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Evidence from unexpected temporary school closures and reduced instruction time suggests school closures will reduce educational achievement, both in the short and long term. Children from disadvantaged backgrounds are likely to be affected more than others by school closures, with fewer family resources and less access to online learning resources to offset lost instruction time. In England, the total cost of the resources lost in each week of state school closure is more than £1 billion. Educational deficits from time lost to school shutdowns can be made up with additional hours of teaching when schools reopen, though schools might need to put back more hours than were lost and it may not be feasible to do this within the traditional school year. Compensating lost instruction time through additional resources, without additional hours, is likely to be even more expensive.

Recent research has established that teachers matter for student achievements, albeit because of dimensions of 'teacher quality' that are largely unexplained. A less closely investigated issue is whether teacher turnover directly harms student academic achievement. In this paper, we examine whether teacher turnover affects academic achievement of 16 year old state secondary school students using a unique data set of linked students and teachers in England. Identification comes from either: a school fixed effects design which exploits year-on-year variation in turnover in different subject groups, within schools; or student fixed effect design that where the variation comes from the cross sectional variation in turnover in different subjects, in the same school, experienced by a student. Both methods give similar results, suggesting that a higher teacher entry rate reduces students' test scores, albeit by small amounts.

Education policy worldwide has sought to incentivize school improvement and facilitate pupil-school matching by introducing reforms that promote autonomy and choice. Understanding the way in which families form preferences during these periods of reform is crucial for evaluating the impact of such policies. We study the effects on choice of a recent shock to the English school system--the academy programme--which gave existing state schools greater autonomy, but provided limited information on possible expected benefits. We use administrative data on school applications for three cohorts of students to estimate whether academy conversion changes schools' popularity. We find that families--particularly non-poor, White British ones--rank converted schools higher on average. Expected changes in composition, effectiveness and other school policies cannot explain this updating of preferences. Instead, the patterns suggest that families combine the signal of conversion with prior information on quality, popularity and proximity as a heuristic for assessing a school's expected future performance. The following are appended: (1) Robustness checks; and (2) Estimating Academies' Effectiveness using Legacy Enrolled Pupils. [This paper was produced as part of the Centre for Economic Performance's Education and Skills Programme.]

This report provides an overview and discussion of the past decade of academic evidence on the causal effects of resources in schooling on students' outcomes. Early evidence lacked good strategies for estimating the effects of schools resources, leading many people to conclude that spending more on schools had no effect. More recent evidence using better research designs finds that resources do matter, but the range of estimates of the impacts is quite wide. The review devotes special attention to differences across the early years, primary and secondary phases. Theoretical work has indicated that interventions early in a child's life may be more productive than interventions later on. However, although there are more examples of good quality studies on primary schooling, the existing body of empirical work does not lead to a conclusive case in favour of early interventions. Three appendices present: (1) Differences in characteristics between high and low-resource schools; (2) Benchmarking and Comparing the Size and Strength of Effects Across Different Studies; and (3) An illustration of the theoretical model (one in which events in one period depend on events in previous periods) used by Nobel-laureate, James Heckman in his argument for the efficacy of early investment in children over investment at a later stage. [This work was commissioned by Ofsted as part of the "Access and Achievement in Education--20 Years On" project.]

Existing research shows that house prices respond to local school quality as measured by average test scores. However, higher test scores could signal better quality teaching and academic value-added, or higher ability, sought-after intakes. In our research, we show decisively that value-added drives households' demand for good schooling. However, prior achievement--linked to the background of children in school--also matters. In order to identify these effects, we improve the boundary discontinuity regression methodology by matching identical properties across admissions authority boundaries; by allowing for boundary effects and spatial trends; by re-weighting our data towards transactions that are closest to district boundaries; by eliminating boundaries that coincide with major geographical features; and by submitting our estimates to a number of novel falsification tests. Our results survive this battery of experiments and show that a one-standard deviation change in either school average value-added or prior achievement raises prices by around 3%. (Contains 6 tables, 3 figures and 13 footnotes.)

