1 The socio-economic gap in university drop out Nattavudh Powdthavee University of York Anna Vignoles 1 Institute of Education, University of London January 2009 ABSTRACT In many countries, including the US and the UK, there is ongoing concern about the extent to which young people from poor backgrounds can acquire a university degree. Recent evidence from the UK however, suggests that for a given level of prior achievement in secondary school, a disadvantaged pupil has as much chance of enrolling in a university as a more advantaged student. Yet simply participating in higher education is not sufficient: graduation is as important. This paper therefore investigates whether students from lower socio-economic backgrounds have a higher rate of university drop-out as compared to their wealthier counterparts, once one allows for their differential prior achievement. Using a combination of school and university administrative data sets, we show that there is indeed a sizeable and statistically significant gap in the rate of withdrawal after the first year of university between the most advantaged and disadvantaged English students. This socioeconomic gap in university drop-out remains even after allowing for their personal characteristics, prior achievement in secondary school and university characteristics. In the English context at least, this implies that retention in university of disadvantaged students is arguably a more important policy issue than barriers to entry for these students. Key words: college drop out; college retention; university drop out; prior achievement; socio-economic gap JEL: I2 1 Centre for Economics of Education, Institute of Education. Corresponding author:
2 1. Introduction As in the US and in many other countries, the under representation of poorer students in college or university has been an issue of great policy concern in the UK for many decades. Recent evidence for England indicates that the 20% most disadvantaged students are around 6 times less likely to participate in university compared to the 20% most advantaged pupils (HEFCE, 2005). Furthermore, the socio-economic gap in university participation actually widened in the UK in the mid and late 1990s (Blanden and Machin, 2004; Machin and Vignoles, 2004; HEFCE, 2005). As in the US (Cunha et al. 2006), much of the root cause of this inequality is located earlier in the education system. Chowdry, Crawford, Dearden, Goodman and Vignoles (2008) have shown that in England, if a disadvantaged pupil does reach a sufficient level of achievement in secondary school, s/he has a similar chance of going on to university as a more advantaged student. However, in both the UK and the US, the lower participation rate of poorer students is not the only policy concern. To fully reap the rewards from a university education, poorer students need to complete their degrees. Currently around three quarters of those who start a degree in the UK actually complete it. Although the UK performs well in international league tables of student retention (NAO, 2007), the fact that one quarter of students who enroll in university do not graduate is potentially cause for concern. Specifically, even if disadvantaged students are as likely to participate in higher education for a given level of prior achievement, they may be more likely to drop out than wealthier students. For instance, disadvantaged students may have less complete information about the real costs of studying for a degree, and we know that in the UK poorer students leave university with more debt and are more risk averse in the first place (Pennell and West, 2005). This might mean that students socioeconomic background affects their likelihood of dropping out even if family background does not affect university participation conditional on prior academic achievement (Chowdry et al. 2008, Marcenaro-Gutierrez, Galindo-Rueda and Vignoles, 2007). Certainly in the literature drop out or non-completion has been seen as particularly problematic for students from disadvantaged backgrounds (Dearing,
3 1997; McGivney, 1996; HEFCE, 1999; Quinn, 2004) 2, and the extent to which drop out does indeed vary by socio-economic background is the focus of this paper. In this paper we ask whether disadvantaged entrants to college 3 have a higher probability of dropping out, given their level of prior achievement. In other words, does disadvantage and poverty mean that although you can get into university, you are then more likely to struggle and eventually drop out. This would imply that the focus of widening participation policy needs to be on facilitating degree completion by poorer students, rather than just encouraging participation. Alternatively, is it simply the case that poorer students drop out of university not because they are poor but because they have lower levels of prior education achievement and are therefore less well prepared for college? It may be that poorer students are no more likely to drop out than other more advantaged students with similar levels of (low) prior achievement. With our data we unfortunately cannot identify what specifically causes a student to drop out of university. For instance, we cannot differentiate between students who fail to meet the necessary academic standards and are forced to drop out of college because of this from students who simply choose to withdraw. Certainly different causes of drop out will have different policy solutions. Indeed there is a literature, which we discuss later in the paper, that acknowledges that some drop out may be rational if students drop out when they find the costs (psychic or monetary) exceed the potential benefits broadly defined (Manski (1989); Hartog et al 1989; Oosterbeek 1989; and Altonji 1993). Government intervention to prevent rational drop out would seem inadvisable. However, although we cannot identify the causes of drop out in our data, what we can do is identify the importance of pupils prior academic achievement, as compared to their family background, in explaining drop out. This is important because if poor academic preparation is largely to blame for drop out, the policy solution would include improved school based preparation for university, as well as academic remedial help, rather than say financial assistance. This is particularly important for the English context as the socio-economic gap in HE 2 The socio-economic gap in drop out from college in the US system is discussed extensively in Turner (2008). 3 In this paper we use the terms college, university and higher education (HE) inter-changeably.
