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The worldwide school closures in early 2020 led to losses in learning that will not easily be made up for even if schools quickly return to their prior performance levels. These losses will have lasting economic impacts both on the affected students and on each nation unless they are effectively remediated. While the precise learning losses are not yet known, existing research suggests that the students in grades 1-12 affected by the closures might expect some 3 percent lower income over their entire lifetimes. For nations, the lower long-term growth related to such losses might yield an average of 1.5 percent lower annual GDP for the remainder of the century. These economic losses would grow if schools are unable to re-start quickly. The economic losses will be more deeply felt by disadvantaged students. All indications are that students whose families are less able to support out-of-school learning will face larger learning losses than their more advantaged peers, which in turn will translate into deeper losses of lifetime earnings. The present value of the economic losses to nations reach huge proportions. Just returning schools to where they were in 2019 will not avoid such losses. Only making them better can. While a variety of approaches might be attempted, existing research indicates that close attention to the modified re-opening of schools offers strategies that could ameliorate the losses. Specifically, with the expected increase in video-based instruction, matching the skills of the teaching force to the new range of tasks and activities could quickly move schools to heightened performance. Additionally, because the prior disruptions are likely to increase the variations in learning levels within individual classrooms, pivoting to more individualised instruction could leave all students better off as schools resume. As schools move to re-establish their programmes even as the pandemic continues, it is natural to focus considerable attention on the mechanics and logistics of safe re-opening. But the long-term economic impacts also require serious attention, because the losses already suffered demand more than the best of currently considered re-opening approaches.

This study was requested by the Senate International Affairs Committee. The research questions included: (1) What factors affect the cumulative GPA (CGPA) of International students at TRU?; (2) What factors affect the retention of International students at TRU?; and (3) Are Student Success Courses among the significant factors for GPA and retention? The study included 6,051 International students who were enrolled at TRU from 1999/00 to 2009/10 (117 of whom took Student Success Courses). Participation in the Student Success Courses was not found to have a significant effect on either cumulative GPA or retention. The most significant factor affecting cumulative GPA was first term GPA; the most significant factor affecting student retention was cumulative GPA. Appended are: (1) Research Plan; and (2) Variables Included in the Analysis. (Contains 10 tables, 4 figures and 7 footnotes.) [This paper was prepared for the Senate International Affairs Committee.]

Education is recognized to be a key factor of economic development, not only giving access to technological progress as emphasized by the Schumpeterian growth theory, but also entailing numerous social externalities such as the demographic transition (Murtin, 2009) or democratization (Murtin and Wacziarg, 2010). If the evolution of world distributions of income and longevity over the last two centuries have been described by Bourguignon and Morrisson (2002), changes in the world distribution of education have remained unexplored until now, despite their major importance. How has global education inequality evolved over the twentieth century? How should it be measured? Up to now, existing studies on education inequality have had limited spatial and time coverage. For example, Castello and Domenech (2002) and Thomas et al. (2001) provide a descriptive analysis of years of schooling inequality for a broad panel of countries, but their study starts only in 1960. Also, they remain at the country level and do not consider the world distribution of years of schooling, which takes into account educational differences both within and between countries. In contrast, this paper depicts the world distribution of education over 140 years, improving and extending the database recently released by Morrisson and Murtin (2009), which focuses on average years of schooling. The authors provide both average years of schooling and the distribution of education as summarised up by four quantiles in each country. Importantly, this new database is cross-validated by historical data on illiteracy rates. Then, they describe average stocks of primary, secondary and tertiary schooling by region since 1870, and estimate world inequality in years of schooling, which has been dramatically reduced since 1870. Focusing on the measurement of education inequality, this paper raises an important methodological issue. The authors show that a substantial share of inequality in years of schooling can be mechanically explained by a single component of the distribution of education, namely the population that has not attended school, subsequently called the illiterate population. Actually, they find that the observed decrease in inequality in years of schooling over the XXth century is almost entirely explained by the decline in illiteracy. They believe that this result, derived both theoretically and empirically, could help to reconsider an empirical fact discussed in the literature on education inequality (see Berthelemy (2006)), namely the cross-country negative correlation between the average of and the inequality in years of schooling. This correlation mainly reflects the negative and mechanical correlation between average schooling and the illiteracy rate. In line with a recent macroeconomic literature (see for instance Hall and Jones (1999)), the authors then turn to human capital as defined by Mincer (1974), in order to confer a monetary dimension to education. They propose estimates of the world inequality in human capital, examining several definitions for human capital. They focus on one functional form in particular, which accounts for the existence of diminishing returns to schooling. It is the only one that can account for the cross-country negative correlation between Mincer returns to schooling and average years of schooling, as described by Psacharopoulos and Patrinos (2004). At the national level, they find that that human capital inequality within countries has increased then stabilized or even decreased in most regions of the world. When plotted against average years of schooling, human capital inequality within countries has clearly followed an inverted U-shape curve, namely a "Kuznets curve of education". At the global level, they also find that human capital inequality has increased from 1870 to approximatively 1970, then has decreased. They interpret these findings as a consequence of mass education and the existence of diminishing returns to schooling. (Contains 6 tables, 6 figures and 14 footnotes.)

This report presents data on peer-reviewed S&E journals and conference proceedings reflecting the rapidly expanding volume of research activity, the involvement and scientific capabilities different countries, and the expanding research ecosystem demonstrated through international collaborations. Publication output grew about 4% annually over the past 10 years. China and India grew more than the world average, while the United States and European Union grew less than the world average. Research papers from the United States and EU countries had higher impact scores. International collaborations have increased over the past 10 years. [SRI International, Center for Innovation Strategy and Policy assisted with report preparation.]