Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement
Abstract
The twelfth century rabbinic scholar Maimonides proposed a maximum class size of 40. This same maximum induces a nonlinear and nonmonotonic relationship between grade enrollment and class size in Israeli public schools today. Maimonides' rule of 40 is used here to construct instrumental variables estimates of effects of class size on test scores. The resulting identification strategy can be viewed as an application of Donald Campbell's regression-discontinuity design to the class-size question. The estimates show that reducing class size induces a significant and substantial increase in test scores for fourth and fifth graders, although not for third graders.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Regression discontinuity approaches followed early contributions by Angrist and Lavy (1999) and Hahn, Todd, and Van der Klaauw (2001).
“Regression discontinuity approaches start gaining popularity around 2000, following the early contributions by authors such as Angrist and Lavy (1999) and Hahn, Todd, and Van der Klaauw (2001), which were circulated as NBER working papers a couple of years prior.”
From Technology and Big Data Are Changing Economics: Mining Text to Track Methods (2020) · cites this paper as Angrist and Lavy (1999)
Cites
Regression-discontinuity analysis: An alternative to the ex post facto experiment.
Thistlethwaite, D. L., & Campbell, D. T. (1960) · Journal of Educational Psychology · doi:10.1037/h0044319 · Cited by 1,469 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Recent Developments in the Econometrics of Program Evaluation
Imbens, G. W., & Wooldridge, J. M. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.1.5 · Cited by 4,926 · see citing works
Regression discontinuity designs in economics
Lee, D. S., & Lemieux, T. (2010) · Journal of Economic Literature · doi:10.1257/jel.48.2.281 · Cited by 4,534 · see citing works
Angrist, J. D., & Krueger, A. B. (2001) · Journal of Economic Perspectives · doi:10.1257/jep.15.4.69 · Cited by 2,355 · see citing works
Self-citationOn the Specification and Estimation of the Production Function for Cognitive Achievement
Todd, P. E., & Wolpin, K. I. (2003) · The Economic Journal · doi:10.1111/1468-0297.00097 · Cited by 1,514 · see citing works
Standards of Evidence: Criteria for Efficacy, Effectiveness and Dissemination
Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., Mościcki, E. K., Schinke, S., Valentine, J. C., & Ji, P. (2005) · Prevention Science · doi:10.1007/s11121-005-5553-y · Cited by 1,338 · see citing works
Lavy, V. (2015) · The Economic Journal · doi:10.1111/ecoj.12233 · Cited by 369 · see citing works
Self-citationA Survey of Learning Causality with Data: Problems and Methods
Guo, R., Cheng, L., Li, J., Hahn, P. R., & Liu, H. (2021) · ACM Computing Surveys · doi:10.1145/3397269 · Cited by 362 · see citing works
The Hidden Costs of Teacher Turnover
Sorensen, L. C., & Ladd, H. F. (2020) · AERA Open · doi:10.1177/2332858420905812 · Cited by 284 · see citing works
Can Entrepreneurial Activity be Taught? Quasi-Experimental Evidence from Central America
Klinger, B., & Schündeln, M. (2011) · World Development · doi:10.1016/j.worlddev.2011.04.021 · Cited by 171 · see citing works
Academic Content, Student Learning, and the Persistence of Preschool Effects
Claessens, A., Engel, M., & Curran, F. C. (2014) · American Educational Research Journal · doi:10.3102/0002831213513634 · Cited by 154 · see citing works
Quasi-experimental designs for causal inference
Kim, Y., & Steiner, P. (2016) · Educational Psychologist · doi:10.1080/00461520.2016.1207177 · Cited by 135 · see citing works
“Angrist and Lavy (1999) applied the design to investigate the effect of class size on student achievement.”
MethodTechnology and Big Data Are Changing Economics: Mining Text to Track Methods
Currie, J., Kleven, H., & Zwiers, E. (2020) · AEA Papers and Proceedings · doi:10.1257/pandp.20201058 · Cited by 86 · see citing works
Zooming to Class? Experimental Evidence on College Students’ Online Learning during COVID-19
Kofoed, M. S., Gebhart, L., Gilmore, D., & Moschitto, R. (2024) · American Economic Review: Insights · doi:10.1257/aeri.20230077 · Cited by 125 · see citing works
School crowding, year-round schooling, and mobile classroom use: Evidence from North Carolina
McMullen, S. C., & Rouse, K. E. (2012) · Economics of Education Review · doi:10.1016/j.econedurev.2012.05.005 · Cited by 35 · see citing works
First-Time Boost Beats Experience: The Effect of past Eligibility on Turnout
Bhatti, Y., Hansen, K. M., & Wass, H. (2016) · Electoral Studies · doi:10.1016/j.electstud.2015.12.005 · Cited by 32 · see citing works
Arcand, J., & Wouabe, E. D. (2010) · Health Economics · doi:10.1002/hec.1643 · Cited by 31 · see citing works
Training to Teach Science: Experimental Evidence from Argentina
Albornoz, F., Anauati, M. V., Furman, M., Luzuriaga, M., Podestá, M. E., & Taylor, I. (2020) · The World Bank Economic Review · doi:10.1093/wber/lhy010 · Cited by 28 · see citing works
A laptop for every child? The impact of technology on human capital formation
Hall, C., Lundin, M., & Sibbmark, K. (2021) · Labour Economics · doi:10.1016/j.labeco.2020.101957 · Cited by 21 · see citing works
- Authors
- Angrist, J. D., & Lavy, V.
- Affiliations
- National Bureau of Economic Research (US)
- Hebrew University of Jerusalem (IL)
- Venue
- The Quarterly Journal of Economics
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-05-01
- Volume
- 114
- Issue
- 2
- Pages
- 533-575
- ISSN
- 0033-5533 (ISSN-L)
- 1531-4650
- OpenAlex
- W4240884942
- Cited by
- 1,482
- References
- 1
- Citations by year
- 2026: 43 · 2025: 37 · 2024: 57 · 2023: 57 · 2022: 84 · 2021: 55 · 2020: 90 · 2019: 59 · 2018: 66 · 2017: 153 · 2016: 137 · 2015: 61 · 2014: 68 · 2013: 67 · 2012: 49
- FWCI
- 96.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Quarterly Journal of Economics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Social Sciences › Education › School Choice and Performance
- Social Sciences › Education › Educational Environments and Student Outcomes
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Keywords
- class size, academic performance, test scores, regression discontinuity design, instrumental variables, primary education, education policy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review