Improvement of educational attainment in schools in urban, disadvantaged areas is an important priority for policy--particularly in countries like England which have a long tail at the bottom of the educational distribution and where there is much concern about low social mobility. An anomaly in the spatial dimension of school funding policy in England allows us to examine the effect of increasing school expenditure for schools in urban areas. This anomaly arises because an "area cost adjustment" is made in how central government allocates funds to Local Authorities (school districts) whereas, in reality, teachers are drawn from the same labour market and are paid according to national pay scales. This is one of the features that give rise to neighbouring schools on either side of a Local Authority boundary being allocated very different resources, even if they have very similar characteristics. We find that these funding disparities give rise to sizeable differences in pupil attainment in national tests at the end of primary school. This finding lends adds to the evidence that school resources have an important role to play in improving educational attainment and has direct policy implications for the current "pupil premium" policy in England. (Contains 3 figures, 9 tables and 20 footnotes.)

There are large disparities between the achievements, behaviour and aspirations of children growing up in different neighbourhoods. This has contributed to the view that neighbourhoods can determine individuals' outcomes. Notably, in the long run these effects could lead to larger social inequality and reduce social mobility, which is why they have attracted much attention among researchers and policy makers alike. In fact, many area-based policy responses are predicated on the idea that a young person's outcomes can be causally linked to the characteristics of the childhood neighbourhood, and to the social interactions with children and adolescents who live around him/her. While economists and sociologists have proposed a number of theories to explain potential causal links between place of residence and socio-economic outcomes, empirical evidence has been largely inconclusive. This is because empirical neighbourhood effects research is complicated by two sets of problems. The first problem is that the observed correlation between children's outcomes and neighbourhood characteristics could just be a statistical artefact resulting from general income segregation. Secondly, there is ambiguity in the definition of what constitutes a neighbourhood. As a result, empirical studies have used very different spatial aggregations to delimit the unit of analysis. With these issues in mind, the authors take advantage of a very detailed and spatially disaggregated dataset to examine the existence of social interaction effects in neighbourhoods in England. More specifically, their goal is to answer the following questions: (1) To what extend are school test scores at ages 14 and 16 influenced by the academic quality and other characteristics of other children of similar age who live in the same neighbourhood?; and (2) To what extend are behavioural outcomes of children--such as attitudes towards school truancy, substance use and anti-social behaviour--affected by the academic achievement and other characteristics of children in the neighbourhood? The authors' initial results confirm the existence of a strong cross-sectional association between neighbourhood characteristics and children's outcomes. However, these findings cannot be interpreted as causal and mainly reflect a spurious correlation that arise because of individual sorting and neighbourhood unobserved attributes. In fact, once they control for pupil and family background unosbervables as well as neighbourhood fixed effects, their previously significant estimates become very close to zero and non-significant. In a nutshell, their main results are as follows: (1) There is no evidence that neighbours' characteristics have a causal effect on the cognitive outcomes of 14 to 16 year old children arising from social interactions and role models; and (2) There is weak evidence that the neighbourhood effects are causally linked to young people's behavioural outcomes. However, there is some interesting heterogeneity along the gender dimensions regarding attitudes towards school and anti-social behaviour. All in all, this evidence is in line with the most robust research in the field that identifies neighbourhood effects using randomised control-trials experiments such as the Movement to Opportunity intervention or the Gautreaux programme. Appended are: (1) Descriptive statistics before dropping mobile pupils and small neighbourhoods; (2) Additional results: change-in-change and unobservable effects estimates; (3) Selected descriptive statistics for pupils sampled by the LSYPE (aged 14 in 2004); (4) Population in the neighbourhood and mobility rates; and (5) Constant-cohorts dataset construction; three "main cohorts" and asymmetric peers. (Contains 11 tables, 5 figures and 18 footnotes.)

