Does Private Higher Education Improve Employment Outcomes? Comparative Analysis from Egypt

Abstract

Private players are often perceived as powerful drivers of innovation and efficiency. This argument remains untested in the field of higher education. This paper examines whether there are differences in the labour market outcomes for graduates of public and private higher education institutions in Egypt. Relying on a unique data set tracing graduates, the analysis shows that the type of higher education institution has no statistically significant effect on graduates’ job security and earnings. Ascribed characteristics of gender and parental socio-economic background, along with the sector of employment, were the key predictors of these labour market outcomes.

Full text

Does Private Higher Education Improve
Employment Outcomes? Comparative
Analysis from Egypt
Citation: Barsoum, Ghada and Rashad, Ahmed. 2016. “Does Private Higher Education
Improve Employment Outcomes? Comparative Analysis from Egypt". Public
Organization Review (Springer). On line first at doi:10.1007/s11115-016-0367-x
Ghada Barsoum, PhD
Assistant Professor
Public Policy and Administration Department
School of Global Affairs and Public Policy
The American University in Cairo
Office Number 2076 Jameel Center
Telephone Number: 2615-3380
And
Ahmed Rashad
MA Economics
Research Fellow
Frankfurt School of Finance and Management, Frankfurt Main, Germany
Phone: 06421-2823730
Fax: 06421-2828912
Webpage:http://www.uni-marburg.de/fb02/ike/mitarbeiter/stinfo.2012-07-19.4442670106
To
Public Organization Review
On
July 3, 2016
1

Does Private Higher Education Improve
Employment Outcomes? A Comparative
Analysis from Egypt
Abstract
Private players are often perceived as powerful drivers of innovation and efficiency. This
argument remains untested in the field of higher education. This paper examines whether there
are differences in the labour market outcomes for graduates of public and private higher
education institutions in Egypt. Relying on a unique data set tracing graduates, the analysis
shows that the type of higher education institution has no statistically significant effect on
graduates’ job security and earnings. Ascribed characteristics of gender and parental socio-
economic background, along with the sector of employment, were the key predictors of these
labour market outcomes.
Keywords: private higher education, labour market outcomes, Egypt, Youth
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1. Introduction
The expansion of private higher education has been a global policy direction, described by
Altbach and Levy (2005) as a “global revolution”. About one third of global higher education
enrolment is provided by private institutions, representing the fastest growing sector in the field
(Altbach et al. 2009, Levy and Zumeta 2011). The growth of private higher education has been a
response to higher education massification, where access to education shifts from being a
privilege to the elite to trickle to middle and lower-middle classes (Trow, 2006). This process is
particularly challenging to systems with a tradition of state subsidized tertiary education, similar
to Egypt. The increasing demand for higher education places pressures for more institutions and
more student seats that goes beyond the capacity of state budgets and poses serious constraints
on education quality. This situation opens the way for a bigger role by private institutions to
respond to increasing demand. Altbach et al. (2009) note that most of the growth of private
higher education over the past decades has been in countries in the South, experiencing this
massification process. The neoliberal tide and the impact of globalization have further
constituted two driving forces for a growing role of markets in higher education (e.g. Teixeira
and Dill 2011, Mok 2009). Public policy pertaining to the private provision of higher education
is, therefore, of global importance (Levy and Zumeta 2011).
Despite the growing role of private higher education, there is little knowledge about their labour
market outcomes in comparison to public higher education. Comparative research concerning
private and public higher education is quite rare, with research primarily focusing on public
institutions (Levy and Zumeta, 2011). Whether these newcomers to the higher education
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landscape are effective in delivering quality education that prepares graduates for the labour
market is an important policy and empirical question. Students and their families, the key
stakeholders and consumers of private higher education, pay the consequences of information
asymmetries as they take the decision to choose this new and uncharted route of higher
education. This is particularly relevant to Egypt, because students in public institutions
predominantly pay nominal fees based on a meritocratic admission system, whereas those in
private institutions pay for actual education costs. It is important to investigate whether the
graduates of private institutions are getting a return on the financial investment made by their
families. Moreover, many of assumptions postulated by international agencies about the
potential benefit of expanding private higher education remain untested. For instance, private
institutions are perceived as powerful drivers of innovation, efficiency and responsiveness to the
needs of the labour market (OECD and World Bank, 2010). It has also been argued that the
incentives for quality improvement are more aligned in private institutions given the role of
market competition (World Bank, 2008). These assumptions remain to be tested.
The key research question that this paper seeks to address is whether there is a difference in the
labour market outcomes between graduates of private and public institutions. The analysis is
limited to two key specializations that have witnessed a large growth in private education
provision in Egypt, business administration and information and computing technology (ICT).
Similar to the global experience, Egypt’s private higher education is primarily provided by non-
university-ranked institutions in predominantly applied fields (Levy and Zumeta, 2011). The
analysis relies on a unique data set tracing graduates aged 25-40 years of these two
specializations. The paper focuses on outcomes related to employability in the first six months
4

