How important is the school effect? Schools’ effectiveness in Tuscany

Journal title ECONOMIA PUBBLICA
Author/s Enrico Conti, Silvia Duranti, Carla Rampichini, Nicola Sciclone
Publishing Year 2016 Issue 2015/3
Language Italian Pages 26 P. 59-84 File size 319 KB
DOI 10.3280/EP2015-003003
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The paper aims to provide policy makers a methodological tool to locate schools with “anomalous” performances in terms of effectiveness. The work is inspired by the stream of literature of School Effectiveness Research, which analyses the differences between schools and within schools in relation to pupils' performance indicators, adjusted for observable factors outside the control of schools. The effectiveness of the schools is estimated through a multilevel model, which takes into account the hierarchical structure of the data and allows the disentangle the variability in educational outcomes between the individual level and the school level. Results show that most of the variability in the results of schools is attributable to their net effectiveness, that is their ability to transform inputs into outputs. The proposed method is thus a very useful tool for identifying schools with “anomalous” performance  in terms of effectiveness. The application to the case of Tuscany shows a significant spatial heterogeneity, with some areas characterized by a higher concentration of effective schools.

Keywords: effectiveness; schools; multilevel; Invalsi; spatial heterogeneity; performance

  1. Agasisti T. (2011). The effect of competition on schools’ performance: preliminary evidence from Italy through OECD-PISA data. European Journal of Education, 46(4): 549-565. DOI: 10.1111/apce.12001
  2. Agasisti T., Vittadini G. (2012), Regional Economic Disparities as Determinants of Students’ Achievement in Italy. Research in Applied Economics, 4(2): 33-53. DOI: 10.5296/rae.v4i2.1316
  3. Aitkin M., Longord N. (1986). Statistical Modelling Issues in School Effectiveness Studies. Journal of the Royal Statistical Society, Series A (general), 149(1): 1-43. DOI: 10.2307/2981882
  4. Benadusi L., Fornari R., Giancola O. (2010). La questione dell’equità scolastica in Italia. FGA Working Paper N. 26.
  5. Bratti M., Checchi D. (2013). Re-testing PISA Students One Year Later: On School Value Added Estimation Using OECD-PISA. IZA Discussion Papers 7722.
  6. Bratti M., Checchi D., Filippin A. (2007). Da dove vengono le competenze degli studenti? I divari territoriali nell’Indagine OECD-PISA 2003. Bologna: il Mulino.
  7. Castellano R., Quintano C., Longobardi S. (2009). L’influenza dei fattori socio-economici sulle competenze degli studenti italiani. Un’analisi multilevel dei dati PISA 200. Rivista di Economia e Statistica del territorio, 2: 109-149. DOI: 10.3280/REST2009-002004
  8. Checchi D., Flabbi L. (2007). Intergenerational mobility and schooling decisions in Germany and Italy: the impact of secondary school tracks. IZA Discussion Paper n. 2876.
  9. Cipollone P., Montanaro P., Sestito P. (2010). Value-Added Measures in Italian High Schools: Problems and Findings. Giornale degli Economisti, GDE(Giornale degli Economisti e Annali di Economia), 69(2): 81-114. DOI: 10.2139/ssrn.1670122
  10. Conti E., Duranti S., Sciclone N., Rampichini C. (2014). Learning Outcomes and School’s Effectiveness in Lower Secondary Education: An Analysis for Tuscany, mimeo, presentato al Fifth International Workshop on Applied Economics of Education, 22-24 giugno, Catanzaro.
  11. De Simone G., Gavosto A. (2013). Patterns of Value-Added Creation in the Transition from Primary to Lower Secondary Education in Italy. FGA Working Paper n. 47.
  12. Ferrer-Esteban G. (2011). Beyond the traditional territorial divide in the Italian Education System. FGA Working Paper N. 43.
