IDEAS home Printed from https://ideas.repec.org/p/css/wpaper/2008-06.html
   My bibliography  Save this paper

Quantile regressions analysis of the Italian school system

Author

Listed:
  • Marilena Furno

    (University of Cassino)

Abstract

The score on a reading literacy test of 15 years old Italian students is here analyzed. The data depict a fracture in the Italian school system. By means of quantile regressions and by repeatedly implementing a quantile regression based test for structural break, computed in different sub-samples and at various quantiles, one can pin down the determinants of the gap and rank them. We find that the difference in curricula is the main factor in explaining the gap in the students scores; that the regional difference is linked to structural and behavioral variables, like poor library facilities and students absenteeism, both mirroring the economic lag of the southern Italian regions. In terms of policy actions, curbing absenteeism in the south can reduce the regional gap. If instead the target is to enhance excellence, funds should be directed toward academic track, public schools, north-centre regions.

Suggested Citation

  • Marilena Furno, 2008. "Quantile regressions analysis of the Italian school system," Working Papers 2008-06, Universita' di Cassino, Dipartimento di Economia e Giurisprudenza.
    • Handle: RePEc:css:wpaper:2008-06
    as

    Download full text from publisher

    File URL: https://dipeg-wpe.unicas.it/dipse/files/wp200806.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. D. W. K. Andrews, 2003. "End-of-Sample Instability Tests," Econometrica, Econometric Society, vol. 71(6), pages 1661-1694, November.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Bai, Jushan, 1995. "Least Absolute Deviation Estimation of a Shift," Econometric Theory, Cambridge University Press, vol. 11(3), pages 403-436, June.
    4. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    5. Leslie G. Godfrey & Chris D. Orme, 2000. "Controlling the significance levels of prediction error tests for linear regression models," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 66-83.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    2. Marilena Furno, 2012. "Tests for structural break in quantile regressions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(4), pages 493-515, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Furno, Marilena, 2013. "Quantile regression and structural change in the Italian wage equation," Economic Modelling, Elsevier, vol. 30(C), pages 420-434.
    2. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    3. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    4. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    5. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    6. Chunbei Wang & Le Wang, 2011. "Language Skills and the Earnings Distribution Among Child Immigrants," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 50(2), pages 297-322, April.
    7. Chesher, Andrew, 2017. "Understanding the effect of measurement error on quantile regressions," Journal of Econometrics, Elsevier, vol. 200(2), pages 223-237.
    8. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.
    9. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
    10. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    11. Shabbar Jaffry & Yaseen Ghulam & Vyoma Shah, 2007. "Returns to Education in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 46(4), pages 833-852.
    12. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    13. Chen, Xirong & Li, Degui & Li, Qi & Li, Zheng, 2019. "Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates," Journal of Econometrics, Elsevier, vol. 212(2), pages 433-450.
    14. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    15. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    16. Katarzyna Burzynska & Olle Berggren, 2015. "The Impact of Social Beliefs on Microfinance Performance," Journal of International Development, John Wiley & Sons, Ltd., vol. 27(7), pages 1074-1097, October.
    17. Pereda-Fernández, Santiago, 2023. "Identification and estimation of triangular models with a binary treatment," Journal of Econometrics, Elsevier, vol. 234(2), pages 585-623.
    18. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    19. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2013. "Assessing model adequacy in possibly misspecified quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 558-569.
    20. Rahman, Mustafizur & Al-Hasan, Md., 2018. "Returns to Schooling in Bangladesh Revisited: An Instrumental Variable Quantile Regression Approach," Bangladesh Development Studies, Bangladesh Institute of Development Studies (BIDS), vol. 41(02), pages 27-42, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:css:wpaper:2008-06. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gennaro Zezza (email available below). General contact details of provider: https://edirc.repec.org/data/dccasit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.