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Regional inequalities in PISA: the case of Italy and Spain

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This technical brief analyses the regional distribution of skills in Italy and Spain. Educational attainment rates have frequently been used as an indicator of regional educational development in EU Member States (MS). These rates indicate significant regional disparities in education within countries. However, recent evidence shows that the quality of education, as measured by the level of specific skills, is more important than the number of years one spends in school, in particular when considering the relationship between the cognitive (and non-cognitive) skills and economic growth. International large scale assessments (ILSA) of student performance measure these cognitive skills in key areas. OECD’s Program for International Student Assessment (PISA) provides a very useful and important source of information of students' performance in key cognitive skills. When analysing PISA data, researchers and commentators often focus on cross-country comparisons. However, vast within-country differences exist, also in terms of educational attainment and PISA test scores. A focus on country averages alone would hence provide only a partial view of the status of education within countries. However, the possibility of exploring within-country differences with PISA data is limited to only a few countries. In this report we focus on regional inequalities in cognitive skills (as measured by PISA test scores) in Italy and Spain, using regional PISA data from the most recent 2015 wave, and we analyse the factors that are associated with these inequalities. In order to insure full comparability between the two countries we define regions at the level of NUTS1 (macro-region), following Eurostat’s official NUTS 2013 classification. We investigate regional inequalities by using descriptive statistics, by running a range of OLS regression models that allow us to analyse the associations between PISA 2015 science scores and the explanatory variables within regions and finally by using the Blinder-Oaxaca decomposition method to specify the factors that are related to within-country differences. The results show that there are significant regional differences in PISA scores within both MS. There are several factors that are associated with regional differences within Italy and Spain. The factors most consistently positively associated with regional science achievement are teacher-directed teaching and epistemological beliefs, while grade repetition and truancy are significantly negatively related with achievement. Still, there is also a range of other relevant factors varying between and within both MS. The Blinder-Oaxaca decomposition also shows that variables such as the socio-economic background, the students’ expected occupation, learning outside school time, truancy, immigrant status and grade repetition matter for within-country differences. Our results suggest that policy makers should focus on finding solutions to limit truancy and rethink grade repetition to leverage scores in lower performing regions. Moreover, our results with regard to epistemological beliefs and teaching practices challenge thinking about how science should be taught in schools in Italy and Spain. The specific results for each region may allow policy makers to consider more in detail how a region stands in comparison to the rest of the country, and the specific factors that need to be addressed to improve the within-country inequality related to educational achievement.

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  • Ralph Hippe & Maciej Jakubowski & Luisa De Sousa Lobo Borges de Araujo, 2018. "Regional inequalities in PISA: the case of Italy and Spain," JRC Research Reports JRC109057, Joint Research Centre.
  • Handle: RePEc:ipt:iptwpa:jrc109057
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    1. Peter Dolton & Oscar D. Marcenaro-Gutierrez, 2011. "If you pay peanuts do you get monkeys? A cross-country analysis of teacher pay and pupil performance [Discrimination in the market for public school teachers]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 26(65), pages 5-55.
    2. Ruhose, Jens & Schwerdt, Guido, 2016. "Does early educational tracking increase migrant-native achievement gaps? Differences-in-differences evidence across countries," Economics of Education Review, Elsevier, vol. 52(C), pages 134-154.
    3. Massimiliano Bratti & Daniele Checchi & Antonio Filippin, 2007. "Geographical Differences in Italian Students' Mathematical Competencies: Evidence from Pisa 2003," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 66(3), pages 299-333, November.
    4. Nicola Gennaioli & Rafael La Porta & Florencio Lopez-de-Silanes & Andrei Shleifer, 2013. "Human Capital and Regional Development," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 105-164.
    5. Claude Diebolt & Ralph Hippe, 2018. "Remoteness equals backwardness? Human capital and market access in the European regions: insights from the long run," Education Economics, Taylor & Francis Journals, vol. 26(3), pages 285-304, May.
    6. Agasisti, Tommaso & Cordero-Ferrera, Jose M., 2013. "Educational disparities across regions: A multilevel analysis for Italy and Spain," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1079-1102.
    7. Daniele Checchi, 2004. "Da dove vengono le competenze scolastiche?," Stato e mercato, Società editrice il Mulino, issue 3, pages 413-454.
    8. Hanushek, Eric A. & Woessmann, Ludger, 2015. "The Knowledge Capital of Nations: Education and the Economics of Growth," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262029170, December.
    9. Andrés Fuentes, 2009. "Raising Education Outcomes in Spain," OECD Economics Department Working Papers 666, OECD Publishing.
    10. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    11. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    12. Asma Benhenda & Julien Grenet, 2015. "How much does grade repetition in French primary and secondary schools cost?," Post-Print halshs-02539810, HAL.
    13. Gabriele Cappelli, 2016. "Escaping from a human capital trap? Italy's regions and the move to centralized primary schooling, 1861–1936," European Review of Economic History, European Historical Economics Society, vol. 20(1), pages 46-65.
    14. Joerg Baten & Ralph Hippe, 2018. "Geography, land inequality and regional numeracy in Europe in historical perspective," Journal of Economic Growth, Springer, vol. 23(1), pages 79-109, March.
    15. Hanushek, Eric A. & Luque, Javier A., 2003. "Efficiency and equity in schools around the world," Economics of Education Review, Elsevier, vol. 22(5), pages 481-502, October.
    16. Ciccone, Antonio & Garcia-Fontes, Walter, 2009. "The quality of the Catalan and Spanish education systems: A perspective from PISA," IESE Research Papers D/810, IESE Business School.
    17. Asma Benhenda & Julien Grenet, 2015. "How much does grade repetition in French primary and secondary schools cost?," PSE-Ecole d'économie de Paris (Postprint) halshs-02539810, HAL.
    18. Mariagiulia Matteucci & Stefania Mignani, 2014. "Exploring Regional Differences in the Reading Competencies of Italian Students," Evaluation Review, , vol. 38(3), pages 251-290, June.
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    1. Orazio Giancola & Luca Salmieri, 2020. "Family Background, School-Track and Macro-Area: the Complex Chains of Education Inequalities in Italy," Working Papers 4/20, Sapienza University of Rome, DISS.
    2. Svetoslav Danchev & Georgios Gatopoulos & Niki Kalavrezou & Nikolaos Vettas, 2023. "Intergenerational Mobility in Education in Greece: an exploration into socioeconomic determinants of students' performance and future career plans before, during and after the crisis," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 185, Hellenic Observatory, LSE.
    3. Ralph Hippe & Maciej Jakubowski, 2018. "Immigrant background and expected early school leaving in Europe: evidence from PISA," JRC Research Reports JRC109065, Joint Research Centre.
    4. Rikkert M. van der Lans & Ridwan Maulana & Michelle Helms-Lorenz & Carmen-María Fernández-García & Seyeoung Chun & Thelma de Jager & Yulia Irnidayanti & Mercedes Inda-Caro & Okhwa Lee & Thys Coetze, 2021. "Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance," SAGE Open, , vol. 11(3), pages 21582440211, August.

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    Keywords

    Regions; Europe; PISA; education; skills; multilevel analysis;
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