4 participation in the UK has indeed been found to be largely attributable to poor academic preparation by lower income students rather than barriers at the point of entry into university, such as credit constraints (Chowdry et al. 2008). As such, the policy solution to under representation of poorer students in higher education must be at least partially school focused and would need to raise the academic achievement of deprived children. It would be informative to determine whether drop out from university is also largely attributable to weak academic preparation as opposed to other family background related factors. To address these questions, we use administrative data on an entire cohort 4 of young people in England who potentially could enter university in 2004/5 (at age 18). These data are unique in that they include information on each pupil s personal characteristics (e.g. ethnicity, date of birth and indicators of their socio-economic background) and also provide a complete record of each child s educational achievement from age 11 onwards 5. This is the first time that such longitudinal data have been available to study the important issue of college drop out in the UK context. The paper starts with a brief description of the English university system in section 2, to provide context to the paper. We then proceed to describe the previous literature (section 3) and the data (section 4). Section 5 gives the econometric model and section 6 the results. Section 7 concludes. 2. The English higher education system For context, we briefly describe the English university system. In England, students who apply to university straight after secondary school (one fifth of the cohort) apply through a centralized admissions system called the University Centralised Admission System or UCAS. Students have to apply to specific degree courses i.e. they have to pre-select a specific degree subject in a specific institution. Hence by contrast to the 4 We have data on all students in schools funded by the state in England who turned age 18 in 2003/4, i.e. more than half a million students. We exclude students in private schools. To the extent that such students have lower university drop out rates, we may be understating the socio-economic gap in university drop out. 5 In the UK pupils take achievement tests or externally validated examinations at ages 11, 14, 16 and 18, hence we have a complete record of educational achievement from age 11 to age 19.
5 US system, the process of applying to university is more centrally coordinated and students are limited in the number of different institutions they can apply to (they can choose up to 5). It is usual for students to apply to study the same or similar degree subjects at a range of different institutions (although some students may only specify one or two options). Students can then be offered a place on a particular degree course subject to academic conditions, such as minimum grades achieved at age 18 (in their Advanced (A level) examinations which are equivalent to high school graduation). The results of students examinations at age 18 are not generally known before application to university which means there may be a potential mismatch between students expectations about their A level grades (which will determine their choice of degree subject and institution) and their actual A level grades. In England it normally takes three years to achieve a Bachelors degree and, again unlike the US, transfer between institutions is not usual (fewer than 3% switch institutions). This is partly because there is no agreed system of college credits so transfer is difficult. Students progression from one year to the next in their degree course is subject to a minimum academic level of achievement. This means that potentially students may drop out either because they fail to reach the required academic standard (the extent to which they have to pass examinations to progress from one year to the next varies by institution but all have some form of assessment) or because they anticipate that they will fail. Students are allowed to repeat parts of their degree that they have failed. If a student fails an element of their degree (a module) they may retake it the following year. However, there are limits (that vary by institution) to the number of times a student can retake an element of their degree course. Students that persistently fail will not be allowed to continue on their course. As in the US, in England there are concerns that financial barriers may both prevent students from enrolling in HE in the first place and then cause them to drop out (Callender, 2003). However, the English system differs substantially from the US system in terms of the costs of study, with the former system being appreciably more generous, in terms of the state s contribution to the costs of university. English universities have historically been free to students, with costs paid by the general tax payer. This has changed in the last decade and institutions can now charge English
6 students up to 3000 per annum (although foreign students will pay more). These fees are means tested, with the poorest students fully exempt from fees. Repayment is also now on an income contingent basis after graduation, to minimize the disincentive effect on students from disadvantaged socio-economic backgrounds. Furthermore, students also have access to loans to fund their living costs during their degree. One feature of the English university system that is particularly important for this paper is the fact that, unlike in the US and countries such as New Zealand and Sweden, England has historically had low levels of student drop out from higher education (Dearing, 1997; NAO, 2007). Recent data suggests that 91.6% of full time students starting university in 2004/05 continued into their second year and 78.1% are expected to complete their degree (NAO, 2007) 6. However, as the sector has expanded and the rate of non-completion has risen (Johnes and McNabb, 2004), so policy attention has shifted to this issue, and non-completion rates are now part of a range of indicators used by government to measure university performance. Indeed university league tables are produced in UK newspapers, ranking universities on a number of metrics, including their drop out rate. These league tables generally do not control for student characteristics, and therefore may give a misleading impression