upon graduation; earnings and access to job security in graduates’ current job at the time of data
collection.
The main finding of this study is that the impact of the type of the institution is dwarfed by the
impact of pre-university variables pertaining to ascribed characteristics and post-university
variables pertaining to the sector of employment of these graduates. Specifically, gender and
parental socio-economic status are shown to be significant determinants in all three models of
employability in the first six months upon graduation; earnings; and access to job security in
current job. While keeping the two specializations of ICT and business administration constant,
variables pertaining to the characteristics of the higher education institution, in terms of the type
of the institution, teaching approaches and language of instruction had no statistically significant
impact on the labour market outcomes in the analysis. Work-related variables, specifically the
sector of employment in the current job, have been consistently significant in our analysis of
labour market outcomes pertaining to access to job security and higher earnings.
This paper is organized as follows. This introductory part is followed by a description of the
higher education system in Egypt and situation of the labour market. The methodology, data and
the descriptive statistics are then discussed, followed by the estimation results. The paper
concludes with a discussion of the policy implications of these results and key transferable
lessons.
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2. Background: The Structure and Governance of the Higher Education
System in Egypt and Youth Employment Issues
The higher education system in Egypt is the largest in the Arab region. The system enrolled 2.6
million students in 2009/10 and is expected to enrol 1.1 million more students in 2021,
increasing the higher education participation rate from 28% to 35% over the same period (OECD
& World Bank 2010:22). The system carries a legacy of state monopoly over the provision of
higher education. 1 System expansion is rooted in the legacy of Egypt’s development project of
the 1960s, particularly when higher education was declared a free right to all Egyptians in 1962,
based on a meritocratic admission system. Private non-university-ranked two- and four-year
higher education institutions started to show presence in the 1970s with the implementation of
market-oriented policies. Since their inception, these private players were designed to absorb
students who could not achieve the needed score in the secondary school completion
examination to join public universities. Until the 1990s, Egyptian universities were almost
exclusively public.2 In 1992, Law 101 was passed to authorize and regulate the establishment of
private universities. Following the promulgation of the law, four new universities opened their
doors in 1996, followed by five more in 2000 and six more in 2006 (OECD & World Bank
2010). These legal changes marked a shift in the student body of private institutions, opening
the door for more achieving students to choose private education. Many of these students opt to
private education to study the discipline of their choice, as opposed to being placed in a less
desired discipline in public institutions based on their secondary education examination score.
1 This has been the case despite the fact that the first modern university in Egypt, Cairo University, was
established as a private university in 1908.
2 A key exception was the American University of Cairo, which was founded in 1919 as private non-profit
American institution. The sample did not include graduates of this institution.
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According to recent data obtained from the Ministry of Higher Education, private institutions
provided enrolled about 21.2% of tertiary education in Egypt in 2010/11. Most of this private
education is provided by non-university-ranked institutes (providing 17.6% of total higher
education enrolment in 2010/11). The number of these institutes, however, jumped from 132
institutes in 2010/11 to 171 in 2014/15 as shown on the Ministry of Higher Education’s website.3
Private universities only provide higher education to 3.5% of students enrolled in tertiary
education in Egypt, provided by 20 private universities in 2014/15, up from 19 universities in
2010/11. Similar to the global experience, it is envisioned that the role of private institutions will
increase with population growth and higher education massification. A larger role by private
higher education institutions has been one of the key recommendations by international entities
to the Egyptian government (e.g. OECD and World Bank 2010, World Bank 2008).
This complex structure is closely governed by the state, in a system described as “highly
centralized” (OECD & World Bank 2010). Operationally, the Ministry oversees the process of
approving new private institutions and regulating existing institutions through specialized sub-
bodies. This supervisory role primarily focuses on education inputs of student-to-staff ratios,
faculty credentials, and taught curricula to ensure comparability with public institutions for
degree accreditation. This governance structure is similar to what Neave (2012) terms as the
“maintenance mode” of evaluation, describing the governance structure in Europe before the
Bologna process with its earlier focus on a priori education inputs. In the case of Egypt, this
3 Data provided in this paragraph build on the author’s communication with the Strategic Planning Unit at
the Ministry of Higher Education. The author is grateful for the support extended by this unit to the study.
More recent data was obtained from the governmental website for higher education admission:
http://www.tansik.egypt.gov.eg/application/Certificates/Fani/Dalel/12.htm.
7

