STUDENTS AND TERM-TIME EMPLOYMENT RICHARD J JONES AND PETER J SLOANE

Welsh Economy Labour Market Evaluation and Research Centre (WELMERC),

University of Wales Swansea, Singleton Park, Swansea, SA2 8PP.

Emails: p.j.sloane@swansea.ac.uk and richard.j.jones@swansea.ac.uk;

ABSTRACT In recent years, changes in financing of higher education and the expansion in student numbers has meant that students have become an increasingly significant component of the labour market. In this paper, we investigate the nature and extent of student employment amongst the full-time undergraduate students at the University of Wales, Swansea and then examine the effect term-time employment has on students’ exam performance. After sending a questionnaire to around five thousand undergraduates, we find that nearly half of the 784 students who responded had undertaken some form of paid employment during term-time with most of the employment being concentrated in low wage and low skilled jobs. Using a tobit estimation framework, we find that after controlling for personal characteristics and entry qualifications, working long hours (more than 16 hours per week) has a negative impact on exam performance.

JEL Classification: H0, I, J2.

Keywords: Student Performance, Term-Time Employment.

ACKNOWLEDGEMENTS

The Authors are grateful to the Welsh Assembly Government for funding this

research and to members of the WELMERC steering committee for useful comments.

INTRODUCTION

In recent years, changes in financing of higher education and the expansion in student

number has meant that students have become an increasingly significant component

of the labour market. In this paper, we investigate the nature and extent of student

employment amongst the full-time undergraduate students at the University of Wales,

Swansea and then examine the effect term-time employment has on students’ exam

performance.

The paper is divided into five sections. First, we review the previous literature on this

topic. In the second and third sections, we describe the results of the student survey

and a survey of employers. In the fourth section, we use the information from the

student survey to examine the effect of term-time employment on students’ exam

performance. Finally, we draw some conclusions and suggest some implications for

policy.

LITERATURE REVIEW

Callender and Kemp (2000) argue that the reduction of student state-maintenance

payments, through the erosion of the value of the student grant, reduced access to

state benefits to students, particularly the gradual replacement of student grants by

loans and the introduction of fees, has encouraged more students to engage in paid

employment. They estimate that two-thirds of full-time students were employed at

some time during the academic year in 1998/99.

A study by the UK National Institute for Economic and Social Research, (Metcalf,

2001) based on four universities found that almost half the students questioned had

obtained paid employment during term-time, averaging 12 hours per week, while four

per cent regularly worked at least 20 hours per week. The authors report that working

during term-time adversely affected the perceived quality of education as around two-

thirds of students who worked reported that they had difficulties in balancing

employment and studies. Financial pressures were cited as the main reason for

working; students whose father did not have a degree (a group less likely to go to

university) and women (especially those from ethnic minorities) were more likely to

work in term-time and hence lose out in educational terms from their time at

university relative to other groups.

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In a further paper based on the same four universities (Metcalf 2003), the focus was

placed on the implications for equity and for the higher education system. The extent

of term-time working varied across the four universities. The research suggested that

the financial system might lead to an increasingly polarised university system: those

that facilitate term-time working and those that do not, with the more prestigious

universities tending to be in the latter category. This would distort the university

choice of those who needed to work during term-time, inhibiting their access to

prestigious universities, and lead to greater disadvantage amongst those who worked

despite being at universities that made fewer concessions for term-time working.

Taylor (1998) surveyed paid employment undertaken by a sample of computer studies

undergraduates based at Heriot-Watt University during the 1995-96 academic year.

Though the sample is small (191) it represents an overall response rate of 55 per cent.

The results show that paid work tends to increase in each year of study before

declining in the final (4th) year. During term-time, a quarter of respondents worked at

weekends and 10 per cent during weekdays. While a quarter of those in paid

employment felt they benefited academically from the nature of work they were

doing, but two-thirds felt that paid employment was detrimental to their academic

studies.

Two further unpublished studies, reported by Tanguey and Pugh (2002), were carried

out in Wales (UWIC, 2001 and University of Glamorgan, 2001). The first, a survey

of 100 full-time undergraduates at the University of Glamorgan and 56% full-time

under-graduates at UWIC, was conducted in May 2001 to investigate how many

hours students were working during term-time and what effect this had on their

students In UWIC 50% worked during term-time, two-thirds of them working less

than 16 hours. A quarter reported missing lectures because of paid employment. At

Glamorgan 50% undertook paid employment during term-time, but in this case 60%

worked more than 16 hours.

