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The July 2021 release of learning poverty estimates involves several changes to the data underlying the country-level learning poverty figures. This document provides details of the key changes made. Some country-level estimates have changed or become available for the first time due to new data from recent assessments: TIMSS 2019, PASEC 2019, and SEA-PLM 2019. In cases where new assessment data call for a change to the learning poverty estimates, the corresponding enrollment data used for learning poverty calculations have also been updated so that the enrollment year is as close as possible to the assessment year, depending on data availability. In the latest release, country-level estimates of learning poverty are available for 120 countries.

This paper presents simulations of the potential effect of COVID-19-related school closures on schooling and learning outcomes. It considers four scenarios—varying in both the duration of school closures and the effectiveness of any mitigation strategies being deployed by governments. Using data on 174 countries, the analysis finds that the global level of schooling and learning will fall substantially. School closures could result in a loss of between 0.3 and 1.1 years of schooling adjusted for quality, bringing down the effective years of basic schooling that students achieve during their lifetime from 7.8 years to between 6.7 and 7.5 years. Close to 11 million students from primary up to secondary education could drop out due to the income shock of the pandemic alone. Exclusion and inequality will likely be exacerbated if already marginalized and vulnerable groups, such as girls, ethnic minorities, and persons with disabilities, are more adversely affected by school closures. Students from the current cohort could, on average, face a reduction of $366 to $1,776 in yearly earnings. In present value terms, this amounts to between $6,680 and $32,397 dollars in lost earnings over a typical student's lifetime. Globally, a school shutdown of 5 months could generate learning losses that have a present value of $10 trillion. By this measure, the world could stand to lose as much as 16 percent of the investments that governments make in the basic education of this cohort of students. In the pessimistic and very pessimistic scenarios, cumulative losses could add up to between $16 and $20 trillion in present value terms. Unless drastic remedial action is taken, the world could face a substantial setback in achieving the goal of halving the percentage of learning poor by 2030.

Pakistan was among the first countries in the world to institute widespread school closures as a result of Coronavirus 2019 (COVID-19). What are the expected levels of learning that teachers will have to deal with in the class? Will children have lost learning while schools were closed? What should teachers, parents, and children expect from the first few weeks of schooling? How can parents, teachers, and the school system as a whole help children catch up? While school closures have been effective in supporting efforts at social distancing, they may well have serious consequences for schooling and learning. This note presents results from a series of simulations that aim to capture the impacts that school closures in Pakistan may have on the learning levels, enrollment, and future earnings of children and students. In this note, the authors present an overview of how these numbers are calculated and how to interpret them. This note draws on a simulation exercise for all countries on which data is available, including Pakistan, conducted by researchers at the World Bank.

School closures due to COVID-19 have left more than a billion students out of school. This paper presents the results of simulations considering three, five and seven months of school closure and different levels of mitigation effectiveness resulting in optimistic, intermediate and pessimistic global scenarios. Using data on 157 countries, the analysis finds that the global level of schooling and learning will fall. COVID-19 could result in a loss of between 0.3 and 0.9 years of schooling adjusted for quality, bringing down the effective years of basic schooling that students achieve during their lifetime from 7.9 years to between 7.0 and 7.6 years. Close to 7 million students from primary up to secondary education could drop out due to the income shock of the pandemic alone. Students from the current cohort could, on average, face a reduction of $355, $872, or $1,408 in yearly earnings. In present value terms, this amounts to between $6,472 and $25,680 dollars in lost earnings over a typical student's lifetime. Exclusion and inequality will likely be exacerbated if already marginalized and vulnerable groups, like girls, ethnic minorities, and persons with disabilities, are more adversely affected by the school closures. Globally, a school shutdown of 5 months could generate learning losses that have a present value of $10 trillion. By this measure, the world could stand to lose as much as 16 percent of the investments that governments make in the basic education of this cohort of students. The world could thus face a substantial setback in achieving the goal of halving the percentage of learning poor and be unable to meet the goal by 2030 unless drastic remedial action is taken.

