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The Effect of Parental Involvement on Student Achievementin Junior Secondary School:
Examining Data from the Botswana TIMSS 2007
YAMASAKI Izumi＊

I. Introduction
This study examines the effect of school-based management（SBM）on student
achievement, with a particular focus on junior secondary schools in Botswana. It
analyzes how parental involvement affects mathematics and science test scores, using
TIMSS（Trends in International Mathematics and Science Survey）2007 data.
1. Motivation and Background of the Research
Recently many developing countries including African countries have promoted
decentralization and applied school-based management（SBM）to improve the qualityof basic education. SBM is“the decentralization of levels of authority to the schoollevel”（Barrera-Osorio, Fasih, Patrinos, 2009）. Under the SBM system, more decisionmaking and management responsibilities over school operation are given to principals,
teachers, parents, sometimes students, and other community members. However,schools still have to operate within the policies determined by the central government（Barrera-Osorio et al., 2009）. Given the fact that traditional approaches, which
increased physical and human resources, did not sufficiently improve the quality ofbasic education, SBM was designed to provide an accountability system between thebeneficiaries（students and parents）and the agents（teachers and policy makers）inorder to improve the quality of basic education.
There is no universally used method of applying SBM and therefore each SBM
have unique features. There are two key axes regarding SBM: the amount ofautonomy a given school has and who manages the authority. Bruns, Filmer and＊ Research Fellow, Graduate School of International Cooperation Studies, Kobe University.
Assistant Professor, Institution of Education and Student Support, Wakayama University.
I would like to thank Professor Keiichi Ogawa for his support for and advice on this research. Also I would
like to express my gratitude to the participants in the 10th African Education Research Forum（Japan）
who gave me various thoughtful comments on this study.
Journal of International Cooperation Studies, Vol.21, No.1（2013.7）

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Patrinos（2011, p. 95）categorized SBM into three levels of autonomy: strong,intermediate and weak. Strong SBM is defined as“almost full control of schools bycouncils, parents, and school administrators（including full choice through creation of
new public schools）or high degree of autonomy given to councils over staffing andbudgets”. Under the intermediate SBM,“（school）Councils have authority to set
curricula but limited autonomy regarding resources”. With the weak SBM,“School
councils（are）established but serve mainly in an advisory role”.
The second component in SBM is divided into four key dimensions（Barrera-Osorio
et al., 2009）. The first one is administrative-control SBM in which the authority isdevolved to the school principal. The second one is professional-control SBM in whichteachers hold the main decision-making authority so as to use their knowledge of theschool and its students. The third one is community-control SBM in which parents orthe community have the major decision-making authority. The forth one is balancedcontrol SBM in which decision making authority is shared by parents and teachers.
Rigorous studies have been conducted to assess the effect of SBM over many
countries. Most studies found measurable effects of SBM on student performance but
some found small or no effects. Also there are few studies on SBM in African countries
on this topic even though this system is prevalent throughout Africa.
Two African countries, Botswana and Ghana, participated in TIMSS 2007 whichcontains information on parental involvement in school management and school
activities. The research in this paper explores the Botswana TIMSS 2007 data andanalyzes the effect of parental involvement on math and science test scores in juniorsecondary school. The next section briefly summarizes the school-based management
in Botswana.
2. School-based Management in Botswana
Botswana is a middle income country who has been active in empoweringparental and community within its schools. In fact, the 1994 Revised National Policy on
Education encourages the involvement of all stakeholders in basic education（Ministryof Education, Botswana, 2000; UNESCO-IBE, 2010）. In primary schools, local
communities are asked to participate in Parent-Teacher Associations, while community
junior secondary schools have a Board of Governors（school committee）working with

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school management teams and operate the school together（UNESCO-IBE, 2006;
UNESCO-IBE, 2010; Isaacs, 1997）. In fact, in the 1994 Revised Policy on Education, allsecondary schools were asked to have Boards of Governors appointed by communities
and approved by the Minister of Education（Ministry of Education, Botswana, 2001）.
According to Ministry of Education, Botswana（2001）, Boards of Governors are
responsible for“the appointment of the ancillary staff as well as for the maintenance ofteachers’houses”（p. 14）. Boards can also raise funds to provide additional
infrastructure. In addition, schools can receive donations from private enterprises andorganizations who are in partnership with the Botswanan government. The SBM in
Botswana could be categorized as a strong/intermediate SBM according to the criteria
set by Bruns et al.（2011）. Also it is a balanced-control SBM according to the criteria
set by Barrera-Osorio et al.（2009）. However, in reality, the degree of parental andcommunity involvement in school management varies by school. Usually there is no
general consensus on how to involve in the SBM among schools, parents andcommunities（Boaduo, Milondzo, & Adjei, 2009）.
3. Objective of the Study, Research Question and the Significance of the Study
Using the TIMSS 2007 data, containing some information on parental involvementin junior secondary schools, this study provides evidence of parental involvement
among junior secondary schools in Botswana and its effect on student achievement.
Since TIMSS 2007 does not have information on community involvement in school but
parental involvement in school, this study focuses on parental involvement and its
effect on student achievement at junior secondary school. Parents are an importantcomponent of SBM as they are beneficiaries of education as well as students. The key
research question of the paper is“To what extent does parental involvement affectmath and science test scores in junior secondary school in Botswana?”.
Few studies have been conducted on SBM practices in African countries; in fact
worldwide, Africa is under represented. According to Bruns et al.（2011）,there is only
one study on Kenya regarding the effect of SBM on student achievement in basic
education（Duflo, Dupas, & Kremer, 2007）, while there are five studies on five Asian
countries and fifteen studies on thirteen Latin American countries. This study is
relevant as there has not been a rigorous analysis on the impact of SBM and parental

