Authors:

Gillian Hampden-Thompson 

Jamie S. Johnston 

American Institutes for Research 

Contact: 

Patrick Gonzales 

NCES 

415-920-9229 

STATISTICS IN BRIEF April 2006 

Variation in the Relationship Between 

Nonschool Factors and Student Achievement 

on International Assessments 

Introduction 

Over the past 20 years, findings from international assessment 

studies have influenced U.S. educational policy debates.1 Each 

wave of results has received significant media attention, public 

interest, and criticism. The critics have argued that methodological 

incompatibilities2

 and school organizational differences between 

countries prevent fair comparisons of achievement outcomes across 

the countries participating in the assessments (Bracey 1998; 

Rotberg 1990, 1995, 1998). In addition, it has been suggested that 

systems of education are bound by countries’ national cultures 

(Purves 1987), and this has implications for the interpretation of 

achievement cross nationally.3 

A number of researchers have attempted to address these concerns 

(Baker 1993, 1997; Boe and Shin 2005; National Research Council 

2002; Stedman 1994; Suter 2000; Westbury 1992, 1993). However, 

their response has centered exclusively on the methodological 

issues concerning the design of these assessments and schoolrelated factors (e.g., curriculum, school funding, and teacher 

qualifications) between countries, while differences in nonschool 

factors (e.g., students’ socioeconomic and immigrant status) 

 1

 The first item of evidence presented in A Nation at Risk (U.S. Department of 

Education 1983), a landmark report that became a key catalyst for nation-wide 

education reform, was that “on 19 academic tests American students were never 

first or second and, in comparison with other industrialized nations, were last 

seven times.” 

2

 Methodological incompatibilities include sampling and test bias. See the 

National Research Council (2002) for a comprehensive overview of the 

methodological advances in international student assessment. 

3

 It is important to recognize that policy environments have a salient role in 

shaping the economic and social contexts of students who reside in a particular 

country. For example, countries differ significantly in their policies toward 

immigration. Policy environments can significantly influence the economic and 

social milieu of a country, which in turn can have implications for the relationship 

between economic and social contextual factors and educational achievement. 

However, while it is essential to consider the policy environments that may 

influence these factors when interpreting achievement scores, it is beyond the 

scope of this brief to analyze the influence of different policy environments on 

the relationship between macro policy decisions and student achievement. 

U.S. Department of Education 

Institute of Education Sciences 

NCES 2006–014 
2

between countries have received less attention 

(for exception, see Buchmann 2002). 

As is well known, students’ nonschool factors are 

key predictors of children’s educational 

achievement. Equality of Educational 

Opportunity and Children and Their Primary 

Schools (Coleman et al. 1966; Plowden 1967), 

both published in the 1960s, showed that much, 

but not all, of the variation in achievement scores 

between students could be accounted for by 

nonschool factors. Since this time, a substantial 

amount of research has reinforced this finding 

(Blau and Duncan 1967; Entwisle and Alexander 

1993; Hout 1988; Jencks et al. 1979). The main 

purpose of this Statistics in Brief is to use NCES 

data to describe differences in nonschool factors 

that are related to achievement, which can inform 

the discussion about the concern that differences 

between countries on nonschool factors hinder 

cross-national comparisons of achievement 

outcomes. 

 

To accomplish this objective, this report 

considers six nonschool factors that are related to 

student achievement. These are the highest level 

of education attained by either of the students’ 

parents; the highest occupational status of either 

of the students’ parents; the number of books that 

students have access to in the home; whether 

students speak the native language of the country 

at home; students’ immigrant status; and 

students’ family structure.4

 These six nonschool 

factors can be categorized into two distinct 

groups: the first three factors (parents’ 

educational level, parents’ occupational status, 

and number of books in the home) are used to 

represent students’ socioeconomic status (SES) 

characteristics; the last three factors (students’ 

language at home, students’ immigrant status, and 

students’ family structure) represent students’ 

family characteristics. 

 

4

 For further information on the variables used for this 

study, see the technical notes at the end of this report. 

Data 

The data used for this study are from the Program 

for International Student Assessment (PISA), 

which is one of several international assessments 

the United States has participated in over the 

years. PISA was first implemented in 2000 and is 

carried out by the Organization for Economic 

Cooperation and Development (OECD). PISA 

measures 15-year-olds’ capabilities in reading 

literacy, mathematics literacy, and science literacy 

every 3 years. Each PISA data-collection effort 

assesses one area in depth, even as all three are 

assessed in each cycle so that participating 

countries have an ongoing source of achievement 

data in every subject. In addition to the major 

subject areas, PISA also measures general or 

cross-curricular competencies such as learning 

strategies and problem solving. In 2003, 

mathematics literacy was the subject area 

assessed in depth. The average U.S. score in 

mathematics literacy was 483 on a scale of 0-

1,000 with an average of 500 scale points.5

 On 

average, students in 15 of the 20 countries 

included in this report outperformed U.S. students 

(Lemke et al. 2004). 

Due to the large number of countries that 

participated in the PISA 2003 survey, and in an 

attempt to compare countries at similar levels of 

economic development, the study was restricted 

to 20 countries belonging to the World Bank 

high-income group (World Bank Country 

Classification 2005).6

 The international average 

referred to in this report is the average of the 

national averages of the 20 countries included in 

the study. 

 

5

 The mathematics literacy scale was constructed to have an 

average, across the OECD countries, of 500 points and a 

standard deviation of 100 points, with two-thirds of the 

students scoring between 400 and 600 points. 

6

 Japan and Korea both participated in PISA and are 

members of the World Bank high-income group. However, 

they both withheld key socioeconomic and family variables. 

Therefore, they were excluded from the study. In addition, 

due to low response rates, the United Kingdom is also 

excluded from this study. See technical notes at the end of 

this report for more information on the classification of 

economies by the World Bank. 
3

Objectives and Analytic Strategy 

This report has three objectives. The first is to 

describe how the population of 15-year olds in 

the United States differs from the same 

population in other countries on the six nonschool 

factors that are associated with student 

achievement. For instance, how does the 

percentage of students who are foreign-born in 

the United States compare to the percentage of 

foreign-born students in 19 other countries? To 

meet this objective, this report examines the 

distributions of SES and family characteristics 

within countries. 

The second objective is to describe variation in 

the nature of the relationships between student 

achievement and these factors cross-nationally. 

For example, does being a foreign-born student 

have the same educational implications in the 

United States as in other countries? To 

accomplish this objective, the mean achievement 

scores were calculated for each country and the 

achievement gaps by SES and family 

characteristics were compared. 

The third objective is to identify any interactions 

between SES and family characteristics and, in 

turn, determine if these relationships are 

associated with student achievement. For 

example, after SES is taken into account, how do 

foreign-born students perform compared to their 

native-born counterparts?7

 

The third objective was addressed by using an 

ordinary least squares regression in order to 

describe predict achievement gaps before and 

after controlling for SES and then comparing the 

gaps. This was done for language spoken at 

home, immigrant status, and family structure. 

 

7

 As immigrant status is, on average, correlated with 

language spoken in the home (r = .543), language in the 

home is possibly measuring the same construct as 

immigrant status. 

Findings 

Socioeconomic Status Characteristics 

Blau and Duncan’s (1967) seminal work 

established a relationship between parent 

education and occupational status with children’s 

educational outcomes. Research has linked 

children’s academic achievement with their 

parents’ educational attainment and parents’ 

occupational status (Heyneman and Loxley 1983; 

Shavit and Blossfield 1993). Parental income, 

parental education, and parental occupation are 

considered the three main indicators of SES 

(Gottfried 1985; Hauser 1994; Mueller and Parcel 

1981). Studies have examined the relationship 

between these variables and moderate correlations 

have been found, indicating that these three 

components are unique and measure different 

aspects of SES (Bollen, Glanville, Stecklov 2001; 

Hauser and Huang 1997). 

A fourth indicator of SES is often used. 

Researchers have highlighted the significance of 

various home resources as measures of SES 

(Coleman 1988; Duncan and Brooks-Gunn 1997; 

Entwisle and Astone 1994). These home resource 

measures include household possessions such as 

the availability of books and computers in the 

home. Large-scale international studies such as 

the Trends in International Mathematics and 

Science Study (TIMSS), the Progress in 

International Reading Literacy Study (PIRLS), 

and PISA do not collect parental income 

variables. In the absence of this measure, the 

number of books in a student’s home, which been 

shown to be an important predictor of student 

achievement (Wößmann 2003), was used in this 

study. 

Parent education. Forty-eight percent of 15-yearold students in the United States reported having 

at least one parent who had a college degree or a 

postsecondary vocational qualification (table 1).8

 

Comparing the United States to the other 19 

countries in this study, 7 countries had a higher 

percentage of 15-year-old students who reported 

 

8

 Student reports of parents’ educational attainment may be 

inaccurate as some students either do not know or 

exaggerate parent education (Williams et al. 2000). 
4

that at least one of their parents was educated to 

the postsecondary level (Australia, Belgium, 

Canada, Denmark, Finland, Norway, and 

Sweden). Eleven countries had a smaller 

percentage of students with postsecondaryeducated parents when compared to the United 

States. The international average of the 20 

countries, which was 46 percent, was not 

significantly different from the U.S. average of 48 

percent. 

On average, in all 20 countries, 15-year-old 

students with at least one postsecondary-educated 

parent performed better than students whose 

parents were educated to the secondary level or 

below (figure 1.1). The mathematics literacy 

achievement gap between students with 

postsecondary-educated parents and students who 

did not have postsecondary-educated parents 

ranged from 19 score points in Austria to 52 score 

points in Germany (tables 2 and 3). 

The United States had a larger achievement gap 

than six countries (Austria, Canada, Finland, 

Iceland, Italy, and Sweden; table 3). Germany 

had a larger achievement gap than the United 

States (52 versus 41 score points). No 

measurable differences were found between the 

United States and the other 12 countries. The 

United States did not differ significantly from the 

international average score gap of 40 score 

points. 

