Discussion Papers In Economics
And Business

The effect of ratio between PTA teachers and Government employedteachers on Education outcomes in Kenya Primary Schools

Ayako Wakano

Discussion Paper 16-14

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe effect of ratio between PTA teachers and Government employedteachers on Education outcomes in Kenya Primary Schools

Ayako Wakano

Discussion Paper 16-14

May 2016

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe effect of ratio between PTA teachers and Government employed teachers on Education outcomesin Kenya Primary Schools
Ayako Wakano†
Abstract
Do locally hired teachers benefit pupils’ school achievements more than governmental employedteachers? This is the question to examine in this paper. Although social experiment results have shownthat the marginal product in terms of test score is positive and significant when pupils are taught by
PTA teachers, it is not yet known about the “relative” effectiveness between government teacher andlocally hired teachers. This paper is going to find whether the PTA teacher ratio (the ratio of locally
hired PTA teachers against total number of teachers in one primary school) has statistically significant
explanatory power on pupil test score, after controlling various factors.
In Republic of Kenya (below referred as Kenya), there are two types of teachers teaching in public
primary schools. One is those teachers employed by the government and the other is those hired by the
local school community, named “PTA teacher”. Although wage level for PTA teachers in public
primary schools in Kenya is one fourth of that of government teachers, school outcomes of pupils
taught by locally hired contract teachers are higher than those of pupils taught in controlled group
schools, according to the result of social experiment (Duflo et al. 2012).
This paper will examine, by using nationally representing observational data, to estimate the relative
effect of PTA teachers on school outcome. In the end, by using Propensity Score Matching Estimation
method, the result shows that the effect of PTA teacher ratio is positive and significant on school testscore in all three subjects for lower standard grade pupils except Kernel and Radius matching and in
Kiswahili subject for all seven different matching algorisms, though the magnitude of coefficient isrelatively small. Although background mechanism of this finding is not solely determined, this paper
is to assume that the effort level of PTA teacher in teaching tends to be higher than that ofgovernmental teachers, based on several reasons.
JEL code: I21, I28, J18
Keywords: Absenteeism, PTA teacher, Locally hired teacher, test score†Corresponding author: Graduate School of Economics, Osaka University,
Address: 1-7, Machikaneyama, Toyonaka, Osaka, 560-0043, JAPAN,
E-mail address: qgp802wa@student.econ.osaka-u.ac.jp

1．Introduction
For the concerns of education policy, the “contract” teacher or locally hired teacher has become one of
the substantial topics in education sector. As Millennium Development Goals (below referred as
MDGs) declares high priority on the Universal Primary Education (below referred as UPE) putting it
as Goal Two, UPE has been perceived as one of the most important issues by the international
community.1 Since then, the gross enrollment rate for primary education has increased drastically indeveloping countries; however supply of education input was not kept up with the pace. One of theissues is to supply school teachers.

In order to tackle with high demand of primary school teachers within the limited budget, various
developing countries were to introduce the system of “contract teachers” whose contracts are fixed andshorter term and with lower qualifications in general than governmentally hired teachers and withlower salaries (Duthilleul 2005). For example, in West African countries where many countries had
started to introduce the “contract teacher” policy in national scale, over 50 percent of primary school
teachers are contract teachers on average of 12 West African countries, either employed by thegovernment or by the parents with government subsidies. Those teachers are employed primarily
because of the shortage of teachers and of the relatively high salary of government teachers, whose
average salary in Sahel countries remained at 6.4 times the GNP per capita, while in the rest of Africa
it was about 4.4, in Asia about 2.9, in Middle East and North Africa about 2.3 and in Latin America 2.3
times the GNP per capita (Duthilleul 2005).

There are two types of contract teachers; one is hired by the government with fixed term contract andthe other is hired by the local community surrounding the school. The former type of teachers is wellobserved in Western African countries. For example, in Senegal about 50.2 percent of total teachers

1

The MDG Goal Two says, “Ensure that by 2015 all children, particularly girls, children in difficult
circumstances, and those belonging to ethnic minorities, have access to and complete free and compulsory
primary education of good quality.”-1-and in Niger 41.5 percent of total teachers are composed of “contract teachers” hired by thegovernment in 2003 (Duthilleul 2005). This paper is to focus solely on the latter type of teachers, called“PTA teachers”. As for PTA teachers, it is said there are advantages not only because of less cost, butalso that it may result in stronger accountability towards the school community if the direct employer
is located at the school level.

It is the motivation of this paper, in addition to the importance of educational policy concern, tocontribute to the academic research which has paid attention to the incentive of teachers. The
academic research about education outcome is shifted from the educational inputs to analysis ofincentives and institutional conditions of teaching and learning. Relevant to teacher incentives andmonitoring effects by school communities, one of those policies coming under the spot light is“contract teacher” policy, which is to hire locally available teachers whose contract is in general “shortterm”, “not fixed” wage rate and directly hired and monitored by the school communities.

2. Preceding Studies
2.1 Social Experiment Result
In spite of the significant meaning of contract teachers in developing countries, not many precedingstudies have examined the effect of “contract teachers” on school outcome. It is true that many studies
have focused on incentives and institutional conditions of teaching and learning, such as “teacher
performance pay” contract, or “teacher monitoring” effect as well as “community monitoring effect”
on school outcome. However, publications which solely deal with locally hired “contract teacher”
effect is scarce. The table in Appendix 1 shows a part of previous studies and estimation results for“contract teacher” effect on school outcome in developing countries. While some are using
experimental data and others use observational data, motivation is the same as to estimate the effect of“contract teacher”. Firstly, by using experimental data, there are three literatures.

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i)

Duflo et al. (2012) showed the result of randomized social experiment in Kenya from2005 to 2006, in Western Province. The result is that the marginal product of contract
teachers is positive and significant for pupils’ test score assigned by PTA teachers.

ii)

Bold et al. (2012) introduced a similar evaluation study to Duflo et al. (2012), however
their contribution is i) expanding the area from one region to eight regions. In addition, ii)
they used two separate implementation method by the Ministry of Education Science andTechnology (MoEST) and by the International NGO (INGO) and compared the result. In
the end, the program impact is positive and significant on pupil test score.

iii)

Sundaraman et al. (2010) showed the impact of hiring additional “contract teachers”, andtheir main findings is marginal product of contract teachers is positive and significant on
pupils school outcome.

From these social experiment results, the effect of adding one locally hired teacher is significantly
positive on school test score, however it is not yet known if locally hired teachers can raise test scorebetter than governmental teachers, even if the marginal product is positive and significant. To thisquestion, following literature introduces the relative effect of PTA teachers.

2.2 Observational data research
The Sundaraman et al. (2010) study shows the result of estimation using observational data,comparing the effect of governmental teachers versus locally hired teachers. In short, by using pupil
level and school level panel observational data, it concluded that they cannot reject the null hypothesisthat existing contract teachers are as effective as government teachers in improving student learning
outcomes. On the other hand, Bourdon, J. et al. (2006), by using observational data for Niger with
Propensity Score Matching Estimation, the estimated effect of contract teacher is positive andsignificant in grade 5th for Math, French and combined score, but not significant for the 2nd grade
pupils in any subjects. Therefore, it is still remained uncertain whether the existing PTA teacher is-3-

more effective to school achievement or not, and if so, in which grade and subject, they are more
effective to the outcome.

In this paper, the objective is to find the relative effect of “existing” PTA teachers on pupils’ schooloutcome, not to measure the marginal effect of “newly” hired teacher. Therefore we use nonexperimental data. It is worth noting there is a clear difference between newly hired teacher byexperimental programs and existing PTA teachers paid by school communities in terms of contract andpayment scheme which is likely to affect motivation of teachers. Firstly, in setting of social experiment,in order to secure randomness, recruitment of local community teacher should be perfectly
independent from school community characteristics; therefore the decision to recruit has to be
exogenous. On the other hand, as for existing PTA teachers, it is endogenous decision for the schoolcommunity to hire PTA teachers. This paper will focus more on school outcome by existing PTA
teachers who are supported by parents’ contributions or school community contributions to
supplement the governmental teachers. Hence we use non experimental data.

In addition to preceding literature, contribution of this paper is as follows:
1) In addition to Bold et al. (2012), it is estimated by using more nationally representing data andincreased number of samples from 192 primary schools (Bold et al. 2012) to 2216 primaryschools.
2) As for preceding literatures in Kenya, there is no study to estimate the relative effect of PTA
teachers hired by local community.

2.3 PTA teacher ratio and concerns
Due to data limitation, it is not possible to identify whether pupils are taught by PTA teachers or not;however it is possible to identify the ratio of PTA teachers and school average test score. Therefore,
this paper puts a certain assumption that if PTA teachers are more effective to raise pupil test score-4-than government teachers, then the higher ratio of PTA teachers might have the positive effect on pupil
education outcome, after controlling class size and pupil teacher ratio. The validity of this assumption
is discussed more detailed in the section 5. Another concern remained unsolved is whether the PTA
teacher ratio does not always represent PTA teachers’ actual teaching practice. It is because data does
not tell who and which subject is taught by PTA teacher. Therefore, in following estimation, cases
where PTA teachers are likely to teach are specified. In detail, it will be explained in section 6.

In order to estimate precisely the effect of PTA teacher ratio, it is necessary to control other school orvillage characteristics where higher PTA teacher ratio is observed. Therefore, the following section
explains about who are PTA teachers in the context of Kenya.

3. Characteristics of PTA Teachers in Public Primary Schools in Kenya
As for the qualification, government (TSC) teachers and PTA teachers differ. In order for teachers tobe certified by TSC, one needs to have “academic qualifications”, ranging from P4 (the lowest grade
and graduates of primary schools) to Diploma. If non-graduate primary school teacher wishes to be ateacher, they need to acquire a relevant degree or qualification from a recognized institution(UNESCO 2010). There are 25 public and 8 private colleges for training primary school teachers.
These provide pre-service teacher training courses which take two years.

As for the number of teacher, although PTA teachers are not offered “legitimate status” to teach in
public primary schools, the number of PTA teachers in Kenya is not small. One survey under“Community Teachers Research Project” conducted in 2009 reported that out of all teachers insurveyed schools, 17 percent of teachers were hired under PTA contract and another report says, “onaverage, 1 out of 5 teachers is employed by parents” (UWEZO 2010).

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In terms of salary, although the wage level of PTA teacher differs among schools, one report estimatedthat the average payment for PTA teachers was 4,151 Kenya Shillings, which is one fourth of theaverage salary 19,372 Kenya Shillings of TSC teachers. The source of the salary for PTA teachers
differs from school to school. It might be paid from the collected fund by local community members
or from the school capitation grant provided by the central government (Nishimura et al. 2009; WorldBank 2009). Therefore, it is not yet clear where the source of salary has come from, however it is clearthat decision to allocate the pooled fund is left with the school community. It is reasonable to assume
that PTA teachers would work hard, since PTA teacher wage is determined by the school community,
while that of TSC teachers is managed by the MoEST, the central government.

4. Conceptual Framework and Hypothesis
It is not possible for us to observe “PTA teacher effort level” from the current dataset, however often
pointed out that contract teacher have superior performance in terms of teaching effort level, forexample, attendance rate or teaching activities. Duflo et al. (2012) shows that contract teachers are
27.8 percentage points more likely to be found in a classroom during random visits than government
teachers. Sundaraman et al. (2010) also shows significantly lower level of absence compared togovernment teachers. These superior performances are due to combination of factors, such as “beingfrom local area and feeling more connected to the community, living much closer to the school andtherefore having lower marginal costs of attendance, or the superior incentives from being on annually
renewable contracts without the job security of civil-service tenure” (Sundaraman et al., 2010).

In this paper, it is not possible to decompose the relative importance of these factors; however, as aconcept, there are possible explanations as below why PTA teachers tend to have better incentive towork harder than TSC teachers.
i)Less monitoring on TSC teachers:-6-Government teachers (TSC teachers) are not as closely monitored by principles, that is, theCentral Government, the Ministry of Education Science and Technology (MoEST), as PTA
teachers monitored by the school surrounding communities. In Kenya, country is divided into
eight administrative regions (known as provinces). Each province has a Provincial Director of
Education Office. In each province, there are districts, and in total 158 districts exist in the entire
land. The work of primary school teachers are principally monitored by each district, the Districtof Education Office. However, due to the large number of schools, district education officers are
not well checking the work of each primary school teacher. On the other hand, PTA teachers areworking harder because they are under direct monitoring by the school community.

ii) Accountability of usage of schools fund:
Before introducing the Free Primary Education policy, public primary schools were in charge ofcollecting school fees from parents and were entitled to decide how to spend the collected money.
In that time, schools were obliged to make efforts to be accountable to payers, that is, parents ofpupils. However after introducing the FPE (Free Primary Education) policy, schools need to be
more accountable to the district level of education officers as well as to the Central Government
where the capitation fund has allocated to each school (Sasaoka et al. 2007). In this way, while theFree Primary Education has succeeded in assisting low income parents to send their children toschool, however it happened to deprive the interest of parents to manage schools or incentive tomonitor schools (Sawamura 2004a).

iii) Future Job opportunity for PTA teachers:
Moreover, the job opportunity for PTA teachers to become registered government teachers is open
after teaching and when they go to school. Though quantitative information is not found, in
qualitative study, it reveals that a PTA teacher works hard to be a registered TSC teacher (Ito 2011).
Also, new graduates of teacher training colleges often work for several years as PTA teachers and-7-

obtain positions as civil service teachers (Duflo et al. 2009). In the system of registration, it holds
the opportunity open for non-graduate teacher to become a registered teacher.

iv) Wage payment system:
The difference in teaching effort level can be also explained by the clearly different payment
system as well. It is often observed that in developing countries, hiring, salaries and promotion are
decided by educational qualifications and seniority, with less scope for performance thandeveloped countries (Chaudhury et al. 2006). In Kenya, the wage for TSC teachers is determinedby school education history of teachers, not by their performance (Sawamura 2004b). Moreover,
not only the wage level, but also decisions regarding hiring, firing, and transferring teachers in
Kenya have long been made centrally by the Ministry of Education. It is famous that Kenyan
public school teachers have strong civil service and union protection and are difficult to fire
(Glewwe et al.2010). On the other hand, if PTA teacher is hired by the community decision, it’smore likely for PTA teacher’s performance to be reflected in the wage. To put this in more
simplified manner, borrowing from Sawada (2000), it is assumed the linear function of wage as
below for both TSC and PTA teachers.
1)

W = 𝑎1 + 𝑎2 𝑂𝐸“OE” stands for “observable effort” by the community and note that a case of 𝑎1 > 0 and
𝑎2 = 0 represents a fixed wage contract, while 𝑎2 > 0 is a piece rate contract. Though thepayment scheme for each PTA teachers are not certain, it is clear that TSC teachers have the fixed
wage contract, where wage function (1) has 𝑎2 = 0, in other words, wage level does not dependon the level of “OE”. From this condition, TSC teachers would make less effort to teach, since𝑎2 = 0 and it does not change wage level. On the other hand, it is assumed that PTA teachers are
more likely to make efforts than TSC teachers, because wage is endogenously determined by the“observed effort”.

-8-v) Based on those various reasons mentioned above, it is reasonable to assume PTA teachers havebetter incentive to make more efforts in teaching than that of TSC teachers. However, it isremained uncertain how effectively PTA teachers can teach with their higher effort level. In otherwords, since there are no variables to estimate the ability of PTA teachers, it is not yet known if
the level is efficient or not. In short, if test score Y of the ith pupil in jth school can be written as2)

𝑌𝑖𝑗 = 𝐹(𝑋𝑖𝑗 𝑍𝑗 𝐸𝑗 𝑎𝑗 𝑒𝑗 )where Y is a function of school observed characteristics Z, pupil and household characteristics X,
Environment (Village) characteristics E, 𝑎𝑗 is the total ability of PTA teachers at jth school and 𝑒𝑗
is the total effort level of PTA teachers. Although it is not possible to estimate the level of effort andability for PTA teachers directly, the ratio of PTA and TSC teachers are observable in dataset. In thispaper, under the simplest assumption, PTA teacher represents higher effort level with lower ability
in teaching, while TSC teacher represents lower effort level with higher ability in teaching as table 1
below. Therefore, under this simplified assumption, by looking at the coefficient of PTA teacher
ratio, it is possible to estimate which marginal effect, ability or effort level, would bring stronger
impact on test score.
Table 1 Simplified category of PTA teacher and TSC teacher ability and effort level

Ability Level

Effort LevelHigh

TSC teacher

PTA teacher

Low

PTA teacher

TSC teacher

If the coefficient of PTA teacher ratio is positive and significant, it means that the effort level has
stronger impact on pupil education outcome than that of ability. If the coefficient of PTA teacher
ratio is negative and significant, it can interpret that the ability is stronger impact than that of effort
level.

5. Identification Strategy-9-In order to estimate the impact of PTA teacher on school outcome, there are two different estimations
made in this paper. First is to estimate the impact of whether at least one teacher exists in school or not.
Second, since the impact of the average treatment on the treated (below referred as TOT) is
heterogeneous among schools as following section presents, in the second estimation, the outcome(TOT) will be regressed on PTA teacher ratio, so as to see if the ratio of PTA teacher has explanatory
power on heterogeneous variation of TOT.

5. 1 Propensity Score Matching Estimation Concept
Now, 𝑌0𝑗 denotes the average test score outcome in jth school where there is no PTA teacher, while
𝑌1𝑗 denotes the average test score outcome in jth school where there is at least one PTA teacher. To
define the average treatment effect on the treated (TOT), it is derived as follows:(1) 𝑇𝑂𝑇 ≡ 𝐸(𝑌1𝑗 − 𝑌0𝑗 |𝐷𝑗=1 )= {𝐸(𝑌1𝑗 |𝐷𝑗=1 ) − 𝐸(𝑌0𝑗 |𝐷𝑗=0 )} − {𝐸(𝑌0𝑗 |𝐷𝑗 = 1) − 𝐸(𝑌0𝑗 |𝐷𝑗 = 0)}
The observable difference in test score between treated and controlled group in the second equation ofleft hand side denoted as 𝐸(𝑌1𝑗 |𝐷𝑖=1 ) − 𝐸(𝑌0𝑗 |𝐷𝑗=0 ), which is not precisely estimating TOT, since
this includes the selection bias term of 𝐸(𝑌0𝑗 |𝐷𝑗 = 1) − 𝐸(𝑌0𝑗 |𝐷𝑗 = 0). In order for us to estimate the𝑇𝑂𝑇 ≡ 𝐸(𝑌1𝑗 − 𝑌0𝑗 |𝐷𝑖=1 ), we need to know the value of counterfactual 𝐸(𝑌0𝑗 |𝐷𝑗 = 1). By putting theConditional Independence Assumption { Y0𝑗, Y1𝑗 } ⊥ D𝑗 | 𝑋𝑗 , equation (1) can be rewritten(1)′ 𝑇𝑂𝑇 ≡ 𝐸(𝑌1𝑗 − 𝑌0𝑗 |𝐷𝑗=1 )= {𝐸(𝑌1𝑗 |𝑋𝑗 , 𝐷𝑗=1 ) − 𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗=0 )} − {𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗 = 1) − 𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗 = 0)}= {𝐸(𝑌1𝑗 |𝑋𝑗 , 𝐷𝑗=1 ) − 𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗=0 )}The second term of right hand side equation of (1)′ 𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗 = 1) − 𝐸(𝑌0𝑗 |𝑋𝑗 , 𝐷𝑗 = 0)
become zero, since Conditional Independence Assumption (below referred as CIA) assures that the
PTA teacher existence is independent from the outcome of school test score average, conditioned on
𝑋𝑗 .

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However, if there are many covariates, such strategies may not be feasible nor impractical, since thedimension of X could be very high. Therefore as Rosenbaum and Rubin (1983) explained, analternative approach is based on the propensity score, the conditional probability of receiving
treatment given covariates. They had proved that if the treatment assignment is “strongly ignorable”
given covariates X, then it is strongly ignorable given any balancing score b(X), and the propensity
score is defined as one of the balancing score. As a result, adjusting solely for differences in propensity
score between the treated and control units removes all biases under the CIA, and reduces a potentiallyhigh-dimensional matching problem to a single-dimensional problem. In the formula, under the CIA,
the outcome of Y is independent distribution from 𝐷𝑗 if the propensity score is similar, that is,{ Y0𝑗, Y1𝑗 } ⊥ D𝑗 | 𝑃(𝑋𝑗 )In the end, the average treatment effect on the treated (TOT) can be derived with the estimatedPropensity Score as follows;(1)′′ 𝑇𝑂𝑇 ≡ 𝐸 {𝐸(𝑌1𝑗 |𝑃(𝑋𝑗 ), 𝐷𝑗=1 ) − 𝐸(𝑌0𝑗 |𝑃(𝑋𝑗 ), 𝐷𝑗=0 )| 𝐷𝑗=1 }5.2 Advantages and Concerns in using PSM Estimation
There are several reasons the PSM estimation is preferred in this paper to the traditional regression
analysis, though CIA is not perfectly satisfied. Even so, it is still more preferable to use PSM than
OLS. One reason is that PSM estimation does not require functional form to be linear. Because ofnature of relationship between educational inputs and school achievement, it is more appropriate toassume nonlinear functional form.

In addition, as the second point, in order to estimate consistent parameter by PSM method, it requires
good number of variables which exist for both treated and controlled group. In this paper, because of
the characteristics of the dataset, aiming to cover most of important variables to estimate pupil schooloutcome, it is reasonable to judge that number of variables are not too small to estimate the propensity
score appropriately.
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In addition, according to Khandker (2010), given two broad provisions, the bias in PSM program
estimates can be low. First, it is preferred to use the same data source for treatment and controlledgroup, which ensures the observed characteristics are measured similarly. Regarding this point, thedataset satisfies that both treated and controlled groups were drawn from the same dataset. As for thesecond point, it is preferable to use the representative sample survey of nonparticipants as well as
participants. In this point, the survey constructing the data is well corresponded since the UWEZO
takes the nationally representing survey scheme.

In the end, from a part of descriptive statistics table below, it is obvious that characteristics of villages
and educational inputs differ greatly between PTA teacher zero school and PTA teacher none zeroschool. The difference is clear in school test score and other village and regional characteristics. In
terms of Kiswahili and English average test score difference, the null hypothesis that mean between
two groups is zero is rejected. Hence, PSM estimation is more sensible to compare across treated andmatched control units by using the Propensity Matching Score.
Table 2 Descriptive Statistics for PTA teacher zero school and for PTA teacher none zeroschool(1) PTA Teacher RATIO=0(2) PTA Teacher RATIO>0

Sample(#)

Mean

Std. Dev.

