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Assumptions of Value-Added Models for Estimating School Effects


  • Sean F. Reardon

    () (School of Education, Stanford University)

  • Stephen W. Raudenbush

    () (Department of Sociology, University of Chicago)


The ability of school (or teacher) value-added models to provide unbiased estimates of school (or teacher) effects rests on a set of assumptions. In this article, we identify six assumptions that are required so that the estimands of such models are well defined and the models are able to recover the desired parameters from observable data. These assumptions are (1) manipulability, (2) no interference between units, (3) interval scale metric, (4) homogeneity of effects, (5) strongly ignorable assignment, and (6) functional form. We discuss the plausibility of these assumptions and the consequences of their violation. In particular, because the consequences of violations of the last three assumptions have not been assessed in prior literature, we conduct a set of simulation analyses to investigate the extent to which plausible violations of them alter inferences from value-added models. We find that modest violations of these assumptions degrade the quality of value-added estimates but that models that explicitly account for heterogeneity of school effects are less affected by violations of the other assumptions. © 2009 American Education Finance Association

Suggested Citation

  • Sean F. Reardon & Stephen W. Raudenbush, 2009. "Assumptions of Value-Added Models for Estimating School Effects," Education Finance and Policy, MIT Press, vol. 4(4), pages 492-519, October.
  • Handle: RePEc:tpr:edfpol:v:4:y:2009:i:4:p:492-519

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    References listed on IDEAS

    1. repec:fth:prinin:366 is not listed on IDEAS
    2. Hanushek, Eric A., 2002. "Publicly provided education," Handbook of Public Economics,in: A. J. Auerbach & M. Feldstein (ed.), Handbook of Public Economics, edition 1, volume 4, chapter 30, pages 2045-2141 Elsevier.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    4. Card, David & Krueger, Alan B, 1992. "Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 1-40, February.
    5. David Card & Alan B. Krueger, 1996. "School Resources and Student Outcomes: An Overview of the Literature and New Evidence from North and South Carolina," Journal of Economic Perspectives, American Economic Association, vol. 10(4), pages 31-50, Fall.
    6. Jörn-Steffen Pischke, 2007. "The Impact of Length of the School Year on Student Performance and Earnings: Evidence From the German Short School Years," Economic Journal, Royal Economic Society, vol. 117(523), pages 1216-1242, October.
    7. Marcotte, Dave E., 2007. "Schooling and test scores: A mother-natural experiment," Economics of Education Review, Elsevier, vol. 26(5), pages 629-640, October.
    8. Ozkan Eren & Daniel Millimet, 2007. "Time to learn? The organizational structure of schools and student achievement," Empirical Economics, Springer, vol. 32(2), pages 301-332, May.
    9. David Card & Alan Krueger, 1996. "School Resources and Student Outcomes: An Overview of the Literature and New Evidence from North and South Carolina," Working Papers 745, Princeton University, Department of Economics, Industrial Relations Section..
    10. Grogger, Jeff, 1996. "Does School Quality Explain the Recent Black/White Wage Trend?," Journal of Labor Economics, University of Chicago Press, vol. 14(2), pages 231-253, April.
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    Cited by:

    1. Lindsay Fox, 2016. "Playing to Teachers’ Strengths: Using Multiple Measures of Teacher Effectiveness to Improve Teacher Assignments," Education Finance and Policy, MIT Press, vol. 11(1), pages 70-96, Winter.
    2. Papay, John P. & Kraft, Matthew A., 2015. "Productivity returns to experience in the teacher labor market: Methodological challenges and new evidence on long-term career improvement," Journal of Public Economics, Elsevier, vol. 130(C), pages 105-119.
    3. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.
    4. Condie, Scott & Lefgren, Lars & Sims, David, 2014. "Teacher heterogeneity, value-added and education policy," Economics of Education Review, Elsevier, vol. 40(C), pages 76-92.
    5. Gary Henry & Roderick Rose & Doug Lauen, 2014. "Are value-added models good enough for teacher evaluations? Assessing commonly used models with simulated and actual data," Investigaciones de Economía de la Educación volume 9,in: Adela García Aracil & Isabel Neira Gómez (ed.), Investigaciones de Economía de la Educación 9, edition 1, volume 9, chapter 20, pages 383-405 Asociación de Economía de la Educación.

    More about this item


    value-added models; School effects; teacher effects;

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education


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