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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 2 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. 3 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 4 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. 5 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). 13 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. 14 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. 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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. 16