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Class size: reducing average class size by one student in grade 1

Pre-K to 12 Education
Benefit-cost methods last updated December 2024.  Literature review updated January 2013.
This program was archived December 2024.
Washington State's prototypical school funding formula allocates funding for an average class size of 25.23 students in grades K–3 (RCW 28A.150.260). We estimate the benefits and costs of reducing 1st grade average class sizes by one student.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our 2023 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $335 Benefits minus costs $1,165
Participants $783 Benefit to cost ratio $5.71
Others $417 Chance the program will produce
Indirect ($123) benefits greater than the costs 84%
Total benefits $1,413
Net program cost ($247)
Benefits minus cost $1,165

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our 2023 Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
High school graduation
On-time completion of high school with a diploma (excluding GED attainment).
 6 77 1000 0.008 0.004 6 0.008 0.004 18 0.008 0.163
Test scores
Standardized, validated tests of academic achievement.
6 77 1000 0.018 0.010 6 0.007 0.005 17 0.018 0.059
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
High school graduation Criminal justice system $2 $0 $5 $1 $8
Test scores Labor market earnings associated with test scores $332 $783 $413 $0 $1,528
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($124) ($124)
Totals $335 $783 $417 ($123) $1,413
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $198 2011 Present value of net program costs (in 2022 dollars) ($247)
Comparison costs $0 2011 Cost range (+ or -) 10%
The cost estimate accounts for state and school district teacher compensation, marginal operating, and capital costs. Annual teacher costs were calculated using the 2011-12 average total (state and local) salary for Washington certificated teachers reported in the Office of Superintendent of Public Instruction School District Personnel Summary Profiles. The calculation includes salaries and benefits as well as central administration and special education costs. Assumptions for capital cost calculations were provided by legislative staff, with one exception: the interest rate on bonds is from the Federal Reserve's November 2012 state and local rate. Aos, S., & Pennucci, A. (2013). K–12 class size reductions and student outcomes: A review of the evidence and benefit-cost analysis (Doc. No. 13-01-2201). Olympia: Washington State Institute for Public Policy.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our 2023 Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Akerhielm, K. (1995). Does class size matter?. Economics of Education Review, 14(3), 229-241.

Altinok, N., & Kingdon, G. (2012). New evidence on class size effects: A pupil fixed effects approach. Oxford Bulletin of Economics and Statistics, 74(2), 203-234.

Angrist, J. D., & Lavy, V. (1999). Using Maimonides' Rule to estimate the effect of class size on scholastic achievement. The Quarterly Journal of Economics, 114(2), 533-575.

Blatchford, P., Martin, C., Moriarty, V., Bassett, P., & Goldstein, H. (2002). Pupil adult ratio differences and educational progress over reception and Key Stage 1 (Research Report No. 335). London: Department for Education and Skills.

Bonesrønning, H. (2003). Class size effects on student achievement in Norway: Patterns and explanations. Southern Economic Journal, 69(4), 952-965.

Bressoux, P., Kramarz, F., & Prost, C. (2008). Teachers' training, class size and students' outcomes: Learning from administrative forecasting mistakes [IZA Working paper]. Bonn: Institute for the Study of Labor.

Browning, M., & Heinesen, E. (2007). Class size, teacher hours and educational attainment. The Scandinavian Journal of Economics, 109(2), 415-438.

Buddin, R., & Zamarro, G. (2009). Teacher qualifications and student achievement in urban elementary schools. Journal of Urban Economics. 66(2), 103-115.

Burke, M. & Sass, T. (2011). Classroom peer effects and student achievement. Boston, MA: Federal Reserve Bank of Boston.

Chetty, R., Friedman, N., Hilger, N., Saez, E., Schanzenbach, D., & Yagan, D. (2010). How does your kindergarten classroom affect your earnings? Evidence from Project STAR.

Cho, H., Glewwe, P., & Whitler, M. (2012). Do reductions in class size raise students' test scores? Evidence from population variation in Minnesota's elementary schools. Economics of Education Review, 31(3), 77-95.

Clotfelter, C.T., Ladd, H.F., & Vigdor, J.L. (2010). Teacher credentials and student achievement in high school: A cross-subject analysis with student fixed effects. Journal of Human Resource, 45(3), 655-681.

Clotfelter, C.T., Ladd, H.F., & Vigdor, J.L. (2006). Teacher-student matching and the assessment of teacher effectiveness. The Journal of Human Resources, 41(4), 778-820.

Croninger, R.G., Rice, J.K., Rathbun, A., & Nishio, M. (2007). Teacher qualifications and early learning: Effects of certification, degree, and experience on first-grade student achievement. Economics of Education Review, 26(3), 312-324.

Dearden, L., Ferri, J., & Meghir, C. (2002). The effect of school quality on educational attainment and wages. The Review of Economics and Statistics, 84(1), 1-20.

Dee, T.S., & West, M.R. (2011). The non-cognitive returns to class size. Educational Evaluation and Policy Analysis, 33(1), 23-46.

Dobbelsteen, S., Levin, J., & Oosterbeek, H. (2002). The causal effect of class size on scholastic achievement: Distinguishing the pure class size effect from the effect of changes in class composition. Oxford Bulletin of Economics and Statistics, 64(1), 17-38.

Eberts, R.W., & Stone, J.A. (1987). Teacher unions and the productivity of public schools. Industrial and Labor Relations Review, 40(3), 354-363.

Ecalle, J., Magnan, A., & Gibert, F. (2006). Class size effects on literacy skills and literacy interest in first grade: A large-scale investigation. Journal of School Psychology, 44(3), 191-209.

Feinstein, L., & Symons, J. (1999). Attainment in secondary school. Oxford Economic Papers, 51(2), 300-321.