In 2018, the World Bank released World Development Report which showed that the world is facing a ‘Learning Crisis’. Following up from that report, the Bank has launched the Human Capital Project to mobilize more resources, including for the improvement of learning outcomes. Subsequently, global leaders have been increasingly focused on solving this learning crisis and have renewed attention for Sustainable Development Goal 4: Quality Education. Pakistan is an early adopter of this Human Capital Project, and the new government is taking the lead to address the root causes of the learning crisis. This report aims to help the government with that agenda, by quantifying the extent of the learning crisis, and to highlight the main causes of the crisis. According the World Development Report, the ‘Learning Crisis’ consists of three main elements. The first is that access to schooling is still unequally distributed. While there have been huge efforts to expand schooling, there are still countries (including Pakistan) with millions of children out of school. Children living in regions with violence, children from poorer families and children with physical or mental disabilities are still often excluded. The second element is that even those who are in school are often not learning anything at all. In Malawi and Zambia, for instance, 89 percent of students could not read a single word by the end of Grade 2. In India, that figure is 85 percent. These numbers are important, as children who do not master basic literacy will probably never catch up with the curriculum. In other words, schooling is not necessarily the same as learning. The third element of the learning crisis is that the proximate causes of the learning crisis, low quality teaching, student school readiness, school leadership and school inputs, are not systematically addressed by actors in the system. One of the reasons behind this is that there is no systematic data collection on these factors.

Policy makers are increasingly searching for ways to allow more disadvantaged students to access and complete higher education. The quickly growing (quasi-)experimental literature on policy interventions in higher education provide the opportunity to identify the causal effects of these interventions on disadvantaged students and discuss inequality mechanisms at the last stage of the educational system. The paper reviews 75 studies and rigorously compares more than 200 causal effects of outreach and financial aid interventions on the access and completion rates of disadvantaged students in higher education. The paper finds that outreach policies are broadly effective in increasing access for disadvantaged students when these policies include active counseling or simplify the university application process, but not when they only provide general information on higher education. For financial aid, the paper finds that need-based grants do not systematically increase enrollment rates but only lead to improvements when they provide enough money to cover unmet need and/or include an early commitment during high school. Still, need-based grants quite consistently appear to improve the completion rates of disadvantaged students. In contrast, the evidence indicates that merit-based grants only rarely improve the outcomes of disadvantaged students. Finally, interventions combining outreach and financial aid have brought promising results, although more research on these mixed interventions is needed.

Defence date: 13 February 2018 Examining Board: Prof. Hans-Peter Blossfeld, European University Institute (Supervisor); Prof. Fabrizio Bernardi, European University Institute; Prof. Herman van der Werfhorst, University of Amsterdam; Prof. Carlo Barone, Sciences Po Paris Policy-makers are increasingly looking for ways to reduce inequality in higher education. But what is the size of this problem? How does public policy affect inequality, if it at all? And what actually works to reduce inequality? In this thesis, which combines four empirical papers around this topic, I define inequality as the parental background effect on access to and completion of higher education. The broad goal, then, is to better understand how public policy affects intergenerational inequality. I use a variety of data sources and research methods to provide an answer. Cross-sectional population surveys are analyzed to provide a descriptive picture of inequality in Europe. I also use research findings as data, by doing a systematic literature review on the current state of the evidence. I analyse government register data to better understand the effect of policy changes in England. To analyse the dynamics of completion, I use administrative data as well as the administrative archives from the European University Institute. I find that there is substantial variation between European countries in both the absolute level and the trend in inequality. No country has come close to eliminating inequality completely. Public policy may be a factor that explains this cross-country variation. In terms of what works, I find that some outreach policies, particularly those that include counselling and academic tutoring can work to increase access for disadvantaged groups. Needs-based financial aid also seems to work, while performance-based aid looks promising. The relationship between tuition fees and inequality should still be clarified. While there is extensive evidence that costs can be a barrier, recent increases in tuition fees do not seem to have affected inequality in enrolment. Finally, I find that a reinforced program structure as well as more extensive financial aid may help doctoral students from finishing their dissertations more quickly. Chapter 4 'How did the latest increase in fees in England affect student enrollment and inequality?' draws upon an earlier version published as a chapter (2015) in the book 'The European higher education area : between critical reflections and future policies' Chapter 5 'How to increase PhD completion rates? An impact evaluation of two reforms in a selective graduate school, 1976-2012' draws upon an earlier version published as an article 'How to increase PhD completion rates? An impact evaluation of two reforms in a selective graduate school, 1976-2012' (2017) in the journal 'Research in higher education'