Parent occupational status. Parent occupational 

status is based on either the student’s father’s or 

mother’s occupation (whichever is higher) as 

reported by the student.9

 Occupations were 

coded to the International Standard Classification 

of Occupations 1988 (ISCO-88) and then grouped 

into major occupational groups.10 For the 

purposes of this study, the variable was 

transformed into quarters with the “high” 

 

9

 Values on the index range from 16 to 90; low values 

represent low socio-economic status and high values 

represent high socio-economic status. 

10 See Ganzeboom, DeGraaf, and Treiman (1992) for 

details of this methodology. For more details concerning 

this variable, see the technical notes at the end of this 

report. 

occupational status group representing the upper 

25 percent of the distribution. 

Thirty-three percent of 15-year-old U.S. students 

reported having at least one parent whose 

occupational status was in the upper quarter (high 

occupational status; table 1). The United States 

had a higher percentage of 15-year-old students 

with one or both parents of high occupational 

status than 17 of the other 19 countries. Only 

Iceland had a measurably higher percentage of 

15-year-old students with one or both parents 

from the upper occupational status group than the 

United States (37 versus 33 percent). The U.S. 

percentage was higher than the 20-country 

average of 27 percent. 

As shown in figure 1.2, having parents of high 

occupational status is associated with higher 

student mathematics literacy performance on 

average in all 20 countries included in the study. 

The estimated difference in performance between 

15-year-old students with parents of high 

occupational status versus middle and low 

occupational status on the mathematics literacy 

assessment ranged from 29 points (Iceland) to 75 

points (Portugal) on the PISA 2003 score scale 

(tables 2 and 3). 

The United States had a larger achievement gap 

between students with parents of high 

occupational status and students with parents of 

mid and low occupational status than Canada, 

Finland, and Iceland, but a smaller gap than 

Belgium, Germany, and Portugal (table 3). There 

was no measurable difference between the size of 

the achievement gap in the United States and the 

other 13 countries. Furthermore, the international 

average score gap of 55 points was not 

measurably different from the performance gap in 

the United States, which was 54 score points. 

Books in the home. Twenty-two percent of 15-

year-old U.S. students reported having more than 

200 books in their home (table 1). The United 

States had a higher percentage of 15-year-old 

students who reported having more than 200 

books in the home than Greece and Portugal. In 

contrast, the percentage of U.S. students reporting 
5

more than 200 books in the home was less than in 

nine other countries. No discernable difference 

was found between the United States and the 20-

country average (22 versus 24 percent). 

As shown in figure 1.3, having more books in the 

home is associated with higher student 

mathematics literacy performance on average in 

all 20 countries in the study. The estimated 

difference in performance between students from 

homes with more than 200 books versus 200 or 

fewer books ranged from 40 points (Canada) to 

74 points (Austria) on the PISA score scale 

(tables 2 and 3). 

Compared to Australia, Belgium, Canada, 

Denmark, Finland, Iceland, Ireland, and Norway, 

the United States had a larger achievement gap 

between students who reported more than 200 

books versus those with 200 or fewer books 

(table 3). The U.S. achievement gap was not 

found to be measurably different from those in 

the remaining 11 countries. No measurable 

difference was found between the 20-country 

average achievement gap of 66 score points and 

the U.S. achievement gap of 68 score points. 
6

representing the upper quarter. The response rate in New Zealand for parent occupational status was below 85 percent. 

average is the weighted mean of the data values for the 20 countries included in the study and reflects the value for a given variable when the 20 countries are considered as a whole (i.e., one single entity). The individual 

country estimates were calculated using the final student weight. The SES characteristics—parent education, parent occupational status, and number of books in the home—are based on students' reports. If either of a 

student's parents completed a bachelor's, master's, or postgraduate degree (corresponding to the International Standard Classification of Education (ISCED) levels 5A, 5B, or 6), the student was considered as having 

postsecondary-educated parents. Parent occupational status is based on either of the student's parents' occupation (whichever is higher), and the variable was transformed into quarters with "high" occupational status

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

Figure 1. Percentage of 15-year-old students and average mathematics literacy scores, by students' socioeconomic status (SES) characteristics and country: 2003

Figure 1.1 Percentage of students with postsecondary-educated parents (left scale) and average mathematics literacy performance of students with 

Figure 1.1 postsecondary-educated and non-postsecondary-educated parents (right scale), by country: 2003

NOTE: The solid bars represent the percentage of students in each country that indicated having parents educated at the postsecondary level (figure 1.1), of high occupational status (figure 1.2), or from a household with 

Figure 1.2 Percentage of students with parents of high occupational status (left scale) and average mathematics literacy performance of students with parents of high 

Figure 1.2 occupational status and students with parents of middle and low occupational status (right scale), by country: 2003

Figure 1.3 Percentage of students with more than 200 books in the home (left scale) and average mathematics literacy performance of students with more than 200 

Figure 1.3 books in the home and students with 200 or fewer books in the home (right scale), by country: 2003

more than 200 books (figure 1.3). The scale on the left side indicates the percentage of students. The extended lines represent the differences between the average scores for students whose parents are educated at the

postsecondary level and students whose parents are educated at the secondary level or below (figure 1.1), of high and middle or low occupational status (figure 1.2), or from a household with more than 200 books and 200

or fewer books (figure 1.3). The scale on the right side indicates the average scale score. The achievement gap is the achievement score point difference between the two mean achievement estimates. The international 

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Mean mathematics literacy score of students with at least one parent educated to the postsecondary level, with parents of high occupational status, or with more than 200 books in the home

Mean mathematics literacy score of students with parents educated to the secondary school level and below, with parents of middle or low occupational status, or with 200 or fewer books in the home

Mean achievement gap
7

Family Characteristics 

Migration patterns across many of the countries 

in the World Bank high-income group have 

resulted in a significant population of students 

whose home language is not the language of 

instruction in the schools they attend. The 

United States is no exception. The last two 

decades have seen a significant rise in the 

percentage of students in the United States 

speaking a language other than English at home 

(Shin and Bruno 2003). There are clear 

educational achievement disadvantages to 

receiving instruction in a language that is 

different from the one spoken at home (Schmid 

2001). 

Students who are foreign-born face a number of 

challenges, especially as they adjust to a new 

country. Immigrant students often encounter 

difficulties in their new environment because 

educational systems, culture, and language of 

instruction may differ from those in their country 

of origin. A number of studies have documented 

significant educational achievement 

disadvantages associated with immigrant 

status.(Eldering and Kloprogge 1989; Lollock 

2001). Research conducted in the United States 

indicates that many of the educational 

achievement disadvantages of immigrant 

children are associated with the lower economic 

status of immigrant families (Schmid 2001). 

In recent years, dynamic changes have occurred 

in the structure and composition of families. 

Around the world, the two-parent household has 

become an ever-shrinking phenomenon with 

many children living in single-parent, step, and 

guardian families (Bradshaw and Finch 2002). 

Research findings, both in the United States and 

abroad, have shown that alternative family 

structures are associated with lower educational 

achievement (Downey 1994; HampdenThompson and Pong 2005; McLanahan and 

Sandefur 1994; Pong, Dronkers, and HampdenThompson 2003). Research indicates that much 

of the educational achievement disadvantage of 

residing in a single-parent, step, or guardian 

family can be attributed to socioeconomic factors 

(Duncan and Brooks-Gunn 1997; Haverman, 

Wolfe, and Spaulding 1991; McLanahan and 

Sandefur 1994). 

Language spoken at home. Nine percent of the 

15-year-old students in the United States reported 

that they spoke a language other than the test 

language at home always or most of the time 

(table 1). The United States had a higher 

percentage of 15-year-old students reporting that 

they were non-test-language speakers at home 

than eight other countries. In contrast, Belgium, 

Canada, Italy, the Netherlands, Spain, and 

Switzerland reported higher percentages of nontest-language speaking students compared to the 

United States. The 20-country average of 10 

percent was not measurably different from the 

U.S. average (9 percent). 

In the majority of countries included in the study, 

15-year old students who spoke the language of 

the test at home had higher mathematics literacy 

achievement scores, on average, than students 

who did not speak the language of the test at 

home (figure 2.1). The exceptions were Ireland 

and Spain, where achievement between testlanguage speakers and non-test-language 

speakers was not measurably different. Non-testlanguage speakers did not perform measurably 

better than test-language speakers in any of the 

20 countries (tables 2 and 3). 

Of the countries with a significant achievement 

gap between non-test-language speakers and testlanguage speakers, the United States had a larger 

gap than Belgium, Canada, the Netherlands, and 

New Zealand and a smaller gap than Germany 

and Switzerland (table 3). In the United States, 

test-language speakers performed an estimated 

46 score points better than non-test-language 

speakers. This was not measurably different 

from the international average of 42 score points. 

 

The OLS regression estimates of achievement 

showed that on average in the United States, 

students who spoke the language of the test at 

home outperformed students who spoke a 

language other than the test language at home 

(figure 3). This was also the case in the 
8

remaining countries included in the study, with 

the exception of Ireland and Spain. 

After taking SES into account, the estimated 

achievement gap between test-language-speaking 

students and non-test-language-speaking 

students was significantly reduced, though not 

eliminated, in the United States and Switzerland. 

Thus, some of the educational achievement 

disadvantage of being a non-test-languagespeaking student can be explained by students’ 

SES.11 In the remaining 18 countries, the 

inclusion of the SES variables did not 

significantly reduce the achievement gap. 

