Publication Bias and Model Uncertainty in Measuring the Effect of Class Size on Achievement

Matej Opatrny, Tomas Havranek, Zuzana Irsova and Milan Ščasný ()

No 2023/19, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

Abstract: Class size reduction mandates are frequent and invariably justified by studies reporting positive effects on student achievement. Yet other studies report no effects, and the literature as a whole awaits correction for potential publication bias. Moreover, if identification drives results systematically, the relevance of individual studies will vary. We build a sample of 1,767 estimates collected from 62 studies and for each estimate codify 42 factors reflecting estimation context. We employ recently developed nonlinear techniques for publication bias correction and Bayesian model averaging techniques that address model uncertainty. The results suggest publication bias among studies featured in top five economics journals, but not elsewhere. The implied class size effect is zero for all identification approaches except Tennessee´s Student/Teacher Achievement Ratio project. The effect remains zero for disadvantaged students and across subjects, school types, and countries.

Keywords: Class size; student learning; meta-analysis; publication bias; Bayesian model averaging (search for similar items in EconPapers)
JEL-codes: C83 H52 I21 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2023-05, Revised 2023-05
References: Add references at CitEc
Citations: View citations in EconPapers (2)

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https://ies.fsv.cuni.cz/en/veda-vyzkum/working-papers/6770 (application/pdf)

Related works:
Working Paper: Publication Bias and Model Uncertainty in Measuring the Effect of Class Size on Achievement (2023)
Working Paper: Publication Bias and Model Uncertainty in Measuring the Effect of Class Size on Achievement (2023)
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