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«Draft, April 21, 2008 Teacher Effects: What Do We Know? Helen F. Ladd Edgar Thompson Professor of Public Policy Studies and professor of economics Duke ...»

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Magnitudes of the effects To the extent that Boyd et al (in progress) are correct that the estimated effect sizes should be adjusted upward to take account of measurement error, these North Carolina estimates, like the those for New York City, substantially underestimate the relevant effect sizes. We have also used other methods for evaluating the effect sizes. In our work on elementary school teachers we compare the predicted effects of teachers with “strong” bundles of credentials with those of teachers with “weak” bundles and conclude that the effects of teacher credentials are sufficiently large to offset the estimated effects of low parental education on student achievement for math but not fully for reading. In addition we conclude that teacher credentials are far more predictive of student achievement than class size reductions of moderate size. At the high school level, we conclude that a teacher at the 90th percentile of the predicted distribution of the achievement based on teacher credentials would increase student achievement by about 0.18 standard deviations relative to a teacher at the 10 th percentile. Thus, we conclude that teacher credentials are important predictors of student achievement. At the same time, however, we are careful to note that teachers with similar bundles of credentials exhibit substantial variation in their effectiveness.

Ladd, Teacher Effects, Draft April 21, 2008 References.

Aaronson, Daniel, Lisa Barrow, and William Sander. 2007. “Teachers and Student Achievement in the Chicago Public High Schools,” Journal of Labor Economics 25:95-135.

Ballou, Dale. 2005. “Value-added assessment: Lessons from Tennessee.” In R. Lissetz (ed.) Value Added Models in Education: Theory and Applications. Maple Grove, MN: JAM Press.

Ballou, Dale, William Sanders and Paul Wright. 2004. “Controlling for Student Background in Value-Added Assessment of Teachers.” Journal of Educational and Behavioral Statistics, 29 (1), pp. 37-66.

Boyd, Don, Pam Grossman, Hamp Lankford, Susanna Loeb, and James Wyckoff. In progress.

“Measuring Effect Sizes: The Effect of Measurement Error.” Paper presented at the American Education Finance Association Meetings, April, 2008 in Denver, Colorado.

Corneliβen, Thomas. 2006. “Using Stata for a Memory Saving Fixed Effects Estimation of the Three-Way Error Component Model.” Unpublished. Hannover: University of Hannover.

Clotfelter, C.T., Ladd, H.F., & Vigdor, J.L. (2006). “Teacher-student matching and the assessment of teacher effectiveness.” Journal of Human Resources, XLI (4), 778-820.

Clotfelter, C. T., H. F. Ladd, and J. L. Vigdor.( 2007a). “Teacher Credentials and Student Achievement: Longitudinal Analysis with Student Fixed Effects.” Economics of Education Review. December.

Clotflelter, C.T., Ladd, H.F., & Vigdor, J.L. (2007b). “How and why teacher credentials matter for student achievement.” National Bureau of Economic Research Working Paper.12828. Also available on the CALDERweb site (Caldercenter. org)..

Clotfelter, C.T., H.F. Ladd, & J.L. Vigdor (2007c) “Teacher Credentials and Student Achievement in High School: A Cross-Subject Analysis with Student Fixed Effects.” National Bureau of Economic Research Working Paper 13617. Also available on the CALDER web site (Caldercenter. Org).

Goldhaber, Dan. 2008. “Teachers Matter, but Effective Teacher Quality Policies are Elusive.” In Helen F. Ladd and Edward B. Fiske, eds, Handbook of Research in Education Finance and Policy. New York and London: Routledge. Pp.146-165.

Hanushek, Eric A. 1997. “Assessing the Effects of School Resources on Student Performance:

An Update” Educational Evaluation and Policy Analysis. 19(2): 141-164.

Hanushek, Eric A., John F. Kain, Daniel M. O’Brien, Steven G. Rivkin. 2005. “The Market for Teacher Quality” NBER Working Paper 11154.

Ladd, Teacher Effects, Draft April 21, 2008 Koedel, Cory and Julian R. Betts. 2007. “Re-examining the Role of Teacher Quality in the Educational Production Function.” Working Paper #2007-03. Nashville, TN: National Center on Performance Initiatives.

Kupermintz, Hagggai. 2003. “Teacher Effects and Teacher Effectiveness: A Validity Investigation of the Tennessee Value Added Assessment System,” Educational Evaluation and Policy Analysis. Vol 25, no. 3 (Fall), pp. 287-298.

Hill, C. H. Bloom, A. Black, M. Lipsey. 2007. “Empirical Benchmarks for Interpreting Effect Sizes in Research. MDRC Working Paper. July.

Lockwood, J.R. and Daniel F. McCaffrey. 2007. “Controlling for individual heterogeneity in longitudinal models, with applications to student achievement,” Electronic Journal of Statistics. Vol 1, ppl 223-252.

Lockwood, J.R., Daniel F. McCaffrey, and Time R. Sass. 2008. “The Intertemporal Stability of Teacher Effect Estimates.” Paper prepared for the Value Added Conference at the University of Wisconsin, April 23 and 24, 2008.

McCaffrey, Daniel F., J.R. Lockwood, Daniel M. Koretz, Laura S. Hamilton. 2003. Evaluating Value-Added Models for Teacher Accountability. Santa Monica, CA: Rand Corporation.