 

11 See table 4 for coefficients and standard errors from the 

ordinary least squares (OLS) regression analysis. 
9

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

Figure 2.1. Percentage of 15-year-old students and average mathematics literacy scores, by students' family characteristics and country: 2003

Figure 2.1 Percentage of non-test-language-speaking students (left scale) and average achievement of non-test-language-speaking students and test-language-speaking 

Figure 2.1 students on PISA 2003 (right scale), by country: 2003

Figure 2.2 Percentage of foreign-born students (left scale) and average mathematics literacy performance of foreign-born students and native-born students (right scale), by 

Figure 2.2 country: 2003

Figure 2.3 Percentage of students from non-two-parent homes (left scale) and average mathematics literacy performance of students from non-two-parent and two-parent 

Figure 2.3 homes on PISA 2003 (right scale), by country: 2003

NOTE: The solid bars represent the percentage of students in each country that indicated being a non-test-language speaker (figure 2.1), foreign-born (figure 2.2), or from a non-two-parent home (figure 2.3). The scale on 

responses. The response rate in New Zealand for parent occupational status was below 85 percent.

the left side indicates the percentage of students. The extended lines represent the differences between the average scores for students who speak the test language and do not speak the test language (figure 2.1), are

native- and foreign-born students (figure 2.2), or are from two-parent and non-two-parent homes (figure 2.3). The scale on the right side indicates the average scale score. The achievement gap is the achievement score 

point difference between the two mean achievement estimates. The international average is the weighted mean of the data values for the 20 countries included in the study and reflects the value for a given variable when the

20 countries are considered as a whole (i.e., one single entity). The individual country estimates were calculated using the final student weight. The family characteristics—language spoken at home, immigrant status, and 

family structure—are based on students' reports. "Test-language" students reported speaking the language in which the test was administered always or most of the time at home while "non-test-language" students 

reported using another language always or most of the time at home. Students from a "two-parent family" reported living with both their mother and father. The category "non-two-parent family" encompasses all other 

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Australia Austria Belgium Canada Denmark Finland France Germany Greece Iceland Ireland Italy Netherlands New

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Australia Austria Belgium Canada Denmark Finland France Germany Greece Iceland Ireland Italy Netherlands New

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Mean mathematics literacy score of test-language speakers, native-born students, or students from two-parent families

Mean achievement gap

Mean mathematics literacy score of non-test-language speakers, foreign-born students, or students from non-two-parent families
10

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

# Rounds to zero. 

Figure 3. Estimated achievement gap of 15-year-old test-language-speaking students versus 15-year-old non-test-language-speaking 

Figure 3. students on the PISA mathematics literacy assessment, by country: 2003 

NOTE: Each bar represents the predicted achievement gap between native-born students and their foreign-born counterparts. Language spoken at home 

is based on students' reports. Students were asked to report what language they spoke at home always or almost always. The responses were then 

grouped into two categories: 1) test-language-speaking students (students who speak the language of the test at home always or almost always) and 2) 

non-test-language-speaking students (students who speak another language always or most of the time at home). The socioeconomic status controls are 

parent education, parent occupational status, and number of books in the home. The response rate in New Zealand for parent occupational status was 

below 85 percent.

12

57

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13

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#

0 20 40 60 80 100 120 140

Australia

Austria

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Iceland

Ireland

Italy

Netherlands

New Zealand

Norway

Portugal

Spain

Sweden

Switzerland

United States

Country

PISA score points

Achievement gap Achievement gap after controlling for socioeconomic status

#

#
11

Immigrant status. Nine percent of 15-year-old 

U.S. students reported that they were foreign 

born (table 1). Compared to the other 19 

countries in this study, the United States had 

more foreign-born students than 10 of them. In 

contrast, Australia, Canada, Germany, New 

Zealand, and Switzerland all had significantly 

larger foreign-born populations. The U.S. 

average did not differ significantly from the 

international average of 10 percent. 

On average, with the exception of Ireland, 

foreign-born 15-year old students in the 

remaining 19 countries fared worse on the 

mathematics literacy tests than their native-born 

counterparts (figure 2.2). In these 19 countries, 

the achievement gap ranged from 15 score points 

in both Australia and New Zealand to 126 score 

points in Belgium (tables 2 and 3). 

Of the countries with a significant achievement 

gap between foreign-born and native-born 

students, the United States gap was larger than 

those of Australia, Canada, and New Zealand 

(table 3). Five countries had larger achievement 

gaps than that of the United States, and the gaps 

in 10 countries were not measurably different. 

The international average of 55 score points was 

not significantly different from the U.S. 

achievement gap of 53 score points. 

 

These family factors, in addition, are interrelated 

with SES factors. For example, it has been 

shown that students from immigrant families in 

the United States are at a disadvantage due, in 

part, to the association between SES and 

immigrant status (Schmid 2001). However, this 

may not be the case in other nations. In order to 

quantify this relationship, OLS regression was 

used to describe predicted achievement gaps 

between immigrant and non-immigrant status 

both before and after controlling for SES and 

then comparing gaps. 

The OLS regression estimates showed that on 

average in the United States, native-born 

students outperform foreign-born students. With 

the exception of Ireland, this result appears 

consistent across the other countries included in 

the study (figure 4). In 19 of the 20 countries, on 

average, 15-year-olds who were native born 

outperformed their foreign-born counterparts. 

After taking into account SES, the predicted 

achievement gap between native- and foreignborn 15-year-olds was significantly reduced, 

though not eliminated, in the United States, as 

well as Belgium, Canada, Germany, the 

Netherlands, Sweden, and Switzerland. Thus, 

some of the educational achievement 

disadvantage for a foreign-born student, in these 

seven countries, can be explained by students’ 

SES.12 In the other countries, the inclusion of the 

SES variables did not significantly reduce the 

achievement gap. 

Family structure. In the United States, 45 

percent of 15-year-old students reported living in 

non-two-parent households, including singleparent households, step-families, and guardian 

families (table 1). This percentage was higher 

than the percentage of students from non-twoparent households in all of the remaining 19 

countries in this study and higher than the 

international average of 34 percent. 

As shown in figure 2.3, on average in all 20 

countries students from two-parent homes (live 

with a mother and father) performed better on the 

PISA mathematics literacy assessment than 

students from other homes. The achievement 

gap ranged from 12 score points in Austria to 46 

score points in the United States (tables 2 and 3). 

The United States had a larger achievement gap 

between 15-year-olds from two-parent homes 

and other homes than 17 other countries (table 

3). The two exceptions were Belgium and New 

Zealand, where the achievement gaps were not 

measurably different from the U.S. achievement 

gap. The achievement gap in the United States 

was significantly different from the international 

average (46 versus 35 score points). 

 

12 See table 5 for coefficients and standard errors from the 

OLS regression analysis. 
12

Figure 4. Estimated achievement gap of native-born 15-year-old students versus foreign-born 15-year-old students on the PISA Figure 4. 

 mathematics literacy assessment, by country: 2003 

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

NOTE: Each bar represents the predicted achievement gap between native-born students and their foreign-born counterparts. Immigrant status is based on students' 

reports. Students were asked to report whether or not they and their parents were born in the country of assessment or in another country. The responses were then 

grouped into two categories: 1) native-born students (those students born in the country of assessment regardless of parent birthplace) and 2) foreign-born students (those 

students born outside the country of assessment and whose parents were also born outside of the country). The socioeconomic status controls are parent education, parent 

occupational status, and number of books in the home. The response rate in New Zealand for parent occupational status was below 85 percent. 

15

65

25

63

65

72

94

53

68

2

47

109

15

58

85

51

88

83

53

7

51

82

10

51

53

54

39

44

57

11

36

64

16

38

78

41

61

69

35

126

0 20 40 60 80 100 120 140

Australia

Austria

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Iceland

Ireland

Italy

Netherlands

New Zealand

Norway

Portugal

Spain

Sweden

Switzerland

United States

Country

PISA score points

Achievement gap Achievement gap after controlling for socioeconomic status
13

Some research indicates that much of the 

educational achievement disadvantage of 

residing in an alternative family structure to the 

two-parent household can be attributed to 

economic factors (McLanahan and Sandefur 

1994). In order to quantify this relationship, 

OLS regression was used to describe predicted 

achievement gaps between 15-year-olds from 

two-parent homes and those from non-twoparent homes both before and after controlling 

for SES and then comparing gaps. 

The regression estimates showed that in the 

United States and the other 19 countries, there 

appears to be an educational achievement 

advantage to residing in a two-parent household 

(figure 5). In all 20 countries, 15-years-olds who 

live in a two-parent household have higher 

mathematics literacy achievement, on average, 

than those students who live in non-two-parent 

families. 

After taking into account selected SES measures, 

the predicted achievement gap was significantly 

reduced, though not eliminated, in the United 

States and Australia, Belgium, Canada, New 

Zealand, and Sweden. Thus, some of the 

educational achievement disadvantage for 15-

year-olds who reside in non-two-parent 

households in these six countries can be 

explained by the students’ SES.13 In the other 

countries, the inclusion of the SES variables did 

not significantly reduce the achievement gap. 

 

13 See table 6 for coefficients and standard errors from the 

OLS regression analysis. 
14

2.743

NOTE: Each bar represents the achievement gap between students from two-parent families and students from other family structures. Family 

structure is based on students' reports. Students from a "two-parent family" reported living with both their mother and father. "Other" family 

structures encompasses all other responses. The economic context controls are parent education, parent occupational status, and number of 

books in the home. The response rate in New Zealand for parent occupational status was below 85 percent. 

Figure 5. Estimated achievement gap of 15-year-old students from two-parent families versus 15-year-old students from 

Figure 5. non-two-parent family structures on the PISA mathematics literacy assessment, by country: 2003 

# Rounds to zero. 

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

31

12

28

29

13

21

11

25

17

33

18

34

38

25

17

13

30

24

46

21

8

33

20

23

6

13

20

11

28

17

27

25

17

14

10

20

21

29

43

#

0 20 40 60 80 100 120 140

Australia

Austria

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Iceland

Ireland

Italy

Netherlands

New Zealand

Norway

Portugal

Spain

Sweden

Switzerland

United States

Country PISA score points

Achievement gap Achievement gap after controlling for socioeconomic status
15

Summary 

This Statistics in Brief described the differences 

in the distributions of nonschool factors related 

to student achievement among 15-year-old 

students and their families in the United States 

and other countries at similar levels of economic 

development. The first objective was to describe 

how the United States differs from the other 

countries assessed in terms of the distribution of 

SES and family characteristics. Generally, the 

United States did not differ from the other 19 

countries in terms of the distribution of SES and 

family factors on four, but not all, of the 

characteristics. These were parental education, 

the number of books in the home, immigrant 

status, and language spoken at home. There 

were differences when looking at two 

characteristics parent occupation and family 

structure. The United States had a higher 

percentage of 15-year-olds with parents of high 

occupational status and a higher percentage of 

15-year-olds residing in non-two-parent 

households compared to the 20-country average. 

Describing the associations between these factors 

and mean achievement scores was the second 

objective of this report. The relationship 

between SES and achievement was consistent 

across all 20 countries. Students with highest 

levels of SES, as measured in this study, had an 

educational advantage over their lowest SES 

counterparts. This reinforces the associations 

previously documented in the literature both in 

the United States and abroad between SES and 

student educational achievement. 

