Download School Resources, Parents and GDP: Shaping the Future of Education:

School Resources, Parents and GDP: Shaping the Future
of Education
Shazeen Dhanji
Monash University
Department of Economics, School of Business,
Monash University, Jalan Lagoon Selatan, Bandar Sunway,
46150 Selangor, Malaysia
Eduard Bomhoff
Monash University
Department of Economics, School of Business,
Monash University, Jalan Lagoon Selatan, Bandar Sunway,
46150 Selangor, Malaysia
&
Grace H.Y. Lee
Monash University
Department of Economics, School of Business,
Monash University, Jalan Lagoon Selatan, Bandar Sunway,
46150 Selangor, Malaysia

Corresponding author. E-mail address: [email protected]; phone: +60 3 5514 4907; fax:
+60 3 5514 6192/6194
1
Abstract
According to UNICEF there are 2.2 billion children in the world, out of which
every second child lives in poverty. Education can provide them with the
opportunity to improve their economic condition and prepare them for a
better life. In line with this vision, from the 1960s onwards many
governments have substantially increased funding of schooling by large
amounts; harder to measure is whether more inputs have also improved
quality of education. Notably, cognitive skills tests have indicated the need
for attention towards the quality of the education system in developing and
developed countries.
This research examines the relationship between education outcomes and
some important determining factors. Particularly, it aims to address the
following key questions: 1) To what extent do education resources and the
level of development of a country influence education outcomes? 2) How
important is teacher quality – in as far as we can measure it - for education
outcomes; and 3) Do parents have significant influence on the academic
achievement of their children?. Programme for International Student
Assessment (PISA) outcomes of comparable tests of 2000 and 2006 for all
countries for which these tests are available have been employed to
measure the quality of education. In addition, data from the two most recent
waves of the World Values Survey (WVS) and European Value Survey
(EVS) is used to explore some features of the parental attitudes that are
important for educational outcomes in the cross-sectional tests.
The results obtained show that increased resources and level of
development of a country have a positive influence on education outcomes,
albeit not a very strong relationship, signifying that other factors are more
important. The quality of education is heavily influenced by the manner of
public spending. Consistent with other studies, the findings suggest that
teacher quality is very crucial for student performance and also influences
the class size effect. Parental attitude towards important child qualities
appears to have a significant impact on children’s academic achievement.
The findings have important policy implications regarding parent awareness
programs, educational program development and government budget
allocation for education.
Keywords: PISA Test Scores, World Value Survey, Government, GDP, Teachers,
Quality Education
JEL Codes: I22, I24, I25, Z1
Field of Research: Development Economics, Education Development
1.0
Introduction
As per the United Nations Development Program, by end of the year 2003, around
113 million children around the world were not enrolled in school (Hillman & Jenkner,
2004); and 94 percent of these children were from developing countries (UNESCO,
2002). In order to remedy this deplorable situation, people at every level need to work
together, from world leaders, international organisations and governments to parents
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and every single individual in the soceity, to make education the tool to improve the
welfare of 2.2 billion (and growing) children in the world. The important policy
question that arisesfrom all this is how to provide education services to such a large
popluation and ensure acceptable quality levels.
This study aims to investiagte into the factors which influence education quality,
measured by test scores, in order to povide policy makers with the direction to
formulate programs and policies such as parent awareness programs, educational
program development and government budget allocation for education. Furthermore,
a comparison between several developing and developed countries is conducted to
provide valuable analysis for policy making.
The PISA database for international test scores has been employed for this study
with separate values for math, science and reading. Previous studies have combined
the subjects, providing aggregated values, and have also combined test scores from
other bodies such as TIMMS and PIRLS. This combination approach does not take
into account the differences in testing methods or the testing material and focus.
PISA measures education's application to real-life problems and life-long learning,
and tests skills and knowledge acquired at school, home and elsewhere; whereas
TIMMS and PIRLS only account for curriculum based skills and knowledge.