Sample(#)

Mean

Std. Dev.

School Average Kiswahili Score

414

4.032

0.718

1802

3.941

0.710

Ho: diff = 0(P-value)
0.0191

School Average English Score

414

4.000

0.714

1802

3.909

0.686

0.0169School Average Numeracy Score

414

6.311

1.252

1802

6.321

1.127

0.8804Village has electricity infra

414

0.528

0.499

1802

0.403

0.490

0.0000Village has concrete paved roads
Household Level Variable(School Average)
Parents who paid tuition

414

0.207

0.406

1802

0.136

0.343

0.0002

414

0.409

0.388

1802

0.438

0.362

0.1509Mother Education History

414

0.797

0.332

1802

0.808

0.318

0.5397

School Level Variable

Village Level Variable

5.3 Estimation of Propensity Score
In order to find appropriate propensity score, it requires variables which would affect the likelihood of
having at least one PTA teacher as well as variables which influence the outcome. The propensity- 12 -

score is estimated as follows. First, let us assume that the latent variable of 𝐷𝑗 ∗ can be written as
below:(2)𝐷𝑗 ∗= 𝑋𝑗 𝐵 + 𝜇𝑗
When the latent variable 𝐷𝑗 ∗ is greater than 0 then 𝐷𝑗 denotes 1 and when
𝐷𝑗 ∗ is equal to or smaller than 0 then 𝐷𝑗 denotes 0. 𝑋𝑗 includes a vector of followings: 1) average
household and pupils characteristics attending on jth school, 2) jth school characteristics and 3) village
characteristics where jth school is located as well as 4) a vector of district dummy, existing one
hundred twenty one districts in the dataset. 𝜇𝑗 is a vector of error term, by assumption E( 𝜇𝑗 ) =0 and Var (𝜇𝑗 ) = 𝜎 2 . The descriptive statistics of those variables from 1) to 4) are attached in the
Appendix 1 and probit estimation result is found in Appendix 2. The error term of 𝜇𝑗 is assumed tofollow the Normal Distribution. Then, the propensity score can be written𝑃(𝐷𝑗 = 1|𝑋𝑗 ) = Φ(𝑋𝑗 𝐵/𝜎)

5.4 Average Treatment Effect on the Treated (TOT)
After estimation of Propensity Score, the predicted value of Propensity score is used to estimate the
TOT by matching treated schools and none treated schools. There are different matching criteria used
to assign the treated and none treated schools. In this paper, seven different methods of matching were
tested to see the robustness as follows:i)

Nearest neighbor Matching: The each treated school is matched to none treated schools whichhave the 1st, 2nd and 4th nearest or closest propensity score obtained.

ii)

Radius Matching: There is a possibility that the matched propensity is very different from thenearest one of those treated school. Therefore, the radius matching limits propensity scorewithin a certain range to be matched.

iii)

Kernel Matching: In order not to use only small number of controlled group schools asmatched schools, the kernel matching can use a weighted average of all nonparticipants toconstruct the counterfactual match for each participant.
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5.5 Heterogeneous Impact of PTA teacher ratio on the outcome
The following histograms are the TOT distribution of Numeracy, English and Kiswahili test score. Bylooking at the TOT distribution among treated schools, it is widely distributed from negative topositive point. If PTA teacher has only positive impact on test score at any school, it is assumed that
TOT can be always positive. However, it does not hold true. Rather the impact of at least one PTA
teacher existence is heterogeneous among treated schools.

From the left, Figure 1 Histogram for TOT of English for one to one nearest matching estimation
In the middle, Figure 2 Histogram for TOT of Kiswahili for one to one nearest matching estimation
From the right, Figure 3 Histogram for TOT of Numeracy for one to one nearest matching estimation

Hence, as Lin et al. (2009) explores the heterogeneity feature of the effectiveness of the treatment, inorder to examine the causes of this heterogeneous impact on the treated, TOT is regressed on PTA
teacher ratio so as to see if heterogeneous impact can be explained by the PTA ratio or not. Followedby preceding studies of education production function, the outcome of production function can be
written by equation (3). For the jth school, Y, the education outcome of Numeracy, English andKiswahili, can be written as function of school and village characteristics Z, school averaged pupil andhousehold characteristics H, district dummy variables E and 𝐷𝑟𝑎𝑡𝑖𝑜 𝑗 is PTA ratio value for the jthschool, ranging from a value of 0 to 1 if all teachers are PTA teachers.
(3)𝑌𝑗 = 𝐹(𝐻𝑗 𝑍𝑗 𝐸𝑗 𝐷𝑟𝑎𝑡𝑖𝑜 𝑗 )By linearizing and adding a stochastic term, the equation (3) can be rewritten as follows.
(4)𝑌𝑗 = 𝐻𝑗 𝛽 + 𝑍𝑗 𝛾 + 𝐸𝑗 𝛼 + 𝐷𝑟𝑎𝑡𝑖𝑜 𝑗 𝛿 + 𝜇𝑗
by assumption, E( 𝜇𝑗 ) = 0 and Var (𝜇𝑗 ) = 𝜎 2 .
- 14 -

Now, it is our interest to estimate the coefficient of PTA teacher ratio, that is, 𝛿 for the PTA ratio
effect on outcome, TOT. Therefore the estimation model of (4) should be rewritten as below:(5) 𝐸 {𝐸(𝑌1𝑗 |𝑃(𝑋𝑗 ), 𝐷𝑗=1 ) − 𝐸(𝑌0𝑗 |𝑃(𝑋𝑗 ), 𝐷𝑗=0)| 𝐷𝑗=1 } = H𝑗 ε + 𝑍𝑗 η + 𝐸𝑗 λ + 𝐷𝑟𝑎𝑡𝑖𝑜 𝑗 𝜔 + 𝜇𝑗

6. Data
6.1Nature of Data
This paper uses dataset available through website of UWEZO Kenya, which is a part of Twaweza, “anindependent East African initiative” supported by donors, such as the World Bank and others(UWEZO East Africa 2012). For education individual data, UWEZO dataset contains the largest
national assessment results conducted in three Eastern African countries of Tanzania, Kenya andUganda, “350,000 children in over 150,000 households across the three countries were tested in theirability to perform basic numeracy and literacy tasks at the Standard 2 level” (UWEZO East Africa2012).2

In Kenya, there are two surveys conducted by UWEZO Kenya in September to October in 2009 and in
February to March in 2010. Both 2009 and 2010 UWEZO assessments adopted survey methods that
produced a nationally representative random sample of the target population.3 In total, 2009 and 2010
UWEZO Kenya has covered following number of schools, villages, households and children.4
However, due to the large number of missing values in 2009 dataset, this paper chooses to use 2010
dataset for estimation.

2

Other surveys conducted to test the education achievement in eastern African regions, such as SACMEQ I, II,
and III, those surveys do not have much samples as UWEZO.
3Those samples are children of primary school age up to and including children aged 16. Though there are some
districts not surveyed in 2009 (88 districts) and in 2010 (36 districts), the random sample selection method wasmaintained as follows: First, all the surveys have followed a three stage random sampling process, 1) selection of
districts (strata) by simple random selection, with each district given an equal probability of selection; 2)
selection of enumeration area (typically villages) with probability proportional to population size and 3)
selection of households in each enumeration area by systematic sampling.
4
The dataset which was available from the website slightly differ in number of samples from what the reportsays. For example, the dataset available from website contains 179,370 samples for individuals, 3,565 villages
surveyed and 3,448 schools were surveyed in UWEZO Kenya dataset 2010. As for UWEZO Kenya dataset 2009,
it contains 106,273 samples for individuals, 2,160 villages and 2,160 primary schools surveyed.

- 15 -

Table 3 2009 and 2010 UWEZO Kenya Surveyed Samples
Survey Round2009 (Sep/Oct)2010 (Feb/Mar)Districts
70
122

Schools
2,029
3,474

Villages
2,029
3,628

Household33,76055,843Pupils
79,693
131,9715(Source: UWEZO East Africa at Twaweza, 2012 August)

6.2 Descriptive Statistics and Variables
From UWEZO dataset 2010, the effective sample size for this estimation is 2,216 public primaryschools. The descriptive statistics is attached in Appendix 2.
1) Independent Variables
Test score of Kiswahili, English and Numeracy which were tested at time of household survey. Score
of Kiswahili and English is rated from 1 to 5 while Numeracy is rated from 1 to 8 as follows:
Kiswahili; 1; Nothing, 2; Able to read Letter, 3; Words, 4; Paragraph, and 5; Story
English; 1; Nothing, 2; Able to read Letter, 3; Word, 4; Paragraph, and 5; Story
Numeracy; 1; Nothing, 2 ;Able to count 1-9, 3; Able to count 10-99, 4; Able to count greater than
10-99, 5; Able to calculate addition, 6; Able to calculate subtraction, 7; Able to calculate multiplication,and 8; Able to calculate division.

In order to control other effects than PTA teacher ratio, following variables are selected as controllingvariables, based on preceding estimations for education production function.

2) Class size, Pupil Teacher Ratio (PTR) and PTA teacher ratio Variables
It is our interest to estimate the effect of PTA teacher ratio, which is closely related with pupils perclass size and pupils per government teacher. Therefore, it is essential to control these two effects to
TOT, otherwise PTA teacher ratio is likely to estimate the effect of large class size or large number of5

Initially, the surveyed dataset has 179,411 samples of individuals. After grouping samples who have been to
those surveyed public primary schools and grade less than 8th (this is the highest grade of public primary schools
in Kenya), the sample size has reduced to 65,541. Due to the large number of missing values, the effective
samples are 30,633 individuals and 2,216 primary schools.

- 16 -

pupils per one teacher. That is because the motivation for public primary schools to hire a PTA teacher
is to compensate the shortage of TSC (government) teachers. To control the effect of high pupilteacher ratio (PTR), there are two variables: one is pupil teacher ratio (PTR) and the other is pupil TSC(government) teacher ratio. The former is to control the effect of teacher shortage in general after theyhire PTA teachers, while the latter variable is specifically controlling the shortage of government
teacher. Since both are highly correlated, this paper chooses to select the pupils TSC teacher ratio as
control variable. That is because if otherwise, the PTA teacher ratio variable is only to capture theeffect of government teacher shortage. In addition to pupil TSC teacher ratio, the variable for class size
is included. As those above variables are skewed to the left, they were converted to logarithm and usedin the estimation, which histogram is available in Appendix 3.

3) Household and Pupil Variables
As in preceding studies, the socio-economic index based on family possessions is included as control
variables (Bourdon, J. et al., 2007), household decision to invest in children is closely related with thehousehold socio-economic characteristics. As proxies for wealthiness of a household, the asset
variables were used, such as Type of house and possession of telephone. Also, there might be aresource allocation issue about who to be invested most if the number of children is large. There is novariable for the number of siblings; however as the proxy variable, total number of household
members is used to control the effect of resource competition. In addition, the effect of mother’s
education whether they have graduated primary school or not is controlled, since it directly affects
living standards of children as well as indicates socio economic status of family. In order to control
preference over children education, the variable if parents pay tuition or extra fee to school is added.

As for pupil characteristics, though it is impossible to control the innate ability directly, variables
included are age, age squared and their school grade, since the older they are, it becomes much easier
to take good score, since the test level is set for Standard grade two level. However, the effect of- 17 -

getting “old” is none linear to school outcome, therefore the squared term is added. To control thephysical health which directly affects the school outcome, the number of meal in one day that pupil
can take is also controlled.

4) School Input Variables
In the early study of education production function, Heyneman and Loxley (1983) explained that “thepoorer the national setting in economic terms, the more powerful this (school inputs and teacher
quality) effect appears to be”. Since this “H-L effect” has been widely recognized and supported byseveral preceding studies, it is necessary to control the supply side information in estimating pupils
school outcome. This paper includes three variables for school inputs. 1) Dummy variable if school
has learning supplement materials or not. 2) Dummy variable if the classroom is suitable for learningspace or not. These two variables are to capture the primary condition of learning space and materials.
3) Dummy variable if school is fenced or not, since the security in some areas in Kenya are still
remained fragile especially after the large scale of post-election violence in 2008. The variableindicates if school is careful in surrounding security incident or not.

5) Village and District Variables
Since there are large disparities between regions in Kenya, environmental factors are important to becontrolled. In order to control the similarity at the district level, one hundred twenty one district
dummy variables are added. It is very likely that the characteristics of the district area is similar eachother therefore, it is possible to see if PTA teacher ratio still has explanatory power on the outcome,after controlling the district level similarities. As for village where school is located, the dummy
variable if roads are paved by concrete is added. Also, dummy variable is selected to show if village
has an electricity infrastructure or not. Those variables are proxy variable to control the access andease of transportation to villages.

- 18 -

7. Result and Interpretation
In this section, it is divided into three. First, it shows the result of probit estimation, which is toconstruct the propensity scoreecond, the average treatment effect on the treated (TOT) is reported for
different matching algorism. At last, heterogeneity of TOT will be regressed on PTA teacher ratio andother controlling variables so as to find if PTA teacher ratio can explain the heterogeneous impact on
the treated with statistical significance.

7.1 Probit Estimation Result
First, the probit model is used to generate a propensity score that assesses a school or village’s
likelihood of hiring at least one PTA teacher. Table in Appendix 4 shows the estimation result thatvariables of village characteristics and school inputs are statistically significant. For example, whether
village has electricity infra or not is negative and the size of class as well as supplementary materials
in school are negative and significant. This means that PTA teacher is likely to be hired where villages
do not have electricity or have less educational input such as learning supplementary materials, inaddition to less number of pupils in one class after controlling the TSC teacher shortage. In terms ofgovernment teacher shortage, it is obvious that PTA teacher is likely to be hired where pupil
government teacher ratio (PTR) is high in school, indicating positive and one percent statisticalsignificance.

On the other hand, none of the average household and pupil characteristics variables become
statistically significant. From this result, though it seems less important to include household andindividual characteristics in the estimation of propensity score, it is essential to do so since thepropensity score must be calculated on the basis of all observed covariates X that jointly affectparticipation and the outcome of interest, that is, the school average test score.

7.2 Average treatment on the treated- 19 -

In addition to the CIA, in order to make PSM estimation appropriately, it is necessary to confirm thatthe common support exists and overlapping condition is satisfied. The histogram in Appendix 3 is tocompare the distribution of Propensity Score for both treated and controlled for Kiswahili and English
as an example. The shape of distribution does not look similar between treated and controlled;
however the propensity score of the treated group is mostly covered by the distribution area of thecontrolled group. In the end, total effective samples become 1887 for all standard grade estimation andto 1720 for standard grade below three pupils.

The following table 4 presents TOT for seven different matching algorithms by subject, Numeracy,
English and Kiswahili and two different grade groups. 95 percent of confidence intervals are estimatedusing bootstrapped standard errors (500 replications). With different matching algorithms, innearest matching estimation one to one, one to two and one to four as well as kernel normal
matching estimation, it is consistent for Numeracy subject, estimated TOT is positive andstatistically different from zero. In other subjects, TOT does not become statisticallysignificant by any matching criteria. In spite of the significance in Numeracy, that magnitude
is relatively small. For example in the nearest one to one matching estimation, the impact of
the treatment on outcome is 0.29 score higher on school average than those controlled schools
with similar characteristics. Also in the 95 percent confidence interval, the minimum value of
TOT includes negative value in the nearest matching estimation.

There are possible explanations why the treatment effect on the treated is weak in Numeracy
and not significant in any other subjects. One of the reasons could be that TOT only shows theeffect of whether one PTA teacher exists or not. It does not specify the level of treatment, sincetreatment dummy is 1 even if ten PTA teachers exist in a school or only one PTA teacher exits
in a school. In short, it is natural that the PTA teacher effect on outcome should differ,depending on level of treatment, that is, ratio of PTA teachers. However this TOT estimation- 20 -

does not differentiate the impact of it.6 Hence, it is more sensible to find the relative effect,that is, PTA teacher ratio on outcome in the next estimation.

In separate estimation, TOT was estimated by different group of PTA teacher ratio. Schools with
PTA teacher are divided into 5 groups from the highest PTA teacher ratio to the lowest ratio group.
Then, in each group, the matching was done with the controlled group. As a result, TOT is positiveand significant in the highest PTA teacher ratio group in Numeracy. The detailed estimation result
is available from author.
6- 21 -

Table 4 Treatment effect on the treated (TOT)) with different matching criteria[Nearest Matching: N=1]
Kiswahili
EnglishNumeracy

Coef.
0.099094
0.1086848
0.2979102

Std. Error
0.0839997
0.0795833
0.1441951

z
1.18
1.37
2.07

P>|z| [95% Conf. Interval]
0.238 -0.065542 0.2637304
0.172 -0.047296 0.2646652
0.039 0.0152931 0.5805274

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.090576
0.0085987
0.0266911

0.0939274
0.0915486
0.1609512

-0.96
0.09
0.17

0.335
0.925
0.868

[Nearest Matching: N=2]
Kiswahili
EnglishNumeracy

Coef.
0.0630791
0.0715681
0.2328433

Std. Error
0.0774228
0.0678459
0.1235065

z
0.81
1.05
1.89

P>|z| [95% Conf. Interval]
0.415 -0.088667 0.2148249
0.291 -0.061408 0.2045436
0.059 -0.009225 0.4749115

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.032194
0.0131391
0.1024195

0.0920423
0.082894
0.1588129

-0.35
0.16
0.64

0.727
0.874
0.519

[Nearest Matching: N=4]
Kiswahili
EnglishNumeracy

Coef.
0.0630791
0.0715681
0.2328433

Std. Error
0.0774228
0.0678459
0.1235065

z
0.81
1.05
1.89

P>|z| [95% Conf. Interval]
0.415 -0.088667 0.2148249
0.291 -0.061408 0.2045436
0.059 -0.009225 0.4749115

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.032194
0.0131391
0.1024195

0.0920423
0.082894
0.1588129

-0.35
0.16
0.64

0.727
0.874
0.519

[Kernel Epanechnikov]
Kiswahili
EnglishNumeracy

Coef.
-0.003638
0.005942
0.1304541

Std. Error
0.0534219
0.0484326
0.0911568

z
-0.07
0.12
1.43

P>|z| [95% Conf. Interval]
0.946 -.1083428 .1010673
0.902 -.0889843 .1008682
0.152 -.04821 .3091182

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.055638-0.023244
0.0627457

0.0663704
0.0594192
0.1130825

-0.84
-0.39
0.55

0.402 -.1857211
0.696 -.1397037
0.579 -.1588919[Kernel normal Matching]
Kiswahili
EnglishNumeracy

Coef.
0.099094
0.1086848
0.2979102

Std. Error
0.0834914
0.0795895
0.1410998

z
1.19
1.37
2.11

P>|z| [95% Conf. Interval]
0.235 -0.064546 0.2627341
0.172 -0.047308 0.2646774
0.035 0.0213597 0.5744607

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.090576
0.0085987
0.0266911

0.1014663
0.0886113
0.164207

-0.89
0.1
0.16

0.372
0.923
0.871

[Radious 0.05]
Kiswahili
EnglishNumeracy

Coef.
-0.007359
0.003339
0.125088

Std. Error
0.0489946
0.048436
0.0897142

z
-0.15
0.07
1.39

P>|z| [95% Conf. Interval]
0.881 -0.103387 0.0886686
0.945 -0.091594 0.0982719
0.163 -0.050749 0.3009247

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.05563-0.022831
0.0599964

0.0689579
0.0643576
0.1143695

-0.81
-0.35
0.52

0.42
0.723
0.6

[Radius 0.1]
Kiswahili
EnglishNumeracy

Coef.
-0.032346-0.02563
0.0599805

Std. Error
0.0476492
0.0446959
0.0794656

z
-0.68
-0.57
0.75

P>|z| [95% Conf. Interval]
0.497 -0.125737 0.0610445
0.566 -0.113232 0.0619727
0.45 -0.095769 0.2157303

Kiswahili
Std<=3English
Std<=3
Numeracy Std<=3-0.083115-0.051569
0.0479331

0.066229
0.0616157
0.1038951

-1.25
-0.84
0.46

0.209
0.403
0.645

7.3 Heterogeneous Impact of the treatment- 22 --0.27467-0.170833-0.288768-0.212594-0.14933-0.208848-0.212594-0.14933-0.208848-0.289446-0.165076-0.295149-0.190784-0.14897-0.164164-0.212921-0.172333-0.155697

0.0935186
0.1880306
0.3421497

0.1482054
0.1756083
0.4136871

0.1482054
0.1756083
0.4136871.0744459.0932153.2843833

0.1082946
0.1822737
0.348531

0.0795254
0.1033076
0.2841564

0.046692
0.0691958
0.2515637

As it was briefly explained in the previous section showing the histogram of TOT, the treatment effecthas differed greatly from school to school. In some schools, TOT is negative, while others present
positive outcome. To analyze this heterogeneous effect on outcome, TOT will be regressed by the PTA
teacher ratio. This estimation is to find if the magnitude of TOT for each treated school can be
explained by the PTA teacher ratio. The following table 5 is only to report the estimated coefficient of
PTA teacher ratio by different matching algorism. There are seven different matching algorisms used
for the estimation of TOT and detailed estimation result is attached in Appendix 5. From table 7 to 20
in Appendix 5, in column (1) is the result of TOT regressed merely by PTA teacher ratio. From column(2) to (7), it adds following variables to column (1) estimation as independent variables accordingly:
column (2) village variables, column (3) education resource variables, column (4) average householdsocio economic characteristics for pupils variables, column (5) average pupil characteristics variables,
column (6) average of age and age squared for pupils as well as log of pupils per classroom and pupilteacher ratio in school and lastly column (7) estimation includes one hundred twenty one district
dummies.

In summary of the result from table 7 to table 20, after column (5), controlling the household and pupilcharacteristics on school average, the estimated coefficient of PTA teacher ratio is always positive andsignificant effect to TOT. Also, as the number of variables becomes increased from column (1) to (6),
it is observed that the magnitude of coefficient has become larger in all estimation result. This meansthat after controlling various factors which would affect TOT, the explanatory power of PTA teacher
ratio has become more distinctive. However, once it adds one hundred twenty one district dummies incolumn (7), the statistical significance of PTA teacher ratio is observed only in the standard grade
below three pupils except Kernel and Radius matching algorism. Only Kiswahili subject, it isconsistently observed positive and significant in seven algorism.