focus on education inputs is aimed to ensure that students in private institutions get similar
curricula to those in public institutions and are taught by faculty that are equally qualified. This
governance structure measures private institutions based on the yardstick of education inputs in
public institutions. This is probably one reason for the similarity of education outcomes of
graduates of the two types of institutions as the analysis in this paper shows.
The graduates of both public and private institutions, however, transition to a labour market that
is characterized by high educated youth unemployment. Those with post-secondary education
constitute 39 per cent of the unemployed (Assaad and Krafft, 2013). Unemployment affects
approximately one-sixth (15.7 per cent) of the youth (15-29) in the Egyptian labour market
(Barsoum et al., 2014). Young women are at a particular disadvantage, with their unemployment
rate reaching more than five times the rate among young men (38.1 per cent compared to 6.8 per
cent) (Barsoum et al., 2014). Moreover, unemployment is not the only concern about youth
labour market outcomes in Egypt. Nine out of ten workers from the youth aged 15-29 (91.1 per
cent) are in informal employment in Egypt (Barsoum et al., 2014). These include workers in
informal (unregistered) enterprises and paid employees holding informal jobs in the formal
sector but do not receive other benefits such as social security contributions or paid annual or
sick leave. Higher education in Egypt has long been a shelter from employment informality,
thanks to a scheme of guaranteed employment for graduates in the civil service and state-owned
enterprises that was initiated in 1962. This sector of employment provides formal job stability
and security benefits that are not matched by the private sector. However, with the relinquishing
of the guaranteed employment scheme and the implementation of structural adjustment policies
in the early 1990s, university graduates came to face new realities of employment informality
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and limited access to job security (Barsoum, 2015). Employment characteristics, however, are
greatly defined by the sector of employment in Egypt. The civil service sector and state-owned
enterprises provide employees with work stability, access to work contracts and different social
security benefits. Their salaries, however, can be lower than the formal private sector (Said,
2009). Barsoum (forthcoming) documents the continued valorisation of civil service jobs among
youth for benefits related to job security.
3. Research Framework
3.1 Research on Private Institutions and Higher Education Outcomes
There is little empirical research examining the labour market outcomes of private higher
education institutions in comparison to public institutions. The fact that the growing role of
private institutions is a relatively recent phenomenon in the higher education landscape
worldwide explains this dearth of empirical studies. The novelty of the phenomenon and the
typology of institutions take the prime focus of research (e.g. Altbach et al. 2009, Levy 2011,
Mok 2009, Teixiera and Dill 2009). Similarly, the notion of “privateness” in higher education
and the impact of globalization and the neoliberal tide dominate the literature (e.g. Mok 2009,
Levy 2011). Issues of governance and relationship to the state have also attracted researchers
and debates (e.g. Dobbins and Leišyte 2013, Neave 2012). Hazelkorn (2011) has particularly
focused on governmental role in education assessment in view of the growth of private
institutions. She identifies two key global approaches: the Finnish Higher Education Evaluation
Council, which assesses higher education institutions based on their own criteria; and the
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Australian government approach with its stringent standards and outcomes. In Egypt, most of
the research on private higher education focuses on their impact on equity of access to higher
education due to the legacy of state subsidy (e.g. Fahim, 2010; and Al-Araby, 2010).4
There is, however, a rich body of literature on higher education access and outcomes that would
be relevant to a comparative study of private institutions in Egypt. In this literature, the role of
the family background and socio-economic status is shown to be a significant determinant of life
opportunities and labour market outcomes. The Nobel Prize winner, Gary Becker (1988:10),
stresses how earnings regress strongly to the mean between fathers and sons “in every country
with data” that he has seen. Rumberger (2010), looking at data from the United States,
highlights the powerful impact of social class background on college completion, showing that
the odds of completing college for a student from a higher socio-economic status are more than
six times higher than for a student from a lower social class background. Similarly, Bowles and
Gintis (2002: 21–22) note that parental income and wealth are strong predictors of the likely
economic status of the next generation. The sociological literature on the impact of family
background on education outcomes is abundant. Seminal works by Pierre Bourdieu and
colleagues stress the impact of social and cultural class reproduction (for example Bourdieu,
1990; and Bourdieu and Passeron, 1977).
A few studies focused on determinants pertaining to the characteristics of the higher education
stage and their impact on labour market outcomes. For example, Rumberger and Thomas (1993)
focus on the role of the type of specialization, the undergraduate performance as measured by
4 A key exception is Assaad et al. (2014) who looked at different labour market outcomes for graduates of
public and private institutions in Egypt and Jordan.
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grade point average (GPA), and the quality of the higher education institutions. Smith et al.
(2000) similarly focused on the effect of the subject of study and ranking of the institution as
significant determinants, while still accounting for the importance of family background and
socio-economic status on labour market outcomes in the United Kingdom. Taking a comparative
approach, Støren and Wiers-Jenssen (2010) compared outcomes of foreign and local diplomas in
labour market outcomes in immigrant societies.
In terms of outcome variables, earnings and employability remain the predominant variables in
empirical research on higher education. Rumberger and Thomas (1993) looked at earnings as
their dependent variable. Smith et al. (2000) focused on the employability of graduates and their
first destination as the outcome variable. This paper extends the analysis on labour market
outcomes for higher education by also looking at job security as a third outcome. The rationale
for the inclusion of job security relates to the earlier discussion on the increasing employment
informality in Egypt, particularly among the youth. This analysis resonates with Baah-
Boateng’s (2015) argument for the inadequacy of the focus on unemployment as a
measure of economic integration in contexts with high informality such as sub-Saharan
Africa or the Middle East. By addressing job security as an education outcome, it is
hypothesized that investment in higher education would safeguard graduates from precarious
jobs and would offer a higher level of job security in comparison to the general population.
Job security remains an understudied domain in relation to higher education outcomes. This is
probably the case since it has been long assumed that graduates of higher education would be
sheltered from insecure jobs by virtue of their education, despite global evidence that this is not
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the case (e.g. Standing 2011, Castells and Portes 1989). Anker et al. (2002, 2003) address
security at work in relation to the need to help safeguard health, pensions and livelihoods, and to
provide adequate financial and other protection in the event of health and other contingencies.
The focus on job security recognizes workers’ need to limit the insecurity associated with the
possible loss of work and livelihood. Adequate social protection is a defining feature of decent
work around the world (Anker et al., 2002:52). The International Labour Organization estimates
that only about 20 per cent of the world’s labour force has access to adequate social protection
(Anker et al., 2002).
3.2 Research Question
This paper is concerned with the question on whether there are differences in the labour market
outcomes between graduates of public and private higher education institutions. The paper
addresses three specific labour market outcomes: the employment probability during the first six
months after graduation; the level of job security in the current job through a constructed job
security index as discussed in the following section; and the earnings of the current job at the
time of data collection.
4. Data and Method
The paper benefits from the analysis of a recently fielded household survey (2012) tracing
university graduates aged 25-40 in two disciplines that have been the target of private education
institutions, namely business administration and information technology. The questionnaire
collected information on graduates’ socio-economic background and parental characteristics,
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education experience, first job experience, current job experience and employment history and
mobility. The sample for this survey has been extracted from the national sample of the Labour
Force Survey (LFS), with the help of Egypt central statistical bureau, CAPMAS.5 The
interviewed graduates were a sub-sample of the LFS. The sample of the LFS is a nationally
representative sample extracted based on a two-stage stratified cluster sample and self-weighted
to the extent practical (CAPMAS, 2012). The survey sub-sample was selected based on a
number of criteria. Because university graduates are highly heterogeneous in terms of skills and
specialization, we limited the sample and the analysis to a small number of specializations,
namely business administration and information sciences. As noted earlier, these two
specializations were selected because of the larger role of private universities play in the
production of these skills. The survey focused on graduates aged 25-40 in these two disciplines
who are currently working or have ever worked.
The final sample of the survey had 1,713 graduates. Out of this sample, 413 respondents
graduated from private higher education institutions, constituting 24% of the sample. This is a
good representation that resonates with national statistics about private higher education in the
country as noted earlier. The mean age of the subsample of graduates was 28.9 years, with a
standard deviation of 4.2 years. About 74% of the respondents in the sample were male. This
gender skewedness in the sample representation is due to the fact that the survey design limited
the criteria for inclusion to graduates who ever worked. The increasing de-feminization of the
Egyptian labour market (Assaad, 2005) explains this low representation of female graduates in
the sample.
5 Central Agency for Public Mobilization and Statistics. Data collection for this study was undertaken by
CAPMAS in collaboration with the Economic Research Forum.
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4.1 Methodology
Using the graduate tracer study data, the analysis in this paper is based on two modeling
approaches: linear probability model regression for the probability of employment in the first six
months after graduation; and ordinary least squares (OLS) analysis of determinants of access to
job security and earnings. The dependent variable of our second model, job security, is
an index built based on access to the following benefits: a stable work contract that is
for a minimum duration of one year; social insurance; health insurance; paid annual
leaves; paid sick leaves; end of service compensation; and access to bonuses and
salary raises.6 In the analysis of the third model, wages in the current job are transformed into
natural log form. This reduces the influence of outliers in income and allows for the
interpretation of the effect of covariates as a per cent change in wages.
The paper examines three categories of explanatory variables for all three models:
1. Pre-higher-education variables: These include gender (with 1 as male and 0 as female to
show the male effect); years since graduation; access to computers at home at age 15;
pre-university type of schooling in terms of access to foreign languages (with dummy 1
for private language schools, which are more expensive than public schooling); and score
in the secondary education graduation completion examination “thanawya ama”.
Analysis also includes the father’s highest education level (with dummy 1 for post-
6 The job security index is based on a principal components analysis with each of these characteristics receiving a
weight based on the analysis of principal components.
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secondary education; and mother’s highest education level (with dummy 1 for post-
secondary education). The model also has a dummy 1 for those living in metropolitan
governorates. The analysis controls for the age of the respondent by including an
explanatory variable on the years since graduation. By controlling for these pre-
enrolment characteristics, the analysis corrects for selection bias into private versus
public higher education institutions.
2. Higher education institutional level variables: These include the type of the higher
education institution (private versus public) is included as a binary variable, with 1 for
private institutions. Other institutional level variables included in the analysis are the
language of instruction in higher education (dummy variable for access to teaching in
English or a mix of English and Arabic); and use of active learning methods in teaching
(group work, problem solving techniques, student presentations and research projects,
with a dummy variable of 1 for any of these teaching techniques). In absence of
institutional ranking in Egypt and other quality variables, similar to those used by
Rumberger and Thomas (1993) or by Smith et al. (2000), the analysis is limited to these
variables at the institution level.
3. Post-education variables including whether the graduate had internships opportunities;
volunteering experience; summer-time employment during school; and sector of current
employment. The latter is only used for the two models related to job security and
earnings labour market outcomes. The analysis includes a dummy 1 for employment in
civil service and publically owned enterprises.
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5. Results
5.1 Descriptive Statistics
Data analysis shows that more than half the graduates in the sample were working in the first six
months following graduation, with 51.9 per cent as wage workers, 2.3 per cent as employers and
4 per cent being self-employed. Unemployment prevalence in the first status after graduation
was at 29.3 per cent among all graduates, with more prevalence about graduates of public
universities (30.5 per cent) than among graduates of private universities (26.9 per cent).
Moreover, 11.1 per cent of graduates were detached from the labour market (not in employment
or searching for employment), with the prevalence among graduates of private universities
higher than among public universities (17.8 per cent compared to 7.7 per cent). These results are
commensurate with labour statistics in Egypt with regards to university graduates discussed
earlier.
In terms of job security, descriptive analysis of survey data shows that graduates of private
institutions generally had lower access to job security (with a mean score of -0.10 compared to
a mean score of 0.05 among graduates of public institutions). Because employment
characteristics are greatly defined by the sector of employment in Egypt as noted earlier, the
analysis relies on the sector of employment as one of our explanatory variables for Models 2 and
3. The sector of employment is a key determining factor in access to social security in Egypt.
16

