- 6. Data on Mechanisms As well as considering Ofsted reports we study mechanisms by looking at survey results from the Department for Education (2014), head teacher change and teacher turnover.
Paper not yet in RePEc: Add citation now
Abdulkadiroglu A., J. Angrist, P. Hull and P. Pathak (2014) Charters Without Lotteries: Testing Takeovers in New Orleans and Boston, National Bureau of Economic Research Working Paper 20792.
Abdulkadiroglu A., J. Angrist, S. Dynarski, T. Kane and P. Pathak (2011) Accountability and Flexibility in Public Schools: Evidence From Boston's Charters and Pilots, Quarterly Journal of Economics, 126, 699-748.
- Adonis, A. (2012) Education, Education, Education: Reforming England’s Schools, Biteback Publishing.
Paper not yet in RePEc: Add citation now
Altonji, J., T. Elder and C. Taber (2005) Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools, Journal of Political Economy, 113, 151-84.
Angrist J., P. Pathak and C. Walters (2013) Explaining Charter School Effectiveness, American Economic Journal: Applied Economics, 5, 1-27.
Angrist J., S. Cohodes, S. Dynarski, P. Pathak and C. Walters (2014) Stand and Deliver: Effects of Boston's Charter High Schools on College Preparation, Entry and Choice, mimeo.
Angrist J., S. Dynarski, T. Kane, P. Pathak and C. Walters (2010) Inputs and Impacts in Charter Schools. KIPP Lynn, American Economic Review, 100, 239-43.
- Appendix Data Description 1. Data on Academy Schools We first identified all schools that became academies over the school years 2002/03 to 2010/11. Our sources for this are Department for Education extracts that give information on all academies that have opened or are in the process of doing so. The extract gives the opening date of the academy, its URN (a unique identifier for the school allowing us to identify it in various governmental data sources such as the National Pupil Database and the Pupil Level Annual Census data), DFE number (a second unique identifier combining school specific and local authority specific numbers) and the URN number of the predecessor school.
Paper not yet in RePEc: Add citation now
- b - Academy schools (prior to 2010/11): all ability independent specialist schools, which do not charge fees, and are not maintained by the local authority; established by sponsors from business, faith, HE institutions or voluntary groups, working in partnership with central government. Sponsors and the DfE provide the capital costs for the Academy. Running costs are met by the DfE in accordance with the number of pupils, at a similar level to that provided by local authorities for maintained schools serving similar catchment areas.
Paper not yet in RePEc: Add citation now
- Bloom, N., R. Lemos, R. Sadun and J. Van Reenen (2015) Does Management Matter in Schools?, Economic Journal, 125, 647-74.
Paper not yet in RePEc: Add citation now
- c - City Technology Colleges: all ability independent schools, which do not charge fees, and are not maintained by the local education authority. Their curriculum has a particular focus on science and technology education (see West and Bailey, 2013). They were established by sponsors from business, faith or voluntary groups. Sponsors and the DfE provided the capital costs for the CTC. Running costs are met by the DfE in accordance with the number of pupils, at a similar level to that provided by local authorities for maintained schools serving similar catchment areas. d – Voluntary-aided schools are maintained by the local authority. The foundation (generally religious) appoints most of the governing body.
Paper not yet in RePEc: Add citation now
- Center for Research on Education Outcomes (2009) Multiple Choice: Charter Performance in Sixteen States, Stanford University, CREDO.
Paper not yet in RePEc: Add citation now
Clark, D. (2009) The Performance and Competitive Effects of School Autonomy, Journal of Political Economy, 117, 745-83.
- Department for Children, Schools and Families (2007) Academies and Independent Schools: Prospectus http://dera.ioe.ac.uk/6578/1/Academies_Prospectus.pdf.
Paper not yet in RePEc: Add citation now
Department for Education (2013) Types of schools. http://www.education.gov.uk/schools/leadership/typesofschools Department for Education (2014) Do Academies Make Use of Their Autonomy? https://www.gov.uk/government/publications/do-academies-make-use-of-theirautonomy 31 Dobbie W. and R. Fryer (2011) Are High Quality Schools Enough to Close the Achievement Gap? Evidence From a Social Experiment in Harlem, American Economic Journal: Applied, 3, 158–87.
Dobbie W and Fryer R (2013) Getting Beneath the Veil of Effective Schools: Evidence from New York City, American Economic Journal: Applied, 5, 58–75.
- e - Foundation (formerly grant-maintained) schools are maintained by the local authority. The governing body is responsible for admissions, employing the school staff, and either the foundation or the governing body owns the school’s land and buildings (DfE, 2013).
Paper not yet in RePEc: Add citation now
Evans W. and R. Schwab (1995) Finishing High School and Starting College: Do Catholic Schools Make a Difference?, Quarterly Journal of Economics, 100, 941-74.
Eyles, A., C. Hupkau and S. Machin (2015) Academies, Charter and Free Schools: Do New School Types Deliver Better Outcomes?, Centre for Economic Performance mimeo.
- Eyles, A., S. Machin and O. Silva (2014) Academies 2: The New Batch, Centre for Economic Performance mimeo.