A study by Bailey and Mallier (1999) examined the summer-vacation employment

experiences of 1,919-second year degree and HND students at Coventry University.

Using a tobit framework to model hours of work the authors found that a range of

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personal characteristics had no effect on the total number of hours worked, but pay

did have a positive effect. In a second paper, they examined the job search process,

finding that the use of either Job Centres or responses to newspaper advertisements

increased the probability of finding work. However, females were found to be less

likely to gain full-time employment than males.

A more extensive study was carried out at the University of Northumbria on behalf of

the DfEE (2000). This report examines the nature of the labour market participation

of university students and its impacts. Drawing upon data from a large-scale (1814

students – one-fifth of full-time, EU undergraduate degree students at the University

of Northumbria) questionnaire survey, the Survey of Undergraduates describes the

pattern of participation by undergraduate students, during the second semester of the

1998/99 academic year. The report’s focus is upon term-time employment rather than

the traditional practice of vacation work, (it also excludes sandwich courses and other

course-related placements). It identifies the proportion of students involved in term-

time employment, the types of jobs undertaken (levels of pay, etc.) and, perhaps more

significantly, the motivations that result in the decision to seek work while studying

full-time. The study is particularly interested in exploring the interaction between

employment and academic activity, from the perspective of time allocation effects

upon academic attainment levels and in respect of the financial decision-making

processes undertaken by students. The study concluded that the primary reason for

undertaking term-time work was a financial one.

As the large scale survey focuses largely on the student perspective of labour market

activity, a second, small scale, interview-based survey of selected local employers

(Undergraduates in the Labour Market: Survey of Employers) was carried out. Its

aim was to act in a complementary capacity and provide some information regarding

the nature of demand for student labour and some of the wider effects of student

participation in the local labour market. The survey found that the deregulation of

opening hours across a range of service sector activities and the growth of alternative

methods of delivery (e.g. Call Centres), has resulted in an increase in the number of

part-time jobs available to students.

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The findings of the two surveys have been combined to provide a fuller, more

complete picture of the increasing participation of students in the labour market. This

has then been placed in its wider context: the shift from grant to loan finance as the

means of public support for maintenance (plus from 1998, some students having to

pay fees); the gap between publicly available funds and the typical spending levels of

students; and, the increasing flexibility of UK labour markets. The report also

commences an exploration of the effects of student participation upon the local labour

market; whether increased participation by students may represent intangible assets

for employers in human capital terms, but may cause the displacement of other

workers. On the question of labour market displacement, virtually all employers said

if denied access to student labour they would substitute them by other part-time

labour, suggesting students were substitutes for such workers.

McVicar and McKee (2001) examined the effects of examination performance of

having a part-time job whilst in full-time post-sixteen education, using the first two

sweeps of the Status Zero Survey (1995 and 1999) on young people in Northern

Ireland. Around 35% of the 450 individuals sampled were engaged in part-time

employment during their education spell, compared to over 60% found by some

British studies. This may be related to Northern Ireland’s comparatively slack youth

labour market and might reflect part-time employment levels in other peripheral

regions. The authors use an ordered probit framework to model exam performance,

measured as NVQ level or equivalent attained at the end of the education spell. Their

estimations suggest working part-time per se is not detrimental to examination

performance, although working long hours (15+ hours) is.

Hodgson and Spours (2001) traced the development of different strands of research in

this area over the last decade. They attribute the increased interest in the phenomenon

of part-time work among full-time learners to changes in the youth labour market

allied to rising levels of post-16 participation. Using evidence from three recent

studies, they suggest that the scale and intensity of participation in part-time work

amongst full-time 16-19 year olds appears to have increased significantly towards the

end of the 1990s and that a growing commitment to part-time work has become the

norm for learners in full-time 16-19 courses. Their research suggests, however, that

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learners in advanced-level courses have combined study and paid work in different

ways.