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involvement on student achievement in basic education in Botswana.
4. Structure of the Paper
This article consists of seven parts. The first part explains the motivation andbackground of the study, the application of SBM in Botswana, the research question athand, and the related significance of the study. The second part examines previous
empirical studies on the impact of SBM on student achievement. The third part
explains the data and variables used in the research. The fourth section presents themethodologies utilized to estimate the effect of parental involvement in school
management and activities on student achievement. The descriptive statistics andresults are explained in the fifth and the sixth parts. Conclusions are discussed in theseventh.
II. Literature Review
SBM is now prevalent throughout the world and has been reported as being
effective in most studies. For instance, Jimenez and Sawada（1999）evaluatedcommunity-managed schools in El Salvador using the Heckman-type correction modeland found increased reading scores and decreased absenteeism. The Heckman-stylecorrection model was also employed by Di Gropello and Marshal（2005）to assess
Honduran schools and found slightly increased test scores and a slight decrease indropout rates. Duflo, Dupas, and Kremer（2007）conducted a randomized evaluation ofa project containing SBM components, which showed that SBM increased student testscores, lowered teacher absenteeism and slightly decreased dropout rates. Other
studies also showed a positive impact of SBM on student performance（e.g. Gertler etal., 2010. See more studies introduced in Bruns, et al., 2011）. Khattri et al.（2006）
evaluated a program in the Philippines by difference-in-difference and propensity scorematching and also found small positive effects of SBM on student test scores.
In contrast, some studies have found no positive effects of SBM. Gunnarsson,
Orazem, Sánchez, and Verdisco（2004）analyzed ten Latin American countries
employing the instrumental variable approach and found no influence of SBM on
student test scores. King, Orazem, and Gunnarsson（2003）examined a program in
Nicaragua using matching and panel data and found no positive impact of de jureThe Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 200799

autonomy, while real autonomy（hire/fire teachers）increased test scores（see more
examples in Bruns et al., 2011）.
The results of investigations in SBM are inconclusive. Most of studies foundpositive effects of SBM on student performance but a few found very small or no
impact of SBM. In fact, the study by King et al.（2003）suggests that the degree of
autonomy among schools and actual application of SBM methods improve student
achievement not legal system of SBM. As we see, there have not been many rigorous
empirical studies in many countries yet, especially in African countries. It is usually
very difficult to evaluate SBM because of the great variety of SBM projects andprograms, and the lack of data. Only some randomized projects were conducted to
examine the effect of SBM on student achievement so far. Most studies previously
conducted have relied on observational data. Most of the studies conducted quasiexperimental studies using either Heckman correction, instrumental variable approach,difference-in-difference, panel data, propensity score matching, or other matching
method.
III. Data
1. Trends in International Mathematics and Science Study（TIMSS）2007
Trends in International Mathematics and Science Study（TIMSS）is aninternational achievement test survey conducted by International Association for the
Evaluation of Educational Achievement（IEA）. It measures mathematics and scienceachievement at the fourth and eighth grades. TIMSS has been conducted every 4
years since 1995. For the study in 2007, 59 countries participated in the study
including Botswana（IEA TIMSS & PIRLS International Study Center, 2013）. This
study attempts to provide some evidence in Botswana using the TIMSS 2007 data,
which contains information on parental involvement in junior secondary schools.
Botswana joined TIMSS in 2003 and has continued its participation. The country
measured student achievement for 8th grade students, however, started to include thestudy of 4th grade students in 20111. The Botswana TIMSS 2007 data contains 3,601
students in 127 schools with parental involvement in school committees and 523
students in 20 schools without parental involvement in school committees.

