On the Distribution of Worker Productivity: The Case of Teacher Effectiveness and Student Achievement

References

• Aaronson, D., Barrow, L., and Sander, W. (2007), “Teachers and Student Achievement in the Chicago Public High Schools.” Journal of Labor Economics, 25, 95–135. Retrieved (http://www.journals.uchicago.edu/doi/abs/10.1086/508733).
   Web of Science ®Google Scholar
• Amrein-Beardsley, A. (2014), “Rothstein, Chetty et al., and VAM-Based Bias.” Posted on Vamboozled! October 19, 2014. Available online at http://vamboozled.com/rothstein-chetty-et-al-and-vam-based-bias/
   Google Scholar
• Bacher-Hicks, A., Kane, T., and Staiger, D. (2014), “Validating Teacher Effect Estimates Using Changes in Teacher Assignments in Los Angeles,” NBER Working Paper No. 20657.
   Google Scholar
• Bandiera, O., Barankay, I., and Rasul, I. (2009), “Social Connections and Incentives in the Workplace: Evidence from Personnel Data.” Econometrica, 77, 1047–1094.
   Web of Science ®Google Scholar
• Boyd, D., Grossman, P., Lankford, H., Loeb, S., and Wyckoff, J. (2006), “How Changes in Entry Requirements Alter the Teacher Workforce and Affect Student Achievement,” Education Finance and Policy, 1, 176–216.
   Web of Science ®Google Scholar
• Boyd, D., Grossman, P., Lankford, H., Loeb, S., and Wyckoff, J. (2008), Measuring Effect Sizes: The Effect of Measurement Error. Paper prepared for the National Conference on Value-Added Modeling, University of Wisconsin-Madison. April 22–24, 2008.
   Google Scholar
• Boyd, D. J., Hamp Lankford, S. L., and Wyckoff, J. (2010), Teacher Layoffs: An Empirical Illustration of Seniority vs. Measures of Effectiveness, Washington, DC: National Center for Analysis of Longitudinal Data in Education Research.
   Google Scholar
• Cascio, E. U. and Staiger, D. O. (2012), “Knowledge, Tests, and Fadeout in Educational Interventions,” NBER Working Paper #18038.
   Google Scholar
• Chetty, R., Friedman, J., and Rockoff, J. (2014a), “Measuring the Impacts of Teachers. I: Evaluating Bias in Teacher Value-Added Estimates,” American Economic Review, 104(9), 2593–2632.
   Web of Science ®Google Scholar
• Chetty, R., Friedman, J., and Rockoff, J. (2014b), “Measuring the Impacts of Teachers. II: Teacher Value-Added and Student Outcomes in Adulthood,” American Economic Review, 104(9), 2633–2679.
   Web of Science ®Google Scholar
• Chetty, R., Friedman, J. N., Hilger, N., Saez, E., Schanzenbach, D. W., and Yagan, D. (2011), “How Does Your Kindergarten Classroom Affect Your Earnings? Evidence From Project STAR,” Quarterly Journal of Economics, CXXVI(4), 1593–1660.
   Web of Science ®Google Scholar
• Clotfelter, C., Glennie, E., Ladd, H., and Vigdor, J. (2008), “Teacher Bonuses and Teacher Retention in Low-Performing Schools: Evidence from the North Carolina $1,800 Teacher Bonus Program,” Public Finance Review, 36, 63–87.
   Google Scholar
• Clotfelter, C. T., Ladd, H., and Vigdor, J. L. (2009), “Are Teacher Absences Worth Worrying About in the United States?” Education Finance and Policy, 4(2), 115–149. Retrieved August 4, 2014 (http://www.nber.org/papers/w13648).
   Web of Science ®Google Scholar
• Clotfelter, C., Ladd, H., and Vidgor, J. (2010), “How and Why do Teacher Credentials Matter for Student Achievement?” CALDER Working Paper #2. Available online at http://files.eric.ed.gov/fulltext/ED509655.pdf
   Google Scholar
• Dee, T., and Wyckoff, J. (2013), “Incentives, Selection, and Teacher Performance: Evidence from IMPACT,” NBER Working Paper 19529.
   Google Scholar
• Delaigle, A., and Gijbels, I. (2002), “Estimation of Integrated Squared Density Derivatives from a Contaminated Sample,” Journal of the Royal Statistical Society, Series B, 64, 869–886.
   Google Scholar
• Delaigle, A., and Gijbels, I. (2004), “Practical Bandwidth Selection in Deconvolution Kernel Density Estimation,” Computational Statistics & Data Analysis, 45, 249–267.