Most of the previous work in this area focus on a particular university. One notable

exception are the Unite Student Living Reports (Unite, 2001 to 2004). In 2001, 1,103

face-to-face interviews with students were carried out. A majority (59%) had

engaged in work activity – 30% in part-time work while at university and 45% during

vacations. The amount of work undertaken was influenced by year of study. Among

undergraduates 26% worked part-time in their first year, rising to 35% in the second

year. During the third or subsequent years, the pressures of academic work tend to

reduce the proportion working part-time to some extent. However, the majority of

those who have worked part-time agreed that this had an adverse effect on their

studies. Those living with their parents or in their own home were more likely to

have part-time jobs (41%) than those who have moved away from their home

environment. This may be the result of their established links with local businesses

and the commercial environment.

A further Unite survey conducted in 2003/4 (Unite 2004) found a higher rate of work

activity with 74% of the 1,065 students interviewed reporting that they had

undertaken work at some time – 41% part-time work during term time, 25% part-time

work during vacations and 23% full-time work during vacations. This survey

contained data on students studying in Wales. Amongst these students there was a

higher propensity to work with the corresponding figures being 49% working part-

time during term-time, 27% part-time during the vacation and 32% full-time during

the vacation. Those who worked during term-time tended to be concentrated in just

three sectors – retail (33%), bar-work (16%) and catering (12%). Average earnings

were £83.40 per week and average hours 14.3. Eleven per cent of the work sample

strongly agreed that working adversely affected their studies and a further 29% tended

to agree with this statement.

TERM-TIME EMPLOYMENT: THE STUDENTS’ PERSPECTIVE

To investigate the extent of student employment in the Swansea University we created

and distributed a questionnaire. This method was selected as no existing data on

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student employment has been collected by the university. Individual interviews were

not a suitable method because of time and resource constraints. The questionnaire

was piloted on students from the Economics department. Once the design of the

questionnaire had been finalised it was distributed to students in paper form in

lectures, in the careers centre and in the students’ union. In an attempt to improve the

response rate, a web version of the questionnaire was also created.

Univariate Analysis

We received 784 usable questionnaires, a response rate of around 15%. Whilst there is

a potential problem of sample selection bias if students who work are more likely to

respond, the proportion in work is in line with that found in other studies. Comparing

those who are currently working and those who are not, female students are more

likely to be working than males as are older students and those who are originally

from Wales, particularly Swansea and if living with parents. Those living in halls of

residence are less likely to work. Having previously worked before becoming a

university student increases the probability of being currently employed, whether this

was a full-time holiday job or a part-time job during school term-time.

Nearly 46 per cent of the sample had taken up part-time work during term-time and

31 per cent had done so in vacations1. Only 3 per cent had worked full-time during

term-time, but 30 per cent had done so in the vacations. The most common jobs were

retail/sales (43 per cent), bar work (16 per cent) and waiter/waitress (6 per cent).

These were predominantly low wage jobs. In general, more teaching contact hours

seems to deter paid-employment. The main reason for seeking work was to improve

their financial situation. Of those responding to the questions on financial

circumstances, 15 per cent had received a local authority grant, 26 per cent had taken

out a student loan, 84 per cent borrowing the maximum amount. Of those not taking

out a student loan in the previous year, 18 per cent anticipated doing so in the future.

Almost a third of respondents claimed to be financially independent of their parents

prior to entering the University, but parental contribution was the most cited means of

financial preparation for being a student (54 per cent of respondents). A range of

other means was common with 49 per cent being reliant on past savings, 38 per cent 1 Number of respondents = 784. Number who worked part time during term-time = 359 giving 359/784 = 46%.

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had obtained a full-time holiday job before starting university, 32 per cent a part-time

job during school term-time and 30 per cent a part-time holiday job.2

Students claimed a wide range of hours of university tuition that they were scheduled

to receive each week, but the median number of hours was 11½ to 12 (mean 13.1

hours). This was almost identical to the number of hours of employment during a

typical term-time week (mean 13.3). The University recommends that no more than

16 hours of paid work should be undertaken. Yet almost one quarter of those working

were doing more than this and some appreciably so.

The median hourly wage was just under £5 per hour (mean £5.48) not much more

than the National Minimum Wage at the time, though it should be noted that younger

students would not be eligible for the adult rate. This confirms the fact that student

employment tends to be concentrated in the low wage labour market. However, some

flexibility in the choice of hours makes it easier for students to combine work with

their studies. Over a third of students had some control over the hours they worked.

Almost half worked a different number of hours each week and slightly less different

shifts. There was a wide variety of shift patterns, the most popular being evening

work or a combination of daytime and evenings.

