WP6: Educational Services Indicators
Objective: To develop indicators for Education, including output, inputs and productivity and quality adjustments using outcomes.
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WP6 leader: Jorgen Mortensen ( This e-mail address is being protected from spambots. You need JavaScript enabled to view it )
Full details of the workpackage can be found in the description of work.
WP6 will be concerned with indicators for educational services. It will consider alternative measures of output of the educational system, including conventional measure of number of pupils and students educated at different levels (cost weighted), the average duration of education and an indicator for inequalities in educational attainment through the calculation of an “education GINI coefficient”.
The second task in measuring indicators for education is to examine the use of outcomes both to quality adjust output measures and in their own right as measures of performance. This will investigate how to incorporate standard outcome measures but will also consider the feasibility of including experimental measures. It will make use of the PISA standardised academic achievement tests, arguably the best available evidence on quality in schools.
Two additional methods for quality adjustment in education will also be reviewed. The first will use quality measures from ratings scales such as ECERS (Early Childhood Environment Rating Scale) and from provider inspection data collected by Ofsted (the Office for Standards in Education) for the UK. It will assess how well school quality indicators as measured by Ofsted and other rating scales can predict a range of outcomes for children at different stages of compulsory schooling. This will enhance measures which focus exclusively on attainment at the end of compulsory schooling, by considering outcomes at different stages of compulsory schooling using outcome data which reflect not only academic attainment but other broader goals of education including health, safety, enjoyment and social contribution.
The second potentially useful approach is to use earnings of age cohorts as a quality adjuster. This captures the idea that the relative earnings of younger workers to the population as a whole today are different to the relative earnings of younger workers say a decade ago. In this work we will evaluate the usefulness of an approach that assumes that differences between younger and older workers stem from the skills taught in the education sector.
Finally, using the data above WP6 will produce provisional estimates of labour productivity and total factor productivity growth of the education sector and analyse the sensitivity of these measures to various adjustments for quality.