- 23 -

Table 5 PTA teacher ratio coefficient
Kiswahili
Nearst Matching 1 to 1 matching
PTA teacher ratio

Nearst Matching 1 to 2 matching
PTA teacher ratio

Nearst Matching 1 to 4 matching
PTA teacher ratio

Kernel Matching
PTA teacher ratio

Kernel Normal
PTA teacher ratio

Radius 0.05
PTA teacher ratio

Radius 0.1
PTA teacher ratio

EnglishNumeracy Kiswahili English
Numeracy
All Grades
Standard Grade below 3

0.2722[1.02]

0.3047[1.22]

0.8297[1.97]**

0.955[2.95]***

0.6457[2.11]**

1.1477[1.97]**

0.3061[1.47]

0.2451[1.21]

0.6752[1.88]*

0.9238[3.28]***

0.6316[2.54]**

1.0439[2.07]**

0.3806[2.05]**

0.2939[1.67]*

0.7192[2.28]**

0.7149[2.86]***

0.4113[1.82]*

0.8392[1.90]*

0.2389[1.57]

0.069[0.47]

0.4182[1.60]

0.5171[2.22]**

0.2319[1.10]

0.6444[1.56]

0.2722[1.02]

0.6457[2.11]**

0.8297[1.97]**

0.955[2.95]***

0.6457[2.11]**

1.1477[1.97]**

0.2229[1.46]

0.0527[0.36]

0.3838[1.46]

0.4907[2.11]**

0.2065[0.98]

0.612[1.47]

0.1561[1.03]-0.0015[-0.01]0.2639[1.01]

0.4149[1.78]*

0.1865[0.89]

0.5968[1.45]

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value
to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.

It is natural that there is a difference in the statistical significance and magnitude of PTA teacher ratio
between the school average and lower standard grade average of TOT, since it is said that PTA teacher
tends to teach lower grade pupils where the largest enrolled pupils exist. In order to compensate theteacher shortage, PTA teachers are often assigned to teach lower standard grade pupils. In this sense, if
effort level in teaching of PTA teachers is higher than those of ability level, then it should be more
apparent in lower grade pupils test score. Therefore, the statistical significance and sign of PTA ratio isunderstandable. On the other hand, in terms of magnitude, for example if PTA teacher ratio increases 1
percent, then the test score of Kiswahili is increased 0.0095 point, based on the result of nearest one to
one neighbor matching. In spite the fact that the test score ranges from 1 to 5 in Kiswahili and the- 24 -

percentage of PTA ratio does not increase by 1 percent, rather it increases in larger percentage point byadding one PTA teacher, the magnitude of 0.009 point increase by PTA ratio one percent increase isrelatively small.

As for other control variables, the coefficient of log of pupil government teacher ratio is statisticallysignificant and positive in column (7) for the nearest neighbor one to one, one to two and one to four
matching as well as for kernel normal matching algorism as it shows in Appendix 5 table from 7 to 20.
This is a counter intuitive sign, since the large number of pupils per one government teacher should
negatively affect the test score of pupils. However, it is understandable, if the independent variable is
TOT, not actual average test score of each school. TOT was estimated by matching with similar
characteristics of controlled schools. Therefore, if the shortage of government teacher is serious, that is,the value of log of pupil government teacher ratio is large, and still there is no PTA teacher tocompensate the shortage in control schools, that leads to assume that the value of TOT is likely to belarge, since TOT is a test score difference between control and treated schools. On the other hand, if
the shortage of government teacher is not serious, then TOT value is not assumed to be large. In thisway, by the value of log of pupil government teacher ratio, the difference between the treated andcontrolled is likely to differ. As the value of log of pupil government teacher ratio becomes larger, theoutcome difference between the treated and controlled schools would become larger.

In order to confirm this finding, following section is to estimate the effect of PTA teacher ratio inshortage of teacher. If the interaction term of PTA teacher ratio and shortage of teacher dummy ispositive and statistically significant, then it means that the PTA teacher ratio effect to TOT is more
distinctive in those schools where teachers are short than those schools where sufficient teachers exist.
The dummy variable of shortage of teacher is made by the log of pupil teacher ratio. If the pupilteacher ratio is higher than the average, the dummy takes 1 and otherwise, zero.

- 25 -

7.4 PTA teacher and their roles in primary schools
Table 6 shows the coefficient of PTA teacher ratio and of interaction term as well as the resultof joint test that the sum of total effect is zero. There are several findings from table 6. First,
1) All the estimation result except Numeracy of lower standard grade pupils has showed thatthe interaction term of coefficient of PTA teacher ratio and Teacher shortage dummy ispositive and significant. This is consistent through all estimated TOT by seven different
matching algorisms.7 Moreover, 2) as for the coefficient of PTA teacher ratio, none of theestimation result has become negative and significant except radius 0.1 matching, after
controlling the shortage of teachers. This means that PTA teacher ratio does not havenegative effect on TOT, even in schools where teachers are sufficient. Third, 3) although it is
not statistically significant, signs of some PTA teacher ratio coefficients are negative. However,based on the result of joint hypothesis test, the total effect of PTA teacher ratio to TOT is
statistically different from zero with less than one percent significance, except Numeracy oflower standard grade pupils in. Even in Numeracy of lower standard grad pupils, TOT
estimated by nearest matching and kernel normal matching algorisms are statisticallydifferent from zero with five percent significance. In this way, it can be inferred that PTA
teacher ratio itself has positive effect on TOT without specifying type of schools.

Nearly the same finding was confirmed in the estimation of “government” teacher shortage.
In the separate estimation, the interaction term of PTA teacher ratio and shortage of“government” teachers was replaced with the shortage of teachers. The finding is that in any
cases, the interaction term is not negative and statistically significant. Also, even if thenegative value of coefficient of interaction term was estimated, the joint test result rejects
with the statistical significance the null hypothesis that sum of coefficient of PTA teacher
ratio and the shortage of teacher is zero.
- 26 7

Table 6
Kiswahili
Nearest Neighbor Matching (one to one)
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term=0)
Nearest Neighbor Matching (one to two)
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term=0)
Nearest Neighbor Matching (one to four)
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term
=0)
Kernel Matching
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term
=0)
Kernel Normal Matching
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term=0)
Radius (0.1) Matching
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term=0)
Radius (0.05) Matching
PTA Ratio and Teacher shortage DummyPTA Teacher Ratio
Teacher shortage Dummy
F statistics
P value (Ho: PTA Ratio+Interaction Term
=0)

EnglishAll Grades

Numeracy

Kiswahili
EnglishNumeracyStandard Grade below 3

0.92281.01171.5553
1.10750.9613
1.0575[2.55]**[2.98]***[2.76]***[2.35]**[2.18]**[1.25]
0.24270.26170.64890.049-0.0778
0.2947[0.78][0.89][1.35][0.13][-0.21][0.42]-0.1263-0.1515-0.238-0.4069-0.2945-0.379[-1.25][-1.62][-1.48][-2.98]*** [-2.33]**[-1.57]
20.22
27.72
27.63
11.84
7.69
4.55
0.00000.00000.00000.00060.0056

0.03311.15171.18541.65321.4304
1.37761.6069[3.79]***[4.09]***[3.30]***[3.50]***[3.80]***[2.19]**
0.06180.03150.41970.0096-0.1258
0.0891[0.26][0.14][1.00][0.03][-0.43][0.14]-0.2053-0.1931-0.2383-0.4113-0.3306-0.4057[-2.46]**[-2.47]**[-1.74]*[-3.54]*** [-3.26]*** [-1.97]**
27.78
31.65
30.23
24.37
22.5
10.29
0.00000.00000.00000.00000.00000.00141.08161.088
1.61990.9924
1.1061
1.0643[3.95]***[4.28]***[3.60]***[2.75]***[3.38]***[1.67]*
0.0896
0.03340.3833-0.0425-0.28450.0883[0.40][0.16][0.99][-0.15][-1.05][0.16]-0.2119-0.1942-0.2639-0.3237-0.2866-0.3143[-2.76]*** [-2.77]*** [-2.10]**[-3.12]*** [-3.13]*** [-1.75]*
35.14
38.86
35.52
14.23
12.67
6.4
0.00000.00000.00000.00020.00040.01150.76720.78021.00170.99811.00580.5489[3.57]***[3.91]***[2.74]***[3.04]***[3.40]***[0.93]-0.1254-0.24230.0173-0.188-0.3692
0.1258[-0.70][-1.45][0.06][-0.71][-1.48][0.25]-0.1933-0.1729-0.213-0.3131-0.2583-0.2137[-3.15]*** [-3.12]*** [-2.10]**[-3.37]*** [-3.13]*** [-1.31]
17.85
16.26
13.77
11.62
9.11
2.67
0.00000.00010.00020.00070.00260.10280.92281.03
1.5553
1.10750.9613
1.0575[2.55]**[2.22]**[2.76]***[2.35]**[2.18]**[1.25]
0.2427-0.0958
0.64890.049-0.0778
0.2947[0.78][-0.25][1.35][0.13][-0.21][0.42]-0.1263-0.3237-0.238-0.4069-0.2945-0.379[-1.25][-2.47]**[-1.48][-2.98]*** [-2.33]**[-1.57]
20.02
27.72
7.47
11.84
7.69
4.55
0.00000.00000.00640.00060.0056

0.0331

0.671
0.71180.86110.89991.00650.5085[3.14]***[3.59]***[2.38]**[2.75]***[3.42]***[0.86]-0.2595-0.3653-0.265-0.3227-0.4457
0.1216[-1.46][-2.21]**[-0.88][-1.23][-1.80]*[0.24]-0.196-0.18-0.2364-0.3199-0.2731-0.2112[-3.20]*** [-3.24]*** [-2.34]**[-3.46]*** [-3.33]*** [-1.30]
7.35
5.45
5.77
5.81
7.03
2.34
0.00680.01970.01650.01610.00810.12650.72230.73310.9182
0.99390.98050.4886[3.37]***[3.68]***[2.51]**[3.05]***[3.33]***[0.82]-0.1404-0.2541-0.0122-0.2027-0.3767
0.1113[-0.78][-1.52][-0.04][-0.77][-1.52][0.22]-0.1877-0.1658-0.2025-0.3106-0.2515-0.205[-3.06]*** [-2.98]*** [-2.00]**[-3.36]*** [-3.06]*** [-1.26]
14.97
12.78
11.11
11.13
8.25
2.1
0.00010.00040.00090.00090.00410.1478Robust st andard errors are used for est imat ion and t he est imat ed t -values are in parent heses. *, **, and *** are indicat ed t o show p-value t o reject null
hypot hesis wit h p<0.1, p<0.05, p<0.01 respect ively.

- 27 -

8. Policy Implication and for further analysis
Based on the above result, the policy implication is summarized as below:
1. The empirical result of this paper supports that the impact of at least one PTA teacher exists inschool is effective to the test score in Numeracy for all grade pupils, however in other subject, inEnglish and Kiswahili, the impact is not statistically different from zero. Also, the magnitude of
TOT in Numeracy is relatively small and 95% confidence interval includes the negative value of
TOT. Therefore, though the subject of Numeracy is exceptional, this is rather consistent result
from the Sundaraman et al. (2010) which uses the observational data, concluding that it cannot
reject the null hypothesis that the PTA teacher effect to the school outcome is the same asgovernmentally hired teacher effect on test score.
2. On the other hand, after being matched with seven different matching criteria, the PTA teacher
ratio effect on TOT, difference of test score between the treated and matched none treated schools
is statistically significant in the lower grade in all three subjects on average. This result is
intuitively understandable, for younger grade pupils tend to be taught by PTA teachers in Kenya
public primary schools. The largest number of enrolled pupils is the pupil in the first grade.
Therefore, to tackle with the large number of pupils, PTA teachers tend to teach lower grads. If
there should be positive effect of PTA teacher ratio on outcomes, it should be found in the
education outcome of lower grade pupils.
3. Regarding the implication of the finding, although the higher PTA teacher ratio has statisticallysignificant explanatory power to TOT in lower grades, it does not mean that all teachers have to be
replaced with PTA teachers. Rather, this result leads an important implication that government
hired teachers need to put more efforts on teaching, since the result of estimation shows that if
pupils are in lower grades, the ratio of government teacher should be less than PTA teacher, though
they are paid better and “certified” by the national education system. This result is well reflecting
one of the problems that Kenya public primary schools have faced. It is often criticized that the
primary education is so much oriented toward the entrance exam of secondary school and thescore of final exams at the 8th grade for which many governmental primary school teachers have- 28 -

put the highest priority in teaching higher grade pupils in the school (Ito et al. 2011). Results on
the national primary school leaving exam (KCPE) determine what secondary schools, if any,
enroll graduating primary school students, and this is one of the highest concerns of headmaster ofprimary schools (Glewwe et al. 2010). However teaching in younger grade should not be
substituted because of following reasons, therefore the well-designed mechanism for government
teachers to be motivated for making as much efforts as PTA teachers do is necessary.
4. First, it is because of the repetition rate and dropout rate. They are both high in rural primaryschools in Kenya, especially for those pupils who do not attend the nursery schools before
entering the primary schools. This is partly because those pupils without going to nursery schools
could not catch up with school learning in the middle of grades. This is also one of the reasons
why there is a high correlation found between dropout pupils and pupils who had not enrolled innursery schools. In this sense, for those pupils still in the lower grades, it is crucial for them tolearn better, especially where the school is located in disadvantaged area in terms of educational
resources and living infrastructure.
5. Also, it is pointed out that after the FPE policy, number of enrolled pupils who had not been able
to come to school has newly joined schools. Therefore that leads parents with higher preferenceson education decided to leave public primary schools to join private ones, since they worried
about the deteriorated education quality with those pupils who had never been enrolled in schools(Sasaoka 2007). From these facts, it is essential to control the education quality, even after the FPE
has been introduced. Otherwise, the FPE policy is going to create another disparity between
household which could afford to access better quality of education and those who do not.
6. Concerning the background mechanisms why PTA teacher ratio has positive effect on TOT, itcannot be determined solely. However, it is partly because teaching in lower grades does not needhigh pedagogical input; rather other factors are more important. For example, Banerjee et al.
(2010) shows that village volunteer teachers who were only trained by a week training of
pedagogical technique for basic reading skills, those volunteer teachers have effectively increased- 29 -

1.7 percent more likely to read at least letters for those who had not been able to read. This showsthat not only the pedagogical technique, rather other factors effect on raising score in the earlytime of learning.
7. For further study, it requires not only to find the mechanism for PTA teacher to maintain the
incentive to teach, rather it is also essential to search better institutional mechanism forgovernment teachers to have better incentive.

- 30 -

Appendix 1 Chart of Preceding Studies
The Quantitative Analysis of Impact of locally hired contract teachers
AuthorYear

Duflo et al.
(2012)

20052006

Bold et al.
(2012)

Sundaraman et al.
(2010)

2010

20052006

Country(Area)
Kenya,
Western
Province

Kenya,
eight
Provinces

India (APstate)

Data

Outcome

Variable of Interest

Identification
Strategy

Experimental
Data

End line Test
Score for
Grade one forsubject ofMath,
Literacy andTotal score

Treatment Dummy (If PTA
teacher is assigned or not)Ordinary Least
Squares Estimation

End line Test
Score for
Grade one,
two and threepupils for
combined
total scoreEnd line Test
Score from
Grade one to
five inNumeracy,
Language andCombinedscore

Experimental
Data

Experimental
Data

Observational
Data

Bourdon, J.
et al. (2006)

20002001

Niger

Observational
Data(PASEC data)

Outcome istest score ofMath andFrenchControl VariablesTreatment Dummy (If PTA
teacher is assigned or not)Month
(Length)ofTreatment

Ordinary Least
Squares
Estimation

Instrument Variable
Estimation

Treatment Dummy (Ifcontract teacher is assigned
or notOrdinary Least
Squares Estimation

Treatment Dummy (IfContract teacher exist ornot)

Panel School Fixed
Level



Treatment Dummy (if pupil
is taught by Contract
teacher or not)Panel Pupil Fixed
Level



Treatment effect on treatedby estimating the average
difference between classes
taught by contract teacher
and classes by regularteacher, conditioned thatconditional independence
holds true.

Propensity scorematching (classes
taught by contract
teachers and taught
by regular teachers)

ResultNo
control
Variables
School size, Shareof female among
TSC teacher, Girl,
Age, Baseline Test
Score

1)

No
Control
Variables
Baseline Score
SchoolFixed
Effect

1)

2)

2)

3)








Without control Variable, Treatment Dummy and Length ofTreatment become statistically significant with 10 percent.
By adding baseline score, the Treatment Dummy andlength of Treatment becomes positive and 5 percent
significant.
In School Fixed Effect, the Treatment Dummy and Monthsof Treatment are both positive and statistically significant
with 5 percent on outcome.

No
Control
Variables
Household, School
and
Pupil
characteristics

1)

Compared to the baseline score, the Treatment dummy isstatistically significant with 1percent for Numeracy,
Literacy and Combined tests with or without controlled
variable.

SchoolFixed
Level
Household level
andclassroomlevel controls
Pupil Fixed Level

1)

Without any control variables in school level fixed effects,
or with all control variables in school fixed effects, in either
case, the null hypothesis that difference between contract
teacher and regular teacher is zero cannot be rejected1)

Without any control variables, with pupil level fixed
effects, with pupil fixed effects and all control variables,
the null hypothesis that difference between contract teacher
and regular teacher is zero cannot be rejected
In grade 5th, the difference between the score of classes
with a contract teacher with counterfactual outcome of thesame classes is positive and significant for French, Mathand Combined test score. The author concludes that
contract teacher program is positive for grade 5.
On the hand, in the second grade, the difference is notstatistically significant in any of subjects.

1)

2)

31

With control or without control variables, Treatment
Dummy in Math and total score is statistically significant
with 1 percent and in Literacy; it is statistically significant 5
percent.
After one year, the statistical significance fell down to 10
percent in Total score and Literacy and it vanished in Math.

Appendix 2 Descriptive Statistics
Descriptive Statistics for School Level Estimation
Variable

Obs

Mean

Std. Dev.

Min

Max

Dependent Variables
Average Test Score of Kiswahili
Average Test Score of English

2216
2216

3.9582143.926845

0.712659
0.692587

1
1

5
5

Average Test Score of Numeracy

2216

6.319342

1.151761

1

8

Total Number of family (School average)

2216

6.726254

2.3318772

85

Sex of Household Head (School average, 1 is Male)
Type of House(School average, 1 is the lowest quality and 5 is the finest quality)

2216
2216

0.789774
2.283702

0.27704
1.4007820115Possession of telephone (School average, Dummy)

2216

0.651886

0.314935

01

Number of meal in one day (School average)
Age (School average)

2216
2216

2.73166
10.81903

0.409718
1.346922

1
6

3
16

Age square (School average)2216

125.3273

29.3161136

256

Boy (School average, Dummy)
Mother Age (School average)

2216
2216

0.510334
36.25552

0.210786
4.857104

0
20

1
72

Mother Education History (School average, Dummy 1 if graduated of primary)

2216

0.806514

0.321416

01Grade in School (School average)
Parents paid tuition (School average, Dummy)

2216
2216

4.359844
0.433179

1.192257
0.367398

1
0

11.5
1

Supplement for school material is available at classroom (Dummy)

2216

0.762184

0.425842

01Classroom is suitable for learning (Dummy)

2216

0.672383

0.4694501School is fenced (Dummy)
PTA Teacher Dummy (At least one PTA teacher exist in school)

2216
2216

0.671931
0.813177

0.469616
0.389857

00

1
1

PTA Teacher ratio

2216

0.190611

0.152874

00.857143

Log Pupil Teacher Ratio for TSC teacher
Log Pupils per classroom

2216
2216

3.773858
3.6448020.460016
0.400623

2.371578
1.904238

6.539586
6.263398

Electricity Infra is available in village (Dummy)
Road is tarmac in village (Dummy)

2216
2216

0.427347
0.14982

0.494805
0.3569750011Percent of Unemployment (District Level)
Level of Unemployment rate (1 is the lowest and 4 is the highest)

2216

0.06072

0.051004

0.010581

0.403876

Province Dummy (Central Province)

2216
2216

2.374097
0.111913

1.089841
0.315331

10

4
1Province Dummy (Coast Province)

2216

0.081227

0.273246

0

1

Province Dummy (Eastern Province)
Province Dummy (Nairobi Province)

2216
2216

0.192238
0.000903

0.394148
0.030035

0011Province Dummy (North Eastern Province)

2216

0.056408

0.2307601Province Dummy (Nyanza Province)
Province Dummy (Rift Valley Province)

2216
2216

0.102437
0.319495

0.30329
0.4663860011Province Dummy (Western Province)

2216

0.135379

0.342205

0

1

Independent Variables
Household and Individual Characteristics

School Characteristics

Village Characteristics and District Dummy

32

Descriptive Statistics in Common support samples for school average of all grade pupils
VariableObs

All schools
Mean
Std. Dev.

Obs

Treated Schools
Mean
Std. Dev.