The impact of the role of parents on a child's test score in three different subjects
(Math, Science and Reading) is also determined in this study. The impact of
important child qualities, emphasised by parents, on international tests has been
examined in this study for the first time (previous studies have used the link to
examine the gender inequality in education). It signifies the importance of the link
between the home and school environment and the extent to which certain qualities
impact academic performance.
2.0
Literature Review
2.1
Education and Economic Growth
Human development is the backbone for sustained economic growth and therefore is
it important to develop a skilled and educated labour force capable of making
important decisions (Dowling & Valenzuela, 2010). The notion of knowledge-based
economy, based on production, distribution and use of knowledge and information, is
rapidly spreading across the globe; raising demand for highly skilled work force
(Dunning, 2002).
However, education development as well as economic growth is often compromised
due to inequality. A large proportion of the world’s population still resides in extreme
poverty; inequality of access to opportunities offered by society to the underprivileged
hampers them from improving their condition. Thus, to ensure equality and economic
growth the marginalised need to be brought to the mainstream by ensuring access to
basic education for everyone.
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2.2
Comparison of Developing and Developed Countries
Provision of basic education has been widely implemented in the developed world
and is increasingly being adopted in the developing world; however, there is a huge
gap between the two (Hanushek & Woessmann, 2007). Enrollment and completion
rates in developing countries are not comparable to those in developed countries
(Barro, 2001). Some countries, though, have managed to improve the level of
completion rates for primary education; Brazil for instance, improved from less than
50 percent in 1990 to more than 70 percent in 2000 (World Bank, 2003).
2.3
Quality of Education
Various international organizations conduct international tests to assess student
performance such as the International Association for the Evaluation of Educational
Achievement (IEA), the International Assessment of Educational Progress (IAEP)
and the OECD Program for International Student Assessment (PISA). The IEA and
IAEP tests are curriculum based which focus on mathematics and science but not
reading. On the other hand, the PISA tests focus on mathematics, science and
reading and are designed to test the application of knowledge of these subjects to
real life problems (Baldie et. al., 2007). The PISA tests give insight into the factors
that influence the development of skills, not only at school, but also at home and
elsewhere; and determine the interactions of those factors for policy making (OECD,
2004). Recently, the test scores have taken a downward trend in some countries
raising the issue of the quality of education being provided.
2.4
Government’s role in Education
Governments have the institutional capacity to make a change in the society by
providing access to education, at least at the basic level. The 1960s saw a turning
point in provision of education in developing and developed countries whereby
governments undertook rapid expansion of the public educational system in order to
provide educational opportunities to the majority of the population (Dowling
&Valenzuela, 2010). Many governments in developing countries have initiated the
Conditional Cash Transfer (CCT) program whereby they provide education and
health facilities to the underprivileged families (Aber & Rawlings, 2011). With the help
of such programs and an improvement in the quality of and expected returns from
public schooling, governments can ensure an educated nation, at least at the basic
level.
2.5
Parents role in Education
Parents have a very important and influential role in an individual’s life. The manner
of upbringing, parenting style and the home environment has a significant impact on
the way a child develops. Baumrind (1978) found that authoritative parenting enabled
children to develop into mature and independent people with a dynamic outlook of
life. In another study, Steinberg et al. (1992) found that authoritative parenting had a
positive impact on school involvement and results of individuals as their parents
provide emotional security and a sense of comfort and independence which helps
them succeed at school. Also, these parents provide explanation for their actions
which gives children a sense of awareness and understanding of their parent’s
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values and morals; thus, when children follow these values and morals they are in a
position to perform well at school (Durkin, 1995).
3.0
Methodology
The following equation is estimated:
Log(Ti) = β0 + β1 Q(w) + β2 AE + β3 Class_Ratio + β4 Log(GDP) + β5 Log(Gov_Exp)
Log(Ti) denotes the logarithm of the international test scores where i represents
math, science and reading.
