This document analyzes factors affecting education in Pakistan through domestic and international analyses. Domestically, it studies expected years of schooling for Pakistani children ages 5-9, finding gender bias and relationships between schooling expectations and income, family size, and distance to school. Internationally, it compares Pakistan's primary enrollment and adult literacy rates to other countries, finding relationships between enrollment, literacy, life expectancy, teacher ratios, and gender balance of teachers. Primary enrollment is highest in grade 1 and declines in later grades in medium HDI countries like Pakistan, India, and Bangladesh. Adult literacy correlates with female teacher percentages, mortality rates, and life expectancy.

1. A Domestic and Cross-Country Analysis of
Expected Schooling, Primary Enrollment, and
Adult Literacy
Saahir Shafi1
,Faisal Azim2
, Mehad Azeem3
1
University of Punjab, Lahore, Pakistan (saahir23@gmail.com)
2
University of Manchester, Manchester, United Kingdom (shahinshahfaisal@gmail.com)
3
Center for Advanced Studies in Engineering, CASE, Islamabad, Pakistan (Mehad08@gmail.com)
Abstract -- The study seeks to investigate those factors
which act as constraints against actual educational
attainment decisions. For this purpose, a field survey was
conducted to investigate the socio-economic trends which affect
the current decisions of parents considering their children’s
expected years of schooling. The population under study was a
group of 80 lower middle income class families with children
between the ages of 5-9, belonging to various villages across
Pakistan. Results suggest a gender bias in expected years of
child’s schooling as well as the significance of factors such as
total monthly family income, total number of children, distance
of nearest schools to home, and child’s performance in school.
Child’s performance in school was found to be directly related
to teacher education levels and satisfaction with quality of
schooling. A cross-country comparison was carried out to
determine international factors that contribute to low primary
enrollment and adult literacy rates in Pakistan against those of
other countries from varying human development index
rankings. Results show a coincidence of health and education
sector problems as predominant factors affecting both primary
enrollment and literacy rates. Further, international analysis
revealed a possible relationship between primary enrolment
and retention rates of medium human development countries
with human development indices and adult mortality rates.
Keywords: expected schooling, net primary enrollment,
adult literacy, grade retention levels, cross-country
1. INTRODUCTION
The existing primary educational system in Pakistan has not
been able to give desired results. The deteriorated public
school system is physically difficult to access by a major
proportion of the population while the expenses and material
outlays of sending their children to school prove to be more
than most parents can or will afford to pay for low standards
of education with no visible short or long term benefits [1].
As a result, the average male child is reported to receive 5
years of education, while the average female child receives
2.5 years[2]. The importance of primary schooling is
established as previous research states that only two third of
children in Pakistan become enrolled in primary school and
only one third of those enrolled complete the fifth grade [2].
The factors that play into Pakistan’s ineffective public
provision of education include non-existence of cost-
effective schooling and poor curriculum, especially in rural
areas [3]. In a related study, it was found that in urban slums,
poverty was the main factor affecting demand for schooling
[4]. Historically the government has tried to expand primary
education by establishing schools, but its qualitative
improvement has been ignored [5]. Further, the allocation of
government funds is skewed towards higher education so
that the benefits of public subsidy on education are largely
reaped by the upper income class [6]. Whereas education
spending, especially at the primary level, is considered to
produce positive external benefits and a strong case can be
made for the continued involvement of the government for
gender equitable public spending on education at primary
levels [7]. In terms of spending, there is perceived to be a
positive correlation between district literacy rates and district
allocation of funds to the education sector [8]. Also, low
official requirements for teaching positions and extremely
low teacher salaries, especially at primary level imply the
low level of priority accorded to basic education by the
government [9]. A related study, [10], found that improving
school quality (through reducing pupil teacher ratios)
increased grade attainment and efficiency by approximately
9 percent in rural Mozambique.
The present study makes an analysis of primary schooling
in Pakistan from a domestic and international perspective.
Domestically, primary schooling is analyzed through
expected years of schooling of children, in the primary age
bracket (ages 5 to 9), while internationally; primary net
enrollment rates and adult literacy are analyzed across 110
countries with differing degrees of human development
indices. This study distinguishes itself from that of previous
research as previously primary enrollment rates were
analyzed on a domestic level, rather international. Further,
our domestic analysis concerns itself with perceived
schooling expectations rather enrollment rates.
2. RESEARCH METHODOLOGY: DOMESTIC
ANALYSIS
A field survey analysis was conducted on data collected
from a group of 80 lower middle income class families with

