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The effect of school resources on test scores in England

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  • Cheti Nicoletti
  • Birgitta Rabe

Abstract

We analyze the effect of school expenditure on children's test scores at age 16 by means of an education production model. By using unique register data of English pupils, we exploit the availability of test scores across time, subjects and siblings to control for various sources of input omission and measurement error bias. We overcome one of the main criticisms against the value-added model by proposing a novel method to control for the endogeneity of the lagged test. We find evidence of a positive but small effect of per pupil expenditure on test scores.

Suggested Citation

  • Cheti Nicoletti & Birgitta Rabe, 2013. "The effect of school resources on test scores in England," CHILD Working Papers Series 15, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
  • Handle: RePEc:cca:wchild:15
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    References listed on IDEAS

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    1. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 497-532.
    2. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja & Tristan Zajonc, 2011. "Do Value-Added Estimates Add Value? Accounting for Learning Dynamics," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 29-54, July.
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    6. Stephen Gibbons & Sandra McNally & Martina Viarengo, 2018. "Does Additional Spending Help Urban Schools? An Evaluation Using Boundary Discontinuities," Journal of the European Economic Association, European Economic Association, vol. 16(5), pages 1618-1668.
    7. Flavio Cunha & James J. Heckman, 2008. "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
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    Cited by:

    1. Cheti Nicoletti & Birgitta Rabe, 2019. "Sibling spillover effects in school achievement," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 482-501, June.
    2. Gibbons, Stephen & Silva, Olmo & Weinhardt, Felix, 2017. "Neighbourhood Turnover and Teenage Attainment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 746-783.
    3. Gabriella Conti & Mark Hanson & Hazel Inskip & Sarah Crozier & Cyrus Cooper & Keith Godfrey, 2018. "Beyond Birth Weight: The Origins of Human Capital," Working Papers 2018-089, Human Capital and Economic Opportunity Working Group.
    4. Marie Hyland & Richard Layte & Seán Lyons & Selina McCoy & Mary Silles, 2015. "Are Classroom Internet Use and Academic Performance Higher after Government Broadband Subsidies to Primary Schools?," The Economic and Social Review, Economic and Social Studies, vol. 46(3), pages 399-428.
    5. Annemarie Künn-Nelen & Andries Grip & Didier Fouarge, 2015. "The Relation Between Maternal Work Hours and the Cognitive Development of Young School-Aged Children," De Economist, Springer, vol. 163(2), pages 203-232, June.
    6. Stephen Gibbons & Sandra McNally, 2013. "The Effects of Resources Across School Phases: A Summary of Recent Evidence," CEP Discussion Papers dp1226, Centre for Economic Performance, LSE.

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    More about this item

    Keywords

    Education production function; cognitive achievements; child development JEL codes: I22; I24;
    All these keywords.

    JEL classification:

    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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