Q(w): denotes quality of child
AE: Average years of total schooling for adults aged 25+ (represents teachers
education)
Class_Ratio: student to teacher ratio in secondary schools
Log(GDP): GDP per capita
Log(Gov_Exp): Government expenditure on education
3.1
Data
The variables employed in this study are:
test scores,
average years of total schooling, age 25+,
pupil-teacher ratio, secondary,
public expenditure on education as a % of GDP,
GDP per capita; and
child qualities.
The data in this study is analysed for the time period from 2000 and 2005 for 67
countries. Test scores data is obtained from the Programme for International Student
Assessment (PISA) database. The Barro Lee data set is used to collect data on
average years of total schooling (age 25+) which is used to proxy for the education of
the parents and teachers. Data on Pupil-teacher ratio in secondary level and Public
expenditure on education as % of GDP is obtained from the World Bank database.
The Penn World Table is used to attain data for GDP per capita, PPP (constant 2005
international $). Data on child qualities is obtained from the World Value and
European Value Survey database.
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4.0
Findings and Discussion
4.1
Regression Results for Test Scores
Table 1: OLS Regressions for Test Scores by Subject
(1)
(2)
(3)
(4)
(5)
Math
Science
Reading Math
Science
Constant
4.952***
5.147***
4.970***
5.077***
5.232***
(34.698)
(40.728) (39.265) (33.722) (41.468)
a
Child Quality
0.289***
0.201***
0.186***
0.186**
0.185**
(4.005)
(3.143)
(2.896)
(2.127)
(2.513)
Av. years of total
0.016***
0.017***
0.010*
0.018***
0.017***
schooling of adults
(2.761)
(3.268)
(0.073)
(2.858)
(3.292)
Pupil-teacher ratio,
-0.005**
-0.002
-0.001
-0.004*
-0.002
Secondary
(-2.172)
(-1.327)
(-0.611)
(-1.829)
(-1.150)
Log(GDP per capita) 0.085***
0.070***
0.086***
0.076***
0.061***
(5.171)
(4.794)
(5.893)
(4.168)
(4.012)
Log(Gov_Exp)
0.101**
0.082**
0.124***
0.087*
0.078*
(2.376)
(2.155)
(3.291)
(1.866)
(1.996)
No . of observations 67
67
66
67
67
2
Adjusted R
0.703
0.676
0.695
0.651
0.659
(6)
Reading
5.047***
(39.118)
0.126*
(1.691)
0.011**
(2.002)
-0.001
(-0.429)
0.080***
(5.141)
0.115***
(2.924)
66
0.668
a
Dependent variables are logarithm of math, science and reading.
The variable of child quality
represents values encouraged by parents. Two of the most significant qualities have been tested for
their impact on student performance. In columns (1), (2) and (3) the child quality of thrift saving money
and things is regressed on the test scores while in columns (4), (5) and (6) the child quality of
determination and perseverance is tested in the above equations. Absolute values of t-statistics are
2
reported in parentheses. The adjusted R values apply to each equation individually. Significance
*
***
**
*
levels are denoted by (significant at 1% , 5% , 10 % ).
The table above illustrates the results of the regressions for the Math, Science and
Reading test scores. The results, as expected, show a positive relationship of each
input (apart from pupil-teacher ratio) on test scores. The variables are mostly
significant and indicate a strong influence on student achievement. The OLS
regressions of log test scores, in all six models above, test the same input variables,
except child quality, whereby two different child qualities are tested on each subject.
The child quality of thrift saving money and things, considered important by parents,
has a highly significant and positive relationship with all three subject test scores.
Development of this quality tends to improve test scores by 33.5, 22.26 and 20.44
percentages on average for math, science and reading respectively. The child
quality of determination and perseverance regressed on test scores shows that
encouragement of this quality by parents tends to enhance the child’s cognitive ability
in math, science and reading by 20.44, 20.32 and 13.43 percentage respectively on
average.
