Schooling of Last Resort?

Madrassa, Private, or Public Schools

March 2010

Paper prepared for the Duke University Conference, April 2-3, 2010

Preliminary, Incomplete, please do not quote

Tahir Andrabi, Pomona College, tandrabi@gmail.com

Jishnu Das, The World Bank, jdas1@worldbank.org

Asim Ijaz Khwaja, Harvard University, akhwaja@hks.harvard.du

Over the last few years, US and international foreign policy concerns have focused on the

rise of extremism in the Islamic world. Pakistan is mentioned as prominent case and is

considered as pivotal in the war on terror. There is by now a widespread conventional

narrative surrounding the role of the Pakistani educational system in the rise of religious

extremism in the country. The general claim is that the public schooling system in

Pakistan is failing especially for the poor. As a result, large numbers are exiting the state

system both through attrition or lack of enrollment in the first place. Madrassas have

proliferated to fill the vacuum as a result of the Pakistani state and society to provide

mainstream schooling opportunities for its children. This narrative has been pushed

forward largely in the media but also in policy circles in the United States and by some

policy studies as well. The Af-Pak policy framework developed under the Obama

administration has also highlighted this point.

In earlier paper (ADKZ, CER 2007), we utilized all available published and verifiable

data sources to demonstrate that madrassa enrollment was low across the country. We

also showed using household level data collected by the authors in the Learning and

Educational Achievement in Punjab Schools (LEAPS) project that madrassa enrollment

was not only small but also did not follow any consistent pattern across households. In

fact, there was considerable within household variation in schooling choices and

madrassa enrollment.

In that paper and in subsequent work (ADK 2008), we have shown that there has been

dramatic change in the Pakistani education landscape but it is not the madrassa

proliferation but a rise in private schooling. These private schools are a grassroots,

decentralized phenomenon in large part driven by mom-and-pop entrepreneurs largely

unaffiliated with any chains or organizations, religious or otherwise. Thus we were able

to show that both in terms of levels and trends, private schools were a considerably more

significant phenomenon in Pakistan at both the urban and rural level.

However, because of data limitations, we could not address the considerable

heterogeneity at the country level existing within the rural areas. In this paper, we utilize

a new data source, the National Education Census 2005 (NEC), conducted by the

Pakistan Federal Bureau of Statistics (FBS) to fill in the gaps in this debate. The NEC

has several features that make it especially suitable to analyze this question. First, it is the

only national level data source that provides a full enumeration of all the schooling

types—public schools, madrassas and private schools in Pakistan.

There is an ongoing discussion over whether madrassa numbers in this data are accurate.

What is or is not a madrassa is subject to debate. The NEC 2005 includes residential and

non residential madrassas. It also includes madrassas affiliated with various wafaq-ul-

madaris and those unaffiliated. However, if one starts thinking of every Quran teaching

school associated with a mosque or of people teaching the Quran informally to almost

every Pakistani child, the number of those providers would be in the millions and

difficult to enumerate. Our independent work in some districts in Punjab and in the

earthquake areas shows similar numbers from the household surveys as well as school

enumeration.

Secondly, and importantly, the data collected by the FBS has a coding scheme that allows

us to merge it with the Pakistan Population Census 1998 at the village level. Given that

we have data in the census on over 46,000 villages in Pakistan, combining the two data

sources provides a comprehensive look at education in rural Pakistan at the most

disaggregated geographical level possible. Moreover, the census provides us a rich array

of socioeconomic indicators at the village level: village housing construction type,

electricity and water availability, numbers on adult education levels, TV, radio and

newspaper penetration as well as number of people registered in government national

identity card databases. These data allows us to construct a village level socioeconomic

status index status using principal component analysis. Going to a disaggregated level

within rural areas and classifying villages both in terms of size, physical infrastructure

and other socioeconomic characteristics, one can examine the important questions of

madrassa location vis-a-vis indicators of poverty. Importantly, one can also look at

madrassa location patterns in comparison to both public school availability as well as

seeing how madrassas locate relative to the growing number of private schools. This

merger of data sets allows us an examination of schooling options available to villages at

different socioeconomic levels—a crucial question on the link between madrassa

location, alternative schooling choices and poverty.

Having done this, we are able to examine the schooling options available at the village

level by looking at the location patterns of the madrassa in relation to other alternatives.

The specific questions we ask are i) whether madrassas locate mostly in more deprived,

lower socioeconomic status (SES) villages and ii) whether they are more likely to open

up in villages where there are fewer schooling alternatives.

