Why are pupils from disadvantaged families more often found studying in poorly performing schools? Is it choice or is it constraint? Is it because the families choose local schools despite low performance? Or is it because the school admissions system which focusses on proximity to school works against poorer families?
New research from CMPO, IFS and Cambridge shows that differences in constraints in school choice between households of high and low socio-economic status drives the unequal allocation of pupils across schools much more than differences in preferences.
Our research looked at the choices of primary schools made on the Local Authority application form for thousands of families in England (using the Millennium Cohort Study). We first show that there are substantial differences in the academic quality of the local schools for families in different socio-economic groups. On average, the richest socio-economic quintile of families have schools nearby that get grades 46% of a standard deviation than those available to families in the poorest fifth of families.
On top of that is a second layer of difference. When popular schools have more applicants than places, there has to be some mechanism to ration those places. The most widespread criterion in England is proximity – families living closer to the school are given priority. Our study shows that this adds a substantial further difference to the quality of available schools – the gap in average school quality for the richest and poorest fifth of families is one third greater when considering schools feasible in terms of distance and the probability of admission. It is this criterion that is responsible for a significant component of inequality in access to high-performing schools.
The figure shows the mean school academic quality available to families across the socio-economic spectrum, differentiating between those that are nearby but not necessarily feasible (“local”) and those that are have a high probability of admission once we take account of the proximity rule (“proximity”).
Of course it could still be true that differences in preferences are much more important than these differences in available choices. But our analysis shows that this is not the case. Different families have different sets of schools to choose from: richer families choose between schools that on average have higher performance than poorer families. The differences in school choices made between households with higher and lower socio-economic status therefore largely reflects differences in the available schools.
Our research related families’ choices of school to the attributes of all local and feasible schools to estimate the strength of the families’ preferences for these attributes. We also investigated the variation in observed preferences between socio-economic groups. Our results show that families care about three main school attributes: the academic quality of the school, its socio-economic composition, and the home-school distance. The majority of households prefer schools with higher academic standards. On average, families prefer schools with fewer children living in low-income households. Almost all households have strong preferences for a school near where they live. Preferences differ across socio-economic (SES) groups: those in the lowest SES group in particular have distinct preferences, with a preference for lower academic quality and a higher proportion of pupils from low-income backgrounds, on average. Households from each SES group value proximity to the same extent, however.
In summary, households from different SES groups face differences in the type of schools available, but also have different preferences to some extent. Both factors may contribute to the unequal presence of pupils from different SES groups in different schools: we wanted to know which factor was more important. Because of the spatial clustering of our survey data, the majority of our sample share feasible school choice sets with at least one other household. This allows us to control for all the characteristics of the choice sets (technically, to define choice set fixed effects) and therefore to compare the choices of households from different SES groups confronted with exactly the same feasible school choices. This allowed us to decompose the overall relationship between SES and the academic quality of the chosen school into a component due to different preferences and a component due to differences in school quality across feasible choice sets. We show that the constraints account for two thirds of the overall observed difference. These constraints are largely driven by admissions criteria (principally the proximity criterion), which means that choice is restricted for some households.
To address these questions we assembled a unique dataset. We used survey information on parents’ primary school choices and a rich set of family socio-economic and neighbourhood characteristics. We linked this to administrative data on the characteristics of schools, and the nature of the local school choice mechanism. To identify parents’ constraints in terms of available school choices, we used the national pupil census with embedded spatial information to model de facto catchment areas around schools within which there is a high probability of admission.
The broader implications of our results for choice in education are mixed. Most parents in our data have a strong preference for schools with high academic attainment. This supports the idea that competition to meet these preferences should help to raise the standards in England’s schools. The measure of academic attainment we use is an absolute measure of test scores as this is what parents are most likely to be familiar with, and not an estimate of school effectiveness. How schools try to increase their test scores, either through increasing effectiveness or manipulating their intake of pupils, is therefore another important question in the chain between parental preferences and school effectiveness.
Our results confirm parents’ preference for a school near to home. We are confident that this is a true preference and not the result of proximity enabling entry, as all schools in the set we define as having a high probability of admission should be considered feasible by parents. This implies the existence of de facto local monopolies, not through the lack of choice, but through strong preferences for proximity amongst parents of primary school children, perhaps due to transport costs and practical considerations of travel with young children.