Adult education, measured by average years of total schooling for individuals aged
25 and above, has a significant positive effect on test scores. It is taken as a proxy to
measure the education level of teachers, indicating teacher quality. An increase in
the average years of total schooling of adults by one year is estimated to raise math
6
test scores in the range of 1.6 to 1.8 percentage points on average, holding all other
variables constant. Similarly, science scores are estimated to increase by about 1.7
percentage points and reading scores between 1 and 1.1 percentage points on
average. Therefore, the results propose that the education of teachers, as well as
parents, is important for children’s academic performance.
Pupil-teacher ratio has a negative relationship with test scores, suggesting that
smaller classes are associated with better student performance. The estimated
coefficients in column 1 and 4 imply that a reduction by one student in the class can
improve the math test score between 0.399 to 0.498 percentage points on average,
keeping all other variables constant. Similarly, science scores and reading scores are
estimated to increase by about 0.199 and 0.099 percentage points respectively on
average. However, the coefficients for science and reading are not significant.
The positive coefficients on the log of per capita GDP suggests that secondary
school children from higher income countries tend to achieve higher test scores,
holding other factors that influence student achievement constant. The estimated
coefficients for all three subjects suggest that a 10 percentage point increase in per
capita GDP increases test scores between 0.73 to 0.81, 0.58 to 0.67 and 0.77 to 0.82
percentage points for math, science and reading respectively on average. This result
implies that the level of development of a country (also reflecting parents income
level) has a strong positive effect on children’s academic performance. The mean
value of math test score in the sample is 469.2114 points, so a 10 percent increase in
GDP per capita would improve math test score from the mean level to 472.8 points.
The log of Government Expenditure on education as a percentage of GDP is also
indicated to have a significant and positive relationship with the test scores. Holding
other factors that influence student achievement constant, a 10 percentage point
increase in Government Expenditure increases test scores between 0.83 to 0.97,
0.75 to 0.78 and 1.1 to 1.2 percentage points for math, science and reading
respectively on average.
7
4.2 Analysis of Variables for Developing and Developed Countries
Table 2: Correlation Table
Developed Countries
Reading Math
Science
0.323**
0.349**
Av. Years of total schooling of 0.190
adults
0.537***
0.489*** 0.472***
Pupil-teacher ratio, Secondary
Developing Countries
Reading Math
Science
0.523***
0.601***
0.654***
-0.318
-0.418**
GDP per capita
Governmnet
expenditure
on
education
Independence(Q1)
Hard work(Q2)
Feeling of responsibility(Q3)
Imagination(Q4)
Tolerance and respect for other
people(Q5)
Thrift
saving
money
and
things(Q6)
Determination perseverance(Q7)
Religious faith(Q8)
-0.044
0.009
-0.111
0.624***
0.518***
0.563***
0.377***
0.280*
0.161
0.389*
0.225
0.294
0.270*
0.411***
0.389***
0.195
0.299
0.284
-0.325**
-0.269*
-0.220
0.300
0.485**
0.446**
0.292*
0.289*
0.214
0.057
-0.022
-0.019
0.542***
0.430***
0.336**
-0.377*
-0.465**
-0.441**
0.275*
0.154
0.104*
-0.008
-0.120
-0.115
0.078
0.202
0.157
0.448**
0.541***
0.505***
0.322**
0.336**
0.400***
0.382**
0.500***
0.556***
-0.227*
-0.034
0.383***
-0.075
-0.593***
Unselfishness(Q9)
Obedience(Q10)
0.475***
-0.027
0.638***
-0.365*
0.604***
-0.310
-0.135
-0.215
-0.166
-0.511*
-0.380*
0.587***
0.622*** 0.586***
Note: Significance levels are denoted at the 1% ***, 5%** and 10%* levels. Q1-Q10 represents the
variable of Child Quality.
Table 2 indicates the relationship between the dependent and independent variables
for developed and developing countries. The correlation values indicate how strongly
pairs of variables are related. The significance levels are also specified at 1%, 5%
and 10 % levels indicating whether a variable is significantly related to another and at
what level.
