IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Resources and standards in urban schools

Listed author(s):
  • Machin, Stephen
  • McNally, Sandra
  • Meghir, Costas

Do resources matter? This question remains controversial in the economics of education as many studies find no relationship between school resources and educational outcomes. Yet, improving educational performance, especially of ‘hard to reach’ children, is a key area for government policy. This is particularly the case in countries like the UK and the US where the fact that many adults have poor basic skills is frequently attributed to people being ‘let down’ by the education system. In the UK, particular attention has been paid to schools in inner-city areas, where many pupils face problems of socio-economic deprivation and where there has been a concern about educational underachievement for many years. We study a flagship policy of the UK government – the Excellence in Cities (EiC) programme – which has been designed to address these problems. This enables us to consider not only whether this particular policy was successful, but also to contribute to the more general debate as to whether resources matter and in what circumstances. We look at the distributional impacts of resources in a way that is not addressed by much of the existing literature. Excellence in Cities was launched in 1999 in over 400 secondary schools in England and since then progressively increased in coverage. It is now implemented in about a third of all secondary schools (over 1,000 schools). The policy involves allocating resources to Partnerships of Local Education Authorities (LEAs) and LEA maintained schools within their respective regions. Since there is considerable heterogeneity in the degree of disadvantage and school performance within LEAs, the policy does not cover every disadvantaged or poorly performing school in England and hence it is possible to find a comparison group of schools outside the policy. The three core strands of EiC are as follows: Learning Mentors, to help students overcome educational or behaviour problems; Learning Support Units, to provide short-term teaching and support programmes for difficult students; and a Gifted and Talented programme, to provide extra support for 5-10 per cent of pupils in each school. Other aspects of the EiC policy are the designation of particular schools as Specialist (i.e. in particular subjects) or Beacon (to disseminate good practice). Schools which are successful in their application for such status receive significant amounts of money. Finally, EiC also involves the creation of City Learning Centres (to provide ICT facilities) and Education Action Zones (where there is an emphasis on the sharing of good practice). We evaluate the average impact of EiC on educational attainment and attendance at school over time since its introduction in 1999. Thus, we assess the extent to which the whole range of activities carried out as a result of EiC funding led to an improvement in important educational outcomes. We focus on pupil-level attainment at age 14 (the end of Key Stage 3) and a measure of school attendance (the percentage of half days missed). We consider variation in the effect of the policy according to when it was introduced to different areas; time since its introduction; the level of disadvantage of the school (and of pupils of different abilities within these schools). Our methodology is based on a comparison between outcomes in schools where the EiC has been in place and schools in an appropriate comparison group before and after the policy was introduced. Specifically, we use a difference-in-differences approach that is combined with statistical matching. Our results show a positive effect of EiC on pupil attainment in Mathematics (though not in English) and on school attendance. A simple assessment suggests that the policy is cost-effective – at least for more recent years. However, the effect of the policy is heterogeneous along a number of dimensions: it is stronger the longer the policy has been in place; for disadvantaged schools; for medium-high ability pupils within disadvantaged schools. Our results show that ‘resources matter’ but that it is difficult to help the ‘hard-to-reach’ using this level of resources (i.e. low ability children within disadvantaged schools). For such children, different and probably more intensive policy treatments may be required – ideally earlier in their schooling career.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
File Function: Open access version.
Download Restriction: no

Paper provided by London School of Economics and Political Science, LSE Library in its series LSE Research Online Documents on Economics with number 3650.

in new window

Length: 40 pages
Date of creation: Feb 2007
Handle: RePEc:ehl:lserod:3650
Contact details of provider: Postal:
LSE Library Portugal Street London, WC2A 2HD, U.K.

Phone: +44 (020) 7405 7686
Web page:

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

in new window

  1. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 497-532.
  2. Bénabou, Roland & Kramarz, Francis & Prost, Corinne, 2009. "The French zones d'éducation prioritaire: Much ado about nothing?," Economics of Education Review, Elsevier, vol. 28(3), pages 345-356, June.
  3. Kenneth Y. Chay & Patrick J. McEwan & Miguel Urquiola, 2005. "The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools," American Economic Review, American Economic Association, vol. 95(4), pages 1237-1258, September.
  4. Victor Lavy & Analia Schlosser, 2005. "Targeted Remedial Education for Underperforming Teenagers: Costs and Benefits," Journal of Labor Economics, University of Chicago Press, vol. 23(4), pages 839-874, October.
  5. Carneiro, Pedro & Heckman, James J., 2003. "Human Capital Policy," IZA Discussion Papers 821, Institute for the Study of Labor (IZA).
  6. Richard Blundell & Monica Costa Dias & Costas Meghir & John Van Reenen, 2004. "Evaluating the Employment Impact of a Mandatory Job Search Program," Journal of the European Economic Association, MIT Press, vol. 2(4), pages 569-606, June.
  7. Krueger, Alan B & Whitmore, Diane M, 2001. "The Effect of Attending a Small Class in the Early Grades on College-Test Taking and Middle School Test Results: Evidence from Project STAR," Economic Journal, Royal Economic Society, vol. 111(468), pages 1-28, January.
  8. Alan B. Krueger, 2003. "Economic Considerations and Class Size," Economic Journal, Royal Economic Society, vol. 113(485), pages 34-63, February.
  9. Janet Currie, 2001. "Early Childhood Education Programs," Journal of Economic Perspectives, American Economic Association, vol. 15(2), pages 213-238, Spring.
  10. Stephen Machin & Sandra McNally & Costas Meghir, 2004. "Improving Pupil Performance in English Secondary Schools: Excellence in Cities," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 396-405, 04/05.
  11. Eric A. Hanushek, 2003. "The Failure of Input-Based Schooling Policies," Economic Journal, Royal Economic Society, vol. 113(485), pages 64-98, February.
  12. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 533-575.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:3650. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (LSERO Manager)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.