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2. Dependent Variables and Independent Variables
The analysis uses math and science test scores for 8th grade students as
dependent variables. The study especially uses“standardized raw scores”instead ofplausible values used for international comparison because it is more appropriate when
we compare test scores of students within a country（Foy & Olson, 2009）.
The study employs several independent variables on parental involvement. The
independent variables of interest are（1）parental involvement in the schoolcommittee at the school level（whether parents are asked to serve on the schoolcommittee or not）,（2）degree of parental support for student achievement at theschool level（how much parents support student achievement within school）, and（3）degree of parental involvement in school activities at the school level（how muchparents involve in school activities）2. The variable（1）is a dummy variable in which 1means that parents are asked to serve on the school committee and 0 otherwise.
Variable（2）and（3）have a 5-point scale（very low=1, low=2, medium=3, high=4,
and very high=5）.
Other independent variables are student, household, school, teacher andcommunity characteristics. Student and family characteristics contains gender ofstudent（female=1, male=0）, language of test spoken at home（always=3, almost
always=2, sometimes=1, never=0）, dummy variables of mother and father’s tertiary
education attainment.
Variables across math and science teacher characteristics are gender, years ofexperience, teaching licensure, whether the teacher took a subject-specific major at apost-secondary level, whether the teacher majored in teaching the subject at a postsecondary level, completion of a 1st degree of theoretically based tertiary education,and completion of a 2nd degree of theoretically based tertiary education. Also pupilteacher ratio is included3.
School characteristics contain total enrollment of school, whether a student’sschool has more than 50% of students from economically affluent homes, and whether
a student’s school has more than 50% of students from economically disadvantaged
homes.
TIMSS 2007 has only one relevant community characteristics variable which is a
categorical variable of the size of the city where the school is located. The estimation

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uses the city size dummies（3000 people or fewer, 3001 to 15000 people, 150001 to
50000 people, 50001 to 100000 people, 100001 to 500000 people, more than 500000
people）.
IV. Methodologies
1. Baseline Model
The baseline model to estimate the effect of parental involvement on student
achievement is（4.1）Yi ＝α＋βPIi ＋ Xi' δ＋ ui
where Yi is math or science test scores, PIi is either（1）parental involvement in theschool committee at the school level,（2）parental support for student achievement at
the school level, or（3）parental involvement in school activities at the school level. Xi
is the set of control variables including student and family characteristics（gender,
language, mother’s education, father’s education）, teacher characteristics（age, gender,
teaching experience, education qualifications, pupil-teacher ratio）,school characteristics（total school enrollment, if the school has more than 50% of students from
economically affluent homes, if the school has more than 50% of students from
economically disadvantaged homes）, and community characteristics（the size of citywhere the school is located）. The model is estimated by ordinary least squares（OLS）
and propensity score matching.
2. Propensity Score Matching
In addition to the OLS, propensity score matching（PSM）is used to estimate theeffect of parental involvement on student achievement. PSM is used to deal with theendogeneity of parental involvement. Parental involvement is an endogenous variablebecause it could be affected by unobserved characteristics of student, parents, schools
and communities while these unobserved characteristics could affect student
achievement. For example, a school with a motivated and skilled principal probably
encourages more parental involvement in school while the principal with better school
management skill could improve student test scores as well. In this case we do notknow which one, parental involvement itself or the principal’s school management, that
improves students test scores. Therefore we need to control for this endogeneity（see

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Wooldridge, 2010 for more details on endogeneity）.
The propensity score is the conditional probability of assignment to a particulartreatment given observed covariates（Rosenbaum & Rubin, 1983）. PSM constructs astatistical comparison group based on the propensity score using observed
characteristics. Individuals in the treatment group are matched to individuals who are
not in the treatment group according to the propensity score. The average treatment
effect of the program is estimated by calculating the mean difference in outcomes
across two groups.
Rosenbaum and Rubin（1983）showed that, under certain assumptions, matchingon the propensity scores P（X）＝ Pr（T ＝ 1 ¦ X）is as good as matching on observed
characteristics X. It is easier to match on P（X）than X because P（X）is one variable,
while X is a set of variables. The assumptions required to identify the program effectare（a）conditional independence and（b）the presence of a common support（World
Bank, 2010）. If external validity holds, we can estimate the average treatment effect（ATE）using PSM. However, researchers can usually ensure only internal validity sothat they can estimate the average treatment effect of the treated（ATT）instead of
ATE.
Conditional independence or unconfoundedness, according to Rosenbaum andRubin（1983）, means that given a vector of observable covariates X that are notaffected by treatment, potential outcomes Y are independent of treatment assignment
D. If Y（1）equals outcomes for participants and Y（0）outcomes for nonparticipants,
conditional independence implies（Π（4.1） Y（1），Y（0） D ¦ X

denotes independence）.