Controlled Schools
H0: Diff=0
Obs
Mean
Std. Dev. (P-value)

Dependent Variables
Average Test Score of Kiswahili
Average Test Score of English
Average Test Score of Numeracy

1887
1887
1887

3.965652 0.7120691
3.932993 0.6921375
6.330878 1.152425

1494
1494
1494

3.949017 0.7104351
3.916178 0.6868616
6.331772 1.129941

393
393
393

4.028894 0.7156284
3.996919 0.709092
6.327476 1.235683

0.04780.0396
0.9476

1887
1887
1887
1887
1887
1887
1887
1887
1887
1887
1887
1887

6.660244
0.7865646
2.294128
0.6531852
2.72451
10.81892
125.3029
0.5078172
36.25061
0.7985971
4.355303
0.4344641

1.657696
0.2800994
1.396627
0.3169442
0.4167904
1.3442529.31103
0.2130589
4.769957
0.3283746
1.177131
0.3705932

1494 6.704518 1.657934
1494 0.7891543 0.273554
1494 2.261457 1.379914
1494 0.6509788 0.3136704
1494 2.728774 0.4136835
1494 10.84613 1.329278
1494 125.8955 29.02604
1494 0.5114376 0.2084027
1494 36.26247 4.792234
1494 0.801531 0.3259465
1494 4.361513 1.169916
1494 0.441563 0.3650651

393
393
393
393
393
393
393
393
393
393
393
393

6.491936
0.7767199
2.418326
0.6615729
2.708302
10.71548
123.0502
0.4940544
36.20555
0.787444
4.331696
0.4074774

1.648056
0.3038674
1.453531
0.3293685
0.4285461
1.3966130.30221
0.229661
4.690057
0.3376368
1.205389
0.3902008

0.02370.43370.04750.5556
0.38640.08650.08680.15010.83330.44940.65510.1047

1887
1887
1887
1887
1887
1887
1887

0.7657658
0.6645469
0.6693164
0.7917329
0.180955
3.758036
3.639635

0.4236315
0.4722738
0.470584
0.4061765
0.1526263
0.4572262
0.4082227

1494
1494
1494
1494
1494
1494
1494

0.439351
0.4760851
0.4688933
00.1361614
0.4459378
0.3963924

393 0.8676845 0.3392654
393 0.7073791 0.4555458
393 0.6513995 0.4771347
393
0
0
393
0
0
393 3.593656 0.462822
393 3.627751 0.4507172

0.00000.04330.3964n/a
n/a
0.00000.51671494 0.4056225 0.4911765
1494 0.1419009 0.3490653
1494 0.0580445 0.0461341
1494 2.292503 1.091027

393 0.5114504 0.5005061
393 0.2010178 0.4012722
393 0.0701865 0.054423
393
2.59542 1.130143

0.00020.00390.00000.0000Independent Variables
Household and Individual Characteristics
Total Number of family (School average)
Sex of Household Head (School average, 1 is M ale)Type of House(School average, 1 is the lowest quality and 5 is the finest quality)
Possession of telephone (School average, Dummy)
Number of meal in one day (School average)
Age (School average)
Age square (School average)
Boy (School average, Dummy)
M other Age (School average)
M other Education History (School average, Dummy 1 if graduated of primary)
Grade in School (School average)
Parents paid tuition (School average, Dummy)

School Characteristics
Supplement for school material is available at classroom (Dummy)
Classroom is suitable for learning (Dummy)
School is fenced (Dummy)
PTA Teacher Dummy (At least one PTA teacher exist in school)
PTA Teacher ratio
Log Pupil Teacher Ratio for TSC teacher
Log Pupils per classroom

0.7389558
0.6532798
0.6740295
10.2285557
3.801277
3.642761

Village Characteristics and District Dummy
Electricity Infra is available in village (Dummy)
Road is tarmac in village (Dummy)

Percent of Unemployment (District Level)
Level of Unemployment rate (1 is the lowest and 4 is the highest)

1887 0.427663 0.4948708
1887 0.154213 0.3612486
1887 0.0605733 0.0482161
1887 2.355591
1.1058533

Descriptive Statistics in Common support samples for Standard grade below three
VariableObs

All schools
Mean
Std. Dev.

Obs

Treated Schools
Mean
Std. Dev.

Controlled Schools
H0: Diff=0
Obs
Mean
Std. Dev.
(P-value)

Dependent Variables
Average Test Score of Kiswahili
Average Test Score of English
Average Test Score of Numeracy

1720
1720
1720

2.952054 0.8969595
2.919097 0.8275752
4.694302 1.516378

1371
1371
1371

2.91174 0.8914024
2.882853 0.8144723
4.671458 1.503788

349
349
349

3.110423 0.9024505
3.061475 0.8637394
4.78404 1.563829

0.00020.00030.2157

1720
1720
1720
1720
1720
1720
1720
1720
1720
1720
1720
1720

6.596458
0.7917327
2.197293
0.6367892
2.715625
8.326783
72.91323
0.5201871
34.25272
0.7983608
2.050793
0.2660371

1.780762
0.3022176
1.434143
0.3526677
0.4447905
1.209341
22.64777
0.2934888
5.504335
0.3398301
0.4647443
0.3787845

1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

6.630485
0.7955257
2.169003
0.6334648
2.720163
8.33712573.03283
0.52517634.32356
0.7993519
2.056746
0.2643525

1.787954
0.2928241
1.427705
0.3499144
0.4429728
1.195061
22.29828
0.2913417
5.557959
0.3401934
0.449175
0.3741058

349
349
349
349
349
349
349
349
349
349
349
349

6.462787
0.7768321
2.308429
0.6498489
2.69788.286156
72.44339
0.5005891
33.97441
0.7944675
2.027408
0.2726548

1.748346
0.3366352
1.455908
0.3635006
0.4520616
1.264831
23.9991
0.3014022
5.286964
0.3388582
0.5214757
0.3971173

0.11630.30240.10490.43860.40190.4822
0.66440.16240.29020.8106
0.29250.7148

1720
1720
1720
1720
1720
1720
1720

0.7622093
0.6616279
0.6668605
0.797093
0.1847168
3.76627
3.635846

0.4258541
0.4732934
0.471473
0.4022808
0.1533508
0.458448
0.4045139

1371
1371
1371
1371
1371
1371
1371

0.7374179
0.6491612
0.6725018
10.2317381
3.809041
3.6392050.4401977
0.4774067
0.4694719
00.1363912
0.4461851
0.3927561

349 0.8595989 0.3479015
349 0.7106017 0.4541342
349 0.6446991 0.4792915
349
0
0
349
0
0
349 3.598252 0.4679027
349 3.622648 0.4480921

0.00000.03030.3255n/an/a
0.00000.495

1371 0.3924143 0.4884663
1371 0.134938 0.341782
1371 0.058783 0.0472281
1371 2.307805 1.084767

349 0.5014327 0.5007158
349 0.2063037 0.4052321
349 0.0693809 0.0540972
349 2.573066 1.133841

0.00020.00080.00030.0001

Independent Variables
Household and Individual Characteristics
Total Number of family (School average)
Sex of Household Head (School average, 1 is M ale)Type of House(School average, 1 is the lowest quality and 5 is the finest quality)
Possession of telephone (School average, Dummy)
Number of meal in one day (School average)
Age (School average)
Age square (School average)
Boy (School average, Dummy)
M other Age (School average)
M other Education History (School average, Dummy 1 if graduated of primary)
Grade in School (School average)
Parents paid tuition (School average, Dummy)

School Characteristics
Supplement for school material is available at classroom (Dummy)
Classroom is suitable for learning (Dummy)
School is fenced (Dummy)
PTA Teacher Dummy (At least one PTA teacher exist in school)
PTA Teacher ratio
Log Pupil Teacher Ratio for TSC teacher
Log Pupils per classroom

Village Characteristics and District Dummy
Electricity Infra is available in village (Dummy)
Road is tarmac in village (Dummy)

Percent of Unemployment (District Level)
Level of Unemployment rate (1 is the lowest and 4 is the highest)

1720 0.4145349 0.4927848
1720 0.1494186 0.3566043
1720 0.0609334
0.048871720 2.361628 1.099756

34

Percent

2
0

4

30
20
10

0

.2

.4
.6
psmatch2: Propensity Score

.8

1

0

Percent

6

40

8

50

10

Appendix 3 Figures

0

200

400
ptr_tsc

600

800

Figure 8 Propensity Score Distribution for ControlledGroup for Kiswahili for all grades

0

0

5

5

Percent

Percent

10

10

15

15

Figure 4 Pupil TSC teacher ratio

2

3

4

5

6

.2

7

.4

lnptrtsc.6
psmatch2: Propensity Score.81

Figure 9 Propensity Score Distribution for
Treated Group for Kiswahili for all grades

0

10

2

4

6

Percent

20

Percent

30

8

40

10

Figure 5 Log of Pupil TSC teacher ratio

.2

100

200

300
classsize

400

.4

.6

.8

1

psmatch2: Propensity Score
Figure 10 Propensity
Score Distribution forControlled Group for English grade below 3

0
0

500

Percent

5

10

0

5

.2

0

Percent

10

15

20

15

Figure 6 Pupil per class2

3

4lnclasssize

5

6

.4
.6
psmatch2: Propensity Score.81

Figure 11 Propensity Score Distribution for
Treated Group for English grade below 3

Figure 7 Log of Pupil per class size

35Appendix 4 Probit Model Estimation Result
Probit Estimation Reuslt
Independent Variable is PTA Teacher Dummy (0 or 1)
All grades
Electricity Infra is available in village (Dummy )-0.2191[-2.50]**
The road is tarmac in village (Dummy )-0.1389[-1.32]
Sup p lement for school material is available atclassroom (Dummy )Classroom is suitable for learning (Dummy )School is fenced (Dummy )Log Pup il Teacher Ratio for TSC teacher
Log Pup ils p er classroom
Total Number of family (School average)
Sex of Household Head (School average, 1 is M ale)

Std <=3-0.23[-2.52]**-0.2117[-1.90]*-0.3598-0.3285[-3.56]***-0.0343[-0.43]-0.0652[-0.73]0.7409[4.21]***-0.3049[-2.36]**-0.0093[-0.37]0.1371[0.95][-3.18]***-0.0704[-0.84]-0.0033[-0.04]0.7768[4.21]***-0.3334[-2.36]**-0.009[-0.40]0.1969[1.37]-0.0429-0.0001[-1.12]0.1101[0.74]
0.1283[1.24]
0.2754[1.14]-0.0122[-1.10]0.1857[1.14]-0.0054[-0.64]-0.1116[-0.58]0.0306[0.66]
0.0966[0.79]-2.727[-1.69]*[-0.00]0.0598[0.45]
0.1345[1.32]
0.2668[1.17]-0.015[-1.28]0.1056[0.81]
0.009[1.20]-0.1445[-0.76]
0.0566[0.63]-0.0277[-0.25]-2.8467[-1.98]**

Ty p e of House(School average, 1 is lowest quality
and 5 is the finest quality )Possession of telep hone (School average)
Number of meal in one day (School average)
Age (School average)
Age square (School average)
Boy (School average)
M other Age (School average)
M other Education History (School average)
Grade in School (School average)
Parents p aid tuition (School average)

Constant

Wald chi2(121) =Prob > chi2=
Pseudo R2=
N

313.790.00000.1887
1887

Wald chi2(121) =Prob > chi2=
Pseudo R2=

301.930.00000.19841720

Robust st andard errors are used for est imat ion and t he est imat ed t -values are in parent heses. *, **, and *** areindicat ed t o show p-value t o reject null hypot hesis wit h p<0.1, p<0.05, p<0.01 respect ively.

District Dummy is excluded from table, because it becomes long.

36

Table 7

Appendix 5 Regression Result
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

0.12050.1215School is fenced (Dummy)
Total Number of famly (School
average)0.03940.0402-0.0256[-0.41]0.068

0.06690.00870.1343[1.25]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.2084[1.99]**

Number of meal in one day(School average)

0.0795[1.19]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.0001[0.00]

0.0037[0.25]

Constant
R-squared
Adj-R-squaredN

0.0274-0.0002[-0.01]0.1018[1.07]

0.1051[1.11]

0.075[3.99]***
0.0807[0.83]-0.0276

0.02660.0781[4.13]***
0.0855[0.89]
0.0306

0.11710.1162-0.0875[-1.52]0.00010.0036

0.0579[0.95]

0.04710.2324[3.21]***
0.1185-0.0138-0.0153-0.056

0.0578-0.0151[-0.25]0.05190.0112[0.21]

0.0176[0.32]

0.00920.0116-0.0773[-1.40]0.0246[1.09][0.99][0.20][0.25][0.53]-0.0523-0.0715-0.1015-0.1086-0.1142[-0.93][-1.28][-2.01]** [-2.16]** [-2.18]**-0.005-0.0109[-0.32][-0.66]0.21460.1065[2.21]**[1.05]

0.05780.1166[2.12]**[5.97]***

0.09150.2289[0.92][2.31]**

0.0764-0.0193[-1.22]-0.026-0.0244[-1.52]0.0759[0.87]

0.0802[0.92]

0.0822[4.52]***[1.17]-0.0275[-1.70]*[4.71]***
0.1134[1.24]

0.013

0.01820.071[2.76]***
0.1058[1.16]
0.0571[0.22][0.31][0.90]
0.95050.94880.9112[5.34]*** [5.29]*** [5.19]***-0.0395-0.0395-0.0374[-5.02]*** [-4.99]*** [-4.74]***-0.0837-0.075-0.0909[-0.68][-0.60][-0.77]-0.0025-0.00220.0039[-0.48][-0.41][0.75]
0.00150.00610.0321[0.02][0.06][0.25]
0.262
0.26480.25[7.50]*** [7.48]*** [7.33]***0.20920.1968[2.55]**[2.80]***

0.1969[2.81]***

0.263

0.15350.10410.1088-0.0391

0.1949[2.49]**
0.2832-0.1095-0.1112-0.1658[1.17][1.22][-0.44][-1.33][-1.35][-1.85]*0.02990.0333-0.0616-0.0463-0.0428-0.1029[0.26][0.29][-0.52][-0.43][-0.40][-0.86]-0.2252-0.2328-0.1426-0.0847-0.0926-0.3418[-5.73]*** [-5.86]*** [-3.35]*** [-1.92]*[-2.06]** [-1.95]*-0.0548[-0.56]0.143-0.1382[-1.42]-0.0766[-0.84]0.1505-0.0698[-0.77]0.0875-0.1848[-1.90]*0.09

0.1052[1.59][1.69]*[1.08][1.11][1.27]-0.0804-0.1153-0.155-0.1626-0.1833[-0.87][-1.26][-1.82]*[-1.91]*[-2.01]**0.0139[0.53]

0.2059[2.25]**

0.08620.1071

0.0682[0.99][0.00][0.04][-0.20]0.27190.27410.2693[7.33]*** [7.32]*** [7.26]***0.23230.0237[2.18]**[2.15]**[0.44][-0.28][-0.32][-1.08]0.05390.0523-0.0172-0.0101-0.0068-0.0816[0.76][0.74][-0.24][-0.16][-0.11][-1.25]-0.0905-0.0967-0.0451-0.0157-0.023-0.2613[-3.86]*** [-4.07]*** [-1.77]*[-0.62][-0.89][-2.50]**[0.45][0.52][1.17]
1.08031.079
1.0423[6.03]*** [6.00]*** [5.87]***-0.0459-0.046-0.0445[-5.81]*** [-5.79]*** [-5.60]***0.067
0.07370.092[0.52][0.57][0.72]-0.0049-0.0046
0.0024[-0.91][-0.86][0.45][3.21]***
Log Pupil Teacher Ratio for TSC
teacher

0.005[0.09]

0.0256

0.1124[5.59]***

Possession of telepohne (School
average)-0.0032[1.23][1.22][0.52][0.56][0.95]-0.0647-0.0811-0.1153-0.1207-0.1222[-1.11][-1.40][-2.19]** [-2.30]** [-2.22]**[0.54]
Sex if Household Head (School
average, 1 is Male)-0.002[2.17]**[2.18]**[0.71][-0.04][-0.06][-0.50]0.04390.0433-0.0171-0.0156-0.0131-0.0796[0.61][0.60][-0.23][-0.24][-0.20][-1.16]-0.0887-0.0957-0.0463-0.0147-0.0204-0.1626[-3.65]*** [-3.89]*** [-1.75]*[-0.55][-0.75][-1.80]*[0.64]Classroom is suitable for learning(Dummy)TOT (Nearest One to One Matching Estimation for school average) regressed on PTA teacher ratio

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.42550.63720.65030.86271.22191.06040.27220.40060.614
0.63320.84281.203
0.99380.30470.9594
1.28841.2814
1.69722.23852.01430.8297[2.01]**[2.95]*** [2.98]*** [3.82]*** [6.12]*** [4.72]*** [1.02][1.97]**[2.98]*** [3.04]*** [3.92]*** [6.36]*** [4.62]*** [1.22][2.91]*** [3.84]*** [3.78]*** [4.95]*** [7.12]*** [5.74]*** [1.97]**0.29[1.82]*
0.1368[4.15]***
0.6257[3.93]***
0.0866[0.82]-0.0002[-0.01]0.2525[1.76]*
0.0873[2.77]***
0.3858[2.57]**
0.0059-0.0056[-0.23]0.2571[1.80]*
0.0916[2.88]***
0.3926[2.61]***
0.0115-0.02[-0.77]0.4303[2.74]***
0.0673[1.46]
0.3508[2.26]**
0.1002[0.06][0.12][0.94]
1.9581
1.9563
1.9225[6.74]*** [6.70]*** [6.56]***-0.0826-0.0827-0.0805[-6.35]*** [-6.34]*** [-6.10]***0.01150.02080.0203[0.06][0.10][0.10]
0.00340.00380.0103[0.37][0.42][1.12]
0.13530.1402

0.032[0.78][0.80][0.14]
0.33290.33590.3434[5.64]*** [5.64]*** [5.60]***0.3509[2.99]***

0.3511[2.99]***
0.16450.2738[2.05]**
0.3663[1.79]*[3.45]***[2.45]**[4.01]***[1.52][2.96]***
0.00180.10160.0838-0.7465-7.5625-7.9666-8.17440.01710.12070.0857-0.5717-6.727-7.2506-7.2790.07860.47330.4912-0.9323-13.2135-13.7746-14.5351[0.03][1.19][0.74][-2.79]*** [-7.82]*** [-8.17]*** [-7.95]*** [0.34][1.47][0.79][-2.11]** [-6.98]*** [-7.40]*** [-7.03]*** [0.96][3.63]*** [2.82]*** [-2.31]** [-8.52]*** [-8.73]*** [-8.32]***0.00330.01810.0201
0.05250.23750.23940.35940.00310.01930.02130.0586
0.24920.25270.37850.00640.03120.03330.06790.22550.227
0.32680.00270.01550.01550.04480.22770.22910.30290.00250.01670.01670.051
0.23950.24250.32370.00570.02860.02870.06030.2156
0.21650.2674
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

37

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 8 TOT (Nearest One to One Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio

PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.03960.336
0.39660.52010.56950.88530.955-0.04720.22580.27070.37450.41910.65250.64570.29830.80360.8696
1.0975
1.18391.61111.1477[0.18][1.49][1.75]*[2.24]**[2.42]**[3.35]*** [2.95]*** [-0.23][1.03][1.23][1.66]*[1.84]*[2.59]*** [2.11]**[0.75][1.92]*[2.05]**[2.54]**[2.69]*** [3.35]*** [1.97]**
0.34920.33720.1869[2.62]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.27560.067

0.1371[1.90]*
0.0587-0.0408

0.1226[0.97]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0657[2.47]**

Possession of telepohne (School
average)

0.1633[1.33]

Number of meal in one day(School average)-0.0112[-0.14]Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)0.1297[1.79]*
0.0459-0.039[-1.92]*0.1441[1.14]
0.0529[1.93]*
0.1406[1.10]

Constant
R-squared
Adj-R-squaredN

0.15150.1213[1.68]*
0.0445-0.0094-0.0312[-1.54]0.1368[1.08]
0.0472[1.73]*
0.1269[1.00]-0.01760.311

0.30570.0503[0.63]-0.1615-0.16610.156[2.31]**

0.05210.1584[1.57]-0.23770.22110.225

0.11930.062

0.1069[1.56]
0.04870.1004[1.46]

0.0942[1.37]

0.03530.03430.0259[0.34]
0.0439[0.99][0.78][0.57][0.56][0.68]-0.0601-0.0816-0.0977-0.0896-0.0445[-0.88][-1.19][-1.42][-1.31][-0.60]-0.0323-0.0608[-1.52]-0.0607-0.0549-0.0531[-3.21]*** [-3.11]*** [-2.81]*** [-2.51]**

0.14280.0515[1.04][0.43]

0.09020.0545[2.22]**[2.19]**

0.13770.2109[1.00][1.81]*-0.0303-0.0434[-0.56]-0.1159

0.0784[0.65]

0.0729[0.60]

0.0454[1.77]*

0.0411[1.60]

0.1968[1.61]

0.1867[1.53]-0.0378-0.04390.1164[0.89]-0.1943

0.1576[1.21]-0.0418-0.0833[-1.44][-1.47][-0.47]0.11690.11080.0867[2.55]**[2.43]**[1.81]*

0.13910.1266[1.23][1.29]

0.1252[1.29]-0.1948-0.1756

0.35690.33760.23

0.1349[1.25]-0.1155

0.19520.20240.1177[2.93]*** [2.76]*** [1.83]*[1.55][1.60][0.84]
0.086
0.07870.01280.03780.0285-0.0693[0.50][0.46][0.08][0.22][0.17][-0.37]-0.1685-0.168-0.1191-0.1176-0.1032
0.283[-3.26]*** [-3.13]*** [-2.03]** [-1.83]*[-1.60][1.23]
0.1352[1.09]
0.12050.089[0.71]

0.1271[1.00]

0.11120.1157[0.91]

0.09250.0922[0.65]

0.0906

0.0528[1.05][0.97][0.80][0.79][0.43]
0.04510.00830.00820.0231-0.035[0.36][0.07][0.07][0.18][-0.25]-0.0837[-2.39]**0.1521[0.68]

0.0846[2.21]**[-0.47][-0.54][-0.47]0.59320.59080.626[2.47]**[2.48]**[2.61]***-0.0288-0.0284-0.0293[-2.56]** [-2.54]** [-2.60]***0.11940.11270.0862[0.71][0.67][0.49]
0.00080.0005-0.0052[0.11][0.07][-0.66]-0.1908[-1.16][-1.20][-0.61]0.12570.11750.1086[2.65]*** [2.48]**[2.16]**
0.16030.2393[4.58]*** [4.45]*** [3.39]*** [3.11]*** [3.17]*** [1.63]-0.0722-0.0751-0.1247-0.1189-0.124-0.1967[-0.72][-0.76][-1.27][-1.20][-1.25][-1.89]*-0.0165-0.0251
0.00610.00270.01050.0013[-0.58][-0.85][0.19][0.08][0.30][0.02][-0.11][-0.21][-0.32]0.56520.56190.5048[2.30]**[2.30]**[2.04]**-0.0279-0.0274-0.0251[-2.43]** [-2.39]** [-2.17]**0.23520.22620.2459[1.31][1.26][1.30]-0.0005-0.0009-0.0064[-0.06][-0.11][-0.77][1.58]
Log Pupil Teacher Ratio for TSC
teacher

0.2605[1.02][0.89][0.70][0.68][0.75]-0.0221-0.0436-0.0629-0.052-0.0053[-0.30][-0.60][-0.86][-0.71][-0.07][-2.05]**
Sex if Household Head (School
average, 1 is Male)