In England, the "Every Child Matters" (ECM) initiative has driven important changes in educational services in order to support five key outcomes for children and young people identified by the ECM initiative, namely to "be healthy", to "stay safe", to "enjoy and achieve", to "make a positive contribution" and to "achieve economic wellbeing". The question then arises as to whether these kinds of objectives can be met in the current school context, where policy makers and parents tend to evaluate schools' excellence on the basis of academic achievement and pupils' test scores. With these issues in mind, the authors consider whether parental perceptions of school quality are based on academic standards and aligned with the wellbeing of the children. They examine children's attitudes towards their school along three dimensions: general happiness, relationships with teachers and intellectual stimulation. In parallel, they consider parents' judgement of overall school quality, and their views on teachers' relationships with their child and the progress that their child is making at school. The authors' main goal is to answer two related research questions, that is: (1) To what extent are attitudes and experiences, amongst pupils and their parents, linked to standard test-score based measures of academic performance?; and (2) To what extent are parents' perceptions of school quality linked to their children's happiness and enjoyment of school? To do so, they use direct information on stated perceptions in the Longitudinal Survey of Young People in England (LSYPE) matched to UK administrative records on pupil achievements. Their analysis reveals the following key findings: (1) Parents' judgement of school quality is dominated by school average test scores, over and above other school characteristics. This is true for parents from different backgrounds and with children of all abilities; (2) However, children's self-reported happiness and satisfaction with their learning environment is unrelated to average test results in their school: children are just as happy in schools where average test scores are low as in schools where average test scores are high; (3) Parents' satisfaction and judgements of school quality are not strongly correlated with their children's enjoyment of school. Any correspondence between the subjective views of parents and children is better explained by shared family characteristics, than by anything "objective" the authors can observe about schools; and (4) Schools which receive more favourable parent and child ratings tend to have higher local house prices, but not once the authors control for standard test-based measures of school performance (such as school value-added). This reinforces the evidence that school quality as measured by test scores tends to dominate parental perceptions of educational excellence. Finally, the authors' findings show that pupil enjoyment at school is only very loosely related to school academic performance or its composition. This implies that policies that seek to address child wellbeing at school might have to be decoupled from policies that seek to raise academic standards. Appended are: (1) Details on self-reported variables and data construction; and (2) Estimating school attendance zones for housing market analysis. (Contains 11 tables and 8 footnotes.)

Commuting or re-location costs could be an in important influence on students' university choices and might even deter some from going to university. The barriers presented by these costs may be high for lower-income students, and students for whom there are cultural incentives to remain in or close to the parental home. If this is the case, then the geographical accessibility of universities has an important bearing on differences in higher education choices for different income and ethnic groups, and, in turn, on their earnings and life chances. Existing evidence has shown that university places are not evenly spatially distributed in Britain. Research has also found that "non-traditional" students--those from backgrounds in which higher-education participation is emerging--cite the location of institutions as a factor affecting their decision to go in to higher education. However, it is easy to make the mistake of attributing behaviour to ethnicity, gender or income when these behaviours are really due to other differences, like academic achievement, or home location which will have strong bearing on if and where students go to university. In fact, there is no large scale, systematic evidence for the UK that shows that proximity to a university really matters for higher education participation or choice amongst universities, or that it matters more for specific ethnic or income groups. The authors' research looks at these questions using administrative data on the population of school leavers and university entrants in England. These data allow the authors to link the choices of students from different ethnic and income backgrounds to distances between home and university, whilst accounting for schooling, neighbourhood and other background characteristics. Their key findings are: (1) Universities are not evenly distributed around the country but 90% of locations have three institutions and 4000 first degree places within 100km; (2) Non-white ethnic groups and low-income students actually live closer to their nearest three higher education institutions and closer to their nearest three high-quality research institutions than their white and high-income counterparts. These facts suggest that disparities in geographical access are unlikely to be a source of disadvantage to ethnic minorities and poor students; (3) Home-to-university distance has only a tiny influence on the probability of participation in higher education, relative to achievement and other background factors. Their statistical models imply that doubling the distance to the nearest institution would reduce the probability of white female participation by at most 4.5% in relative terms--reducing the probability of participation at the mean from 28.4% to 27.1%. For males, the effect is only half that, but there are no systematic differences by ethnic or income group; (4) In contrast, distance is the strongest factor influencing university choice amongst those who participate. The probability that a student attends a specific university decreases by 8%-15% with each 10% increase in home-to-university distance. This distance cost is observed for all ethnic and income groups, but is highest for Pakistani and Bangladeshi girls and low income students, and lowest for Black students and those from Professional backgrounds; and (5) The influence of distance on choice of institution could make a difference to the type of higher education received by different demographic groups. This is a moot point for ethnic minorities, who have high participation rates at "elite" research intensive universities relative to whites, but provides a potential explanation for lower participation rates amongst women and low income groups in top ranked research universities. The findings therefore offer no support for the idea that improving the accessibility of higher education institutions is an effective route to raising participation. However, targeting the accessibility of higher-quality institutions could increase uptake of high quality HE places amongst suitably qualified students from lower-occupational status backgrounds. Such policies might include action to reduce the role of distance (distance learning) but also policies to encourage higher status institutions to undertake outreach activities further afield. In any case, the authors find no evidence to suggest that such a policy need be gender or ethnically targeted. One further important spatial implication from this work is that the type and quality of higher education in which students enroll is in part governed by the type and quality of local institutions, which in turn partly determines the skill composition of the local population. Given this, the local mix of institution types and quality could have a strong bearing on the quality and composition of the local human capital stock. (Contains 11 tables, 4 figures and 23 footnotes.)

