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Diminishing Marginal Returns and the Production of Education: An International Analysis


  • Douglas Harris


Diminishing marginal returns (DMR) to school inputs could explain a wide variety of findings in the research literature. One important example is the influential finding by Heyneman and Loxley that school inputs are the 'predominant influence' on achievement in developing nations, where input levels are low, even though the same school inputs have relatively little influence in developed nations, where input levels are higher. However, few studies of education production, including those related to the Heyneman-Loxley hypothesis, use functional forms that allow for DMR, and common tests for DMR appear to be invalid. Various tests are implemented using data from 32 countries. As is commonly found in the literature, the marginal effects of school inputs are frequently negative, precluding DMR. In those cases with positive marginal effects, there is more evidence for DMR than for increasing returns, but constant returns rarely can be rejected. DMR therefore does not appear to explain the differences in results between developing and developed nations.

Suggested Citation

  • Douglas Harris, 2007. "Diminishing Marginal Returns and the Production of Education: An International Analysis," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 31-53.
  • Handle: RePEc:taf:edecon:v:15:y:2007:i:1:p:31-53
    DOI: 10.1080/09645290601133894

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    Cited by:

    1. Sam Jones, 2020. "Testing the Technology of Human Capital Production: A General‐to‐Restricted Framework," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1429-1455, December.
    2. Yang, Minseok & Lee, Ho Jun, 2022. "Do school resources reduce socioeconomic achievement gap? Evidence from PISA 2015," International Journal of Educational Development, Elsevier, vol. 88(C).
    3. Dangxing Chen & Luyao Zhang, 2023. "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers 2301.07060,
    4. Sass, Tim R. & Semykina, Anastasia & Harris, Douglas N., 2014. "Value-added models and the measurement of teacher productivity," Economics of Education Review, Elsevier, vol. 38(C), pages 9-23.
    5. Bouhlila, Donia Smaali, 2015. "The Heyneman–Loxley effect revisited in the Middle East and North Africa: Analysis using TIMSS 2007 database," International Journal of Educational Development, Elsevier, vol. 42(C), pages 85-95.
    6. Cong Li & Minglai Li, 2020. "The Policy Information Gap and Resettlers’ Well-Being: Evidence from the Anti-Poverty Relocation and Resettlement Program in China," IJERPH, MDPI, vol. 17(8), pages 1-20, April.
    7. Donia Smaali Bouhlila, 2013. "Students’ Achievement in the MENA Countries: The Heyneman-Loxley Effect Revisited Using TIMSS 2007 Data," Working Papers 779, Economic Research Forum, revised Oct 2013.


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