Analysis of descriptive statistics on the sector of employment among graduates shows that the
majority of working graduates were employed in the private sector. However, more of the
graduates of private institutions were employed in the private sector than graduates of public
institutions (85.2 per cent versus 78.6 per cent).
In terms of job earnings, descriptive statistical analysis show that the mean current salary for
graduates from both public and private institutions was LE 1531.27 (about US$230 according to
the exchange rate at the time of data collection) and the minimum monthly pay was LE 200
(about US$50). Table 1 provides a description of all variables included in the analysis.
Table about here
5.2 Estimation Results
In the following discussion of the estimation results of the three models, the focus will be
on variables that were shown to be statistically significant in the tables. Explanatory
variables shown to be not statistically significant are not discussed, except in relation to
the argument of the paper.
5.2.1 Employment in the first six months after graduation
The first model explores the probability of being employed within six months of graduation for
graduates of both types of institutions. Table 2 includes the results of this model. The
likelihood-ratio tests indicate that all three specifications included in columns 1,2, and 3 are
significant based on the F-test and chi2 test results shown on the table. However, the explanation
power of the model increases from column (1) to (2) to (3) with the addition of education and
post-education explanatory variables.
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The results indicate that there is a statistically significant negative impact of graduating from a
private institution on the likelihood of getting a job in the first six months following graduation.7
As the descriptive statistics discussed above show, more of the graduates of private institutions
were detached from the labour market in the first six months following graduation. This might
reflect a preference in the job market for graduates of public institutions; or lower social capital
and networking potentials to find jobs among these graduates of private institutions.
Alternatively, unemployed graduates might just be in a situation where they would prefer to wait
for better opportunities and do not accept the first job opportunity made available to them.
Gender is shown to be a significant determinant to the likelihood of finding a first job within six
months of graduation. Table 2 shows the male advantage in the probability of getting a job in
the first month upon graduation. Female high unemployment is a key characteristic of the labour
market in Egypt (Assaad and Krafft 2013). This tracer study shows that being female places the
graduate at a disadvantage in the likelihood of finding a job in the first six months following
graduation. It can also show that women are more likely to wait for an appropriate job
opportunity.
Another variable showing a significant impact on the likelihood of getting a job in the first six
months following graduation is the number of years since graduation. Older graduates seem to
have been less privileged than the more recent graduates as these results suggest. The years
since graduation variable here is to be interpreted as a cohort effect. One explanation for this
was provided by Assaad and Krafft (2013) who argue that the impact of the youth bulge on the
7 In odd-ratio modeling, less than one is the marker of a negative impact
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labour market has eased, comparing data from 2006 and 2012. This places more recent
graduates at a better advantage compared to earlier cohorts that were part of the youth bulge.
Table
Another significant predictor in this model as Table 2 shows is summer work. In the context of
OECD countries, public programs promoting early labour market contacts for high school
students are commonplace and have been repeatedly advocated by the OECD (Alam, Carling and
Nääs, 2013). Häkkinen (2006) notes that pre-graduation employment may provide an
opportunity complement the formal education and improve study motivation, particularly when
the employment relates to the field of study. Pre-graduation work allows to improve job search
skills along with other important life skills such as better communication skills (2006). These
opportunities also familiarize students with the world of work and allow them to gain a sense of
responsibility. These valuable skills can have a positive impact on employment outcomes post-
graduation. Häkkinen (2006) also argues that summer employment might signal potential future
employers about attributes such as motivation and work ethics. Other favourable arguments for
summer jobs discussed by Alam, Carling and Nääs (2013) include access to labour-market
relevant skills; the potentials to enhance motivation to study; earnings to alleviate poverty; and
the potentials for social networking to help in finding the first regular job.
5.2.2 Level of Access to job security in the Current Job
The second dependent variable relates to access to job security measures in the current job. In
this model, multivariate OLS is applied. Unlike the earlier model on the probability of finding a
job in the first six months after graduation, the results of this model indicate that the type of
19