A wide variety of job search methods were used, but use of friends and contacts at the

place of employment was the most popular, and may be one reason why there is a link

between being from the locality and probability of having paid employment. The next

most popular method was approaching the employer directly, which may also be

linked with a knowledge of the local labour market. University links such as the

Work link scheme or university departments were much less cited.

Of those students who were not working in term-time, the main reason given for not

working was a fear that this would reduce the grades obtained on the course (229

responses), followed by the ability to supplement income from vacation work (113

responses) and having sufficient income from a grant and/or a loan (109 responses).

Only 80 students said that they had been unable to find a suitable job and a further 26

2 More than one option may by chosen, so these add up to more than 100 per cent.

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any job at all. Of those answering the question, 52 per cent anticipated getting a term-

time job during the remainder of their course and nearly three-quarters claimed to be

actively searching for a term-time job. A similar number intended to get a job in the

vacation periods and for the vast majority this would be outside the Swansea area.

Therefore, a period or periods of paid employment in some form or other is rule rather

than the expectation for the vast majority of university undergraduates.

When examining student views of paid employment we find that for a clear majority

the availability of term-time employment was not an important consideration in

determining choice of university, though a substantial majority said the availability of

paid employment for students within the university and in the Swansea area was good.

To the vast majority it also seemed that employers appreciated their course

commitments and had tried to be flexible about the hours they worked. Students were

less positive about the role of the University in enabling them to dovetail paid

employment with their studies. They were divided about the academic staff’s

understanding of their need to work, though only a minority, if a substantial one, had

considered dropping out of university for financial reasons. About a quarter of those

working felt that the activity adversely affected their studies, but against this 58 per

cent thought the experience helped them to develop time management skills and a

third felt that their experience would help them to get a job after graduation. Most

disagreed with the statement that they had received help and advice to help them

balance the need to work with their course commitments or that they had received

help and advice from the University in choosing paid work that would minimise any

adverse effect on their studies, (though the University Careers Service was absolved

from blame by most students). Yet, more disagreed than agreed with the statement

that working during term-time had adversely affected their studies and while they

were sceptical about the ability of their employment to develop skills that would help

them with their studies they were much more positive about the development of skills

which would improve their future employment prospects. They were particularly

positive about the effect of paid employment on the development of time and

management skills. Most students enjoyed their experience of paid work and a clear

majority would continue working if the student loan was increased to match the

income they currently obtain from paid employment. However, if an additional grant

equal to the amount of income received from work was provided more would give up

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work than would continue with it. There appears, therefore, to be a certain amount of

ambivalence amongst students about the virtues of paid employment and their ability

to handle it satisfactorily.

Multivariate Analysis

In the multivariate analysis, there are two questions to be addressed. First, what

determines whether students chose paid employment or not and second given that

students have chosen paid employment what determines the number of hours they

work?

Participation equations are modelled using a probit framework where the dependent

variable takes the value one if whether students have worked during term-time at any

time during their period as an undergraduate and zero otherwise (Table 1a). In second

specification, the dependent variable takes the value one if the student is currently

working during term-time and zero otherwise. Place of origin matters (Swansea being

the omitted variable) with all the included location dummies being negative and

significant. Likewise being resident in a hall of residence significantly reduces the

probability of paid employment. Other significant negative effects arise from the

presence of children, the receipt of a parental contribution and a greater number of

tutorial hours. Significant positive effects arise from having previous paid

employment prior to entry into university. Similar effects are found in relation to

current paid employment (Table 1b) and are not discussed further.

Analysis of the number of hours worked (Table 2) is complicated by the problem that

many of the respondents report zero hours. This means that error terms in the

regression are drawn from a truncated normal distribution. To deal with this problem

We adopt a tobit estimation framework, though Ordinary Least Squares estimates are

also provided for comparison. The included variables are identical to those used in

the participation equations and generally behave in the same way. Exceptions are that

the age variable becomes significant – older students work longer hours, as does the

presence of a grant or past savings, both of which reduce the necessity for working

long hours. The OLS estimates are similar to those obtained from tobit estimation.

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Student paid employment patterns are related to place of origin, current type of

residence, type of financial support, past employment patterns and student contact

hours.