On the aggregate, madrassas are evenly divided between rural and urban areas. Given

that more than two thirds of Pakistan’s population resides in rural areas, this points to

much higher penetration of madrassas in the urban areas. Within rural areas, we find on

the first question that madrassas do not locate in poorer villages. In fact, madrassa

presence, controlling for village population and district fixed effects, is on the average

flat and in fact slightly increases as village SES becomes better..

Secondly, the establishment data confirms the household sources: madrassa prevalence is

much lower than both public and private schooling numbers. This is true at all SES

levels. In the rural areas in general and in the lowest SES villages in particular, public

schooling is the most prevalent option by a large margin. In the urban areas, it is the

private schools that dominate the landscape. As we move up the SES ladder in the rural

areas, while public schools still remain the dominant option, private schools become an

increasingly greater option while the madrassa option remains relatively flat. The

elasticity of private school prevalence vis-a-vis village SES is much higher than that of

the madrassa. If we look at the components of the SES index, we see that private schools

respond most to female empowerment. Madrassas too respond positively to this sub

component of the index in a small but statistically significant way. Madrassas also do not

locate in areas where there are fewer schooling options. In fact they locate, albeit at a

much smaller level, precisely in areas where private schools and girls’ public schools

locate.

The above findings have important implications towards policy reform. If one’s main

concern is for access to education towards the poor then madrassa clearly is not the

schooling of choice. One needs to think seriously in terms of public school reform and

expansion, especially for girls as they are the dominant mode of education provision I

these villages. In terms of trends both over time and as to where the poor are sending

their children as they exit poverty, private schooling is the preferred option.

Our study raises some deeper conceptual questions as well--how to infer Muslim

preferences. Child school choice around very poor levels of socioeconomic status reveals

a more nuanced view of the world.

Empirical Analysis:

The last population census in Pakistan was conducted in 1998. Pakistan has four

provinces—NWFP, Punjab, Sindh, Balochistan and three territories with special status

(Azad Jammu Kashmir (AJK), federally Administered Northern Areas (FANA) and

Federally Administered Tribal Areas (FATA) and Islamabad the capital territory. We

have complete data on village characteristics for the four provinces, about 93% of the

country’s population. Urban areas represent 33% of total population. The accompanying

table provides the distribution of villages and population by province in rural Pakistan.

Punjab is the largest province and the most well off. Table 1 provides the population

distribution.

Distribution of Schools

The NEC school distribution is presented in Figure 1 with the rural urban breakdown.

The breakdown reveals an oft ignored fact about schooling opportunities in Pakistan. The

public schooling system is large and dominates the rural landscape with more than

120,000 schools. The rise of private schooling has been documented in earlier work by

the authors and the data clearly show that while private schools have become an equally

prevalent in urban areas, they are also a significant presence in rural areas. Madrassas

split evenly between the rural and urban areas but are a distant third to both private and

public schools. In rural areas, the madrassa numbers are about a fourth of private schools.

There is considerable heterogeneity in the rural areas of Pakistan in terms of size as well

as physical infrastructure and educational outcomes. The heterogeneity exists not only

across provinces but also within provinces to the level of district. (Each province is

further subdivided into districts. The number of districts in Pakistan is 118 thus the

average district has a rural population of around 900,000.)

Schooling Location and Village Socioeconomic Status

The census provides us a rich array of village level characteristics. We use information

on proportion of houses with concrete (pakka) construction, having electricity, piped

water as our measure of village infrastructure. We have data on the informational

resources available in a village: proportion of households having a TV, a radio and

getting a newspaper. Finally, we use proportion of women going beyond high school

(matric) and those with national identity cards as a measure of female empowerment. For

our main regressions, we combine all these variables using principal component analysis

in a village level socioeconomic status (SES) index. This is the first time that this index

has been created for Pakistan at the village level. The index values range from a

minimum of -3 to the 99th percentile being +3 and some values ranging beyond 10.

We first present the prevalence of school types at the village level in Table 2. The first

panel in Table 2 shows the percent of villages having number of different school types.