institution does not have a statistically significant impact on the level of job security in the
current job, with a value coefficient that is very close to zero. Other institutional-level variables
such as teaching approaches also do not hold a significant impact on this labour market outcome.
The results in Table 3 show that ascribed characteristics are significant determinants to labour
market outcomes in Egypt. Father’s post-graduate education is a key determinant to the level of
job security in the current job. Private schooling in the primary stage is another statistically
significant determinant. This is a proxy for family higher socio-economic status since private
pre-university education is more expensive than public schooling. The impact of these ascribed
pre-education variables dwarf the effect of the type of higher education institution in the labour
market outcome pertaining to job security.
Gender, or the male effect in this model, which had a significant positive effect in the earlier
model, has a significant but negative effect in this model. This can be explained by the fact that
when educated women work in Egypt, the public sector is their main employer (Hendy, 2012).
In fact, the sector of employment in the current job is shown to be a key determinant of level of
access to job security. As Table 3 shows, employment in the civil service or publically owned
enterprises is positively associated with a higher level of job security and benefits.
Male graduates, on the other hand, are not concentrated in public sector jobs, but are distributed
among other sectors. The impact of gender, however, is not statistically significant in the third
column, the last iteration of the model, with the inclusion of job characteristics and the sector of
employment. This shows that the gender effect has been a proxy for employment in the public
sector.
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Score in the secondary education completion examination had a positive significant impact on
the level of job security. Higher scores could indicate higher innate abilities pertaining to hard
work or intellectual and mental capabilities. While the impact of the score is not significant in
the first model, perhaps because students with higher scores might prefer to wait for better jobs,
it pays off in terms of job quality as Table 3 shows. The score can also be a proxy for the family
background and socio-economic status. Because it is common for families to complement
secondary education schooling with private tutoring, higher scores can be a proxy of the family’s
spending on this usually costly support to students in order to perform better in the final
examination (El-Badawy, 2009).
The number of years since graduation had a significant positive effect in this model, similar to
the earlier one. This can be understood as a cohort effect, as the analysis in this model confirms
that more recent cohorts, particularly those that came after the demographic youth bulge, fare
better in the employment outcome pertaining to job security as they did in terms of their
employment probability in the first six months post their graduation. This variable can also be
understood as reflecting the impact of years of experience among the employed, which concurs
with international literature on the decent work deficit among new entrants to the labour market
from the youth (ILO, 2014).
However, summer work, which had a positive significant impact in finding the first job in the six
months upon graduation, did not have significant impact on job security in the current job. This
might signify that the rush towards the labour market might result in obtaining any job, as
21