TERM-TIME EMPLOYMENT: THE EMPLOYERS’ PERSPECTIVE

To investigate student employment from the employers’ perspective, we undertook a

postal survey of employers in the Swansea in Wales. We sent questionnaires to 400

workplaces, chosen either because they had previously used the University’s careers

service to advertise a vacancy or because they were named in the student survey as an

employer. We also selected around 100 at random from the phone book to boost the

sample size. Again, we produced a web-based questionnaire in the hope of boosting

the response rate. We received 116 completed questionnaires, a response rate of 29%.

The results of the employer survey are consistent with the responses given in the

student questionnaire. Students undertake a diverse range of jobs in the area. The

stereotypical forms of student employment abound, with employers using students in

personal service (20 workplaces), sales (29 workplaces) or routine unskilled

occupations (28 workplaces) in the wholesale and retail (20 workplaces), hotels and

restaurants (34 workplaces) and other industrial sectors (9 workplaces). However,

there were a number of firms who were making use of the skills students were

learning on their courses by employing them in managerial, professional and technical

and scientific occupations. This also manifests itself in the reasons why firms

employ workers. Most firms employ students to give help at busy times with the

additional demand often generated by other students (48 firms). However, a number

of firms use the students because they have specialist skills (11 firms) or in the hope

of recruiting them after they have completed their studies (10 firms). Only three

employers cited lower wages as the reason they employed students. It should be

borne in mind that student labour in the Swansea area is drawn from a range of

institutions, the University of Wales Swansea, Swansea Institute of Higher Education,

Further Education Colleges and the secondary schools in the area. Thus, the notion of

student labour in employers’ minds might not just mean the undergraduates

considered in the student survey.

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Firms that employed students tended to have higher proportions of their workforce

aged 20 or less, from a non-white ethnic minority and paid the minimum wage.

Those firms who did not employ students tended to have higher concentrations of

part-time workers, workers with a disability and workers aged 50 or over. Of the 44

firms who did not employ students, most cited not receiving applications from

students or a lack of readily available student labour as being the main reasons. Only

three firms said they would not consider employing students in the future. The main

reason was that by the time they had trained workers to do the job properly, they

would probably leave.

Around 80% of the employers we contacted employed more than one student, with

half employing 4 or less. The organisation employing 250 students is the student’s

union. More than half the employers who employed students said that student labour

formed a significant or very significant component of their overall manpower

strategy. There is some evidence of students being employed in jobs that used to be

done by non-students; although we cannot say why this change came about.

Student labour appears to be cheap to find with most firms using low cost recruitment

methods such as the university careers centre (38 firms3) and recommendations from

other employees (29 firms). Only 8 firms used newspaper adverts.

The flexibility of student labour is emphasised by the basis on which they are

employed by firms with the majority of firms using some form of short-term contract.

Almost half of the firms who employed student workers employed them for more than

the university’s recommended sixteen hours a week. This however appears to be

matter of student choice since only 10 firms said students had no control over the

number of hours they worked. Similarly, only in minority of firms did students lack

flexibility over the times of day they worked or the days of the week they worked. No

firms said that students couldn’t take time off for reasons related to their course.

Employers generally rated students as being similar to other workers across most of

the criteria we listed, exceptions being IT and numerical skills where students were

3 Though this is possibly because of the method, by which we selected our sample.

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often rated higher. In contrast, students were often perceived as being less reliable

and less punctual.

TERM – TIME WORKING AND ACADEMIC PERFORMANCE

Of particular concern to students, policy makers and academics is the effect that

working during term-time has on student’s academic performance. To examine this

issue we used the marks obtained by students in their latest examinations and

regressed these against a set of explanatory variables including gender, entry

qualifications, accommodation type and hours of work. We model entry qualification

as a series of dummy variables capturing ranges of A-Level scores. Compared to

inserting A-level score as a continuous variable, this approach also allows us to

include those students who have qualifications other than A-levels. We derive a

student’s A-level score using the old UCAS system 10 points for an ‘A’ grade, 8 for a