Average years of total schooling of adults, the proxy for teacher quality, indicates how
important teachers’ education level is for the academic performance of students. This
variable also represents the education level of parents, signifying the relation
between parents and children’s education. In developed as well as developing
countries average years of total schooling of adults has the most significant and
positive association with science scores, with correlation coefficients of 0.35 and 0.65
respectively.
Clearly, the association in developing countries is much greater, suggesting that
higher teachers’ and parent’s education level in developing countries can be
associated with improvement in the education outcomes of students by a significant
amount. This analysis highlights the immense importance of teacher quality as one of
the most imperative input variable in the education system.
Pupil-teacher ratio is a highly debatable variable in relation to its significance to
education outcomes. The output here suggests that it has a highly significant and
8
positive relationship with all three subject scores in developed countries. On the
contrary, there is a negative relationship between the pairs of variables in developing
countries, as indicated by the correlation coefficients with the largest negative
association with math scores.
The correlation coefficient for GDP per capita in developed countries shows an
unexpected sign for reading and science scores indicating a negative relationship
with these scores. However, the coefficients are insignificant for all three subjects;
hence there is insufficient evidence to draw any conclusions. On the other hand the
correlation coefficient for math, science and reading is highly significant and positive
for developing countries with the largest association of 0.62 with reading scores.
The correlation coefficient for government expenditure on education appears to be
significant only for the reading and math scores for developed countries; and reading
only for developing countries. The correlations also seems to be weak indicating that
for the sample of countries selected, government spending on education is not of
much significance compared to other factors which may be of higher significance to
education outcomes. This confirms results from previous studies, whereby, public
spending has not led to a significant improvement in education outcomes.
From amongst the 10 child qualities, the qualities of imagination and thrift saving
money and things have the highest significant and positive correlation value for
reading and math scores in developed and developing countries respectively. On the
other hand, science scores are highly associated with the quality of determination
and perseverance relative to the other qualities in both developing and developed
countries. Although highly significant, as evident these associations are just
moderate. There appears to be an interesting observation from the signs of the
correlation coefficient. Apart from the qualities of independence, thrift saving money
and things, and determination and perseverance the rest of the qualities have a
negative relationship with the test scores either for developed or developing
countries, or both.
Studies indicate that parents from the working class prefer the development of
obedience in their children as opposed to the middle class parents who give more
importance to the independence of a child (Alwin, 1988; Gecas, 1979; GrimmThomas & Perry-Jenkins, 1994; Kohn, 1977; Spade, 1991, as cited in Xiao, 1999).
According to Kohn (1977, as cited in Xiao, 1999) emphasis on independence enables
an individual to grow and rise to a higher social class whereas obedience restricts
this growth.
This analysis is also evident from the results obtained in this study, whereby, the
quality of independence is positively associated with the test scores in both groups of
countries, but only significant for developed countries. Alternatively, obedience has a
negative correlation with the test scores in both groups of countries, indicating that an
increase in this quality can hamper development.
The comparison between developing and developed countries with respect to the
above mentioned variables can further be elaborated by the use of the descriptive
statics presented in Table 3A and 3B.
9
Table 3A: Descriptive Statistics for Developing Countries
Variables
Mean
Science
Math
Reading
424.022
411.200
413.676
6
8.373
Av. Years of total schooling of adults
Mod
e
393
370
393
Maximum
489.544
486.421
479.4918
Minimum
333.000
292.000
327
Std.
Dev.