What can be done? Popular schools cannot take everyone who applies – there has to be some mechanism to ration places. If we want to break the link between access to high-performing schools and family income, then we need an alternative to proximity as a tie-breaker. A lottery for over-subscribed places is one idea used around the world, but only infrequently in England. Schools could set aside a fraction of places for applicants who live beyond the “catchment” area of the school. Alternatively, schools could apply a banding system often used in the past, whereby schools’ intake of pupils is spread across the distribution of prior attainment or socio-economic background.
The overall goal for policy is to make all schools excellent. But until that nirvana arrives we cannot ignore the question of how places in the better performing schools are allocated. And at the moment, the proximity criterion for admissions means that differences in family income have a substantial and regressive impact on that allocation.
Nomakeupselfie showed how charitable giving can be contagious. It powerfully demonstrated the potential to harness social networks to spread giving to a good cause.
But recent online experiments suggest that nomakeupselfie may be the exception rather than the rule. Researchers looked at what happened when they gave donors the opportunity to ask others in their social network to join them in supporting the same charity. The donors could ask others by posting on their Facebook wall or sending a message to a single friend (the two options were offered randomly).
More donors chose to post to their wall than to send a private message – but very few did either (7% and 4% respectively). The response rate – measured by the number of those who received the suggestion who made a donation – was also very low at 1.2%, all from the wall posts. Putting the two together suggests that it would take more than 1,500 donors (and their social networks) to yield a single extra donation.
Replicating the nomakeupselfie may be hard, but there are ways that charities can encourage giving through social networks.
First, online individual fundraising is more effective than a simple “ask”. Most of the people who are asked for sponsorship are the fundraiser’s friends, family and colleagues. A survey of JustGiving donors showed that of those asked to sponsor, 96% had been asked by a friend (of whom 67% always gave), 89% had been asked by a colleague (48% always gave), 84% had been asked by a family member (87% always gave) and 70% had been asked by a charity representative (9% always gave). The typical JustGiving donor who links their fundraising page to their Facebook page has 251 Facebook friends and gets nine donations – an implicit “response rate” of 3.6%. In smaller networks, the response rate is even higher. Two things make online individual fundraising a more powerful ask – first, the fundraising activity itself (the fact that someone is not just asking for charity, but running a marathon) and second, the fact that the donations are observable (the fundraiser can see who has responded to their request).
Second, incentives matter. The researchers also looked at what happened when they offered donors incentives (in the form of extra donations) to ask their friends. A $1 donation increased the percentage posting to their wall to 17% (from 7%) and sending a message to 9% (from 4%). A $5 donation increased the percentages further to 19% and 14%, but wasn’t cost effective.
It could be possible to use incentives to greater effect. At a schools charity challenge we held with sixth formers last year, the single best idea was to “pass the match” – to allow a donor to leverage incentives by passing on a financial match to a friend as a way of encouraging them to donate. It’s a clever idea to combine financial incentives with social pressure and one that would be well worth testing in the field.
In a world where academics are assessed on their impact as well as the number and quality of their peer-reviewed papers, findings must answer one of two questions in the affirmative – “Is it important?”, or “Is it cool?”
There is no doubt that Behavioural Economics is cool – this has been assured by books like Dan Ariely’s Predictably Irrational, which brought the subject to widespread attention, as well as Nobel Prize winner Daniel Kahneman’s Thinking Fast and Slow.
From a public policy perspective, Thaler and Sunstein’s book, Nudge, is probably the most important of these, as it is geared most heavily towards applying insights from behavioural economics and psychology to real world problems with which governments are concerned.
The attention of policymakers, as well as the nascent replication crisis in psychology changes the question that must be asked of findings – it is not sufficient simply to be cool. The majority of the famous studies in this field are conducted in laboratories, primarily on university students, and primarily on female economics and psychology undergraduate students at that. This is the way science is conducted, but it is important to know whether findings generalise to other contexts.
At the same time, large scale field experiments can be costly, time consuming, and are subject to a lot of noise. These are the very reasons that lab experiments are so attractive for researchers.
There is a halfway house – conducting lab-like experiments, where we take the structure of the lab into the field, where things are noisy and people might be distracted by other things. In a study published today, we do just that.
Participants were members of the public, and they were asked to play a trust game. In this game, one player starts off with a small amount of money, for example £1, and is asked if they’d like to trust the other player. If they do so, the other player receives the £1, plus an additional £3, giving them £4 in total. They then choose whether or not to split the money with the first player. If they do, both players keep £2 – if they don’t, the second player gets £4 and the first player walks away empty handed. The question is – will you trust, and are you trustworthy?
