IDEAS home Printed from https://ideas.repec.org/p/cdl/indrel/qt5gq4j7kq.html
   My bibliography  Save this paper

Revisiting the Impacts of Teachers

Author

Listed:
  • Rothstein , Jesse

Abstract

Chetty, Friedman, and Rockoff (2014a, 2014b) study value-added (VA) measures of teacher effectiveness. CFR (2014a) exploits teacher switching as a quasi-experiment, concluding that student sorting creates negligible bias in VA scores. CFR (2014b) finds VA scores are useful proxies for teachers’ effects on students’ long-run outcomes. I successfully reproduce each in North Carolina data. But I find that the quasi-experiment is invalid, as teacher switching is correlated with changes in student preparedness. Adjusting for this, I find moderate bias in VA scores, perhaps 10-35% as large, in variance terms, as teachers’ causal effects. Long-run results are sensitive to controls and cannot support strong conclusions.

Suggested Citation

  • Rothstein , Jesse, 2017. "Revisiting the Impacts of Teachers," Institute for Research on Labor and Employment, Working Paper Series qt5gq4j7kq, Institute of Industrial Relations, UC Berkeley.
    • Handle: RePEc:cdl:indrel:qt5gq4j7kq
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/5gq4j7kq.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    2. Thomas J. Kane & Douglas O. Staiger, 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation," NBER Working Papers 14607, National Bureau of Economic Research, Inc.
    3. Jesse Rothstein, 2009. "Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables," Education Finance and Policy, MIT Press, vol. 4(4), pages 537-571, October.
    4. Richard K. Mansfield, 2015. "Teacher Quality and Student Inequality," Journal of Labor Economics, University of Chicago Press, vol. 33(3), pages 751-788.
    5. Cassandra M. Guarino & Mark D. Reckase & Jeffrey M. Woolrdige, 2014. "Can Value-Added Measures of Teacher Performance Be Trusted?," Education Finance and Policy, MIT Press, vol. 10(1), pages 117-156, November.
    6. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2006. "Teacher-Student Matching and the Assessment of Teacher Effectiveness," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
    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. Dan Goldhaber, 2018. "Impact and Your Death Bed: Playing the Long Game," Education Finance and Policy, MIT Press, vol. 13(1), pages 1-18, Winter.
    2. Javaeria Qureshi & Ben Ost, 2019. "Does Teacher‐Family Experience Affect Test Scores?," Contemporary Economic Policy, Western Economic Association International, vol. 37(3), pages 509-523, July.
    3. Jesse Rothstein, 2017. "Measuring the Impacts of Teachers: Comment," American Economic Review, American Economic Association, vol. 107(6), pages 1656-1684, June.

    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. Jesse Rothstein, 2017. "Measuring the Impacts of Teachers: Comment," American Economic Review, American Economic Association, vol. 107(6), pages 1656-1684, June.
    2. Koedel, Cory & Mihaly, Kata & Rockoff, Jonah E., 2015. "Value-added modeling: A review," Economics of Education Review, Elsevier, vol. 47(C), pages 180-195.
    3. Koedel Cory & Leatherman Rebecca & Parsons Eric, 2012. "Test Measurement Error and Inference from Value-Added Models," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 12(1), pages 1-37, November.
    4. Nirav Mehta, 2019. "Measuring quality for use in incentive schemes: The case of “shrinkage” estimators," Quantitative Economics, Econometric Society, vol. 10(4), pages 1537-1577, November.
    5. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 175-214.
    6. Hermann, Zoltán & Horváth, Hedvig, 2022. "Tanári eredményesség és tanár-diák összepárosítás az általános iskolákban. Empirikus mintázatok három magyarországi tankerület adatai alapján [Teacher effectiveness and teacher-student matching in ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1377-1406.
    7. Godstime Osekhebhen Eigbiremolen, 2020. "Estimating Private School Premium for Primary School Children in Ethiopia: Evidence from Individual-level Panel Data," Progress in Development Studies, , vol. 20(1), pages 26-44, January.
    8. 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.
    9. Canales, Andrea & Maldonado, Luis, 2018. "Teacher quality and student achievement in Chile: Linking teachers' contribution and observable characteristics," International Journal of Educational Development, Elsevier, vol. 60(C), pages 33-50.
    10. Jeffrey Max & Steven Glazerman, 2014. "Do Disadvantaged Students Get Less Effective Teaching? Key Findings from Recent Institute of Education Sciences Studies (Evaluation Brief)," Mathematica Policy Research Reports a7da30900bb047038d31acd56, Mathematica Policy Research.
    11. Goldhaber, Dan & Krieg, John & Theobald, Roddy, 2020. "Effective like me? Does having a more productive mentor improve the productivity of mentees?," Labour Economics, Elsevier, vol. 63(C).
    12. Jesse Rothstein, 2009. "Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables," Education Finance and Policy, MIT Press, vol. 4(4), pages 537-571, October.
    13. Nirav Mehta, 2019. "Measuring quality for use in incentive schemes: The case of “shrinkage” estimators," Quantitative Economics, Econometric Society, vol. 10(4), pages 1537-1577, November.
    14. Azam, Mehtabul & Kingdon, Geeta Gandhi, 2015. "Assessing teacher quality in India," Journal of Development Economics, Elsevier, vol. 117(C), pages 74-83.
    15. Hanushek, Eric A. & Rivkin, Steven G. & Schiman, Jeffrey C., 2016. "Dynamic effects of teacher turnover on the quality of instruction," Economics of Education Review, Elsevier, vol. 55(C), pages 132-148.
    16. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
    17. Rockoff, Jonah E. & Speroni, Cecilia, 2011. "Subjective and objective evaluations of teacher effectiveness: Evidence from New York City," Labour Economics, Elsevier, vol. 18(5), pages 687-696, October.
    18. 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.
    19. Dan Goldhaber & Michael Hansen, 2013. "Is it Just a Bad Class? Assessing the Long-term Stability of Estimated Teacher Performance," Economica, London School of Economics and Political Science, vol. 80(319), pages 589-612, July.
    20. Eric Parsons & Cory Koedel & Li Tan, 2019. "Accounting for Student Disadvantage in Value-Added Models," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 144-179, April.

    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:cdl:indrel:qt5gq4j7kq. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/irucbus.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.