   Web of Science ®Google Scholar
• Delaigle, A., and Meister, A. (2008a), “Density Estimation with Heteroscedastic Error,” Bernoulli, 14, 562–579.
   Web of Science ®Google Scholar
• Delaigle, A., Hall, P., and Meister, A. (2008b), “On Deconvolution with Repeated Measurements,” Annals of Statistics, 36, 665–685.
   Web of Science ®Google Scholar
• Finn, J. D., Boyd-Zaharias, J., Fish, R. M., and Gerber, S. B. (2007), Project STAR and Beyond: Database User's Guide. Lebanon, TN: HEROS, Inc.
   Google Scholar
• Folger, J. (1989), “Editor's Introduction: Project STAR and Class Size Policy,” Peabody Journal of Education, LXVII, 1–16.
   Google Scholar
• Garet, M. S., Cronen, S., Eaton, M., Kurki, A., Ludwig, M., Jones, W., Uekawa, K., Falk, A., Bloom, H. S., Doolittle, F., Zhu, P., and Sztejnberg, L. (2008), The Impact of two Professional Development Interventions on Early Reading Instruction and Achievement. Washington, DC: U.S. Department of Education, National Center for Education Statistics.
   Google Scholar
• Glazerman, S., Protik, A., Teh, B.-R., Bruch, J., and Max, J. (2013), “Transfer Incentives for High-Performing Teachers: Final Results from a Multisite Randomized Experiment,” (NCEE 2014–4004). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.
   Google Scholar
• Glazerman, S., Loeb, S., Goldhaber, D., Staiger, D., Raudenbush, S., and Whitehurst, G. (2010), “Evaluating Teachers: The Important Role of Value Added.” Washington, DC: Brown Center on Education Policy at Brookings.
   Google Scholar
• Goldhaber, D. (2006), “National Board Teachers Are More Effective, But Are They In The Classrooms Where They're Needed The Most?” Education Finance and Policy, 1(3), 372–382.
   Web of Science ®Google Scholar
• Goldhaber, D. (2007), “Everyone's Doing It, But What Does Teacher Testing Tell Us About Teacher Effectiveness?” Journal of Human Resources, 42, 765–794.
   Web of Science ®Google Scholar
• Goldhaber (2015), “Exploring the Potential of Value-Added Performance Measures to Affect the Quality of the Teacher Workforce.” Education Researcher, 44(2), 87–95.
   Web of Science ®Google Scholar
• Goldhaber, D., and Chaplin, D. (2015), “Assessing the ‘Rothstein Falsification Test’: Does It Really Show Teacher Value-Added Models Are Biased?” Journal of Research on Educational Effectiveness, 8(1), 8–34.
   Web of Science ®Google Scholar
• Goldhaber, D., and Hansen, M.. (2010), “Race, Gender, and Teacher Testing: How Informative a Tool Is Teacher Licensure Testing?” American Educational Research Journal, 47(1):218–251. Available online at http://aer.sagepub.com/cgi/doi/10.3102/0002831209348970.
   Web of Science ®Google Scholar
• Goldhaber, D., and Hansen, M. (2013), “Is it Just a Bad Class? Assessing the Long-Term Stability of Estimated Teacher Performance,” Economica, 80(319), 589–612.
   Web of Science ®Google Scholar
• Goldhaber, D., and Theobald, R. (2013), “Managing the Teacher Workforce in Austere Times: The Determinants and Implications of Teacher Layoffs.” Education Finance and Policy, 8(4), 494–527. Available online at http://www.cedr.us/papers/working/CEDRWP2011-1.2TeacherLayoffs(6-15-2011).pdf.
   Web of Science ®Google Scholar
• Goldhaber, D., Brewer, D., and Anderson, D. (1999), “A Three-Way Error Components Analysis of Educational Productivity,” Education Economics, 7(3), 199–208.
   Google Scholar
• Goldhaber, D., Cowan, J., and Walch, J. (2013a) “Is a good elementary teacher always good? Assessing teacher performance estimates across subjects,” Economics of Education Review, 36, 216–228.
   Web of Science ®Google Scholar
• Goldhaber, D., Walch, J., and Gabele, B. (2013b) “Does the Model Matter? Exploring the Relationship Between Different Student Achievement-Based Teacher Assessments,” Statistics and Public Policy, 1(1), 1–12.
   Google Scholar
• Goldhaber, D., Lavery, L., and Theobald, R. (2015), “Uneven Playing Field? Assessing the Teacher Quality Gap Between Advantaged and Disadvantaged Students,” Educational Researcher, 44, 293–307.