Less research has been conducted crossnationally on the association between students’ 

family characteristics and student achievement. 

Results of this study found that in nearly all of 

the countries, 15-year-olds with certain family 

characteristics outperformed other students. For 

example, there is an educational achievement 

disadvantage associated with residing in a nontwo-parent family across all 20 countries. 

The last objective of this study was to examine 

the interrelationship between SES and family 

factors to determine if low SES accounts for 

some of the educational achievement 

disadvantage of those students who do not speak 

the language of the test regularly at home, are 

foreign born, or who reside in a non-two-parent 

household. In some countries, a student’s SES 

accounted for a portion of the disadvantage 

associated with being an immigrant or residing in 

a non-two-parent household. This was not the 

case, however, across all the countries in this 

study. 

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19

Methodology and Technical Notes 

Sampling, Data Collection, and Response Rates 

for All Participating Countries 

The sample of Program for International Student 

Assessment (PISA) students was selected in a 

way that represented the full population of 15-

year-old students in each of the 41 countries that 

participated in 2003. The desired population in 

each country consisted of 15-year-olds attending 

both publicly and privately controlled 

educational institutions in grades 7 and higher. 

A minimum of 4,500 students from a minimum 

of 150 schools was required. Within schools, a 

sample of 35 students was to be selected in an 

equal probability sample unless fewer than 25 

students age 15 were available (in which case all 

students were selected). International standards 

required that students be sampled based on an 

age definition of 15 years and 3 months to 16 

years and 2 months at the beginning of the 

testing period. The testing period was required 

not to exceed 42 days between March 1, 2003, 

and August 31, 2003. Each country collected its 

own data, following international guidelines and 

specifications. 

A minimum response rate target of 85 percent 

was required for initially selected educational 

institutions. In instances in which the initial 

response rate of educational institutions was 

between 65 and 85 percent, an acceptable school 

response rate could still be achieved using 

replacement schools, which were selected at the 

time of sample selection. 

PISA also required a minimum participation rate 

of 80 percent of sampled students from original 

and replacement schools within each country. A 

student was considered a participant if he or she 

participated in the first testing session or a 

follow-up or makeup testing session. 

Sampling, Data Collection, and Response Rates 

in the United States 

The 2003 PISA school sample was drawn for the 

United States in November 2002. The sample 

design was developed to retain some of the 

properties of the 2000 PISA U.S. school sample 

and to follow international requirements as given 

in the PISA sampling manual. Unlike the 2000 

PISA sample, which had a three-stage design, in 

the United States, the 2003 sample was drawn 

using a two-stage sampling process with the first 

stage a sample of schools, and the second stage a 

sample of students within schools. For 

PISA in 2000, the U.S. school sampling process 

used the selection of a sample of geographic 

Primary Sampling Units (PSUs) as the first stage 

of selection. The sample was not clustered at the 

geographic level for PISA 2003. This change 

was made in an effort to reduce the design effects 

observed in the 2000 data and to spread the 

respondent burden across school districts as 

much as possible. 

The sample design for PISA was a stratified 

systematic sample, with sampling probabilities 

proportional to measures of size. The PISA 

sample had no explicit stratification and no 

oversampling of subgroups. The frame was 

implicitly stratified (i.e., sorted for sampling) by 

five categorical stratification variables: grade 

span of the school (five levels), type of school 

(public or private), region of the country 

(Northeast, Central, West, Southeast), type of 

location relative to populous areas (eight levels), 

and minority status (15 percent and below and 

above 15 percent). The last sort key within the 

implicit stratification was by estimated 

enrollment of 15-year-olds based on grade 

enrollments. 

At the same time that the PISA sample was 

selected, replacement schools were identified 

following the PISA guidelines by assigning the 

two schools neighboring the sampled school on 

the frame as replacements. There were several 

constraints on the assignment of substitutes. One 

sampled school was not allowed to substitute for 

another, and a given school could not be assigned 

to substitute for more than one sampled school. 

Furthermore, substitutes were required to be in 

the same implicit stratum as the sampled school. 

If the sampled school was the first or last school 

in the stratum, then the second school following 

or preceding the sampled school was identified 

as the substitute. One was designated a first 
20

If an original school refused to participate, the 

first replacement was then contacted. If that 

school also refused to participate, the second 

school was then contacted. 

The U.S. PISA school sample consisted of 420 

schools. This number was increased from the 

international minimum requirement of 150 to 

offset school nonresponse, reduce design effects. 

The schools were selected with probability 

proportionate to the school’s estimated 

enrollment of 15-year-olds from the 2003 NAEP 

school frame with 2000-01 school data. The data 

for public schools came from the Common Core 

of Data (CCD), and the data for private schools 

came from the Private School Universe Survey 

(PSS). Any school containing at least one 7ththrough 12th-grade class as of the school year 

2000–01 was included on the school sampling 

frame. Participating schools provided lists of 15-

year-old students, and a sample of 35 students 

was selected within each school in an equal 

probability sample. The overall sample design 

for the United States was intended to 

approximate a self-weighting sample of students 

as much as possible, with each 15-year-old 

student having an equal probability of being 

selected. 

In the United States, for a variety of reasons 

reported by school administrators (such as 

increased testing requirements at the national, 

state, and local levels; concerns about timing of 

the PISA assessment; and loss of learning time), 

many schools in the original sample declined to 

participate. When it became clear that the 

United States would not meet the minimum 

response rate standards, in order to improve 

response rates and better accommodate school 

schedules, a second testing window was opened 

from September to November 2003 with the 

agreement of the PISA Consortium. For the fall 

data collection, the school sample included only 

original schools from the sample that had refused 

to participate in the spring but indicated a 

willingness to participate in a fall assessment. 

Substitute schools were not included in the fall 

sample because their participation would have 

had little effect on raising the final response rate. 

In order to achieve a comparable sample of 

students in spring and fall, the age definition for 

students tested in the fall was adjusted such that 

all students tested were the same age. 

In the United States, of the 420 sampled schools, 

382 were eligible (some did not have any 15-

year-olds enrolled) and 179 agreed to participate 

in the spring of 2003. An additional 70 original 

schools participated in the fall assessment for a 

total of 249 participating original schools. The 

school response rate (including spring and fall 

assessments) before replacement was 65 percent 

(weighted and unweighted). The weighted 

school response rate before replacement is given 

by the formula: 

weighted school response 

rate before replacement = 

 

where Y denotes the set of responding original 

sample schools with age-eligible students, N 

denotes the set of eligible nonresponding original 

sample schools, Wi denotes the base weight for 

school i, Wi = 1/Pi , where Pi denotes the school 

selection probability for school i, and Ei denotes 

the enrollment size of age-eligible students, as 

indicated on the sampling frame. 

In addition to the 249 participating original 

schools, 13 replacement schools also participated 

in the spring for a total of 262 participating 

schools in the United States. 

A total of 7,598 students were sampled for the 

assessment. Of these students, 261 were deemed 

ineligible because of their enrolled grades, 

birthdays, or other reasons and were removed 

from the U.S. sample. Of the eligible 7,337 

sampled students, an additional 534 students 

were excluded using the criteria described above, 

for a weighted exclusion rate of 7 percent. 

Of the 6,803 remaining sampled students, a total 

of 5,456 students participated in the assessment 

in the United States, but 114 of these came from 

schools that had less than 50 percent student 

participation. Schools that had less than 50 

∑

∑

∈ ∪

∈

i (Y N )

i i

i Y

i i

W E

W E
21

percent student participation were classified as 

school nonrespondents, and these students (114 

participating students and 187 nonparticipating 

students) were therefore excluded for the 

purposes of calculating student response rates. 

Thus, although data for 5,456 students are 

included in the database, student response rates 

were calculated by subtracting the 114 students 

from the 5,456 for a total of 5,342 participating 

students. The denominator for the student 

response rate is 6,502, which consists of 7,598 

sampled students minus the following students: 

261 ineligible; 534 excluded; 114 responding 

students from nonresponding schools; and 187 

nonresponding students from nonresponding 

schools. An overall weighted student response 

of 83 percent was achieved (82 percent 

unweighted). 

Two separate bias analyses were conducted in 

the United States to address potential problems 

in the data due to school nonresponse and 

possible achievement differences between 

students in spring and fall testing windows. 

Based on the nonresponse bias analysis, it was 

concluded that the data for the United States 

were adequate to generalize to the U.S. 15-yearold population and should be included in the 

international report and database. Based on the 

results of the second bias analysis, which was 

concerned with the possible achievement 

differences between students in spring and fall 

testing windows, it was concluded that the data 

for the United States were again adequate to 

generalize to the U.S. 15-year-old population and 

should be included in the international report and 

database. 

Weighting. Students included in the final PISA 

sample for a given country were not all equally 

representative of the full student population, 

even though random samplings of schools and 

students were used to select the sample. The use 

of sampling weights is necessary for the 

computation of statistically sound, nationally 

representative estimates. Survey weights help 

adjust for intentional over- or under-sampling of 

certain sectors of the population, school or 

student nonresponse, or errors in estimating size 

of a school at the time of sampling. Survey 

weighting for PISA 2003 was carried out by 

Westat, Inc., as part of the PISA Consortium. 

The internationally defined weighting 

specifications for PISA required that each 

assessed student’s sampling weight be the 

product of the inverse of the school’s probability 

of selection, an adjustment for school-level 

nonresponse, the inverse of the student’s 

probability of selection, and an adjustment for 

student-level nonresponse. All PISA analyses 

were conducted using these sampling weights. 

The base weight for each replacement school was 

equal to the base weight of the original school it 

replaced. 

The individual country estimates and the 

international average are calculated using the 

final student weight (w_fstuwt). 

Data Limitations 

As with any study, there are limitations to PISA 

2003 that researchers should take into 

consideration. Estimates produced using data 

from PISA 2003 are subject to two types of error, 

nonsampling and sampling errors. Nonsampling 

errors can be due to errors made in the collection 

and processing of data. Sampling errors can 

occur because the data were collected from a 

sample rather than a complete census of the 

population. 