Paper not yet in RePEc: Add citation now
- f – Voluntary-controlled schools are maintained by the local authority. These are mostly religious schools where the local authority continues to be the admission authority. Land at voluntary-controlled schools is usually owned by trustees, although the local authority often owns any playing field land (DfE, 2013). g - Community schools are maintained by the local authority. The local authority is responsible for admissions, employing the school staff, and it also owns the school’s land and buildings.
Paper not yet in RePEc: Add citation now
- Figure 5: Event Study Instrumental Variable Estimates of Pupil Performance and Academy Conversion, Key Stage 4, Year 11 Pupils By Cohort -.2 0 .2 .4 .6 Estimated Coefficient and 95% CI c-4 c-3 c-2 c-1 c c+1 c+2 c+3 Event Time (c = Year of Academy Conversion) 2002/03 and 2003/04 Cohort 2004/05 and 2005/06 Cohort 2006/07 and 2007/08 Cohort 2009 Cohort KS4 of Pupils Enrolled in Year 11 by Cohort Pupil Performance and Academy Conversion, IV Estimates Notes: From cohort specific estimates of column (9) specification of Table 6. Table 1 - Characteristics of Autonomy and Governance in English Secondary Schools Non-LA Admission Authority Maintained by NonLA body Not obliged to follow National Curriculum Fee Charging Registered independent schoola Academyb City technology collegec Voluntary-aidedd Foundatione Voluntary-controlledf Communityg Notes: a - Registered independent schools are independent of the local authority (LA), and are fee-charging.
Paper not yet in RePEc: Add citation now
- Finally it is worth noting that PLASC does not cover years prior to 2002. For our observations before then we do still have NPD data on KS2 and KS4 performance (we have these going back to 1997 for KS4 and 1996 for KS2). Therefore these observations are missing all demographic covariates with the exception of gender. Similarly in our fake policy results the only covariates, aside from year dummies and school fixed effects, are pupil gender. This is why, in Table 9, we reproduce our main specification without covariates so as to make the fake and actual policy results comparable.
Paper not yet in RePEc: Add citation now
- For the teacher and pupil analysis we use data from the annual schools census. The data gives us the number of qualified and unqualified teachers at all maintained secondary schools for the years 2001-2009. We weight the total number of teachers, at the school level, by the number of pupils of compulsory secondary schooling age (11-15) relative to the total number of pupils in the school. This prevents a potentially spurious relationship between the number of teachers and academy conversion caused by many schools opening 6th forms post-conversion. The weighted number of teachers, total pupils in compulsory secondary schooling along with the ratio of these two variables form the dependent variables in Table 14. Controls are the same as those reported in Table 11.
Paper not yet in RePEc: Add citation now
Fryer, R. (2014) Injecting Charter School Best Practices into Traditional Public Schools: Evidence From Field Experiments, Quarterly Journal of Economics, 129, 1355-1407.
- Gorard, S. (2014) The link between Academies in England, pupil outcomes and local patterns of socio-economic segregation between schools, Research Papers in Education, 29, 268284.
Paper not yet in RePEc: Add citation now
Green F., S. Machin, R. Murphy and Y. Zhu (2012) The Changing Economic Advantage From Private School, Economica, 79, 658-79.
Hanushek E. and L. Woessmann (2011) The Economics of International Differences in Educational Achievement, in Hanushek E., S. Machin and L. Woessmann (eds.) Handbook of the Economics of Education, Volume 3, Amsterdam: Elsevier.
Hanushek E. and L. Woessmann (2015) The Knowledge Capital of Nations: Education and the Economics of Growth, MIT Press.
Hoxby C. and S. Murarka (2007) Methods of Assessing Achievement of Students in Charter Schools, in Behrens, M. (ed.) Charter School Outcomes. The Analytic Press, New York Hoxby C. and S. Murarka (2009) Charter Schools in New York City: Who Enrolls and How They Affect Student Achievement, National Bureau of Economic Research Working Paper 14852.
Hsieh, C. and M. Urquiola (2006) The Effects of Generalized School Choice on Achievement and Stratification: Evidence from Chile's Voucher Program, Journal of Public Economics, 90, 1477-503.
http://www.nao.org.uk/publications/1011/academies.aspx. Accessed 12 March 2011 Neal, D. (1997) The Effects of Catholic Secondary Schooling on Educational Achievement, Journal of Labor Economics, 15, 98-123.
- In order to have a balanced panel we focus on academies that have some form of predecessor school open from at least 1996 onwards. Any later and the school will not have KS4 results for 2001. In order for our sample to be balanced for intake we exclude academies who do not enrol pupils in year 7. The final sample contains 106 treatment schools (those that opened as academies prior to, or in, September 2008) and 114 control schools with observations ranging over the years 2000/01-2008/09. None of our control schools become academies during these sample years.
Paper not yet in RePEc: Add citation now
Machin S. and J. Vernoit (2011) Changing School Autonomy: Academy Schools and their Introduction to England’s Education, Centre for the Economics of Education Discussion Paper 123.
