Search

It is widely discussed that the pandemic has impacted on educational inequalities across the world. However, in contrast to data on health or unemployment, data on education outcomes are not timely. Hence, we have extremely limited knowledge about the actual impact of the pandemic on learning outcomes at the national and the cross-national level. As it might take years to get new comparative evidence on the actual extent of the problem, this paper uses the latest large scale international student assessment data from before the pandemic, the Trends in International Mathematics and Science Study (TIMSS) 2019 and applies simple descriptive analysis, regressions and logical deductions to map potential consequences of the Covid-19 crisis across Europe. We obtain the relative trajectories of children's learning loss and its unequal distribution from information on home and school resources, the importance of these resources for learning outcomes and countries' school closure duration policies and compare Covid-19 related risk of learning loss between European countries. Results based on 4th graders' school achievements indicate that throughout Europe educational inequalities between and within countries are likely to increase substantially. Some European countries are highly likely to face already an education crisis.

Concerns about loneliness and social isolation are growing more than ever. With the COVID-19 pandemic entering its second year, there are fears that the toll on loneliness could have consequences long after the virus recedes. This study offers a comparative overview of the incidence and determinants of loneliness and social isolation in Europe in the pre-COVID-19 period. The empirical results indicate that 8.6% of the adult population in Europe suffer from frequent loneliness and 20.8% from social isolation, with eastern Europe recording the highest prevalence of both phenomena. Trends over time do not indicate any change in the incidence of social isolation following the widespread adoption of social media networks from 2010 onwards. The empirical analysis shows that favourable economic circumstances protect against loneliness and social isolation, while living alone and poor health constitute important loneliness risk factors. Although social isolation increases with age, the elderly do not report more frequent feelings of loneliness than other age groups, all other things being equal. The relative contributions of the different objective circumstances included in the empirical analysis — demographic characteristics, economic conditions, living arrangements, health status, religious beliefs and geographical location — to chronic loneliness and social isolation vary substantially.

Erasmus+ is one of the most popular programmes financed by the European Union. It provides international mobility grants to university students while staying enrolled at their home university. This paper brings novel evidence on the effect of participating in the programme on students' academic outcomes, using rich administrative data from one of the largest public universities in Italy. We rely on a fuzzy Regression Discontinuity Design, since the selection of applicants to Erasmus mobility programmes depends on a continuous score assigned during the application process. Our results show that Erasmus mobility does not delay graduation at the home university and, in addition, it has a positive and significant impact on undergraduates' final degree mark. Investigating possible heterogeneous effects, we find that Erasmus mobility improves graduation results for undergraduate students in scientific and technical fields (STEM) and for those who apply for the Erasmus grant in the first year of their studies. Finally, the positive impact on performance at graduation appears to be stronger for students who visit foreign universities of relatively lower quality compared with their home university and for those who stay abroad for more than six months.

Policies supporting international student mobility prepare young people for the challenges of global and multicultural environments. However, disadvantaged students have lower participation rates in mobility schemes, and hence benefit less from their positive impacts on career progression. Therefore, policy makers aim to make mobility programmes more inclusive. Nevertheless, it is far from clear how policy design can achieve this aim. This study investigates factors driving unequal mobility uptake. It goes beyond existing research by not only focusing on individual choices but also on university characteristics, like university segregation, excellence and student support. In addition, the study is novel in comparing rich graduate survey and administrative data merged with university level ETER data across four countries. Multilevel regression results show consistently across all countries that disadvantaged students do not only lose out on mobility experience due to their background but also due to them being clustered in universities with lower mobility opportunities. Universities' support and excellence while important for explaining mobility uptake do not appear to mitigate unequal uptake in any of the countries examined.

This study shows that the intergenerational transmission of inequality in most of the 28 EU countries is higher than what a parent-to-child paradigm would suggest. While a strand of the literature claims that this is due to a direct grandparental effect, economic historian Gregory Clark maintains that multigenerational mobility follows a Markovian process. In his view, previous estimates of social status persistence are not only (severely) attenuated by an errors-in-variables problem, but are also constant across time and space. Using a survey covering all 28 EU countries, we provide evidence against such a "universal law of mobility". We show that, while in most EU countries traditional estimates of social status persistence are indeed downward biased, there are sizable differences across countries driven by country-specific factors. Further, for a few EU countries we cannot reject the hypothesis of a direct grandparental effect after accounting for a number of parents related covariates possibly affecting the multigenerational transmission process.