Nonsampling errors. Nonsampling error is a 

term used to describe variations in the estimates 

that may be caused by population coverage 

limitations, nonresponse bias, and measurement 

error, as well as by data collection, processing, 

and reporting procedures. For example, the 

sampling frame for the United States was limited 

to regular public and private schools in the 50 

states and the District of Columbia. The sources 

of nonsampling errors are typically problems like 

unit and item nonresponse, the differences in 

respondents’ interpretations of the meaning of 

the questions, response differences related to the 

particular time the survey was conducted, and 

mistakes in data preparation. Some of these 

issues (particularly unit nonresponse) are 
22

discussed above in the section on U.S. sampling 

and data collection. 

Missing data. There are four kinds of missing 

data. “Nonresponse” data occurs when a 

respondent was expected to answer an item but 

no response is given. Responses that are 

“missing or invalid” occur in multiple-choice 

items where an invalid response is given. The 

code is not used for open-ended questions. An 

item is “not applicable” when it is not possible 

for the respondent to answer the question. 

Finally, items that are “not reached” are 

consecutive missing values at the end of each 

test session. All four kinds of missing data are 

coded differently in the PISA 2003 database. 

In general, it is difficult to identify and estimate 

either the amount of nonsampling error or the 

bias caused by this error. In PISA 2003, efforts 

were made to prevent such errors from occurring 

and to compensate for them when possible. For 

example, the design phase entailed a field test 

that evaluated items as well as the 

implementation procedures for the survey. It 

should also be recognized that most background 

information was obtained from students’ selfreports, which are subject to respondent bias. 

One potential source of respondent bias in this 

survey was social desirability bias, for example, 

if students overreported their mathematics 

ability. 

Missing background data are not included in the 

analyses for this report and are not imputed. 

Listwise deletion is applied to deal with cases 

that have missing values. In general, item 

response rates for the variables discussed in this 

report were over the NCES standard of 85 

percent to report without notation. The one case 

in which more than 15 percent of the student 

responses were missing is flagged (for New 

Zealand for student report of parent occupation, 

with an item response rate of 84 percent). 

Sampling errors. Sampling errors occur when 

the discrepancy between a population 

characteristic and the sample estimate arises 

because not all members of the reference 

population are sampled for the survey. The size 

of the sample relative to the population and the 

variability of the population characteristics both 

influence the magnitude of sampling error. The 

particular sample of 15-year-old students from 

the 2002–03 school year was just one of many 

possible samples that could have been selected. 

Therefore, estimates produced from the PISA 

2003 sample may differ from estimates that 

would have been produced had another 15-yearold sample been drawn. This type of variability 

is called sampling error because it arises from 

using a sample of 15-year-old students in 2002–

03, rather than all 15-year-old students in that 

year. 

The standard error is a measure of the variability 

due to sampling when estimating a statistic. The 

approach used for calculating sampling variances 

in PISA was the balanced repeated replication 

(BRR), or balanced half-samples (Fay’s method). 

Standard errors can be used as a measure for the 

precision expected from a particular sample. 

Standard errors for all of the estimates can be 

found in tables 1-5. 

Statistical Procedures 

International average. The international average 

is the weighted mean of the data values for all of 

the 20 countries. It reflects the value for a given 

variable when the 20 countries are considered as 

a whole (i.e., one single entity). The 

international average is calculated using the final 

student weight. 

Significance tests. Comparisons made in the text 

were tested for statistical significance to ensure 

that the differences are larger than might be 

expected due to sampling variation. When 

comparisons are made, t statistics were 

calculated using the following formula: 

2

2

2

1

1 2

( ) ( )

( )

se se

est est

t

+

− =

Some tests, however, compared estimates from 

related groups (e.g., U.S. students compared to 

the international average). To account for this 
23

sample dependency, the t statistic for dependent 

samples was computed using the following 

formula, where p is the proportion of the 

subgroup to the total group: 

( ) () 2 2 2

sub tot 2 sub

sub tot

se se p se

E E

t

+ −

− =

Ordinary least squares regression. The 

regression analysis is used in this report to 

investigate the relationship between a dependent 

variable (achievement scores) and several 

independent variables. Regression coefficients 

were calculated in WesVar14 using the following 

model: 

Υi = β1χi1 +...+ βpχip+εi

where Υi is the observed value of Υ for the i-th 

individual in the sample, χij is the value of 

independent variable j for unit i, and εi is a 

random error with a mean of zero. 

Country Classification 

The World Bank classifies economies for 

analytical and operational purposes. The main 

criterion for classifying economies is gross 

national income (GNI) per capita. Each 

economy is classified as low income, middle 

income (lower middle income and upper middle 

income), or high income based on its GNI per 

capita. In 2004, the high income group threshold 

was set at a GNI per capita of $10,066 or more. 

Constructs and Variables Used in Study 

Parent education. Students were asked to 

indicate the highest level of education of their 

parent/parents based on national qualifications. 

The students’ responses were then coded in 

accordance with the International Standard 

Classification of Education (ISCED) in order to 

obtain internationally comparable categories for 

the parents’ educational attainment level.15 For 

both mothers’ and fathers’ educational 

attainment there was a range from zero (did not 

 

14 For further information, see Westat (2000). 

15 See United Nations Educational, Scientific, and Cultural 

Organization (1997). 

go to school) to six (completed college). In this 

study, if either of a student’s parents completed a 

bachelor’s, master’s, or postgraduate degree or 

held some sort of postsecondary vocational 

qualification (which correspond to ISCED levels 

5A, 5B, or 6), the student was considered as 

having postsecondary-educated parents. It 

should be noted that the distribution of students 

whose parents have completed a bachelor’s, 

master’s, or postgraduate degree and students 

whose parents hold some sort of postsecondary 

vocational qualification does vary cross 

nationally.

Parent occupational status. Parent occupational 

status is based on either the student’s father’s or 

mother’s occupation (whichever is higher) as 

reported by the student. Occupations were coded 

to the International Standard Classification of 

Occupations 1988 (ISCO-88) and then grouped 

into major occupational groups.16 Values on the 

index range from 16 to 90; low values represent 

low socio-economic status and high values 

represent high socio-economic status. For the 

purposes of this study, the variable was 

transformed into quarters with the “high” 

occupational status group representing the upper 

25 percent. 

Books in the home. Students were asked to 

report how many books they had in their home. 

Students were asked if they had 0-10, 11-25, 26-

100, 101-200, 201-500, or more than 500 books 

at home. For the purposes of this report, these 

categories were collapsed to form a dichotomous 

variable of more than 200 books and 200 or 

fewer books in the home. 

Language spoken at home. Students were asked 

what language they spoke at home always or 

most of the time. In the United States, the 

assessment was given in English and students 

were asked if they spoke English, Spanish, or 

another language. Other countries included 

response options for students to choose an 

official national language other than the language 

 

16 For more information about ISCO-88, see International 

Labor Organization (ILO) (1990). 
24

of the assessment (for example, in Canada, 

students taking an assessment in English could 

choose French) or a national dialect. For the 

purposes of this report, students were grouped 

into two categories: test-language speakers 

(students whose native language was the 

language in which the assessment was 

administered) and non-test-language speakers 

(students whose native language was a language 

other than the one in which the assessment was 

administered). 

Immigrant status. Students were asked to report 

whether or not they and their parents were born 

in the country of assessment or in another 

country. The responses were then grouped into 

two categories: 1) native-born students (those 

students born in the country of assessment 

regardless of parent birthplace) and 2) foreignborn students (those students born outside the 

country of assessment and whose parents were 

born outside of the country).

Family structure. Students were asked to report 

who usually lived at home with them. The 

response categories were then grouped into two 

categories: 1) two-parent households (students 

who reported living with both mother and father) 

and 2) non-two-parent households (all other 

response combinations including single-parent 

families, step-families, and guardian families). It 

should be noted that there was no response 

category for students to indicate whether parents 

were biological or not. 

For further details about the assessment and any 

of the topics discussed here, see the OECD’s 

PISA 2003 Technical Report (Adams in press). 

Acknowledgments 

The authors thank the following people for their 

thoughtful reviews and suggestions that 

improved the quality of this report: Stephen 

Mistler, Pia Peltola, Aparna Sundaram and Jared 

Tank of the Education Statistics Services 

Institute (ESSI); Catherine Freeman, Gail 

Mulligan, Val Plisko, and Bruce Taylor from the 

National Center for Education Statistics (NCES); 

and Andrew White of the Institute of Education 

Sciences (IES). 

For More Information 

For more information about this Statistics in 

Brief, contact Patrick Gonzales, Project Officer, 

National Center for Education Statistics, 1990 K 

Street NW, Washington, DC 20006-5651; or call 

415-920-9229; or e-mail 

patrick.gonzales@ed.gov. For more information 

about the PISA dataset, contact Holly Xie, 

National Center for Education Statistics, 1990 K 

Street NW, Washington, DC 20006-5651; or call 

202-502-7314; or e-mail holly.xie@ed.gov. To 

download files and documentation, visit the 

PISA website (http://nces.ed.gov/surveys/PISA). 
25

Country Percent se Percent se Percent se Percent se Percen

International average 45.8 0.47 54.2 0.47 27.1 0.48 72.9 ▲ 0.48 24.

Australia 54.2 0.80 45.8 ▼ 0.80 30.8 0.68 69.2 ▲ 0.68 34.

Austria 43.2 1.05 56.8 ▲ 1.05 18.0 0.97 82.0 ▲ 0.97 22.Belgium 57.2 0.84 42.8 ▼ 0.84 27.2 0.86 72.8 ▲ 0.86 23.Canada 63.6 0.75 36.4 ▼ 0.75 29.0 0.77 71.0 ▲ 0.77 29.4 Denmark 58.5 1.26 41.5 ▼ 1.26 21.0 1.04 79.0 ▲ 1.04 26.Finland 66.7 0.77 33.3 ▼ 0.77 26.6 0.88 73.4 ▲ 0.88 23.France 37.4 1.05 62.6 ▲ 1.05 21.7 1.02 78.3 ▲ 1.02 21.Germany 41.1 0.96 58.9 ▲ 0.96 21.8 0.90 78.2 ▲ 0.90 29.Greece 41.6 1.76 58.5 ▲ 1.76 20.5 1.57 79.5 ▲ 1.57 17.Iceland 40.3 0.80 59.8 ▲ 0.80 37.1 0.81 62.9 ▼ 0.81 38.Ireland 39.9 1.19 60.1 ▲ 1.19 21.3 1.10 78.7 ▲ 1.10 21.Italy 34.4 0.92 65.7 ▲ 0.92 18.4 0.78 81.6 ▲ 0.78 21.Netherlands 47.6 1.16 52.4 1.16 29.4 1.01 70.6 ▲ 1.01 25.