   Web of Science ®Google Scholar
• Goldhaber, D., Liddle, S., and Theobald, R. (2013c), “The Gateway to the Profession: Assessing Teacher Preparation Programs Based on Student Achievement,” Economics of Education Review, 34, 29–44.
   Web of Science ®Google Scholar
• Gross, B., DeArmond, M., and Goldhaber, D. (2010), “Is it Better to be Good or Lucky? Decentralized Teacher Selection in 10 Elementary Schools,” Education Administration Quarterly, 46(3), 322–362.
   Web of Science ®Google Scholar
• Guarino, C., Maxfield, M., Reckase, M., Thompson, P., and Wooldridge, J. (2015), “An evaluation of empirical bayes' estimation of value-added teacher performance measures,” Journal of Educational and Behavioral Statistics, 40, 190–222.
   Web of Science ®Google Scholar
• Hall, P., and Kang, K.-H. (2001), “Bootstrapping nonparametric density estimators with empirically chosen bandwidths,” The Annals of Statistics, 29, 1443–1468.
   Web of Science ®Google Scholar
• Hanushek, E. (1999), “Some Findings from and Independent Investigation of the Tennessee STAR Experiment and from other Investigations of Class Size,” Educational Evaluation and Policy Analysis, 21, 143–161.
   Web of Science ®Google Scholar
• Hanushek, E. (2009), “Teacher Deselection,” in Creating a New Teaching Profession, D. Goldhaber and J. Hannaway, eds., Washington, DC: Urban Institute Press, 165–180.
   Google Scholar
• Hanushek, E., and Rivkin, S. G. (2010), “Generalizations about Using Value-Added Measures of Teacher Quality,” American Economic Review: Papers and Proceedings, 100, 267–271.
   Web of Science ®Google Scholar
• Jackson, K., and Bruegmann, E. (2009), “Teaching Student and Teaching Each Other: The Importance of Peer Learning for Teachers,” American Economic Journal, 1, 1–27.
   Google Scholar
• Johnson, M. T., Lipscomb, S., and Gill, B. (2015), “Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables,” Journal of Research on Educational Effectiveness, 8, 60–83. doi:10.1080/19345747.2014.967898.
   Web of Science ®Google Scholar
• Kalogrides, D., and Loeb, S. (2013), “Different Teachers, Different Peers: The Magnitude of Student Sorting within Schools,” Educational Researcher, 42, 304–316.
   Web of Science ®Google Scholar
• Kane, T. J., and Staiger, D. O. (2002), “The promises and pitfalls of using imprecise school accountability measures.” Journal of Economic Perspectives, 16, 91–114.
   Web of Science ®Google Scholar
• Kane, T. J., and Staiger, D. O. (2008), “Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation,” NBER Working Paper 14607.
   Google Scholar
• Kane, T. J., and Staiger, D. O. (2012), “Gathering Feedback for Teaching: Combining High-Quality Observations with Student Surveys and Achievement Gains. Research Paper. MET Project,” Bill & Melinda Gates Foundation, Retrieved August 25, 2015 (http://eric.ed.gov/?id=ED540960).
   Google Scholar
• Kane, T. J., McCaffrey, D. F., Miller, T., and Staiger, D. O. (2013), Have We Identified Effective Teachers? Validating Measures of Effective Teaching Using Random Assignment. Available online at www.gatesfoundation.org.
   Google Scholar
• Kane, T. J., Rockoff, J. E., and Staiger, D. O. (2008), “What Does Certification Tell us About Teacher Effectiveness? Evidence from New York City,” Economics of Education Review, 27, 615–631.
   Web of Science ®Google Scholar
• Krieg, J. M. (2006), “Teacher Quality and Attrition.” Economics of Education Review, 25, 13–27.
   Web of Science ®Google Scholar
• Krueger, A. (1999), “Experimental Estimates of Education Production Functions,” The Quarterly Journal of Economics, 114(2), 497–532.
   Web of Science ®Google Scholar
• Lanier, J. (1997), “Redefining the Role of the Teacher: It's a Multifaceted Profession,” Edutopia: What Works in Education. Available online at http://www.edutopia.org/redefining-role-teacher
   Google Scholar
• Lefgren, L., and Sims, D. (2012), “Using Subject Test Scores Efficiently to Predict Teacher Value-Added,” Educational Evaluation and Policy Analysis, Retrieved August 25, 2015 (http://epa.sagepub.com/content/34/1/109.short).