ΠThis suggests that participation in the program is based entirely on observed
characteristics. Rosenbaum and Rubin（1983）show that if potential outcomes are
independent of treatment conditional on covariates X, they are also independent oftreatment conditional on the propensity score P（D ＝ 1 ¦ X）＝ P（X）, i.e., the probabilityof an individual participating in a treatment given his/her observed covariates X.
Hence, if Eq.（4.1）holds, all biases due to observable characteristics can be removed
by conditioning on the propensity score（Imbens, 2004）.Therefore（4.2）Y（0），Y（1） D ¦ P（X）.
ΠTo estimate the ATT instead of the ATE, weaker assumptions are required

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103（4.3）Y（0） D ¦ X andΠ（4.4）Y（0） D ¦ P（X）ΠIn this study, average treatment effect on the treated is as follows.
（4.5）τATT ＝ E（τ¦ D ＝ 1）＝ E［Y（1）¦D ＝ 1］－ E［Y（0）¦D ＝ 1］
where τATT is defined as the test score differential between schools with the parental
involvement in the school committee（Board of Governors）and schools withoutparental involvement in the school committee. D ＝ 1 represents a school with parental
involvement in the school committee, D ＝ 0 represents schools without parental
involvement in the school committee, and Y is either math or science test scores. Given
the conditional independence that assumption holds and assuming additionally that
there is overlap between both groups, the PSM estimator for ATT can be written ingeneral as［Y（1）¦D ＝ 1, P（X）］－ E［Y（0）¦D ＝ 0, P（X）］（4.6）τATT ＝ EP（X）¦ D ＝ ｛E1
PSM

The PSM estimator is simply the mean difference in outcomes over the common
support, appropriately weighted by the propensity score distribution of theparticipants.
The advantage of PSM is that it does not necessarily require a baseline or panel
survey（World Bank, 2010）. PSM is based on very strong assumptions and possibly
leads to biased estimates（Heckman, Ichimura, and Todd, 1998; Shadish, Cook, &Campbell, 2002）. However, the study utilizes this method since neither proper
instruments nor other methods are applicable given the limited data. It is still worth
conducting the PSM in addition to the OLS to examine the effects of parental
involvement on student achievement.
V. Descriptive Statistics
Table 5.1 shows the descriptive statistics of the variables used in the analysis.
Since the study uses the standardized raw test scores, the mean and standard
deviation of math and science test scores are 50 and 10. 87% of schools of students inthe dataset ask parents to serve on the school committee, or 127 of schools in thesurvey ask parents to serve on the school committee. The average degree of parental
support for student achievement is 2.39 out of 5, while the average degree of parental
involvement in school activities is 2.33 out of 5.

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Female students account for 48% of all students. The measure for language of test
spoken at home is 1.51, which means many students do not speak languages of test
very often at home. 18% of mothers of students completed tertiary education, and 28%
of fathers completed tertiary education.
Gender parity of math and science teachers in junior secondary schools is almost
equal. 42% of math teachers, and 40% of science teachers in the data collected arefemale. Years of teaching experience of math and science teachers are 7.77 and 7.44
respectively. Almost all math and science teachers have a teaching license, while afewer number of teachers majored in the subject（math or science）or education of
the subject（math education or science education）. 74% of math teachers majored inmath and 61% of them majored in math education in post-secondary education. Also
69% of science teachers majored in science and 69% of them majored in scienceeducation in post-secondary education. Furthermore, 11% of math teachers completed
a 1st degree of theoretically based tertiary education, and 2% of them completed a 2nd
degree of theoretically based tertiary education or higher. In contrast, 74% of scienceteachers completed a 1st degree of theoretically based tertiary education, and 39% ofthem completed a 2nd degree of theoretically based tertiary education or higher. Pupilteacher ratios are 37.4 for math and 37.0 for science respectively.
Average total enrollment of schools of students is 565.4. 17 % of students go toschool where more than 50% of students are from economically affluent homes, while
49% of students go to school where more than 50% of students are from economicallydisadvantaged homes. Also, 5% of students go to school in a city with 3,000 people or
fewer; 6% of students go to school in a city with 3001 to 15,000 people; 13% of students
go to school in a city with 150,001 to 50,000 people; 18% of students go to school in acity with 50,001 to 100,000 people; 33% of students go to school in a city with 100,001 to
500,000 people; and 25% of students go to school in a city with more than 500,000
people.
Figure 5.1 and Figure 5.2 show the distributions of students in schools with andwithout parental involvement in the school committee on mathematics and science testscores. The distributions overlap but the ones for students whose schools are withparental involvement in the school committee are skewed to the left:
Figure 5.3 and Figure 5.4 display parental involvement in the school committee