New Zealand1 44.6 0.78 55.4 ▲ 0.78 28.9 0.87 71.1 ▲ 0.87 29.

Norway 62.8 0.96 37.2 ▼ 0.96 34.5 0.98 65.5 0.98 38.Portugal 25.9 1.15 74.1 ▲ 1.15 13.8 1.07 86.2 ▲ 1.07 16.Spain 38.0 1.50 62.0 ▲ 1.50 14.1 1.00 85.9 ▲ 1.00 27.4 Sweden 60.6 0.94 39.4 ▼ 0.94 27.1 0.87 72.9 ▲ 0.87 36.Switzerland 41.5 1.04 58.5 ▲ 1.04 21.7 1.18 78.3 ▲ 1.18 24.4 United States 48.5 0.99 51.5 0.99 33.2 0.96 66.8 0.96 22.See notes at end of table.

Parent occupational status

Table 1. Percentage distribution and standard errors of 15-year-old students, by select socioeconomic status (SES) and family characterisTable 1. country: 2003 

SES characteristics

Parent education 

Postsecondary Secondary and below High More 

Middle and low 
26

Country Percent se Percent se Percent se Percent se Percent 

International average 90.3 0.35 9.7 0.35 90.5 0.25 9.5 0.25 65.7 

Australia 91.0 0.66 9.0 0.66 87.0 0.72 13.0 ▲ 0.72 69.4 

Austria 91.0 0.74 9.0 0.74 89.7 0.72 10.3 0.72 75.9 

Belgium 83.8 0.80 16.2 ▲ 0.80 92.0 0.73 8.0 0.73 71.9 Canada 86.6 0.74 13.4 ▲ 0.74 79.0 0.95 21.0 ▲ 0.95 70.0 

Denmark 96.1 0.48 3.9 ▼ 0.48 95.4 0.42 4.6 ▼ 0.42 66.3 

Finland 97.1 0.22 2.9 ▼ 0.22 96.9 0.27 3.1 ▼ 0.27 69.7 

France 93.3 0.75 6.7 ▼ 0.75 94.5 0.55 5.5 ▼ 0.55 69.9 

Germany 92.3 0.57 7.7 0.57 83.6 0.85 16.4 ▲ 0.85 74.5 

Greece 96.8 0.39 3.2 ▼ 0.39 92.1 0.69 7.9 0.69 71.2 Iceland 98.4 0.22 1.6 ▼ 0.22 97.4 0.31 2.7 ▼ 0.31 71.2 

Ireland 97.6 0.53 2.4 ▼ 0.53 95.9 0.50 4.1 ▼ 0.50 79.9 

Italy 81.0 1.09 19.0 ▲ 1.09 95.7 0.39 4.4 ▼ 0.39 79.6 

Netherlands 85.4 1.28 14.6 ▲ 1.28 91.7 1.39 8.3 1.39 78.7 New Zealand 90.7 0.70 9.3 0.70 84.9 0.74 15.1 ▲ 0.74 64.9 

Norway 94.8 0.54 5.2 ▼ 0.54 95.1 0.50 4.9 ▼ 0.50 64.0 

Portugal 98.6 0.21 1.4 ▼ 0.21 96.4 1.05 3.6 ▼ 1.05 77.2 

Spain 84.2 1.46 15.8 ▲ 1.46 96.0 0.42 4.0 ▼ 0.42 81.3 

Sweden 92.4 0.71 7.6 0.71 92.8 0.72 7.2 ▼ 0.72 66.0 

Switzerland 87.9 0.70 12.1 ▲ 0.70 87.7 0.58 12.3 ▲ 0.58 73.5 

United States 91.0 0.69 9.0 0.69 90.9 0.45 9.1 0.45 55.3 SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003.

Native born Two-pare

Table 1. Percentage distribution and standard errors of 15-year-old students, by select socioeconomic status (SES) and family characteristiTable 1. country: 2003—Continued

Language in the home Immigrant status 

Family characteristics

always or most of the time at home while "non-test-language" students reported using another language always or most of the time at home. Students living with both their mother and father. The category "non-two-parent family" encompasses all other responses. se means standard error. Detail may 

1The response rate for parent occupational status is below 85 percent.

NOTE: The international average is the weighted mean of the data values for the 20 countries included in the study and reflects the value for a given v

considered as a whole (i.e., one single entity). The international average is not related to the OECD average as referred to in the PISA international repnational reports. The individual country estimates were calculated using the final student weight. The SES and family characteristics are based on stu

parents completed a postsecondary vocational qualification or a bachelor's, master's, or postgraduate degree (corresponding to the International Stand

[ISCED] levels 5A, 5B, or 6), the student was considered as having postsecondary-educated parents. Parent occupational status is based on either of 

(whichever is higher), and the variable was transformed into quarters with "high" occupational status representing the upper quarter. "Test-language" s

Test-language Non-test-language Foreign born

▲ Percentage larger than the respective U.S. percentage (p < .05).▼ Percentage smaller than the respective U.S. percentage (p < .05).
27

Country Score se Score se Score se Score se Score 

International average 519.4 ▲ 1.64 478.9 ▲ 1.55 541.0 ▲ 1.90 486.1 ▲ 1.30 546.5 

Australia 544.1 ▲ 2.56 504.9 ▲ 2.59 564.4 ▲ 2.59 514.3 ▲ 2.02 558.2 

Austria 518.8 ▲ 3.87 499.4 ▲ 3.34 555.0 ▲ 5.30 498.6 ▲ 2.98 564.8 

Belgium 560.6 ▲ 2.59 511.1 ▲ 2.77 589.7 ▲ 3.28 521.8 ▲ 2.61 578.0 

Canada 547.7 ▲ 1.95 517.6 ▲ 1.93 568.3 ▲ 2.57 526.3 ▲ 1.50 564.6 

Denmark 535.7 ▲ 2.95 490.3 ▲ 3.14 562.5 ▲ 4.34 508.5 ▲ 2.71 552.9 

Finland 554.1 ▲ 1.98 526.7 ▲ 2.58 576.4 ▲ 2.94 534.6 ▲ 1.95 578.9 

France 535.1 ▲ 3.03 502.0 ▲ 2.79 559.1 ▲ 4.14 503.2 ▲ 2.53 562.3 

Germany 545.8 ▲ 3.85 493.7 ▲ 3.78 567.7 ▲ 4.03 500.8 ▲ 3.25 562.7 

Greece 466.3 ▼ 5.38 430.0 ▼ 3.21 497.4 ▼ 5.73 436.7 ▼ 3.49 494.0 

Iceland 532.7 ▲ 2.32 504.6 ▲ 1.93 536.5 ▲ 2.67 507.7 ▲ 1.88 540.6 

Ireland 525.4 ▲ 3.20 489.2 ▲ 2.53 545.4 ▲ 3.66 496.1 ▲ 2.34 537.0 

Italy 481.6 ▼ 3.77 457.6 3.31 510.7 ▼ 5.46 459.4 ▼ 3.18 512.2 

Netherlands 566.5 ▲ 3.38 527.2 ▲ 3.50 583.7 ▲ 3.77 531.4 ▲ 3.08 592.3 

New Zealand1 549.6 ▲ 2.83 513.9 ▲ 2.75 564.6 ▲ 3.36 510.7 ▲ 2.37 566.3 

Norway 510.9 2.70 475.0 ▲ 2.63 532.4 3.44 483.1 ▲ 2.42 528.0 

Portugal 492.8 ▼ 5.52 458.7 3.01 532.3 4.20 457.3 ▼ 3.25 525.3 

Spain 510.9 3.03 471.9 ▲ 2.27 534.4 3.82 479.6 ▲ 2.23 529.0 

Sweden 521.0 ▲ 2.80 498.2 ▲ 3.10 554.4 ▲ 3.99 499.8 ▲ 2.31 550.0 

Switzerland 549.0 ▲ 4.64 514.0 ▲ 2.76 570.3 ▲ 4.16 518.6 ▲ 3.21 578.0 

United States 505.6 3.40 464.6 2.97 526.4 3.38 472.2 2.77 536.9 See notes at end of table.

Postsecondary Secondary and below High Middle and low More 

Parent education Parent occupational status 

Table 2. Mean mathematics literacy scores and standard errors of 15-year-old students, by select socioeconomic status (SES) and family 

