers to the movement of pupils between schools at times other than the normal stages of transition. Considered to have negative consequences for children who move school, as well as for pupils in the new school and the overall performance of the new school that they move to. Evidence from the NPD: Mobile pupils are more socially disadvantaged than non-mobile pupils and are significantly less likely to have a good prior education record. Of the mobile pupils, children from better off backgrounds are more likely to end up in a school with better KS performance than the one they left. Question: Is there a scope for mobility to change the trajectory of child outcomes (e.g. if changes in schooling and/or residence allow for access to improved school quality)? Tie in the NPD to survey data such as the LSYPE and the MCS.

Our Use of School Census Information These projects use the following linked data sources:- National Pupil Database (NPD) records, including:-  Pupil Level Annual School Census (PLASC)  Key Stage records of attainment And: Annual School Census files Edubase Data School Performance files Potentially sensitive information used in some projects:- Pupil home postcode (PLASC) Pupil ethnicity (PLASC) School postcode (EDUBASE)

Why do we need such information? Data linkage: raises issues of ethics, confidentiality and privacy of the subjects. Data is linked via an anonymous unique pupil reference number and/or a unique school reference number. In our projects the most confidential level of information we use is the home postcode of the pupil. How do we get access to it? Make individual or group applications to the DCSF for permission to receive and use sensitive data such as pupil home postcode. Exact details of the project are set out, including why the use of sensitive data is vital to the feasibility of a project relative to other, more aggregated, available data. How do we present such information? Through aggregated tables of results: summary statistics and empirical regression results. We do not present very low-level micro analysis of a particular school or small group of schools or individual pupil-level behaviour.