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versus math and science test scores. These figures do not show the positive
correlation between parental involvement and test scores but slightly negative
correlation. In contrast, a positive correlation is shown for parental support for student
achievement versus student test scores, and parental involvement in school activities
versus student test scores（Figure 5.5, 5.6, 5.7, 5.8）.
Table 5.1 Descriptive Statistics
Mean
Outcomes
Math score
50
Sciene score
50
Parental involvement measures
Parental involvement in school committees（yes=1, no=0）
0.87
Parental support for student achievement（very low=1, low=2, medium=3, high=4, very high=5） 2.39
Parental involvement in school activities（very low=1, low=2, medium=3, high=4, very high=5）
2.33
Student and family characteristics
Gender（female=1, male=0）0.48
Language of test spoken at home（always=3, almost always=2, sometimes=1, never=0）
1.51
Mother has completed tertiary education
0.18
Father has completed tertiary education
0.28
Math teacher characteristics
Math teacher gender（female=1, male=0）0.42Math teacher years of experience
7.77
Math teacher teachng licence
0.99
Math teacher majored in math in post-secondary education
0.74
Math teacher majored in education-math in post-secondary education
0.61
Math teacher completed the 1st degree of theoretically based tertiary education
0.11
Math teacher completed the 2nd degree of theoretically based tertiary education or higher
0.02
Pupil-math teacher ratio
37.43
Science teacher characteristics
Science teacher gender（female=1, male=0）0.40
Science teacher years of expericne
7.44
Science teacher licence
0.96
Science teacher majored in science in post-secondary education
0.69
Science teacher majored in science education in post-secondary education
0.69
Science teacher completed the 1st degree of theoretically based tertiary education
0.74
Science teacher completed the 2nd degree of theoretically based tertiary education or higher
0.39
Pupil-science teacher ratio
37.06
School Characteristics
Total enrollment
565.49More than 50% of students are from economically affluent homes
0.17
More thatn 50% of students are from economically disadvantaged homes
0.49
Communiyty characteristics : cize of city
3000 people or fewer
0.053001 to 15000 people
0.06
15001 to 50000 people
0.1350001 to 100000 people
0.18
100001 to 500000 people
0.33
More than 500000 people
0.25
Note: SD means standard deviation.

SD
10
10
0.33
1.03
0.90
0.50
0.88
0.39
0.45
0.49
5.08
0.08
0.44
0.49
0.31
0.14
5.19
0.49
6.13
0.50
0.46
0.46
0.74
0.77
5.41
176.10
0.38
0.50
0.22
0.24
0.34
0.38
0.47
0.47

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Figure 5.1 Distributions of Students in Schools with and without Parental Involvement in the
School Committee on Average Mathematics Test Scores

Figure 5.2 Distributions of Schools with and without Parental Involvement in the School
Committee on Average Science Test Scores

The Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 2007

Figure 5.3 Math Test Scores Vs. Parental Involvement in the School Committee

Figure 5.4 Science Test Scores Vs. Parental Involvement in the School Committee

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Figure 5.5 Math Test Scores Vs. Parental Support for Student Achievement

Figure 5.6 Science Test Scores Vs. Parental Support for Student Achievement

The Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 2007

Figure 5.7 Math Test Scores Vs. Parental Involvement in School Activities

Figure 5.8 Science Test Scores Vs. Parental Involvement in School Activities

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VI. Regression Results
1. Ordinary Least Square Results
Table 6.1 shows the OLS results on the effect of parental involvement in theschool committee on math and science test scores. Models in columns（1）and（4）only include student and family characteristics as covariates, while models in columns（2）and（5）contain teacher and school characteristics in addition to student andfamily characteristics. Models in columns in（3）and（6）add city size dummies ascommunity characteristics4.
The estimated effect of parental involvement in the school committee on math testscores is negative and statistically significant for Models（1）and（2）. Model（1）estimates that parental involvement in the school committee decreases the student
standardized math test score by 1.72 points. The impact gets statistically insignificant
when teacher/school characteristics and city size dummies are included in Models（2）and（3）. Model（3）is considered to be the best OLS estimate since it includes
variables which are likely to affect student test scores. In contrast, the estimated effectof parental involvement in school committee on science test scores is negative andstatistically insignificant in all models.
Table 6.2 displays the OLS results on the effect of parental support for student
achievement on math and science test scores. Again, Models（1）and（4）only include
student and family characteristics as covariates, while Models（2）and（5）contains
teacher and school characteristics in addition to student and family characteristics.
Models（3）and（6）also have city size dummies as community characteristics.
The effect of parental support for student achievement on math test scores ispositive and statistically significant for Model（1）; one point increase in parental
support for student achievement increases the student standardized test scores by
1.10 points for math. The effect gets statistically insignificant in models with teacher
and school characteristics, and with teacher/school characteristics and city size
dummies. Also, Model（4）suggests that a one point increase in parental support for
student achievement increases science test score by 1.03 points. The effects are
positive but statistically insignificant in Models（5）and（6）with teacher, school, andcommunity characteristics as well.
Table 6.3 outlays the OLS results on the effect of parental involvement in school

The Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 2007111

activities on math and science test scores. Again, Model（1）shows that the effect ofparental involvement in school activities is positive and statistically significant; onepoint increase in parental involvement in school activities is associated with 0.54 points
increase in student math test scores. However, in Models（2）and（3）, the impact getsstatistically insignificant. In Model（4）a one point increase in parental support ofstudent achievement estimated an increase science test scores by 0.72 points. The
effects become statistically insignificant in Models（5）and（6）when teacher, school,
and community characteristics are added.
In sum, the OLS results show that parental involvement in school committee,
parental support for student achievement and parental involvement in school activities
have no significant effect on student math and science test scores.
Another important finding is that both mother’s and father’s tertiary education
have significantly positive impacts on math and science test scores across all models,although they are not the variables of interest in this research. For example, in Models（3）and（6）in the OLS results on the effect of parental involvement in schoolcommittees（Table 6.1）, if the mother has completed a tertiary education, student testscores increase by 1.67 points and 2.35 points for math and science respectively, whilestudent math and science test scores increase by 1.41 points and 1.47 points
respectively if the father has completed a tertiary education. The OLS results on theeffect of parental support for student achievement and the effect of parental
involvement in school activities also show a similar effect of mother and father’stertiary education attainment（Tables 6.2 and 6.3）.
2. Propensity Score Matching Results
In order to tackle the endogeneity problem of parental involvement in the schoolcommittee, propensity score matching（PSM）is used. Because the PSM compares theaverage treatment effect on the treated, we can only look at the effect of parental
involvement in school committees as a dummy variable. The effect of parental support
for student achievement and parental involvement in school activities are notestimated by PSM because these variables are discrete variables with more than two
categories.
Table 6.4 show the effect of parental involvement in the school committee on math

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and science test scores estimated by PSM. The PSM estimations indicate that there is
no statistically significant impact of parental involvement in school committee on mathand science test scores. Parental involvement in school committee is associated with a
2.29 point decrease in student math test scores but it is statistically insignificant. Also
parental involvement in school committee is associated with a 2.57 point decrease in
student science test scores and again this is statistically insignificant.
Table 6.1 The Effect of Parental Involvement in School Committees on Math and Science Test
ScoresParental involvement in school committee
Student and family characteristics
Gender（female=1, male=0）
Language of test spoken at home
Mother has completed tertiary education
Father has completed tertiary education
Math or science teacher characteristics
Teacher gender
Teacher years of experience
Teacher teachng licence
Teacher majord in math/science in post
secondary education
Teacher majored in math educaiton orscience educaiton in post-secondary education
Teacher completed the 1st degree oftheoretically based tertiary education
T e a c h e r c o m p l e t e d t h e 2n d d e g r e e o ftheoretically based tertiary education or higher
Pupil teacher ratio in math or science class
School characteristics
Total enrollment（1）－1.72**（0.65）

Math
（2）
－1.43
（0.82）（3）－0.78（0.85）（4）－1.25（0.65）

Science
（5）
（6）
－0.78
－0.74
（0.76） （0.81）－0.92*（0.41）
0.76**（0.23）
3.90***（0.59）
2.19***（0.52）－0.98*（0.45）
0.25（0.25）
2.11**（0.66）
1.53**（0.58）－0.93*（0.45）
0.21（0.26）
1.67*（0.67）
1.41*（0.58）－1.01*（0.41）
0.60*（0.23）
4.32***（0.59）
1.76***（0.52）－0.96*（0.47）
0.36（0.26）
2.60***（0.69）
1.39*（0.59）－0.88（0.47）
0.35（0.27）
2.35***（0.69）
1.47*（0.60）

1.37**（0.47）
0.028（0.06）－14.4***（2.98）
0.17（0.54）
0.21（0.49）
3.50***（0.92）
7.39***（2.21）－0.17***（0.05）

1.20*（0.48）－0.01（0.06）－13.5***（2.97）
0.19（0.56）
0.64（0.50）
4.57***（0.98）
7.19**（2.23）－0.03（0.05）

0.59（0.49）
0.11*（0.05）（1.09）（1.59）
0.091（0.58）
0.56（0.60）－0.62（0.43）
1.38**（0.45）－0.19***（0.05）

0.72（0.51）
0.083（0.05）（1.18）（1.61）－0.018（0.59）
0.6（0.62）－0.59（0.45）
1.09*（0.47）－0.14*（0.06）

0.0022 －0.0012（0.002） （0.002）
2.73***
1.38（0.74） （0.77）－1.19*－1.29*（0.52） （0.54）

More than 50% of students are from
economically affluent homes
More than 50% of students are from
economically disadvantaged homes
Community characteristics
City size dummies
Yes
Constant
49.0***
67.9***
63.0***
48.8***（0.75） （3.28） （3.41） （0.75）
R squared
0.064
0.17
0.2
0.061
Number of observations
2057
1526
1464
2057
Notes: * p<0.05, ** p<0.01, *** p<0.001. Robust standard errors are in parentheses.