of the true institutional quality in terms of retaining students, particularly for universities with a larger number of deprived and lower achieving students. Ideally value added models, which control for students prior achievement, are needed to assess whether institutions have particularly high or low drop out rates relative to their student intake. Such models have not been possible previously, due to limited data. However, in this paper we show how such models may be operationalised using administrative data. 3. Previous literature There is a large and growing literature on the role of family background, i.e. income and socio-economic status, in determining education outcomes, particularly university achievement (Blanden and Gregg, 2004; Carneiro and Heckman, 2002 and 2003; Gayle et al. 2002; Meghir and Palme, 2005; Haveman and Wolfe, 1993). Such studies 6 The drop out rate in our data is somewhat lower than this as we focus specifically on young full time entrants. Comparable HESA data indicates that the UK non-continuation rate from the first year of a degree to the second for young full time entrants was 7.2% in 04/05. In our data for England the figure is very similar (just over 6%).
7 have found family background to be an important determinant of educational achievement and have also suggested that the socio-economic gap in educational achievement emerges early (see CMPO, 2006 and Feinstein, 2003 for the UK; Cunha and Heckman, 2007 and Cunha et al., 2006 for the US). In fact Cunha et al. (2006) concludes that family background and specifically credit constraints play only a limited role in determining HE participation, conditional on achievement in secondary school, although some recent studies dispute this (Belley and Lochner, 2007). Even if education inequality emerges early, in the US at least, the raw socio-economic gap widens substantially if one measures Bachelor degree completion as opposed to enrolment (Turner, 2008). This raises the question as to whether the conditional drop out rate is higher for lower socio-economic group students, taking account of their prior education achievement. The literature on the relationship between socioeconomic background and drop out from university is limited, although the US evidence finds differential drop out by family income (see Corrigan, 2003, Haveman and Wilson, 2005 and related issues in Bound, Lovenheim and Turner, 2008). In the English context, Johnes & McNabb (2004) analyzed students entering and leaving the old (pre ) universities and distinguished between voluntary drop out and involuntary drop out i.e. failure. Jones & McNabb found that students from a lower socio-economic background were more likely to drop out voluntarily. Smith & Naylor (2001) used the same data to examine completion and non-completion. Using a binomial regression analysis of the probability that an individual withdraws from university for whatever reason, the authors found the risk of dropping out to be extremely high amongst students from lower social class backgrounds and living in high unemployment rate areas. More recently, Bennett (2003) showed self-declared financial hardship to be the most powerful predictor of a student s decision to withdraw from their degree course in the Business Studies department in a new university in Greater London. Using data collected by the author himself, Bennett estimated a confirmatory factor analysis of the probability of non-completion among business students. He found self-declared financial hardship to be one of the strongest 7 Prior to 1992, English higher education was divided into universities (higher status more academically oriented universities) and polytechnics (more vocationally oriented higher education institutions). In 1992 polytechnics became universities.
8 predictors of the individual quit decision. Other important factors also included low self-esteem and academic performance at university. Whilst these studies were able to control to some extent for a student s entry qualifications, they did not have rich data on students prior achievement, and only considered a sub-set of UK universities. This paper therefore estimates models of student drop out or non-completion using all universities in England. It is worth considering why we might be concerned with student drop out. Firstly, there may be economic costs associated with noncompletion; there may have been a waste of resources if a student starts but does not complete a course (Yorke, 1998). Another potential concern is the sense of failure that a student may feel after dropping out of university and the impact on his or her productivity and earnings. That said we must be cautious in interpreting our results. Although the UK does not have the long standing US tradition of part time and intermittent higher education, increasingly UK students do enroll part time and progression may not be linear. This is particularly true of mature students (McGivney, 1996). Labelling (temporary) withdrawal as academic failure or wastage would seem inappropriate: just because students withdraw from their studies does not mean that they have not received any benefit from university (Johnes and Taylor, 1989). This is not merely a semantic debate: universities in England now face clear incentives to encourage student completion in the normal time and non-completion whatever the cause is penalized financially 8. If indeed poorer students are more likely to drop out than their more advantaged counterparts for a given level of prior achievement, this may lead to a tension between the widening participation agenda that encourages greater participation by deprived students and the desire by universities not to incur penalties from high levels of student withdrawal (Palmer, 2001). Some economists have also made the argument that drop out from HE is efficient: weaker students who would not benefit from completing their degrees rightly drop out. Manski (1989) for example, argues that lower dropout rates would not necessarily make society better off. He suggests the decision to enrol is a decision to initiate an experiment, a possible outcome of which is dropout (see also Hartog et al 1989; Oosterbeek 1989; and Altonji 1993). Thus enrolment in HE incurs a risk for all 8 Public funding received by each university in England is potentially affected by their performance. Non-completion is one measure of university performance used by the authorities.