0.2552[4.86]*** [4.66]*** [3.68]*** [3.39]*** [3.47]*** [1.92]*-0.0535-0.0588-0.1032-0.1013-0.1082-0.149[-0.53][-0.58][-1.03][-1.01][-1.08][-1.41]-0.0005-0.0060.02990.0321
0.04280.0142[-0.02][-0.20][0.87][0.86][1.14][0.13]-0.0926[-2.57]**0.2199[0.98]

0.037[0.84]
0.6095[2.89]***-0.1741[-1.30]-0.082[-2.28]**0.21[0.93]

0.044[0.97]-0.15450.2253[0.88]

0.0362[0.80]

0.5236[2.38]**-0.0906[-2.30]**0.1064[1.64]

0.505[2.29]**-0.1656

0.4688[1.96]**-0.2119[-1.11][-1.19][-1.29]1.77871.7744
1.7799[3.96]*** [3.96]*** [3.82]***-0.0796-0.079-0.0791[-3.82]*** [-3.80]*** [-3.64]***-0.0257-0.0378-0.0249[-0.08][-0.12][-0.08]0.01340.01290.0059[0.97][0.94][0.40]-0.1105-0.1168-0.109[-0.45][-0.48][-0.33]0.029
0.01790.0474[0.34][0.21][0.53]
0.1092[0.62]

0.1066[0.61]-0.32140.0553[0.29]-0.1719[-2.88]*** [-2.04]**[-2.23]** [-1.24][-2.27]** [-1.03]-0.0998-0.297-0.4593-0.5229-3.6863-2.8517-2.74250.0195-0.1179-0.2209
0.0089-3.2675-2.651-3.2667-0.04240.0778-0.13850.2604-9.5827-8.4539-9.535[-1.58][-2.92]*** [-3.38]*** [-1.56][-2.98]*** [-2.23]** [-2.05]** [0.33][-1.20][-1.67]*[0.03][-2.67]*** [-2.11]** [-2.51]** [-0.39][0.44][-0.59][0.47][-4.11]*** [-3.53]*** [-3.63]***00.01870.02440.03580.0512
0.05690.170100.01730.02220.0377
0.05340.05680.19020.00040.01830.02030.03280.04950.053
0.1364-0.00070.01580.01940.02730.03780.04290.0897-0.00070.01440.01720.02920.0401
0.04290.1117-0.0003
0.01540.01520.02430.0361
0.039
0.0527
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

38

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 9 TOT(Nearest One to two Matching Estimation for school average) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.27930.46950.48190.64341.01970.94720.30610.21220.407
0.42220.58110.957
0.84440.24510.7843
1.0621
1.04461.38671.93781.811
0.6752[1.50][2.48]**[2.54]**[3.31]*** [6.22]*** [5.35]*** [1.47][1.16][2.20]**[2.27]**[3.07]*** [6.01]*** [4.89]*** [1.21][2.59]*** [3.46]*** [3.39]*** [4.47]*** [7.05]*** [5.99]*** [1.88]*
0.10880.1038-0.0066[-0.12]

Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)0.03530.0701-0.0624[-1.17]0.0681-0.0015

0.1084[1.16]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0903[5.24]***

Possession of telepohne (School
average)

0.1428[1.55]

Number of meal in one day(School average)

0.0996[1.68]*

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)-0.0378[-0.82]0.0287-0.0063[-0.52]0.0654[0.83]
0.0524[3.39]***
0.0123[0.15]

Constant
R-squared
Adj-R-squaredN-0.0499-0.0356[-0.77]0.02950.0395-0.008[-0.65]0.0669[0.85]
0.0538[3.46]***
0.0145[0.18]
0.04130.11250.1066-0.1109[-2.40]**0.04330.04490.0065[0.12]

0.04530.1916[3.10]***
0.0531-0.0111-0.0119-0.0679

0.0531-0.0572[-1.09]0.0456-0.0316[-0.69]-0.0282[-0.62]0.00420.0054-0.1166[-2.58]***0.0116[1.14][0.99][0.11][0.14][0.30]
0.023
0.0029-0.0289-0.0328-0.0328[0.48][0.06][-0.70][-0.79][-0.75]-0.011-0.0246[-0.87][-1.69]*0.17180.0752[2.12]**[0.85]

0.046

0.0939[2.04]**[5.53]***-0.00190.1714[-0.02][1.95]*

0.10510.0895[1.47]-0.0128-0.0325[-2.45]**-0.0352

0.0365[0.50]

0.0388[0.53]

0.0584[3.87]***

0.0606[4.00]***

0.0457[0.59]-0.0357[-2.62]*** [-2.63]***0.0491[0.64]

0.02880.03150.1588[2.04]**
0.0576[2.70]***
0.0101[0.13]

0.03740.083

0.0446[0.42][0.44][0.39]
0.27290.27440.2571[9.00]*** [8.98]*** [8.52]***0.17130.1732[2.60]***[2.90]***

0.1733[2.90]***

0.20710.08260.07880.0783-0.0568

0.1714[2.71]***
0.2343-0.126-0.1269-0.1979[1.03][1.01][-0.73][-1.81]*[-1.82]*[-2.69]***0.0061
0.011-0.0772-0.0628-0.0608-0.1189[0.06][0.11][-0.77][-0.72][-0.69][-1.24]-0.2042-0.2019-0.1214-0.0622-0.06660.5129[-5.98]*** [-5.83]*** [-3.29]*** [-1.68]*[-1.77]*[4.43]***-0.1354[-1.58]-0.2105[-2.47]**0.12810.13-0.1501[-1.93]*0.0685-0.1463[-1.88]*0.0699-0.251[-3.13]***0.0815[1.63][1.66]*[1.01][1.03][1.18]
0.0199-0.0157-0.0564-0.0607-0.09[0.25][-0.20][-0.79][-0.85][-1.17]-0.0164[-0.70]0.2474[1.76]*
0.1116[3.91]***
0.5473[3.82]***[0.56][0.62][1.48]
0.88090.88
0.8272[5.86]*** [5.82]*** [5.62]***-0.0364-0.0365-0.0334[-5.56]*** [-5.54]*** [-5.16]***-0.106-0.1013-0.091[-1.01][-0.97][-0.92]-0.004-0.0038-0.0014[-0.85][-0.81][-0.30]0.0349[0.50][0.51][-0.11]0.28210.28310.276[8.47]*** [8.45]*** [8.33]***0.19150.0257[2.40]**[2.26]**[0.54][-0.27][-0.29][-1.63]0.04390.0429-0.0186-0.0125-0.0107-0.0673[0.70][0.69][-0.30][-0.24][-0.20][-1.25]-0.0791-0.0781-0.03160.0006-0.0033
0.1625[-3.89]*** [-3.79]*** [-1.43][0.03][-0.16][2.45]**[0.76][0.80][1.82]*
0.96480.96420.9096[6.31]*** [6.29]*** [6.06]***-0.0408-0.0408-0.0383[-6.18]*** [-6.16]*** [-5.84]***
0.006
0.009
0.0605[0.05][0.08][0.56]-0.0066-0.0065-0.003[-1.43][-1.41][-0.65][3.10]***
Log Pupil Teacher Ratio for TSC
teacher-0.0049[1.46][1.43][0.71][0.73][1.14]
0.0143-0.0021-0.0378-0.0402-0.0385[0.29][-0.04][-0.89][-0.95][-0.85][-0.11]
Sex if Household Head (School
average, 1 is Male)-0.0044[2.28]**[2.16]**[0.72][-0.10][-0.11][-1.13]0.03770.0374-0.0135-0.0125-0.0113-0.0534[0.60][0.59][-0.21][-0.23][-0.21][-0.97]-0.0797-0.0794-0.0359-0.0015-0.0040.2731[-3.84]*** [-3.78]*** [-1.57][-0.07][-0.18][3.93]***

0.0646[0.68]-0.0298[-1.44]0.2042[1.65]*
0.0616[2.34]**
0.3046[2.32]**-0.0193-0.0328[-1.57]0.2068[1.67]*-0.0417[-1.92]*0.3722[2.79]***

0.0641[2.42]**
0.3084[2.35]**-0.01620.04[1.06]
0.2457[1.84]*
0.0865[-0.23][-0.19][0.93]
1.88591.88491.8423[7.04]*** [7.01]*** [6.98]***-0.0797-0.0798-0.0772[-6.79]*** [-6.77]*** [-6.67]***0.01360.01890.0711[0.08][0.11][0.42]
0.00350.00380.0065[0.45][0.47][0.82]
0.17170.1745-0.016[1.14][1.16][-0.08]0.3401
0.34180.3443[6.18]*** [6.19]*** [6.07]***0.3106[3.08]***

0.3107[3.08]***
0.09310.248[2.35]**
0.3495[0.98][3.38]***[1.58][4.03]***[1.04][3.34]***-0.0008
0.089
0.0369-0.6552-6.8137-6.995-7.6337
0.02310.108
0.0497-0.4492-6.2176-6.4992-6.8580.05360.42540.4267-0.5608-12.4633-12.7808-14.3098[-0.02][1.22][0.39][-2.79]*** [-8.07]*** [-8.24]*** [-8.68]*** [0.52][1.53][0.54][-1.90]*[-7.45]*** [-7.70]*** [-7.94]*** [0.74][3.76]*** [2.85]*** [-1.55][-8.59]*** [-8.70]*** [-9.42]***0.002
0.01840.02
0.04920.297
0.29750.42770.00120.01860.01980.05570.31250.31380.45070.00570.03220.03560.069
0.27280.2734
0.39810.00130.01570.01540.04150.28790.28790.37720.00050.016
0.01520.04810.30360.30450.40220.005
0.0296
0.0311
0.06150.26340.2635
0.345
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

39

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 10 TOT (Nearest One to two Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio

PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.29980.5682
0.63360.75750.8264
1.05670.92380.213
0.46520.51880.61320.68030.8242
0.6316
0.46370.89230.96751.23231.303
1.66251.0439[1.55][2.87]*** [3.19]*** [3.78]*** [4.07]*** [4.63]*** [3.28]*** [1.21][2.58]*** [2.85]*** [3.37]*** [3.68]*** [4.01]*** [2.54]**[1.33][2.44]**[2.62]*** [3.28]*** [3.42]*** [3.96]*** [2.07]**0.29850.27980.1887[3.03]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)0.2221

0.02260.1352[2.16]**
0.0145-0.0333

Sex if Household Head (School
average, 1 is Male)

0.14[1.24]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.079

0.1177[1.11]-0.0279[-0.39]Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.1356[2.15]**
0.0046-0.0333[-1.88]*0.1504[1.36][3.47]***

Number of meal in one day(School average)

0.0674[2.88]***
0.0719[0.65]

Constant
R-squared
Adj-R-squaredN

0.08920.1295[2.06]**
0.0036-0.0395-0.0276[-1.57]0.1451[1.31]

0.26970.25530.0666[0.97]

0.1688[3.06]***

0.0021[2.70]***
0.0619[0.56]

0.0034-0.0304-0.1361-0.1395

0.233[2.69]***-0.1733

0.17390.0674-0.00960.1198[2.15]**

0.116[2.08]**-0.0216-0.02220.0448[0.73]-0.0211-0.0563-0.0527-0.0491[-3.33]*** [-3.45]*** [-3.24]*** [-2.81]***0.16250.0725[0.71]

0.10830.0654[3.11]***[3.22]***

0.06880.1404[1.46]-0.0948-0.0509[-0.78]-0.18310.0938[0.93]

0.0904[0.90]

0.0584[2.81]***

0.0558[2.68]***

0.1038[1.03]

0.0976[0.97]-0.056-0.0598

0.1531[1.45]
0.1014[3.33]***
0.0435[0.41]-0.0911[-0.83][-0.88][-1.26]
0.77170.77020.7469[3.75]*** [3.76]*** [3.66]***-0.0361-0.0358-0.0344[-3.75]*** [-3.74]*** [-3.62]***-0.126-0.1301-0.1638[-0.87][-0.90][-1.09]0.00140.0012-0.0031[0.22][0.19][-0.49]-0.1591[-1.12][-1.15][-1.10]0.1154
0.10940.1133[2.73]*** [2.59]*** [2.49]**
0.23430.1173[2.11]**-0.0534[-1.69]*[0.58]-0.0455

0.1715[0.07][-0.19][-0.42][-0.43][-0.40]0.03270.014-0.00310.00190.0196[0.58][0.25][-0.06][0.03][0.32][1.36]

0.06330.1963[4.87]*** [4.57]*** [3.43]*** [3.00]*** [3.04]*** [1.13]
0.05350.04740.00070.01560.0124-0.0446[0.64][0.57][0.01][0.19][0.15][-0.53]0.00220.003
0.03120.03620.041-0.035[0.09][0.13][1.16][1.26][1.42][-0.41][-0.54][-0.61][-1.17]0.73850.73610.6713[3.36]*** [3.37]*** [3.04]***-0.0351-0.0347-0.0324[-3.42]*** [-3.40]*** [-3.18]***-0.0552-0.0617-0.0473[-0.34][-0.38][-0.28]-0.0029-0.0032-0.0067[-0.43][-0.47][-0.96][2.69]***
Log Pupil Teacher Ratio for TSC
teacher

0.1976[0.39][0.25][0.08][0.06][0.03]
0.0509
0.032
0.01
0.018
0.0489[0.81][0.51][0.16][0.29][0.72][-1.89]*Possession of telepohne (School
average)

0.1937[4.85]*** [4.50]*** [3.47]*** [3.03]*** [3.09]*** [1.31]
0.05290.04530.00190.01320.0082-0.0198[0.61][0.53][0.02][0.15][0.10][-0.22]0.01180.01370.04720.06
0.06780.0585[0.45][0.52][1.58][1.85]*[2.08]**[0.99]-0.1612-0.1668[-1.44][-1.47][-1.13]0.10340.09970.0835[2.68]*** [2.60]*** [2.11]**0.19320.1751[2.01]**[2.16]**

0.1742[2.16]**-0.1096-0.1082

0.1606[1.81]*-0.0246

0.27720.24560.13770.08840.0944-0.0136[2.59]*** [2.28]**[1.25][0.80][0.86][-0.11]
0.23920.2276
0.16220.20090.19310.1248[1.64][1.57][1.13][1.41][1.36][0.79]-0.1197-0.1052-0.0444-0.0395-0.0274
0.3598[-2.66]*** [-2.24]** [-0.87][-0.72][-0.49][1.69]*
0.1506[1.37]

0.0937[0.84]

0.02

0.1368[1.23]

0.01580.00370.1272[1.15]

0.0774[0.62]

0.0021-0.0378[0.20][0.16][0.04][0.02][-0.36]0.18060.14
0.14110.15360.1159[1.63][1.26][1.27][1.38][0.93]-0.0654[-2.12]**0.2912[1.53]-0.0751[-2.37]**0.3648[1.92]*

0.066[1.70]*
0.5291[2.85]***-0.1331[-1.15]0.0776[1.95]*-0.0662[-2.09]**0.3564[1.87]*
0.0711[1.79]*

0.4255[2.22]**-0.1170.41[2.14]**-0.1264-0.0714[-2.07]**0.3956[1.85]*
0.1431[2.54]**
0.3204[1.57]-0.2074[-0.98][-1.06][-1.46]2.10482.10112.0189[5.17]*** [5.18]*** [4.91]***-0.0948-0.0943-0.0906[-5.04]*** [-5.02]*** [-4.75]***-0.3843-0.3945-0.4202[-1.35][-1.39][-1.46]0.01650.01610.0109[1.33][1.30][0.82]-0.1503-0.1555-0.2657[-0.72][-0.75][-0.94]-0.0002-0.00960.0308[-0.00][-0.13][0.39]
0.1988[1.30]

0.1967[1.29]-0.2705

0.1556[0.91]-0.0955[-2.41]** [-1.33][-1.62][-0.32][-2.14]** [-0.65]-0.1017-0.3153-0.5147-0.5932-4.4694-3.8607-3.5445-0.0362-0.2128-0.3693-0.159-4.3013-3.9212-3.9696-0.0050.0309-0.2516-0.2383-11.5156-10.5657-11.0663[-1.85]*[-3.60]*** [-4.55]*** [-2.05]** [-4.01]*** [-3.36]*** [-2.98]*** [-0.74][-2.68]*** [-3.53]*** [-0.62][-4.08]*** [-3.61]*** [-3.49]*** [-0.05][0.20][-1.23][-0.49][-5.33]*** [-4.80]*** [-4.61]***0.00150.02080.028
0.04350.06920.07320.20250.001
0.02080.02730.04720.07720.079
0.22530.00120.017
0.0207
0.0361
0.0656
0.06880.16680.00080.018
0.0231
0.035
0.05620.05950.12520.00020.01790.02230.03880.06420.06540.15030.00050.01420.01570.0276
0.05250.055
0.0861
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

40

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 11

TOT (Nearest One to four Matching Estimation for school average) regressed on PTA teacher ratio

PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.17670.36390.38390.55790.94630.88780.38060.113
0.3162
0.34120.5046
0.88360.80220.29390.6316
0.89440.88481.21991.80051.676
0.7192[1.03][2.09]**[2.20]**[3.11]*** [6.57]*** [5.57]*** [2.05]**[0.68][1.88]*[2.02]**[2.93]*** [6.50]*** [5.30]*** [1.67]*[2.26]**[3.15]*** [3.10]*** [4.25]*** [7.40]*** [6.19]*** [2.28]**0.13730.13050.0169[0.33]Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.0596

0.0648-0.0381[-0.76]
0.06390.00040.1242[1.34]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.1709[1.96]**

Number of meal in one day(School average)

0.0928[1.64]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)-0.0138[-0.33]0.0238-0.0054[-0.47]0.0772[1.02]

0.0897[5.51]***

Possession of telepohne (School
average)

Constant
R-squared
Adj-R-squaredN-0.0121[-0.28]0.0245-0.0068[-0.58]0.0784[1.03]

0.051[3.63]***-0.0257

0.0521

0.042[0.57]

0.028

0.14470.1356-0.0753[-1.79]*0.02950.0267[0.54]

0.03610.05940.0581-0.01210.1876[3.28]***
0.0429-0.0354[-0.73]0.0517-0.0226[-1.04][-1.58]0.16220.0893[1.02]

0.05280.0193-0.0094[-0.23]-0.0069[-0.17]0.00920.0101[5.88]***

0.0104-0.0318[-2.47]**-0.0366-0.084[-2.08]**0.0164[2.19]**

0.07190.089[1.55]-0.0082

0.0519[0.76]

0.0566[4.30]***

0.1805[0.14]-0.0338

0.0581[4.40]***

0.058[0.84]-0.036[-2.60]*** [-2.76]***0.0502[0.73]

0.0918[2.63]***

0.0605[0.88]

0.02670.02870.1604[2.26]**
0.0626[3.38]***
0.0092[0.14]
0.0596[0.56][0.60][1.16]
0.81140.81080.7255[6.00]*** [5.96]*** [5.61]***-0.0328-0.0329-0.0287[-5.66]*** [-5.64]*** [-5.10]***-0.1343-0.1309-0.1238[-1.40][-1.36][-1.34]-0.0042-0.004-0.0025[-0.94][-0.91][-0.59]0.0358[0.73][0.74][-0.08]0.28740.28810.2879[8.53]*** [8.50]*** [8.73]***0.18760.0199[1.34][1.21][0.27][0.29][0.49]
0.03750.017-0.0135-0.0163-0.0194[0.83][0.38][-0.36][-0.44][-0.50][0.58][0.61][1.30]
0.87150.871
0.7769[6.12]*** [6.10]*** [5.67]***-0.0363-0.0363-0.0323[-5.98]*** [-5.97]*** [-5.44]***-0.0321-0.0297
0.0236[-0.31][-0.29][0.23]-0.0069-0.0068-0.0041[-1.52][-1.50][-0.91]
0.0581

0.055[3.33]*** [3.10]*** [1.24][0.54][0.53][-0.99]0.01280.0107-0.0498-0.0427-0.0414-0.102[0.21][0.18][-0.83][-0.88][-0.85][-2.05]**-0.0676-0.0658-0.01850.01390.011
0.096[-3.55]*** [-3.41]*** [-0.89][0.73][0.58][1.72]*[2.10]**[3.70]***

0.0402[0.54][3.28]***
Log Pupil Teacher Ratio for TSC
teacher

0.0208[1.43][1.43][0.65][0.67][1.01]
0.01960.0025-0.0334-0.0354-0.0329[0.43][0.05][-0.86][-0.92][-0.81][0.03]
Sex if Household Head (School
average, 1 is Male)

0.0212[3.05]*** [2.88]*** [1.29][0.54][0.53][-0.63]-0.0024-0.0037-0.0552-0.0534-0.0525-0.0965[-0.04][-0.06][-0.89][-1.06][-1.04][-1.85]*-0.0629-0.0625-0.0174
0.01890.01680.1877[-3.20]*** [-3.14]*** [-0.80][0.92][0.81][3.18]***

0.03760.0474[0.48][0.51][0.48]
0.2707
0.27180.2623[9.06]*** [9.02]*** [8.93]***0.16310.1728[2.74]***[3.18]***

0.1729[3.18]***

0.159

0.05970.1631[2.88]***
0.17760.10340.0993-0.0353-0.103-0.1039-0.1867[1.43][1.35][-0.47][-1.60][-1.61][-2.72]***-0.0489-0.0454-0.1328-0.1182-0.1162-0.1728[-0.50][-0.46][-1.35][-1.41][-1.38][-1.88]*-0.1833-0.1786-0.0983-0.0336-0.0379
0.3772[-5.68]*** [-5.44]*** [-2.79]*** [-1.00][-1.12][3.18]***-0.1165[-1.43]0.1087-0.1893[-2.36]**0.1103-0.1276[-1.78]*0.0472-0.1238[-1.73]*0.0485-0.2302[-3.12]***
0.0567[1.48][1.51][0.76][0.79][0.92]
0.05050.0155-0.0261-0.0303-0.0592[0.68][0.21][-0.40][-0.47][-0.83]-0.0135[-0.58]0.1919[1.39]
0.1057[3.97]***
0.5557[4.16]***
0.1038[1.15]-0.0287[-1.42]0.1386[1.17]
0.0534[2.28]**
0.3092[2.63]***
0.0098-0.0316[-1.55]0.1411[1.20]-0.0406[-1.94]*0.2816[2.25]**