International student mobility is the most recognised element of Erasmus+, a major EU policy. Not enough is known about the causal effect of studying abroad on labour market outcomes. This is because most of the existing studies dismiss selection bias: the different composition of students opting and not opting for studying abroad. The purpose of this paper is to answer the following three questions, whilst accounting for selection bias. First, does international student mobility (ISM) have an effect on labour market outcomes? Second, do the returns to ISM vary between two countries with contrasting labour market and education systems? Third, do the returns to ISM differ according to the socio-economic background of the students? Results are compared between Italy and the UK using Italian Institute of National Statistics and UK Higher Education Statistics Agency graduate survey data. Using propensity score matching, the returns to study-related stays abroad are estimated on a set of labour market outcomes around six to twelve months and three years after graduation for undergraduates (UK and Italy) and postgraduates (Italy only). Results indicate that mobility is positively associated with some outcome variables under scrutiny. Mobile graduates seem to benefit from better employment chances than non-mobile graduates. Returns to ISM tend to be slightly higher among graduates in Italy. Mobility seems to matter most for uptake and completion of further post-graduate studies in Italy. It is the especially the socially disadvantaged mobile who opt for further education after graduation.

Consumption surveys often record zero purchases of a good because of a short observation window. Measures of distribution are then precluded and only mean consumption rates can be inferred. We show that Propensity Score Matching can be applied to recover the distribution\ud of consumption rates. We demonstrate the method using the UK National Travel Survey, in which c.40% of motorist households purchase no fuel. Estimated consumption rates are plausible judging by households' annual mileages, and highly skewed. We apply the same approach to estimate CO2 emissions and outcomes of a carbon cap or tax. Reliance on means apparently distorts analysis of such policies because of skewness of the underlying distributions. The regressiveness of a simple tax or cap is overstated, and redistributive\ud features of a revenue-neutral policy are understated.

Consumption surveys often record zero purchases of a good because of a short observation window. Measures of distribution are then precluded and only mean consumption rates can be inferred. We show that Propensity Score Matching can be applied to recover the distribution of consumption rates. We demonstrate the method using the UK National Travel Survey, in which c.40% of motorist households purchase no fuel. Estimated consumption rates are plausible judging by households' annual mileages, and highly skewed. We apply the same approach to estimate CO2 emissions and outcomes of a carbon cap or tax. Reliance on means apparently distorts analysis of such policies because of skewness of the underlying distributions. The regressiveness of a simple tax or cap is overstated, and redistributive features of a revenue-neutral policy are understated.

Consumption surveys often record zero purchases of a good because of a short observation window. Only mean consumption rates can then be inferred. We show that propensity scores can be used to estimate each unit's consumption rate, revealing the distribution. We demonstrate the method using the UK National Travel Survey, in which c.40% of motorist households purchase no fuel. Estimated consumption rates are plausible judging by households' annual mileages, and highly skewed. We apply the same approach to estimate CO2 emissions and direct outcomes of a carbon cap or tax. Analysis of such policies based solely on means appears to have a negative bias, because of skewness of the underlying distributions. The regressiveness of a simple tax or cap is overstated, and redistributive features of a revenue-neutral policy are understated.

Tertiary education has been expanding hugely over the last decades, so that tertiary dropout students will constitute a growing distinctive group in future labour markets. University dropout is regularly discussed as a ‘negative’ indicator in terms of reinforcing socio-economic inequalities and being a sign of university inefficiency. However, research on actual career trajectory of dropout students is virtually non-existent. Using data from the 2011 Programme for the International Assessment of Adult Competencies (PIAAC) this study first validates the uncommon self-reported measure of dropout used and compares the percentage of adults with tertiary dropout experience between EU countries. Second, we examine whether tertiary dropout is a permanent decision as a considerable part of literature assumes. In a third step, we investigate characteristics of adults with dropout experience. Finally, we estimate the effect of dropout in terms of their employment status and success of entering managerial professions comparing results of logistic regressions and propensity score matching taking individuals’ socio-economic and demographic background, work experience and cognitive skills into account.Results indicate that consistently across countries dropout is repeatedly a ‘positive’ indicator in the labour market. This is first due to the fact that the dropout decision is often not a permanent one as well as that for those adults who do not reenrol into tertiary education labour market chances are better than for equally educated adults in about half of the countries examined

Using logistic and multilevel logistic modelling we examine non-response at the school and pupil level to the important educational achievement survey Programme for International Student Assessment (PISA) for England. The analysis exploits unusually rich auxiliary information on all schools and pupils sampled for PISA whether responding or not, including data from two large-scale administrative sources on pupils' results in national public exams, which correlate highly with the PISA target variable. Results show that characteristics associated with non-response differ between the school and pupil levels. The findings have important implications for the survey design of education data.