‘B’ grade and so on. Credit is also given for AS level where a candidate does not go

on to complete the A level in that subject. In the case of AS levels an ‘A’ grade is

worth 5 points, a ‘B’ grade 4 points and so on. The dependent variable is the mean

mark obtained in the modules taken by the student. In theory, the correct estimation

technique is the tobit framework since the dependent variable is bounded between 0

and 100. Hence the error term is drawn from a truncated distribution. However,

because none of the observed values of the dependent variable are at, or even near,

these limits then there is practically no difference between the tobit estimates and the

ordinary least squares estimates. We model hours of using a series of dummy

variables (table 3). After experimenting with a number of different groupings

including using a dummy variable for each discrete hourly group (i.e. one dummy

indicating one hour per week worked on average; another dummy indicating two

hours per week and so on). Using this approach we find that working between one

and six hours (inclusive) has a positive impact on academic performance, possibly

through improving time management skills etc. Working more than seven hours per

week has a statistically significant negative effect on academic performance; reducing

mean module score by over 1.5 percentage points, for the average student. Beyond

seventeen hours per the effect is even greater reducing mean module performance by

over 4 percentage points. Thus, it appears that working long hours rather than

working per se which has a detrimental effect on student performance.

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CONCLUSIONS

This study attempts to ascertain the extent of student paid employment, particularly

during term-time and its impact on student exam performance, based on a survey of

Swansea University undergraduates.

Though there may be some biases in the responses we received, out results do not

appear to be out of line with previous literature. Nearly, half of the student

respondents had worked during term-time at point in their studies, averaging 12-13

hours at a mean wage of £5.50 per hour. There was a suggestion from a majority of

students that the University was not providing sufficient help to enable them to

dovetail paid employment and academic study.

The multivariate analysis reveals that students from the locality are more likely to

take up paid employment and there is a relationship between experience of paid

employment prior to university and at university. Current type of residence, type of

financial report and student contact hours also play a part.

After controlling for entry qualifications and other personal characteristics we find

that paid employment has a variable impact on student performance, measured in

terms of the mean mark, in modules taken by students. Small amounts of part-time

work, one to six hours per week are associated with an increase in exam performance.

Longer hours, however, have the opposite effect, with predicted exam performance,

for the average student, falling by 1.5% percentage points if they work between seven

and seventeen hours per week. There is support for the University’s suggested

maximum of 16 hours per week for paid employment in term-time, with predicted

exam performance falling by more than 4 percentage points for those who work more

than 17 hours per week.

One implication of this study is that an increasing tendency to study at a home

university, perhaps to reduce the costs of subsistence whilst studying as a result of

changes in the student support regime, is likely to result in an increase in student paid

employment. Universities also need to examine their provision of courses, perhaps

allowing students to vary the length of courses, although we found no evidence that

students were in favour of this.

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This research could be developed further by tracking students through their time

through university and asking them to record their employment history. The benefit

of this approach is that it would allow more sophisticated econometric techniques to

be used and stronger results obtained.4 Moreover, we could examine the effect of

term-time working on the probability that a student leaves a course and the effect on

their success in gaining employment following graduation.

4 Specifically, it would allow the use of a random effects estimator which would allow us to control for unobserved heterogeneity i.e. things that affect exam performance that are not included in the independent variables.

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TABLE 1(A) Participation Equation Dependent Variable takes value 1 if the student worked during term-time AT ANY TIME during university; 0 otherwise. Probit estimates Male -0.130 (1.200) Age 0.016 (1.244) Married 0.039 (0.186) Kids -0.722** (2.267) Other dependents 0.161 (0.390) Place of usual residence (omitted group = Swansea) South West Wales -0.487** (2.173) Wales -0.615*** (2.684) UK excluding Wales -0.976*** (4.491) EU excluding UK -0.928*** (2.808) Rest of world -0.622** (2.066) Residence Type (Omitted Group = Rented Accomodation) Own home -0.021 (0.082) Halls -0.463*** (3.788) Parents 0.213 (1.019) Other accommodation -0.043 (0.083) Grant -0.110 (0.762) Loan -0.192 (1.365) Scholarship -0.018 (0.110) Past savings -0.157 (1.463) Parental Contribution -0.215** (2.065) Hardship Grant 0.097 (0.400)

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Family loan -0.127 (0.497) Full-time holiday job 0.466*** (4.137) Part-time holiday job -0.025 (0.205) Part-time job whilst in school 0.699*** (5.884) Saved gifts/inheritance etc -0.261** (2.052) Year out 0.175 (1.013) Financially independent 0.006 (0.056) Tutorial Hours -0.029*** (3.952) Constant 0.820** (2.015) Observations 765 LR chi2(28) 152.89 Prob > chi2 0.0000 Pseudo R2 0.1444 Log likelihood -452.91554 Absolute value of z statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