9 students, namely the risk that they may have to drop out for whatever reason. Poorer students may face higher levels of this risk. For example, they may be more likely to fail to reach the level of educational achievement required or make their decisions about choice of institution and subject of study on the basis of poorer quality information. This higher level of risk may partially explain lower participation rates by poorer students. Even if poorer students face the same risk of drop out as their advantaged peers, if they are more risk adverse (Callender, 2003), then this too would at least partially explain their lower enrolment rate. 4. Data We use linked administrative data sets to carry out the analysis: namely, the English National Pupil Database (NPD) / Pupil Level Annual School Census (PLASC) and individual student records maintained by the Higher Education Statistics Agency (HESA). The school administrative data (NPD/PLASC) 9 contain each pupil s record of their primary and secondary schooling, including information on their educational attainment from age 11 to 18, their personal characteristics, such as date of birth, ethnicity, home postcode, entitlement to free school meals 10 and whether English is an additional language in their home. The university records (HESA data) contain information on the degree subject, institution and other details of each student s university education, for all students studying for a first degree at UK universities. With these two sources of data linked together 11, we have longitudinal data on a cohort of students from age 11 through to potential HE participation at age 18 in 2004/5 and continued participation at age 19 in 2005/6. For the purposes of this paper, we consider only HE participants in English institutions and have a sample size of 121,827 observations from 120 HE institutions. The dependent variable of interest is simply whether or not the pupil continued from one year to the next, i.e. continued in the same university from 04/05 to 05/06. We recognize that we are only able to consider drop out from the first year of study and if 9 These data are maintained by the Department for Children, Schools and Families. 10 This can be thought of as a proxy for very low family income. Pupils are eligible for Free School Meals (FSM) if their parents receive Income Support, income-based Jobseeker's Allowance, or Child Tax Credits, with a gross household income of less than 14,495 (in prices). 11 School administrative records are fuzzy matched to higher education administrative records, using a variety of variables including name, date of birth and postcode. The matching process was carried out by the Department for Children, Schools and Families.
10 students from different socio-economic backgrounds tend to drop out at different stages, we may have partial results. For instance, if more advantaged students manage to remain in university longer, we may overstate the socio-economic gap in drop out in comparison to what we might expect to see in terms of degree completion. Around 6% of pupils failed to progress from one year to the next, indicating they dropped out from their institution (voluntarily or involuntarily) or decided to move to another institution in the following year. As our cohort only potentially entered HE the previous year, we are essentially measuring drop out after the first year of 3 years of study 12. With our data we are not able to separate out those who drop out of higher education altogether, from those who switch institutions. Data from the Higher Education Statistics Agency suggest that 2.9% of students from low income neighborhoods switch institutions (across all years of enrolment) as compared to 2.7% of students from higher income neighbourhoods 13. Since switching occurs at a similar rate across different types of student, this problem would not appear to be a major source of bias in our results. A key feature of the data we use is that they include test score information on pupils from age 11 onwards. The test score information comes from age 11 (Key Stage 2) and age 14 (Key Stage 3) tests. These are national achievement tests sat by all children in state schools in England in English, Mathematics and Science. The tests are externally validated i.e. they are marked by individuals outside of the child s school. We include test scores in three subject areas English, Mathematics and Science 14, using a non linear specification. The test data are supplemented by the results from public examinations taken by most students at age 16, namely General Certificates of Secondary Education (GCSEs), and for some students, Advanced levels (A-levels) at age 18. For GCSE, we use the capped total point score: this gives the total number of points accumulated from the student s eight highest GCSE grades. 15 At 18, we use the total (uncapped) point score. We divide the population into 12 The vast majority of UK Bachelors degrees are 3 years of study. 13 Higher Education Statistics Agency: 14 We are grateful to an anonymous referee for guidance on the use of these scores. 15 We use a capped total point score to avoid conflating the quantity of GCSEs taken and the grades received, as students may take a varying number of qualifications. For example, receiving 10 Grade D GCSEs would be equivalent (in terms of total points scored) to receiving 8 Grade C GCSEs (using the old tariff system), while we may not believe these are equivalent in terms of achievement.