36.862
46.393
35.06857
11.585
4.765
1.714
29.353
9.519
5.623
13240.45
0
5.359
2920.630 2845.642
2.500
0.839
N/A
0.29
0.87
0.76
0.18
0.68
0.820
0.910
0.850
0.320
0.840
0.290
0.190
0.610
0.060
0.530
0.160
0.262
0.068
0.071
0.087
0.38
0.25
0.18
0.33
0.53
0.580
0.570
0.910
0.610
0.640
0.150
0.200
0.090
0.090
0.150
0.131
0.103
0.254
0.148
0.151
N/A
Pupil-teacher ratio,Secondary
15.552
N/A
GDP per capita
8491.13
6
on 3.976
Governmnet
expenditure
education
Independence
0.472
Hard work
0.566
Feeling of responsibility
0.756
Imagination
0.203
Tolerance and respect for other 0.673
people
Thrift saving money and things
0.385
Determination perseverance
0.382
Religious faith
0.379
Unselfishness
0.321
Obedience
0.418
N/A
*No of observations: 23
10
Table 3B: Descriptive Statistics for Developed Countries
Variables
Science
Math
Reading
Av. Years of total schooling of adults
Pupil-teacher ratio,Secondary
GDP per capita
Mean
504.015
499.536
496.236
10.284
12.160
28290.79
Mode
507
504
519
12.25
13.92
4.42
Maximum
563.000
557.000
556.000
13.092
21.020
71160.50
Minimum
443.000
446.000
441.000
7.222
7.138
11500.59
Governmnet expenditure on education
Independence
Hard work
Feeling of responsibility
Imagination
Tolerance and respect for other people
Thrift saving money and things
Determination perseverance
Religious faith
Unselfishness
Obedience
4.988
0.565
0.448
0.779
0.246
0.740
0.391
0.418
0.193
0.308
0.277
31610.63
0.69
0.62
0.9
0.25
0.83
0.43
0.45
0.17
0.12
0.14
8.290
0.830
0.860
0.920
0.570
0.940
0.730
0.670
0.530
0.600
0.14
3.348
0.230
0.020
0.560
0.070
0.500
0.100
0.250
0.050
0.050
0.050
Std. Dev.
25.646
28.505
24.396
1.428
2.799
11379.4
6
1.064
0.171
0.240
0.091
0.113
0.115
0.119
0.118
0.128
0.144
0.118
*No. of Observations: 43 (Reading), 44 (Science and Math)
Note: Data Set Restricted to Countries with comparable PISA Scores and WVS/EVS data. Mode
indicates the most frequently occurring value.
The average science, math and reading scores for developing countries in the
sample are 424, 411 and 414 points; with standard deviations of 37, 46 and 35
points; whereas, the average scores recorded for developed countries are 504, 500
and 496 points with standard deviations of 26, 28 and 24 points respectively. On
average, developed countries have higher test score levels in all three subjects
compared to developing countries. Relative to the other two subjects, developing
countries have the lowest score in math while developed countries score low in
reading. The difference in mean math score is observed to be the largest between
the two groups of countries.
Also, it can be concluded that adults have greater average years of total schooling in
developed countries with slightly less variation around the mean compared to
developing countries. This is one of the most important input variables, in terms of
school and family resources, which dictates the education performance of students.
Another school resource employed in this study is the pupil-teacher ratio at
secondary level which indicates the number of students per teacher in a class. On
average, there are around 16 students per teacher in secondary classes in the
selected developing countries with the maximum number of up to around 29
students. On the other hand, in developed countries there are around 12 students
per teacher with the maximum number of students being 21.
Apart from the school resources, the GDP per capita also tends to influence the
educational performance of students in a country. The average value is around
28290 units of per capita GDP for developed countries; however, as mentioned
11
earlier, GDP per capita does not have a significant relationship with student
performance in the selected developed countries. Conversely, it has a highly
significant association, as mentioned earlier, with test scores in developing countries
with a value of around 8491 units per capita GDP for the combined time period of
2000 and 2005.
The average government expenditure on education is around 4% of GDP, with the
highest proportion of around 5% in the selected developing countries and 5% of GDP
with highest proportion of around 8% in the selected developed countries. The
variation around the mean is similar for both groups of countries.