There is a large gap in higher education attainment between different groups of society, especially along gender, class and ethnic dimensions. Reducing these gaps in attainment has been at the forefront of policy makers, not only in this country but also in most advanced economy with policies ranging from financial support to positive discrimination. However, policies can only be effective if the reasons behind these gaps are understood. This research explores another reason why individuals from specific group do not invest in higher education. The authors postulate that they may have misbelieves in their own ability and under estimate their chance of success. To test this hypothesis the authors rely on two datasets. The first is the 2003 PISA (Programme for International Student Assessment) which surveyed 15 year old, and administered a comprehensive test in mathematics. The second dataset is based on an online survey of first year students in two British universities. The authors find that males overestimate their own performance in math and English, as well as their position in the score distribution. Relative to students with the most favourable background, working class students under-estimate their performance in math and white students under-estimate their relative position in both math and English. The gender and class gaps are especially large in numeracy, at around 20% of the average score. Self-perception also correlates with educational confidence in general but the effect is small. The effect of self-perception on the decision to participate in higher education does not seem to work through its effect on risk aversion and the returns to higher education, because self-perception is only weakly correlated with these factors. Policies that raise academic self-confidence in schools are, unsurprisingly, likely to raise participation rates but are unlikely to close participation gaps unless targeted only at underrepresented groups. This is not to suggest that students should be praised whatever their results but on the contrary, trained to develop objective views about their own ability. (Contains 7 tables, 3 figures and 23 footnotes.)

We consider the influence that mobile pupils have on the academic achievements of other pupils in English primary schools. We find that immobile pupils in year-groups (a la US "grades") that experience high pupil entry rates progress less well academically between ages 8 and 11 than pupils in low-mobility year groups (grades), even within the same school. The disruptive externalities of mobility are statistically significant, but actually very small in terms of their educational impact. An increase in annual entry rates from 0 to 10% (a 4 standard deviation change) would set the average incumbent pupil back by between 1 and 2 weeks, or about 4% of one standard deviation of the gain in pupil achievement between ages 7 and 11. (Contains 1 figure, 7 tables and 7 footnotes.)

We explore the association between urban density and pupil attainment using three cohorts of pupils in schooling in England. Although--as widely recognised--attainment in dense urban places is low on average, this is not because urban environments disadvantage pupils, but because the most disadvantaged pupils with low average attainments attend the most urbanised schools. To control for this, we exploit changes in urban density faced by pupils during compulsory transition from Primary to Secondary school, and measure educational progress at the end of the Secondary phase, relative to attainments at the end of Primary schooling. Our results suggest that there are small but significant benefits from education in schools in more densely urbanised settings: Pupils in schools in relatively dense places--measured in terms of school density and other urban indicators--progress faster than others in their cohort, but the elasticity is low, at around 0.02. We detect this density advantage even amongst pupils moving relatively short distances between Primary and Secondary schools within urban areas, so we cannot attribute it to broad urbanisation effects experienced by pupils making rural-urban school moves. A more likely explanation lies in greater school choice and competition between closely co-located educational providers. Estimation of Two-Way Fixed Effects is appended. (Contains 6 tables, 1 figure and 18 footnotes.)

The issue of social segregation in schools has seen a recent resurgence of interest--in the US, UK and internationally--as the debate rages on about whether policies that expand families' freedom to choose amongst schools encourage divergence or convergence in the types of pupil different schools admit. Most attention has been focussed on segregation along lines of ethnic or social background. Yet, the real consideration that seems to be in the back of most people's minds is the issue of segregation or stratification of schools along lines of pupil ability. We look explicitly at this issue using data on the population of pupils entering Secondary school in England from 1996 to 2002. Our study does highlight wide disparities between peer-group ability in different schools. But we also find that, contrary to popular opinion, almost nothing has changed over these years in terms of the way pupils of different age-11 abilities are sorted into different Secondary schools. Appended are: (1) Construction of the smoothed inverse-cumulative distributions; (2) Table 6: Sample sizes in base year; (3) Table 7: Factor analysis of pupil test scores, London 1996; (4) Figure 3: Bootstrap 95% Confidence interval on inverse-cumulative distribution, London, 1995; (5) and Table 8: Cell sizes for school types in Table 4. (Contains 2 figures, 8 tables, and 17 footnotes.)