   Web of Science ®Google Scholar
• Lipsey, M. W., Puzio, K., Yun, C., Hebert, M. A., Steinka-Fry, K., Cole, M. W., Roberts, M., Anthony, K. S., and Busick, M. D. (2012), Translating the Statistical Representation of the Effects of Education Intervention into More Readily Interpretable Forms. (NCSER 2013–3000). Washington, DC: National Center for Special Education Research, Institute of Education Sciences, U.S. Department of Education. Available online at http://ies.ed.gov/ncser/.
   Google Scholar
• Mas, A., and Moretti, E. (2009), “Peers at Work,” American Economic Review, 99, 112–145.
   Web of Science ®Google Scholar
• Mayer, T. (1960), “The Distribution of Ability and Earnings,” The Review of Economics and Statistics, 42(2), 189–195.
   Web of Science ®Google Scholar
• McCaffrey, D., Sass, T., Lockwood, J. R., and Mihaly, K. (2009), “The Intertemporal Variability of Teacher Effect Estimates,” Education Finance and Policy, 4:572–606. Available online at http://utla.net/system/files/mccaffrey_study.pdf.
   Web of Science ®Google Scholar
• McGuinn, P. (2010), “Ringing the Bell for K-12 Teacher Tenure Reform,” Center for American Progress Report.
   Google Scholar
• Mehta, N. (2015), “Targeting the Wrong Teachers: Estimating Teacher Quality for Use in Accountability Regimes,” Paper presented at the 2015 annual meeting of the Association for Education Policy and Finance.
   Google Scholar
• Meister, A. (2009), Deconvolution Problems in Nonparametric Statistics, Berlin: Springer.
   Google Scholar
• Nye, B., Konstantopoulos, S., and Hedges, L. V. (2004), “How Large Are Teacher Effects?” Educational Evaluation and Policy Analysis, 26, 237–257.
   Web of Science ®Google Scholar
• Paarsch, H. J., and Shearer, B. S. (1999), “The Response of Worker Effort to Piece Rates: Evidence from the British Columbia Tree-Planting Industry,” Journal of Human Resources, 34, 643–667.
   Web of Science ®Google Scholar
• Pereda-Fernández, S. (2016), “Social Spillovers in the Classroom: Identification, Estimation and Policy Analysis,” Unpublished working paper, Banca d'Italia.
   Google Scholar
• Rivkin, S. G., Hanushek, E. A., and Kain, J. F. (2005), “Teachers, Schools, and Academic Achievement,” Econometrica, 73, 417–458.
   Web of Science ®Google Scholar
• Rockoff, J. E. (2004), “The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data,” American Economic Review, 94(2), Papers and Proceedings of the 116th Annual Meeting of The American Economic Association, 247–252.
   Google Scholar
• Rothstein, J. (2009), “Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables,” Education Finance and Policy, 4, 537–571. Available online at http://mres.gmu.edu/pmwiki/uploads/Main/RothsteinVAM.pdf.
   Web of Science ®Google Scholar
• ——— (2010), “Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement, The Quarterly Journal of Economics, 125, 175–214.
   Web of Science ®Google Scholar
• ——— (2014), “Revisiting the Impacts of Teachers.” Working Paper available online at http://eml.berkeley.edu/∼jrothst/workingpapers/rothstein_cfr.pdf.
   Google Scholar
• ——— (2015), “Teacher Quality Policy When Supply Matters,” American Economic Review, 105, 100–130. Retrieved (http://pubs.aeaweb.org.offcampus.lib.washington.edu/doi/pdfplus/10.1257/aer.20121242).
   Web of Science ®Google Scholar
• TNTP. (2015), “The Mirage: Confronting the Hard Truth About Our Quest for Teacher Development.”
   Google Scholar
• Word, E., Johnston, J., Bain, H., et al. (1990), “The State of Tennessee's Student/Teacher Achievement Ratio (STAR) Project: Technical Report 1985– 1990,” Tennessee State Department of Education, Nashville, TN.
   Google Scholar
• Xu, Z., Ozek, U., and Corritore, M. (2012), “Portability of Teacher Effectiveness Across School Settings,” CALDER Working Paper, 77, 1–54. Available online at papers3://publication/uuid/6AC95688-F063-4E55-97DB-6B74427932C9.
   Google Scholar
• Yoon, K. S., Duncan, T., Lee, S.W.Y., Scarloss, B., and Shapley, K.. (2007), Reviewing the Evidence on how Teacher Professional Development Affects Student Achievement, (Issues & Answers Report, REL 2007–No. 033). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Southwest. Available online at http://ies.ed.gov/ncee/edlabs.
   Google Scholar