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Can flexible non-linear modeling tell us anything new about educational productivity?

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  • Baker, Bruce D.

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  • Baker, Bruce D., 2001. "Can flexible non-linear modeling tell us anything new about educational productivity?," Economics of Education Review, Elsevier, vol. 20(1), pages 81-92, February.
    • Handle: RePEc:eee:ecoedu:v:20:y:2001:i:1:p:81-92
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    References listed on IDEAS

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    1. George E. Johnson & Frank P. Stafford, 1973. "Social Returns to Quantity and Quality of Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 8(2), pages 139-155.
    2. Sharda, Ramesh & Wang, Jun, 1996. "Neural networks and operations research/management science," European Journal of Operational Research, Elsevier, vol. 93(2), pages 227-229, September.
    3. Figlio, David N., 1999. "Functional form and the estimated effects of school resources," Economics of Education Review, Elsevier, vol. 18(2), pages 241-252, April.
    4. David Card & Alan B. Krueger, 1996. "Labor Market Effects of School Quality: Theory and Evidence," NBER Working Papers 5450, National Bureau of Economic Research, Inc.
    5. Tim Liao, 1992. "A modified GMDH approach for social science research: exploring patterns of relationships in the data," Quality & Quantity: International Journal of Methodology, Springer, vol. 26(1), pages 19-38, February.
    6. Elaine M. Worzala & Margarita Lenk & Ana Silva, 1995. "An Exploration of Neural Networks and Its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 10(2), pages 185-202.
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    Cited by:

    1. Liao, Hailin & Wang, Bin & Li, Baibing & Weyman-Jones, Tom, 2016. "ICT as a general-purpose technology: The productivity of ICT in the United States revisited," Information Economics and Policy, Elsevier, vol. 36(C), pages 10-25.
    2. Michael Creel & Montserrat Farell, 2016. "On the Production of Cognitive Achievement and Gaps in Test Scores," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 228-247, April.
    3. Daniel Santín, 2006. "Measuring technical efficiency in schools: a critic revision," Hacienda Pública Española / Review of Public Economics, IEF, vol. 177(2), pages 57-82, April.
    4. Santín, Daniel & Delgado, Francisco & Valiño, Aurelia, 2001. "Measuring Technical Efficiency with Neural Networks: a Review," Efficiency Series Papers 2001/09, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    5. 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.
    6. Daraio, Cinzia & Simar, Léopold, 2022. "Approximations and Inference for Nonparametric Production Frontiers," LIDAM Discussion Papers ISBA 2022017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Ying Wang & Peipei Shang & Lichun He & Yingchun Zhang & Dandan Liu, 2018. "Can China Achieve the 2020 and 2030 Carbon Intensity Targets through Energy Structure Adjustment?," Energies, MDPI, vol. 11(10), pages 1-32, October.
    8. Michael Creel & Montserrat Farell Ferrer, 2006. "The black-white test score gap widens with age?," UFAE and IAE Working Papers 670.06, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

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