－0.00062 －0.0022（0.002） （0.002）
3.77***
3.46***（0.76） （0.79）
－0.69
－0.71
（0.56） （0.56）
Yes
55.6***
54.9***（2.66） （2.72）
0.14
0.15
1484
1460

The Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 2007

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Table 6.2 The Effect of Parental Support for Achievement on Math and Science Test Scores（1）
Parental support for student achievemnet 1.10***（0.21）
Student and family characteristics
Gender（female=1, male=0）－0.97*（0.41）
Language of test spoken at home
0.70**（0.23）
Mother has completed tertiary education
3.80***（0.59）
Father has completed tertiary education
2.07***（0.52）
Math or science teacher characteristics
Teacher gender
Teacher years of experience
Math teacher teachng licence
Teacher majord in math/science inpost secondary education
Teacher majored in math educaiton orscience educaiton in post-secondary education
Math teacher completed the 1st degree oftheoretically based tertiary education
Math teacher completed the 2nd degree oftheoretically based tertiary education or higher
Pupil teacher ratio in math or science class
School characteristics
Total enrollment
More than 50% of students are from
economically affluent homes
More thatn 50% of students are from
economically disadvantaged homes
Community characteristics
City size dummies
Constant

Math
（2）
0.33
（0.24）（3）
0.35（0.25）（4）
1.03***（0.21）

Science
（5）
（6）
0.45
0.43
（0.26） （0.27）－0.94*（0.45）
0.26（0.25）
2.25***（0.66）
1.51**（0.58）－0.94*（0.46）
0.2（0.26）
1.66*（0.68）
1.43*（0.59）－1.03*（0.41）
0.54*（0.23）
4.11***（0.59）
1.70**（0.52）－0.94*（0.47）
0.37（0.27）
2.65***（0.69）
1.39*（0.60）－0.87（0.48）
0.37（0.27）
2.41***（0.70）
1.46*（0.61）

1.44**（0.48）
0.041（0.05）－14.5***（2.96）
0.14（0.54）
0.21（0.49）
3.74***（0.91）
6.53**（2.20）－0.19***（0.05）

1.29**（0.49）－0.015（0.06）－13.3***（2.95）
0.2（0.56）
0.6（0.50）
5.09***（1.05）
6.73**（2.24）－0.047（0.05）

0.7（0.49）
0.099*－1.48
1.15*（0.46）
0.13（0.57）
0.65（0.60）－1.48（1.60）－0.54（0.44）－0.20***（0.05）

0.82（0.51）
0.074（0.05）
0.86（0.49）－0.028（0.59）
0.66（0.62）－1.57（1.62）－052（0.46）－0.16**（0.06）

0.0023 －0.0011（0.002） （0.002）
2.53***
1.01（0.75） （0.79）－1－1.19*（0.53） （0.54）

Yes
45.0***
66.3***
61.9***
45.4***（0.65） （3.25） （3.38） （0.65）
R squared
0.076
0.17
0.21
0.072
Number of observations
2041
1510
1427
2041
Notes: * p<0.05, ** p<0.01, *** p<0.001. Robust standard errors are in parentheses.

－0.00097 －0.0025（0.002） （0.002）
3.53***
3.22***（0.78） （0.81）
－0.59
－0.62
（0.56） （0.57）

54.8***（2.63）
0.14
1463

Yes
54.2***（2.69）
0.15
1439

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Table 6.3 The Effect of Parental Involvement in School Activities for on Math and Science Test
ScoresParental involvement in school activities
Student and family characteristics
Gender（female=1, male=0）
Language of test spoken at home
Mother has completed tertiary education
Father has completed tertiary education
Math or science teacher characteristics
Teacher gender
Teacher years of experience
Math teacher teachng licence
Teacher majord in math/science in post
secondary education
Teacher majored in math educaiton orscience educaiton in post-secondary education
Math teacher completed the 1st degree oftheoretically based tertiary education
Math teacher completed the 2nd degree oftheoretically based tertiary education or higher
Pupil teacher ratio in math or science class
School characteristics
Total enrollment