0.0558[2.37]**
0.313[2.66]***
0.01280.0484[1.43]
0.2088[1.77]*
0.0994[0.12][0.16][1.13]
1.74051.73951.6303[7.23]*** [7.20]*** [6.93]***-0.0723-0.0724-0.0671[-6.98]*** [-6.96]*** [-6.61]***-0.0339-0.02880.048[-0.21][-0.18][0.30]
0.00140.00160.0019[0.20][0.23][0.26]
0.20960.2123-0.0279[1.53][1.54][-0.15]0.35170.35340.362[6.23]*** [6.24]*** [6.40]***0.3128[3.37]***

0.3129[3.36]***
0.09140.2697[2.81]***
0.2936[0.90][2.93]***[1.31][3.52]***[1.15][3.24]***-0.0078
0.0383-0.0323-0.7544-6.4535-6.5998-6.6626
0.01430.0624-0.0265-0.554-5.9836-6.1874-6.1606
0.05930.38440.3581-0.7044-11.9058-12.2173-12.8544[-0.18][0.55][-0.36][-3.29]*** [-8.19]*** [-8.32]*** [-8.25]*** [0.35][0.94][-0.30][-2.39]** [-8.00]*** [-8.18]*** [-8.14]*** [0.87][3.53]*** [2.52]**[-1.97]** [-9.14]*** [-9.21]*** [-9.33]***0.00090.01660.01850.05310.33930.33970.46450.00040.01970.02190.06240.36280.36360.49910.00420.02960.03270.06930.313
0.31360.43790.00020.014
0.01380.04540.33080.33070.4173-0.0003
0.017
0.01730.05480.35460.35490.455
0.00350.027
0.0282
0.06170.30410.30430.3883
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

41

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 12 TOT (Nearest One to four Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.02680.25810.32770.45730.52810.80120.7149-0.04010.18190.25
0.34090.41960.628
0.41130.06450.4421
0.52830.79870.89691.30270.8392[0.15][1.41][1.79]*[2.48]**[2.81]*** [3.87]*** [2.86]*** [-0.25][1.10][1.49][2.04]**[2.48]**[3.33]*** [1.82]*[0.20][1.35][1.59][2.38]**[2.66]*** [3.55]*** [1.90]*
0.25940.23940.1968[3.59]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.175

0.03060.1318[2.39]**
0.0202-0.03430.1304[1.25]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0966[4.55]***

Possession of telepohne (School
average)

0.0215[0.32]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.1284[2.32]**
0.0095-0.0314[-1.91]*0.1351[1.31]
0.0841

0.045[0.44]

Constant
R-squared
Adj-R-squaredN

0.0416-0.02470.12880.01480.0792[3.62]***
0.0331[0.32]
0.00770.21130.0712[1.18]

0.0083[-1.50]0.2302-0.1588-0.16280.202[4.07]***

0.004

0.1525[1.90]*-0.2055

0.12480.12830.02260.02120.1377[2.75]***
0.00510.1393[2.77]***

0.1338[2.67]***-0.0066-0.0075

0.0742[1.34]-0.013[0.44][0.11][-0.14][-0.16][-0.27]0.04590.02630.009
0.01630.038[0.89][0.51][0.18][0.32][0.69]-0.0286-0.0548[-1.78]*-0.0558-0.0506-0.0483[-3.72]*** [-3.71]*** [-3.37]*** [-3.06]***0.13170.0527[1.19][0.57]

0.11640.0849[3.47]***[4.43]***

0.05050.0747[0.47][0.85]-0.0269

0.0089[0.15]-0.2072

0.0666[0.73]

0.0617[0.68]

0.0769[3.93]***

0.0731[3.75]***

0.0392[0.43]

0.0302[0.33]

0.0043-0.00110.1032[1.08]
0.1118[3.99]***-0.013[-0.14]-0.0291[0.07][-0.02][-0.44]0.75560.75340.7481[3.87]*** [3.89]*** [3.92]***-0.0357-0.0354-0.0347[-3.93]*** [-3.92]*** [-3.92]***-0.1195-0.1255-0.1443[-0.88][-0.92][-1.03]-0.0017-0.002-0.0038[-0.30][-0.35][-0.67]-0.1441[-1.39][-1.43][-1.29]0.14310.13590.1289[3.61]*** [3.44]*** [3.06]***0.15410.1474[4.55]*** [4.15]*** [2.85]*** [2.41]**[2.49]**[0.42]
0.06090.0532-0.0001
0.01230.0078-0.0479[0.79][0.70][-0.00][0.17][0.11][-0.63]-0.00070.00070.03390.037
0.044-0.3155[-0.03][0.03][1.36][1.39][1.66]*[-4.03]***[0.22][0.11][-0.37]0.71420.7114
0.6763[3.50]*** [3.51]*** [3.34]***-0.0343-0.0339-0.0328[-3.60]*** [-3.58]*** [-3.50]***-0.0293-0.0371-0.0081[-0.19][-0.24][-0.05]-0.0087-0.0091-0.0096[-1.40][-1.47][-1.54][1.92]*
Log Pupil Teacher Ratio for TSC
teacher

0.1211[2.19]**[1.26][3.83]***

0.0792[0.81]

Number of meal in one day(School average)

0.1558[0.58][0.39][0.18][0.16][0.08]
0.05440.03380.01190.02140.0647[0.94][0.59][0.21][0.37][1.08][-2.10]**Sex if Household Head (School
average, 1 is Male)

0.1512[4.61]*** [4.22]*** [3.02]*** [2.61]*** [2.70]*** [0.68]
0.01640.0083-0.0417-0.0343-0.0403-0.074[0.20][0.10][-0.53][-0.45][-0.53][-0.94]0.00390.00590.04530.052
0.0612-0.2516[0.16][0.24][1.66]*[1.76]*[2.08]**[-3.62]***-0.1472-0.1546[-1.42][-1.46][-1.11]0.12420.1187
0.0946[3.36]*** [3.23]*** [2.54]**0.15090.1038[1.72]*[1.38]

0.1026[1.37]-0.1562-0.1568

0.1195[1.48]-0.0760.23850.20790.09090.039

0.0459-0.0717[2.53]**[2.18]**[0.93][0.40][0.47][-0.68]0.13760.1261
0.04860.08590.077
0.0312[1.04][0.96][0.38][0.68][0.61][0.23]-0.1311-0.1223-0.0584-0.053-0.0394-0.1002[-3.28]*** [-2.96]*** [-1.29][-1.08][-0.80][-0.57]0.179[1.88]*
0.0823

0.0984[1.03]
0.07220.1421[1.48]

0.1313[1.37]

0.06030.05850.0893[0.83]
0.0101[0.90][0.79][0.67][0.65][0.11]
0.13380.09630.09530.1094
0.0971[1.35][0.97][0.97][1.12][0.90]-0.0595[-2.21]**0.2283[1.29]
0.1102[3.15]***-0.0667[-2.44]**0.2943[1.68]*
0.1191[3.36]***

0.4393[2.66]***-0.0795[-0.76]0.324[1.90]*-0.065-0.0567[-2.07]**0.2848[1.63]
0.1117[3.16]***
0.3064[1.80]*-0.0756-0.0702[-2.38]**0.2724[1.42]
0.1546[3.10]***
0.2651[1.47]-0.1558[-0.61][-0.70][-1.26]
2.198
2.19382.1677[6.00]*** [6.01]*** [5.94]***-0.1001-0.0994-0.0982[-5.87]*** [-5.85]*** [-5.78]***-0.3733-0.3848-0.4254[-1.49][-1.54][-1.67]*0.01510.01460.0122[1.37][1.34][1.06]-0.1199-0.1258-0.1133[-0.64][-0.67][-0.43]0.03590.02540.0607[0.52][0.37][0.86]
0.1226[0.89]

0.1202[0.88]-0.3053

0.1277[0.84]-0.1518[-3.24]*** [-2.08]**[-2.63]*** [-1.10][-2.85]*** [-1.21]-0.0737-0.2402-0.4536-0.6661-4.2571-3.5354-3.3104-0.0321-0.1805-0.3846-0.3088-4.2879-3.7372-3.87420.04660.1495-0.1526-0.2994-12.0301-10.9579-11.8832[-1.44][-2.99]*** [-4.43]*** [-2.52]** [-4.11]*** [-3.32]*** [-3.03]*** [-0.70][-2.44]** [-3.99]*** [-1.31][-4.31]*** [-3.67]*** [-3.67]*** [0.54][1.10][-0.86][-0.70][-6.22]*** [-5.52]*** [-5.63]***00.01690.02660.05050.08090.08760.231100.018
0.02970.059
0.09280.09750.258300.01660.02160.04270.08120.08640.2009-0.00070.0141
0.02160.04210.068
0.074
0.1567-0.00070.01510.02470.05070.08010.08420.1864-0.00070.01370.0166
0.03430.06830.07290.1235
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

42

Table 13 regressed on PTA teacher ratio (Kernel Matching Estimation for school average) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.2688-0.0678-0.01130.144
0.48830.57040.2389-0.3611-0.1415-0.0783
0.05790.39110.43730.069-0.22160.10180.15670.47050.98571.08790.4182[-1.84]*[-0.46][-0.08][0.95][4.21]*** [4.29]*** [1.57][-2.55]** [-1.00][-0.56][0.40][3.60]*** [3.46]*** [0.47][-0.93][0.43][0.67][1.99]**[5.06]*** [4.78]*** [1.60]
0.14940.13470.1159[2.64]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.07140.0942

0.0636[1.47]
0.09210.00140.1003[1.16]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0876[6.04]***

Possession of telepohne (School
average)

0.1426[1.81]*

Number of meal in one day(School average)

0.0619[1.23]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.0804[2.37]**
0.0504-0.0045[-0.44]

Constant
R-squared
Adj-R-squaredN

0.0779[2.30]**
0.0495-0.0025[-0.25]0.0684[1.01]

0.0667[0.99]

0.0529[4.43]***
0.0489[0.77]

0.00150.011

0.15730.13970.0229[0.67]

0.0513[4.30]***
0.04640.1266[2.98]***

0.0471

0.0937-0.0054-0.0706

0.1799[3.62]***-0.06030.0854[-1.60]0.11050.0471[0.59]

0.04660.0903[2.71]***[6.49]***

0.06520.1337[1.79]*

0.02750.0624[1.24]-0.05880.04110.0858[2.62]***

0.0844[2.58]***

0.0408-0.0049

0.0173[0.53]

0.0403-0.0296[-2.54]**-0.0285[-2.44]**0.0247[0.42]

0.0238[0.40]

0.0588[5.28]***[5.21]***

0.0484[0.82]

0.047[0.80]

0.01550.01430.032-0.0281[-2.39]**0.09470.0571[3.65]***
0.0402[0.70]
0.0248[0.40][0.37][0.59]
0.75220.75260.6892[5.85]*** [5.87]*** [5.71]***-0.0302-0.0302-0.0271[-5.57]*** [-5.59]*** [-5.28]***-0.1283-0.1303-0.1125[-1.48][-1.50][-1.33]-0.0047-0.0047-0.0039[-1.20][-1.22][-1.00]-0.0944-0.0196[-1.48][-1.49][-0.24]0.26510.26450.2522[8.88]*** [8.86]*** [8.64]***0.17730.1657[3.39]***[3.52]***

0.1657[3.52]***

0.0213-0.03390.16630.14830.1801[3.60]***
0.05520.0229-0.0333-0.0326-0.0828[2.65]*** [2.34]**[0.35][-0.63][-0.61][-1.46]0.03
0.0252-0.0589-0.0456-0.0472-0.0638[0.35][0.29][-0.68][-0.66][-0.68][-0.85]-0.1629-0.1612-0.0871-0.0466-0.0430.0083[-5.80]*** [-5.59]*** [-2.85]*** [-1.68]*[-1.53][0.12]
0.0717[1.06][1.58]

0.0579-0.0933[-0.98][-1.00][-0.63]0.28190.28080.278[8.41]*** [8.40]*** [8.56]***0.18

0.0672[1.61]-0.0206[-0.53][0.27][0.22][0.58]
0.79450.79520.7136[5.76]*** [5.78]*** [5.49]***-0.0328-0.0328-0.0295[-5.66]*** [-5.68]*** [-5.34]***-0.0636-0.067-0.0059[-0.66][-0.70][-0.06]-0.0078-0.0079-0.006[-2.00]** [-2.03]** [-1.51]-0.06880.0407[2.43]**[2.26]**[1.42][1.40][1.14]
0.03940.0243-0.0026-0.00110.0056[1.00][0.62][-0.09][-0.04][0.18][1.03]
0.009

0.0691[4.13]*** [3.66]*** [1.79]*[1.35][1.36][-0.16]
0.05720.0506-0.00490.00170.0009-0.0335[1.06][0.95][-0.09][0.04][0.02][-0.82]-0.0591-0.0594-0.0215-0.0037-0.00210.0207[-3.55]*** [-3.51]*** [-1.17][-0.24][-0.13][0.63][1.63][0.73][3.62]***
Log Pupil Teacher Ratio for TSC
teacher

0.0404[2.32]**[2.31]**[1.63][1.60][1.54]
0.01960.0065-0.0258-0.023-0.0071[0.48][0.16][-0.80][-0.71][-0.21][0.11]
Sex if Household Head (School
average, 1 is Male)

0.0398[3.74]*** [3.36]*** [1.75]*[1.20][1.22][0.04]
0.02620.0205-0.027-0.025-0.0263-0.0457[0.47][0.37][-0.49][-0.58][-0.61][-1.05]-0.0571-0.0588-0.0210.001
0.00390.059[-3.30]*** [-3.33]*** [-1.09][0.06][0.22][1.67]*

0.1285-0.0039[-0.06]0.12870.0444[0.80]
0.06180.0413[0.75]-0.0398[-0.69]0.06070.0406[1.98]**[2.01]**[1.20][1.17][0.78]
0.05720.0267-0.01-0.0065-0.0166[0.88][0.42][-0.19][-0.12][-0.29]-0.0083[-0.41]0.1847[1.44]
0.1156[4.96]***
0.4726[3.98]***
0.0918[1.17]-0.023[-1.30]0.1569[1.48]
0.0687[3.54]***
0.2867[2.88]***
0.0216-0.0205[-1.16]0.1548[1.46]-0.0269[-1.48]0.2196[1.95]*

0.0668[3.45]***
0.2836[2.85]***
0.019

0.0428[1.54]
0.2632[2.66]***
0.0612[0.33][0.29][0.84]
1.61151.61231.5111[7.21]*** [7.24]*** [6.95]***-0.0668-0.0668-0.0621[-7.05]*** [-7.07]*** [-6.76]***-0.025-0.0292
0.0473[-0.17][-0.20][0.32]
0.00070.00060.0012[0.12][0.09][0.19]
0.00310.0008-0.0677[0.03][0.01][-0.43]0.35310.35170.3609[6.31]*** [6.30]*** [6.57]***0.2839[3.55]***

0.2838[3.55]***-0.0750.2846[3.46]***
0.0693[-1.53][0.48][-0.91][1.33][-1.18][0.94]
0.05780.0785-0.0841-0.6734-5.8329-5.6274-5.37160.08850.102-0.0852-0.4679-5.4781-5.3626-5.18050.18110.409
0.225-0.7875-11.1568-10.9011-10.7932[1.55][1.29][-1.08][-3.33]*** [-7.76]*** [-7.48]*** [-7.21]*** [2.48]**[1.75]*[-1.13][-2.29]** [-7.74]*** [-7.57]*** [-7.55]*** [3.06]*** [4.31]*** [1.88]*[-2.55]** [-9.28]*** [-8.99]*** [-8.78]***0.00260.02340.03340.07010.41020.4112
0.52140.005
0.03080.04340.086
0.44590.44630.56240.00070.0326
0.03720.08120.38020.3807
0.48380.00190.02080.02880.0626
0.4026
0.40320.47910.00440.02820.03890.07860.43880.43880.523800.03
0.03270.07380.37220.37230.4383
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

43

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 14 TOT (Kernel Estimation for Lower standard grade below three) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.03140.21630.27630.394
0.46760.711
0.5171-0.1060.12270.18480.26370.34180.519
0.2319-0.16450.21580.28750.5886
0.67571.11130.6444[-0.18][1.24][1.58][2.22]**[2.60]*** [3.59]*** [2.22]**[-0.69][0.78][1.16][1.66]*[2.13]**[2.88]*** [1.10][-0.54][0.69][0.92][1.87]*[2.14]**[3.22]*** [1.56]
0.2493

0.23690.1871[3.60]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.17250.14830.05510.1195[2.28]**
0.04220.1161[2.22]**-0.0397

0.1034[1.05]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0308-0.0380.0996

0.0643[0.69]

Number of meal in one day(School average)
Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.0867[4.22]***
0.0295[0.30]

0.01[0.17]

0.1067[1.10][4.96]***
Possession of telepohne (School
average)

Constant
R-squared
Adj-R-squaredN

0.1096[2.10]**
0.0298-0.0001-0.0319[-2.10]**0.1011[1.04]
0.0822[4.03]***
0.0189[0.20]-0.0065

0.21940.206

0.0624[1.10]-0.1628-0.1664

0.1998[4.20]***

0.02670.1883[2.47]**-0.1832

0.12370.1267

0.026

0.039

0.1333[2.79]***
0.02130.1339[2.81]***

0.1291[2.72]***

0.00720.00640.0631[1.21]-0.0043[0.86][0.48][0.16][0.15][-0.10]-0.0062-0.0243-0.0416-0.0354-0.0191[-0.13][-0.50][-0.87][-0.74][-0.38]-0.0315-0.0573[-2.11]**-0.0599-0.0555-0.0505[-4.10]*** [-4.22]*** [-3.92]*** [-3.40]***0.08690.0442[0.83][0.51]

0.12730.0894[4.16]***[4.94]***

0.02460.0428[0.24][0.52]-0.0434-0.0032[-0.06]-0.2288

0.0628[0.74]

0.0587[0.69]

0.0824[4.48]***

0.0792[4.33]***

0.0148[0.17]

0.0071[0.08]-0.0061-0.01070.0798[0.89]
0.1155[4.49]***-0.0333[-0.37]-0.0435[-0.11][-0.19][-0.71]0.74790.74610.737[4.01]*** [4.02]*** [4.03]***-0.035-0.0347-0.0339[-4.04]*** [-4.04]*** [-4.00]***-0.1466-0.1516-0.1676[-1.12][-1.16][-1.26]-0.0011-0.0013-0.0016[-0.20][-0.24][-0.29]-0.1766[-1.51][-1.55][-1.51]0.14230.13590.1345[3.88]*** [3.73]*** [3.43]***0.18970.1446[4.58]*** [4.26]*** [2.98]*** [2.57]**[2.64]*** [0.52]
0.06140.05560.00170.01570.0119-0.0551[0.85][0.78][0.02][0.23][0.17][-0.77]-0.0172-0.0210.00940.00940.0154-0.4565[-0.83][-1.00][0.40][0.38][0.62][-5.93]***[-0.00][-0.10][-0.65]0.68770.68520.6543[3.55]*** [3.56]*** [3.38]***-0.0328-0.0324-0.0315[-3.63]*** [-3.62]*** [-3.52]***-0.0624-0.0693-0.0373[-0.43][-0.48][-0.25]-0.0089-0.0092-0.0083[-1.52][-1.58][-1.39][2.48]**
Log Pupil Teacher Ratio for TSC
teacher

0.0396[1.10][0.85][0.63][0.61][0.54]-0.0141-0.0334-0.0569-0.0485-0.0174[-0.26][-0.62][-1.06][-0.90][-0.31][-2.61]*** [-2.50]**
Sex if Household Head (School
average, 1 is Male)

0.1524[4.71]*** [4.42]*** [3.18]*** [2.74]*** [2.83]*** [0.70]
0.05330.0478-0.00440.0044-0.0009-0.0617[0.72][0.65][-0.06][0.06][-0.01][-0.84]-0.0119-0.01650.02010.02910.0373-0.5047[-0.53][-0.72][0.79][1.05][1.35][-6.04]***-0.1792-0.2019[-1.84]*[-1.88]*[-1.56]0.12660.122
0.102[3.63]*** [3.52]*** [2.84]***0.2054

0.1081[2.49]**[1.50]

0.1071[1.49]-0.1284-0.1333

0.1498[1.93]*-0.0523

0.25710.23590.10430.05350.0609-0.0599[2.90]*** [2.62]*** [1.15][0.59][0.68][-0.61]0.04510.0369-0.0493-0.014-0.0235-0.1126[0.36][0.30][-0.40][-0.12][-0.20][-0.89]-0.1428-0.1409-0.0698-0.0625-0.0479-0.2353[-3.75]*** [-3.58]*** [-1.61][-1.35][-1.03][-1.55]0.1704[1.95]*
0.08350.0808[0.92]
0.07210.1171[1.33]
0.05930.1055[1.21]

0.0405[0.41]

0.05740.025[0.97][0.84][0.70][0.68][0.29]
0.058
0.01850.01230.02740.0138[0.62][0.20][0.13][0.30][0.14]-0.0575[-2.27]**0.1896[1.14]
0.1229[3.71]***
0.4928[3.15]***-0.0386[-0.40]-0.064[-2.51]**0.2509[1.53]
0.1285[3.81]***
0.3895[2.41]**-0.0279-0.0533[-2.09]**0.2408[1.47]
0.1206[3.60]***
0.3706[2.29]**-0.0393-0.0547[-2.03]**0.1622[0.91]
0.1687[3.71]***
0.3231[1.90]*-0.1047[-0.28][-0.39][-0.91]2.04632.04182.0036[6.01]*** [6.01]*** [5.87]***-0.0931-0.0924-0.0905[-5.86]*** [-5.84]*** [-5.69]***-0.3493-0.3617-0.3254[-1.44][-1.50][-1.34]0.01080.01020.0081[0.99][0.95][0.73]-0.1659-0.1723-0.2287[-0.93][-0.97][-0.91]0.04930.03790.0668[0.77][0.59][1.01]
0.2053[1.58]