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TABLE 1(B) Participation Equation Dependent Variable takes value 1 if the student is currently working during term-time; 0 otherwise. Probit estimates Male -0.109 (0.983) Age 0.009 (0.666) Married 0.042 (0.201) Kids -0.846** (2.555) Other dependents -0.018 (0.042) Place of usual residence (omitted group = Swansea) South West Wales -0.037 (0.173) Wales -0.205 (0.933) UK excluding Wales -0.520** (2.512) EU excluding UK -0.531 (1.571) Rest of world -0.206 (0.680) Residence Type (Omitted Group = Rented Accommodation) Own home 0.287 (1.183) Halls -0.391*** (3.045) Parents 0.498** (2.449) Other accommodation 0.367 (0.729) Grant 0.092 (0.632) Loan -0.251* (1.798) Scholarship -0.130 (0.755) Past savings -0.018 (0.161) Parental Contribution -0.374*** (3.550) Hardship Grant -0.181 (0.746)

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Family loan 0.061 (0.241) Full-time holiday job 0.340*** (2.967) Part-time holiday job 0.035 (0.280) Part-time job whilst in school 0.514*** (4.358) Saved gifts/inheritance etc -0.318** (2.408) Year out -0.053 (0.296) Financially independent -0.018 (0.163) Tutorial Hours -0.025*** (3.274) Constant 0.300 (0.735) Observations 765 LR chi2(28) 130.70 Prob > chi2 0.0000 Pseudo R2 0.1310 Log likelihood -433.70166 Absolute value of z statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

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TABLE 2 Analysis of Hours Worked Dependent Variable = Hours Worked in current or most recent term-time job. Tobit Estimates OLS

Estimates Male -1.989 -0.647 (1.556) (1.020) Age 0.278* 0.162 (1.786) (2.042)** Married 1.568 0.688 (0.654) (0.551) Kids -6.365* -3.567 (1.731) (1.883)* Other dependents 3.181 2.501 (0.673) (1.001) Place of usual residence (omitted group = Swansea) South West Wales -4.837** -2.906 (2.047) (2.311)** Wales -5.399** -2.571 (2.192) (1.979)** UK excluding Wales -8.917*** -4.473 (3.880) (3.691)*** EU excluding UK -7.685** -4.101 (2.007) (2.112)** Rest of world -4.048 -2.792 (1.188) (1.585) Residence Type (Omitted Group = Rented Accommodation) Own home 0.558 1.205 (0.199) (0.838) Halls -5.202*** -1.872 (3.478) (2.635)*** Parents 2.060 1.437 (0.915) (1.199) Other accommodation -1.586 -0.837 (0.270) (0.271) Grant -2.897* -1.656 (1.691) (1.958)* Loan -1.783 -1.016 (1.112) (1.234) Scholarship -0.084 -0.150 (0.044) (0.154) Past savings -2.989** -1.464 (2.388) (2.336)** Parental Contribution -3.255*** -1.533 (2.679) (2.497)** Hardship Grant -0.682 -0.080 (0.249) (0.058)

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Family loan -3.135 -0.991 (1.013) (0.659) Full-time holiday job 5.124*** 2.463 (3.891) (3.716)*** Part-time holiday job 0.692 0.526 (0.478) (0.730) Part-time job whilst in school 6.779*** 2.923 (5.022) (4.287)*** Saved gifts/inheritance etc -2.999** -1.249 (1.990) (1.683)* Year out -0.410 -0.293 (0.203) (0.293) Financially independent 0.078 0.097 (0.061) (0.151) Tutorial Hours -0.296*** -0.138 (3.439) (3.239)*** Constant 7.019 9.111 (1.502) (3.782)*** Observations 765 765 LR chi2(28) 137.30 Prob > chi2 0.0000 Pseudo R2 0.0387 Log likelihood -1707.5941 F( 28, 736) 4.68 Prob > F 0.0000 R-squared 0.1512 Adj R-squared 0.1190 Root MSE 7.8785 Absolute value of t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

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TABLE 3 The Effect of Part-Time Working on Academic Performance Dependent Variable is the average module mark obtained by the student.