11 five evenly sized quintile groups ranked according to their score at GCSE and A level or equivalent 16 to capture attainment at these levels. All in all these data contain the richest possible information on students prior achievement to better enable us to identify the distinct role of academic preparation and socio-economic background in dropping out of university. Based on the person s university, we also linked in an institution-level indicator of the university s research quality from the 2001 Research Assessment Exercise (RAE) 17. We then combine this indicator of the quality of each institution s research, with an indicator of whether or not the institution is a member of the Russell Group of universities, a self-defined elite grouping of English universities. We define a high status institution as being all 20 of the research-intensive Russell Group institutions, plus any UK university with an average 2001 RAE rating that exceeds the lowest RAE score for a Russell Group university (see Chowdry et al for further details and a list of institutions). In summary, we create a binary indicator of whether an institution is an elite institution or otherwise, recognizing the inherent problems in defining what constitutes quality in higher education from a student perspective. The data do however, have a number of limitations. Firstly, the indicators for students family background are problematic. Students who apply through the UCAS centralized application system described earlier are asked about the occupations of their parents. However, for students not applying through UCAS this information is absent altogether. For young full time entrants to a first degree, if we rely on data on parental socio-economic background, we have missing data for around one in five students. This is a long recognized problem in the UK. For instance, the UK National Audit Office have stressed the poor quality of the data available to identify the socioeconomic background of students in HE. An alternative to using parental SES is to use administrative records from earlier in these individuals schooling. We do have an indicator of whether or not a student was eligible for free school meals (FSM) in secondary school. This indicator is limited by 16 For students taking vocational qualifications at age 18 instead of A-levels, we have their point score using the official equivalencies between vocational and academic qualifications. 17 The RAE is a quality assessment exercise to assess research quality across the HE sector in England and Wales. Quality assessment is based on peer review.
12 not being contemporaneous with HE participation and also by measuring the very bottom of the income distribution. Around 5% of students entering HE were eligible for free school meals in secondary school. We also have each pupil s postcode (similar to a zipcode) in secondary school when they were applying to enter university, and we can use this geographical marker 18 to link in information on the characteristics of the pupil s neighborhood. Specifically we can link in measures of socio-economic deprivation. (namely an Index of Multiple Deprivation (IMD) score, derived from Census data on the characteristics of individuals living in their neighborhood 19 and an Income Deprivation Affecting Children Index (IDACI) score, again constructed on the basis of Census data on individuals living in their neighborhood 20 ). Whilst these administrative measures of family deprivation are not ideal (family income would be preferable, for example), we use individual and administrative measures of socio-economic background and test the robustness of our findings to using these alternative indicators. In our main table, we include individual measures of parental socio-economic status where available, with a missing dummy for those who do not provide this information. We then include our Free School Meal indicator and geographical measures which should capture, at least to some extent, the socio-economic circumstances of those pupils for whom we have missing individual level data. Another limitation of the data is that we only consider young HE participants i.e. those participating at age 18. The drop out behavior of older HE participants may differ so our results are not necessarily generizable to older students. Finally, we only have data on state school pupils. A significant minority of students in England attend private schools prior to entering HE (just under 7% at age 16 in our data). If these more advantaged students were included in our sample and if they have very low drop 18 See Geronimus, Bound and Neidert (1995) for a discussion of the limitations of using geographical based measures of socio-economic status in the context of health research. They conclude that there is a tendency for geographical measures to exaggerate the apparent effect of socio-economic characteristics on health outcomes. However, they acknowledge their findings are data specific and urge caution when making inference from geographically based measures. In this paper we explore both individual and geographical measures to address this problem. 19 This is available at Super Output Area (SOA) level (comprising approximately 700 households), and makes use of information from seven different domains: income; employment; health and disability; education, skills and training; barriers to housing and services; living environment; and crime. 20 IDACI is an additional supplementary element to the Index of Multiple Deprivation.