opposed to a better quality job. Conversely, Table 3 shows that internships had a significant and
positive impact on job quality. This corresponds with the global literature, where pre-graduation
work-related experience in the field of study is associated with better labour market outcomes
(Häkkinen, 2006).
Table
5.2.3 Earnings of Current Job
In the analysis of the third model, wages in the current job are transformed into natural log form.
The results in Table 4 show that private higher education is only associated with a positive
impact on income when the employment post-education variables are not controlled for. Once
these variables are included in the analysis, the impact of the type of the institution is not
statistically significant.
The results in Table 4 support the arguments made earlier about the role of ascribed
characteristics. First, gender remains a major predictor of income. Being male is associated with
an increase of income by more than 50% (Table 4). Another significant predictor is the father’s
access to post-secondary education, which is associated with higher income in the current job.
As the table shows, the value of the father education coefficient is quite high relative to the rest
of the variables, associated with an approximate 20% increase in wages. Also statistically
significant and directly related to the family background is the access to primary private
schooling. Private schooling is a marker of family wealth. Better-off families opt to give their
children more expensive private schooling, particularly in the early stages. The earlier argument
22

about the role of the score in the secondary education completion examination in determining the
level of job security is also valid in relation to income. Similarly, employment in a metropolitan
area, given the higher living costs in these areas, is associated with higher income.
Summer education, which has been a significant determinant of finding a job in the first six
months following graduation, has no significant impact on income in the current job. However,
Table 4 shows that one additional year of experience after graduation increases nominal salary by
4 per cent.
The sector of employment is a key determinant of earnings similar to the earlier model on the
level of access to job security. However, while employment in the civil service or publically
owned enterprises is positively associated with a higher level of job security and benefits, it has a
negative impact on income. This can be explained by the fact that other non-pecuniary benefits
included in our second models are offered by this sector in relation to job security.
Table
6. Conclusion and Transferable Lessons
The analysis in this paper shows that the type of the institution did not have a statistically
significant impact on labour market outcomes for graduates in ICT and business in Egypt.
23