Estimation Framework Tobit OLS A level score (omitted group = 30 or more points) 25-29 -4.284*** -4.284*** (3.310) (3.221) 20-24 -5.209*** -5.209*** (4.680) (4.554) 15-19 -8.690*** -8.690*** (6.835) (6.650) less than 15 points -7.940*** -7.940*** (5.718) (5.563) Other qualifications -6.974*** -6.974*** (4.290) (4.174) Hours of work (omitted group = not working/didn’t work) 1-6 3.223** 3.223** (2.317) (2.254) 7-17 -1.589* -1.589* (1.918) (1.866) 17+ -4.131** -4.131** (2.835) (2.785) Male 0.046 0.046 (0.059) (0.058) Age 0.198 0.198 (1.615) (1.571) Married 0.558 0.558 (0.360) (0.350) Kids 1.910 1.910 (0.751) (0.731) Other dependents -2.990 -2.990 (0.701) (0.682) Place of usual residence (omitted group = Swansea) South West Wales excluding Swansea -0.558 -0.558 (0.325) (0.317) Rest of Wales excluding South West Wales -1.951 -1.951 (1.130) (1.099) UK excluding Wales 1.035 1.035 (0.629) (0.612) EU excluding UK 3.359 3.359 (1.209) (1.176) Rest of the world excluding EU 5.359** 5.359** (2.060) (2.004) Residence Type (Omitted Group = Rented Accommodation) Own home -2.535 -2.535 (1.186) (1.154) Halls 0.494 0.494 (0.240) (0.234)

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Parents 1.998 1.998 (1.314) (1.278) Other accommodation -6.296 -6.296 (1.177) (1.145) Constant 58.586*** 58.586*** (18.729) (18.222) Observations 682 682 R-squared 0.200 Absolute value of t statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

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TABLE 4 Variable Descriptions Male 1 if the individual is male; 0 otherwise. Age The individual’s age in years. Married 1 if the individual is married; 0 otherwise. Kids 1 if the individual has any dependent children; 0

otherwise. Other dependents 1 if the individual has any dependents apart from

children; 0 otherwise. Swansea 1 if the individual is originally from Swansea; 0

otherwise. South West Wales excluding Swansea

1 if the individual is originally from South West Wales excluding Swansea; 0 otherwise.

Rest of Wales excluding South West Wales

1 if the individual is originally from Wales excluding South West Wales; 0 otherwise.

UK excluding Wales 1 if the individual is originally from the UK excluding Wales; 0 otherwise.

EU excluding UK 1 if the individual is originally from the EU excluding the UK; 0 otherwise.

Rest of the world excluding EU

1 if the individual is originally from the Rest of the world excluding the EU; 0 otherwise.

Rented 1 if the individual lives in rented accommodation; 0 otherwise.

Own home 1 if the individual lives in their own home; 0 otherwise. Halls 1 if the individual lives in halls of residence; 0

otherwise. Parents 1 if the individual lives with their parents; 0 otherwise. Other accommodation 1 if the individual lives in other accommodation; 0

otherwise. Grant 1 if the individual receives a local authority

maintenance grant; 0 otherwise. Loan 1 if the individual the individual has taken out a student

loan; 0 otherwise. Scholarship 1 if the individual applied for scholarship(s) to finance

their studies; 0 otherwise. Past savings 1 if the individual uses past savings to finance their

studies ; 0 otherwise Parental Contribution 1 if the individual parental contribution to finance their;

0 otherwise. Hardship Grant 1 if the individual applied for a hardship grant to

finance their studies; 0 otherwise. Family Loan 1 if the individual received a loan from my

parents/family to finance their studies; 0 otherwise. Full time holiday job 1 if the individual had a full-time holiday job before

starting university ; 0 otherwise. Part –time holiday job 1 if the individual had a part-time holiday job before

starting university; 0 otherwise. Part time job in school 1 if the individual had a part-time job during school

term time before starting university. 0 otherwise.

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Saved gift 1 if the individual saved money given to me as presents gifts/inheritance to finance their studies; 0 otherwise.

Year out 1 if the individual took a year (or more) out to work and save before starting university; 0 otherwise.

Financially independent 1 if the individual was financially independent of their parents prior to commencing university; 0 otherwise.

Tutorial hours The number of hours of university tuition the individual is scheduled to receive.

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