- Machin S. and J. Wilson (2008) Public and Private Schooling Initiatives in England: The Case of City Academies, in Chakrabarti R. and P. Peterson (eds.) School Choice International. MIT Press, Cambridge MA.
Paper not yet in RePEc: Add citation now
- National Audit Office (2010) Department for Education: The Academies Programme.
Paper not yet in RePEc: Add citation now
OECD (2011) School Autonomy and Accountability: Are They Related to Student Performance?, PISA Focus 2011/9.
- Post 2005 there are 4 possible inspection ratings – outstanding, good, satisfactory and inadequate. Prior to 2005 the possible ratings given were excellent, very good, good, satisfactory, unsatisfactory, poor and very poor. To measure whether academies improve over time we equate the 7 ratings given prior to 2005 into the 4 categories given post 2005 in the following manner: Prior to 2005 Post 2005 Excellent, very good Outstanding Good Good Satisfactory Satisfactory Unsatisfactory, poor, very poor Inadequate Our main interest is whether schools converting to academies are more likely to improve their rating relative to the control schools. 33 Throughout this and the other mechanisms section school refers to the variable school that we cluster on as described in the treatment section of the appendix – all mechanism regressions are performed at this level. 34 Overall effectiveness ratings have been awarded since 2000.
Paper not yet in RePEc: Add citation now
- Table 2 - Number (Percent) of Secondary Schools in England, 2001/02 and 2008/09 Number (Percent) of Secondary Schools by Type 2001/02 2008/09 Academy 0 (0.0) 133 (4.0) City technology college 14 (0.4) 3 (0.1) Voluntary aided 549 (15.8) 537 (16.0) Foundation 501 (14.4) 560 (16.7) Voluntary controlled 129 (3.7) 111 (3.3) Community 2278 (65.6) 2017 (59.9) Total 3471 3361 Notes: Source – School Census. Includes middle schools. Excludes special schools. This is partially available from Tables 2.1 and 2.2 in http://webarchive.nationalarchives.gov.uk/20120504203418/http://education.gov.uk/rsgateway/DB/VOL/v000359/dfes_schools_final.pdf and Table 2a in http://www.education.gov.uk/rsgateway/DB/SFR/s000925/sfr09-2010.pdf.
Paper not yet in RePEc: Add citation now
- Table 3: The Nature of Academy Conversions All Schools Pre-Academy School Type All New Independent City technology college Voluntary aided Foundation Voluntary controlled Community All academies 244 12 5 12 18 34 2 161 Become academies, up to 2008/09 133 12 5 12 10 15 1 78 Future academies, after 2008/09 111 0 0 0 8 19 1 83 All Schools With Full Data (Pre- and Post-Academy Conversion) Pre-Academy School Type All New Independent City technology college Voluntary aided Foundation Voluntary controlled Community All academies 220 0 0 12 15 33 2 158 Become academies, up to 2008/09 106 0 0 12 10 15 1 68 Future academies, after 2008/09 114 0 0 0 5 18 1 90 Notes: Source for upper panel, same as Table 2. Source for lower panel, own calculations from Edubase, School Performance Tables and Annual Schools Census.
Paper not yet in RePEc: Add citation now
- Table A5: Structure of Fake Policy Sample Key Stage 4 (Year 11) E = c-11 c-10 c-9 c-8 c-7 c-6 c-5 c-4 c-3 c-2 c-1 Number of Conversions 2002/03 459 468 475 427 399 3 2003/04 1072 1090 1086 1020 1128 1115 7 2004/05 248 214 259 278 263 302 301 2 2005/06 1011 995 1006 986 1069 1149 1200 1145 8 2006/07 2313 2352 2310 2341 2346 2520 2603 2499 15 2007/08 4308 4246 4378 4305 4561 4611 4796 4653 29 2008/09 6655 6706 6635 6749 6858 7220 7227 7468 39 Notes: E denotes event year and c is the year of conversion. Sample sizes and number of academy conversions by cohort for the fake policy sample used in columns (1) and (2) of Table 9.
Paper not yet in RePEc: Add citation now
- The governing body is responsible for admissions and employing the school staff. Land at voluntary-aided schools is usually owned by trustees, although the local authority often owns any playing field land (DfE, 2012).
Paper not yet in RePEc: Add citation now
- Using performance tables data from the Department for Education (DfE) we match in predecessor school types. The data gives 244 schools that became academies between the first 3 academy openings in 2002/03 and those that gained academy status by September 2010 (the beginning of the academic school year). We omit those that were previously independent schools due to pupils in these schools not having exam information at KS4. Similarly, we omit new schools as they have no predecessor school.
Paper not yet in RePEc: Add citation now
- We collect data on head teachers using edubase and match a head teacher to each of our schools for each year (excluding 2001 for which data are not available) in our sample. For each year we define a binary variable equal to 1 if this year’s head teacher is different from last years. When two schools merge we set this variable to 1 only if the head is not the head of either of the predecessors. When two separate schools are defined as being the same (with respect to the clustering variable) we set this variable to 1 if either school change their head teacher in that year. Controls in this linear model are the same as those reported in Table 10.
Paper not yet in RePEc: Add citation now