0.2027[1.57]-0.3277

0.2698[1.88]*-0.1812[-3.02]*** [-1.83]*[-2.38]** [-0.83][-3.21]*** [-1.52]-0.0483-0.1834-0.3453-0.4536-3.9161-3.273-2.7958
0.0013-0.1063-0.2745-0.1212-4.0948-3.6265-3.5787
0.10090.23530.005-0.3072-11.1577-10.0068-10.7931[-1.01][-2.41]** [-3.58]*** [-1.83]*[-3.93]*** [-3.21]*** [-2.63]*** [0.03][-1.51][-3.08]*** [-0.55][-4.28]*** [-3.73]*** [-3.57]*** [1.22][1.82]*[0.03][-0.76][-6.25]*** [-5.47]*** [-5.59]***00.02020.03
0.0587
0.09620.10220.24730.00030.02020.0326
0.06720.10890.1127
0.27190.00020.02030.02420.05230.09270.09940.2189-0.00070.01730.025
0.05040.08340.08890.1744-0.0004
0.01730.02760.059
0.09640.09960.2014-0.0005
0.01750.01920.044
0.07990.08610.1432
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

44

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 15 TOT (Kernel Normal Matching Estimation for school average) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available in village
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.42550.63720.65030.86271.22191.06040.27220.40060.614
0.63320.84281.203
0.99380.30470.9594
1.28841.2814
1.69722.23852.01430.8297[2.01]**[2.95]*** [2.98]*** [3.82]*** [6.12]*** [4.72]*** [1.02][1.97]**[2.98]*** [3.04]*** [3.92]*** [6.36]*** [4.62]*** [1.22][2.91]*** [3.84]*** [3.78]*** [4.95]*** [7.12]*** [5.74]*** [1.97]**0.12050.12150.0402[0.64]Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)0.03940.068-0.0256[-0.41]
0.06690.00870.1343[1.25]

Type of House (School average, 1 islowest quality and 5 is the finest
quality)
Possession of telepohne (School
average)Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School average)
Log Pupil Teacher Ratio for TSC
teacher
Constant
R-squared
Adj-R-squaredN

0.02560.005[0.09]
0.02740.0037[0.25]
0.1018[1.07]-0.0002[-0.01]0.1051[1.11]

0.075

0.0781[5.59]***[3.99]***[4.13]***

0.20840.08070.08550.0795[1.19]

Age (School average)

0.0001[0.00]

0.1124[1.99]**
Number of meal in one day (School
average)-0.0032-0.0276[0.83]
0.0266[0.89]
0.0306

0.11710.11620.0579[0.95]

0.04710.0036

0.0578-0.0050.23230.2324[3.21]***
0.1185-0.0151[-0.25]0.0519-0.0109[-0.32][-0.66]0.21460.1065[2.21]**[1.05]

0.05780.1166[2.12]**[5.97]***

0.09150.2289[0.92][2.31]**

0.07640.0112[0.21]-0.01530.0176[0.32]

0.0092-0.0193[-1.22]0.0759[0.87]

0.0116-0.026-0.0244[-1.52]0.0802[0.92]

0.0822[4.52]***
0.1071[1.17]

0.0682[0.99]-0.056-0.0773[-1.40]0.02460.013-0.0275[-1.70]*[4.71]***
0.11340.01820.071[2.76]***
0.1058[1.16]
0.0571[0.22][0.31][0.90]
0.95050.94880.9112[5.34]*** [5.29]*** [5.19]***-0.0395-0.0395-0.0374[-5.02]*** [-4.99]*** [-4.74]***-0.0837-0.075-0.0909[-0.68][-0.60][-0.77]-0.0025-0.00220.0039[-0.48][-0.41][0.75]
0.00610.0321[0.02][0.06][0.25]
0.262
0.26480.25[7.50]*** [7.48]*** [7.33]***0.20920.1968[2.55]**[2.80]***

0.263

0.1969[2.81]***
0.15350.10410.1088-0.0391

0.1949[2.49]**
0.2832-0.1095-0.1112-0.1658[1.17][1.22][-0.44][-1.33][-1.35][-1.85]*0.02990.0333-0.0616-0.0463-0.0428-0.1029[0.26][0.29][-0.52][-0.43][-0.40][-0.86]-0.2252-0.2328-0.1426-0.0847-0.0926-0.3418[-5.73]*** [-5.86]*** [-3.35]*** [-1.92]*[-2.06]** [-1.95]*-0.0548[-0.56]0.143-0.1382[-1.42]-0.0766[-0.84]0.1505-0.0698[-0.77]0.0875-0.1848[-1.90]*0.09

0.1052[1.59][1.69]*[1.08][1.11][1.27]-0.0804-0.1153-0.155-0.1626-0.1833[-0.87][-1.26][-1.82]*[-1.91]*[-2.01]**0.0139[0.53]

0.2059[2.25]**

0.0862[1.24]

0.0015[0.00][0.04][-0.20]0.27190.27410.2693[7.33]*** [7.32]*** [7.26]***[3.21]***-0.0138[1.09][0.99][0.20][0.25][0.53]-0.0523-0.0715-0.1015-0.1086-0.1142[-0.93][-1.28][-2.01]** [-2.16]** [-2.18]**[0.45][0.52][1.17]
1.08031.079
1.0423[6.03]*** [6.00]*** [5.87]***-0.0459-0.046-0.0445[-5.81]*** [-5.79]*** [-5.60]***0.067
0.07370.092[0.52][0.57][0.72]-0.0049-0.0046
0.0024[-0.91][-0.86][0.45]
0.00010.0237[2.18]**[2.15]**[0.44][-0.28][-0.32][-1.08]0.05390.0523-0.0172-0.0101-0.0068-0.0816[0.76][0.74][-0.24][-0.16][-0.11][-1.25]-0.0905-0.0967-0.0451-0.0157-0.023-0.2613[-3.86]*** [-4.07]*** [-1.77]*[-0.62][-0.89][-2.50]**-0.0875[-1.52][1.23][1.22][0.52][0.56][0.95]-0.0647-0.0811-0.1153-0.1207-0.1222[-1.11][-1.40][-2.19]** [-2.30]** [-2.22]**[0.54]
Sex if Household Head (School
average, 1 is Male)-0.002[2.17]**[2.18]**[0.71][-0.04][-0.06][-0.50]0.04390.0433-0.0171-0.0156-0.0131-0.0796[0.61][0.60][-0.23][-0.24][-0.20][-1.16]-0.0887-0.0957-0.0463-0.0147-0.0204-0.1626[-3.65]*** [-3.89]*** [-1.75]*[-0.55][-0.75][-1.80]*0.29[1.82]*
0.1368[4.15]***
0.6257[3.93]***
0.0866[0.82]-0.0002[-0.01]0.2525[1.76]*
0.0873[2.77]***
0.3858[2.57]**
0.0059-0.0056[-0.23]0.2571[1.80]*
0.0916[2.88]***
0.3926[2.61]***
0.0115-0.02[-0.77]0.4303[2.74]***
0.0673[1.46]
0.3508[2.26]**
0.1002[0.06][0.12][0.94]
1.9581
1.9563
1.9225[6.74]*** [6.70]*** [6.56]***-0.0826-0.0827-0.0805[-6.35]*** [-6.34]*** [-6.10]***0.01150.02080.0203[0.06][0.10][0.10]
0.00340.00380.0103[0.37][0.42][1.12]
0.13530.1402

0.032[0.78][0.80][0.14]
0.33290.33590.3434[5.64]*** [5.64]*** [5.60]***0.3509[2.99]***

0.3511[2.99]***
0.16450.2738[2.05]**
0.3663[1.79]*[3.45]***[2.45]**[4.01]***[1.52][2.96]***
0.00180.10160.0838-0.7465-7.5625-7.9666-8.17440.01710.12070.0857-0.5717-6.727-7.2506-7.2790.07860.47330.4912-0.9323-13.2135-13.7746-14.5351[0.03][1.19][0.74][-2.79]*** [-7.82]*** [-8.17]*** [-7.95]*** [0.34][1.47][0.79][-2.11]** [-6.98]*** [-7.40]*** [-7.03]*** [0.96][3.63]*** [2.82]*** [-2.31]** [-8.52]*** [-8.73]*** [-8.32]***0.00330.01810.0201
0.05250.23750.23940.35940.00310.01930.02130.0586
0.24920.25270.37850.00640.03120.03330.06790.22550.227
0.32680.00270.01550.01550.04480.22770.22910.30290.00250.01670.01670.051
0.23950.24250.32370.00570.02860.02870.06030.2156
0.21650.2674
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

45

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 16 TOT (Kernel Normal Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.03960.336
0.39660.52010.56950.88530.955-0.04720.22580.27070.37450.41910.65250.64570.29830.80360.8696
1.0975
1.18391.61111.1477[0.18][1.49][1.75]*[2.24]**[2.42]**[3.35]*** [2.95]*** [-0.23][1.03][1.23][1.66]*[1.84]*[2.59]*** [2.11]**[0.75][1.92]*[2.05]**[2.54]**[2.69]*** [3.35]*** [1.97]**
0.34920.33720.1869[2.62]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.27560.067

0.1371[1.90]*
0.0587-0.0408

0.1226[0.97]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0657[2.47]**

Possession of telepohne (School
average)

0.1633[1.33]

Number of meal in one day(School average)-0.0112[-0.14]Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)0.1297[1.79]*
0.0459-0.039[-1.92]*0.1441[1.14]
0.0529[1.93]*
0.1406[1.10]

Constant
R-squared
Adj-R-squaredN

0.15150.1213[1.68]*
0.0445-0.0094-0.0312[-1.54]0.1368[1.08]
0.0472[1.73]*
0.1269[1.00]-0.01760.311

0.30570.0503[0.63]-0.1615-0.16610.156[2.31]**

0.05210.1584[1.57]-0.23770.22110.225

0.11930.062

0.1069[1.56]
0.04870.1004[1.46]

0.0942[1.37]

0.03530.03430.0259[0.34]
0.0439[0.99][0.78][0.57][0.56][0.68]-0.0601-0.0816-0.0977-0.0896-0.0445[-0.88][-1.19][-1.42][-1.31][-0.60]-0.0323-0.0608[-1.52]-0.0607-0.0549-0.0531[-3.21]*** [-3.11]*** [-2.81]*** [-2.51]**

0.14280.0515[1.04][0.43]

0.09020.0545[2.22]**[2.19]**

0.13770.2109[1.00][1.81]*-0.0303-0.0434[-0.56]-0.1159

0.0784[0.65]

0.0729[0.60]

0.0454[1.77]*

0.0411[1.60]

0.1968[1.61]

0.1867[1.53]-0.0378-0.04390.1164[0.89]-0.1943[2.21]**
0.1576[1.21]-0.0418-0.0833[-1.44][-1.47][-0.47]0.11690.11080.0867[2.55]**[2.43]**[1.81]*

0.13910.1266[1.23][1.29]

0.1252[1.29]-0.1948-0.1756

0.35690.33760.23

0.1349[1.25]-0.1155

0.19520.20240.1177[2.93]*** [2.76]*** [1.83]*[1.55][1.60][0.84]
0.086
0.07870.01280.03780.0285-0.0693[0.50][0.46][0.08][0.22][0.17][-0.37]-0.1685-0.168-0.1191-0.1176-0.1032
0.283[-3.26]*** [-3.13]*** [-2.03]** [-1.83]*[-1.60][1.23]
0.1352[1.09]
0.12050.089[0.71]

0.1271[1.00]

0.11120.1157[0.91]

0.09250.0922[0.65]

0.0906

0.0528[1.05][0.97][0.80][0.79][0.43]
0.04510.00830.00820.0231-0.035[0.36][0.07][0.07][0.18][-0.25]-0.0837[-2.39]**0.1521[0.68]

0.0846[-0.47][-0.54][-0.47]0.59320.59080.626[2.47]**[2.48]**[2.61]***-0.0288-0.0284-0.0293[-2.56]** [-2.54]** [-2.60]***0.11940.11270.0862[0.71][0.67][0.49]
0.00080.0005-0.0052[0.11][0.07][-0.66]-0.1908[-1.16][-1.20][-0.61]0.12570.11750.1086[2.65]*** [2.48]**[2.16]**
0.16030.2393[4.58]*** [4.45]*** [3.39]*** [3.11]*** [3.17]*** [1.63]-0.0722-0.0751-0.1247-0.1189-0.124-0.1967[-0.72][-0.76][-1.27][-1.20][-1.25][-1.89]*-0.0165-0.0251
0.00610.00270.01050.0013[-0.58][-0.85][0.19][0.08][0.30][0.02][-0.11][-0.21][-0.32]0.56520.56190.5048[2.30]**[2.30]**[2.04]**-0.0279-0.0274-0.0251[-2.43]** [-2.39]** [-2.17]**0.23520.22620.2459[1.31][1.26][1.30]-0.0005-0.0009-0.0064[-0.06][-0.11][-0.77][1.58]
Log Pupil Teacher Ratio for TSC
teacher

0.2605[1.02][0.89][0.70][0.68][0.75]-0.0221-0.0436-0.0629-0.052-0.0053[-0.30][-0.60][-0.86][-0.71][-0.07][-2.05]**
Sex if Household Head (School
average, 1 is Male)

0.2552[4.86]*** [4.66]*** [3.68]*** [3.39]*** [3.47]*** [1.92]*-0.0535-0.0588-0.1032-0.1013-0.1082-0.149[-0.53][-0.58][-1.03][-1.01][-1.08][-1.41]-0.0005-0.0060.02990.0321
0.04280.0142[-0.02][-0.20][0.87][0.86][1.14][0.13]-0.0926[-2.57]**0.2199[0.98]

0.037[0.84]
0.6095[2.89]***-0.1741[-1.30]-0.082[-2.28]**0.21[0.93]

0.044[0.97][2.38]**-0.15450.2253[0.88]

0.0362[0.80]

0.5236-0.0906[-2.30]**0.1064[1.64]

0.505[2.29]**-0.1656

0.4688[1.96]**-0.2119[-1.11][-1.19][-1.29]1.77871.7744
1.7799[3.96]*** [3.96]*** [3.82]***-0.0796-0.079-0.0791[-3.82]*** [-3.80]*** [-3.64]***-0.0257-0.0378-0.0249[-0.08][-0.12][-0.08]0.01340.01290.0059[0.97][0.94][0.40]-0.1105-0.1168-0.109[-0.45][-0.48][-0.33]0.029
0.01790.0474[0.34][0.21][0.53]
0.1092[0.62]

0.1066[0.61]-0.32140.0553[0.29]-0.1719[-2.88]*** [-2.04]**[-2.23]** [-1.24][-2.27]** [-1.03]-0.0998-0.297-0.4593-0.5229-3.6863-2.8517-2.74250.0195-0.1179-0.2209
0.0089-3.2675-2.651-3.2667-0.04240.0778-0.13850.2604-9.5827-8.4539-9.535[-1.58][-2.92]*** [-3.38]*** [-1.56][-2.98]*** [-2.23]** [-2.05]** [0.33][-1.20][-1.67]*[0.03][-2.67]*** [-2.11]** [-2.51]** [-0.39][0.44][-0.59][0.47][-4.11]*** [-3.53]*** [-3.63]***00.01870.02440.03580.0512
0.05690.170100.01730.02220.0377
0.05340.05680.19020.00040.01830.02030.03280.04950.053
0.1364-0.00070.01580.01940.02730.03780.04290.0897-0.00070.01440.01720.02920.0401
0.04290.1117-0.0003
0.01540.01520.02430.0361
0.039
0.0527
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

46

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 17 TOT (Radius 0.05 Matching Estimation for school average) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.3153-0.109-0.0486
0.10560.44750.541
0.2229-0.4034-0.1792-0.11190.02350.35440.4101
0.0527-0.3094
0.02410.0861
0.39810.90881.03120.3838[-2.17]** [-0.74][-0.34][0.70][3.88]*** [4.08]*** [1.46][-2.87]*** [-1.27][-0.80][0.16][3.29]*** [3.25]*** [0.36][-1.31][0.10][0.37][1.70]*[4.70]*** [4.54]*** [1.46]
0.15370.13820.1272[2.90]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.075

0.09740.0745[1.73]*
0.09490.0012

0.0964[1.11]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0883[6.09]***

Possession of telepohne (School
average)

0.1402[1.78]*

Number of meal in one day(School average)

0.0596[1.18]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.0906[2.68]***
0.0532-0.0048[-0.46]
0.0651[0.96]
0.0537[4.49]***
0.0487[0.76]

Constant
R-squared
Adj-R-squaredN

0.00590.0878[2.60]***
0.05210.0092-0.0025[-0.24]0.0632[0.94]

0.16070.14230.0346[1.01]

0.1378[3.25]***

0.0485[4.34]***
0.0458[0.72]-0.0775-0.0796-0.0052

0.182[3.66]***-0.0686

0.088-0.0208[-0.51][-1.62]0.1026

0.0438[0.55]

0.0476

0.0913[2.76]***[6.54]***

0.06640.1313[1.76]*

0.02180.0608[1.21]-0.0577

0.04390.0957[2.92]***

0.094[2.88]***

0.04340.0428-0.0299[-2.57]**-0.0285[-2.45]**0.0222[0.37]

0.021[0.35]

0.0598-0.0018

0.0281[0.86][5.35]***[0.82]-0.028[-2.37]**0.0877[1.46][5.26]***

0.0481

0.0464[0.79]

0.01440.058[3.69]***
0.04220.0204[0.37][0.33][0.49]
0.74450.74490.68[5.76]*** [5.78]*** [5.60]***-0.0299-0.0299-0.0268[-5.49]*** [-5.50]*** [-5.17]***-0.1333-0.1356-0.1179[-1.54][-1.57][-1.40]-0.0047-0.0048-0.0038[-1.20][-1.23][-0.98]-0.1034-0.0192[-1.62][-1.64][-0.24]0.2656
0.26490.2533[8.88]*** [8.87]*** [8.64]***0.18190.1684[3.47]***[3.58]***

0.1683[3.58]***

0.0083-0.0409

0.15470.02950.09160.13440.0154[0.23]

0.1845[3.68]***
0.0435-0.0259-0.025-0.0747

0.0623[1.13]

0.13420.0586[1.06]

0.067

0.0656-0.0197[-0.34]0.0433[2.07]**[2.10]**[1.30][1.27][0.83]
0.05610.0261-0.0105-0.0063-0.0148[0.86][0.41][-0.20][-0.12][-0.25]-0.0086[-0.42]0.1804[1.40][0.73]
0.013

0.1741[2.78]*** [2.44]**[0.46][-0.49][-0.47][-1.32]0.03570.0301-0.0544-0.0409-0.0428-0.0568[0.41][0.35][-0.63][-0.59][-0.62][-0.75]-0.1642-0.163-0.0897-0.0509-0.0466
0.011[-5.85]*** [-5.65]*** [-2.93]*** [-1.84]*[-1.66]*[0.16][1.36]

0.03340.0588-0.1022[-1.10][-1.13][-0.62]0.28230.281
0.2789[8.41]*** [8.39]*** [8.54]***0.18210.0778[1.87]*

0.0966[1.04]

0.00690.0435[2.51]**[2.33]**[1.51][1.49][1.18]
0.03920.0243-0.0027-0.0008
0.0065[0.99][0.62][-0.09][-0.03][0.20][1.51]

0.05190.0717[4.22]*** [3.73]*** [1.86]*[1.44][1.46][-0.06]
0.05840.0513-0.00450.00210.0013-0.0319[1.08][0.96][-0.08][0.05][0.03][-0.78]-0.0602-0.0607-0.0231-0.0061-0.00410.0184[-3.61]*** [-3.57]*** [-1.25][-0.39][-0.26][0.57][0.23][0.17][0.46]
0.78550.78620.7032[5.67]*** [5.69]*** [5.38]***-0.0325-0.0324-0.0291[-5.57]*** [-5.59]*** [-5.23]***-0.07-0.0739-0.0119[-0.73][-0.77][-0.13]-0.0077-0.0079-0.0059[-1.99]** [-2.03]** [-1.49][3.66]***
Log Pupil Teacher Ratio for TSC
teacher

0.0444[2.40]**[2.38]**[1.72]*[1.68]*[1.58]
0.01860.0058-0.0266-0.0234-0.007[0.45][0.14][-0.82][-0.72][-0.21][0.09]
Sex if Household Head (School
average, 1 is Male)

0.0437[3.85]*** [3.45]*** [1.84]*[1.32][1.34][0.18]
0.02790.0217-0.026-0.0239-0.0254-0.0428[0.50][0.39][-0.47][-0.55][-0.59][-0.98]-0.058-0.06-0.0227-0.00140.00190.057[-3.34]*** [-3.39]*** [-1.18][-0.08][0.11][1.60]

0.1171[5.02]***
0.4673[3.93]***
0.0871[1.11]-0.0232[-1.31]0.1542[1.45]-0.0203[-1.14]0.1517[1.43]

0.0704[3.62]***
0.286[2.88]***
0.01820.0681[3.51]***
0.2823[2.85]***
0.0151-0.0263[-1.44]0.2089[1.85]*
0.0442[1.59]
0.2657[2.69]***
0.0516[0.28][0.23][0.70]
1.5952
1.5962
1.4927[7.11]*** [7.14]*** [6.83]***-0.0661-0.0661-0.0614[-6.96]*** [-6.98]*** [-6.64]***-0.032-0.0371
0.0399[-0.22][-0.26][0.27]
0.00070.00050.0013[0.12][0.09][0.21]-0.0142-0.0169-0.0666[-0.12][-0.15][-0.42]0.35420.3526
0.3623[6.32]*** [6.30]*** [6.56]***0.2856[3.57]***

0.2855[3.58]***-0.0898

0.2901[3.53]***
0.0469[-1.76]*[0.19][-1.11][1.05][-1.43][0.64]
0.06470.0841-0.088-0.6649-5.7672-5.5331-5.2592
0.09550.1088-0.0883-0.4616-5.422-5.2826-5.08160.19580.42040.2189-0.7729 -11.0418 -10.7355 -10.6022[1.74]*[1.38][-1.13][-3.29]*** [-7.63]*** [-7.32]*** [-7.01]*** [2.69]*** [1.87]*[-1.18][-2.26]** [-7.63]*** [-7.43]*** [-7.36]*** [3.32]*** [4.43]*** [1.83]*[-2.50]** [-9.14]*** [-8.82]*** [-8.57]***0.00360.02530.0366
0.07330.41190.41320.52070.00630.033
0.04710.08990.44820.44870.562
0.00130.03440.03980.08370.38170.38250.48180.00290.02270.0321
0.06580.40440.40530.47840.00560.03040.04260.0826
0.44110.4412
0.52330.00070.03180.03530.07620.37370.37410.4361
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

