Global data set on education quality (1965-2015)
This paper presents the largest globally comparable panel database of education quality. The database includes 163 countries and regions over 1965-2015. The globally comparable achievement outcomes were constructed by linking standardized, psychometrically-robust international and regional achievement tests. The paper contributes to the literature in the following ways: (1) it is the largest and most current globally comparable data set, covering more than 90 percent of the global population; (2) the data set includes 100 developing areas and the most developing countries included in such a data set to date — the countries that have the most to gain from the potential benefits of a high-quality education; (3) the data set contains credible measures of globally comparable achievement distributions as well as mean scores; (4) the data set uses multiple methods to link assessments, including mean and percentile linking methods, thus enhancing the robustness of the data set; (5) the data set includes the standard errors for the estimates, enabling explicit quantification of the degree of reliability of each estimate; and (6) the data set can be disaggregated across gender, socioeconomic status, rural/urban, language, and immigration status, thus enabling greater precision and equity analysis. A first analysis of the data set reveals a few important trends: learning outcomes in developing countries are often clustered at the bottom of the global scale; although variation in performance is high in developing countries, the top performers still often perform worse than the bottom performers in developed countries; gender gaps are relatively small, with high variation in the direction of the gap; and distributions reveal meaningfully different trends than mean scores, with less than 50 percent of students reaching the global minimum threshold of proficiency in developing countries relative to 86 percent in developed countries. The paper also finds a positive and significant association between educational achievement and economic growth. The data set can be used to benchmark global progress on education quality, as well as to uncover potential drivers of education quality, growth, and development.
New, Most Comprehensive Global Dataset on Education Quality The world is facing a learning crisis, particularly in middle and lower income countries, and though theories abound on how best to address it, one things is clear: policymakers and practitioners alike need more and better information to sufficiently address the challenges ahead. Several important international standardized achievement tests such as PISA and TIMSS provide critical data, but these tests are limited because they often exclude developing countries and only date back to the mid-1990s. Our new working paper, A Global Dataset on Education Quality (1965-2015), addresses that information gap. In it, we present the largest and most current globally comparable dataset on education quality, with harmonized learning scores for 163 countries and regions that covers more than 90 percent of the world’s population. This new World Bank dataset offers a longer time horizon and includes more countries, especially lower income, than any other previous attempt to capture educational information on so granular a level…
What keeps the President of the World Bank up at night? This year’s World Economic Forum Annual Meeting comes at a time of good news for the world economy. As we said in this month’s Global Economic Prospects report, for the first time since the financial crisis, the World Bank is forecasting that the global economy will be operating at or near full capacity. We anticipate growth in advanced economies to moderate slightly, but growth in emerging markets and developing countries should strengthen to 4.5% this year…
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