Ascribed characteristics, particularly gender and parental socio-economic status, were the
significant determinants to the likelihood of finding a first job within six months of graduation;
the level of job security in current job; the earnings in current job. Score in the secondary
education completion examination had a positive significant impact on the level of job security
and income. While higher scores could indicate higher innate abilities pertaining to hard work or
intellectual and mental capabilities, they can also be a proxy for the family socio-economic status
due to the prevalent use of private tutoring. The impact of the score in secondary education
completion examination can be, therefore, related to the parental socio-economic background
and an ascribed characteristics. The type of the higher education institution, and other
characteristics pertaining to teaching approaches and language of instruction, had no significant
impact on the labour market outcomes. This corresponds with the argument by Assaad et al.
(2014), looking at data from Egypt and Jordan, that the labour markets in these two countries are
less responsive to the education institution variables and are primarily affected by ascribed
characteristics of family background and gender. As the analysis in this paper shows, pre-
education and post-education variables mattered most in determining the labour market
outcomes, regardless of the type of higher education obtained and its characteristics.
A number of issues in relation to the difference between private and public higher education
institutions seem to be dwarfing the impact of the type of the institution on labour market
outcomes in Egypt. The first is that private institutions are at fees, whereas public institutions
are predominately for nominal fees. With the significant impact of the family socio-economic
background discussed in this paper, the fees paid could signify a higher socio-economic
background and would be associated with a positive impact on the labour market outcomes of
24

graduates from private institutions. However, the fact that not all public institutions are for
nominal fees confounds this argument. Elite at-fees programs that provide education in foreign
languages in public institutions confound these results. This has been the case for business
administration, with English section opened at higher fees. The presence of these programs
confounds the difference between public and private institutions labour market outcomes.
Moreover, with the exception of elite universities, private institutions accept lower grades in the
secondary education completion examination. Graduates of public institutions, therefore, could
have higher innate abilities pertaining to hard work or intellectual and mental capabilities. This
would have an unobservable impact on labour market outcomes. Moreover, because public
institutions accept students with a higher score, this too can be a proxy to a higher socio-
economic background as noted earlier.
Employment characteristics, specifically those pertaining to the sector of employment, have been
consistently significant in our analysis of their labour market outcomes in terms of job security
and earnings. This is considered as an intermediary variable, as graduates of public institutions
were more likely to join the civil service and publicly owned enterprises thanks to recent
regulation where top performing students from public higher education institutions are invited to
apply to civil service jobs (El-Baradei, 2013). Jobs in the civil service provide social security
measures that are unmatched by the private sector. This explains the association between public
higher education and higher access to social security. The private sector, on the other hand,
compensates for its limited benefits by providing relatively higher wages. Finally, The argument
in relation to the impact of summer work corresponds with the mixed results in the international
literature on this issue (Häkkinen, 2006; Hotz et al., 2002; Alam et al., 2013). Summer work is
25

positively associated with the likelihood of finding a job in the first six months after graduation.
However, its impact diminishes in looking at the level of job security or income in the current
job.
Context-specifity aside, there is a number of transferable lessons in this analysis. First, the
analysis in this paper shows that while private institutions are successful in offering more seats
for students and hence increasing access to higher education, they might not provide a
qualitatively different education experience that would have an impact on labour market
outcomes. Second, this similarity of outcomes can be related to the state governance model of
private institutions. Egypt’s governance model of private institution, discussed earlier, is based
on the control of education inputs. Education inputs in public institutions are also used as the
yardstick for assessing education inputs in private institutions. Third, a key lesson relates to the
importance of a policy focus on education outcomes. The data from Egypt show that the
system’s lack of emphasis on education outcome measurement does not propel these newcomers
to the higher education landscape to address such outcomes. This “maintenance mode” of
evaluation, as Neave (2012) describes this governance structure, reflects an out-dated
governance model that fails to provide the incentives to these institutions to provide better
outcomes.
The key transferable lesson from this analysis pertains to the need for an effective state steering
role with policies geared towards propelling both public and private institutions to focus on
education outcomes. In countries with excess demand for higher education, as in the case of
Egypt, private institutions suffice with their role to address the access challenge and absorb
26

demand. Competition for quality and innovation take less priority in an eco-system of this
nature. The requires a paradigm shift in the state governance structure, with policies to hold
institutions accountable for education outcomes and performance. Whether this can be done by
adhering to government standardized outcomes or by holding institutions accountable based on
their identified objectives (Hazelkorn, 2011), students and their parents deserve to be able to
make informed decisions.
27

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Table : Summary Statistics
Variable Obs Mean Std. Dev Min Max Variable Description
Dependent Variable
Emply 1710 0.58 0.49 0 1 First employment during the six months following graduation
Security_index 1505 0 1 -1.0 1.5 index of job security
logwage 1371 7 0.77 5.2 10.4 Log salary in current position
Individual background
Gender 1710 0.74 0.43 0 1 Male=1 , female=0
Yrsgrd 1710 6.50 4.2 0 20 years since graduation
Computer use 1710 0.33 0.47 0 1 Access to computer at home at age 15
Private_school 1710 0.23 0.42 0 1 pre-university type of schooling in terms of public or private, private =1,
other=0
Father_edu 1703 0.59 0.49 0 1 Post secondary education=1 and zero equals zero otherwise
Mother_edu 1702 0.44 0.49 0 1 Post secondary education=1 and zero equals zero otherwise
Score 1654 75.7 9.6 50 97 Grade percentage in the secondary education graduation completion
examination “thanawya ama”
Institutional variables
univ_priv 1710 0.33 0.47 0 1 0-1 dummy variable, =1 if student is a graduate of private institute
(University or institute)
language 1710 0.15 0.36 0 1 language of instruction in higher education, English or English and
Arabic=1, only Arabic=0
Active 1710 0.33 0.47 0 1 use of active learning methods in teaching in higher education. Dummy
variable=1 if teaching always involves groups projects, research projects,
students’ presentations, teaching based on problem solving and case studies
Post-graduation
variables
internship 1710 0.11 0.32 0 1 Had an internship during university study=1 and otherwise=0
summerwork 1710 0.46 0.49 0 1 Had a job during university study or summer vacation during the
bachelor=1 and otherwise=0
volunteer 1710 0.05 0.22 0 1 Volunteer work during university study=1 and otherwise=0
Sector 1527 0.19 0.39 0 1 Employed in civil service or publiclly-owned enterprises
Source: Authors’ calculations, survey data
34