47

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 18 TOT (Radius 0.05 Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.0433
0.20330.26180.37890.45190.68910.4907-0.1191
0.10710.16880.24790.32460.499
0.2065-0.1991
0.18450.2546
0.55550.6363
1.07830.612[-0.25][1.17][1.50][2.14]**[2.52]**[3.49]*** [2.11]**[-0.77][0.68][1.06][1.56][2.02]**[2.77]*** [0.98][-0.66][0.59][0.81][1.76]*[2.01]**[3.12]*** [1.47]
0.2486

0.23680.1845[3.55]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.17280.05430.1169[2.23]**
0.0415-0.0394

0.1053[1.07]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0996[4.97]***

Possession of telepohne (School
average)

0.0603[0.65]

Number of meal in one day(School average)

0.0126[0.21]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.1129[2.16]**

Constant
R-squared
Adj-R-squaredN

0.04080.1066[2.04]**

0.0301-0.0378[-2.48]**0.1087[1.12]
0.0866[4.22]***
0.0266[0.28]

0.029

0.0022-0.0319[-2.10]**0.1031[1.06]
0.0823[4.03]***
0.0163[0.17]-0.0040.217

0.20390.061[1.08]-0.1647-0.16820.2003[4.21]***

0.02690.1908[2.50]**-0.1785

0.122

0.125

0.02490.03850.1338[2.80]***
0.02080.1337[2.81]***

0.1291[2.72]***

0.00670.00590.0637[1.22]-0.031-0.0569[-2.07]**-0.0596-0.0044-0.0552-0.05[-4.06]*** [-4.19]*** [-3.89]*** [-3.38]***0.08970.0459[0.86][0.53]

0.12720.0898[4.16]***[4.97]***

0.02140.0407[0.21][0.49]-0.0417-0.0027[-0.05]-0.2275

0.0649[0.76]

0.0609[0.72]

0.0827[4.51]***

0.0795[4.35]***

0.0142[0.16]

0.0066[0.08]-0.0056-0.0102-0.1833

0.20940.1117[1.56]

0.1106[1.55]-0.1235-0.13120.11

0.16950.08080.0806[0.92]

0.1148[4.47]***-0.0326[-0.37]-0.0441-0.20290.154[1.99]**-0.0503

0.05960.1151[1.31]

0.067-0.05240.06960.1033[1.18]

0.05650.05460.0408[0.41]
0.0226[0.94][0.81][0.67][0.65][0.26]
0.05220.01370.00720.02260.0082[0.56][0.15][0.08][0.25][0.08]-0.0547[-2.17]**0.179[1.08][-1.89]*[-1.93]*[-1.57]0.12660.12210.1018[3.63]*** [3.52]*** [2.84]***[2.55]**

0.24090.0833[0.94][-0.10][-0.18][-0.72]0.73220.73040.7223[3.93]*** [3.95]*** [3.95]***-0.0343-0.034-0.0333[-3.97]*** [-3.96]*** [-3.93]***-0.1465-0.1515-0.1682[-1.12][-1.17][-1.27]-0.0009-0.0011-0.0013[-0.17][-0.21][-0.24]-0.1808

0.2612[2.95]*** [2.69]*** [1.22][0.66][0.75][-0.54]0.04780.0399-0.0455-0.0102-0.0199-0.1068[0.39][0.32][-0.37][-0.09][-0.17][-0.84]-0.1417-0.1404-0.0702-0.0642-0.0493-0.2617[-3.73]*** [-3.57]*** [-1.62][-1.38][-1.07][-1.74]*[1.94]*[0.85][0.47][0.15][0.14][-0.10]-0.0088-0.0269-0.0442-0.0382-0.0227[-0.18][-0.55][-0.92][-0.80][-0.45][-1.53][-1.57][-1.50]0.14250.13630.1346[3.91]*** [3.76]*** [3.44]***0.19220.1427[4.53]*** [4.22]*** [2.95]*** [2.54]**[2.61]*** [0.50]
0.0606
0.05480.00110.01510.0113-0.0545[0.84][0.77][0.02][0.22][0.17][-0.77]-0.0171-0.02110.00930.009
0.0149-0.4631[-0.83][-1.00][0.40][0.36][0.60][-6.03]***[0.03][-0.06][-0.62]
0.6686
0.66610.6354[3.45]*** [3.47]*** [3.28]***-0.032-0.0316-0.0307[-3.54]*** [-3.53]*** [-3.42]***-0.0631-0.0699-0.0385[-0.44][-0.48][-0.26]-0.0088-0.009-0.0081[-1.49][-1.55][-1.36][2.51]**
Log Pupil Teacher Ratio for TSC
teacher

0.1529[1.09][0.84][0.62][0.60][0.54]-0.0176-0.0369-0.0607-0.0524-0.0226[-0.33][-0.68][-1.13][-0.98][-0.40][-2.58]**Sex if Household Head (School
average, 1 is Male)

0.1489[4.70]*** [4.42]*** [3.18]*** [2.76]*** [2.84]*** [0.72]
0.05470.0495-0.0025
0.00620.001-0.059[0.74][0.67][-0.03][0.09][0.02][-0.81]-0.0108-0.0157
0.021
0.02990.0379-0.5222[-0.48][-0.69][0.82][1.08][1.37][-6.24]***0.1229[3.71]***
0.4936[3.15]***-0.0371[-0.38]-0.0613[-2.40]**0.2421[1.48]-0.0504[-1.97]**0.2318[1.42]

0.1284[3.80]***
0.395[2.44]**-0.02540.1204[3.59]***
0.3758[2.33]**-0.037-0.0521[-1.94]*0.1538[0.86]
0.1668[3.67]***
0.329[1.93]*-0.1026[-0.26][-0.37][-0.90]2.02152.017
1.9831[5.94]*** [5.94]*** [5.80]***-0.092-0.0914-0.0897[-5.80]*** [-5.77]*** [-5.64]***-0.3472-0.3598-0.3227[-1.43][-1.49][-1.33]0.01090.01030.0082[1.00][0.96][0.74]-0.1837-0.1902-0.2485[-1.04][-1.08][-0.99]0.04920.03770.0678[0.77][0.59][1.02]
0.2168[1.68]*

0.2141[1.66]*-0.3326

0.2865[1.99]**-0.1906[-2.94]*** [-1.77]*[-2.35]** [-0.80][-3.26]*** [-1.60]-0.0456-0.1826-0.339-0.4559-3.8249-3.198-2.70910.0048-0.1015-0.2674-0.1194-4.0159-3.555-3.5091
0.10610.23540.0125-0.314-11.0273-9.8594-10.6345[-0.96][-2.40]** [-3.53]*** [-1.84]*[-3.84]*** [-3.14]*** [-2.55]** [0.11][-1.44][-3.00]*** [-0.54][-4.21]*** [-3.66]*** [-3.50]*** [1.29][1.82]*[0.08][-0.78][-6.17]*** [-5.39]*** [-5.51]***00.02010.02970.05840.09570.10150.247
0.00040.01990.03240.06710.10870.11240.27240.00030.02060.02440.0522
0.09220.09910.2183-0.00070.01730.02470.05010.083
0.08820.1741-0.0003
0.01710.02740.05880.0961
0.09920.2019-0.0004
0.01780.01930.04380.07940.08580.1425
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

48

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 19 TOT (Radius 0.01 Matching Estimation for school average) regressed on PTA teacher ratio
PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.5234-0.3104-0.2463-0.0955
0.24270.38090.1561-0.5948-0.3635-0.2939-0.1625
0.16510.2581-0.0015-0.7411-0.3911-0.321-0.0166
0.48480.69290.2639[-3.66]*** [-2.15]** [-1.73]*[-0.65][2.14]**[2.94]*** [1.03][-4.29]*** [-2.62]*** [-2.14]** [-1.15][1.56][2.10]**[-0.01][-3.20]*** [-1.69]*[-1.41][-0.07][2.59]*** [3.16]*** [1.01]
0.16890.15260.1369[3.18]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.08920.101

0.0843[1.99]**
0.0985-0.0018

0.1004[1.18]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0864

Possession of telepohne (School
average)

0.135[1.74]*
0.0685[1.38]

Age (School average)
Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)0.1002[3.01]***
0.0571-0.0082[-0.80]0.0697[1.05][6.04]***

Number of meal in one day(School average)

0.0528[4.48]***
0.0453[0.71]

Constant
R-squared
Adj-R-squaredN

0.02460.096[2.90]***

0.0183-0.0049

0.0669[1.00]
0.0501[4.27]***
0.0411[0.65]
0.01490.1576

0.0513[1.51]

0.0556[-0.47]0.1765-0.0762-0.0792

0.1444[3.48]***

0.051

0.1711[3.49]***-0.10140.05990.06050.01780.09940.0847[2.07]**
0.09080.1027[3.21]***

0.0999[3.13]***

0.04650.04550.0431[1.33]
0.0359[2.63]*** [2.45]**[1.66]*[1.62][1.28]
0.038
0.0221-0.0039-0.00070.0117[0.98][0.57][-0.13][-0.02][0.37]-0.0058-0.0236[-0.57][-1.87]*

0.09860.0494[1.46][0.63]

0.04840.0894[2.83]***[6.55]***

0.06230.1237[0.98][1.68]*

0.02440.0688[1.39]-0.0225-0.033-0.0308-0.0281[-2.89]*** [-2.69]*** [-2.39]**0.0282[0.49]

0.0263[0.45]

0.0589[5.40]***

0.0571[5.25]***

0.0417[0.72]

0.0389[0.67]

0.02260.02030.0847[1.42]-0.1005

0.0327[0.57]
0.02370.0127[-1.58][-1.61][0.16]
0.26080.2596
0.2473[8.79]*** [8.78]*** [8.47]***0.17920.1568[3.43]***[3.40]***

0.1567[3.40]***-0.0376-0.0683

0.20530.18420.05980.1802[3.61]***
0.00410.00660.0081-0.0371[3.35]*** [2.98]*** [0.96][0.13][0.16][-0.66]
0.03430.0277-0.0559-0.0403-0.0436-0.0507[0.40][0.32][-0.65][-0.59][-0.64][-0.68]-0.1528-0.1523-0.0766-0.0405-0.0333-0.0051[-5.59]*** [-5.43]*** [-2.56]** [-1.50][-1.21][-0.08]0.1141[1.75]*
0.14280.0386[0.60]

0.0847[1.58]

0.14290.07580.0784[1.47]
0.07350.0242[0.42]
0.0523[2.26]**[2.30]**[1.51][1.46][1.01]
0.05350.0209-0.0135-0.0064-0.0027[0.84][0.34][-0.26][-0.12][-0.05]-0.0141[-0.70]0.2017[1.61]

0.0595[3.87]***[0.60][0.53][0.57]
0.72310.72390.6609[5.55]*** [5.59]*** [5.35]***-0.0289-0.0289-0.0258[-5.26]*** [-5.28]*** [-4.90]***-0.1582-0.1621-0.149[-1.83]*[-1.87]*[-1.75]*-0.0042-0.0043-0.0039[-1.07][-1.12][-0.99]-0.0984[-1.09][-1.14][-0.24]0.278
0.27610.2736[8.33]*** [8.32]*** [8.41]***0.17120.0872[4.72]*** [4.21]*** [2.31]**[2.03]**[2.06]**[0.59]
0.05590.0485-0.00710.0004-0.001-0.0298[1.05][0.92][-0.14][0.01][-0.03][-0.75]-0.0537-0.0544-0.01590.00050.00380.0196[-3.27]*** [-3.26]*** [-0.88][0.03][0.24][0.62][0.46][0.37][0.52]
0.75890.76
0.6789[5.40]*** [5.44]*** [5.11]***-0.0313-0.0312-0.028[-5.29]*** [-5.31]*** [-4.94]***-0.0978-0.1035-0.0469[-1.01][-1.07][-0.49]-0.0072-0.0074-0.0059[-1.83]*[-1.89]*[-1.47][3.49]***
Log Pupil Teacher Ratio for TSC
teacher

0.0598[2.52]**[2.50]**[1.88]*[1.83]*[1.67]*
0.01840.0044-0.027-0.0223-0.0007[0.46][0.11][-0.85][-0.70][-0.02][-0.15]
Sex if Household Head (School
average, 1 is Male)

0.0588[4.29]*** [3.87]*** [2.22]**[1.80]*[1.84]*[0.73]
0.02660.0199-0.0278-0.0248-0.027-0.0397[0.48][0.36][-0.51][-0.58][-0.63][-0.92]-0.0513-0.0535-0.0151
0.00540.01030.0584[-3.00]*** [-3.07]*** [-0.80][0.32][0.60][1.68]*

0.1788[1.72]*

0.113[4.96]***
0.4482[3.87]***
0.1055[1.36]-0.0297[-1.70]*0.0683[3.59]***
0.2727[2.80]***
0.0383-0.0247[-1.42]0.1745[1.69]*
0.0643[3.40]***
0.2664[2.75]***
0.0332-0.0267[-1.47]0.2087[1.87]*
0.0491[1.80]*
0.2467[2.53]**
0.0575[0.60][0.52][0.79]
1.54351.5452
1.4421[6.98]*** [7.03]*** [6.61]***-0.0638-0.0637-0.059[-6.82]*** [-6.86]*** [-6.39]***-0.0814-0.09-0.0278[-0.56][-0.63][-0.19]0.00240.002
0.0016[0.40][0.34][0.27]-0.0217-0.0263-0.0201[-0.19][-0.23][-0.13]
0.34610.34330.3511[6.25]*** [6.23]*** [6.38]***0.2627[3.37]***

0.2625[3.37]***-0.1527

0.2824[3.45]***-0.047[-2.64]*** [-0.86][-1.88]*[0.10][-2.49]** [-0.65]
0.08730.0838-0.0976-0.6747-5.6238-5.278-4.9834
0.11030.101-0.1017-0.4742-5.3109-5.0781-4.85960.22940.41150.1902-0.8128-10.8016-10.2809-10.0632[2.37]**[1.40][-1.27][-3.39]*** [-7.35]*** [-6.90]*** [-6.56]*** [3.13]*** [1.76]*[-1.38][-2.36]** [-7.42]*** [-7.10]*** [-6.93]*** [3.93]*** [4.45]*** [1.63][-2.68]*** [-9.07]*** [-8.58]*** [-8.17]***0.01
0.03250.04540.082
0.416
0.41890.51450.01390.04190.05740.10080.457
0.45840.556
0.008
0.04140.04830.09270.39070.39330.46970.00940.02990.04090.0746
0.40850.411
0.47170.01330.03930.05290.09360.45
0.45110.51680.00730.03890.04380.08530.38290.385
0.4229
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494
1494

49

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

Table 20 TOT (Radius 0.1 Matching Estimation for Lower standard grade below three) regressed on PTA teacher ratio

PTA teacher ratio
Electricity infra is available invillage
The road is tarnac in village
Unemployment Level (1-5)
Supplement for school material isavailable at classroom (Dummy)

Kiswahili for All Standard Grades
English for All Standard Grades
Numeracy for All Standard Grades
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.2549
0.006
0.06970.1816
0.24970.53990.4149-0.238-0.0026
0.06270.1396
0.21680.40890.1865-0.1990.18610.258
0.55580.63861.04990.5968[-1.49][0.03][0.40][1.02][1.38][2.74]*** [1.78]*[-1.54][-0.02][0.40][0.89][1.36][2.30]**[0.89][-0.66][0.60][0.83][1.78]*[2.04]**[3.06]*** [1.45]
0.26540.25290.1975[3.79]***Classroom is suitable for learning(Dummy)School is fenced (Dummy)
Total Number of famly (School
average)

0.18950.16540.06960.13[2.47]**
0.05590.1241[2.37]**-0.04080.0892[0.90]

Type of House (School average,
1 is lowest quality and 5 is thefinest quality)

0.0448-0.0390.09930.0599[0.65]

Number of meal in one day(School average)

Age Square (School average)
Boy (School average)
Mother Age (School average)
Mother Education History (School
average)
Grade in School (School average)
Parents paid tuition (School
average)

0.0859[4.18]***
0.0293[0.30]

0.004[0.07]

Age (School average)

Constant
R-squared
Adj-R-squaredN

0.0435-0.00710.085[0.87]
0.0806[3.96]***
0.0167[0.17]-0.01470.21420.0799[1.40]

0.208[4.40]***

0.0414-0.0318[-2.09]**0.228-0.1766-0.1809

0.2085[2.75]***-0.2184

0.13220.13540.03930.04910.1417[2.99]***
0.03120.1418[3.00]***

0.1367[2.90]***

0.01740.01660.0755[1.45]
0.0073[1.09][0.71][0.40][0.38][0.16]-0.0112-0.0293-0.047-0.0404-0.0188[-0.23][-0.61][-0.99][-0.85][-0.37]-0.03-0.0583[-2.01]**-0.0609-0.0561-0.0491[-4.20]*** [-4.33]*** [-4.01]*** [-3.34]***0.0551

0.0462[0.53][0.53]

0.1294[4.24]***[4.96]***

0.02550.041[0.25][0.50]-0.0617-0.0084[-0.15]-0.2120.064[0.76]

0.08880.0595[0.71]

0.0815[4.48]***[4.31]***

0.0129[0.15]

0.0046[0.05]-0.0125

0.0644[0.73]

0.078

0.1173[4.62]***-0.0381[-0.43]-0.0175-0.0538[-0.22][-0.31][-0.87]0.72580.72380.7167[3.93]*** [3.95]*** [3.94]***-0.034-0.0337-0.0329[-3.98]*** [-3.97]*** [-3.92]***-0.1508-0.1563-0.1762[-1.15][-1.20][-1.33]-0.001-0.0012-0.0022[-0.19][-0.23][-0.40]-0.176[-1.63][-1.68]*[-1.38]0.14310.13550.135[3.95]*** [3.78]*** [3.47]***0.21020.1533[4.80]*** [4.48]*** [3.20]*** [2.77]*** [2.86]*** [0.79]
0.06930.06330.00960.02370.0195-0.0453[0.96][0.89][0.14][0.35][0.29][-0.64]-0.0141-0.0186
0.01130.01210.0186-0.4809[-0.69][-0.89][0.49][0.49][0.75][-6.36]***[-0.11][-0.23][-0.91]
0.63310.63010.6096[3.25]*** [3.26]*** [3.11]***-0.0304-0.03-0.0295[-3.35]*** [-3.33]*** [-3.25]***-0.0747-0.083-0.0599[-0.51][-0.57][-0.40]-0.0093-0.0097-0.0094[-1.57][-1.65]*[-1.55][2.76]***
Log Pupil Teacher Ratio for TSC
teacher

0.1164[2.23]**

0.0918[0.95][4.94]***
Possession of telepohne (School
average)

0.0618[1.39][1.13][0.92][0.90][0.83]-0.0244-0.0427-0.0672-0.0571-0.0194[-0.45][-0.79][-1.26][-1.07][-0.34][-2.65]*** [-2.56]**
Sex if Household Head (School
average, 1 is Male)

0.1703[5.00]*** [4.72]*** [3.49]*** [3.07]*** [3.18]*** [1.09]
0.06930.06370.01150.02020.0139-0.0446[0.93][0.86][0.16][0.28][0.20][-0.60]-0.0061-0.0120.02270.03170.0414-0.5509[-0.27][-0.52][0.89][1.14][1.50][-6.71]***-0.1788-0.1896[-1.85]*[-1.88]*[-1.46]0.12580.12080.1017[3.57]*** [3.45]*** [2.79]***0.23810.1202[2.91]***[1.69]*

0.119[1.68]*-0.1802-0.14450.1683[2.19]**-0.07160.26

0.23910.10930.05690.0639-0.0528[2.95]*** [2.68]*** [1.22][0.64][0.72][-0.54]0.04630.0382-0.046-0.0111-0.0201-0.1037[0.38][0.31][-0.38][-0.09][-0.17][-0.82]-0.1448-0.1437-0.0757-0.0669-0.053-0.3612[-3.81]*** [-3.65]*** [-1.74]*[-1.44][-1.14][-2.28]**0.1677[1.92]*
0.09510.0815[0.93]

0.1158[1.32]

0.08380.1048[1.20]

0.071

0.0393[0.40]

0.06920.0367[1.11][0.98][0.84][0.82][0.43]
0.05190.01490.00670.021
0.012[0.56][0.16][0.07][0.23][0.12]-0.053[-2.09]**0.1553[0.94]
0.1189[3.59]***
0.5052[3.22]***-0.0397[-0.41]-0.0593[-2.31]**0.2171[1.33]-0.0491[-1.92]*0.2075[1.27]

0.123[3.63]***
0.4018[2.49]**-0.0302-0.0494[-1.82]*0.1228[0.69]

0.1156[3.44]***
0.384[2.39]**-0.0409

0.1654[3.62]***
0.3365[1.98]**-0.1133[-0.30][-0.41][-0.99]2.033
2.02872.002[6.01]*** [6.01]*** [5.86]***-0.0927-0.092-0.0908[-5.88]*** [-5.85]*** [-5.71]***-0.3225-0.3342-0.3011[-1.33][-1.38][-1.23]0.01060.01010.0082[0.98][0.94][0.75]-0.1783-0.1843-0.2385[-1.00][-1.04][-0.93]0.05190.04120.0723[0.82][0.65][1.09]
0.2457[1.91]*

0.2433[1.90]*-0.30960.3127[2.18]**-0.1705[-3.61]*** [-2.58]***[-2.60]*** [-1.14][-3.05]*** [-1.43]-0.0241-0.184-0.3538-0.4188-3.5702-2.8034-2.24140.0036-0.1173-0.2935-0.1176-3.9758-3.4682-3.3479
0.09410.23080.0004-0.308-11.0905-10.0035-10.6467[-0.50][-2.42]** [-3.69]*** [-1.69]*[-3.54]*** [-2.73]*** [-2.08]** [0.08][-1.68]*[-3.31]*** [-0.53][-4.19]*** [-3.60]*** [-3.35]*** [1.15][1.78]*[0.00][-0.76][-6.27]*** [-5.51]*** [-5.50]***0.00150.02420.0356
0.06390.10120.10980.24850.00160.02310.03710.07220.114
0.11850.26990.00030.02110.0251
0.0522
0.09320.09920.21650.00080.02140.0306
0.05570.0886
0.09660.17570.00090.02030.0321
0.064
0.10150.10550.1991-0.0004
0.01830.0201
0.04380.08040.08590.1406
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371
1371

50

Robust standard errors are used for estimation and the estimated t-values are in parentheses. *, **, and *** are indicated to show p-value to reject null hypothesis with p<0.1, p<0.05, p<0.01 respectively.
District Dummy is excluded from table, because it becomes long.

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