2. children in the primary school age bracket to analyze the
socio-economic trends present in parent’s current decisions
regarding expected years of child’s schooling. For this
purpose, family heads were interviewed with the aid of a
preconceived questionnaire, formed by combining the
Education Demographics and Public School survey
templates, and making the necessary adjustments to meet the
needs of the population under study [11]. This method was
in compliance with the needs of a semi-literate population.
Field survey data was analyzed through multiple regression
analysis as well as various statistical techniques. The
analysis aimed to determine those factors which had any
significant relation to expected years of child’s schooling
decisions. The multiple linear regression model was
specified as:
Y1 = β0 + β1X1i + β2X2i + … + β11X11i + β12X12i +μ (1)
Where
Y1 = expected years of child’s schooling
X1i = gender
X2i = total monthly family income
X3i = education of father
X4i = education of mother
X5i = total number of children
X6i = child’s order in siblings
X7i = satisfaction with quality of schooling
X8i = distance to school
X9i = education of teacher
X10i = teacher’s weekly absence
X11i = child’s school performance
X12i = income spent on child’s education
μ = random error term
2.1 Results
The regression model was found to be of significance, of the
variables considered, however, only a few gave robust
results, shown in Table 1.
Table 1: Expected Years of Schooling
*Significant at ρ < 0.05
Results reveal a gender bias in expected years of schooling.
The average perceived education level for females was set at
12 years (F.A./F.Sc) while that of males was 14 years
(B.A./B.Sc.) Statistical analysis reveals a positive
relationship between family transitory income and expected
years of schooling. Factors such as distance to school and
total number of children had an inverse relationship with
expected schooling.
The relationship between transitory income and expected
schooling is illustrated in Figure 1. Higher levels of income
generally comply with higher levels of investment in child’s
expected schooling. Those families with higher total
monthly incomes were found to desire greater levels of
education for their children while lower income families
gave less importance to expected schooling decisions.
5
10
15
20
25
30
35
5.0 7.5 10.0 12.5 15.0 17.5 20.0
TransitoryIncome(Thousands)
Expected Years of Schooling
Correlation
= 0.524
Figure 1: Transitory Income vs. Expected Years of Schooling
Child’s performance in school had a positive effect on
expected schooling decisions A further regression analysis of
child’s school performance revealed the importance of
teacher’s education levels and parental satisfaction with
quality of schooling in relation to child school performance.
This implies an indirect relationship between teacher’s
education and quality of schooling with expected years of
schooling. This is shown in table 2.
Table 2: Child’s School Performance
*Significant at ρ < 0.05
Variable Coefficient t-value p-value
Constant 8.6175 2.5603 0.0127
Gender -1.2938 -2.3935 0.0195*
Transitory income 0.0003 4.4681 0.0000*
Father’s education -0.0693 -0.6419 0.5231
Mother’s education -0.0033 -0.0498 0.9604
Number of children -0.6728 -2.9574 0.0043*
Order in siblings 0.2961 1.1611 0.2497
Quality of schooling -0.6606 -1.0242 0.3094
Distance to school -0.2221 -2.3860 0.0199*
Teacher’s education 0.2768 1.3103 0.1946
Teacher’s absence 0.4250 0.9693 0.3359
Child’s performance 1.1890 2.1168 0.0380*
Income spent -0.0004 -0.5845 0.5608
Variable Coefficient t-value p-value
Constant 0.0853 0.1191 0.9055
Father’s education -0.0137 -0.6081 0.5451
Mother’s education 0.0040 0.3078 0.7591
Quality of school 0.5647 4.3684 0.0000*
Class size 0.0023 0.4707 0.6393
Teacher’s education 0.1061 2.3122 0.0236*
Teacher’s absence 0.1689 1.7684 0.0812
Extra help 0.0321 0.2626 0.7936

