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Geographical Differences in Italian Students' Mathematical Competencies: Evidence from Pisa 2003

Author

Listed:
  • Massimiliano Bratti

    () (University of Milan)

  • Daniele Checchi

    (University of Milan)

  • Antonio Filippin

    (University of Milan)

Abstract

In this paper we investigate the existence and the size of geographical differences in Italian students’ mathematical competencies. We analyze a novel data set that combines the 2003 wave of the OECD Programme for International Student Assessment (PISA) with information about local economic conditions and school-level administrative data. We find there is significant positive correlation, across provinces, between mathematical literacy and school buildings maintenance and local employment probabilities. About 75% of the North-South differential in mathematical literacy is accounted for by resource differences, while geographical differences in school production functions account for the remaining fraction.

Suggested Citation

  • 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.
  • Handle: RePEc:gde:journl:gde_v66_n3_p299-333
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    References listed on IDEAS

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    1. Giorgio Brunello & Daniele Checchi, 2004. "School Vouchers Italian Style," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 63(3-4), pages 357-399, December.
    2. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    3. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
    4. Edward P. Lazear, 2001. "Educational Production," The Quarterly Journal of Economics, Oxford University Press, vol. 116(3), pages 777-803.
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    Citations

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    Cited by:

    1. Isabella Sulis & Mariano Porcu, 2015. "Assessing Divergences in Mathematics and Reading Achievement in Italian Primary Schools: A Proposal of Adjusted Indicators of School Effectiveness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 607-634, June.
    2. Masci, Chiara & Ieva, Francesca & Agasisti, Tommaso & Paganoni, Anna Maria, 2016. "Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students," Socio-Economic Planning Sciences, Elsevier, vol. 54(C), pages 47-57.
    3. Tommaso Agasisti & Francesca Ieva & Anna Maria Paganoni, 2017. "Heterogeneity, school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(1), pages 157-180, March.
    4. González De San Román, Ainara & De La Rica, Sara, 2016. "Gender Gaps in PISA Test Scores: The Impact of Social Norms and the Mother?s Transmission of Role Attitudes /Brechas de género en los resultados de PISA: El impacto de las normas sociales y la transmi," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 34, pages 79-108, Enero.
    5. González de San Román, Ainara & de la Rica, Sara, 2012. "Gender Gaps in PISA Test Scores: The Impact of Social Norms and the Mother's Transmission of Role Attitudes," IZA Discussion Papers 6338, Institute for the Study of Labor (IZA).
    6. Adriana Di Liberto & Fabiano Schivardi & Giovanni Sulis, 2015. "Managerial practices and student performance," Economic Policy, CEPR;CES;MSH, vol. 30(84), pages 683-728.
    7. Tindara Addabbo & Maddalena Davoli & Marina Murat, 2018. "Is there an immigrant-gender gap in education? An empirical investigation based on PISA data from Italy," Department of Economics 0124, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    8. Giambona, Francesca & Porcu, Mariano, 2015. "Student background determinants of reading achievement in Italy. A quantile regression analysis," International Journal of Educational Development, Elsevier, vol. 44(C), pages 95-107.
    9. repec:eee:soceps:v:61:y:2018:i:c:p:52-69 is not listed on IDEAS
    10. Tindara Addabbo & Maddalena Davoli & Marina Murat, 2018. "Is there an immigrant-gender gap in education? An empirical investigation based on PISA data from Italy," Center for Economic Research (RECent) 136, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    11. Giuseppe Di Giacomo & Aline Pennisi, 2015. "Assessing Primary and Lower Secondary School Efficiency Within Northern, Central and Southern Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(2), pages 287-311, July.
    12. Mariagiulia Matteucci & Stefania Mignani, 2014. "Exploring Regional Differences in the Reading Competencies of Italian Students," Evaluation Review, , vol. 38(3), pages 251-290, June.

    More about this item

    Keywords

    education; PISA; students; territorial differences;

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education

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