McCafffrey, Daniel, F, J.R. Lockwood, Daniel Koretx, Thomas A. Louis, and Laura Hamilton.

2004. “Modesl for Value-Added Modeling of Teacher Effects,” Journal of Educational and Behavioral Statistics, vol. 29, no. 1 (Spring), pp. 67-101.





Nye, Barbara, Spyros Konstantopoulos, and Larry Hedges. 2004. “How Large Are Teacher Effects?. Educational Evaluation and Policy Analysis. Vol 26, no. 3, pp. 237-257.

Rivkine, Steven, 2006. “Cumulative Nature of Learning and Specificatin Bias in Education Research. ” Unpublished manuscript. (January).

Rivkin, Steven G. 2007. “Value-Added Analysis and Education Policy.” Brief 1. Center for Analysis of Longitudinal Data n Education Research (CALDER). (November) “Rivkin, Steven G., Eric A. Hanushek, and John F. Kain. 2005. “Teachers Schools, and Academic Achievement”. Econometrica, Vol 73, no. 2 (March), pp. 417-458.

Rowan, B., R. Correnti, and R.J. Miller. 2002. “What large-scale survey research tells us about teacher effects on student achievement: Insights from the Propsects study of elementary schools. Teachers College Record, 104, pp. 1525-1567.

Wright, S.P., S. P. Horn and W.L. Sanders. 1997. “Teacher and classroom context effects on student achievement: Implications for teacher evaluation. Journalof Personnel Evaluation in Education. 11, pp. 57-67.

Ladd, Teacher Effects, Draft April 21, 2008 Table 1. Classroom and Teacher Differences in Student Achievement Gains

–  –  –

Source. Hanuschek, Kain, O’Brien, and Rivkin (2005), Table 1.

a. The entries in this row are the variance in student achievement gains explained by fixed effects for teachers by year.

b.The demographic controls include free or reduced lunch, gender, race/ethnicity, grade, limited English proviciency, special education, student mobility status, and year indicator variables.

Ladd, Teacher Effects, Draft April 21, 2008 Table 2. Estimated Effect Sizes for Teacher Attributes Model for Math Grades 4 and 5 with Student Fixed Effects, NYC 2000-2005.

–  –  –

Attended competitive 0.014* 0.022 0.054 college One S.D. increase in math 0.041** 0.065 0.158 SAT score Source. Boyd,,Grossman, Lankford, Loeb, and Wyckoff, in progress. Table from power point slides for presentation at AEFA meetings, Denver, April, 2008.

** 1% statistical significance * 5% statistical significance.

Ladd, Teacher Effects, Draft April 21, 2008

–  –  –

1-2 0.057** 0.032** 0.050** 3-5 0.072** 0.046** 0.061** 6-12 0.079** 0.053** 0.061** 13-20 0.082** 0.062** 0.059** 21-27 0.092** 0.067** 0.062** 27 0.084** 0.062** 0.043** Source. Elementary results are from Clotfelter, Ladd and Vigdor 2007, Tables 2 and 3.

High school results are from Clotfelter, Ladd and Vigdor, revised 2008, Table 3.

Licensure status. ** denotes statistical significance at the 0.01 level; * at the 0.05 level.

Table 4. Achievement effects of teacher credentials: Licensure status.

–  –  –

Source. Elementary results are from Clotfelter, Ladd and Vigdor 2007, Table 2. High school results are from Clotfelter, Ladd and Vigdor, revised 2008, Table 3.

** denotes statistical significance at the 0.01 level; * at the 0.05 level.

Ladd, Teacher Effects, Draft April 21, 2008

–  –  –

Source. Elementary results are from Clotfelter, Ladd and Vigdor 2007, Table 6. High school results are from Clotfelter, Ladd and Vigdor, revised 2008, Table 3. NBCT-2 denotes two years prior to the certification year; NBCT-1 denotes one year prior to the Certification year. Pre NBCT notes any year prior to certification. N.A. indicates not applicable because the variable was not included.

** denotes statistical significance at the 0.01 level; * at the 0.05 level.

Ladd, Teacher Effects, Draft April 21, 2008

–  –  –

Source. Elementary results are from Clotfelter, Ladd and Vigdor 2007, Table 5. High school results are from Clotfelter, Ladd and Vigdor, revised 2008.

** denotes statistical significance at the 0.01 level; * at the 0.05 level.

Ladd, Teacher Effects, Draft April 21, 2008

–  –  –

Source. Elementary results are from Clotfelter, Ladd and Vigdor 2007, Table 3. High school results are from Clotfelter, Ladd and Vigdor, Revised 2008, Table 4.

Unexp. Denotes that the sign of the coefficient was unexpected.

** denotes statistical significance at the 0.01 level; * at the 0.05 level.

Ladd, Teacher Effects, Draft April 21, 2008 Table 8. Achievement effects of teacher credentials: Teacher certification, high school only Alg. and geo. : Teacher certified in math 0.120**

–  –  –

English – certified in some other subject -0.145** unexp.

Source. Clotfelter, Ladd and Vigdor, Revised 2008, Table 4.

Unexp. Denotes that the sign of the coefficient was unexpected.

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