The use of the variable of child quality is a different approach in assessing the effect
of family resources on PISA test scores compared to previous studies. This study
employs 10 distinctive qualities to ascertain which qualities significantly influence
education outcomes of students. Figures 2A and 2B display an overall representation
of this difference.
12
Figure 2A: Bubble Graphs representing the Mean and Mode values for
Developing Countries
Figure 2B: Bubble Graphs representing the Mean and Mode values for
Developed Countries
Developing Countries
Developed Countries
1
1
Q2
0.87
0.9
0.8
0.6
MODE
MODE
Q1
0.69
0.7
Q5
0.68
0.6
Q10
0.53
0.5
0.4
Mode values
Q6
0.38
Q1
0.29
0.3
0.2
Q7
0.25
Q4
0.18
Q9
0.33
0.3
0
6
QUALITY
8
10
12
Q7
0.45
Q4
0.25
0.2
Q8
0.18
0
4
Q6
0.43
0.4
0.1
2
Q2
0.62
0.5
0.1
0
Q5
0.83
0.8
Q3
0.76
0.7
Q3
0.9
0.9
0
2
4
Mode values
Q8
Q10
0.17 Q9
0.14
0.12
6
8
10
12
QUALITY
Bubble charts are commonly used to understand social relationships; and in this study the charts represents the relationship
between the mean and mode values of the child qualities (refer to Appendix 1 for the details of the child qualities represented in the
figures as Q1-Q10). The values inside the bubbles indicate the mode values for each quality while the size of the bubble represents
the mean values (shown in Tables 3A and 3B).
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From figure 2A it can be noticed that the smallest bubble corresponds to the smallest
mean value of 0.203(Q4), suggesting that on average around 20% of parents in
developing countries consider the quality of imagination (Q4) to be important. In this
group, mostly 18% (mode) of the parents from most of the countries valuate
imagination as an important quality for children. Conversely, about 25% (mode) of the
parents in most developed countries place importance on imagination (Q4) as
indicated in figure 2B; where the average percentage of parents valuating this quality
is approximately 25 (mean).
Upon comparing the modes, it is identified that the largest difference between the two
groups of countries, in terms of parent’s valuation of the qualities, is for the quality of
independence (Q1). About 69% of parents in most developed countries regard
independence as important, as opposed to most developing countries where only
29% of parents emphasise on the quality. These differences arise due to many
reasons such as influence of cultural history and social systems due to which the
characteristics valued in children differ amongst societies (Xiao, 1999). Many
societies in developed countries are individualistic while those in developing are
collectivist. This inherent cultural framework in the society formulates the home
environment which determines the adoption of values and qualities by a child.
5.0
Conclusion
The purpose of the study is to investigate the impact of teacher quality, pupil-teacher
ratio, government expenditure on education, GDP per capita and child quality on
international test scores. The results obtained identify the factors that significantly
influence the quality of education. From the OLS regression analysis, as expected,
there is a positive relationship between each input (apart from pupil-teacher ratio)
and test scores. The negative impact of an increase in class size on education
outcomes strengthens part of the argument in the extant literature regarding the
influence of this variable on the education of students. Child qualities provide insight
into the link between the home and school environment, a relationship not examined
before in this approach. There are other factors such as the health factor, not taken
into account in this study, which can provide more meaning to the variations in the
test scores. Important policy implications arise from the results obtained from the
study, including programs to reduce the pupil teacher ratio in developing countries.
This can be done by increasing or effectively allocating the existing government
budget on education towards productive inputs, such as improving teacher training
programs, in order to increase the number of trained teachers, and thus, provide
students in developing countries more attention in class to improve their learning
outcomes. Also, teachers and heads of schools should be able to make important
decisions like setting education attainment targets instead of reforms enforced by the
government. They are in a better position to set targets for the school based on the
level of resources and performance levels of the students. This increases
accountability of teachers who then exert more effort to improve the class room
learning process.
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Reference List
Aber, L and Rawlings, LB 2011, North-South knowledge sharing on incentive-based
conditional cash transfer programs, Social Protection Discussion Papers.