3. 0
4
8
12
16
20
Children
Total number ofChildren Expected Years of Schooling
Distance of School Child's School Performance
Poly. (Total numberof Children) Poly. (ExpectedYears ofSchooling)
Poly. (Distance ofSchool) Poly. (Child's School Performance)
Figure 2: Trend Line Analysis: Expected Years of Schooling, Total Number of Children, Distance to School, Child's School
Performance
0
20
40
60
80
100
Life Expectancyat Birth Net enrolment rate. Primary. Total
Pupil-teacher ratio. Primary Poly. (Life Expectancy at Birth)
Poly. (Net enrolment rate. Primary. Total) Poly. (Pupil-teacherratio. Primary)
Figure 3: Primary Net Enrollment Rate, Life Expectancy at Birth, Pupil Teacher Ratio
Figure 2 highlights the relationship between expected years
of schooling and significant factors such as distance to
school, total number of children and child’s performance in
school. Trend lines for distance to school and total number
of children vary inversely with expected years of schooling
showing that attending schools at greater distances from
their homes reduced expected schooling decisions as did
large family sizes. Child's performance in school is shown
to directly correspond with expected schooling as families
were less hesitant to spend on higher education levels when
the perceived gains from investment in education were
considered greater.
3. RESEARCH METHODOLOGY: CROSS
COUNTRY COMPARISON
On an international level, data analysis was conducted on a
population of 110 countries across the globe with varying
degrees of human development. Various human
development indicators were analyzed in order to perceive
the relative importance and contribution of each factor in
determining primary school enrollment rates as well as adult
literacy rates. For this purpose, both enrollment and literacy
rates were taken as dependent variables in separate multiple
linear regression models. The multiple linear regression
models were specified as:
Y2 = β0i + β1iX1i + β2iX2i + … + β7iX7i + β8iX8i +μ (2)
Y3 = β0i + β1iX1i + β2iX2i + … + β7iX7i + β8iX8i +μ (3)
Where
Y2 = net primary enrollment rate
Y3 = adult literacy rate
X1i = adult mortality rate (probability of dying

4. between ages 15 to 60 per 1000 persons)
X2i = Inequality ratio (richest 10% to poorest
10%)
X3i = GDP per capita (US$)
X4i = Life expectancy at birth
X5i = Government corruption
X6i = Education spending (% GDP)
X7i = Percentage primary female teachers
X8i = Primary pupil teacher ratio
μ = random error term
3.1 Primary Net Enrollment
Multiple regression analysis of primary net enrollment
revealed the significance of life expectancy at birth and
primary pupil teacher ratios in determining enrollment rates.
This relationship is highlighted in Figure 3, above. Trend
lines for primary enrollment rate and life expectancy at birth
show a positive relationship as they are shown to vary
together. High life expectancy rates coincide with likewise
high primary enrollment rates. The relationship between
primary enrollment rates and pupil teacher ratios is shown to
be inverse. Low trends of pupil teacher ratios correspond
with high enrollment rates and vice versa. Those countries
with higher pupil teacher ratios were also found to have
lower primary enrollment rates
An analysis of primary enrollment rates of Pakistan as
compared to other countries belonging to the Medium
Human Development bracket showed a trend of significant
differences between grade retention levels in primary school.
Discrepancies between grade levels showed the greatest
difference to occur between grades one and two, shown in
Figure 4 below.
Results reveal a significant gap between grade one
enrollment rates as compared to subsequent grade
enrollment rates. These differences are found to be
particularly pronounced in Pakistan, Bangladesh, Kenya and
India, where Kenya has the highest discrepancies between
grade 1 and grade 5 enrollments at 74%, followed by India
at 65%, Pakistan at 54%, and Bangladesh at 50%. Thus,
analysis implies that the greatest number of children are
withdrawn from school in class one and those children who
complete grade one have much higher chances of
completing primary school than those who are withdrawn
prematurely.
Table 3: Primary Net Enrollment Rate
*Significant at ρ < 0.05
Variable Coefficient t-value p-value
Constant 40.6947 1.6837 0.0953
Adult mortality 0.0035 0.1576 0.8751
Inequality ratio 0.0924 1.7714 0.0795
GDP per capita 0.0000 -0.1014 0.9194
Life expectancy at birth 0.6251 2.1249 0.0360*
Government corruption 0.4482 0.6048 0.5467
Education spending 0.0537 0.1376 0.8908
Primary female teachers 0.0555 1.9713 0.0514
Pupil teacher ratio -0.1644 -2.0351 0.0445*

5. 0
6
12
18
24
30
36
Enrolment in primary. Grade 1. Total_MHD
Enrolment in primary. Grade 2. Total_MHD
Enrolment in primary. Grade 3. Total_MHD
Enrolment in primary. Grade 4. Total_MHD
Enrolment in primary. Grade 5. Total_MHD
Poly. (Enrolment in primary. Grade 1. Total_MHD)
Poly. (Enrolment in primary. Grade 2. Total_MHD)
Poly. (Enrolment in primary. Grade 3. Total_MHD)
Poly. (Enrolment in primary. Grade 4. Total_MHD)
Poly. (Enrolment in primary. Grade 5. Total_MHD)
Figure 4: Trend Line Analysis: Primary Enrollment Grades 1 to 5 vs. Countries with Medium Human Development
0
20
40
60
80
100
Adult Literacy Rate
Percentage female teachers. Primary
Pupil-teacher ratio. Primary
Poly. (Adult LiteracyRate)
Poly. (Percentage female teachers. Primary)
Poly. (Pupil-teacherratio. Primary)
Figure 5: Trend Line Analysis:
Adult Literacy Rate, Pupil Teacher Ratio, Percentage Female Primary Teachers
3.2 Adult Literacy
Multiple regression analysis of human development
indicators and related factors across countries showed the
significance of adult mortality rates, life expectancy at birth,
percentage of female teachers, and pupil teacher ratios in
determining adult literacy rates, shown in Table 4.
Figure 5 shows the relationship between adult literacy rate,
pupil teacher ratio, and percentage female primary teachers.
Trend lines show a direct relationship between literacy rates
and percentage of female teachers as greater levels of female
teachers correspond with higher literacy rates. Pupil teacher
ratios are inversely related to literacy rates as lower class
sizes concur with higher literacy levels.
Table 4: Adult Literacy Rate