（1）
0.54*
（0.24）

Math
（2）
0.012
（0.26）（3）
0.19（0.27）（4）
0.72**（0.23）

Science
（5）
（6）
0.33
0.34
（0.28） （0.28）－0.92*（0.41）
0.73**（0.23）
3.79***（0.59）
2.17***（0.52）－0.93*（0.45）
0.27（0.25）
2.06**（0.66）
1.57**（0.57）－0.94*（0.46）
0.2（0.26）
1.45*（0.68）
1.45*（0.59）－1.03*（0.41）
0.55*（0.23）
4.02***（0.59）
1.72***（0.52）－1.01*（0.47）
0.37（0.26）
2.43***（0.69）
1.32*（0.59）－0.95*（0.47）
0.36（0.27）
2.18**（0.70）
1.37*（0.60）

1.37**（0.47）
0.054（0.06）－14.7***（2.96）
0.033（0.54）
0.33（0.48）
3.67***（0.91）
6.84**（2.19）－0.18***（0.05）

1.15*（0.48）
0.024（0.06）－13.3***（2.96）
0.23（0.56）
0.77（0.50）
5.25***（1.05）
6.56**（2.23）－0.044（0.05）

0.62（0.49）
0.13*（0.05）
1.22**（0.45）
0.21（0.57）
0.56（0.60）－1.1（1.59）－0.65（0.44）－0.21***（0.05）

0.76（0.51）
0.11*（0.05）
0.86（0.47）
0.026（0.59）
0.46（0.63）－1.18（1.60）－0.73（0.47）－0.17**（0.06）

0.0023 －0.00093（0.002） （0.002）
2.91***
1.39（0.73） （0.77）－1.06*－1.10*（0.53） （0.54）

More than 50% of students are from
economically affluent homes
More thatn 50% of students are from
economically disadvantaged homes
Community characteristics
City size dummies
Yes
Constant
46.2***
66.9***
61.6***
46.1***（0.7）（3.27） （3.41） （0.7）
R squared
0.061
0.17
0.2
0.059
Number of observations
2048
1517
1434
2048
Notes: * p<0.05, ** p<0.01, *** p<0.001. Robust standard errors are in parentheses.

－0.00039 －0.0016（0.002） （0.002）
3.97***
3.70***（0.77） （0.79）
－0.47
－0.44
（0.56） （0.57）

54.5***（2.67）
0.14
1470

Yes
54.1***（2.74）
0.14
1446

The Effect of Parental Involvement on Student Achievement in Junior Secondary School: Examining Data from the Botswana TIMSS 2007

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Table 6.4 The Effect of Parental Involvement in School Committees, Estimated by Propensity
Score Matching

Parental involvement in school committee
Number of treated
Number of untreatedNote: Standard errors are in parentheses.

Math
（1）
－2.287（1.928）1433
179

Science（2）－2.569（2.748）1522
186

VII. Conclusions
Botswana has been encouraging parents（and communities）to become more
involved in school management and activities in junior secondary schools since
Revised National Policy on Education was released in 1994. However, no rigorousstudies exist that can assess the impact of the school-based management and parental
involvement on student performance. This study utilized TIMSS 2007 data to explore
the impact of parental involvement in school management and activities on student
math and science test scores in junior secondary schools.
This study could not find a systematic relationship between parental involvement
and test scores in both OLS and PSM models. As already suggested, the degree ofparental involvement and contents of activities they have conducted affect the qualityof education. If we had more information, we could explore the reasons for the noeffect of parental involvement but unfortunately, TIMSS did not collect sufficient dataon the details of SBM and parental involvement.
Furthermore, the issue of endogeneity has not been completely resolved yet
because we possibly have unobserved characteristics not included in the PSM model.
Also, the smaller number of students and schools without parental involvement onschool committees could be a reason for the statistically insignificant results in PSM
and OLS results on the effect of parental involvement in school committees.
Further study is needed to examine concrete data and employ othermethodologies such as instrumental variable approach and Heckman two-stepcorrection model.
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Notes
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The data from TIMSS 2011 was just released and this study was unable to include the data.
Further study will conduct research on Botswana using TIMSS 2011.
２ The exact question wordings asked to schools are as follows. Parental involvement in schoolcommittees:“Does your school ask parents to serve on school committee（e.g., select school
personnel, review school finances）?”Parental support for student achievement:“How would
you characterize parental support for student achievement?”Parental involvement in school
activities:“How would you characterize parental involvement in school activities?”
３ Pupil-teacher ratios for math and science are not exactly the characteristics of teachers but
they are included in this category, teacher characteristics, as a matter of convenience.
４ A model in a specific column is called Model（column number）from the next paragraph.