  13. Fisher R. A. (1935). The Design of Experiments. London: Oliver and Boyd.
  14. Fondazione Agnelli (2010). Rapporto sulla scuola in Italia 2010. Laterza: Roma-Bari.
  15. Giuliano P. (2008). Culture and the Family: An Application to Educational Choices in Italy. Rivista di Politica Economica, 98 4): 3-38.
  16. Goldstein H. (1997). Methods in school effectiveness research. School Effectiveness and School Improvement, 8: 369-395. DOI: 10.1080/0924345970080401
  17. Grilli L., Rampichini C. (2009). Multilevel models for the evaluation of educational institutions: a review. In: Bini M., Monari P., Piccolo D., Salmaso L. (Eds.). Statistical Methods for the Evaluation of Educational Services and Quality of Products. Heidelberg: Physica-Verlag HD, 61-80.
  18. Grilli L., Sani C. (2011). Differential variability of test scores among schools: a multilevel analysis of the fifth‐grade Invalsi test using heteroscedastic random effects. Journal of Applied Quantitative Methods, 6(4): 88‐99.
  19. Hanushek E.A., Woessmann L. (2010). The Economics of International Differences In Educational Achievement. NBER Working Paper Series.
  20. Imbens G., Rubin D. (2015). Causal inference for statistics, social, and biomedical sciences. New York: Cambridge University Press.
  21. INVALSI (2013). Rilevazioni nazionali sugli apprendimenti 2012-2013. Roma: INVALSI.
  22. IRPET (2012). Rapporto sulla scuola e il territorio in Toscana. Firenze: IRPET.
  23. IRPET (2014). Rapporto sulla dispersione scolastica in Toscana. Firenze: IRPET.
  24. Luyten H., Sammons P. (2010). Multilevel Modelling. In: Creemers B.P.M., Kyriakides L., Sammons P. (Eds.). Methodological Advances in Educational Effectiveness Research. London: Routledge Taylor Francis, 246-276.
  25. Martin M.O., Mullis I.V.S. (2013). Timss and Pirls 2011: Relationships Among Reading, Mathematics, and Science Achievement at the Fourth Grade-Implications for Early Learning. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
  26. Mocetti S. (2007). Scelte post-obbligo e dispersione scolastica nella scuola secondaria, mimeo, presentato alla XIX Conferenza SIEP, Pavia, Italia.
  27. Mocetti S. (2012). Educational choices and the selection process: before and after compulsory schooling. Education Economics, 20(2): 189-209. DOI: 10.1080/09645291003726434
  28. Raudenbush S., Willms J. (1995). The estimation of school effects. Journal of Educational and Behavioral Statistics, 20: 307-335. DOI: 10.3102/10769986020004307
  29. Sammons P. (1999). School Effectiveness Coming of Age in the 21st Century. London: Swets & Zeitlinger.
  30. Scheerens J. (2000). Improving school effectiveness. Fundamentals of Educational Planning, 68, UNESCO.
  31. Snijders T.A., Bosker R. (2011). Multilevel analysis: An introduction to basic and advanced multilevel modeling. 2nd edition. London: Sage.
  32. StataCorp (2013). Stata: Release 13. Statistical Software College Station, TX: StataCorp LP.
  33. Strietholt R., Bos W., Gustafsson J.E., Rosén M. (2014). Educational Policy Evaluation through International Comparative Assessments. New York: Waxman.
  34. US National Research Council (2010), Getting Value Out of Value-Added: Report of a Workshop, Washington, DC: The National Academies Press.
  35. van der Werf, Greetje (1997). Differences in School and Instruction Characteristics between High‐, Average‐, and Low‐Effective Schools. School Effectiveness and School Improvement: An International Journal of Research, Policy and Practice, 8: 430-448. DOI: 10.1080/0924345970080403

Enrico Conti, Silvia Duranti, Carla Rampichini, Nicola Sciclone, Quanto conta l’effetto scuola nel ciclo primario? L’efficacia delle istituzioni scolastiche in Toscana in "ECONOMIA PUBBLICA " 3/2015, pp 59-84, DOI: 10.3280/EP2015-003003