6. *Significant at ρ < 0.05
Adult mortality rates had an inverse effect on literacy rates
while life expectancy at birth was positively related to rates
of adult literacy. The impact of adult mortality on literacy
rates may be explained by the incidence of parental mortality
and its effects on child’s enrollment and completion rates. In
Figure 5, these trends are illustrated as higher adult mortality
rates correspond with dips in the adult literacy trend line
while lower mortality rates occur with higher points of
literacy levels. Life expectancy at birth varies directly with
adult literacy rates as relative rises and falls in the trend lines
coincide.
4. DISCUSSIONS
Domestic and international data concurs the need of the
Government to intervene and take preliminary steps to
improve its primary education sector through enhanced
qualitative reconstruction and improvement in educational
facilities. In this aspect, change is required on both federal
and provincial levels.
The significance of life expectancy at birth in net primary
enrollment rates and adult literacy gives an indication of the
importance of population health and longevity in enrollment
rates, thus implying an intermittent relationship between the
health and educational sector and necessitating the need to
make changes so as to improve living standards through
increased access to healthcare. Whereas Pakistan’s public
health expenditure in 2007 was 4 percent, ranking amongst
the lowest percentages spent among countries with similar
domestic resources, Human Development Report, (2007),
United Nations.
Those countries with higher pupil teacher ratios were found
to have lower primary enrollment rates. As pupil teacher
ratios can be used as a qualitative measure of a country’s
educational sector, these results indicate the need to focus
funding on the qualitative reconstruction of educational
facilities.
There is a general coincidence in determining factors of
adult literacy rates and primary enrollment rates as both
regression models revealed the importance of health, living
standards, and longevity in meeting education sector targets.
This implies a need to invest strategically in these areas in
order to attain maximum benefits from scarce resources and
lead to long term domestic upliftment through increases in
enrollment and literacy rates.
5. RECOMMENDATIONS
Policy implications corresponding to the prior study are as:
• As transitory income plays a significant role in
excepcted schooling, measures must be taken to
minimize costs for schooling. This may be done
through providing educational subsidies focused on
primary schooling, particularly for those families in
the lower income bracket. This may seem to be
costly in the short run, but long term benefits in the
form of greater enrolloment and prospective years
of schooling outweigh immediate costs.
• As gender discrepencies in enrollemnt as well as
schooling expectations remain high, educational
subsidies should focus on improving prospects for
female enrollemnt. This may be addressed through
allowing for family allowances to those households
in which female children are enrolled in school.
• Programs be inititated in rural localities to create
awareness of the benefits of educational investment
with emphasis placed on female education.
• School bus services be made compulsory and free
of cost, where costs of transportation are included
in government recurrent expenditures.
• Teacher entry qualification be raised from
intermediate to B.A./B.Sc.
• Measures be taken to attract a greater number of
teachers, particularly female, to the field of
education in rural localities through increaseed
salaries as well as benefit schemes.
• Measures be taken to reduce primary drop out rates,
especially between grades one and two. This may
be initiated through providing family allowances,
encouragement of greater parental participation in
the education process and educating rural families
on the short and long term benefits of schooling.
• Increases in educational expenditures must coincide
with proportional increase in healthcare
expenditures with access to free healthcare in close
proximity to rural and less developed areas.
• Health Clinics be opened in all rural localities with
the aim to provide service free of cost to all who
need it.
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[1] ICG, “Pakistan: reforming the education sector”, Asia
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Variable Coefficient t-value p-value
Constant -68.4133 -1.9273 0.0567
Adult mortality 0.1003 3.0848 0.0026*
Inequality ratio 0.1462 1.9094 0.0590
GDP per capita 0.0000 0.2548 0.7994
Life expectancy at birth 1.6987 3.9316 0.0002*
Government corruption 1.5471 1.4217 0.1582
Education spending -0.2222 -0.3876 0.6991
Primary female teachers 0.2826 6.8341 0.0000*
Pupil teacher ratio -0.5921 -4.9896 0.0000*

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