Previous experiments, carried out in the lab, found that when you frame the game as a “Betrayal game”, people were significantly less trusting, and significantly less trustworthy as well, than when the game is described as a “Partnership game”. In our experiment, we showed graphs for one condition or the other to different participants. So, some people saw the results for the “Betrayal game”, while other people saw the results for the “Partnership game”. According to theories on framing, the first group should be less trusting and less trustworthy, as they have been “primed” by Betrayal.
What do we find? Interesting, despite the noisy environment, and the fact that we were using members of the public rather than students, we still saw some effects. People were significantly less likely to trust each-other if they were primed with the untrusting game, but, they were no less likely to split the money. This suggests that outside of the lab, people can still be primed in their beliefs about other people, but that their own preferences don’t change – in the real world, people are more difficult to make less nice, but it might still be possible to make them trust other people less. We should never read too far into an individual study, but if it holds up in repeated and larger studies, the implications are potentially interesting. Not trusting other people is sensible if other people aren’t trustworthy, but if they are, we can lose many beneficial opportunities if we trust too little. If priming can lead people to hold incorrect beliefs about how trustworthy other people are, it could actually make us worse off as a society.
 Ariely (2008): “Predictably Irrational”, Harper Collins
 Kahneman (2012): “Thinking, Fast and Slow” Penguin.
 Thaler and Sunstein (2008): “Nudge: Improving decisions about health, wealth and happiness” Penguin
 Burnham, McCabe and Smith (2000) “Friend-or-foe intentionality priming in an extensive form trust game” Journal of Economic Behavior and Organisation Vol 43 No.1 pp57-73
David Erasmus wants us to give to charity little and often. He draws parallels between charitable giving and dieting and thinks there is a role for the weight watchers of donating. Giving little and often will help get us into a giving habit.
He may be right. Good intentions – losing weight, giving to charity – can be hard to keep. We know what the long-term benefits are, but there is some short-term pain. Giving to charity may not be as costly as giving up sweet and fatty treats, but it takes time and effort out of busy lives.
So how does weight watchers help?
First, there is the public commitment to fulfilling the good intention; this makes it costly NOT to take action. The super rich are already doing this through their Giving Pledge; the same principle could be applied on a smaller scale.
Second, regular meetings and weigh ins provide immediate benefits. And there may be more satisfaction in (publicly) losing a pound a week for 10 weeks than in losing the 10 pounds in one go. The same could be true of giving. Economists think the “warm glow” from giving comes from the (total) amount given. But could it be more rewarding to give £1 ten times than to give £10 once? Diminishing marginal utility may mean it makes sense to spread donations – if you give £10 in one go, the first pound adds more to your happiness than the tenth, so why not spread it out? The very act of giving also gives us satisfaction. Psychologists have shown that giving money away makes people happy; and are doing more work to understand why this is. Personal connections and having an impact seem to be important, not just the total amount given.
Third, weight watchers opens up the process to public scrutiny. People feel good from having other people appreciate and share in their weight loss. Also, like the initial commitment, it also almost certainly makes it more costly to give up giving up.
So, perhaps there is something in the idea that giving little and often and in public can make the process of donating more rewarding and can help to sustain a longer-term commitment to a good intention. The only real difference is that while most people hope to attend weight watchers only once, charitable giving should be something that they are more than happy to carry on with.
Britain’s youth are better educated than any previous generation and desperate to work. Young people all over Europe have borne the brunt of this recession, not only in their job prospects but their wages, with young people’s wages falling to levels last seen in 1998 in the UK. The widespread problems of youth employment stem primarily from a lack of jobs but in the UK we are enjoying a mini jobs boom with employment up by over 1 million in the last two years. Yet youth remain at the margins of the labour market, getting just 12% of that increase in employment, despite them making up 40% of the unemployed. With unemployment generally falling, the critical position of young people is perhaps one of the most underappreciated factors of our labour market today. Here then the problem is of policy failure, a system that is exceptionally badly set up to meet their needs, rather than a jobs shortage or an unwillingness to work. With scarring effects on their future jobs prospects and earnings, which are add up costs to the Exchequer years into the future, this policy failure is costing us all dearly.