Public schools are the dominant option at the village level. Almost every village in

Pakistan has a public school and a considerable number have many. However, in Punjab

and parts of NWFP and Balochistan, schooling is segregated by gender. The next column

shows that availability of girls schooling at the village level. Sindh is coeducational at the

primary level. The prevalence of girls schooling at the village level is only a small

fraction of overall government schooling with 30% of villages having no access to a girls

public school. Private schooling is the next most prevalent option with about 23% of

villages now having at least one private school. Madrassa is the least prevalent option at

the village level with less than 7% of the villages having a madrassa. Notice also that,

less than 1% of the villages have three or madrassas.

Village sizes vary considerably in Pakistan with a median population of 1169 with the

99th percentile being 12,176 and the 1st percentile a village of only 15 people. Thus if

schools locate in larger villages, looking simply at village numbers without weighting

them for population could be misleading. The second panel in Table 2 does so. The

numbers show that it is indeed true: the prevalence of schooling opportunities in larger

villages is greater. The percentage of people living in a village with a school type is

greater. The numbers for madrassas, private schools and girls public school jumps up but

the relative rankings remain similar. 83% of people live in villages without a madrassa

and the corresponding number for villages without a private school falls to 55%. The

larger villages have more private schools in them as the percentage of population living

in villages with 3 or more madrassas goes up to 5%. Almost 20% of the Pakistan rural

population is living in villages with 3 or more private schools. So school choice at the

rural level is very much a fact of life.

As one might expect, village size is also correlated with its SES index, therefore we do

multiple regression analysis to control for the confounding factors. We run a regression

on the presence of a school of a given type in a village as a function of the SES index,

controlling for village log population and province fixed effects. The results are robust to

whether one uses the likelihood of presence of a school of a certain type, the number of

schools or schools per capita as the outcome variable or whether one weights the vilaleg

level observations with village population size.

Table 3 presents the results of a regression with the outcome as likelihood of presence of

a certain school type with province fixed effects to gauge the prevalence across provinces

as well as the effect of village size and socioeconomic status. Apart from public schools

which are present in almost all villages, the other school types follow a similar pattern.

While it is somewhat expected to see private schools locating more in larger villages and

those with higher SES status, it might surprise some to see that madrassa are also more

likely to locate in higher SES villages. Going from an SES index of -3 to +3, the

likelihood of a village having a madrassa increases by 3.6% percentage points. The

population effect is even larger. Going from a village population size of 500 to a village

population size of 2000 increases the likelihood of a madrassa by 6% percentage points.

The private schools is not only more prevalent but has an almost eight times higher

elasticity with respect to the SES status and more than two and a half times that of

population than the madrassa.

Figure 2 plots the predicted likelihood of a school in a village from the above regression

against the village SES index holding other variables at their mean levels. Madrassas do

not locate in poorer villages. In fact they are slightly more likely to exist in higher SES

index villages. The rate of increase is statistically significant but as the slope of the graph

shows the difference is small. The private school graph provides an important and

perhaps unexpected similarity to the madrassa distribution. Private schools follow a

qualitatively similar location pattern to the madrassa! Their existence in lower SES index

villages is low and increases as the village SES index improves. However the magnitude

of both the likelihood of a school and its change is more pronounced than that of the

madrassa. Both madrassas and private schools start off with relatively even likelihood of

schools in the lowest SES villages, with private schools having a little edge. But their

difference starts to grow rapidly as we move up the SES index. In the most well off

villages, a village has a .45 predicted likelihood of having a private school compared to

about .10 for a madrassa.

The role of public schools in providing education to the rural poor location is quite often

ignored in the madrassa debate. The figure shows that public schools are the dominant

schooling option in the rural areas, especially when we look at the lowest SES index

villages. The widespread presence of public schools all across the SES spectrum is noted

in the high level of existence and the flatness of the graph. The situation of girls’ public

schooling is different. It too follows a pattern much like the private school albeit at a

higher presence at the village level. Private schools show the greatest SES elasticity in

terms of their prevalence.

The coefficients on the province dummy variables show that there is considerable

heterogeneity in both madrassa and private school presence at the grassroots level.

Punjab has the highest private school numbers and lower madrassa numbers. The

provincial heterogeneity does not lend itself to any straightforward cultural or ethno-

linguistic explanations. NWFP has high private school presence and high madrassa

presence compared to Sindh. We are extending this analysis to the province level and the

sub provincial level in a continuing revision of this paper.