We provide estimates of the effect of attending a Faith school on educational attainment progress during the Primary education phase in England. We argue that there are no credible instruments for Faith school attendance. Instead, we control for selection on religious schooling by tracking pupils over time and comparing attainments of students who exhibit different levels of commitment to religious education through their choice of Secondary school and residence. Our findings suggest that, once family preferences and selection into religious education are controlled for, Faith schools have only a very small effect on pupil educational progression in Primary school, this effect being between zero and under one-percentile on test scores at age 11, conditional on scores at age 7. Appended are: (1) Additional tables; and (2) Denominational differences. (Contains 14 tables and 20 footnotes.)

It is a common belief that children will thrive if educated amongst better class and schoolmates. It is a belief that guides many parents in their choice of school, and has important implications for policy on school choice and organisation. Many studies have tried to measure this "peer-group" effect, but the enterprise is plagued by conceptual and empirical difficulties. In this study, we use the population of state Secondary school pupils in England to tease out how pupil attainments at age 14 respond to differences in the prior, age-11 attainments of their current school grade peer-group. Data on home addresses and school attendance allow us to compare outcomes of children who live in the same street, or who attended the same Primary school up to age 11, but then move on to different Secondary schools with different peer-group quality. These "peer-group" effects seem to exist, but they are small in magnitude--a 1 s.d. increase in peer-group prior attainments allows a pupil to improve their own score by barely 0.08 of a standard deviation. We tackle various gnarly empirical problems arising in regression models of pupil attainments that incorporate individual and group prior attainments as explanatory variables. Estimates from such models are seriously biased by transient components in prior pupil attainments, correlation between current and prior peer-group characteristics and by ability sorting into Secondary schooling. We address these issues by using teachers predictions as instruments for prior attainments, defining a pupil's current peer-group in terms of those school mates with whom he or she has had no contact in the past, and by predicting current peer-group attainments with the productivity of their origin Primary schools, measured by the gain in attainments of different cohorts between ages 7 and 11. (Contains 1 figure, 7 tables, and 14 footnotes.)

The expansion of school choice and greater competition between schools is currently the centrepiece of government educational policy in the UK. There is an increasing emphasis on parents' right to choose their preferred schools, and whilst many parents may value choice itself, the advocates of these market oriented reforms usually argue that the main benefits are to force educational providers to improve standards. In this study we look to see whether we can find any empirical foundation for these claims amongst the primary school population in the south east of England. Our key findings are that: (1) Pupils who have a wider choice of schools at their place of residence perform no better than those with more limited choice; (2) Secular schools located in places where they face strong competition from other schools perform no better than secular schools in more isolated, monopolistic settings; (3) Church schools seem to respond more positively to competition, particularly from other church schools. We have some evidence to show that pupils in more isolated church schools perform less well than those in competitive church school "markets"; (4) The benefits of competition seem strongest amongst pupils in church schools with the highest concentrations of low-income children; and (5) On balance, choice and competition does not seem to be generally effective in raising standards in the school context. Although the issue has been widely researched, especially in the US, existing evidence on the beneficial effects of competition on educational achievements is at best mixed, and does not provide a solid ground for policy conclusions. We use a large administrative census of primary school pupils in London and the surrounding area. This allows us to improve on the existing literature along two dimensions. First, exploiting pupil residential details and information on school location, we construct separate "choice" and "competition" indices and study their impact on pupil attainment. Choice is a property of pupil residential location, and depends on the schools from which a family can feasibly choose. Competition is a property of schools, and depends on the number of institutions competing for the same pool of pupils. Secondly, we make use of the fact that institutional barriers limit school attendance outside the Local Education Authority (LEA) of residence and that, as a result, very few pupils cross district boundaries to attend primary school. Because of this, pupils near LEA boundaries face less choice and schools near LEA boundaries tend to face less competition. We can use this feature of the admissions system to help solve the difficult issues of reverse causation arising from the fact that school performance may influence the patterns of choice and competition that we observe. Controls, summary statistics are appended. (Contains 6 figures, 9 tables and 21 footnotes.)