Table 2. characteristics and country: 2003

SES characteristics
28

Country Score se Score se Score se Score se Score 

International average 502.4 ▲ 1.45 460.2 ▲ 3.30 499.8 ▲ 1.46 444.7 2.98 508.8 

Australia 527.3 ▲ 2.05 515.1 ▲ 5.81 526.2 ▲ 2.08 511.4 ▲ 5.11 534.3 ▲ 

Austria 513.0 ▲ 3.30 456.2 7.20 512.3 ▲ 3.23 447.1 6.22 510.2 

Belgium 541.3 ▲ 2.74 529.6 ▲ 4.77 539.4 ▲ 2.38 413.7 9.11 545.9 ▲ 

Canada 538.6 ▲ 1.63 525.1 ▲ 4.06 537.7 ▲ 1.58 513.0 ▲ 3.84 544.5 ▲ 

Denmark 517.1 ▲ 2.69 474.1 ▲ 10.11 517.2 ▲ 2.65 454.0 8.41 524.8 ▲ 

Finland 546.3 ▲ 1.92 496.0 ▲ 6.68 546.3 ▲ 1.86 481.7 ▲ 8.84 548.4 ▲ 

France 517.7 ▲ 2.43 456.3 8.46 514.7 ▲ 2.30 442.7 10.71 519.0 ▲ 

Germany 523.1 ▲ 3.32 433.6 6.78 518.4 ▲ 3.50 424.4 5.36 514.9 ▲ 

Greece 446.9 ▼ 3.86 399.1 ▼ 9.37 449.1 ▼ 3.92 396.1 ▼ 6.19 452.7 ▼ 

Iceland 516.5 ▲ 1.46 467.6 13.45 516.9 ▲ 1.45 449.2 9.71 520.4 ▲ 

Ireland 503.3 ▲ 2.44 490.2 ▲ 11.73 502.9 ▲ 2.43 500.7 ▲ 13.03 509.7 

Italy 475.1 ▼ 3.04 441.4 6.15 467.7 ▼ 3.06 420.6 7.49 470.0 ▼ 

Netherlands 549.0 ▲ 3.29 524.9 ▲ 8.52 546.9 ▲ 2.89 437.9 10.17 550.8 ▲ 

New Zealand 526.4 ▲ 2.39 507.7 ▲ 6.52 525.8 ▲ 2.39 510.8 ▲ 4.23 538.0 ▲ 

Norway 499.8 ▲ 2.29 449.7 8.10 498.0 ▲ 2.36 439.9 8.14 505.1 

Portugal 467.7 ▼ 3.42 426.8 15.49 469.1 ▼ 2.96 383.7 ▼ 17.04 469.7 ▼ 

Spain 485.3 2.76 485.1 ▲ 4.18 487.1 2.36 435.9 10.19 487.9 ▼ 

Sweden 517.5 ▲ 2.22 456.8 10.00 515.4 ▲ 2.42 427.4 8.40 520.0 ▲ 

Switzerland 540.0 ▲ 3.74 467.2 ▲ 6.14 536.7 ▲ 3.26 454.2 ▲ 5.66 533.4 ▲ 

United States 489.9 2.86 443.7 6.27 487.7 2.88 434.8 6.41 504.5 

▲ Score larger than the respective U.S. score (p < .05).▼ Score smaller than the respective U.S. score (p < .05).

Family characteristics

Table 2. Mean mathematics literacy scores and standard errors of 15-year-old students, by select socioeconomic status (SES) and familyTable 2. characteristics and country: 2003—Continued

Language in the home Immigrant status 

Test-language Non-test-language Native born Foreign born Two-pare

1The response rate for parent occupational status is below 85 percent.

NOTE: The international average is the weighted mean of the data values for the 20 countries included in the study and reflects the value for a given variable 

a whole (i.e., one single entity). The international average is not related to the OECD average as referred to in the PISA international report (OECD 2004) as windividual country estimates were calculated using the final student weight. The SES and family characteristics are based on students' reports. If either of a stupostsecondary vocational qualification or a bachelor's, master's, or postgraduate degree (corresponding to the International Standard Classification of Educatiostudent was considered as having postsecondary-educated parents. Parent occupational status is based on either of the student's parents' occupation (whichtransformed into quarters with "high" occupational status representing the upper quarter. "Test-language" students reported speaking the language in which thSOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003.

"non-test-language" students reported using another language always or most of the time at home. Students from a "two-parent family" reported living with bo"non-two-parent family" encompasses all other responses. se means standard error. 
29

Country Gap se Gap se Gap se Gap se Gap 

International average 40.4 1.69 54.9 1.84 65.9 1.64 42.2 3.41 55.1 

Australia 39.2 3.30 50.2 2.38 50.1 ▼ 2.53 12.2 ▼ 5.61 14.8 ▼ 

Austria 19.5 ▼ 3.82 56.5 4.86 74.1 3.57 56.8 7.25 65.2 Belgium 49.5 3.58 67.9 ▲ 4.33 54.4 ▼ 3.77 11.7 ▼ 5.57 125.7 ▲ 

Canada 30.1 ▼ 2.34 42.0 ▼ 2.69 40.1 ▼ 2.33 13.5 ▼ 3.99 24.6 ▼ 

Denmark 45.4 3.70 54.1 4.83 51.0 ▼ 3.43 43.0 10.08 63.1 

Finland 27.4 ▼ 2.67 41.8 ▼ 3.16 44.5 ▼ 2.94 50.3 7.02 64.6 

France 33.2 3.65 56.0 4.67 63.0 4.34 61.4 8.80 72.1 Germany 52.2 ▲ 4.22 66.9 ▲ 3.98 71.9 3.76 89.5 ▲ 6.58 94.0 ▲ 

Greece 36.3 5.03 60.7 5.58 58.2 5.34 47.7 9.41 53.1 

Iceland 28.0 ▼ 3.20 28.7 ▼ 3.43 39.7 ▼ 3.52 48.9 13.63 67.8 

Ireland 36.2 3.50 49.4 3.99 42.9 ▼ 4.11 13.1 ▼ 11.90 2.2 ▼ 

Italy 24.0 ▼ 3.51 51.3 5.31 58.0 3.92 33.7 6.28 47.2 

Netherlands 39.3 4.07 52.3 4.16 65.7 4.62 24.0 ▼ 9.33 108.9 ▲ 

New Zealand1 35.7 3.70 54.0 3.55 58.1 3.41 18.7 ▼ 6.91 15.0 ▼ 

Norway 35.9 2.81 49.3 3.56 51.6 ▼ 3.16 50.2 8.06 58.2 

Portugal 34.1 4.75 74.9 ▲ 4.31 69.6 5.22 41.0 14.76 85.4 

Spain 38.9 3.06 54.8 4.08 59.5 2.97 0.3 ▼ 5.07 51.3 

Sweden 22.8 ▼ 3.31 54.6 3.84 62.9 3.55 60.8 9.50 88.0 ▲ 

Switzerland 35.0 3.75 51.7 4.11 67.7 3.58 72.8 ▲ 6.26 82.5 ▲ 

United States 41.0 3.52 54.3 3.51 68.0 3.47 46.1 6.48 52.9 Table 3. Mean mathematics literacy achievment gaps and standard errors of 15-year-old students, by select socioeconomic status and Table 3. family characteristics and country: 2003

▲ Achievement gap larger than the respective U.S. achievement gap (p < .05).

NOTE: The international average is the weighted mean of the data values for the 20 countries included in the study and reflects the value for a gcountries are considered as a whole (i.e., one single entity). The international average is not related to the OECD average as referred to in the PI2004) as well as other national reports. The individual country estimates were calculated using the final student weight. The SES and family chastudents' reports. The achievement gap represents the average achievement score point difference of students with postsecondary-educated pawith parents educated to the secondary level or below. If either of a student's parents completed a postsecondary vocational qualification or a bapostgraduate degree (corresponding to the International Standard Classification of Education [ISCED] levels 5A, 5B, or 6), the student was consipostsecondary-educated parents. Student reports of parents’ educational attainment may be inaccurate as some students either do not know or parent education. Parent occupational status is based on either of the student's parents' occupation (whichever is higher), and the variable was trachievement gap for parent occupational status represents the average achievement score point difference of students with one or more parents compared to students with parents whose occupations fell in the lower quarters. The achievement gap for books in the home represents the avedifference between students from homes with more than 200 books in the home and students from homes with 200 or fewer books. The achievehome represents the average achievement difference between test-languange and non-test-language students. "Test-language" students reportwhich the test was administered always or most of the time at home while "non-test-language" students reported using another language always The achievement gap for immigrant status represents the average achievement score point difference between native-born and foreign-born stud

SES characteristics Family characte

SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003.

1The response rate for parent occupational status is below 85 percent.

for family structure represents the average achievement score point difference between students from two-parent families and students from othe

from a "two-parent family" reported living with both their mother and father. The category "non-two-parent family" encompasses all other respons

Parent education Immigrant sta

Parent

occupational status Books in the home

Language 

in the home

▼ Achievement gap smaller than the respective U.S. achievement gap (p < .05).
30

Variables Before After Before After Before After Before After Before After Before After Before After Before Intercept 515.1 494.4 456.2 454.6 529.6 517.9 525.1 502.4 474.1 456.7 496.0 472.3 456.3 458.6 433.6 

(5.81) (5.73) (7.20) (6.75) (4.77) (4.59) (4.06) (4.06) (10.11) (10.79) (6.68) (6.91) (8.46) (7.64) (6.78) 

Family characteristic

Test-language speaker 12.2 3.0 56.8 39.4 11.7 -0.6 13.5 10.3 43.0 31.8 50.3 49.3 61.4 41.3 89.5 

(5.61) (5.68) (7.25) (6.77) (5.57) (4.87) (3.99) (3.76) (10.08) (10.42) (7.02) (7.18) (8.80) (7.93) (6.58) 

SES factors

Parent education

Postsecondary educated † 19.5 † 1.4 † 24.2 † 15.8 † 30.0 † 14.8 † 8.7 † 

† (2.54) † (3.58) † (3.16) † (2.07) † (3.45) † (2.73) † (3.59) † 

Parent occupational status 

High occupational status † 33.9 † 35.2 † 42.1 † 31.6 † 31.1 † 30.8 † 35.3 † 

† (2.06) † (4.52) † (3.89) † (2.72) † (4.76) † (3.52) † (4.70) † 

Number of books in the home

More than 200 books † 37.9 † 62.0 † 32.3 † 30.7 † 35.5 † 34.7 † 47.8 † 

† (2.23) † (3.51) † (3.34) † (2.20) † (3.36) † (2.95) † (3.64) † 

See notes at end of table. Table 4. Coefficients and standard errors from Ordinary Least Squares regression of the achievement of 15-year-old students who are test-language speakers beTable 4. for socioeconomic status (SES) characteristics: 2003

Australia Austria Belgium Canada Denmark Finland France Germ
31

Variables Before After Before After Before After Before After Before After Before After Before After Before Intercept 490.2 477.9 441.4 438.3 524.9 513.6 507.7 472.5 449.7 431.5 426.8 426.9 485.1 463.5 456.8 

(11.73) (11.54) (6.15) (6.35) (8.52) (8.05) (6.52) (7.81) (8.10) (7.51) (15.49) (14.62) (4.18) (4.07) (10.00) 

Family characteristic

Test-language speaker 13.1 8.5 33.7 21.7 24.0 9.0 18.7 27.4 50.2 34.4 41.0 27.8 0.3 0.0 60.8 

(11.90) (11.56) (6.28) (6.63) (9.33) (8.49) (6.91) (7.97) (8.06) (9.02) (14.76) (14.93) (5.07) (4.55) (9.50) 

SES factors

Parent education

Postsecondary educated † 17.7 † -0.8 † 15.8 † 16.7 † 16.9 † -1.0 † 21.7 † 

† (3.30) † (3.19) † (3.86) † (7.97) † (2.90) † (5.05) † (2.90) † 

Parent occupational status

High occupational status † 34.6 † 32.6 † 28.7 † 38.0 † 33.1 † 54.1 † 24.8 † 

† (3.89) † (4.81) † (3.86) † (3.92) † (3.76) † (4.73) † (4.23) † 

Number of books in the home

More than 200 books † 29.7 † 46.3 † 49.4 † 46.8 † 40.8 † 51.2 † 47.0 † 

† (3.74) † (3.78) † (4.41) † (4.05) † (3.27) † (5.80) † (2.89) † 

† Not applicable.

