{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T10:22:56Z","timestamp":1779358976205,"version":"3.51.4"},"reference-count":12,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T00:00:00Z","timestamp":1755216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>This study presents an extended dataset on educational quality covering 101 countries, from 1970 to 2023. While existing international assessments, such as the Programme for International Student Assessment (PISA) and Trends in International Mathematics and Science Study (TIMSS), offer valuable snapshots of student performance, their limited coverage across countries and years constrains broader analyses. To address this limitation, we harmonized observed test scores across assessments and imputed missing values using both linear interpolation and machine learning (Least Absolute Shrinkage and Selection Operator (LASSO) regression). The dataset included (i) harmonized test scores for 15 year olds, (ii) annual educational quality indicators for the 15\u201319 age group, and (iii) educational quality indexes for the working-age population (15\u201364). These measures are provided in machine-readable formats and support empirical research on human capital, economic development, and global education inequalities across economies.<\/jats:p>","DOI":"10.3390\/data10080130","type":"journal-article","created":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T14:24:28Z","timestamp":1755267868000},"page":"130","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Extended Dataset of Educational Quality Across Countries (1970\u20132023)"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2292-0919","authenticated-orcid":false,"given":"Hanol","family":"Lee","sequence":"first","affiliation":[{"name":"Research Institute of Economics and Management, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu 611130, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3152-4961","authenticated-orcid":false,"given":"Jong-Wha","family":"Lee","sequence":"additional","affiliation":[{"name":"Economics Department, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1038\/s41586-021-03323-7","article-title":"Measuring human capital using global learning data","volume":"592","author":"Angrist","year":"2021","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1080\/00036846.2013.868592","article-title":"A new international database on education quality: 1965\u20132010","volume":"46","author":"Altinok","year":"2014","journal-title":"App. Econ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s10887-023-09239-3","article-title":"Educational quality and disparities in income and growth across countries","volume":"29","author":"Lee","year":"2024","journal-title":"J. Econ. Growth"},{"key":"ref_4","unstructured":"Holland, P.W., and Rubin, D.B. (1982). Observed-score test equating: A mathematical analysis of some ETS equating procedures. Test Equating, Academic Press."},{"key":"ref_5","unstructured":"World Bank (2025, June 14). World Development Indicators. Available online: https:\/\/datacatalog.worldbank.org\/dataset\/world-development-indicators."},{"key":"ref_6","unstructured":"World Bank (2025, June 14). Education Statistics. Available online: https:\/\/datacatalog.worldbank.org\/dataset\/education-statistics."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Che, Z., Purushotham, S., Cho, K., Sontag, D., and Liu, Y. (2018). Recurrent neural networks for multivariate time series with missing values. Sci. Rep., 8.","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Little, R.J., and Rubin, D.B. (2019). Statistical Analysis with Missing Data, John Wiley & Sons. [3rd ed.].","DOI":"10.1002\/9781119482260"},{"key":"ref_9","unstructured":"IEA (2003). TIMSS 2003 International Mathematics Report, TIMSS International Study Centre, Boston College."},{"key":"ref_10","unstructured":"OECD (2004). Learning for Tomorrow\u2019s World, OECD Publishing."},{"key":"ref_11","unstructured":"OECD (2010). Comparing the Similarities and Differences of PISA 2003 and TIMSS, OECD Publishing. OECD Education Working Papers."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.jdeveco.2012.10.001","article-title":"A new data set of educational attainment in the world, 1950\u20132010","volume":"104","author":"Barro","year":"2013","journal-title":"J. Dev. Econ."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/8\/130\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:28:24Z","timestamp":1760034504000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/8\/130"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,15]]},"references-count":12,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["data10080130"],"URL":"https:\/\/doi.org\/10.3390\/data10080130","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,15]]}}}