Does the association between household characteristics and household CO2 emissions differ for different areas such as home energy, transport, indirect and total emissions in the UK? Specific types of households might be more likely to have high emissions in some areas than in others and thus be affected differently by climate mitigation policies that target these areas.Using the Living Costs and Food Survey and Expenditure and Food Survey for the years 2006 to 2009, this paper compares how household characteristics like income, household size, rural/urban location and education level differ in their association with home energy, transport, indirect and total emissions. We find that the association between household characteristics and emissions differs considerably across these areas, particularly for income, education, the presence of children, female headed, workless and rural households. We also test the implicit assumption in the literature that the association between household characteristics and CO2 emission is constant across the CO2 emission distribution using quantile regressions and compare results for poor and rich households. The analysis considers policy implications of these findings throughout.

Due to a lack of emissions data at the household level, studies examining the relationship between UK household CO2 emissions and household characteristics currently rely on expenditure surveys to estimate emissions. There are several possible methods available for doing so but so far there is no discussion in the literature about the advantages and disadvantages related to these options. Such a comparison is relevant because studies in this area often draw policy-relevant conclusions.To address this gap, this paper compares three different methods of estimation to discuss two questions: first, is it at all necessary to convert household expenditure into emissions, given that household expenditure and emissions are strongly correlated, and does research that takes this approach add anything to the insights that already exist in the extensive literature on the determinants of household expenditure? Second, if we assume that it is necessary to convert household expenditure into emissions, are more detailed (and time-consuming) methods of doing so superior to less detailed approaches? The analysis is based on expenditure data from the UK Living Costs and Food Survey 2008-9 and its predecessor the Expenditure and Food Survey 2006-7.

Income is an important correlate for numerous phenomena in the social sciences. But many surveys collect data with just a single question covering all forms of income. This raises issues of quality, and these are heightened when individuals are asked about the household total rather than own income alone. Data are typically banded, implying a loss of information. We investigate the reliability of ‘single-question’ data using the ONS Omnibus and British Social Attitudes (BSA) surveys as examples. We first compare the distributions of income in these surveys – individual income in the Omnibus and household income in the BSA – with those in two other much larger UK surveys that measure income in much greater detail. Second, we investigate an implication of restricting the single question to individual income and interviewing only one adult per household: total income in respondents’ households is unobserved. We therefore examine the relationship between individual and household income in one of the comparator surveys. Third, after imposing bands on comparator survey data, we measure the information loss from banding with Generalised Entropy indices. We then assess its impact on the use of income as a covariate. Disaggregation by gender proves fruitful in much of the analysis.

Within-country differences in educational outcomes are compared for a large group of industrialised countries. We investigate where inequality is greatest, the association between inequality in learning and average levels of learning, the interpretation of measured levels of inequality, and differences in inequality at the top and bottom of the national distributions. Our analysis is based on test score data for 21 countries present in the Trends in International Mathematics and Science Study (TIMSS), the Programme for International Student Assessment (PISA), and the Progress in International Reading Literacy Study (PIRLS). The use of three different surveys avoids reliance on a single source.

The predominant part of the literature states that women are more likely to donate to charitable causes but men are more generous in terms of the amount given. The last result generally derives from the focus on mean amount given. This paper examines gender differences in giving focusing on the distribution of amounts donated and the probability of giving using UK micro-data on individual giving to charitable causes. Results indicate that most women are more generous than men also in terms of the amounts donated. Quantile regression analysis shows that this pattern is robust if we take into account gender differences in individual characteristics such as household structure, education and income. The analysis also examines differences in gender preferences for varying charitable causes. For most of the paper, separate analyses are presented for single and married/cohabiting people, highlighting the very different gender patterns of giving behaviour found in the two groups.