Not all that the government has done has failed though, for instance the raising of the participation age (RPA) to 17 has led to a substantial increase in 17 year olds staying in school. There has also been a moderate increase in apprenticeships among the young. In addition, the Work Programme has had some success at getting long-term unemployed youth into work. But the current system around the school-to-work transition has three deep seated flaws. Firstly, our system prioritises staying in education, until 18 from next year, and then switching entirely to emphasising an exclusive focus on job search, with tight restrictions on combining education and training with on-going efforts to find work. The number of young people leaving school lacking qualifications is falling but poor educational attainment and a lack of good quality vocational skills among those who don’t go to university is one of the long-standing problems, closely linked to our failure to build a better quality labour market. The Wolf Review showed that five out of ten young people reach 18 without good English and Maths, and our priority must be to put that right. But the social security system also needs to play its part for those who fall through the system. For too long, we’ve tolerated a situation where a system designed for adults actively dissuades young people who don’t have the skills they need for work from addressing that gap at the start of their careers.
Secondly, our system leaves young people lacking any work experience, except for apprentices. Young people need guaranteed work, which helps gets them back into the labour market, with a CV and work experience to bring to future employers. Any set of reforms seeking to address youth unemployment needs to support work experience, either combined with formal training as a Traineeship or through a work experience programme.
Thirdly, no government agency has an extensive reach into or engagement with employers. The governments hiring subsidy to employers was an outstanding policy failure with almost no take up. This was essentially because there was no agency responsible or capable of marketing the programme to employers and helping with addressing the bureaucracy. This was the role of Job Centre Plus in the past but now it is only concerned with monitoring and supporting job search by claimants; recruitment has gone on-line and employer engagement disappeared. Work Programme providers and other bespoke private organisations are building such links but they are designed for single purpose functions and are not open to the government to engage employers about any new policy drive.
The media focus of the proposals outlined by Ed Miliband last week was on the means testing of unemployment benefits, but at its heart the proposals are for a phasing out of continuing education, training and work experience, with required and supported job search between the ages of 18 and 21. It can be seen as combining the old Educational Maintenance Allowance, which only required education participation, with benefits requiring job search. At younger ages those with poor qualifications combine study with workplace based training and job search. At older ages or for those with decent qualifications the focus switches to work experience and job search, whilst for those aged over 21 the focus is again exclusively on effective job search until long-term unemployment becomes a risk, when the Job Guarantee will kick in.
Thus these proposals have two important elements for improving the current model. A phased move away from education to focus exclusively on job search: for those with poor qualifications, little training and no work experience, combining efforts to redress these shortcomings, whilst maintaining job search. Plus a central role for work experience. The third element remains to be clearly addressed, that is how to gain employer engagement with this new model. For me this should be led by local partnerships formed from schools, FE colleges, local authorities and employers who should oversee the tracking and engagement of young people at risk of becoming NEET and engaging employers about apprenticeships, traineeships and work experience and, of course, hiring young people.
The next few weeks might be a horrible time of year if you are 15 or 16. There are some big decisions coming up. One the one hand: the final exams for the GCSE courses, completing two years of work leading up to this moment. There is a lot of studying still to do, notes to be read, exercises to be worked through, understanding to be really nailed down. Final revision.
But on the other hand: the World Cup. In Brazil. England qualified, and while no-one thinks of England as favourites … who knows? Who would want to miss watching Gerrard and the team confounding the pundits and cruising into the semis?
What to do? This is a classic question of time preference: jam today (watching the game) versus jam tomorrow (getting the grades and higher lifetime income). What is the trade-off between grades and goals?
Our research < http://cmpo.wordpress.com/2011/12/06/a-report-of-two-halves/ > can help. We have studied < http://www.bristol.ac.uk/cmpo/publications/papers/2011/wp276.pdf > the decisions of about 3.5m students facing this dilemma in previous summers. We compared the GCSE performance of as-good-as-identical students in years with World Cups (or the European Championship) and years with no exam-time distractions.
On average, grades were slightly lower in World Cup years. We interpreted this as some students taking some time out from studying to keep an eye on the tournament. While there are other possible explanations, our statistical techniques rule out more or less everything else.
That’s on average. Some groups of students saw sizeable declines in their grades. Again, the interpretation of this has to be that they prioritised the tournament and seriously cut down on study time.
How much does this matter? It depends on how close to the key borderline the student’s performance is likely to be. Achieving at least 5 good passes (C grade and above) including English and maths is widely regarded as a necessary minimum for further education or getting a good job. For students who are near this borderline, a grade or so either way matters a lot.