Assembly, UNG 1948, ‘Universal declaration of human rights’, Resolution adopted by
the General Assembly, Vol. 10, No. 12.
Baldie, S, Jin, Y, Skerner, M, Green, P, Hergel, D and Xie, H 2007, Highlights from
PISA 2006: Performance of U.S. 15-year-old students in Science and Mathematics
Literacy in an International Context (NCES 2008-016), Department of Education,
National Center for Education Statistics, Washington, DC
Barro, RJ 2001, ‘Human capital and growth’, American Economic Review, Vol. 91,
No. 2, pp. 12-17.
Barro, RJ 2001, Education and economic growth. The contribution of human and
social capital to sustained economic growth and well-being, pp. 13-41.
Baumrind, D 1978, ‘Parental disciplinary patterns and social competence in children’,
Youth & Society, Vol. 9, No. 3, pp. 239.
Bellamy, C 2005, ‘Childhood under threat: the state of the world’s Children 2005’,
UNICEF.
Retrieved
from
http://www.unicef.org/sowc05/english/sowc05_chapters.pdf
Birdsall, N, Social, CO, Dynamics, E, Institution, B and University, JH 1999,
Education: the people's asset, Center on Social and Economic Dynamics.
Cochran, C and Malone, E 2010, Public Policy: Perspectives and Choices, 4th edn,
Lynne Rienner Publishers, USA.
Dowling, JM and Valenzuela, MR 2010, Economic Development in Asia, 2nd edn,
Cengage Learning Asia Pte Ltd, Singapore.
Dunning, JH 2002, Regions, globalization, and the knowledge-based economy,
Oxford University Press, USA.
Durkin, K 1995, Developmental social psychology: From infancy to old age, WileyBlackwell.
Hanushek, EA and Woessmann, L 2007, The role of school improvement in
economic
development, Massachusetts: National Bureau of Economic Research
Cambridge, USA.
Hillman, AL and Jenkner, E 2004, ‘Educating Children in Poor Countries’,
International Monetary Fund Economic Issues, (number 33), Retrieved from
http://www.imf.org/external/pubs/ft/issues/issues33/index.htm)
OECD 2004, ‘Learning for Tomorrow’s World: First Results from PISA 2003’,
Retrieved from
http://www.oecd.org/dataoecd/59/21/33917683.pdf.
Steinberg, L, Lamborn, S, Dornbusch, S and Darling, N 1992, ‘Impact of parenting
practices on adolescent achievement: Authoritative parenting, school involvement,
and encouragement to succeed’, Child Development, Vol. 63, pp. 1266–128.
UNESCO 2002, Education for All: Is this World on Track?, UNESCO Publishing,
Paris.
UNDP 2011, ‘What are the Millennium Development Goals?’ Retrieved August 30th,
2011 from http://www.undp.org/mdg/basics.shtml
World Bank 2003, World Development Report 2004: Making Services Work for Poor
People, World Bank and Oxford University Press, Washington, D.C.
Xiao, H 1999, ‘Independence and Obedience: An Analysis of Child Socialization
Values in the United States and China’, Journal article by Hong Xiao; Journal of
Comparative Family Studies, Vol. 30.
15
Appendix 1: Variables
Test scores
Average years of total schooling, age 25+
Pupil-teacher ratio, Secondary
Government expenditure on education
GDP per capita
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Q10
PISA test scores for Math, Science
and Reading for the years 2000 and
2006. It is used as a proxy for quality
of education.
It is used to measure teacher quality.
Number of students per teacher at
secondary level.
Public expenditure on education as %
of GDP
GDP per capita, PPP (constant 2005
international $).
Independence
Hard work
Feeling of responsibility
Imagination
Tolerance and respect for other
people
Thrift saving money and things
Determination perseverance
Religious faith
Unselfishness
Obedience
Note: Q1-Q10 represent Child qualities.
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