1The response rate for parent occupational status is below 85 percent.

NOTE: SES and family characteristics are based on students' reports. Students from a "two-parent family" reported living with both their mother and father. If either of a student's pqualification or a bachelor's, master's, or postgraduate degree (corresponding to the International Standard Classification of Education [ISCED] levels 5A, 5B, or 6), the student was parents. Parent occupational status is based on either of the student's parents' occupation (whichever is higher), and the variable was transformed into quarters with "high" occupatStandard errors are in parentheses. SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

Netherlands New Zealand Spain Swed

1 Ireland Italy Norway Portugal

Table 4. Coefficients and standard errors from Ordinary Least Squares regression of the achievement of 15-year-old students who are test-language speakers before aTable 4. for socioeconomic status (SES) characteristics: 2003—Continued
32

Variables Before After Before After Before After Before After Before After Before After Before After Befor

Intercept 511.4 489.7 447.1 443.1 413.7 435.9 513.0 501.1 454.0 437.2 481.7 468.7 442.7 444.1 424.

(5.11) (4.62) (6.22) (6.34) (9.11) (7.67) (3.84) (4.57) (8.41) (9.34) (8.84) (8.96) (10.71) (10.73) (5.36

Family characteristic

Native-born student 14.8 6.6 65.2 50.6 125.7 82.4 24.6 10.5 63.1 51.3 64.6 53.2 72.1 53.5 94.

(4.66) (4.24) (5.97) (6.11) (9.42) (7.39) (3.30) (4.06) (8.11) (9.21) (8.81) (9.00) (10.59) (10.38) (6.02

SES factors

Parent education

Postsecondary educated † 20.1 † 1.9 † 21.8 † 16.2 † 30.4 † 14.5 † 9.3 

† (2.47) † (3.53) † (3.16) † (2.07) † (3.33) † (2.69) † (3.47) 

Parent occupational status

High occupational status † 34.2 † 34.7 † 43.6 † 31.9 † 30.9 † 30.2 † 37.0 

† (2.08) † (4.42) † (3.92) † (2.70) † (4.67) † (3.54) † (4.73) 

Number of books in the home

More than 200 books † 38.1 † 61.3 † 30.8 † 30.6 † 34.7 † 34.2 † 47.9 

† (2.14) † (3.46) † (3.04) † (2.16) † (3.24) † (2.98) † (3.64) 

See notes at end of table. 

Australia Denmark Finland 

Table 5. Coefficients and standard errors from Ordinary least squares regression of the achievement of native-born 15-year-old students before and Table 5. for socioeconomic status (SES) characteristics: 2003

Austria Belgium Canada France Ge
33

Variables Before After Before After Before After Before After Before After Before After Before After BefIntercept 500.7 475.2 420.6 417.8 437.9 458.6 510.8 483.1 439.9 427.1 383.7 377.5 435.9 423.6 42

(13.03) (11.63) (7.49) (7.31) (10.17) (7.79) (4.23) (5.59) (8.14) (8.76) (17.04) (18.40) (10.19) (9.51) (8

Family characteristic

Native-born student 2.2 11.0 47.2 35.7 108.9 63.9 15.0 16.0 58.2 37.6 85.4 78.1 51.3 41.3 8

(13.00) (11.39) (7.02) (7.08) (10.86) (7.66) (4.32) (5.43) (8.34) (8.87) (16.79) (18.39) (9.94) (8.90) (8

SES factors

Parent education

Postsecondary educated † 17.9 † 1.5 † 15.6 † 17.3 † 17.0 † 1.8 † 22.5 

† (3.30) † (3.06) † (3.69) † (3.93) † (2.95) † (3.92) † (2.87) 

Parent occupational status

High occupational status † 34.9 † 33.3 † 30.6 † 38.3 † 32.7 † 52.9 † 24.9 

† (3.90) † (5.10) † (3.88) † (3.94) † (3.78) † (4.70) † (4.27) 

Number of books in the home

More than 200 books † 29.8 † 47.7 † 48.5 † 47.2 † 40.1 † 49.8 † 46.0 

† (3.72) † (3.96) † (4.18) † (4.00) † (3.27) † (4.91) † (2.87) 

† Not applicable.

Ireland Italy Netherlands New Zealand Spain 

1 Norway Portugal

NOTE: SES and family characteristics are based on students' reports. Students were asked to report whether or not they and their parents were born in the co

 The responses were then grouped into two categories: 1) native-born students (those students born in the country of assessment regardless of parent birthplac

students born outside the country of assessment and whose parents were also born outside of the country). If either of a student's parents completed a postse

bachelor's, master's, or postgraduate degree (corresponding to the International Standard Classification of Education [ISCED] levels 5A, 5B, or 6), the student w

educated parents. Parent occupational status is based on either of the student's parents' occupation (whichever is higher), and the variable was transformed in

representing the upper quarter. Standard errors are in parentheses. SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

Table 5. Coefficients and standard errors from Ordinary Least Squares regression of the achievement of native-born 15-year-old students before an

Table 5. for socioeconomic status (SES) characteristics: 2003—Continued

1The response rate for parent occupational status is below 85 percent.
34

Variables Before After Before After Before After Before After Before After Before After Before After Before Intercept 503.8 481.8 498.7 482.2 502.4 490.4 516.4 498.1 495.9 472.5 535.7 516.1 497.5 486.6 504.1 

(3.04) (2.52) (3.98) (4.26) (3.27) (3.27) (2.23) (2.55) (3.64) (3.80) (2.91) (3.13) (3.74) (3.70) (5.16) 

Family characteristic

Two-parent family 30.5 21.3 11.5 7.8 43.5 32.6 28.1 19.6 29.0 23.2 12.8 6.5 21.5 13.1 10.8 

(2.74) (2.23) (3.83) (3.63) (2.89) (2.50) (2.19) (1.99) (3.33) (3.43) (2.96) (2.93) (3.85) (3.55) (4.43) 

SES Characteristic

Parent education

Postsecondary educated † 19.3 † 1.0 † 23.2 † 15.0 † 29.5 † 14.4 † 9.2 † 

† (2.54) † (3.64) † (3.24) † (2.06) † (3.46) † (2.71) † (3.53) † 

Parent occupational status 

High occupational status † 33.4 † 36.6 † 42.2 † 30.4 † 29.3 † 29.7 † 36.8 † 

† (2.14) † (4.26) † (4.05) † (2.69) † (4.64) † (3.49) † (4.65) † 

Number of books in the home

More than 200 books † 36.7 † 64.6 † 30.0 † 29.6 † 34.6 † 34.1 † 48.0 † 

† (2.18) † (3.58) † (3.13) † (2.15) † (3.28) † (3.00) † (3.66) † 

See notes at end of table. Table 6. Coefficients and standard errors from Ordinary Least Squares regression of the achievement of 15-year-old students from two-parentTable 6. families before and after controlling for socioeconomic status (SES) characteristics: 2003

Australia Austria Belgium Canada Denmark Finland France Germ
35

Variables Before After Before After Before After Before After Before After Before After Before After BIntercept 476.3 463.8 452.1 439.0 516.5 498.9 499.9 483.2 479.7 452.9 453.1 442.1 474.4 455.2 4

(3.75) (3.77) (4.06) (4.45) (4.52) (4.56) (3.33) (3.71) (2.84) (2.97) (5.46) (4.52) (3.49) (3.31) (

Family characteristic

Two-parent family 33.4 28.3 18.0 17.4 34.3 26.7 38.1 24.6 25.4 17.3 16.6 14.0 13.5 10.2 

(3.77) (3.50) (2.95) (2.97) (4.44) (3.60) (3.44) (4.05) (3.03) (3.06) (4.33) (3.70) (3.26) (3.15) (

SES factors

Parent education

Postsecondary educated † 17.5 † 0.9 † 15.3 † 16.1 † 16.5 † -0.9 † 22.0 

† (3.24) † (3.09) † (3.74) † (3.82) † (3.02) † (4.76) † (2.86) 

Parent occupational status

High occupational status † 33.9 † 33.3 † 30.2 † 35.6 † 32.3 † 55.4 † 24.8 

† (3.80) † (5.01) † (3.66) † (4.01) † (3.70) † (4.89) † (4.28) 

Number of books in the home

More than 200 books † 28.2 † 48.0 † 49.2 † 44.6 † 40.0 † 50.9 † 46.4 

† (3.60) † (3.96) † (4.08) † (3.95) † (3.39) † (5.75) † (2.93) 

† Not applicable.Table 6. Coefficients and standard errors from Ordinary Least Squares regression of the achievement of 15-year-old students from two-parent

Table 6. families before and after controlling for socioeconomic status (SES) characteristics: 2003—Continued

Ireland Italy Portugal

1The response rate for parent occupational status is below 85 percent.

NOTE: SES and family characteristics are based on students' reports. If either of a student's parents completed a postsecondary vocational qualification or a bache

(corresponding to the International Standard Classification of Education [ISCED] levels 5A, 5B, or 6), the student was considered as having postsecondary-educated based on either of the student's parents' occupation (whichever is higher), and the variable was transformed into quarters with "high" occupational status representin

parentheses. SOURCE: Organization for Economic Cooperation and Development (OECD), Program for International Student Assessment (PISA), 2003. 

Netherlands New Zealand Spain 

1 Norway