Missing out on 5 good GCSE grades can be very costly. Estimates suggest an average total lifetime cost of around £30,000. This seems a very hefty price to pay for watching some football.
The moral of all this research and numbers: if you are likely to be close to the 5 Cs borderline, stick with the studies, let others suffer the pain of watching England, and get the grades. In the future, you will have earned the money – and the right – to sit back and fully enjoy World Cups.
The role of grammar schools is still a hotly contested topic in education policy in England. We contribute to this debate by showing that earnings inequality is higher under a selective system in which pupils are allocated to secondary schools based on their performance in tests at age 11. While selective systems have declined since their heyday in the mid-1960s, a number of areas retain a selective system and some believe <http://blogs.telegraph.co.uk/news/tobyyoung/100273771/lets-make-every-school-a-grammar-school/ > that this system should again be expanded.
In our recent paper, we moved away from typical questions around grammar schools such as whether access to them is fair (it isn’t) and what the impact of grammar schools is for the marginal student (debatable), to ask about the longer term impacts of these type of systems on earnings inequality.
Using a nationally representative panel data source, Understanding Society, we considered the adult earnings distributions of over 2500 individuals born between 1961 and 1983, comparing those who grew up in an area operating a selective schooling system to those who grew up in very similar areas operating a comprehensive schooling system.
We ensure that the areas we are comparing are very similar by matching areas that are comprehensive to selective areas based on the average hourly wage, unemployment rate and proportion of private schools in both areas. The rich data source also allows us to control for things that may be driving the choice of area and the later earnings distributions, such as parental education and occupation when the individual was 14, gender, age, ethnicity and current area of residence.
We therefore compare the adult earnings of people who have very similar characteristics, live as adults in very similar areas and grew up in very similar areas: the main difference being that one area operated a selective system and the other a comprehensive system.
When we consider these two groups then, we see that earnings inequality is greater for those who grew up in areas operating a selective system compared to those who grew up in comprehensive areas. Comparing individuals of similar characteristics, the variance of earnings (2009-2012) for those who grew up in selective areas is £29.22 compared to £23.10 in non-selective areas. Put another way, the difference in pay between those at the 90th percentile of the wage distribution and those at the 10th percentile for those who grew up in a selective system is £13.14 an hour compared to £10.93 an hour in comprehensive systems.
On a personal level, if you grow up in a selective system and end up with earnings at the 90th percentile, you earn £1.31 more an hour (statistically significant) than the similar individual who grew up in a comprehensive system. At the other end of the scale, if you grow up in a selective system and don’t do so well – earning at the 10th percentile, you earn 90p less an hour (statistically significant) than the similar individual who grew up in a comprehensive system.
We can also compare the 90-10 wage gap between selective and non-selective areas to the overall 90-10 wage gap in the sample. As noted, in selective areas the 90-10 wage gap is £2.21 an hour higher than in comprehensive areas. This accounts for 18% of the overall 90-10 wage gap in our sample. So selective systems account for a large proportion of inequality in earnings. The message is clear. Grammar systems create winners and losers.
There are also interesting differences by gender. If we look separately at males and females, we see that males in selective systems at the top of the earnings distribution do significantly better than their non-selective counterparts (£2.25 an hour) while there is no difference for those at the bottom of the earnings distribution.
For females, the picture is the opposite. Females growing up in selective systems who do well look very similar to successful females from non-selective systems but those who do badly earn significantly less (87p an hour) than their comprehensive system counterparts. We think this could be because males were outperforming girls at school for the cohorts we consider and so more males attended grammars and more females attended secondary moderns within selective systems, although we cannot observe this directly.
What lies behind these differences? Inequality in earnings comes from inequality in qualifications and these in turn might derive from differences in peer effects and teacher effectiveness between the systems. We speculate that in the 1970s and 1980s more able teachers might have been more effectively sorted in a selective system into schools with high attaining pupils. The evidence on peer effects in the UK is mixed but the evidence on teacher effectiveness points to this as a possible key mechanism.
Whatever might be driving this phenomenon, our research shows that inequality is increased by selective schooling systems. If this is combined with evidence < http://www.bris.ac.uk/cmpo/publications/papers/2006/abstract150.html> that sorting within selective systems is actually more about where you are from rather than your ability, then selective systems may not be the drivers of social mobility that some claim. The pros and cons of a system which creates greater inequality will doubtless continue to be passionately debated. What we cannot ignore is that there are losers as well as winners in this story.