Unbundling the Socioeconomic Index:

The socioeconomic index is a composite index of variables that presumably move

together. But these components tell us different aspects of village life as it interacts with

the modern world, its values and its wealth. It could be that madrassas are reacting to

increased wealth in villages but are less likely to exist in villages with greater female

empowerment. We break the index into three subcomponents to isolate these possibly

differing effects. We separate out the village infrastructure component from the media

and information component and the female empowerment component. We create separate

village indices for each of these three sub components using the same principal

component analysis. We run the same regression as above but use the subcomponent

indices instead of the composite index. In addition, in one specification, we also see

whether madrassa presence correlates with the presence of other type of schooling

options. The results are presented in Table 4.

Public school location, because of its presence in almost all villages, reacts only to village

population size and not to any of the components. Private school likelihood increases

with all three subcomponents but most strongly with female empowerment. This is to be

expected given our earlier work on the supply effect of girls’ secondary schooling

creating a pool of low paid, local teachers. What is interesting is that madrassa presence

at the village level also goes up with female empowerment and with media and

information. The estimates are small but statistically significant. They, however, do not

increase with village infrastructure, our proxy for village wealth.

Finally, the striking correlation is that madrassas co-locate with other types of schools.

The presence of a private schools increases the probability of a madrassa present in the

village, controlling for SES, population and province effects, goes up by a large 10%

percentage points. A similar effect is found for the presence of a girl’s public school.

Discussion and Policy Implications:

Access to the Poor:

The claim that madrassas are the schooling option of choice for the poorest segments of

the population is not correct. The data show that people living in rural areas to some

extent and in poorest villages to a large extent have access only to public schools. If one

is concerned about alleviating the problem of access to education for the rural poor, then

the discussion should not focus on madrassas (or private schools for that matter) as both

private schools and madrassas are not locating there. The discussion has largely got to be

about the public sector. Policy should focus on improving quality and learning outcomes

in public schools. The government should concentrate on expanding its role mainly in

these areas that are not covered by other schooling choices.

Gender:

We have discussed elsewhere in detail that existence of a pool of moderately education

women at the village level has provided the impetus behind the rise of private schooling

in the rural areas. As the number of educated women in rural area is increasing with time,

it will create a further expansion of private schools in the moderate to high SES index

villages thus creating a positive feedback loop. The key policy implication in these

villages is for the government to ensure that such local pockets of educated women

expand (through spread of girl’s secondary education) and steps are taken to ensure that

the education market performs competitively and efficiently. The issue of public girls

schooling in the poorest areas needs to be re-emphasized.

School Reform:

At the same time, we recognize that fighting terrorism, militancy, extremism and

violence is perhaps the most pressing problem confronting the Pakistani state and society.

We would like to point out that there is limited overlap between the issue of school

reform and that of extremism. It is counterproductive to view the debate on school reform

solely from the lens violence and extremism. Policy debate on education in Pakistan is

rightfully turning its focus towards issues such as teacher absenteeism, merit pay,

decentralized school management and governance to name a few.

According to the census, approximately one million youth are turning eighteen and

potentially entering the labor market every year. One of the most pressing problems of

the day is training them to participate effectively in society around them and be

productive economically. School reform to achieve credible learning and academic

outcomes is critical in this regard. Our other work has pointed out (the LEAPS report,

2007), private school governance, management and functioning provides significant

lessons for the much needed process of public school reform. Focus on the madrassa does

not add any insight into the crucial issue of improving the vast majority of public schools.

Revealed Preferences:

As one moves up the SES scale in the rural areas, schooling options increase. However,

while the madrassa prevalence does go up, the marginal increase in private school

prevalence is much greater. From a school choice and parental decision making context,

the private schools have emerged as the more ubiquitous alternative to government

schooling. It should be noted that the better SES villages are larger in size and therefore

the bulk of Pakistani rural population resides in them. One expects this trend to continue

as the Pakistani population is increasing and a comparison of the data from 1999 and

2005 shows that the growth in private schools remains strong. The implication is that

Pakistani parents beyond the poorest of the poor are actively making educational choices

regarding their children’s future. As much there is discussion of the average Pakistani

having “extreme” preferences, these data show remarkably “normal” behavior on the part

of Pakistani parents. Preliminary work

The issue of madrassas encouraging violence and militancy or the issues of suicide

bombing coming from young men affiliated with madrassas need to be targeted directly.