Ferguson, R.F., & Ladd, H.F. (1996). How and why money matters: An analysis of Alabama schools. In H. F. Ladd (Ed.), Holding schools accountable: Performance based reform in education (pp. 265–298). Washington, DC: Brookings Institution.

Fredricksson, P., & Öckert, B. (2008). Resources and student achievement – Evidence from a Swedish policy reform. The Scandinavian Journal of Economics, 110(2), 277-296.

Fredriksson, P., O ckert, B., & Oosterbeek, H. (2012). Long-term effects of class size. Uppsala: IFAU.

Fuchs, T., & Wößmann, L. (2007). What accounts for international differences in student performance? A re-examination using PISA data. Empirical Economics, 32(2), 433-464.

Goldhaber, D.D., & Brewer, D.J. (1997). Why don't schools and teachers seem to matter? Assessing the impact of unobservables on educational productivity. The Journal of Human Resources, 32(3), 505-523.

Grissmer, D.W., & Flanagan, A. (2006). Improving the achievement of Tennessee students: Analysis of the National Assessment of Education Progress. Santa Monica, CA: RAND.

Hægeland, T., Raaum, O., & Salvanes, K. G. (2005). Pupil achievement, school resources and family background (IZA Discussion Paper No. 1459). Bonn, Germany: Institute for the Study of Labor.

Harris, D.N., & Sass, T.R. (2011). Teacher training, teacher quality and student achievement. Journal of Public Economics, 95(7- 8), 798-812.

Hoxby, C.M. (2000). The effects of class size on student achievement: New evidence from population variation. The Quarterly Journal of Economics, 115(4), 1239-1285.

Iacovou, M. (2002). Class size in the early years: Is smaller really better? Education Economics, 10(3), 261-290.

Jakubowski, M., & Sakowski, P. (2006). Quasi-experimental estimates of class size effect in primary schools in Poland (Working Paper?). Poland: Warsaw University, Faculty of Economics.

Jepsen, C., & Rivkin, S. (2002). Class size reduction, teacher quality, and academic achievement in California public elementary schools. San Francisco: Public Policy Institute of California.

Krieg, J.M. (2006). Teacher quality and attrition. Economics of Education Review, 25(1), 13-27.

Krueger, A.B. (1999). Experimental estimates of education production functions. The Quarterly Journal of Economics, 114(2), 497-532.

Lee, J.-W., & Barro, R.J. (2001). Schooling quality in a cross-section of countries. Economica, 68, 465-488.

Lee, J., & Reeves, T. (2012). Revisiting the impact of NCLB high-stakes school accountability, capacity, and resources: State NAEP 1990-2009 reading and math achievement gaps and trends. Educational Evaluation and Policy Analysis, 34(2), 209-231.

Li, M. (2007). Bayesian proportional hazard analysis of the timing of high school dropout decisions. Econometric Reviews, 26(5), 529-556.

Long, M. C. (2006). Secondary school characteristics and early adult outcomes (Working Paper No. 2006-06). Seattle: University of Washington, Daniel J. Evans School of Public Affairs.

Milesi, C., & Gamoran, A. (2006). Effects of class size and instruction on kindergarten achievement. Educational Evaluation and Policy Analysis, 28(4), 287-313.

Molnar, A., Smith, P., Zahorik, J., Palmer, A., Halbach, A., & Ehrle, K. (1999). Evaluating the SAGE program: A pilot program in targeted pupil-teacher reduction in Wisconsin. Educational Evaluation and Policy Analysis, 21(2), 165-177.

NICHD Early Child Care Research Network. (2004). Does class size in first grade relate to children's academic and social performance or observed classroom processes?. Developmental Psychology, 40(5), 651-664.

Pirog, M.A., & Magee, C. (1997). High school completion: The influence of schools, families, and adolescent parenting. Social Science Quarterly, 78(3), 710-724.

Pong, S.-i., & Pallas, A. (2001). Class size and eighth-grade math achievement in the United States and abroad. Educational Evaluation and Policy Analysis, 23(3), 251-273.

Ready, D.D., & Lee, V.E. (2006). Optimal context size in elementary schools: Disentangling the effects of class size and school size. In T. Loveless & F. M. Hess (Eds.), Brookings papers on education policy, 2006/2007 (pp. 99-135). Washington, DC: Brookings Institution.

Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools, and academic achievement. Econometrica, 73(2), 417-458.

Rumberger, R. W., & Thomas, S. L. (2000). The distribution of dropout and turnover rates among urban and suburban high schools. Sociology of Education, 73(1), 39-67.

Steele, F., Vignoles, A., & Jenkins, A. (2007). The effect of school resources on pupil attainment: A multilevel simultaneous equation modelling approach.Journal of the Royal Statistical Society: Series A (Statistics in Society), 170(3), 801-824.

Todd, P.E., & Wolpin, K.I. (2007). The production of cognitive achievement in children: Home, school and racial test score gaps. Journal of Human Capital, 1(1), 91-136.

Urquiola, M. (2006). Identifying class size effects in developing countries: Evidence from rural Bolivia. The Review of Economics and Statistics, 88(1), 171-177.

Valdenaire, M. (2006). Do younger pupils need smaller classes? Evidence from France (Preliminary Draft). Paris: Paris- jourdan Sciences Economiques.

Waldfogel, J., & Zhai, F. (2008). Effects of public preschool expenditures on the test scores of 4th graders: Evidence from TIMSS. Educational Research and Evaluation, 14, 9-28.

Wilson, K. (2001). The determinants of educational attainment: Modeling and estimating the human capital model and education production functions. Southern Economic Journal, 67(3), 518-551.

Washington State Institute for Public Policy (2013). The Institute’s state-level fixed effects analysis of NAEP and CCD data is reported in this Technical Appendix.