We provide new evidence about the degree of social segregation in England's secondary schools, employing a cross-national perspective. Analysis is based on data for 27 rich industrialised countries from the 2000 and 2003 rounds of the Programme of International Student Assessment (PISA), using a number of different measures of social background and of segregation, and allowing for sampling variation in the estimates. England is shown to be a middle-ranking country, as is the USA. High segregation countries include Austria, Belgium, Germany and Hungary. Low segregation countries include the four Nordic countries and Scotland. In explaining England's position, we argue that its segregation is mostly accounted for by unevenness in social background in the state school sector. Focusing on this sector, we show that cross-country differences in segregation are associated with the prevalence of selective choice of pupils by schools. Low-segregation countries such as those in the Nordic area and Scotland have negligible selection in schools. High segregation countries like Austria, Germany and Hungary have separate school tracks for academic and vocational schooling and, in each case, over half of this is accounted for by unevenness in social background between the different tracks rather than by differences within each track.

International surveys of learning achievement and functional literacy are increasingly common. We consider two aspects of the robustness of their results. First, we compare results from four surveys: TIMSS, PISA, PIRLS and IALS. This contrasts with the standard approach which is to analyse a single survey with no regard as to whether it agrees or not with other sources. Second, we investigate whether results are sensitive to the choice of item response model used by survey organisers to aggregate respondents' answers. In both cases we focus on countries' average scores, the within-country differences in scores, and on the association between the two. There is mixed news to report.

This paper examines differences in educational achievement between immigrants and natives in ten countries with a high population of immigrant pupils: Australia, Canada, France, Germany, the Netherlands, New Zealand, Sweden, Switzerland, the UK and the USA. The first step of the analysis shows how far countries differ regarding immigrants’ educational disadvantage. In a second step, the paper compares immigrants’ characteristics across countries focusing predominantly on socio-economic status, language proficiency, immigrants’ time spent in the host country and patterns of school segregation. Using a regression framework the last step of the analysis investigates how far these determinants of educational achievement can explain immigrants’ educational disadvantage in the countries examined. The paper evaluates whether results found are robust across different sources of achievement data: the Trends in International Maths and Science Study (TIMSS), the Programme of International Student Assessment (PISA) and the Programme of International Reading Literacy Study (PIRLS). (Updated 2005-02-01 for typing errors)

International surveys of educational achievement are typically analysed in isolation from each other with no indication as to whether new results confirm or contradict those from earlier surveys. The paper pulls together results from four surveys to compare average levels of achievement, inequality of achievement, and the correlates of achievement (especially family background) among the six English-speaking OECD countries and between them and countries from Continental Europe. Our aim is to see whether a robust pattern emerges across the different sources: the Trends in International Maths and Science Study (TIMSS), the Programme of International Student Assessment (PISA), the Programme of International Reading Literacy Study (PIRLS) and the International Adult Literacy Survey (IALS).

In Germany, children are sorted into differently prestigious school types according to their ability at the end of primary schooling, normally at age 10. This early decision about children’s future schooling cannot be easily corrected. However, secondary school attendance has a huge impact on future career options, so that equality in pupils’ distribution to differential school types is important. This paper examines the impact of social and economic background on children’s school type if ability is held constant. The analysis is based on national data taken from two surveys of learning achievement, the Third International Mathematics and Science Study (TIMSS) and the Programme of International Student Assessment (PISA). These data reveal that a large share of pupils in less prestigious school types would fit perfectly well in better school types given their measured ability. Children from rural areas, pupils from lower socio-economic backgrounds and boys in general have a significantly lower probability of being selected to the most academic school track even when their ability is similar to that of their urban and better socially placed counterparts.

This chapter provides information on results of international achievement surveys and their use in monitoring educational outcomes in Finland. The educational monitoring system in Finland differs from that of many other countries. So far, little attention has been paid to its lack of standardised measurements and official control. Furthermore, Finnish education policies are strongly driven not by the aim to reach high rankings in international assessments but rather by the emphasis on quality and equity of education. This chapter describes the Finnish education system, its core curriculum for basic education and teacher training. We also review international achievement survey results and the education policy monitoring of the country in general. At the end of the chapter, we take a closer look at some monitoring results that have had an impact on political reforms and policy changes. nonPeerReviewed