The direction of causality running from madrassas to extremism is not clear. Our

statistical analysis has little to say on this issue except point out a few facts in the next

session about schooling options in such hot shot areas in the next section. In this context,

work on the madrassa, given its peripheral nature to the Pakistan schooling system needs

to be reconceptualized and needs to focus on the few madrassas that are engaged in such

acts. We would argue that even if one were concerned about issues of extremism, it is the

ideological bent of the majority of the population that is the more important target for

policy to study rather than just focus on the madrassa. Our work in progress shows that

private school students show less gender bias, have better civic knowledge and attitudes

and show more trust in state institutions than their public school counterparts. An

approach focusing on more representative data with their richer choice patterns and an

unmistakable trend towards private schools would give us a better idea of where the

youth of the country are heading and where their families’ deeper preferences lie.

Certainly, what goes inside a madrassa is interesting from a sociological point of view

but from the point of view of a poor Pakistani or even the average Pakistani, the madrassa

is largely an irrelevant alternative.

Tables and Figures

Table 1

Pakistan Population Distribution

Province Number Population of Villages (thousands) NWFP 7,175 14,750 FATA 2,585 3,091 PUNJAB 24,538 50,601 SINDH 5,779 15,600 BALOCHISTAN 6,006 4,996 ISLAMABAD 120 276 AJK 1,628 2,599 Total 47,831 91,912

Urban Population 32.5% of Total

Table 2

Number of Schools

All Public Public Girls Private Madrassas

% Villages 0 0.63 30.94 77.32 92.59 1 14.71 37.37 11.92 5.11 2 24.59 12.47 5.41 1.32 3+ 60.07 19.21 5.35 0.97 % Population Living in Villages 0 1.55 11.23 54.99 82.89 1 39.99 31.08 15.91 9.05 2 27.32 15.8 9.94 3.77 3+ 31.14 41.89 19.15 4.29

Table 3

Likelihood of a Given School Type in a Village

(1) (2) (3) (4) VARIABLES Public Girls Public Private Madrassa SES Index -0.000 0.036*** 0.047*** 0.006*** (0.000) (0.001) (0.001) (0.001) Log Population 0.006*** 0.153*** 0.111*** 0.043*** (0.000) (0.001) (0.001) (0.001) Punjab -0.004** 0.104*** 0.022*** -0.086*** (0.002) (0.005) (0.005) (0.003) Sindh 0.004 0.153*** -0.229*** -0.140*** (0.002) (0.007) (0.007) (0.005) Balochistan -0.029*** -0.108*** -0.042*** -0.026*** (0.002) (0.007) (0.007) (0.005) Islamabad -0.048*** -0.163*** 0.066** -0.076*** (0.011) (0.034) (0.034) (0.023) Constant 0.948*** -0.428*** -0.510*** -0.152*** (0.003) (0.010) (0.010) (0.007) Observations 43618 43618 43618 43618 R-squared 0.014 0.357 0.240 0.063 The omitted province is NWFP. Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4

Likelihood of a Given School Type in Village

(1) (2) (3) (4) (5) VARIABLES Public Girls

Public Private Madrassa Madrassa

Village Infrastructure

-0.000 0.035*** 0.045*** -0.004*** -0.009***

(0.001) (0.002) (0.002) (0.001) (0.001) Media and Information

-0.000 0.012*** 0.007*** 0.004*** 0.003***

(0.000) (0.001) (0.001) (0.001) (0.001) Female Empowerment

-0.001 0.012*** 0.052*** 0.018*** 0.013***

(0.001) (0.002) (0.002) (0.001) (0.001) Probability Private School Exists

0.092***

(0.003) Probability Public Girls' School Exists

0.010***

(0.003) Log Population 0.006*** 0.152*** 0.101*** 0.041*** 0.030*** (0.000) (0.001) (0.001) (0.001) (0.001) Observations 43618 43618 43618 43618 43618 R-squared 0.014 0.355 0.250 0.067 0.084

Standard errors in parentheses, regressions with province fixed effects *** p<0.01, ** p<0.05, * p<0.1

Figure 1

Pakistan School Location

5,559 5,495

22,947 29,660

124,301

16,602

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Rural Urban

Num

ber of Schoo

ls

Public

Private 

Madrassas

Source: NEC 2005

Figure 2

0.2

.4.6

.81

Pre

dict

ed P

roba

bilty

of S

choo

l in

Vill

age

-4 -2 0 2 4 6Village Socioeconomic Status Index

Public Schools Girls Public SchoolsPrivate Schools Madrassas

Source: Pakistan Population Census 1998, National Education Census 2005Predicted Probabilty of School in Village village-level regression, controlling for log population, province fixed effects

School LocationRural Pakistan