35

Table : Probability of Employment within the First Six Months Upon Graduation
(1) (2) (3)
VARIABLES odds ratio odds ratio odds ratio
1.gender 1.583*** 1.581*** 1.195
(0.186) (0.186) (0.152)
yrsgrd 0.951*** 0.952*** 0.962***
(0.0119) (0.0120) (0.0124)
1.computer_use 1.033 1.027 1.072
(0.121) (0.121) (0.128)
1.private_school 0.892 0.882 0.931
(0.111) (0.110) (0.121)
score 1.000 1.000 1.001
(0.00584) (0.00587) (0.00599)
1.univ_priv 0.676*** 0.658*** 0.629***
(0.0814) (0.0815) (0.0815)
1.father_edu 1.107 1.116 1.226
(0.144) (0.145) (0.162)
1.mother_edu 0.858 0.848 0.872
(0.111) (0.110) (0.114)
1.language 1.227 1.248
(0.176) (0.183)
1.active 1.015 0.987
(0.112) (0.112)
1.internship 0.886
(0.147)
1.summerwork 1.915***
(0.226)
1.volunteer 1.280
(0.320)
1.metropolian 0.830*
(0.0913)
Constant 1.579 1.544 1.265
(0.775) (0.760) (0.638)
Observations 1,641 1,641 1,641
Pseudo R2 0.0363 0.0363 0.0363
chi2 44.90*** 46.62*** 78.26***
Robust see form in parentheses
*** p<0.01, ** p<0.05, * p<0.1
36

Table : Determinants of Job Security Level at the Current Job
(1) (2) (3)
VARIABLES job_index job_index job_index
1.gender -0.168*** -0.166*** 0.0643
(0.0623) (0.0623) (0.0593)
yrsgrd 0.0695*** 0.0695*** 0.0402***
(0.00645) (0.00646) (0.00614)
1.computer_use -0.0429 -0.0425 -0.0744
(0.0544) (0.0544) (0.0495)
1.private_school 0.0930 0.0916 0.144**
(0.0611) (0.0615) (0.0585)
score 0.0120*** 0.0122*** 0.0103***
(0.00287) (0.00289) (0.00261)
1.univ_priv 0.0183 0.0226 0.0215
(0.0593) (0.0611) (0.0562)
1.father_edu 0.203*** 0.203*** 0.170***
(0.0630) (0.0632) (0.0555)
1.mother_edu 0.0908 0.0907 0.0304
0.0908 (0.0640) (0.0561)
1.language 0.0296 0.00725
(0.0718) (0.0606)
1.active -0.0376 0.00834
(0.0534) (0.0489)
1.internship 0.166**
(0.0748)
1.summerwork -0.0296
(0.0503)
1.volunteer 0.0525
(0.107)
1.metropolian 0.0315
(0.0484)
1.work sector 1.168***
(0.0584)
Constant -1.413*** -1.421*** -1.490***
(0.244) (0.244) (0.220)
Observations 1,445 1,445 1,445
R-squared 0.116 0.116 0.313
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
37

Table : Current Job Earnings (Log transformed)
(1) (2) (3)
VARIABLES logwage logwage logwage
1.gender 0.531*** 0.525*** 0.481***
(0.0439) (0.0439) (0.0473)
yrsgrd 0.0388*** 0.0394*** 0.0453***
(0.00455) (0.00456) (0.00476)
1.computer_use 0.0481 0.0464 0.0607
(0.0411) (0.0410) (0.0409)
1.private_school 0.154*** 0.151*** 0.125***
(0.0438) (0.0439) (0.0442)
score 0.00829*** 0.00788*** 0.00771***
(0.00207) (0.00208) (0.00208)
1.univ_priv 0.128*** 0.107** 0.0801*
(0.0434) (0.0445) (0.0451)
1.father_edu 0.179*** 0.184*** 0.203***
(0.0460) (0.0460) (0.0462)
1.mother_edu 0.0170 0.0108 0.0222
(0.0458) (0.0458) (0.0456)
1.language 0.0383 0.0295
(0.0496) (0.0496)
1.active 0.0844** 0.0506
(0.0398) (0.0404)
1.internship 0.0182
(0.0577)
1.summerwork 0.0526
(0.0410)
1.volunteer 0.111
(0.0825)
1.metropolian 0.0854**
(0.0385)
1.sectortotal -0.171***
(0.0467)
Constant 5.551*** 5.558*** 5.540***
(0.176) (0.176) (0.177)
Observations 1,287 1,287 1,287
R-squared 0.171 0.174 0.191
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
38

39